Latitudinal Effects on Diversity and Body Size: A Case

Latitudinal Effects on Diversity and Body Size: A Case Study with Parasitoid and

Parasitic Wasps

By

Thanushi I. Eagalle

A Thesis

presented to

The University of Guelph

In partial fulfilment of requirements

for the degree of

Master of Science

in

Integrative Biology

Guelph, Ontario, Canada

© Thanushi I. Eagalle, October 2014

ABSTRACT

Latitudinal Effects on Diversity and Body Size: A Case Study with Parasitoid and

Parasitic Wasps

Thanushi I. Eagalle

University of Guelph, 2014

Advisor:

Professor M. A. Smith

While greater species diversity exists at tropical latitudes for many groups, certain

parasitoid wasp families (i.e. Ichneumonidae) exhibit a peak in species diversity at mid-latitudes

(Janzen 1981). Recently, authors have questioned the legitimacy of observed latitudinal trends

in species richness, body size and biology for parasitoids, due to geographic and taxonomic

sampling biases. I combined DNA barcoding data with ecological variables to quantify parasitoid

diversity across a latitudinal gradient (~4.088 - 58.676°N) and to test whether enumerating

diversity using DNA supports a mid-latitude peak. I also compared Ichneumonidae and

Braconidae body size across the same latitudinal gradient to test whether parasitoid wasps

followed the Bergmann’s rule – larger specimens found at higher latitudes. My diversity

estimates suggested that the number of species was consistent across latitude, though species

found at higher latitudes were more closely related to each other. Body size, specifically hind

tibia length, exhibited converse-Bergmann clines.

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ACKNOWLEDGEMENTS

During the course of my MSc thesis, I collaborated with many wonderful individuals.

One such individual is my supervisor, Dr. M. Alex Smith, who was a continuous source of

knowledge, patience, guidance and friendship. I am deeply thankful for all his efforts in helping

me with my MSc thesis and I believe that his optimistic outlook and quick problem solving skills,

has made him standout both as a professor and as a friend.

I am also very thankful for the guidance and advice offered by my Advisory Committee,

Dr. Jinzhong Fu and Dr. Kevin McCann. My thesis has greatly benefited from their expertise in

phylogenetics, evolution and ecology. In addition, Dr. Ryan Gregory’s help with Mesquite and

Anu Stanley’s help with statistics has also been greatly appreciated. I would also like to thank

my Examination Committee, Dr. Vernon Thomas and Dr. Sarah J. Adamowicz.

All of my specimen data was retrieved from the Barcode of Life Data System, so I am

very grateful for the all the researchers who contributed their efforts to previous collections

available on the website, everyone at the Biodiversity institute of Ontario and the Integrative

Biology Department at the University of Guelph.

My field work for this study was supported by the Northern Scientific Training Program

and Northern Research Fund, as well by permits and assistance from the Forest Department,

Ministry of Natural Resources and the Environment Belize, Lamanai Outpost Lodge, Nouragues

Research Station (French Guiana), Nouragues Travel Grants Program 2011, Nouragues

Ecological Research Station French Guiana (Centre national de la recherché scientifique -

France), the Ontario Ministry of Natural Resources, the Shaw Woods Outdoor Education Centre

and Parks Canada for their support of the BIObus program (NAP-2008-1636). The staff and

researchers at the Churchill Northern Scientific Centre and the Wildlife Research Station in

Algonquin made my two field work seasons unforgettable. My research was supported by

grants from the Natural Sciences and Engineering Research Council of Canada (Discovery and

Research Technology and Instrumentation), Canada Foundation for Innovation to Alex Smith.

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When I first joined the Smith Lab, I knew I would be amongst individuals that had the

same interests as me, but I never expected to form such strong connections with many of the

lab mates. Morgan Roblin, Connor Warne, Heather Coatsworth, Kate Pare, Tim Dance, Megan

McPhee, Sean Espinola and Tyler Schmidt made Smith Lab the most epic lab in the entire IBIO

department, though my opinion may be biased.

Without a doubt, none of this would have been possible without the love and support I

have received from my family and friends throughout my academic career. I am eternally

grateful for all the encouragement I have received from my parents, Preethika and Kalika

Perera. Thisuri Eagalle, Aaron Brown, Lauren Jarvis and all of my lovely friends have always

been the perfect dose of laughter, treats, and inspiration, when times were stressful.

Overall, I consider myself to be very lucky to have been surrounded by amazing people

during this entire process.

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TABLE OF CONTENTS

ABSTRACT .......................................................................................................................................... ii

ACKNOWLEDGEMENTS ..................................................................................................................... iii

LIST OF TABLES ............................................................................................................................... viii

LIST OF FIGURES ................................................................................................................................ ix

CHAPTER 1: GENERAL INTRODUCTION; OVERVIEW OF PARASITOID AND PARASITIC WASP LIFE

HISTORY STRATEGIES, IDENTIFICATION AND LATITUDINAL TRENDS ...........................................1

Overview of parasitoid and parasitic wasps ............................................................................................. 1

DNA barcoding and parasitoid wasp identification .................................................................................. 1

Macroecological trends ............................................................................................................................ 2

Diversity ................................................................................................................................................ 2

Body Size ............................................................................................................................................... 3

The objectives of my thesis ....................................................................................................................... 3

CHAPTER 1 FIGURES .................................................................................................................................. 5

CHAPTER 2: PARASITOID AND PARASITIC WASP DIVERSITY ACROSS A LATITUDINAL GRADIENT ...........6

ABSTRACT .................................................................................................................................................. 6

INTRODUCTION ......................................................................................................................................... 7

Latitudinal diversity gradient ................................................................................................................ 7

Exceptions - Parasitoid diversity ........................................................................................................... 8

Doubts about the anomalous diversity ................................................................................................. 9

Parasitoid wasp identification and molecular markers ...................................................................... 10

Objectives............................................................................................................................................ 11

Questions, hypotheses and predictions .............................................................................................. 12

METHODS ................................................................................................................................................ 12

Specimen Selection Criteria ................................................................................................................ 12

Molecular analyses ............................................................................................................................. 13

Sample size for estimating diversity ................................................................................................... 13

Environmental data ............................................................................................................................. 14

Diversity analyses ................................................................................................................................ 14

RESULTS .................................................................................................................................................. 15

Diversity vs. Latitude ........................................................................................................................... 16

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Diversity vs. Environmental variables ................................................................................................. 16

Asymptotic species richness ............................................................................................................... 16

DISCUSSION ............................................................................................................................................. 17

BINs ..................................................................................................................................................... 17

Estimates of PD ................................................................................................................................... 18

Advantages for using BINs and estimates of PD for assessing diversity ............................................. 19

Limitations and improvements ........................................................................................................... 20

Conclusions ......................................................................................................................................... 21

CHAPTER 2 TABLES .................................................................................................................................. 22

CHAPTER 2 FIGURES ................................................................................................................................ 28

CHAPTER 3: ICHNEUMONIDAE AND BRACONIDAE BODY SIZE ACROSS LATITUDE ............................... 37

ABSTRACT ................................................................................................................................................ 37

INTRODUCTION ....................................................................................................................................... 38

Bergmann’s rule .................................................................................................................................. 38

Other body size trends ........................................................................................................................ 38

Insect body size ................................................................................................................................... 39

Objectives............................................................................................................................................ 40

Question, hypothesis and predictions ................................................................................................ 40

METHODS ................................................................................................................................................ 40

Body size measurements .................................................................................................................... 40

Body size comparisons ........................................................................................................................ 41

Statistical analyses .............................................................................................................................. 41

Body size comparisons using phylogenetic comparative method (PCM) ........................................... 41

RESULTS .................................................................................................................................................. 42

Linear regressions Larger sample ....................................................................................................... 42

PCM Ichneumonidae .......................................................................................................................... 43

DISCUSSION ............................................................................................................................................. 43

Support for the converse-Bergmann cline .......................................................................................... 43

Other trends ........................................................................................................................................ 44

Limitations........................................................................................................................................... 44

The significance of this study .............................................................................................................. 46

Conclusions ......................................................................................................................................... 46

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CHAPTER 3 TABLES .................................................................................................................................. 47

CHAPTER 3 FIGURES ................................................................................................................................ 49

CHAPTER 4: SUMMARY; BROADER SIGNIFICANCE AND FUTURE DIRECTIONS ..................................... 54

REFERENCES .................................................................................................................................... 56

APPENDIX 1: Chapter 2 - All specimen information (4785). ................................................................ 63

APPENDIX 2. Chapter 2 – Specimen list for the randomly sampled subset (2240). ............................ 206

APPENDIX 3. Chapter 2 - Outgroup specimens. ............................................................................... 264

APPENDIX 4. Chapter 3 - Ichneumonidae hind tibia and wind length measurements. ....................... 265

APPENDIX 5. Chapter 3 - Braconidae hind tibia and wing length measurements............................... 280

viii

LIST OF TABLES

Table 2.1. Collection site information, including location, collection dates and sampling method. ...... 22

Table 2.2. The webpage URLs for Gigapan habitat panorama galleries taken at the specimen collection

sites. ...................................................................................................................................... 23

Table 2.3. The number of sequences available from each collection site, along with the percentage of

singletons and doubletons from diversity statistics on EstimateS and the results from Chao 2

and BOLD accumulation curve calculations. ............................................................................. 24

Table 2.4. Environmental data was gathered using GPS co-ordinates of a randomly selected specimen

from each collection site. ........................................................................................................ 25

Table 2.5. Linear regression results for comparisons of both Cadotte’s and Faith’s PD with

environmental variables. The results are organized in order of strongest to weakest

relationships for Faith’s PD. .................................................................................................... 26

Table 2.6. Linear regression and p-value results for BINs comparisons with environmental variables.

The results are organized in order of strongest to weakest relationships, though none was

significant. ............................................................................................................................. 27

Table 3.1. The number of specimens from the families Ichneumonidae and Braconidae that were used

for body size measurements and comparisons. From specimens with photos, subsets of

randomly chosen individuals were measured – see methods. Then from the specimens that

were measured, unique BINs per location were selected. The larger and smaller sample sizes

represent how many species were present per site for comparison. ........................................ 47

Table 3.2. PDAP results for the comparison of wing length and hind tibia length for Ichneumonidae

and Braconidae species across latitude. .................................................................................. 48

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LIST OF FIGURES

Figure 1.1. The Bergmann’s rule states that larger specimens are found at higher latitudes because

they have lower surface area-to-volume ratios, which is more beneficial for conserving heat. ....5

Figure 2.1. Parasitoid specimens were collected from the highlighted locations during the flight

season. The map was constructed on Simplemappr (www.simplemappr.net) using average

latitude and longitude points from the collection sites. ........................................................... 28

Figure 2.2. The Classic Chao2 equation used to estimate species richness for the randomly sampled

subset containing 2,240 specimens. ........................................................................................ 29

Figure 2.3. Estimates of Faith’s PD exhibited a linear incline with the number of BINs for all the

samples and the randomly sampled subset of 2,240 specimens, though the linear regression

comparison for all samples was stronger. ................................................................................ 30

Figure 2.4. For the randomly sampled subset of 2,240 specimens, Faith’s PD decreased with latitude,

though BINs did not exhibit any trend. Neither result was statistically significant. .................... 31

Figure 2.5. For the randomly sampled subset of 2,240 specimens, Faith’s PD increased with annual

mean temperature (°C) and BINs slightly decreased. Neither result was statistically significant.

.............................................................................................................................................. 32

Figure 2.6. For the randomly sampled subset of 2,240 specimens, Faith’s PD and BINs exhibited a

linear incline with annual precipitation levels (mm), though neither result was statistically

significant. ............................................................................................................................. 33

Figure 2.7. Asymptotic species richness estimated by the classic Chao2 non-parametric richness

estimator for 280 randomly selected individuals from each of the eight collection sites, totaling

2,240 specimens. .................................................................................................................... 34


estimator for each of the eight collection sites. ....................................................................... 35

Figure 2.9. Asymptotic species richness estimated by BOLD for each of the eight collection sites. ...... 36

Figure 3.1. Possible mechanisms for varying body sizes with latitude (adapted from Shelomi, 2012). . 49

Figure 3.2. Ichneumonidae and Braconidae body size comparisons (mean wing length/hind tibia

length + standard error (SE)) for the larger sample sizes across latitude. .................................. 50


length +SE) for the smaller sample sizes across latitude. .......................................................... 51

Figure 3.4. PDAP results for Ichneumonidae body size across latitude for trees with collapsed

branches. ............................................................................................................................... 52

Figure 3.5. PDAP results for Braconidae body size across latitude for trees with collapsed branches... 53

CHAPTER 1: GENERAL INTRODUCTION; OVERVIEW OF PARASITOID AND PARASITIC WASP LIFE

HISTORY STRATEGIES, IDENTIFICATION AND LATITUDINAL TRENDS

Overview of parasitoid and parasitic wasps

Hymenopteran parasitoids represent one of the largest groups of animals in the world and are

more speciose than the entire Vertebrata (Janzen 1981). In particular, the families

Ichneumonidae and Braconidae are amongst the most diverse, with approximately 24,000 and

17,000 described species, respectively, however estimated to be over 60,000 and 42,653

species respectively (Skillen, Pickering et al. 2000; Jones, Purvis et al. 2009; Quicke 2012). These

organisms are important biological control agents: therefore, understanding their life history

and distribution patterns is critical for maintaining biodiversity, controlling invasive species and

diseases (Gaston 2000).

The developmental process of a parasitoid wasp begins when a female lays her eggs in or on

another organism, including larval and pupal forms of Lepidoptera, Diptera, Coleoptera and

Hymenoptera. After the eggs hatch, the larvae develop by living and feeding on its host, which

eventually leads to the host’s death (Jervis, Heimpel et al. 2001). If the parasitoid is a host

generalist (polyphagous), then it can successfully attack and develop in several species of the

same family, while a host specialist only specializes in one species (Brodeur 1996). Parasitic

species are similar in their life history traits, though they do not kill their host.

DNA barcoding and parasitoid wasp identification

Traditional methods of identifying specimens and describing species involve morphological

taxonomy and behavioural observations. These methods require great attention to detail and

can take 20 years on average to describe a new insect species (Novotny and Miller 2014). To

expedite the documentation of current biodiversity, DNA barcoding has become a popular tool

for species identification and discovery, especially due to the presence of numerous cryptic

species in Hymenopteran groups that are difficult to identify based solely on morphology

(Smith, Rodriguez et al. 2008; Bucklin, Steinke et al. 2011).

DNA barcoding involves the use of a standardized DNA marker, such as the 5 prime region of

mitochondrial cytochrome c oxidase subunit I gene (COI), for comparison to a reference library

containing sequences from known specimens (Hebert, Cywinska et al. 2003a; Hebert,

Ratnasingham et al. 2003b). The Barcode of Life Data System (BOLD) (Ratnasingham and Hebert

2007) is the standard DNA barcode reference library that integrates molecular, morphological

and distributional data. BOLD also clusters barcode sequences using graph theoretic methods

into Barcode Index Numbers (BINs) (Ratnasingham and Hebert 2013). BINs exhibit high

concordance with named species; therefore BINs can be used as a proxy for species, especially

1

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if a newly discovered species has yet to be assigned a Linnaean name (Ratnasingham and

Hebert 2013).

Recent studies using DNA barcoding have suggested that parasitoids may actually be more

diverse than originally thought (Smith, Wood et al. 2007; Smith, Rodriguez et al. 2008;

Rodriguez, Fernández-Triana et al. 2012). For example, there are approximately 2,000 described

species of Micrograstinae (Hymenoptera: Braconidae), yet new estimates have revealed the

species richness to be 8-20 times greater than current numbers (Rodriguez, Fernández-Triana et

al. 2012). In addition, the presence of many cryptic species is revealed through molecular

analyses that integrate ecological information (such as host species) (Smith, Wood et al. 2007;

Smith, Rodriguez et al. 2008). If molecular methods, such as DNA barcoding, allow a more

intimate and accurate understanding of morphologically cryptic groups such as parasitoid

wasps, then it is more important to test how barcode derived estimates of diversity affect

large-scale latitudinal trends.

Macroecological trends

The inclusion of parasitic Hymenoptera, and many other insect groups in macroecological studies is greatly hindered by their exposure to the taxonomic impediment and there is still an overwhelming complexity to hymenopteran life that we do not yet understand (Hoagland 1996; Evenhuis 2007). Therefore the combination of their smaller size, high diversity, morphological plasticity within species and an extreme (and growing) shortage of expert taxonomists results in “an enormous taxonomic impediment in trying to identify and describe hymenopteran biodiversity” (pg. 203, Huber 2009). Macroecological patterns involving global species richness are also sensitive to taxonomic inflation – “known species are raised to species as a result in a change in species concept, rather than to new discoveries” (pg. 464, Isaac, Mallet et al. 2004). Since ‘species’ are treated as units in macroecology, the appropriate species concept – biological or phylogenetic – should be carefully selected for the type of hypothesis being tested (Isaac, Mallet et al. 2004). The biological species concept defines species as reproductively isolated populations, while the phylogenetic species concept defines species to be populations that share a common ancestor, with at least one differing taxonomic character from other taxa (Isaac, Mallet et al. 2004).

Diversity

One of the most prominent macroecological trends is the decline of floristic and faunistic

diversity across latitude (Willig, Kaufman et al. 2003). However, Ichneumonidae wasps were

thought to be an exception to this trend, because their diversity appeared to peak at mid-

latitudes (Owen and Owen 1974; Janzen 1981; Skillen, Pickering et al. 2000). Subsequently, this

anomalous pattern has sparked much interest, and several hypotheses have since been

proposed to explain the underlying mechanisms. Amongst them are the resource scarcity

3

hypothesis (Janzen and Pond 1975; Janzen 1981), nasty-host hypothesis (Gauld, Gaston et al.

1992) and predation hypothesis (Rabinowitz and Price 1976).

Janzen and Pond (1975) and Janzen (1976) have also proposed that this anomalous diversity

may apply to other parasitic Hymenoptera, though Janzen (1981) and Morrison (1979) have

suggested that parasitoid families found attacking eggs, such as Trichogrammatidae, may be

more diverse in the tropics. Morrison (1979) also stated that tropical parasitoids may be

composed of greater levels of species that parasitize eggs and consequently are smaller in size.

Body Size

Another prominent latitudinal trend is the increase in body size of endothermic organisms

within a taxonomic group along latitude. This patterns is referred to as the Bergmann’s rule

(Bergmann 1847; Mayr 1956), and larger specimens are expected at higher latitudes because

they have lower surface area-to-volume ratios which are more beneficial for heat conservation

(Figure 1.1). Ectotherms have also been observed to follow this trend, as well as contradict it

(Ray 1960; Shelomi 2012), with possible mechanisms ranging from genetics to temperature to

voltinism (Blanckenhorn 2004; Shelomi 2012). Voltinism is the number of generations or broods

an insect group produces in a year – univoltine species are composed of only one generation,

bivoltine with two and multi-voltine with three or more (Tauber and Tauber 1981).

Recently, authors have begun to express skepticism about our ability to extract general

conclusions about latitudinal trends in species richness, body size and biology for parasitoid

wasps, due to biases in sampling and/or description (Willig, Kaufman et al. 2003; Santos and

Quicke 2011; Quicke 2012; Veijalainen, Wahlberg et al. 2012; Veijalainen, Sääksjärvi et al.

2014). The presence of many cryptic species within Hymenoptera, along with unequal sampling

efforts (lower sampling intensities in tropical regions) requires researchers to standardize and

intensify their sampling protocols – especially when producing general conclusions with

multiple studies and/or researchers.

Investigating large-scale macroecological trends that are affected by latitude (such as diversity

and body size) is particularly challenging for parasitoids, because they are part of complex

networks involving many ontogenetic and phylogenetic factors (Chown and Gaston 2010). For

example, speciation history, nutrition and the site’s climatic history can influence the trends we

observe (Taylor and Gotelli 1994; Chown and Gaston 2010).

The objectives of my thesis

My first study (Chapter 2) attempts to address the effects of latitude on parasitoid wasp

diversity. Diversity is greatly influenced by environmental variables such as temperature and

precipitation, because higher temperature and greater precipitation increases organismal

productivity and evolutionary speed (Pianka 1966; Rohde 1992). Therefore, if parasitoid

4

diversity is positively correlated with precipitation or temperature, then I should observe a

decrease in diversity at higher latitude sites. Since my hypothesis infers that parasitoid wasp

diversity is lower at higher latitudes due to their decreased ability in adapting to harsh

environmental conditions, thus “a lack of locally adaptive race formation within species” (pg.

465, Isaac, Mallet et al. 2004), my definition of species is based on the phylogenetic species

concept. By combining DNA barcoding methods with morphological and ecological data I

quantified parasitoid diversity (BINs and phylogenetic diversity (PD)(Crozier, Agapow et al.

2009)) across a latitudinal gradient (~4.088 - 58.676°N – The Nouragues field station, French

Guiana; Lamanai, Belize; Multiple State Parks, FL, USA; Haldimond-Dunn Townline, ON, CAN;

Guelph, ON, CAN; Wilberforce, ON, CAN; Algonquin Provincial Park, ON, CAN; Churchill, MB,

Canada). Specimen information was extracted from previous collections on BOLD and I further

expanded these collections with field work in Algonquin Provincial Park and Churchill.

My second study (Chapter 3) investigates the effects of latitude on body size in Ichneumonidae

and Braconidae. Seasonal length – longer time periods of higher temperatures and greater

precipitation – influences the amount of time insects have to forage, develop and grow

(Blanckenhorn 2004). Therefore, if the body sizes of parasitoid wasps have an inverse

relationship with latitude due to temperature or precipitation, then larger specimen will be

found in the tropics (French Guiana), compared to temperate (Algonquin) or sub-arctic

locations (Churchill). By using wing length and hind tibia length as proxies for body size, I was

able to measure specimen images available from BOLD. The body size comparisons were

conducted across the same latitudinal gradient as my diversity analyses, with the exception of

sites in Florida.

Both of these studies investigate large-scale macroecological trends by trying to avoid the

taxonomic impediment through the use of DNA barcodes and a variety of other specimen

information available from BOLD. With my two chapters, I hope to produce general conclusions

regarding spatial patterns and body size of parasitoids inside and outside of the tropics, which

has previously been a very difficult task due to the limited research on parasitoid species

richness (Gaston and Gauld, 1993).

5

CHAPTER 1 FIGURES

Figure 1.1. The Bergmann’s rule states that larger specimens are found at higher latitudes because they have lower surface area-to-volume ratios, which is more beneficial for conserving heat. A represents an organism found at lower latitudes, while B represents an organism found at higher latitudes. Though B is a larger specimen, the surface area-to-volume ratio is lower than that of A.

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CHAPTER 2: PARASITOID AND PARASITIC WASP DIVERSITY ACROSS A LATITUDINAL GRADIENT

ABSTRACT

Latitudinal effects on parasitoids are poorly understood, yet investigating these patterns and

their mechanisms are of great importance to maintaining biodiversity, controlling invasive

species and diseases. Current literature has shown support for mid-latitude peaks in diversity

for the Hymenopteran family Ichneumonidae, as well as greater diversity in the tropics and the

absence of any diversity clines. However, many of these previous studies may be artefacts of

geographic and taxonomic sampling biases, especially with the presence of cryptic species

within Hymenoptera. Therefore I used DNA barcodes available from the Barcode of Life Data

System (BOLD) to quantify parasitoid wasp diversity – Barcode Index Number (BINs) and

Phylogenetic diversity (PD). I found that the number of BINs did not exhibit any relationship

with latitude or environmental variables, while PD decreased across latitude and was

significantly affected by precipitation variables. Overall, greater sampling is still required to

produce general conclusions about diversity patterns for parasitoid wasps.

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INTRODUCTION

Latitudinal diversity gradient

One of the most notable patterns in species diversity is the inverse relationship between

species richness and latitude, which holds true for many taxonomic groups such as mammals,

birds, reptiles, amphibians and fish, regardless of geographic context (marine or terrestrial) or

time domain (past or present)(Willig 2001). In fact, this pattern has existed for over a quarter of

a billion years (Willig, Kaufman et al. 2003).

The general mechanisms believed to influence greater floristic and faunistic diversity in the

tropics compared to higher and lower latitudes are possible combinations of climate, energy

and area processes (Hillebrand 2004). In particular, “the severity, variability and predictability of

local environmental conditions” greatly influence species richness in a specific region (pg. 707,

Willig 2001). Therefore, tropical communities are considered to possess more favourable

environmental conditions for organisms, because high solar insolation and warm temperature

increase productivity, while low intra-annual variation in temperature and rainfall allow

organisms to better predict the elements (Willig 2001; Archibald, Bossert et al. 2010). Recently,

Brown (2014) proposed that kinetics – effects of temperature on ecological and evolutionary

rates – may be the most important factor determining species diversity.

Though a general consensus on which hypotheses best explains this latitudinal diversity

gradient is still lacking, plausible historical and ecological hypotheses for this phenomena are

listed below:

1. Geographic Area Hypothesis (Terborgh 1973): The tropics consist of larger land surface

area than higher latitude regions; therefore the tropics can support greater numbers of

species.

2. Time and Area Hypothesis (Wallace 1878): The lower diversity in temperate regions may

be a result of the effects of glaciation from the Pleistocene era, because those species

have not had enough time to recolonize. As a result a greater number of species have

accumulated for a longer period of time in the tropics compared to higher latitudes

(Mittelbach, Schemske et al. 2007).

3. Productivity Hypothesis (Pianka 1966; Robinson 1966): Greater productivity results in

greater species richness. The tropics are exposed to more solar radiation, which is

positively correlated with energy availability, productivity and biomass, resulting in

greater species richness.

4. Ambient Energy Hypothesis (Willig, Kaufman et al. 2003): Higher latitudes are harsher

and more costly for many organisms, due to the environmental conditions being farther

away from organismal optima. These conditions prevent greater numbers of species

from colonizing higher latitude habitats.

8

5. Rapoport-Rescue Hypothesis (Rapoport 1975): Species’ distribution range size is

inversely related to latitude. Therefore organisms able to withstand greater seasonal

variation can possess larger distribution ranges, whereas tropical organisms with lower

levels of tolerance to seasonal variation are restricted to smaller ranges.

6. Evolutionary Speed Hypothesis (Rohde 1992): The tropics have greater diversity,

because higher temperatures increase speciation rates through shorter generation

times, higher mutation rates and accelerated selection pressure.

7. Geometric Constraints Hypothesis (Colwell and Hurtt 1994): Greater diversity in the

tropics is the result of “random placement of species ranges within a bounded domain”

(pg. 296, Willig, Kaufman et al. 2003) This is similar to a null hypothesis.

Exceptions - Parasitoid diversity

In 2003, Willig, Kaufman et al., found that nearly 71% of 135 analyses regarding diversity across

a latitudinal gradient showed species richness was higher in the tropics, meaning that even

though the majority followed this trend, there were still exceptions. Many of these exceptions

were studies based on parasitic species, aquatic floras and latitudinal band analyses of less than

20° (Willig, Kaufman et al. 2003). Examples include peaks in diversity at polar regions for seals,

penguins and sandpipers, and temperate regions for voles, salamanders and ichneumonid

wasps (Willig 2001). These results were similar to a meta-analysis conducted by Hillebrand

(2004), which examined over 600 studies on latitudinal diversity gradients that showed a small

number of exceptions to the general pattern still exist.

Since Janzen (1981) reported that the greatest diversity of Nearctic Ichneumonidae existed

between 37.5° and 42.4°N latitude with nearly 900 species per 106 km2, the Hymenopteran

parasitoid family Ichneumonidae has received much attention. He also found that species

richness dropped substantially when moving southward from the 37.5°-39.9°N band to the

35.0°-37.4°N band (Janzen 1981). This was thought to be unusual, because the diversity of

many possible host groups for parasitoids, such as those from the orders Lepidoptera and

Coleoptera were dramatically higher in the tropics compared to temperate regions. Skillen,

Pickering et al. (2000) presented results that corroborated the study by Janzen (1981), though

they suggested that the peak in diversity was broader than initially thought. Furthermore,

Janzen and Pond (1975) and Janzen (1976) suggested that this anomalous pattern should be

present for all parasitic Hymenoptera.

Multiple hypotheses have been proposed to explain this anomalous diversity:

1. The Resource Fragmentation Hypothesis (Janzen and Pond 1975): Individuals within the

large number of host species may be too scarce and spread out for the parasitoids to

successfully find them, parasitize them and complete their life cycle.

9

2. The Predation Hypothesis (Rabinowitz and Price 1976): Predation plays an important

role in the distribution of diversity, particularly in the tropics, because higher predation

pressure makes immature/larval stages more vulnerable to predators.

3. The Interphyletic Competition Hypothesis (Eggleton and Gaston 1990): Competition is

greater for host species in the tropics, because parasitoid wasps have to compete with

other parasitic taxa such as nematodes and fungi, which are probably more diverse in

the tropics.

4. The Nasty-host Hypothesis (Gauld, Gaston et al. 1992): Tropical herbivores/hosts are

able to sequester noxious secondary metabolites available in higher quantities in

tropical plants against parasitoids, compared to temperate herbivores/hosts.

5. The Intermediate Disturbance Hypothesis (Wilkinson 1999): Species richness peaks at

intermediate levels of disturbance, because species are more prone to extinction at

higher levels of disturbance (ex. forest fires, deforestation) and at lower levels of

disturbance due to increased competition between subordinate species (Sheil and

Burslem 2003).

Testing these hypotheses is a challenging task, because latitude is considered to be a surrogate

for various environmental gradients, such as temperature, precipitation and seasonality that

interact and correlate with each other (Willig, Kaufman et al. 2003). As a result, all of the

hypotheses may hold some aspects of truth.

Doubts about the anomalous diversity

Since Janzen’s (1981) study, the ichneumonid wasps have been presented as an exception to

the general pattern of diversity increasing towards the tropics and numerous textbooks have

incorporated these findings (Gaston and Williams 1996; Pimentel and Pimentel 2007; Gaston

and Blackburn 2008). However, some researchers have cast doubts upon the validity of these

claims due to insufficient and biased taxonomic and geographic sampling (Skillen, Pickering et

al. 2000; Willig, Kaufman et al. 2003; Jones, Purvis et al. 2009; Baselga, Lobo et al. 2010; Santos

and Quicke 2011; Quicke 2012; Veijalainen, Wahlberg et al. 2012).

It is unlikely that a single researcher could gather sufficient evidence to support diversity

patterns across major latitudinal gradients (Willig, Kaufman et al. 2003). Therefore,

investigating these trends require the compilation of data from multiple researchers. However

this may be a problem because different studies involve different experimental parameters,

making direct comparisons between studies more difficult, especially if the methods were not

standardized. Data from certain geographic regions such as North America and Europe may also

skew results, because these areas are better studied compared to regions such as Central and

South America (Santos and Quicke 2011). Furthermore, Willig, Kaufman et al. (2003) mention

that sampling should be constrained by both time and space, because data gathered over

10

longer time periods may inflate species richness due to communities interacting with each

other.

Recent studies integrating DNA barcoding into the ongoing inventory of tropical biodiversity

within the Area de Conservacion de Guanacaste in Costa Rica has revealed that many previously

presumed polyphagous species were actually morphologically cryptic host specialists (Smith,

Wood et al. 2007; Smith, Rodriguez et al. 2008; Janzen, Hallwachs et al. 2009; Smith,

Fernandez-Triana et al. 2009). The term “cryptic species” is defined as two or more species that

have been classified as a single nominal species due morphological similarities, and they are

frequently revealed to be different species through molecular analyses that integrate ecological

information (such as host species) (Smith, Wood et al. 2007; Smith, Rodriguez et al. 2008). For

example, morphological and DNA analyses were combined with habitat and host records of the

hyperparasitoid Trigonalidae, to provide evidence that one named species is five distinct

species (Smith, Janzen et al. 2012).

Huber (2009) stated “A serious problem in hymenopteran taxonomy is the morphological

plasticity of individuals within species, often combined with their small size (most parasitic

species) and the huge number of species, especially in the tropics….The result is an enormous

taxonomic impediment in trying to identify and describe hymenopteran biodiversity “ (pg. 203).

Therefore due to the frequent presence of cryptic species within Hymenoptera, relying on

studies that incorporate DNA barcoding to help delineate species and expedite the process of

species discovery would allow us to make stronger arguments for diversity patterns.

Parasitoid wasp identification and molecular markers

Traditional methods of identifying specimens and describing species rely on morphological

taxonomy and behavioural observations. DNA barcoding has increased in popularity for tasks

involving unknown specimen and species identification, due to the presence of numerous

cryptic species in hymenopteran groups that are extremely difficult to identify based solely on

morphology. For example, with the use of mitochondrial DNA sequence data, the oak gall wasp,

Andricus quercustozae (Cynipidae), was revealed to have at least two genetically different

individuals within the species (Rokas, Melika et al. 2003) and one morphological fig-pollinating

wasp species, Pleistodontes imperialis, was also revealed to be made up of four cryptic species

(Haine, Martin et al. 2006).

DNA barcoding involves the use of a standardized DNA marker, such as the 658 base pair region

of mitochondrial cytochrome c oxidase I gene (COI), for comparison to a reference library

containing sequences from known specimens (Hebert, Cywinska et al. 2003a; Hebert,

Ratnasingham et al. 2003b). A few of the numerous studies that use the COI marker include

food web interactions with leaf-mining Lepidoptera and gall-inducing Hymenoptera (Kaartinen,

Stone et al. 2010), tropical ichneumonid wasp diversity assessments (Veijalainen, Wahlberg et

11

al. (2012) and assessments in host phylogeny and specialisation in parasitoids (Rougerie, Smith

et al. 2011; Smith, Eveleigh et al. 2011; Desneux, Blahnik et al. 2012).

COI was selected over other mitochondrial protein coding genes for DNA barcoding because

this mtDNA marker can be amplified using near-universal primers that permit unified

methodologies across a broad range of taxonomic levels (Bucklin, Steinke et al. 2011). It was

also the most abundant barcode gene in GenBank for arthropods, which was one of the main

reasons why it was selected as the gold standard marker. Furthermore, its evolution is rapid

enough to differentiate very closely related species in most groups and has “taxonomically

significant intraspecific variation associated with geographic structure” (pg. 173,Bucklin, Steinke

et al. 2011).

COI was the principal molecular marker used for the standardized mtDNA sequencing methods

in my study, because along with the reasons mentioned above, my research is dependent on

analyzing existing specimens and contributing new specimens to the Barcode of Life Data

System – BOLD (Ratnasingham and Hebert 2007). BOLD assembles molecular, morphological

and distributional data and mainly uses COI as its standardized molecular marker for animals.

BOLD also utilizes a Barcode Index Number System (Ratnasingham and Hebert 2013) which is

an online framework that clusters barcode sequences with an algorithm that utilizes graph

theoretic methods to create operational taxonomic units (Barcode Index Numbers -

BINs)(Ratnasingham and Hebert 2013). This is done without prior taxonomic knowledge, and

these BINs can be considered to be synonymous with species. Much of the data available on

BOLD (over 1, 390, 000 sequences with base pair lengths greater than 500) is accessible to the

public, allowing researchers to review BINs webpages and identify possible errors

(Ratnasingham and Hebert 2013).

Objectives

While taking into account the many challenges associated with constructing general conclusions

about diversity patterns, I investigated this anomalous diversity pattern further. I wanted to

reduce the number of taxonomically misidentified specimens that may influence diversity

results by relying on BOLD for specimen information (i.e. sequence, BINs, collection site latitude

and longitude, collection date) that was collected in a standardized manner.

My main objective was to compare parasitic and parasitoid wasp diversity (measured as

molecular operational taxonomic units (BINS) and phylogenetic diversity (PD – (Crozier, Agapow

et al. 2009)) across a latitudinal gradient (~4.9 - 58.7°N) to test whether enumerating diversity

using DNA supported a mid-latitude peak in parasitoid diversity. Both annual mean

temperature and annual precipitation decreased with latitude, therefore latitude was

considered to be a surrogate for temperature and precipitation gradients.

12

Questions, hypotheses and predictions

Question:

Is parasitoid species diversity, measured using DNA barcodes via molecular operational

taxonomic units (BINs), or PD, characterized by a mid-latitude peak in diversity?

Hypothesis and prediction:

Diversity is greatly influenced by environmental variables such as temperature and

precipitation, because higher temperature and greater precipitation have been hypothesized to

increase organismal productivity and “evolutionary speed” (Pianka 1966; Rohde 1992). If

parasitoid diversity is positively correlated with precipitation or temperature, then I should

observe a negative correlation with latitude.

METHODS

Specimen Selection Criteria

Specimens and sequence data were selected from previous collections (principally MAS) based

on ongoing field programs and hosted on BOLD (Table 2.1, Figure 2.1). To standardise specimen

selection and sampling effort I used a set of inclusion criteria:

1. Hymenoptera were from the parasitoid superfamilies Chalcidoidea, Chrysidoidea,

Cynipoidea, Ichneumonoidea, Platygastroidea, Proctotrupoidea and Tenthredinoidea

based on visual examination of specimens compared to Hymenoptera of the World

(Goulet and Huber 1993)

2. The collection sites had to contain Malaise trapped specimens.

This set of inclusion criteria was implemented to create a more comparable set of specimens

across sites; but their stringency also resulted in a reduction in the number of samples. For

example, after filtering BOLD data according to my inclusion criteria, I only had 1,136 Churchill

specimens, though there were more than 7,870 specimens available from Churchill (Stahlhut,

Fernandez-Triana et al. 2013).

I augmented previous collections with specimens collected during field work in Algonquin

Provincial Park, ON as well as Churchill, MB. At all sampling localities, specimens were

predominantly collected using Malaise traps (Townes and Arbor 1962), as well as by yellow pan

traps, UV lights and active searching. The Malaise traps were set up for approximately 5-14 days

prior to collection at the sampling sites.

13

At each sampling site GPS co-ordinates (latitude, longitude, elevation) were recorded, along

with field observations – time on site (arrival and departure), temperature (°C), weather

conditions (sunny, cloudy, windy) and a brief description of area (dominant plant species,

ground cover). GigaPan panoramic photographs (www.gigapan.org) were also taken while

actively collecting insects (Table 2.2). Collected specimens were then preserved in 95% ethanol

for laboratory processing and transported to the University of Guelph.

Molecular analyses

Collected specimens were sorted into morphospecies, databased and photographed using a

Dino-Lite AD413 digital microscope (Dino Canada). The abdomens were removed and used as

tissue samples for DNA extraction.

Tissue samples were used to prepare genomic DNA extracts using the Nucleospin® 94 Tissue Kit

(Macheret-Nagel Duren, Germany), which was then placed in 30µL of dH2O (Smith, Fernandez-

Triana et al. 2009). The 658 base-pair (bp) region near the 5’terminus of the cytochrome c

oxidase 1 (COI) gene was amplified using primers LepF1 or LepRI. If a 658bp was not produced,

shorter sequences were generated using internal primer pairs RonMWASPdeg_t1 and LepR1

(Smith, Fernandez-Triana et al. 2009), and LepF1 and C_ANTMR1D (Smith, Fisher et al. 2005).

These sequences were then overlapped to create composite sequences or used on their own

(Smith, Fernandez-Triana et al. 2009).

The polymerase chain reactions (PCR) was carried out in 96-well plates in 12.5 µL reaction

volumes containing 2.5 mM MgCl2, 5 pmol of each primer, 20 µM deoxyribonucleotide

triphosphate (dNTP), 10 µM Tris (buffered) HCl (pH 8.3), 50 mM KCl, 10-20 ng (1 – 2 µL)

genomic DNA, 1 unit of TaqDNA polymerase (Platinum ® Taq Polymerase – Invitrogen) using a

thermocycling procedure. The PCR profile consisted of one cycle of denaturing at 2 min at 94°C,

five cycles of denaturing for 40 sec at 94°C, annealing for 40 sec at 45°C, and extension for 1

min at 72°C, followed by 36 cycles of denaturing for 40 sec at 94°C, annealing for 40 sec at 51°C,

and extension for 1 min at 72 °C, with a final extension of 5 min at 72 °C (Smith, Fernandez-

Triana et al. 2009). PCR products were visualized using 96-well 2% agarose E-Gel ® plates

(Invitrogen) to assess the presence of samples containing clean single bands. If these bands

showed successful amplification, they were bi-directionally sequenced using BigDye v3.1 on an

ABI 3730xl DNA Analyzer (Applied Biosystems). PHRED scores greater than 20 and 30 were

considered to be high quality and very high quality base calls respectively, and base calls less

than 20 were recorded as N (Hanner 2005). COI barcode sequences containing at least 510bp

with less than 1% N’s were uploaded to BOLD.

Sample size for estimating diversity

Four thousand seven hundred and eighty-five (4,785) hymenopteran parasitoid specimens from

the selected collection sites were barcoded and used in my analyses (APPENDIX 1). Since

14

sample size varied between sites, I wanted to control for sampling intensity by comparing the

diversity of all the specimens with a randomly selected subset of specimens from each site. The

sample size for the subset from all sites was based on the site with lowest number of sequences

(Table 2.3 - Belize), so 280 specimens were randomly selected from all other sites (APPENDIX 2).

Environmental data

To compare diversity with temperature and precipitation variables from each site, climate

information was gathered from 1 km2 WorldClim data (Hijmans, Cameron et al. 2005) using

DIVA-GIS V.7.5 (Hijmans, Guarino et al. 2012).

Diversity analyses

Once the specimens were barcoded, sequences (>300bp) of the COI gene were initially aligned

using the BOLD aligner (Amino Acid based HMM), then by MUSCLE V.3.8.31 (Edgar 2004) and

finally verified by eye. A Neighbor-joining tree (Saitou and Nei 1987) using Kimura-2 parameter

(Kimura 1980) was created for all the specimens using BOLD to evaluate whether sequences

less than 500 bp belonged to specific BINs. If the sequences were not found within a BIN cluster

and were more than 2% divergent from any other sequence in BOLD, then they were assigned a

separate, and provisional, MOTU (i.e. TIE001). These sequences were used to estimate the

diversity of parasitoids using both operational taxonomic units (BINs) and phylogenetic based

measures of diversity (PD). In the literature, there are two definitions for PD;

1. Community PD (Crozier, Agapow et al. 2009; Cadotte, Jonathan Davies et al. 2010): sum

of all phylogenetic branches connecting species within a community

2. Faith’s PD (Faith 1994): sum of all phylogenetic branches connecting species within a

community plus the root from a larger regional phylogeny.

I used both PD measures for my comparisons and these values were calculated using the PD

module in the PICANTE package (Kembel, Cowan et al. 2010) in R version 3.1 (Team 2012).

The phylogenetic tree used to calculate Community PD was a Maximum Likelihood (ML) tree

(Felsenstein 1981) constructed in MEGA V.6 (Tamura, Stecher et al. 2013). To create the best

ML tree, a comparative analysis was first conducted using MEGA to find the best model and

parameters given the data. The analysis involved 1428 unique nucleotide sequences. All

positions containing gaps and missing data were eliminated and the model with the lowest BIC

score was considered to describe the substitution pattern the best. The results indicated that a

General Time Reversible model (GTR) (Nei and Kumar 2000) using a discrete Gamma

distribution (+G) with 5 rate categories and assuming that a certain fraction of sites are

evolutionarily invariable (+1) was the best method. It is important to note that some

hymenopterans display a “6 bp deletion in COI in the 155th and 156th amino acids of the

barcoding region” which is within the third internal loop (pg. 3, Smith, Eveleigh et al. 2011).

15

To calculate Faith’s PD, the same parameters were used as mentioned above, however the ML

tree was rooted with an outgroup containing two Diptera, Hemiptera and Lepidoptera

sequences from BOLD in MEGA (APPENDIX 3). The outgroup taxa were selected in a manner

similar to Heraty, Ronquist et al. (2011), where specimens were chosen from the closest sister

groups to Hymenoptera.

According to Gotelli and Colwell (2001), diversity should only be compared if species

accumulation curves reach a clear asymptote. However, this is highly unlikely for sampling that

involves parasitoids (Sääksjärvi, Haataja et al. 2004), even in relatively depauperate areas such

as Churchill (Stahlhut, Fernandez-Triana et al. 2013). In cases where accumulation curves do not

reach an asymptote, the curves can still be compared when scaled appropriately (Gotelli and

Colwell 2001).

The data available on BOLD are unlikely a true representation of the number of parasitoid

species that exist at any site (Smith, Rodriguez et al. 2008; Stahlhut, Fernandez-Triana et al.

2013). To address this problem I used EstimateS V.9.1 (Colwell and Elsensohn 2014) to create

species accumulation curves with non-parametric richness estimators, using presence or

absence data. I used Chao2 (Chao 1987) calculations to estimate the asymptotic richness of my

specimens with 100 randomizations. Two hundred and eighty (280) randomly sampled

specimens from each of the eight collection sites, totalling 2,240 specimens, were used for the

classic Chao2 non-parametric richness estimator. Though 1000 randomizations per sample is

the standard, EstimateS V.9.1 was unable to calculate 1000 randomizations for my large dataset

(Robert Colwell, pers comm). I also created rarefaction curves for each collection site using

Chao2 with 1000 randomizations and BOLD accumulation curves with 100 iterations to

compare whether the slopes of the curves varied among sites. If the slopes increased at similar

rates, it would allow for better comparisons among sites.

RESULTS

All collection information, photographs, DNA sequences and trace files discussed here have

been deposited on BOLD (http://dx.doi.org/10.5883/DS-TIEPARIS), in GenBank and in APPENDIX

1. The linear regression between estimates of Faith’s PD from all available sequences from the

eight collection sites with BINs exhibited a stronger positive linear relationship (R2=0.733,

F=16.46, p=0.007) compared to the estimates of Faith’s PD for the sample subset (R2=0.184,

F=1.35, p=0.289) (Figure 2.4A, B).

Estimates of Faith’s PD (R2=0.0846, F=0.554, p=0.485) and BINs (R2=0.275, F=2.27, p=0.182)

exhibited non-significant linear inclines with latitude for all the samples, which was opposite to

16

the trends exhibited by the randomly sampled subset. These trends are listed below. It should

also be noted that all of the comparisons involving estimates of Community PD exhibited the

same trends as Faith’s PD, though the linear regressions values for Community PD were

stronger.

Diversity vs. Latitude

Estimates of Faith’s PD from the randomly sampled subset of sequences exhibited a negative

linear relationship with latitude (R2=0.267, F=2.19, p=0.190) (Figure 2.4A), showing support for

my hypothesis. However, the number of BINs did not support my hypothesis, because it

exhibited no relationship with latitude (R2=0.0002, F=0.0011, p=0.974) (Figure 2.4B). Neither of

these results were significant.

Diversity vs. Environmental variables

Estimates of Faith’s PD exhibited stronger, though non-significant relationships with annual

precipitation (R2=0.330, F=2.96, p=0.136) than annual mean temperature (R2=0.212, F=1.62,

p=0.251) (Figure 2.5A, 2.6A), while the number of BINs did not exhibit any trends with any of

the environmental variables (Figure 2.5B, 2.6B; Table 2.6).

The comparison between estimates of Community PD and environmental variables revealed

that PD was most influenced by the precipitation of the driest quarter (R2=0.688, F=13.22,

p=0.011), precipitation of the driest month (R2=0.609, F=9.35, p=0.022), annual precipitation

(R2=0.557, F=7.54, p=0.033) and precipitation of coldest quarter (R2=0.547, F=7.23, p=0.036)

(Table 2.5). Estimates of Faith’s PD were also most influenced by the same environmental

variables, though these trends were not statistically significant.

Asymptotic species richness

Based on 2,240 sequences, the Chao2 species richness estimator over 100 randomizations

illustrated that the number of BINs that should be present in total was 3,640 from the eight

collection sites collectively (Figure 2.7). This number is more than 2.5 times greater than the

number of unique BINs present in the samples – 1428.

In all cases, diversity (as viewed with rarefaction curves) has not been completely sampled and

continues to increase at collection locations after the subsampling of 280 sequences. Also the

rates of increase were not the same (Figure 2.8, Table 2.3). For example, diversity of samples

from French Guiana were seen to increase at a greater rate than the other locations.

Importantly, the Chao2 rarefaction curves calculated at each location show different rates of

the accumulation of diversity – so that although no site has reached an asymptote by 280

samples – there are evident differences in these rates for the different localities. Interestingly,

the rarefaction curves produced by BOLD showed much more overlap than the Chao 2 curves

(Figure 2.9; Table 2.3). This suggests that for groups such as the parasitoid wasps, rarefaction

17

methods that explicitly consider singletons (such as Chao2) are more useful for comparing

molecularly estimated diversity than those that do not.

DISCUSSION

Previous studies examining latitudinal trends in diversity for parasitoid wasps have found

several patterns including a decline in diversity with latitude (Hespenheide 1979; Noyes 1989;

Gaston and Gauld 1993; Gaston 2000), a mid-elevation peak (Owen and Owen 1974; Janzen

and Pond 1975; Janzen 1981; Quicke 1995; Skillen, Pickering et al. 2000) and the absence of any

cline (Veijalainen, Wahlberg et al. 2012). Unfortunately, most of the results from these studies

may be artefacts of geographically and taxonomically biased data (Willig 2001; Willig, Kaufman

et al. 2003; Jones, Purvis et al. 2009; Santos and Quicke 2011). Therefore I focused my efforts

into analyzing specimens available from BOLD, collected and processed using standardized

methods, where diversity was enumerated via BINs and PD.

Both temperature and precipitation variables have been regarded as limiting factors for

diversity, due to their effects on insect physiology and productivity (Srivastava and Lawton

1998). Therefore I expected to see an inverse relationship between parasitoid diversity (BINs

and PD) and latitude, with the assumption that latitude was a surrogate for temperature and

precipitation gradients. The main difference between the two diversity measures is – BINs

represent the number of species found at a site for this study, while estimates of PD represent

how closely related those species are.

BINs did not exhibit any peak in diversity across latitude, while PD estimates were highest at the

lowest latitude site (French Guiana) and lowest at the highest latitude site (Churchill). These

results were not significant, but suggest that there may be different mechanistic drivers for the

two diversity measures. For example the number of species (BINs) found at a site may be

attributed to biotic factors such as competition for host species or predation, and the

relatedness between those species (PD) may be the product of abiotic factors such as limiting

environmental variables or site history.

BINs

The lack of a diversity cline across latitude exhibited by BINs was similar to the results reported

by Veijalainen, Wahlberg et al. (2012), which stated Neotropical orthocentrine species (177)

was roughly similar to the known species found in Nearctic regions (151). They did suggest that

increased sampling will yield higher species numbers at both regions, therefore general

conclusions should not be made about diversity patterns. The Chao2 estimate for species

18

richness for my study was more than double the number of species present in the sample,

indicating insufficient sampling at the collection sites.

The number of BINs found at a site was also not influenced by local environmental variables,

indicating other variables such as competition, predation or resource availability may play a

bigger role in how many parasitoid species are able to persist in certain locations.

There are many forms of competition that could affect these species numbers, ranging from

competition for hosts and other resources among the same species of parasitoids (intraspecific

competition), among other species of parasitoids (interspecific competition) (Rabinowitz and

Price 1976) and among other organisms (Eggleton and Gaston 1990). Therefore competition

can explain the lack of a diversity cline, if the pressure exerted from competition towards

parasitoid wasps was the same, even though the type of competition may differ across latitude.

For example, fungi or other parasitic taxa may be regarded as parasitoid wasp species’ main

competition at lower latitudes, while other parasitoid wasps may be bigger competitors at

higher latitudes, but the overall competitive pressure is the same at all sites.

Predation can also explain the absence of a diversity cline if predation pressures on larval and

adult parasitoid wasps were the same across latitude. Rabinowitz and Price (1976) have stated

that higher predation on immature stages of parasitoids, especially by ants, in the tropics may

result in a decrease in diversity across latitude. Conversely, Gauld (1987) has stated that

predation pressures on adults is higher than for immature stages. Hyperparastioid diversity

patterns are less understood than parasitoid diversity patterns, but it can be assumed

hyperparasitoid diversity is dependent on parasitoids. This opens up the possibility that

predators at different sampling sites may be different groups of taxa and specialize on different

life stages of parasitoid wasps. For example tropical predators may largely prefer eggs or

immature stages, while temperate predators may prefer adults, though the predation pressure

exerted on the parasitoid wasps would be the same across latitude. I have not tested for

competition or predation effects, but it might be of interest for future researchers investigating

mechanisms for diversity patterns.

Estimates of PD

For the randomly sampled subset, specimens from Churchill were more closely related to each

other than specimens from any of the other sites Community PD also exhibited stronger linear

inclines with precipitation variables than temperature variables – specifically the precipitation

of the driest quarter, driest month, annual levels and coldest quarter. Therefore shared

physiological tolerances between related species to low precipitation levels may be one of the

better explanations for the inverse relationship between estimates of PD and latitude.

19

These results support Shapiro (2000), which reported that rainfall (moisture) was key to better

understanding parasitoid activity and that Ichneumonidae activity may be restricted by hot, dry

conditions. Support for hymenopteran diversity gradients being driven by climatic seasonality,

in particular precipitation, is persistent in literature (Abrahamczyk, Steudel et al. 2010;

Archibald, Bossert et al. 2010; Abrahamczyk, Gottleuber et al. 2011). However, Brown (2014)

emphasized that species diversity increased with temperature much more rapidly than with

species abundance or net primary production, because the higher temperatures increased

“rates of metabolism, ecological dynamics and co-evolutionary processes, which generate and

maintain higher biodiversity” (pg. 11). Thus kinetics may be the most important factor in

accounting for species diversity gradients (Brown 2014), which is similar to the evolutionary

speed hypothesis (Rohde 1992).

In addition, the time and area hypothesis (Wallace 1878; Mittelbach, Schemske et al. 2007)

states that diversity may be higher at lower latitudes, because the tropics have had a longer

period of time to accumulate species compared to temperate regions. This hypothesis can be

applied to my study, because lower latitude sites, such as French Guiana have suffered less

from glaciation effects compared to higher latitude sites such as Churchill. In other words,

Churchill species displayed higher levels of relatedness because they have not had enough time

to diversify as much as the species found in French Guiana or Belize.

Other factors that can cause lower biodiversity at higher latitudes range from the loss of

populations though genetic drift and inbreeding depression, slower evolutionary rates at

harsher climates and “geographic/geological barriers to colonization” (pg. 2, Stahlhut,

Fernandez-Triana et al. 2013). Environmental complexity can also affect species interactions

within an ecosystem, thus influencing diversity (Srivastava, Cadotte et al. 2012).

Advantages for using BINs and estimates of PD for assessing diversity

The use of operational taxonomic units (MOTU or BINs) has been shown to be a very fast and

effective method for species identification for many hymenopteran communities (Smith, Fisher

et al. 2005; Smith, Rodriguez et al. 2008; Smith, Eveleigh et al. 2011; Stahlhut, Fernandez-Triana

et al. 2013). They are not always coincident with species, but still show similar species richness

and turnover patterns that is very helpful in short-term studies (Smith, Fisher et al. 2005).

Comparing my estimates of PD generated based on DNA barcodes to a multi-gene phylogeny

would be a natural next step (e.g. Smith, Hallwachs et al. (2014)). However, a species level tree

does not yet exist for hymenopteran parasitoids.

Estimates of PD are especially important for conservation, because they can be used “to assign

conservation value to individual species or assemblages” (pg. 96, Cadotte, Jonathan Davies et al.

2010). Estimates of PD can also be used to help us understand the mechanistic drivers between

20

co-occurring species and whether these evolutionary relationships affect other ecological

processes and interactions (Cadotte, Jonathan Davies et al. 2010).

Limitations and improvements

As expected, estimates of PD increased linearly with BINs for all the sequences available from

the sampling sites, which was similar to the non-significant trend exhibited by the randomly

sampled subset. However, both diversity measures extracted from all the sequences increased

non-significantly with latitude, which was different from the trends exhibited by the randomly

sampled subset. This showcases the importance of avoiding sampling biases when trying to

estimate species richness, because unequal sampling efforts can give rise to false trends.

My results are based on specimens I collected during field work and previously collected

specimens from BOLD that vary in sampling effort across collection sites (temporal and spatial).

Morrison (1979) has mentioned that temporal variation during sampling may be a problem

because species composition varies through time. For example, the adults of several

Ichneumonidae subfamilies have been noted to be less abundant during the dry season

(Shapiro 2000). Therefore an ideal experimental design for the future would consist of year

round sampling, similar to that of Owen and Owen (1974), with strict sampling protocols (type

of traps, specimen processing), incorporating specimens collected at different elevations across

latitude.

Most of my specimens were collected predominantly with Malaise traps, though some

specimens from French Guiana and Florida were also collected using a UV light and other

specimens from Florida were collected with yellow pan traps and active searching. This could

be a potential problem, because different trap types attract different species. Morrison (1979)

has suggested the perhaps Malaise traps are biased against smaller flying insects that are too

small to be caught in the mesh and travel up to the ethanol container. If the tropics do contain

larger populations of smaller species of parasitoids compared to temperate regions, then

Malaise traps are potentially insufficient for collecting these organisms. Veijalainen, Sääksjärvi

et al. (2014) has also indicated that perhaps malaise traps dates are not the best indicator of

sampling effort, because higher population densities at a certain sites (mid and high altitude)

may yield more specimens due to a greater abundance of individuals that come upon the traps.

As a result the number of species at the low population density sites (low altitude) may increase

if more individuals were caught.

To standardise sampling effort across latitude, I restricted the number of samples from sites

with greater sequence numbers. For example, there were 4,785 parasitoid/parasitic

hymenoptera sequences available from the eight sampling sites, but when narrowing the

sequences down to a sampling locality (Belize – 280 samples) and family (Ichneumonidae), I

only had 21 specimens. Thus the constrained sample size of 280 specimens from each sampling

21

site likely affected my analyses, because 280 specimens is a very small number to be an

adequate representation of total diversity at a site. Many hymenopteran species are still

awaiting discovery and identification, which was apparent by the number of singletons and

doubletons present in the randomly sampled subset and at each site (Table 2.3). Morrison

(1979) has also suggested greater sampling effort is perhaps required at tropical habitats

compared to temperate habitats to reach an asymptote in species curves. Therefore my

constrained samples may have exhibited inaccurate patterns.

Many researchers have highlighted that additional research is required to validate latitudinal

trends (Willig 2001; Willig, Kaufman et al. 2003; Jones, Purvis et al. 2009; Veijalainen, Wahlberg

et al. 2012), so it might be more beneficial to thoroughly sample and barcode specimens from

specific locations, instead of spreading thin over greater locations.

Conclusions

Insufficient sampling is one of the biggest downfalls to studies investigating diversity patterns

for parasitoids. Even with advanced methods to identify species with more accuracy and at

greater speed, our results are still obstructed by geographic biases involving unequal sampling

effort. Long-term studies involving year round sampling with a variety of collection methods

across elevational gradients across latitude would be the ideal way to test out these

macroecological trends. However, studies such as these require great levels of funding and

collaborative efforts of many researchers at different sampling localities following the same

sampling protocols. Therefore DNA barcoding platforms, such as BOLD, may be a link for such

collaborative work. I believe that my work, though considered to be quite preliminary, is an

important stepping stone for future investigations of latitudinal patterns.

22

CHAPTER 2 TABLES

Table 2.1. Collection site information, including location, collection dates and sampling method.

A randomly selected specimen from each location was used to retrieve GPS coordinates

(latitude, longitude) of the site (Table 2.4). The number of Malaise traps and the distances

between traps varied among sites. Malaise traps were usually set up for 5-14 days prior to the

collection date.

Collection site Latitude

(°N) Longitude

(°E) Collection dates

Sampling method

Nouragues Station, GUF

4.088 -52.681

1 May-1 Sep, 1999; 6 July-13 December 2000; 1 Oct, 2001; 4 January, 2003; 1 April-1 October, 2005; 1 August, 2007; 29 January-10 February, 2011

Malaise traps, Helipad nightlight

Lamanai, Belize 17.751 -88.654 18 April, 2010 Malaise traps

Multiple State Parks, FL, USA

27.264 -82.288 4 March-1 April, 2010; 4 May-28 May, 2011

Malaise traps, Yellow pan traps, UV light, Active searching

Haldimond-Dunn Townline, ON, CAN

42.861 -79.703 20 September-3 October, 2009; 1 August-21 November, 2010

Malaise traps

Guelph, ON, CAN 43.554 -80.264 23 September-1 November, 2009; 1 May-18 November, 2010

Malaise traps

Algonquin PP, ON, CAN

45.521 -78.429 May-August, 2011; April-November, 2012

Malaise traps

Wilberforce, ON, CAN

45.633 -77.070 18 April-9 October, 2010; 26 June10 July, 2011; 12 October, 2012

Malaise traps

Churchill, MB, CAN

58.633 -93.787

29 July-29 August, 2005; 21 July, 2007; 14-17 July, 2008; 20 July-31 July, 2009; 14 July-15 August, 2010

Malaise traps

23

Table 2.2. The webpage URLs for Gigapan habitat panorama galleries taken at the specimen

collection sites.

Collection site Gallery URL

Algonquin PP, ON, CAN http://www.gigapan.com/galleries/7832

Churchill, MB, CAN http://www.gigapan.com/galleries/10704

Lamanai, Belize http://www.gigapan.com/galleries/7591


http://www.gigapan.com/galleries/11456

Nouragues Station, GUF http://www.gigapan.com/galleries/7695






24

Table 2.3. The number of sequences available from each collection site, along with the

percentage of singletons and doubletons from diversity statistics on EstimateS and the results

from Chao 2 and BOLD accumulation curve calculations.

Collection site

Number of sequences

Singletons (%)

Doubletons (%)

Chao 2 Mean

Chao 2 95% CI Lower Bound

Chao 2 95% CI Upper Bound

BOLD Acumulation

Curve Estimates

Nouragues Station, GUF

464 56.03 7.54 1256.3 945.8 1721.6 296

Lamanai, Belize

280 40.71 8.93 406.9 305.0 580.2 160


456 46.71 12.06 701.3 573.3 889.0 299


297 43.77 8.75 492.5 368.9 698.2 181

Guelph, ON, CAN

988 28.85 7.49 984.1 831.8 1196.3 439

Algonquin PP, ON, CAN

498 40.76 8.63 754.0 598.4 988.0 285

Wilberforce, ON, CAN

668 35.03 8.53 831.3 686.2 1041.3 358

Churchill, MB, CAN

1136 28.43 9.95 1025.3 906.1 1185.6 552

Randomly sampled subset

2240 46.12 10.76 3640.9 3276.3 4077.4 N/A

25

Table 2.4. Environmental data was gathered using GPS co-ordinates of a randomly selected

specimen from each collection site.

Site Process ID of

specimen Latitude

(°N)

Annual Mean Temperature

(°C)

Annual Precipitation

(mm)

Nouragues Station, GUF ASNUR007-11 4.088 24.65 3338

Lamanai, Belize ASBZI045-10 17.751 25.33 1723

Multiple State Parks, FL, USA BBHYA1199-12 27.264 22.45 1385


ASGLE458-10 42.861 8.13 910

Guelph, ON, CAN ASGLE023-10 43.554 6.50 908

Wilberforce, ON, CAN ASAHY001-12 45.521 5.31 831

Algonquin PP, ON, CAN ASAHY226-13 45.633 3.56 945

Churchill, MB, CAN JBHCH290-10 58.633 -7.55 419

26

Table 2.5. Linear regression results for comparisons of both Cadotte’s and Faith’s PD with

environmental variables. The results are organized in order of strongest to weakest

relationships for Faith’s PD.

Environmental variable R2 value for Faith's PD

Faith's PD p-value

R2 value for Community

PD

Community PD p-value

Precipitation of Driest Quarter 0.470 0.060 0.688 0.011*

Precipitation of Driest Month 0.443 0.072 0.609 0.022*

Annual Precipitation 0.330 0.136 0.557 0.033*

Precipitation of Coldest Quarter 0.318 0.146 0.547 0.036*

Precipitation of Wettest Quarter 0.297 0.163 0.482 0.056

Max Temperature of Warmest Month

0.288 0.170 0.396 0.094

Precipitation of Wettest Month 0.267 0.189 0.458 0.065

Mean Temperature of Wettest Quarter

0.256 0.201 0.342 0.128

Mean Temperature of Driest Quarter

0.237 0.221 0.394 0.095

Mean Temperature of Warmest Quarter

0.225 0.235 0.342 0.128

Annual Mean Temperature 0.212 0.251 0.360 0.116

Isothermality 0.207 0.257 0.372 0.109

Mean Temperature of Coldest Quarter

0.196 0.272 0.354 0.120

Mean Diurnal Range 0.194 0.274 0.047 0.604

Temperature Seasonality 0.184 0.289 0.355 0.119

Min Temperature of Coldest Month

0.173 0.305 0.336 0.131

Temperature Annual Range 0.127 0.386 0.293 0.166

Precipitation of Warmest Quarter 0.056 0.574 0.063 0.548

Precipitation Seasonality 0.002 0.908 0.007 0.849

27

Table 2.6. Linear regression and p-value results for BINs comparisons with environmental

variables. The results are organized in order of strongest to weakest relationships, though none

was significant.

Environmental variable BINs R2 value BINs p-value

Precipitation of Coldest Quarter 0.121 0.399

Precipitation of Warmest Quarter 0.099 0.449

Mean Temperature of Warmest Quarter

0.074 0.516

Precipitation of Wettest Quarter 0.065 0.543

Max Temperature of Warmest Month

0.059 0.563

Annual Precipitation 0.057 0.568

Precipitation of Wettest Month 0.056 0.573

Annual Mean Temperature 0.047 0.606

Min Temperature of Coldest Month 0.045 0.614

Mean Temperature of Driest Quarter 0.041 0.632

Mean Temperature of Coldest Quarter

0.038 0.643

Temperature Annual Range 0.038 0.646

Mean Temperature of Wettest Quarter

0.030 0.679

Temperature Seasonality 0.023 0.720

Precipitation Seasonality 0.021 0.735

Precipitation of Driest Quarter 0.016 0.763

Mean Diurnal Range 0.014 0.779

Precipitation of Driest Month 0.008 0.829

Isothermality 0 0.989

28

CHAPTER 2 FIGURES

Figure 2.1. Parasitoid specimens were collected from the highlighted locations during the flight

season. The map was constructed on Simplemappr (www.simplemappr.net) using average

latitude and longitude points from the collection sites.

29

Figure 2.2. The Classic Chao2 equation used to estimate species richness for the randomly

sampled subset containing 2,240 specimens.

30

Figure 2.3. Estimates of Faith’s PD exhibited a linear incline with the number of BINs for all the

samples and the randomly sampled subset of 2,240 specimens, though the linear regression

comparison for all samples was stronger. A) Estimates of PD from all the sequences at the eight

sites exhibited a strong linear incline with BINs (R2=0.773, F=16.46, p=0.007).B) Estimates of PD

from 280 randomly sampled sequences from each of the eight sites also exhibited a linear

incline with BINs, though it was not statistically significant (R2=0.184, F=1.35, p=0.289).

31

Figure 2.4. For the randomly sampled subset of 2,240 specimens, Faith’s PD decreased with

latitude, though BINs did not exhibit any trend. Neither result was statistically significant. A)

Estimates of PD exhibited a linear decline with latitude, though the trend was not statistically

significant (R2=0.267, F=2.19, p=0.190). B) BINs did not exhibit any trend with latitude

(R2=0.0002, F=0.0011, p=0.974).

32

Figure 2.5. For the randomly sampled subset of 2,240 specimens, Faith’s PD increased with

annual mean temperature (°C) and BINs slightly decreased. Neither result was statistically

significant. A) Estimates of PD exhibited a linear decline with temperature, though the trend

was not statistically significant (R2=0.212, F=1.62, p=0.251). B) BINs exhibited a slight decline

with temperature, though the trend was not statistically significant (R2=0.0471, p=606).

33

Figure 2.6. For the randomly sampled subset of 2,240 specimens, Faith’s PD and BINs exhibited

a linear incline with annual precipitation levels (mm), though neither result was statistically

significant. A) Estimates of PD exhibited a linear decline with annual precipitation, though the

trend was not statistically significant (R2=0.330, F=2.96, p=0.136). B) BINs exhibited a slight

decline with annual precipitation, though the trend was not statistically significant (R2=0.0471,

P=0.568).

34


estimator for 280 randomly selected individuals from each of the eight collection sites, totaling

2,240 specimens. The dotted lines represent the upper and lower 95% confidence intervals

calculated based on 100 randomizations. The estimator stabilizes approximately after 2,050

samples, suggesting that the number of total species for my samples areas will be

approximately 3, 640.

0

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35


estimator for each of the eight collection sites. At each of the sites, the curves continue to

increase after sampling 280 random sequences from each collection site and French Guiana

appear to have the greatest slope. The dashed line represents the curves at 280 specimens.

0

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Algonquin Wilberforce Florida Haldimond

Belize Guelph Churchill French Guiana

36

Figure 2.9. Asymptotic species richness estimated by BOLD for each of the eight collection sites.

0

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1 251 501 751 1001

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Churchill Algonquin Belize Florida

French Guiana Guelph Haldimond Wilberforce

37

CHAPTER 3: ICHNEUMONIDAE AND BRACONIDAE BODY SIZE ACROSS LATITUDE

ABSTRACT

Bergmann’s rule states that larger individuals of a species are found at higher latitudes, because

the low surface area-to-volume ratio of larger organisms helps conserve more heat. Many

ectotherms follow this rule, but also show support for converse-Bergmann clines and no clines.

Since latitudinal effects on parasitoid wasp body size is still poorly understood, I investigated

these body size trends for Ichneumonidae and Braconidae along the same latitudinal gradient

as my diversity analyses. By utilizing wing length and hind tibia length as proxies for body size, I

was able to measure specimen photographs available on BOLD. Both linear regression results

and the phylogenetic comparative method (PCM) indicated that hind tibia length of both

families followed the converse-Bergmann rule, while wing length exhibited inconsistent

patterns.

38

INTRODUCTION

Macroecological patterns such as diversity and body size along latitudinal gradients have been

extensively studied in the past, though there is still no general consensus about which

underlying mechanisms are the most important – if they exist. Investigating body size patterns

in insects is particularly challenging, because a large variety of factors such as genetics,

voltinism, interspecific interactions and temperature can all affect body size (Figure 3.1).

Voltinism is the number of generations or broods an insect group produces in a year –

univoltine organisms are composed of only one generation, bivoltine with two and multi-voltine

with three or more (Tauber and Tauber 1981). Hayes and Shonkwiler (2006) have suggested

that size is strongly correlated with many physiological, life-history and ecological traits,

signifying the importance of size based studies for ecology and biology. This idea is supported

by a meta-analysis conducted by Hillebrand (2001) that showed body size determines the

strength of the latitudinal diversity gradient.

Bergmann’s rule

One of the most prominent rules regarding body size is Bergmann’s rule (Bergmann 1847; Mayr

1956) – endothermic species (mammals and birds) tend to be larger at higher latitudes,

because they possess smaller surface area-to-volume ratios that help conserve heat in colder

climates. However, the taxonomic level (inter/intraspecific species) that Bergmann (1847)

refers to is still debated in literature (Shelomi 2012). The same heat conservation hypothesis is

applied to Allen’s rule (Reiss 1991), which states that extremities are shorter in colder climates.

Though the Bergmann’s rule was initially applied to endotherms, Ray (1960) found that

approximately 80% of the ectotherms he reviewed were larger at higher latitudes, and this rule

has since been extended to ectothermic species. However, the heat conserving mechanism is

not necessarily applicable for smaller ectotherms that can instantaneously acclimate to

temperature (Stevenson 1985; Blanckenhorn 2004). Therefore a higher temperature threshold

for development rate than growth rate is considered to be one of the better explanations for

why larger ectotherms are found in colder climates (Van Voorhies 1996; Walters and Hassall

2006). This rule is referred to as the temperature-size rule (Atkinson 1994).

Other body size trends

The converse-Bergmann rule suggests organisms are smaller in colder climates, possibly due to

seasonal effects (Blanckenhorn 2004). In particular the heat-dependent growth rates and

metabolic rates are affected by the earlier diapause and short growing seasons of high-latitude

insects (Shelomi 2012). Since Ray’s (1960) study, researchers have found support for both

Bergmann’s rule and the converse-Bergmann rule, depending on the clade under investigation.

For example, turtles, fish and amphibians appear to follow the Bergmann’s rule, while lizards,

39

snakes, freshwater fish and arctic invertebrates follow the converse-Bergman’s rule (Lindsey

1966; Strathdee and Bale 1998; Belk and Houston 2002; Ashton and Feldman 2003).

The latitudinal compensation hypothesis (Levinton 1983; Conover and Present 1990) further

complies with the seasonal mechanisms behind the converse-Bergmann rule, and states

populations at higher latitudes compensate for seasonal time constraints by evolving faster

growth than their conspecifics at lower latitudes (Blanckenhorn 2004). However, this

hypothesis is too directional.

Some other possible explanations for the body size trends are:

1. Migration ability hypothesis – larger species are found at higher latitudes because

smaller species have lower dispersal ability compared to larger species (Blackburn and

Gaston 1996).

2. Starvation resistance hypothesis – starvation resistance increases with body mass,

which may be more advantageous for larger species at higher latitude with scarcer

resources (Lindstedt and Boyce 1985; Calder 1996). This hypothesis can explain cases of

exceptions.

3. Resource availability hypothesis – larger specimen may be found at intermediate

latitudes, due to possible resource shortages at higher latitudes and resources

competition at low latitudes (Geist 1987).

Insect body size

Blackburn (1999) suggested that intra- and interspecific patterns should be investigated

separately, since they may represent different causal mechanisms. For example scarce

resources in highly seasonal climates may give rise to intraspecific variation, while almost

entirely different resources at different latitudes may give rise to interspecific variation. In a

recent meta-analysis, Shelomi (2012) found the most prevalent interspecific latitudinal trend

for size was no cline, followed by a Bergmann’s cline and converse-Bergmann cline. For

intraspecific studies, the most prevalent trend was a Bergmann’s cline, followed by no cline and

a converse-Bergmann cline.

For 62 studies involving Hymenoptera, almost 42% of the studies exhibited no cline, while 40%

exhibited a Bergmann’s cline and the nearly 18% showed a converse-Bergmann (Shelomi 2012).

Santos and Quicke (2011) also found that for Braconidae and Ichneumonidae, body size and

latitude exhibited an inverse relationship. However when they tried accounting for subfamily,

they found that Rhyssinae showed a significantly opposite trend. The general consensus is that

no consistent pattern exists for insect size along latitudinal gradients, and if studies were to

investigate this trend, they should examine related species (Blackburn 1999; Shelomi 2012).

40

Objectives

Ichneumonidae and Braconidae are amongst the most abundant and diverse families in all of

Hymenoptera with approximately 24,000 and 17,000 described species respectively, however,

estimated be over 60,000 and 42,653 species, respectively (Skillen, Pickering et al. 2000; Jones,

Purvis et al. 2009; Quicke 2012). They are also well represented in the Barcode of Life Data

System (BOLD) (Ratnasingham and Hebert 2007). Therefore I want to determine whether there

is a positive relationship between the body size of Ichneumonidae and Braconidae along the

same latitudinal gradient as predicted by the Bergmann’s rule.

Question, hypothesis and predictions

Question:

Does parasitoid body size vary with latitude?

Hypothesis and prediction:

Seasonal length – longer time periods of higher temperatures and greater precipitation –

influences the amount of time insects have to forage, develop and grow (Blanckenhorn 2004).

Therefore, if the body sizes of parasitoid wasps have an inverse relationship with latitude due

to temperature or precipitation, then larger specimens will be found in the tropics (French

Guiana, Belize), compared to temperate (Algonquin) or sub-arctic locations (Churchill).

METHODS

Body size measurements

From all of the sequence data available on BOLD at each collection site, a Neighbor-joining tree

(Saitou and Nei 1987) using Kimura-2 parameter (Kimura 1980) was created using BOLD to

evaluate which specimens belong to the families Ichneumonidae and Braconidae. It should be

noted that specimens from Florida were not used for body size comparisons because I did not

have the sequence information at the time I was conducting the body size analyses.

There are many morphological proxies for insect body size in the literature. These include

Weber’s length – distance between the anterodorsal margin of the pronotum to the

posteroventral margin of the propodeum (Weber 1949; Geraghty, Dunn et al. 2007), forewing

length – distance between point of insertion in the body to the wing apex (Garcia-Barros 2000;

Salvo and Valladares 2002) and hind tibia length (Rosenheim and Rosen 1991). I found that the

left forewing length and left hind tibia length were popular proxies for body size measurements

in parasitoid wasps (Rosenheim and Rosen 1991; Garcia-Barros 2000; Salvo and Valladares

2002), which I measured from images retrieved from BOLD using the Leica Application Suite

(LAS) V.4.2.

41

The scale bar embedded within the image was used to calibrate the measurements. If the left

hind tibia was not clear, then the right hind tibia was measured, with the assumption that the

insect’s body was bilaterally symmetrical (Sander 1986). If the image was blurry or the scale bar

was absent, no measurements were taken from that specimen.

Body size comparisons

For Ichneumonidae, all specimens with suitable pictures as described above were measured

from Algonquin, Belize and French Guiana. Due to the larger sample sizes found in Churchill,

Guelph, Haldimond and Wilberforce, an arbitrary number of 144 specimens were randomly

chosen from each of these sites and all specimens with suitable pictures from the subset were

measured (APPENDIX 4). Unique BINs from each collection site were selected, by assigning each

specimen a random number, and then choosing the specimen with the lowest number within a

BIN at each site to represent the BIN. These specimens were then used for body size

comparisons and will be referred to as the ‘Ich larger sample’ (Table 3.1). Fifteen random BINs

were also chosen from each of the seven sites to compare wing length and 16 random BINs

were chosen to compare hind tibia length. The limiting factor for the smaller sample size, later

referred to as the ‘Ich smaller sample,’ was the lowest number of measurements at a site,

which was found in Belize.

For Braconidae specimens, all specimens with suitable pictures were measured from the seven

sites (Table 3.1; APPENDIX 5). Each specimen was once again assigned a random number and

Excel was used to find unique BINs from each site with specimens that had the smallest

randomly assigned number. This sample will be referred to as ‘Bra larger sample.’ These results

were then compared to the results from 19 random BINs for wing length and 16 random BINs

for hind tibia length from each site. The limiting factor for the smaller sample size, ‘Bra smaller

sample,’ was the lowest number of measurements, which was found in Belize.

Statistical analyses

The measurement data was tested on R V.3.1 (R Core Team, 2014) to see whether assumptions

were met for single factor ANOVA tests. Normality was tested by conducting a Shapiro-Wilk test

(Shapiro and Wilk 1965) and homoscedasticity was tested with a Levene’s test (Levene 1960).

The data failed to meet these assumptions, so non-parametric tests, Kruskal-Wallis tests, were

conducted for body size comparisons. Post-hoc tests (Tukey’s HSD test) were then conducted

for results that were significant (p<0.05).

Body size comparisons using phylogenetic comparative method (PCM)

Phylogenetic comparative methods allow us to make comparisons between species while

taking into account their evolutionary relationships (Felsenstein 1985). For both Ichneumonidae

and Braconidae specimens with body size measurements, sequence information from BOLD for

those specimens with unique BINs per location was used to create Maximum Likelihood (ML)

42

trees (Felsenstein 1981) rooted with outgroups on MEGA V.6 (Tamura, Stecher et al. 2013). The

GTR+G+I model (Nei and Kumar 2000) was used to build the trees with all codon positions.

The PDAP package (Midford 2010) in Mesquite V.2.75 (Maddison 2011) was used to compare

average wing length and hind tibia length for unique BINs per location of both parasitoid

families with ML trees that had non-collapsed and collapsed branches (accounting for

polytomies). To collapse branches, branch lengths of zero were treated as polytomies, and then

all branch lengths were set to one. One degree of freedom was also subtracted for each

polytomy.

RESULTS

Linear regressions

Larger sample

For Ich larger sample, the comparison of wing lengths showed Wilberforce was larger than

Guelph and Churchill, supporting a mid-latitudinal peak in size (H=22.58, df=6, p<0.05) (Figure

3.2A). However, the comparison of hind tibia lengths expressed a converse-Bergmann cline,

where specimens from French Guiana were larger than Algonquin, Guelph, Haldimond,

Wilberforce and Churchill, and specimens from Wilberforce were larger than specimens from

Guelph and Churchill (H=30.90, df=6, p<0.05) (Figure 3.2C).

For Bra larger sample, the comparison of wing lengths supported a converse-Bergmann cline,

because specimens from French Guiana were larger than specimens from the rest of the

collection sites (H=36.67, df=6, p<0.05) (Figure 3.2B). The comparison of hind tibia lengths also

exhibited a linear decline with latitude, where once again specimens from French Guiana were

larger than specimens from all other collection sites (H=49.96, df=6, p<0.05) (Figure 3.2D).

Smaller sample

For Ich smaller sample, the comparison of wing lengths did not exhibit any significant trend

with latitude (H=7.51, df=6, p>0.05) (Figure 3.3A). However, the comparison of hind tibia

lengths exhibited a linear decline with latitude, where specimens from French Guiana were

larger than Algonquin, Guelph, Haldimond, Wilberforce and Churchill (H=13.07, df=6, p<0.05)

(Figure 3.3C).

For Bra smaller sample, the comparison of wing lengths exhibited a linear decline with latitude,

where specimens from French Guiana were larger than specimens from Churchill (H=13.86,

df=6, p<0.05) (Figure 3.3B). The comparison of hind tibia lengths also exhibited a linear decline

43

with latitude (H=17.04, df=6, p<0.05), where specimens from French Guiana were larger than

specimens from Belize, Haldimond and Churchill (Figure 3.3D).

Overall larger and smaller samples of Ichneumonidae and Braconidae exhibited very similar

latitudinal trends, and hind tibia length comparisons exhibited stronger trends than wing length

(Figure 3.2, 3.3). These results do not support the Bergmann’s rule and instead show support

for the converse-Bergmann cline.

PCM

Ichneumonidae

For Ichneumonidae, wing length exhibited a linear incline with latitude for trees with non-

collapsed branches (R2=0.112, p=0.034), though no significant relationship was seen for

collapsed branches (R2=0.049, p>0.05) (Figure 3.4A; Table 3.2). Comparisons of hind tibia length

exhibited a linear decline with latitude for collapsed (R2=0.111, p=0.021) (Figure 3.4B) and non-

collapsed branched trees (R2=0.193, p=2.78E-4).

Braconidae

For Braconidae, wing length did not exhibit any trend with latitude for trees with collapsed

(R2=0.052, p>0.05) (Figure 3.5A) or non-collapsed branches (R2=0.0179, p>0.05) (Table 3.2). The

comparisons for hind tibia length exhibited linear declines with latitude for both trees that had

collapsed (R2=0.153, p=0.002) (Figure 3.5B) and non-collapsed branches (R2=0.132, p=0.013).

Therefore hind tibia length comparisons show support for the converse-Bergmann cline, while

wing length comparisons display no significant trend.

DISCUSSION

Previous studies investigating Hymenoptera body size across latitude have shown support for

the Bergmann’s cline, converse-Bergmann cline and no cline (Shelomi 2012). Similar to the

Ichneumonidae and Braconidae body size analyses by Santos and Quicke (2011), my results also

exhibited converse-Bergmann clines – hind tibia lengths declined with increasing latitude. Hind

tibia length comparisons were stronger than wing length comparisons, and the converse-

Bergmann trend was more apparent for Ichneumonidae than Braconidae species.

Support for the converse-Bergmann cline

To compare Ichneumonidae and Braconidae body size, unique species from each sampling site

were selected for the linear regressions and the phylogenetic comparative method. It was

interesting to analyze body size in two different ways because linear regressions treated each

species from a site as a unique sample, while PCM integrated the phylogenetic relationships of

44

the species from a ML tree. Therefore the PCM results would help indicate whether a smaller

sized genus at certain sampling sites was skewing the results. Both methods of analyses

supported the converse-Bergmann cline, because hind tibia lengths of unique species per site

decreased with increasing latitude.

Shelomi (2012) found that the absence of a body size cline was most prevalent in interspecific

species and Hymenoptera studies, followed by Bergmann’s cline and finally converse-Bergmann

clines. While a Bergmann’s cline is the product of a temperature effect, the converse-Bermann

cline is thought to be the product of a seasonal length effect and countergradient variation

(Blanckenhorn 2004). My sampling sites exhibit increases in seasonality (greater variation in

temperature and precipitation) with latitude; thus, these results show strong support for the

converse-Bergmann.

My results also demonstrate the Allen’s rule – shorter appendages (hind tibia length) were

found in colder climates. However the heat conservation mechanism behind Allen’s rule where

the growth of cartilage is dependent on temperature (Serrat, King et al. 2008) cannot be

applied to insects. Therefore, genetics and genotype-environmental interactions may be the

best explanation so far as to why this trend appears in ectotherms (Alho, Herczeg et al. 2011).

Other trends

Though the majority of my results exhibited converse-Bergmann clines, there were a few

notable exceptions involving wing length comparisons. Linear regressions involving

Ichneumonidae wing length supported a mid-latitudinal peak in size for the larger sample, and

no significant trend for the smaller sample. For the PCM method involving non-collapsed

branches, Ichneumonidae wing length exhibited a slight linear increase with latitude. PDAP

results for the rest of the wing length analyses for Ichneumonidae and Braconidae did not

exhibit any trends that were significant.

It is unclear as to why hind tibia length consistently supported the converse-Bergmann cline

while wing length of the same specimen did not. There have been other cases of inconsistent

body size patterns within the same populations (Krasnov, Ward et al. 1996; Jang, Won et al.

2009), and Shelomi (2012) has suggested that the type of organ used for measurements is of

great importance, because certain body parts might vary with latitude while others do not.

Limitations

Once again my results were based on previously collected specimens from BOLD with varying

sample sizes and collection times across sampling sites. Therefore I restricted the number of

specimens from sites with greater samples to standardise sampling effort across latitude –

smaller sample. For example the number of Ichneumonidae specimens with photos available

from Churchill (798) was much greater than the number of specimens available from Belize

45

(21). From those specimens, some pictures were of poor quality (ex. blurry images, missing

scale bars) and were not used for body size measurements. Thus the constrained sample size of

both sequences and photos may have affected my analyses, because less than 20 specimens

from a collection site is a very small number to be a true representation of the average body

size of all the species found at that site. However I still ran analyses on the larger sample with

varying sample sizes for both parasitoid wasp families, and both sample sizes (larger and

smaller) exhibited similar linear regression trends. These comparisons reinforced my results,

because regardless of sample size, the trends were the same.

Morrison (1979) and Janzen (1981) have indicated that perhaps the tropics are composed of a

greater abundance of parasitoid species specialized in attacking eggs. Consequently these egg

parasitoids “should be small in size to allow development within the host egg” (pg. 305,

Morrison 1979). Malaise traps are assumed to be adequate tools for collecting flying

Hymenoptera of all sizes, yet Morrison (1979) has suggested that perhaps Malaise traps are

biased against smaller parasitoids unable to be caught within the mesh or strong enough to

travel up to the collection bottle. Therefore traps, such as pan traps or shorter Malaise traps,

designed to collect smaller parasitoids found near the ground should be incorporated into

sampling protocols (Morrison 1979).

Temporal variation during sampling could have also influenced body size analyses, as well as

human error while taking measurements from images. I believe that advanced imaging

techniques now capable of taking 3D images of specimens would provide us with more

accurate measurements than 2D images.

My analyses also did not take into account the sex of the specimens. Therefore sexual

dimorphism within species may have affected my results, because Rensch’s rule (Rensche 1943)

states male body size tends to vary more than female body size within a species. Shelomi (2012)

has suggested that male body size is therefore more likely to show statistically significant clines,

meaning my results may be more or less significant depending on the ratio of male to female

specimens that were measured.

Also, during the PCM analyses, there were occurrences of polytomies at the genera and species

level. Polytomies are a potential problem, because the evolutionary relationships of the

parasitoid wasps were not fully resolved with the currently available data. One solution to

polytomies in a PCM is to assume equal branch length among closely related taxa (collapsed

branches). Since branch length information is necessary for PDAP analyses, this reduced the

variation in my results. I did however run separate PDAP analyses for trees with collapsed and

non-collapsed branches, and they both showed similar trends. Previous literature has also

indicated that there was no significant difference in the ability to detect correlations between

46

PD and ecological patterns across species with a fully resolved molecular phylogeny and a tree

containing polytomies (Cadotte, Jonathan Davies et al. 2010).

The significance of this study

Avoiding geographic and taxonomic sampling biases, while designing experiments to address

macroecological trends, is an overwhelmingly difficult task. Meta-analyses that use previous

literature to address body size trends present some general conclusions, however it is

important to note that many of these studies had specific focal points with inconsistent

experimental designs. Studies such as mine that rely on specimens processed in a standardized

method with DNA barcodes available from BOLD is a very important step forward in avoiding

taxonomic biases, because DNA barcoding can account for cryptic species. Large

specimen/sequence databases, such as BOLD that incorporate genetic, morphological and

ecological data are crucial for studies hoping to investigate macroecological patterns, because

data can be filtered and analysed at a greater speed.

Conclusions

Hind tibia lengths of Ichneumonidae and Braconidae species declined across latitude supporting

the converse-Bergmann rule and Allen’s rule, while many of the wing length analyses did not

exhibit consistent patterns. Larger and smaller sample sizes of both parasitoid wasp families

exhibited the same trends, meaning sample size did not greatly impact my results. However,

these conclusions are based on the assumption that methods utilized to collect specimens (i.e.

Malaise traps) across latitude were adequate to catch flying Hymenoptera of all sizes. Greater

sampling is still required to generalize these patterns.

47

CHAPTER 3 TABLES

Table 3.1. The number of specimens from the families Ichneumonidae and Braconidae that

were used for body size measurements and comparisons. From specimens with photos, subsets

of randomly chosen individuals were measured – see methods. Then from the specimens that

were measured, unique BINs per location were selected. The larger and smaller sample sizes

represent how many species were present per site for comparison.

Ichneumonidae Braconidae

Wing length Hind tibia length Wing length Hind tibia length

Collection site

# of species

in larger

sample size

# of species

in smaller sample

size

# of species

in larger

sample size

# of species

in smaller sample

size

# of species

in larger

sample size

# of species

in smaller sample

size

# of species

in larger

sample size

# of species

in smaller sample

size

French Guiana

48 15 54 16 107 19 94 16

Belize 15 15 16 16 19 19 16 16

Haldimond 51 15 51 16 34 19 30 16

Guelph 75 15 75 16 72 19 70 16

Wilberforce 65 15 63 16 54 19 46 16

Algonquin 34 15 44 16 25 19 27 16

Churchill 116 15 113 16 77 19 79 16

48

Table 3.2. PDAP results for the comparison of wing length and hind tibia length for

Ichneumonidae and Braconidae species across latitude.

Ichneumonidae Braconidae

Non-collapsed

branches Collapsed branches

Non-collapsed branches

Collapsed branches

Wing

length

Hind tibia

length

Wing length

Hind tibia

length

Wing length

Hind tibia

length

Wing length

Hind tibia

length

# of contrasts 353 354 429 432 373 357 429 409

Pearson Product-Moment Correlation Coefficient

0.113 0.193 0.049 0.111 0.018 0.132 0.052 0.154

Two tailed p-value

0.034 2.78E-

04 0.307 0.021 0.729 0.013 0.281 0.002

49

CHAPTER 3 FIGURES

Figure 3.1. Possible mechanisms for varying body sizes with latitude (adapted from Shelomi,

2012).

50


length + standard error (SE)) for the larger sample sizes across latitude. A) Ichneumonidae wing

length exhibited a linear decline with latitude (H=22.58, df=6, p=0.012). Specimens from

Wilberforce were larger than Guelph and Churchill. B) Braconidae wing length exhibited a linear

decline with latitude (H=36.67, df=6, p=4.11E-09). Specimens from French Guiana were larger

than specimens from the rest of the collection sites. C) Ichneumonidae hind tibia length

exhibited a linear decline with latitude (H=30.90, df=6, p=2.06E-06), where specimens from

French Guiana were larger than Algonquin, Guelph, Haldimond, Wilberforce and Churchill and

specimens from Wilberforce were larger than specimens from Guelph and Churchill. D)

Braconidae hind tibia length exhibited a linear decline with latitude (H=49.96, df=6, p=1.58E-

11), where specimens from French Guiana were larger than specimens from all other collection

sites

51


length +SE) for the smaller sample sizes across latitude. A) Ichneumonidae wing length did not

exhibit any significant trend with latitude (H=7.51, df=6, p=0.112). B) Braconidae wing length

exhibited a linear decline with latitude (H=13.86, df=6, p=0.025), where specimens from French

Guiana were larger than specimens from Churchill. C) Ichneumonidae hind tibia length

exhibited a linear decline with latitude (H=13.07, df=6, p=6.23E-04), where specimens from

French Guiana were larger than specimens from Algonquin, Guelph, Haldimond, Wilberforce

and Churchill. D) Braconidae hind tibia length exhibited a linear decline with latitude (H=17.04,

df=6, p=0.004), where specimens from French Guiana were larger than specimens from Belize,

Haldimond and Churchill.

52

Figure 3.4. PDAP results for Ichneumonidae body size across latitude for trees with collapsed

branches. Black regression lines through origin represents ordinary least squares. Green is a

major axis and red is a reduced major axis. A) Wing length exhibited a statistically non-

significant linear incline with latitude (R2=0.049, p0.307). B) Hind tibia length exhibited a linear

decline with latitude (R2=0.111, p=0.021).

53

Figure 3.5. PDAP results for Braconidae body size across latitude for trees with collapsed

branches. Black regression lines through origin represents ordinary least squares. Green is a

major axis and red is a reduced major axis. A) Wing length exhibited a statistically non-

significant linear decline with latitude (R2=0.052, p=0.281). B) Hind tibia length exhibited a

linear decline with latitude (R2=0.154, p>0.002).

54

CHAPTER 4: SUMMARY; BROADER SIGNIFICANCE AND FUTURE DIRECTIONS

Co-evolution – regarded as reciprocal evolution between interacting species (ex. parasitoids

and their hosts) – has the ability to shift populations toward adaptive change and prevent other

populations from doing so (Thompson 2012). With continuously changing climatic conditions, it

is becoming increasingly urgent to correctly identify unknown species of animals and host and

parasitoid relationships that may be very influential in ecosystem stability. Parasitoids in

particular are major predators of herbivorous insects and are frequently used as agents of

biological control (Gaston 2000). How large of a role they play in maintaining community

stability in terms of food web structure and dynamics has been estimated frequently (Eveleigh,

McCann et al. 2007), but remains a complex task due to gaps in parasitoid species identification

(Smith, Rodriguez et al. 2008).

We currently have access to platforms of integrative taxonomy involving morphological,

genomic and ecological data. Specimen databases such as BOLD which rely on DNA barcodes to

delineate species can expedite the process of species discovery and identification, with

collaborative efforts from multiple researchers. Therefore, specimen references libraries

(BOLD) are going to be vital for future studies investigating macroecological trends. With the

currently available data on BOLD, I explored the effects of latitude on the diversity and body

size of parasitoid wasps.

One of the main reasons I chose to study parasitoid wasps was because Ichneumonidae

diversity has been presented as an example of anomalous diversity (Owen and Owen 1974;

Janzen 1981; Skillen, Pickering et al. 2000). Since recent literature involving the use of DNA

barcoding had suggested that greater parasitoid diversity exists in the tropics than was thought

in the past (Smith, Wood et al. 2007; Smith, Rodriguez et al. 2008), I wanted to see whether

enumerating diversity with BINs and PD would still support a mid-latitude peak. Therefore my

first study examined specimens collected from ~4.088 - 58.676°N, and my results indicated that

the number of BINs was consistent across latitude, though their PD decreased with latitude.

However most results were not statistically significant. Greater levels of relatedness amongst

BINs at higher latitudes (Churchill) are believed to be driven by shared physiological tolerances

to low levels of precipitation and/or the effects of glaciation.

Along with diversity, body size trends remain poorly understood for parasitoid wasps.

Ectotherms have been observed to follow Bergmann’s rule (Bergmann 1847; Mayr 1956)–

larger organisms are found at higher latitudes, as well as contradict it and show no clines

(Shelomi 2012). Quicke (2012) reported that Ichneumonidae and Braconidae body size peaked

at temperate regions, so for my second study I wanted to investigate whether these patterns

held true for my dataset. By utilizing specimen images available from BOLD, I measured hind

55

tibia and wing length across the same latitudinal gradient as my diversity analyses. The results

from linear regressions and phylogenetic comparative methods indicated that Ichneumonidae

and Braconidae species exhibit converse-Bergmann clines – decrease in body size (hind tibia

length) across latitude. Wing length comparisons of the same specimens did not exhibit any

clear trends. Hind tibia length measurements also showed support for Allen’s rule.

For both these studies, one of the biggest limitations I faced was unequal sampling effort

(spatial, temporal, collection method) across latitude from the specimens available on BOLD. To

standardize the sampling effort I restricted the number of specimens from sites with higher

numbers to that of the site with the lowest available specimens (Belize). In the end restricting

my sample size may have given rise to false trends, because 280 randomly selected specimens

from each collection site is too small of a number for estimating species richness. Especially

because macroecological studies involving parasitic Hymenoptera are greatly hindered by the

taxonomic impediment and the number of Ichneumonidae species alone is estimated to be

over 60,000 species (Skillen, Pickering et al. 2000; Huber 2009; Jones, Purvis et al. 2009)

Overall the results from my two studies should be treated as stepping stones for future

research investigating macroecological trends of parasitoid wasps. As the BOLD database

expands its collection of specimens/species, researchers can mimic my methodology to retrieve

more accurate results and also investigate specific trends exhibited by different families/species

of parasitoids. It should also be of interest to researchers to thoroughly sample specimens from

specific locations, instead of spreading thin over larger regions. Tropical regions in particular

need greater sampling effort to enumerate diversity.

56

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Willig, M. R., D. M. Kaufman, et al. (2003). "Latitudinal gradients of biodiversity: pattern, process, scale, and synthesis." Annual Review of Ecology, Evolution, and Systematics 34(1): 273-309.

63

APPENDIX 1: Chapter 2 - All specimen information (4785). Complete collection information,

photographs, DNA sequences and trace files discussed can all be retrieved on BOLD

(http://dx.doi.org/10.5883/DS-TIEPARIS).

Process ID BIN Site Latitude Longitude Collection Date

ASAHY202-13 BOLD:AAI5894 Algonquin

Park 46.058 -78.484 12-Jul-2011

ASAHY224-13 BOLD:AAG7687 Algonquin

Park 45.718 -77.81 13-Jul-2011


Park 45.718 -77.81 13-Jul-2011

ASAHY226-13 BOLD:ACC8058 Algonquin

Park 45.521 -78.429 13-Jul-2011


Park 45.521 -78.429 13-Jul-2011

ASAHY229-13 BOLD:AAU9025 Algonquin

Park 45.521 -78.429 13-Jul-2011


Park 45.897 -77.735 11-Jul-2011


Park 45.897 -77.735 11-Jul-2011


Park 45.897 -77.735 11-Jul-2011

ASAHY235-13 BOLD:AAM7454 Algonquin

Park 45.897 -77.735 11-Jul-2011

ASAHY236-13 BOLD:ABY5242 Algonquin

Park 45.897 -77.735 11-Jul-2011


Park 45.897 -77.735 11-Jul-2011


Park 45.524 -78.422 08-Jul-2011


Park 45.524 -78.422 08-Jul-2011


Park 45.524 -78.422 08-Jul-2011


Park 45.524 -78.422 08-Jul-2011


Park 46.099 -78.431 06-Jul-2011


Park 46.099 -78.431 06-Jul-2011


Park 46.099 -78.431 06-Jul-2011


Park 46.099 -78.431 06-Jul-2011

ASAHY246-13 BOLD:ABY4229 Algonquin 46.099 -78.431 06-Jul-2011

http://dx.doi.org/10.5883/DS-TIEPARIS

64

Park


Park 46.099 -78.431 06-Jul-2011


Park 46.099 -78.431 06-Jul-2011


Park 46.099 -78.431 06-Jul-2011


Park 46.099 -78.431 06-Jul-2011

ASAHY251-13 BOLD:ABX2607 Algonquin

Park 46.099 -78.431 06-Jul-2011


Park 45.521 -78.429 08-Jul-2011


Park 45.521 -78.429 08-Jul-2011


Park 45.521 -78.429 08-Jul-2011


Park 45.521 -78.429 08-Jul-2011


Park 45.897 -77.735 05-Jul-2011


Park 45.897 -77.735 05-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011

ASAHY264-13 BOLD:AAD5193 Algonquin

Park 46.058 -78.484 12-Jul-2011

ASAHY266-13 BOLD:AAQ2724 Algonquin

Park 46.058 -78.484 12-Jul-2011

ASAHY267-13 BOLD:ACE4814 Algonquin

Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011

65

ASAHY274-13 BOLD:ABV4136 Algonquin

Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011

ASAHY288-13 BOLD:ACB2170 Algonquin

Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011

ASAHY290-13 BOLD:AAC3876 Algonquin

Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011

ASAHY294-13 BOLD:AAB0192 Algonquin

Park 46.058 -78.484 12-Jul-2011

ASAHY295-13 BOLD:AAF0483 Algonquin

Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011

ASAHY300-13 BOLD:ACC7198 Algonquin 46.058 -78.484 12-Jul-2011

66

Park


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011

ASAHY321-13 BOLD:AAY6820 Algonquin

Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011

ASAHY332-13 BOLD:AAJ5372 Algonquin

Park 46.058 -78.484 12-Jul-2011

ASAHY334-13 BOLD:ABW2905 Algonquin

Park 46.058 -78.484 12-Jul-2011

ASAHY335-13 BOLD:ACA9231 Algonquin

Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011

ASAHY341-13 BOLD:AAN7578 Algonquin

Park 46.058 -78.484 12-Jul-2011

67


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011

ASAHY352-13 BOLD:ACL6033 Algonquin

Park 46.058 -78.484 12-Jul-2011

ASAHY353-13 BOLD:ABA6048 Algonquin

Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 45.76 -77.89 13-Jul-2011


Park 45.76 -77.89 13-Jul-2011


Park 45.76 -77.89 13-Jul-2011


Park 45.76 -77.89 13-Jul-2011


Park 45.76 -77.89 13-Jul-2011


Park 45.76 -77.89 13-Jul-2011


Park 45.76 -77.89 13-Jul-2011


Park 45.76 -77.89 13-Jul-2011


Park 45.76 -77.89 13-Jul-2011

ASAHY390-13 BOLD:ACE3159 Algonquin 45.76 -77.89 13-Jul-2011

68

Park


Park 45.76 -77.89 13-Jul-2011


Park 45.76 -77.89 13-Jul-2011


Park 45.76 -77.89 13-Jul-2011


Park 45.76 -77.89 13-Jul-2011


Park 45.76 -77.89 13-Jul-2011


Park 45.76 -77.89 13-Jul-2011

ASAHY400-13 BOLD:AAH3192 Algonquin

Park 45.523 -78.422 13-Jul-2011


Park 45.523 -78.422 13-Jul-2011


Park 45.523 -78.422 13-Jul-2011


Park 45.46 -78.796 09-Jul-2011


Park 45.897 -77.735 11-Jul-2011


Park 46.058 -78.484 12-Jul-2011

ASAHY414-13 BOLD:ACG2361 Algonquin

Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 46.058 -78.484 12-Jul-2011


Park 45.897 -77.735 11-Jul-2011


Park 45.897 -77.735 11-Jul-2011


Park 45.897 -77.735 11-Jul-2011


Park 45.521 -78.429 13-Jul-2011


Park 45.523 -78.422 13-Jul-2011

ASAHY432-13 BOLD:AAK2038 Algonquin

Park 46.058 -78.484 12-Jul-2011

69


Park 46.058 -78.484 12-Jul-2011


Park 45.521 -78.429 13-Jul-2011


Park 45.521 -78.429 13-Jul-2011


Park 45.521 -78.429 13-Jul-2011


Park 45.897 -77.735 11-Jul-2011


Park 45.46 -78.796 09-Jul-2011


Park 45.521 -78.429 13-Jul-2011


Park 45.897 -77.735 11-Jul-2011


Park 45.897 -77.735 11-Jul-2011


Park 45.897 -77.735 11-Jul-2011


Park 45.897 -77.735 11-Jul-2011


Park 45.897 -77.735 11-Jul-2011


Park 45.897 -77.735 11-Jul-2011


Park 45.897 -77.735 11-Jul-2011


Park 45.76 -77.89 13-Jul-2011


Park 45.76 -77.89 13-Jul-2011


Park 45.76 -77.89 13-Jul-2011


Park 45.76 -77.89 13-Jul-2011


Park 45.76 -77.89 13-Jul-2011


Park 45.897 -77.735 11-Jul-2011


Park 45.523 -78.422 13-Jul-2011


Park 45.523 -78.422 13-Jul-2011


Park 46.058 -78.484 12-Jul-2011

ASAHY469-13 BOLD:AAG7687 Algonquin 45.897 -77.735 11-Jul-2011

70

Park


Park 45.897 -77.735 11-Jul-2011


Park 45.897 -77.735 11-Jul-2011


Park 45.897 -77.735 11-Jul-2011

ASAHY473-13 BOLD:ACH0655 Algonquin

Park 45.897 -77.735 11-Jul-2011


Park 45.897 -77.735 11-Jul-2011


Park 45.46 -78.796 09-Jul-2011


Park 45.46 -78.796 09-Jul-2011


Park 45.46 -78.796 09-Jul-2011


Park 45.46 -78.796 09-Jul-2011


Park 45.46 -78.796 09-Jul-2011

ASAHY483-13 BOLD:AAA7886 Algonquin

Park 45.46 -78.796 09-Jul-2011


Park 45.46 -78.796 09-Jul-2011


Park 45.46 -78.796 09-Jul-2011


Park 45.46 -78.796 09-Jul-2011

ASAHY496-13 BOLD:ACD1925 Algonquin

Park 45.897 -77.735 05-Jul-2011


Park 45.897 -77.735 05-Jul-2011


Park 45.897 -77.735 11-Jul-2011


Park 45.897 -77.735 11-Jul-2011


Park 45.897 -77.735 11-Jul-2011


Park 45.897 -77.735 05-Jul-2011

ASAHY504-13 BOLD:AAZ3271 Algonquin

Park 45.897 -77.735 05-Jul-2011


Park 45.718 -77.81 13-Jul-2011


Park 45.718 -77.81 13-Jul-2011

71

ASAHY510-13 BOLD:ABZ5626 Algonquin

Park 45.718 -77.81 13-Jul-2011


Park 45.718 -77.81 13-Jul-2011


Park 45.718 -77.81 13-Jul-2011


Park 45.718 -77.81 13-Jul-2011


Park 45.718 -77.81 13-Jul-2011


Park 46.099 -78.431 06-Jul-2011


Park 45.76 -77.89 07-Jul-2011


Park 45.76 -77.89 07-Jul-2011


Park 46.099 -78.431 12-Jul-2011


Park 46.058 -78.484 06-Jul-2011


Park 45.521 -78.429 08-Jul-2011


Park 45.521 -78.429 08-Jul-2011


Park 45.521 -78.429 08-Jul-2011


Park 45.521 -78.429 08-Jul-2011


Park 45.521 -78.429 07-Jul-2011


Park 45.521 -78.429 07-Jul-2011


Park 45.521 -78.429 08-Jul-2011


Park 45.521 -78.429 13-Jul-2011


Park 45.524 -78.422 13-Jul-2011


Park 45.524 -78.422 08-Jul-2011


Park 45.524 -78.422 13-Jul-2011


Park 45.633 -77.07 08-Aug-2011


Park 45.633 -77.07 08-Aug-2011

ASAHY545-13 BOLD:ACE9710 Algonquin 45.633 -77.07 08-Aug-2011

72

Park


Park 45.633 -77.07 08-Aug-2011


Park 45.633 -77.07 08-Aug-2011


Park 45.633 -77.07 08-Aug-2011


Park 45.633 -77.07 08-Aug-2011


Park 45.633 -77.07 08-Aug-2011


Park 45.633 -77.07 08-Aug-2011


Park 45.633 -77.07 08-Aug-2011


Park 45.633 -77.07 08-Aug-2011


Park 45.633 -77.07 08-Aug-2011


Park 45.633 -77.07 08-Aug-2011


Park 45.633 -77.07 08-Aug-2011


Park 45.633 -77.07 08-Aug-2011


Park 45.633 -77.07 29-May-2011


Park 45.633 -77.07 29-May-2011


Park 45.633 -77.07 29-May-2011


Park 45.633 -77.07 29-May-2011


Park 45.633 -77.07 29-May-2011


Park 45.633 -77.07 29-May-2011


Park 45.633 -77.07 01-May-2011


Park 45.633 -77.07 01-May-2011


Park 45.633 -77.07 01-May-2011


Park 45.6334 -77.6182 26-Nov-2012


Park 45.6334 -77.6182 26-Nov-2012

73


Park 45.6334 -77.6182 26-Nov-2012


Park 45.6334 -77.6182 26-Nov-2012


Park 45.6334 -77.6182 26-Nov-2012


Park 45.6334 -77.6182 26-Nov-2012


Park 45.6334 -77.6182 26-Nov-2012


Park 45.5239 -78.4205 20-Jul-2012


Park 45.5222 -78.4302 20-Jul-2012


Park 45.5222 -78.4302 20-Jul-2012


Park 45.5222 -78.4302 20-Jul-2012


Park 45.5222 -78.4302 20-Jul-2012


Park 45.5222 -78.4302 20-Jul-2012


Park 45.6334 -77.0697 08-Apr-2012


Park 45.6334 -77.0697 08-Apr-2012


Park 45.6334 -77.0697 08-Apr-2012


Park 45.6334 -77.0697 08-Apr-2012


Park 45.6334 -77.0697 08-Apr-2012


Park 45.6334 -77.0697 08-Apr-2012


Park 45.6334 -77.0697 08-Apr-2012


Park 45.6334 -77.0697 08-Apr-2012


Park 45.6334 -77.0697 08-Apr-2012


Park 45.6334 -77.0697 08-Apr-2012


Park 45.6334 -77.0697 08-Apr-2012


Park 45.6334 -77.0697 08-Apr-2012

ASAHY601-13 BOLD:AAG7661 Algonquin 45.6334 -77.0697 08-Apr-2012

74

Park


Park 45.6334 -77.0697 08-Apr-2012


Park 45.6334 -77.0697 08-Apr-2012


Park 45.6334 -77.0697 08-Apr-2012


Park 45.6334 -77.0697 08-Apr-2012


Park 45.5235 -78.4209 20-Jul-2012


Park 45.6334 -77.0697 24-Sep-2012


Park 45.6334 -77.0697 24-Sep-2012


Park 45.6334 -77.0697 24-Sep-2012


Park 45.6334 -77.0697 24-Sep-2012


Park 45.6334 -77.0697 24-Sep-2012


Park 45.5222 -78.4302 25-Jul-2012


Park 45.8946 -77.7303 17-Jul-2012


Park 45.8946 -77.7303 18-Jul-2012


Park 45.8946 -77.7303 18-Jul-2012


Park 45.6334 -77.6182 08-Apr-2012


Park 45.6334 -77.6182 08-Apr-2012


Park 45.6334 -77.6182 08-Apr-2012


Park 45.6334 -77.6182 08-Apr-2012

ASAHY623-13 BOLD:AAK3185 Algonquin

Park 45.6334 -77.6182 08-Apr-2012


Park 45.6334 -77.6182 08-Apr-2012

ASAHY626-13 BOLD:AAW9549 Algonquin

Park 45.6334 -77.6182 08-Apr-2012


Park 45.6334 -77.6182 08-Apr-2012


Park 46.0578 -78.4844 17-Jul-2012

75


Park 45.8946 -77.7303 17-Jul-2012

ASAHY630-13 BOLD:ACI8670 Algonquin

Park 45.8946 -77.7303 17-Jul-2012


Park 45.8948 -77.7309 18-Jul-2012


Park 45.8948 -77.7309 18-Jul-2012


Park 45.8948 -77.7309 18-Jul-2012


Park 45.8945 -77.7353 18-Jul-2012


Park 45.8945 -77.7353 18-Jul-2012


Park 45.7603 -77.8887 19-Jul-2012


Park 45.8946 -77.7307 01-Aug-2012


Park 45.7182 -77.811 19-Jul-2012


Park 45.8948 -77.7309 18-Jul-2012


Park 45.7604 -77.8893 19-Jul-2012


Park 45.7604 -77.8893 19-Jul-2012


Park 45.8948 -77.7309 18-Jul-2012


Park 45.5235 -78.4209 25-Jul-2012


Park 45.8946 -77.7307 18-Jul-2012


Park 45.4599 -78.7964 25-Jul-2012

ASAHY648-13 BOLD:ACF1442 Algonquin

Park 45.7182 -77.811 19-Jul-2012


Park 45.5222 -78.4299 20-Jul-2012


Park 45.5218 -78.4293 12-Jun-2012


Park 45.5235 -78.4209 12-Jun-2012


Park 45.7181 -77.8106 11-Jun-2012


Park 45.7181 -77.8106 11-Jun-2012

ASAHY654-13 BOLD:AAV6248 Algonquin 45.8948 -77.7309 03-Jun-2012

76

Park


Park 45.8948 -77.7309 03-Jun-2012


Park 45.5235 -78.4209 20-Jul-2012


Park 45.5235 -78.4209 05-Jun-2012


Park 45.5235 -78.4209 05-Jun-2012


Park 45.5235 -78.4209 05-Jun-2012


Park 45.5235 -78.4209 05-Jun-2012


Park 45.5235 -78.4209 05-Jun-2012


Park 45.7604 -77.8891 11-Jun-2012


Park 45.4596 -78.7962 08-Jun-2012


Park 45.4596 -78.7962 08-Jun-2012


Park 45.4596 -78.7962 08-Jun-2012


Park 45.8946 -77.7307 10-Jun-2012


Park 45.8946 -77.7303 10-Jun-2012


Park 45.5222 -78.4299 12-Jun-2012


Park 45.8946 -77.7307 03-Jun-2012


Park 45.8946 -77.7307 03-Jun-2012


Park 45.4596 -78.7962 08-Jun-2012


Park 45.4594 -78.7959 08-Jun-2012


Park 46.0578 -78.4844 09-Jun-2012


Park 46.0578 -78.4844 09-Jun-2012

ASAHY676-13 BOLD:AAW5216 Algonquin

Park 45.5222 -78.4299 05-Jun-2012


Park 45.5222 -78.4299 05-Jun-2012


Park 45.8946 -77.7307 10-Jun-2012

77


Park 45.5235 -78.421 12-Jun-2012


Park 45.5239 -78.4205 12-Jun-2012


Park 45.4596 -78.7962 08-Jun-2012


Park 45.8945 -77.7353 10-Jun-2012


Park 45.4602 -78.7968 22-Jul-2012


Park 45.8946 -77.7307 03-Jun-2012


Park 45.8948 -77.7309 10-Jun-2012


Park 45.46 -78.7965 08-Jun-2012


Park 46.058 -78.4846 23-Jul-2012


Park 45.5235 -78.4209 25-Jul-2012


Park 45.5239 -78.4205 05-Jun-2012


Park 45.7181 -77.8106 04-Jun-2012


Park 45.6334 -77.0697 19-Aug-2012


Park 45.6334 -77.0697 19-Aug-2012


Park 45.6334 -77.0697 19-Aug-2012


Park 45.6334 -77.0697 19-Aug-2012


Park 45.6334 -77.0697 19-Aug-2012


Park 45.6324 -77.0618 09-Oct-2012


Park 45.6324 -77.0618 09-Oct-2012


Park 45.4602 -78.7968 22-Jul-2012


Park 45.4601 -78.7966 22-Jul-2012


Park 45.4601 -78.7966 22-Jul-2012


Park 45.8944 -77.7348 10-Jun-2012

ASAHY721-13 BOLD:AAU8756 Algonquin 46.0992 -78.4312 09-Jun-2012

78

Park


Park 46.0992 -78.4311 02-Jun-2012


Park 46.0992 -78.4311 02-Jun-2012


Park 45.7182 -77.8109 11-Jun-2012


Park 45.5222 -78.4299 05-Jun-2012


Park 45.5218 -78.4293 05-Jun-2012


Park 46.058 -78.4846 02-Jun-2012


Park 46.058 -78.4846 02-Jun-2012


Park 46.058 -78.4846 02-Jun-2012


Park 45.5235 -78.421 05-Jun-2012


Park 45.5235 -78.421 05-Jun-2012


Park 46.0578 -78.4844 02-Jun-2012


Park 46.058 -78.4846 02-Jun-2012


Park 45.7604 -77.8891 04-Jun-2012


Park 46.0991 -78.4315 02-Jun-2012


Park 46.058 -78.4846 09-Jun-2012


Park 45.4598 -78.7964 08-Jun-2012


Park 45.4598 -78.7964 08-Jun-2012


Park 45.5218 -78.4293 12-Jun-2012


Park 46.0992 -78.4312 16-Jul-2012


Park 46.0991 -78.4315 16-Jul-2012


Park 45.4601 -78.7966 08-Jun-2012


Park 46.0993 -78.4309 16-Jul-2012


Park 46.0992 -78.4312 16-Jul-2012

79


Park 45.4596 -78.7962 08-Jun-2012


Park 45.4601 -78.7967 08-Jul-2012


Park 45.8948 -77.7313 10-Jun-2012


Park 45.8945 -77.7353 03-Jun-2012


Park 45.7603 -77.8887 04-Jun-2012


Park 45.7604 -77.8891 04-Jun-2012


Park 45.7604 -77.8891 04-Jun-2012


Park 45.7603 -77.8887 24-Jul-2012


Park 45.7603 -77.8887 24-Jul-2012


Park 45.7603 -77.8887 24-Jul-2012

ASAHY763-13 BOLD:ACK5792 Algonquin

Park 46.099 -78.431 23-Jul-2012


Park 46.099 -78.431 23-Jul-2012


Park 46.099 -78.431 23-Jul-2012

ASAHY767-13 BOLD:ABV2820 Algonquin

Park 46.099 -78.431 17-Jul-2012


Park 46.099 -78.431 17-Jul-2012


Park 46.099 -78.431 02-Jun-2012


Park 46.058 -78.485 17-Jul-2012


Park 46.058 -78.484 09-Jun-2012


Park 45.895 -77.731 18-Jul-2012


Park 45.895 -77.731 03-Jun-2012


Park 45.894 -77.735 10-Jun-2012


Park 45.894 -77.735 10-Jun-2012


Park 45.894 -77.735 10-Jun-2012

ASAHY786-13 BOLD:AAU8213 Algonquin 45.895 -77.73 18-Jul-2012

80

Park

ASAHY788-13 BOLD:ACJ1208 Algonquin

Park 45.895 -77.73 18-Jul-2012


Park 45.894 -77.735 10-Jun-2012


Park 45.895 -77.731 03-Jun-2012


Park 45.522 -78.429 25-Jul-2012


Park 45.522 -78.43 20-Jul-2012


Park 45.522 -78.43 20-Jul-2012


Park 45.524 -78.421 20-Jul-2012


Park 45.524 -78.421 20-Jul-2012


Park 45.524 -78.421 20-Jul-2012


Park 45.524 -78.421 20-Jul-2012


Park 45.718 -77.811 11-Jun-2012


Park 45.718 -77.81 11-Jun-2012


Park 45.718 -77.811 11-Jun-2012


Park 45.718 -77.811 11-Jun-2012


Park 45.718 -77.811 11-Jun-2012


Park 45.76 -77.889 19-Jul-2012


Park 45.76 -77.889 11-Jun-2012


Park 45.76 -77.889 11-Jun-2012


Park 45.76 -77.889 11-Jun-2012


Park 45.46 -78.797 22-Jun-2012


Park 45.46 -78.797 22-Jun-2012


Park 45.46 -78.797 22-Jun-2012


Park 45.46 -78.797 22-Jun-2012

81


Park 45.46 -78.797 22-Jun-2012


Park 45.46 -78.796 22-Jun-2012


Park 45.46 -78.796 22-Jun-2012


Park 45.459 -78.796 22-Jul-2012


Park 46.099 -78.431 02-Jun-2012


Park 46.058 -78.484 23-Jul-2012


Park 46.058 -78.484 23-Jul-2012


Park 45.894 -77.735 10-Jun-2012


Park 45.894 -77.735 10-Jun-2012


Park 45.524 -78.421 20-Jul-2012


Park 45.718 -77.811 11-Jun-2012


Park 46.0992 -78.4311 09-Jun-2012


Park 46.0992 -78.4311 09-Jun-2012


Park 46.0992 -78.4311 09-Jun-2012


Park 46.0992 -78.4311 09-Jun-2012


Park 46.0992 -78.4311 09-Jun-2012


Park 45.8945 -77.7351 10-Jun-2012


Park 46.0578 -78.4844 09-Jun-2012


Park 45.8944 -77.7348 10-Jun-2012


Park 45.8945 -77.7351 01-Aug-2012


Park 45.8945 -77.7351 01-Aug-2012

ASAHY878-14 BOLD:ACJ9210 Algonquin

Park 45.8945 -77.7351 01-Aug-2012


Park 45.8945 -77.7351 01-Aug-2012

ASAHY881-14 BOLD:ACJ1208 Algonquin 45.8946 -77.7307 01-Aug-2012

82

Park


Park 45.8946 -77.7303 01-Aug-2012


Park 45.8948 -77.7309 01-Aug-2012


Park 45.8948 -77.7309 01-Aug-2012


Park 45.6334 -77.0697 09-Oct-2012


Park 45.6334 -77.0697 09-Oct-2012


Park 45.6334 -77.0697 09-Oct-2012


Park 45.6334 -77.0697 09-Oct-2012


Park 45.6334 -77.0697 09-Oct-2012


Park 45.6324 -77.0618 24-Oct-2012


Park 45.6324 -77.0618 24-Oct-2012


Park 45.6324 -77.0618 24-Oct-2012


Park 45.6324 -77.0618 24-Oct-2012


Park 45.6324 -77.0618 24-Oct-2012


Park 45.5218 -78.4293 05-Jun-2012


Park 45.5239 -78.4205 05-Jun-2012


Park 45.5235 -78.421 25-Jul-2012


Park 45.5238 -78.4206 12-Jun-2012


Park 45.5238 -78.4206 12-Jun-2012


Park 45.5238 -78.4206 12-Jun-2012


Park 45.5239 -78.4205 05-Jun-2012


Park 45.7181 -77.8106 11-Jun-2012


Park 45.7181 -77.8106 24-Jul-2012


Park 45.7181 -77.8106 24-Jul-2012

83


Park 45.7181 -77.8106 24-Jul-2012


Park 45.7181 -77.8106 24-Jul-2012


Park 45.7181 -77.8106 24-Jul-2012


Park 45.5238 -78.4206 12-Jun-2012


Park 45.7604 -77.8891 24-Jul-2012


Park 45.7604 -77.8891 24-Jul-2012


Park 45.7604 -77.8891 24-Jul-2012


Park 45.7604 -77.8891 24-Jul-2012


Park 45.7603 -77.8887 04-Jun-2012


Park 45.7603 -77.8887 04-Jun-2012


Park 45.4602 -78.7968 22-Jun-2012


Park 45.4602 -78.7968 22-Jun-2012


Park 45.4599 -78.7964 22-Jul-2012


Park 45.4599 -78.7964 22-Jul-2012


Park 45.4602 -78.7968 08-Jun-2012


Park 45.4599 -78.7964 08-Jun-2012


Park 45.4598 -78.7962 08-Jun-2012


Park 45.4595 -78.7961 08-Jun-2012


Park 45.4595 -78.7961 08-Jun-2012


Park 46.058 -78.4846 09-Jun-2012

ASDHY063-12 BOLD:ABW8247 Algonquin

Park 13-Jul-2011

ASDHY064-12 BOLD:AAG7737 Algonquin

Park 13-Jul-2011


Park 13-Jul-2011

ASDHY066-12 BOLD:AAG7687 Algonquin 13-Jul-2011

84

Park


Park 45.4599 -78.7961 09-Jul-2011


Park 45.4599 -78.7961 09-Jul-2011


Park 45.8968 -77.735 11-Jul-2011

ASDHY071-12 BOLD:AAC0845 Algonquin

Park 45.8968 -77.735 11-Jul-2011


Park 45.8968 -77.735 11-Jul-2011


Park 45.8968 -77.735 11-Jul-2011

ASBZI045-10 BOLD:AAU8533 Belize 17.7507 -88.6539 18-Apr-2010

ASBZI046-10 BOLD:ACL5555 Belize 17.7507 -88.6539 18-Apr-2010

ASBZI047-10 BOLD:ACA2167 Belize 17.7507 -88.6539 18-Apr-2010





ASBZI054-10 BOLD:AAP8557 Belize 17.7507 -88.6539 18-Apr-2010







ASBZI065-10 BOLD:AAC2018 Belize 17.7507 -88.6539 18-Apr-2010





ASBZI074-10 BOLD:ACH1581 Belize 17.7507 -88.6539 18-Apr-2010












85
































ASBZI156-10 BOLD:AAW0405 Belize 17.7507 -88.6539 18-Apr-2010












86




ASBZI176-10 BOLD:ABX5812 Belize 17.7507 -88.6539 18-Apr-2010


ASBZI183-10 BOLD:AAG0936 Belize 17.7507 -88.6539 18-Apr-2010









ASBZI194-10 BOLD:AAE8205 Belize 17.7507 -88.6539 18-Apr-2010
















ASBZI216-10 BOLD:ABY4069 Belize 17.7507 -88.6539 18-Apr-2010













87





ASBZI235-10 BOLD:AAF5976 Belize 17.7507 -88.6539 18-Apr-2010





ASBZI242-10 BOLD:AAI9312 Belize 17.7507 -88.6539 18-Apr-2010


ASBZI344-10 BOLD:AAY6767 Belize 17.7507 -88.6539 18-Apr-2010






ASBZI359-10 BOLD:ABV2730 Belize 17.7507 -88.6539 18-Apr-2010


























88












































89




















ASBZI485-10 BOLD:AAB9372 Belize 17.7507 -88.6539 18-Apr-2010










ASBZI497-10 BOLD:AAN7931 Belize 17.7507 -88.6539 18-Apr-2010





ASBZI555-10 BOLD:AAV4570 Belize 17.7507 -88.6539 18-Apr-2010









90
































ASBZI622-10 BOLD:ABA6156 Belize 17.7507 -88.6539 18-Apr-2010

ASBZI624-10 BOLD:ACD0249 Belize 17.7507 -88.6539 18-Apr-2010

TTSOW560-11 BOLD:AAY6356 Belize 17.751 -88.654 18-Apr-2010

JBHCH290-10 BOLD:AAU4878 Churchill 58.633 -93.787 14-Aug-2010




JBHCH342-10 BOLD:AAH7430 Churchill 58.761 -94.012 15-Aug-2010


JBHCH475-10 BOLD:AAG2853 Churchill 58.761 -94.012 15-Aug-2010

JBHCH570-10 BOLD:ABY2986 Churchill 58.73 -93.78 23-Jul-2010

JBHCH603-10 BOLD:AAG7860 Churchill 58.754 -93.998 22-Jul-2010

91

JBHCH610-10 BOLD:AAU9781 Churchill 58.754 -93.998 22-Jul-2010










JBHCH842-10 BOLD:ACF5774 Churchill 58.633 -93.787 22-Jul-2010

JBHCI167-11 BOLD:AAF4451 Churchill 58.676 -94.144 05-Aug-2010

JBHCI168-11 BOLD:AAH1659 Churchill 58.676 -94.144 05-Aug-2010


JBHCI170-11 BOLD:AAC9247 Churchill 58.676 -94.144 05-Aug-2010


JBHCI173-11 BOLD:AAK3162 Churchill 58.676 -94.144 05-Aug-2010




JBHCI177-11 BOLD:AAE5992 Churchill 58.676 -94.144 05-Aug-2010

JBHCI178-11 BOLD:AAD1879 Churchill 58.676 -94.144 05-Aug-2010

JBHCI179-11 BOLD:AAB3568 Churchill 58.676 -94.144 05-Aug-2010




JBHCI184-11 BOLD:AAL8264 Churchill 58.676 -94.144 05-Aug-2010


JBHCI186-11 BOLD:AAU8918 Churchill 58.676 -94.144 05-Aug-2010





JBHCI191-11 BOLD:ACF0492 Churchill 58.676 -94.144 05-Aug-2010



JBHCI194-11 BOLD:AAP6735 Churchill 58.676 -94.144 05-Aug-2010





JBHCI199-11 BOLD:ABY7035 Churchill 58.676 -94.144 05-Aug-2010


92




JBHCI204-11 BOLD:AAG2855 Churchill 58.633 -93.787 07-Aug-2010


JBHCI206-11 BOLD:AAI9998 Churchill 58.633 -93.787 07-Aug-2010












JBHCI293-11 BOLD:AAA7636 Churchill 58.676 -94.144 05-Aug-2010


JBHCI296-11 BOLD:ACJ6024 Churchill 58.676 -94.144 05-Aug-2010









JBHCI307-11 BOLD:ABZ5036 Churchill 58.676 -94.144 05-Aug-2010










JBHCI347-11 BOLD:AAN7572 Churchill 58.73 -93.78 03-Aug-2010

JBHCI349-11 BOLD:ACL6059 Churchill 58.73 -93.78 03-Aug-2010




93















JBHCI401-11 BOLD:AAU9874 Churchill 58.754 -93.998 26-Jul-2010

JBHCI404-11 BOLD:AAG7860 Churchill 58.754 -93.998 26-Jul-2010



JBHCI410-11 BOLD:ABX6829 Churchill 58.754 -93.998 26-Jul-2010


JBHCI413-11 BOLD:AAD7163 Churchill 58.754 -93.998 26-Jul-2010



JBHCI416-11 BOLD:AAE2401 Churchill 58.754 -93.998 26-Jul-2010















JBHCI461-11 BOLD:ACE6326 Churchill 58.73 -93.78 03-Aug-2010





94




















JBHCI517-11 BOLD:AAN7594 Churchill 58.754 -93.998 06-Aug-2010





JBHCI540-11 BOLD:AAF1375 Churchill 58.754 -93.998 26-Jul-2010


JBHCI542-11 BOLD:AAH1663 Churchill 58.754 -93.998 26-Jul-2010




JBHCI547-11 BOLD:ACL7889 Churchill 58.754 -93.998 26-Jul-2010



JBHCI550-11 BOLD:AAC6734 Churchill 58.754 -93.998 26-Jul-2010





JBHCI595-11 BOLD:ABU5550 Churchill 58.633 -93.787 22-Jul-2010




JBHCI600-11 BOLD:ABZ0669 Churchill 58.633 -93.787 22-Jul-2010

95

JBHCI601-11 BOLD:ACE3334 Churchill 58.633 -93.787 22-Jul-2010

JBHCI602-11 BOLD:AAB3568 Churchill 58.633 -93.787 22-Jul-2010















JBHCI670-11 BOLD:AAM6952 Churchill 58.705 -94.054 28-Jul-2010




JBHCI681-11 BOLD:ABX6188 Churchill 58.705 -94.054 28-Jul-2010






JBHCI690-11 BOLD:AAA4188 Churchill 58.705 -94.054 28-Jul-2010




JBHCI704-11 BOLD:ACI7676 Churchill 58.705 -94.054 28-Jul-2010


JBHCI706-11 BOLD:ACI7676 Churchill 58.705 -94.054 28-Jul-2010

JBHCI707-11 BOLD:AAI1431 Churchill 58.705 -94.054 28-Jul-2010






JBHCI714-11 BOLD:ABY7029 Churchill 58.705 -94.054 28-Jul-2010


JBHCI716-11 BOLD:ACF2213 Churchill 58.705 -94.054 28-Jul-2010


96






JBHCI762-11 BOLD:ACF2205 Churchill 58.761 -94.012 24-Jul-2010







JBHCI773-11 BOLD:AAK5989 Churchill 58.761 -94.012 24-Jul-2010




























JBHCI826-11 BOLD:AAK3158 Churchill 58.761 -94.012 24-Jul-2010



97








JBHCI839-11 BOLD:AAL5459 Churchill 58.633 -93.787 02-Aug-2010




JBHCI843-11 BOLD:ACL8722 Churchill 58.633 -93.787 02-Aug-2010














JBHCI859-11 BOLD:ABX6473 Churchill 58.633 -93.787 02-Aug-2010


















98







JBHCI894-11 BOLD:ACK8156 Churchill 58.633 -93.787 02-Aug-2010


JBHCI896-11 BOLD:AAM9124 Churchill 58.633 -93.787 02-Aug-2010



JBHCI899-11 BOLD:AAJ7918 Churchill 58.633 -93.787 02-Aug-2010




























JBHCI980-11 BOLD:ACE3445 Churchill 58.705 -94.054 30-Jul-2010




99

JBHCI985-11 BOLD:AAJ7918 Churchill 58.705 -94.054 30-Jul-2010




JBHCJ008-11 BOLD:AAU4878 Churchill 58.633 -93.787 03-Aug-2010

JBHCJ013-11 BOLD:AAH1531 Churchill 58.633 -93.787 03-Aug-2010

JBHCJ014-11 BOLD:AAD6970 Churchill 58.633 -93.787 03-Aug-2010


JBHCJ016-11 BOLD:AAG1230 Churchill 58.633 -93.787 07-Aug-2010



JBHCJ031-11 BOLD:AAU9816 Churchill 58.705 -94.054 30-Jul-2010

JBHCJ033-11 BOLD:AAG7860 Churchill 58.705 -94.054 30-Jul-2010


JBHCJ035-11 BOLD:AAH1553 Churchill 58.705 -94.054 30-Jul-2010

JBHCJ036-11 BOLD:AAM6952 Churchill 58.705 -94.054 30-Jul-2010

JBHCJ037-11 BOLD:AAC1404 Churchill 58.705 -94.054 30-Jul-2010

JBHCJ039-11 BOLD:AAD6035 Churchill 58.705 -94.054 30-Jul-2010

JBHCJ040-11 BOLD:AAA9665 Churchill 58.705 -94.054 30-Jul-2010






JBHCJ086-11 BOLD:ABY7029 Churchill 58.705 -94.054 30-Jul-2010

JBHCJ087-11 BOLD:AAF1375 Churchill 58.705 -94.054 30-Jul-2010




JBHCJ092-11 BOLD:ACF0014 Churchill 58.705 -94.054 30-Jul-2010



JBHCJ095-11 BOLD:AAE8389 Churchill 58.705 -94.054 30-Jul-2010





JBHCJ132-11 BOLD:ACK8156 Churchill 58.705 -94.054 31-Jul-2010


JBHCJ134-11 BOLD:AAB0136 Churchill 58.705 -94.054 31-Jul-2010




100

JBHCJ138-11 BOLD:AAK3162 Churchill 58.705 -94.054 31-Jul-2010


JBHCJ140-11 BOLD:ACL9498 Churchill 58.705 -94.054 31-Jul-2010




JBHCJ146-11 BOLD:ABZ1251 Churchill 58.705 -94.054 31-Jul-2010

JBHCJ147-11 BOLD:AAJ7918 Churchill 58.705 -94.054 31-Jul-2010





JBHCJ155-11 BOLD:ACE9496 Churchill 58.766 -94.122 03-Aug-2010

JBHCJ156-11 BOLD:AAB0893 Churchill 58.766 -94.122 03-Aug-2010






JBHCJ162-11 BOLD:AAF8320 Churchill 58.766 -94.122 03-Aug-2010







JBHCJ171-11 BOLD:AAC9247 Churchill 58.705 -94.054 06-Aug-2010

JBHCJ172-11 BOLD:ACL9498 Churchill 58.705 -94.054 06-Aug-2010


JBHCJ174-11 BOLD:AAE5992 Churchill 58.705 -94.054 06-Aug-2010










JBHCJ188-11 BOLD:ACE9872 Churchill 58.705 -94.054 31-Jul-2010




101






























JBHCJ228-11 BOLD:AAA6277 Churchill 58.766 -94.122 03-Aug-2010





JBHCJ233-11 BOLD:AAK3167 Churchill 58.705 -94.054 06-Aug-2010

JBHCJ236-11 BOLD:AAJ8196 Churchill 58.705 -94.054 06-Aug-2010





JBHCJ252-11 BOLD:AAM7219 Churchill 58.705 -94.054 06-Aug-2010



102

JBHCJ255-11 BOLD:ABZ3755 Churchill 58.705 -94.054 06-Aug-2010



JBHCJ258-11 BOLD:ABY6861 Churchill 58.705 -94.054 06-Aug-2010




























JBHCJ364-11 BOLD:ACF2841 Churchill 58.761 -94.012 03-Aug-2010


JBHCJ367-11 BOLD:AAI1546 Churchill 58.761 -94.012 03-Aug-2010










103


JBHCJ411-11 BOLD:AAI1547 Churchill 58.633 -93.787 26-Jul-2010










































104





































JBHCJ519-11 BOLD:AAB0136 Churchill 58.633 -93.787 26-Jul-2010



JBHCJ522-11 BOLD:AAK3180 Churchill 58.633 -93.787 26-Jul-2010




105



























JBHCJ581-11 BOLD:ACJ4858 Churchill 58.761 -94.012 03-Aug-2010

















106





JBHCJ632-11 BOLD:ABY7035 Churchill 58.676 -94.144 05-Aug-2010










JBHCJ642-11 BOLD:ACJ6024 Churchill 58.676 -94.144 05-Aug-2010





























107






























JBHCJ752-11 BOLD:AAY6839 Churchill 58.754 -93.998 11-Aug-2010

JBHCJ753-11 BOLD:AAY6840 Churchill 58.754 -93.998 11-Aug-2010


SAHYM032-10 BOLD:ABZ2380 Churchill 58.7543 -93.9968 31-Jul-2009

SAHYM033-10 BOLD:AAH1648 Churchill 58.7543 -93.9968 31-Jul-2009



SAHYM037-10 BOLD:AAF6039 Churchill 58.7543 -93.9968 31-Jul-2009

SAHYM038-10 BOLD:AAG2856 Churchill 58.7543 -93.9968 31-Jul-2009


SAHYM040-10 BOLD:AAI7642 Churchill 58.7306 -93.7804 20-Jul-2009




108


SAHYM046-10 BOLD:AAN7591 Churchill 58.6153 -93.8222 20-Jul-2009

SAHYM047-10 BOLD:ABY4961 Churchill 58.6153 -93.8222 20-Jul-2009

SAHYM048-10 BOLD:AAE5985 Churchill 58.6153 -93.8222 20-Jul-2009

SAHYM049-10 BOLD:ACJ4858 Churchill 58.6153 -93.8222 20-Jul-2009

















SAHYM067-10 BOLD:AAB8450 Churchill 58.7543 -93.9968 28-Jul-2009






















109




SAHYM092-10 BOLD:AAD0970 Churchill 58.6153 -93.8222 31-Jul-2009


SAHYM094-10 BOLD:AAA5819 Churchill 58.6153 -93.8222 31-Jul-2009


SAHYM096-10 BOLD:ACE6827 Churchill 58.6153 -93.8222 31-Jul-2009




SAHYM100-10 BOLD:ACI2711 Churchill 58.6153 -93.8222 31-Jul-2009





SAHYM105-10 BOLD:ACB0247 Churchill 58.6153 -93.8222 31-Jul-2009





SAHYM110-10 BOLD:ACF5817 Churchill 58.7543 -93.9968 21-Jul-2009













SAHYM123-10 BOLD:ABX6645 Churchill 58.6153 -93.8222 31-Jul-2009





SAHYM128-10 BOLD:AAL8286 Churchill 58.7543 -93.9968 28-Jul-2009




110



































SAHYM173-10 BOLD:AAC9130 Churchill 58.6153 -93.8222 31-Jul-2009









111





SAHYM190-10 BOLD:ACA9884 Churchill 58.6153 -93.8222 31-Jul-2009















SAHYM209-10 BOLD:AAU9501 Churchill 58.7543 -93.9968 21-Jul-2009
























112
















SAHYM267-10 BOLD:AAJ0884 Churchill 58.6153 -93.8222 31-Jul-2009




























113














SAHYM332-10 BOLD:ACL2543 Churchill 58.7306 -93.7804 28-Jul-2009






























114

























SAHYM391-10 BOLD:AAM9124 Churchill 58.7306 -93.7804 20-Jul-2009






SAHYM397-10 BOLD:AAU9814 Churchill 58.7306 -93.7804 20-Jul-2009













115










SAHYM420-10 BOLD:AAO2089 Churchill 58.6153 -93.8222 31-Jul-2009

































TWCHL008-09 BOLD:AAG1947 Churchill 58.649 -94.193 17-Jul-2008

116

TWCHL050-09 BOLD:AAG1902 Churchill 58.731 -93.78 21-Jul-2007

TWHYM022-09

BOLD:AAG0775 Churchill 58.731 -93.78 21-Jul-2007

TWHYM023-09


TWHYM024-09

BOLD:ACJ5244 Churchill 58.731 -93.78 21-Jul-2007

TWHYM025-09


TWHYM027-09


TWHYM028-09


TWHYM037-09


TWHYM038-09


TWHYM039-09


TWHYM040-09


TWHYM043-09

BOLD:ACF4318 Churchill 58.649 -94.193 17-Jul-2008

TWHYM097-09

BOLD:ABU5550 Churchill 58.649 -94.193 17-Jul-2008

TWHYM098-09


TWHYM099-09


TWHYM100-09


TWHYM101-09

BOLD:ABU5550 Churchill 58.649 -94.193 17-Jul-2008

TWHYM102-09


TWHYM104-09


TWHYM105-09


TWHYM106-09


TWHYM107-09

BOLD:AAC9550 Churchill 58.649 -94.193 17-Jul-2008

TWHYM108-09

BOLD:AAM4923 Churchill 58.649 -94.193 17-Jul-2008

TWHYM109-09


117

TWHYM110-09


TWHYM111-09


TWHYM112-09


TWHYM113-09


TWHYM120-09


TWHYM121-09

BOLD:ACF3994 Churchill 58.755 -93.998 14-Jul-2008

TWHYM122-09


TWHYM123-09


TWHYM124-09


TWHYM125-09


TWHYM126-09


TWHYM127-09

BOLD:AAD3209 Churchill 58.734 -94.112 14-Jul-2008

TWHYM128-09

BOLD:AAF4995 Churchill 58.734 -94.112 14-Jul-2008

TWHYM129-09


TWHYM130-09


TWHYM131-09


TWHYM132-09


TWHYM133-09


TWHYM134-09


TWHYM136-09


TWHYM137-09


WSPAH010-06 BOLD:AAU9762 Churchill 58.738 -93.819 01-Aug-2005

WSPAH026-06 BOLD:AAF8096 Churchill 58.738 -93.819 29-Aug-2005

WSPAH042-06 BOLD:AAB0136 Churchill 58.738 -93.819 01-Aug-2005

WSPAH060-06 BOLD:ACF0077 Churchill 58.738 -93.819 01-Aug-2005

118

WSPAH063-06 BOLD:AAH3897 Churchill 58.738 -93.819 29-Jul-2005

WSPAH064-06 BOLD:AAG9161 Churchill 58.738 -93.819 29-Jul-2005

BBHYA109-12 BOLD:AAN7806 Florida 30.705 -86.882 26-May-2011

BBHYA1199-12 BOLD:ABY1607 Florida 27.264 -82.288 24-May-2011



BBHYA1346-12 BOLD:ABX9637 Florida 30.711 -86.882 27-May-2011



BBHYA136-12 BOLD:AAG7772 Florida 25.987 -81.595 19-May-2011




BBHYA1583-12 BOLD:AAF7670 Florida 24.665 -81.257 14-May-2011

BBHYA1584-12 BOLD:ACA6656 Florida 30.437 -83.627 26-May-2011


BBHYA1591-12 BOLD:ACE8627 Florida 25.993 -81.595 18-May-2011









BBHYA1675-12 BOLD:AAZ9571 Florida 30.711 -86.882 28-May-2011



BBHYA171-12 BOLD:AAK8237 Florida 27.582 -81.044 08-May-2011


BBHYA1727-12 BOLD:AAH1900 Florida 27.582 -81.044 11-May-2011


BBHYA1730-12 BOLD:ACF2512 Florida 27.582 -81.044 11-May-2011







BBHYA1746-12 BOLD:AAU8081 Florida 27.582 -81.044 07-May-2011

BBHYA1750-12 BOLD:AAV3504 Florida 27.579 -81.044 07-May-2011



119











BBHYA282-12 BOLD:AAJ2314 Florida 27.246 -82.308 22-May-2011



BBHYA2884-12 BOLD:AAC3220 Florida 27.246 -82.308 24-May-2011







BBHYA2899-12 BOLD:ABV2658 Florida 27.246 -82.308 24-May-2011

BBHYA2905-12 BOLD:AAA4784 Florida 27.246 -82.308 24-May-2011






















120

BBHYA3030-12 BOLD:AAE7934 Florida 27.246 -82.308 24-May-2011






BBHYA3116-12 BOLD:AAD7490 Florida 25.993 -81.595 20-May-2011





































121




























BBHYA4125-12 BOLD:ABA8059 Florida 27.582 -81.044 08-May-2011




BBHYA4174-12 BOLD:ACL1223 Florida 27.581 -81.043 08-May-2011


BBHYA4178-12 BOLD:ACB1342 Florida 27.582 -81.044 08-May-2011






BBHYG742-10 BOLD:AAG3572 Florida 30.3154 -87.4214 01-Apr-2010

BBHYG743-10 BOLD:AAN7798 Florida 30.3154 -87.4214 01-Apr-2010

BBHYG772-10 BOLD:AAG8146 Florida 27.6729 -82.3636 24-Mar-2010


122



BBHYG784-10 BOLD:AAA6182 Florida 24.7726 -80.9405 09-Mar-2010

BBHYG785-10 BOLD:AAN7808 Florida 29.1824 -81.7133 27-Mar-2010








BBHYG826-10 BOLD:ACE9668 Florida 30.2932 -87.4677 31-Mar-2010


BBHYG952-10 BOLD:AAU8459 Florida 29.2631 -81.8552 26-Mar-2010




BBHYH160-10 BOLD:AAN7895 Florida 27.2446 -82.3014 18-Mar-2010



BBHYH166-10 BOLD:AAG1277 Florida 25.9906 -81.5784 13-Mar-2010



BBHYH171-10 BOLD:AAK8237 Florida 27.6665 -82.3795 23-Mar-2010






BBHYH178-10 BOLD:AAL8247 Florida 25.9978 -81.5989 14-Mar-2010










BBHYH196-10 BOLD:ABZ2900 Florida 27.5817 -81.0479 07-Mar-2010




123



BBHYH202-10 BOLD:AAA3764 Florida 27.5817 -81.0479 07-Mar-2010

BBHYH203-10 BOLD:AAM4942 Florida 27.5817 -81.0479 07-Mar-2010


BBHYH208-10 BOLD:AAN7919 Florida 30.3154 -87.4214 01-Apr-2010





BBHYH217-10 BOLD:AAG8133 Florida 30.3154 -87.4214 01-Apr-2010







BBHYH231-10 BOLD:AAI6272 Florida 30.2932 -87.4677 01-Apr-2010



BBHYH234-10 BOLD:AAH7266 Florida 27.5817 -81.0479 07-Mar-2010










BBHYH245-10 BOLD:ACE4724 Florida 27.2756 -82.2661 20-Mar-2010













124

















BBHYH397-10 BOLD:AAQ2659 Florida 24.7726 -80.9405 11-Mar-2010



























125












































126





























BBHYH595-10 BOLD:AAZ1991 Florida 27.2524 -82.2958 21-Mar-2010















127

















BBHYH639-10 BOLD:ABX6121 Florida 27.5817 -81.0479 07-Mar-2010












BBHYH663-10 BOLD:AAH3192 Florida 27.5817 -81.0479 07-Mar-2010















128




























BBHYH733-10 BOLD:AAU8504 Florida 27.5823 -81.0423 07-Mar-2010

ASNUR007-11 BOLD:AAV0048 French Guiana

4.088 -52.681 29-Jan-2011


4.088 -52.681 31-Jan-2011


4.088 -52.681 31-Jan-2011


4.088 -52.681 31-Jan-2011


4.088 -52.681 31-Jan-2011


4.088 -52.681 31-Jan-2011


4.088 -52.681 31-Jan-2011


4.088 -52.681 31-Jan-2011

129

ASNUR022-11 BOLD:ABY4175 French Guiana

4.088 -52.681 31-Jan-2011


4.088 -52.681 31-Jan-2011


4.088 -52.681 31-Jan-2011


4.088 -52.681 31-Jan-2011


4.088 -52.681 31-Jan-2011


4.088 -52.681 31-Jan-2011


4.088 -52.681 31-Jan-2011

ASNUR038-11 BOLD:AAU9981 French Guiana

4.088 -52.681 31-Jan-2011


4.088 -52.681 31-Jan-2011


4.088 -52.681 31-Jan-2011


4.088 -52.681 31-Jan-2011


4.088 -52.681 31-Jan-2011


4.088 -52.681 31-Jan-2011


4.088 -52.681 31-Jan-2011


4.089 -52.677 31-Jan-2011


4.089 -52.677 31-Jan-2011


4.089 -52.677 31-Jan-2011


4.089 -52.677 31-Jan-2011

ASNUR056-11 BOLD:ABX5653 French Guiana

4.089 -52.677 31-Jan-2011


4.089 -52.677 31-Jan-2011


4.089 -52.677 31-Jan-2011


4.089 -52.677 31-Jan-2011


4.089 -52.677 31-Jan-2011

ASNUR061-11 BOLD:AAU9993 French 4.089 -52.677 31-Jan-2011

130

Guiana


4.089 -52.677 31-Jan-2011


4.089 -52.677 31-Jan-2011


4.089 -52.677 31-Jan-2011


4.089 -52.677 31-Jan-2011


4.089 -52.677 31-Jan-2011


4.089 -52.677 31-Jan-2011


4.089 -52.677 31-Jan-2011


4.089 -52.677 31-Jan-2011


4.089 -52.677 31-Jan-2011


4.089 -52.677 31-Jan-2011


4.089 -52.677 31-Jan-2011


4.089 -52.677 31-Jan-2011


4.089 -52.677 31-Jan-2011


4.089 -52.677 31-Jan-2011

ASNUR089-11 BOLD:ABY6803 French Guiana

4.089 -52.677 31-Jan-2011

ASNUR090-11 BOLD:ABZ5615 French Guiana

4.089 -52.677 31-Jan-2011


4.089 -52.677 31-Jan-2011


4.089 -52.677 31-Jan-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011

ASNUR100-11 BOLD:AAZ1977 French Guiana

4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011

131


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.089 -52.677 02-Feb-2011


4.089 -52.677 02-Feb-2011


4.089 -52.677 02-Feb-2011


4.089 -52.677 02-Feb-2011


4.089 -52.677 02-Feb-2011


4.089 -52.677 02-Feb-2011

ASNUR135-11 BOLD:ABX5579 French 4.089 -52.677 02-Feb-2011

132

Guiana


4.089 -52.677 02-Feb-2011


4.089 -52.677 02-Feb-2011


4.089 -52.677 02-Feb-2011


4.089 -52.677 02-Feb-2011


4.089 -52.677 02-Feb-2011


4.089 -52.677 02-Feb-2011


4.089 -52.677 02-Feb-2011


4.089 -52.677 02-Feb-2011


4.089 -52.677 02-Feb-2011


4.089 -52.677 02-Feb-2011


4.089 -52.677 02-Feb-2011


4.089 -52.677 02-Feb-2011


4.088 -52.681 29-Jan-2011


4.088 -52.681 29-Jan-2011


4.088 -52.681 29-Jan-2011


4.088 -52.681 29-Jan-2011


4.088 -52.681 29-Jan-2011


4.088 -52.681 29-Jan-2011


4.088 -52.681 29-Jan-2011


4.088 -52.681 29-Jan-2011

ASNUR164-11 BOLD:AAH8705 French Guiana

4.088 -52.681 29-Jan-2011


4.088 -52.681 01-Feb-2011


4.088 -52.681 01-Feb-2011

133


4.088 -52.681 01-Feb-2011


4.088 -52.681 01-Feb-2011


4.088 -52.681 01-Feb-2011


4.088 -52.681 01-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 02-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011

ASNUR194-11 BOLD:AAV2846 French 4.088 -52.681 04-Feb-2011

134

Guiana


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011

135


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011

ASNUR227-11 BOLD:AAM9598 French Guiana

4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011

ASNUR250-11 BOLD:AAU9996 French 4.089 -52.677 04-Feb-2011

136

Guiana


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011


4.089 -52.677 04-Feb-2011

ASNUR273-11 BOLD:AAA1265 French Guiana

4.088 -52.681 03-Feb-2011


4.088 -52.681 03-Feb-2011


4.088 -52.681 03-Feb-2011


4.088 -52.681 03-Feb-2011


4.088 -52.681 03-Feb-2011


4.088 -52.681 03-Feb-2011


4.088 -52.681 03-Feb-2011

137

ASNUR281-11 BOLD:ACK8030 French Guiana

4.088 -52.681 03-Feb-2011


4.088 -52.681 03-Feb-2011


4.088 -52.681 03-Feb-2011


4.088 -52.681 03-Feb-2011


4.088 -52.681 03-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


138

Guiana


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011

ASNUR322-11 BOLD:AAZ1976 French Guiana

4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.088 -52.681 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011

139


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


140

Guiana


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.089 -52.677 06-Feb-2011


4.088 -52.681 03-Feb-2011


4.088 -52.681 03-Feb-2011


4.088 -52.681 03-Feb-2011


4.088 -52.681 05-Feb-2011


4.088 -52.681 05-Feb-2011


4.088 -52.681 05-Feb-2011


4.088 -52.681 05-Feb-2011


4.088 -52.681 05-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011

141


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 07-Feb-2011


4.088 -52.681 07-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 05-Feb-2011


4.089 -52.677 08-Feb-2011


142

Guiana


4.089 -52.677 08-Feb-2011


4.089 -52.677 08-Feb-2011


4.089 -52.677 08-Feb-2011


4.089 -52.677 08-Feb-2011


4.089 -52.677 08-Feb-2011


4.089 -52.677 08-Feb-2011


4.089 -52.677 08-Feb-2011


4.089 -52.677 08-Feb-2011


4.089 -52.677 08-Feb-2011


4.089 -52.677 08-Feb-2011


4.089 -52.677 08-Feb-2011


4.089 -52.677 08-Feb-2011


4.089 -52.677 08-Feb-2011


4.089 -52.677 08-Feb-2011


4.089 -52.677 08-Feb-2011


4.089 -52.677 08-Feb-2011


4.089 -52.677 08-Feb-2011


4.089 -52.677 08-Feb-2011


4.089 -52.677 08-Feb-2011


4.089 -52.677 08-Feb-2011


4.089 -52.677 08-Feb-2011


4.089 -52.677 08-Feb-2011


4.089 -52.677 08-Feb-2011

143


4.089 -52.677 08-Feb-2011


4.089 -52.677 08-Feb-2011


4.089 -52.677 08-Feb-2011


4.089 -52.677 08-Feb-2011


4.089 -52.677 08-Feb-2011


4.089 -52.677 08-Feb-2011


4.088 -52.681 05-Feb-2011


4.088 -52.681 05-Feb-2011


4.088 -52.681 05-Feb-2011


4.088 -52.681 03-Feb-2011


4.088 -52.681 03-Feb-2011


4.088 -52.681 04-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 08-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


144

Guiana


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.093 -52.678 09-Feb-2011


4.089 -52.677 09-Feb-2011


4.089 -52.677 09-Feb-2011


4.089 -52.677 09-Feb-2011


4.089 -52.677 09-Feb-2011

145


4.089 -52.677 09-Feb-2011


4.089 -52.677 09-Feb-2011


4.089 -52.677 09-Feb-2011


4.089 -52.677 09-Feb-2011


4.089 -52.677 09-Feb-2011


4.089 -52.677 09-Feb-2011


4.089 -52.677 09-Feb-2011


4.089 -52.677 09-Feb-2011


4.089 -52.677 09-Feb-2011


4.089 -52.677 09-Feb-2011


4.089 -52.677 09-Feb-2011


4.089 -52.677 09-Feb-2011


4.089 -52.677 09-Feb-2011


4.089 -52.677 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011

ASNUR537-11 BOLD:AAH8705 French 4.088 -52.681 09-Feb-2011

146

Guiana


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 09-Feb-2011


4.088 -52.681 10-Feb-2011


4.088 -52.681 10-Feb-2011


4.088 -52.681 10-Feb-2011


4.089 -52.677 10-Feb-2011


4.089 -52.677 10-Feb-2011


4.089 -52.677 10-Feb-2011


4.089 -52.677 10-Feb-2011


4.089 -52.677 10-Feb-2011


4.089 -52.677 10-Feb-2011


4.089 -52.677 10-Feb-2011

ASNUR560-11 BOLD:AAB7595 French Guiana

4.088 -52.681 09-Feb-2011

ASQBR541-09 BOLD:AAH6914 French Guiana


147

ASQBR778-09 BOLD:AAI1691 French Guiana


ASQSP654-08 BOLD:AAI5830 French Guiana

4.55556 -52.1386 01-Aug-2005

ASQSP915-08 BOLD:AAH8778 French Guiana

01-Mar-2005

ASQSP918-08 BOLD:AAV7508 French Guiana

01-May-2005

ASQSP935-08 BOLD:ACK7827 French Guiana

5.14981 -52.7114 01-Jun-2005


5.14981 -52.7114 01-Jun-2005


5.14981 -52.7114 01-Jun-2005


5.14981 -52.7114 01-Jun-2005


5.14981 -52.7114 01-Jun-2005

ASQSQ132-09 BOLD:AAH8812 French Guiana

4.71194 -52.1925 01-Oct-2005


01-Oct-2005


01-Apr-2005

ASQSQ252-09 BOLD:ACK7827 French Guiana

5.14981 -52.7114 01-May-2005


01-Aug-2007

ASQSQ800-10 BOLD:ACK0105 French Guiana

01-Aug-2007

ASQSQ810-10 BOLD:AAV7513 French Guiana

01-Dec-2000


07-Aug-2000


01-Mar-1999

ASQSQ813-10 BOLD:ACA7986 French Guiana

01-Dec-2000


18-Jul-2000

ASQSQ816-10 BOLD:ABA9168 French Guiana

01-May-1999


13-Dec-2000

ASQSQ818-10 BOLD:AAV7516 French 30-Oct-1998

148

Guiana

ASQSQ819-10 BOLD:AAW1625 French Guiana

01-Dec-2000

ASQSQ820-10 BOLD:ABA9159 French Guiana

30-Aug-2000


01-Dec-2000


4.25001 -52.3585 04-Jan-2003


01-May-1999


01-Sep-1999

ASQSR147-11 BOLD:AAW1622 French Guiana

01-Oct-2001

ASQSR149-11 BOLD:AAW1624 French Guiana

06-Jul-2000

ASQSR254-11 BOLD:ABA4663 French Guiana

01-Jan-2010

ASGLE022-10 BOLD:AAG7638 Guelph 43.554 -80.264 23-Sep-2009



ASGLE025-10 BOLD:AAU8613 Guelph 43.554 -80.264 23-Sep-2009

ASGLE026-10 BOLD:AAH7283 Guelph 43.554 -80.264 23-Sep-2009





ASGLE033-10 BOLD:AAQ2783 Guelph 43.554 -80.264 23-Sep-2009




ASGLE037-10 BOLD:AAD5194 Guelph 43.554 -80.264 23-Sep-2009


ASGLE039-10 BOLD:AAM7439 Guelph 43.554 -80.264 23-Sep-2009

ASGLE040-10 BOLD:AAO2111 Guelph 43.554 -80.264 23-Sep-2009




ASGLE046-10 BOLD:ABZ7958 Guelph 43.554 -80.264 23-Sep-2009





149



ASGLE054-10 BOLD:ACE5353 Guelph 43.554 -80.264 23-Sep-2009






ASGLE063-10 BOLD:AAC2392 Guelph 43.554 -80.264 23-Sep-2009








ASGLE077-10 BOLD:AAB8493 Guelph 43.554 -80.264 23-Sep-2009



ASGLE081-10 BOLD:ACF3099 Guelph 43.554 -80.264 23-Sep-2009















ASGLE098-10 BOLD:AAN8195 Guelph 43.554 -80.264 23-Sep-2009


ASGLE1000-10 BOLD:AAG3193 Guelph 43.554 -80.264 01-Aug-2010


ASGLE1003-10 BOLD:AAD8806 Guelph 43.554 -80.264 01-Aug-2010

ASGLE1004-10 BOLD:AAB0892 Guelph 43.554 -80.264 01-Aug-2010




150

ASGLE1008-10 BOLD:ABY7035 Guelph 43.554 -80.264 01-Aug-2010

ASGLE1009-10 BOLD:AAA1468 Guelph 43.554 -80.264 01-Aug-2010



ASGLE1012-10 BOLD:AAJ0494 Guelph 43.554 -80.264 18-Aug-2010

ASGLE1013-10 BOLD:AAZ1472 Guelph 43.554 -80.264 18-Aug-2010


ASGLE1015-10 BOLD:AAN3383 Guelph 43.554 -80.264 18-Aug-2010





ASGLE1020-10 BOLD:AAU8646 Guelph 43.554 -80.264 18-Aug-2010










ASGLE1029-10 BOLD:AAJ1464 Guelph 43.554 -80.264 30-May-2010

ASGLE1030-10 BOLD:AAU8641 Guelph 43.554 -80.264 30-May-2010




ASGLE1034-10 BOLD:AAG7737 Guelph 43.554 -80.264 30-May-2010






ASGLE1040-10 BOLD:AAQ2996 Guelph 43.554 -80.264 30-May-2010










151





ASGLE1098-10 BOLD:AAI1292 Guelph 43.554 -80.264 01-Aug-2010





ASGLE1104-10 BOLD:AAP2581 Guelph 43.554 -80.264 01-Aug-2010

ASGLE1105-10 BOLD:ABX5489 Guelph 43.554 -80.264 01-Aug-2010






ASGLE1112-10 BOLD:ABZ7151 Guelph 43.554 -80.264 01-Aug-2010


ASGLE1115-10 BOLD:AAL7396 Guelph 43.554 -80.264 18-Aug-2010








ASGLE1123-10 BOLD:AAE9438 Guelph 43.554 -80.264 18-Aug-2010







ASGLE1132-10 BOLD:AAC1302 Guelph 43.554 -80.264 18-Aug-2010



ASGLE1135-10 BOLD:ACK5169 Guelph 43.554 -80.264 18-Aug-2010







152

ASGLE1144-10 BOLD:AAE0349 Guelph 43.554 -80.264 18-Aug-2010




ASGLE1151-10 BOLD:ABW3285 Guelph 43.554 -80.264 18-Aug-2010






ASGLE1161-10 BOLD:AAM7456 Guelph 43.554 -80.264 18-Aug-2010




ASGLE1167-10 BOLD:ACF4040 Guelph 43.554 -80.264 18-Aug-2010







ASGLE1173-10 BOLD:ACE7616 Guelph 43.554 -80.264 30-May-2010


ASGLE1176-10 BOLD:AAA7636 Guelph 43.554 -80.264 30-May-2010


ASGLE1180-10 BOLD:AAF7225 Guelph 43.554 -80.264 30-May-2010














ASGLE1199-10 BOLD:AAU8342 Guelph 43.554 -80.264 14-Jul-2010

ASGLE1200-10 BOLD:AAN8216 Guelph 43.554 -80.264 14-Jul-2010


ASGLE1203-10 BOLD:AAM7445 Guelph 43.554 -80.264 14-Jul-2010

153










ASGLE1216-10 BOLD:ACF4040 Guelph 43.554 -80.264 14-Jul-2010











ASGLE1230-10 BOLD:AAG7900 Guelph 43.554 -80.264 14-Jul-2010















ASGLE1247-10 BOLD:AAI7643 Guelph 43.554 -80.264 30-May-2010


ASGLE1252-10 BOLD:AAE5602 Guelph 43.554 -80.264 30-May-2010

ASGLE1253-10 BOLD:AAL7396 Guelph 43.554 -80.264 30-May-2010



ASGLE1256-10 BOLD:AAH1764 Guelph 43.554 -80.264 30-May-2010


154

ASGLE1258-10 BOLD:AAD4214 Guelph 43.554 -80.264 30-May-2010


ASGLE1260-10 BOLD:ABY7035 Guelph 43.554 -80.264 30-May-2010





ASGLE1265-10 BOLD:ABY7035 Guelph 43.554 -80.264 14-Jul-2010

ASGLE1266-10 BOLD:AAD5194 Guelph 43.554 -80.264 14-Jul-2010





ASGLE1271-10 BOLD:AAQ2996 Guelph 43.554 -80.264 14-Jul-2010

ASGLE1272-10 BOLD:AAD5194 Guelph 43.554 -80.264 14-Jul-2010



ASGLE1276-10 BOLD:AAA9386 Guelph 43.554 -80.264 14-Jul-2010



ASGLE1279-10 BOLD:ABZ4179 Guelph 43.554 -80.264 14-Jul-2010








ASGLE1333-10 BOLD:AAC2167 Guelph 43.554 -80.264 30-May-2010






ASGLE1340-10 BOLD:ACK5169 Guelph 43.554 -80.264 30-May-2010






ASGLE1346-10 BOLD:AAP2581 Guelph 43.554 -80.264 30-May-2010

ASGLE1347-10 BOLD:AAM4998 Guelph 43.554 -80.264 30-May-2010


155








ASGLE1360-10 BOLD:AAP2581 Guelph 43.554 -80.264 14-Jul-2010










ASGLE1407-10 BOLD:AAU8741 Guelph 43.554 -80.264 25-Jun-2010

ASGLE1408-10 BOLD:AAG9169 Guelph 43.554 -80.264 25-Jun-2010




ASGLE1412-10 BOLD:AAI1549 Guelph 43.554 -80.264 25-Jun-2010

















ASGLE1480-10 BOLD:ABX6808 Guelph 43.554 -80.264 25-Jun-2010



ASGLE1483-10 BOLD:AAP6703 Guelph 43.554 -80.264 25-Jun-2010

156

ASGLE1484-10 BOLD:AAH1890 Guelph 43.554 -80.264 25-Jun-2010






ASGLE1492-10 BOLD:AAM7487 Guelph 43.554 -80.264 25-Jun-2010


ASGLE1494-10 BOLD:AAQ2892 Guelph 43.554 -80.264 25-Jun-2010


ASGLE1496-10 BOLD:AAN8195 Guelph 43.554 -80.264 25-Jun-2010





ASGLE1550-10 BOLD:AAD5318 Guelph 43.554 -80.264 25-Jun-2010





ASGLE1555-10 BOLD:ACE4814 Guelph 43.554 -80.264 25-Jun-2010









ASGLE1595-10 BOLD:AAQ2726 Guelph 43.554 -80.264 14-Jun-2010

ASGLE1596-10 BOLD:AAC9245 Guelph 43.554 -80.264 14-Jun-2010

ASGLE1597-10 BOLD:AAF7684 Guelph 43.554 -80.264 14-Jun-2010

ASGLE1599-10 BOLD:AAE2886 Guelph 43.554 -80.264 14-Jun-2010

ASGLE1600-10 BOLD:AAE2886 Guelph 43.554 -80.264 14-Jun-2010






ASGLE1617-10 BOLD:ACK3058 Guelph 43.554 -80.264 25-Jun-2010




157


ASGLE1623-10 BOLD:AAJ3895 Guelph 43.554 -80.264 25-Jun-2010



ASGLE1626-10 BOLD:AAL5084 Guelph 43.554 -80.264 25-Jun-2010



ASGLE1629-10 BOLD:AAA9461 Guelph 43.554 -80.264 25-Jun-2010






ASGLE1696-10 BOLD:ABY7035 Guelph 43.554 -80.264 14-Jun-2010


ASGLE1698-10 BOLD:AAH1684 Guelph 43.554 -80.264 14-Jun-2010





ASGLE1704-10 BOLD:AAJ1464 Guelph 43.554 -80.264 14-Jun-2010







ASGLE1741-10 BOLD:ACD0417 Guelph 43.554 -80.264 14-Jun-2010


ASGLE1743-10 BOLD:ACC9501 Guelph 43.554 -80.264 14-Jun-2010







ASGLE1752-10 BOLD:AAB0096 Guelph 43.554 -80.264 14-Jun-2010


ASGLE177-10 BOLD:ACH5153 Guelph 43.554 -80.264 23-Sep-2009





158







ASGLE1828-10 BOLD:AAY2114 Guelph 43.554 -80.264 14-Jun-2010

ASGLE1829-10 BOLD:AAZ0148 Guelph 43.554 -80.264 14-Jun-2010





























ASGLE208-10 BOLD:AAF5747 Guelph 43.554 -80.264 23-Sep-2009



ASGLE212-10 BOLD:AAP6689 Guelph 43.554 -80.264 23-Sep-2009




159


ASGLE217-10 BOLD:AAA4782 Guelph 43.554 -80.264 23-Sep-2009




ASGLE222-10 BOLD:ABX6808 Guelph 43.554 -80.264 23-Sep-2009






ASGLE228-10 BOLD:ABY7565 Guelph 43.554 -80.264 23-Sep-2009
































160












































161

























ASGLE408-10 BOLD:AAN7643 Guelph 43.554 -80.264 16-May-2010



















162
















ASGLE447-10 BOLD:AAK3160 Guelph 43.554 -80.264 01-May-2010







ASGLE456-10 BOLD:AAB0892 Guelph 43.554 -80.264 01-May-2010


ASGLE466-10 BOLD:AAF0890 Guelph 43.554 -80.264 01-Nov-2009

ASGLE467-10 BOLD:ABY9254 Guelph 43.554 -80.264 01-Nov-2009

ASGLE468-10 BOLD:AAH7283 Guelph 43.554 -80.264 01-Nov-2009

ASGLE469-10 BOLD:ACE8629 Guelph 43.554 -80.264 01-Nov-2009

ASGLE470-10 BOLD:AAU8494 Guelph 43.554 -80.264 01-Nov-2009

ASGLE471-10 BOLD:AAA6280 Guelph 43.554 -80.264 01-Nov-2009

ASGLE472-10 BOLD:AAG7631 Guelph 43.554 -80.264 09-Oct-2009


ASGLE475-10 BOLD:AAU8495 Guelph 43.554 -80.264 09-Oct-2009











163




































ASGLE525-10 BOLD:ACF0492 Guelph 43.554 -80.264 16-May-2010








164





ASGLE540-10 BOLD:ACF3297 Guelph 43.554 -80.264 16-May-2010
























ASGLE571-10 BOLD:ABA6003 Guelph 43.554 -80.264 16-May-2010















165










































ASGLE659-10 BOLD:AAY6809 Guelph 43.554 -80.264 01-May-2010


166





ASGLE683-10 BOLD:AAM7181 Guelph 43.554 -80.264 01-Nov-2009

ASGLE684-10 BOLD:ACF1641 Guelph 43.554 -80.264 01-Nov-2009



ASGLE687-10 BOLD:AAQ0459 Guelph 43.554 -80.264 01-Nov-2009



ASGLE692-10 BOLD:AAG0783 Guelph 43.554 -80.264 01-Nov-2009




ASGLE697-10 BOLD:ACF3297 Guelph 43.554 -80.264 01-Nov-2009




ASGLE702-10 BOLD:ABX6808 Guelph 43.554 -80.264 01-Nov-2009

ASGLE704-10 BOLD:AAQ2960 Guelph 43.554 -80.264 09-Oct-2009







ASGLE715-10 BOLD:AAP2581 Guelph 43.554 -80.264 09-Oct-2009




ASGLE719-10 BOLD:AAM7494 Guelph 43.554 -80.264 09-Oct-2009

ASGLE720-10 BOLD:AAN8654 Guelph 43.554 -80.264 09-Oct-2009

ASGLE721-10 BOLD:AAD7584 Guelph 43.554 -80.264 09-Oct-2009




ASGLE725-10 BOLD:AAA4188 Guelph 43.554 -80.264 09-Oct-2009




ASGLE729-10 BOLD:ABX6808 Guelph 43.554 -80.264 09-Oct-2009


167



ASGLE733-10 BOLD:ACE7616 Guelph 43.554 -80.264 09-Oct-2009

ASGLE735-10 BOLD:AAA4188 Guelph 43.554 -80.264 09-Oct-2009

ASGLE766-10 BOLD:AAE2886 Guelph 43.554 -80.264 23-Sep-2009


ASGLE773-10 BOLD:AAG7679 Guelph 43.554 -80.264 01-Nov-2009






ASGLE802-10 BOLD:ACE9710 Guelph 43.554 -80.264 01-Aug-2010

ASGLE803-10 BOLD:AAH1872 Guelph 43.554 -80.264 01-Aug-2010





















ASGLE833-10 BOLD:AAB7105 Guelph 43.554 -80.264 14-Jul-2010



ASGLE836-10 BOLD:ACE4814 Guelph 43.554 -80.264 14-Jul-2010


ASGLE838-10 BOLD:AAH1872 Guelph 43.554 -80.264 14-Jul-2010

ASGLE839-10 BOLD:AAE5994 Guelph 43.554 -80.264 14-Jul-2010



168



ASGLE879-10 BOLD:ACE7616 Guelph 43.554 -80.264 01-Nov-2009


ASGLE882-10 BOLD:AAN8185 Guelph 43.554 -80.264 09-Oct-2009















ASGLE944-10 BOLD:ACH3189 Guelph 43.554 -80.264 01-Aug-2010









ASGLF009-11 BOLD:AAE2886 Guelph 43.554 -80.264 29-Oct-2010


ASGLF011-11 BOLD:AAG7670 Guelph 43.554 -80.264 29-Oct-2010

ASGLF012-11 BOLD:AAD5194 Guelph 43.554 -80.264 29-Oct-2010


ASGLF014-11 BOLD:AAH7259 Guelph 43.554 -80.264 29-Oct-2010



ASGLF030-11 BOLD:AAU8831 Guelph 43.554 -80.264 29-Oct-2010

ASGLF031-11 BOLD:AAQ2726 Guelph 43.554 -80.264 29-Oct-2010






169





ASGLF095-11 BOLD:AAA1839 Guelph 43.554 -80.264 29-Oct-2010

ASGLF096-11 BOLD:ABV2747 Guelph 43.554 -80.264 29-Oct-2010





ASGLF101-11 BOLD:AAP2581 Guelph 43.554 -80.264 29-Oct-2010



ASGLF144-11 BOLD:AAN8216 Guelph 43.554 -80.264 29-Oct-2010

ASGLF145-11 BOLD:ABX2612 Guelph 43.554 -80.264 29-Oct-2010






ASGLF156-11 BOLD:ABA6172 Guelph 43.554 -80.264 29-Oct-2010


ASGLF158-11 BOLD:AAM7181 Guelph 43.554 -80.264 29-Oct-2010


ASGLF160-11 BOLD:AAO2111 Guelph 43.554 -80.264 29-Oct-2010


ASGLF163-11 BOLD:AAQ2898 Guelph 43.554 -80.264 29-Oct-2010


ASGLF165-11 BOLD:ACF0461 Guelph 43.554 -80.264 29-Oct-2010


ASGLF167-11 BOLD:AAC5506 Guelph 43.554 -80.264 29-Oct-2010













170




ASGLF274-11 BOLD:AAZ3285 Guelph 43.554 -80.264 29-Oct-2010


ASGLF277-11 BOLD:ABZ2589 Guelph 43.554 -80.264 29-Oct-2010





ASGLF282-11 BOLD:AAP6703 Guelph 43.554 -80.264 29-Oct-2010







ASGLF393-11 BOLD:ACE5710 Guelph 43.554 -80.264 29-Oct-2010




ASGLF401-11 BOLD:ABW3274 Guelph 43.554 -80.264 29-Oct-2010









ASGLF411-11 BOLD:AAY6848 Guelph 43.554 -80.264 29-Oct-2010




ASGLF415-11 BOLD:ABV9378 Guelph 43.554 -80.264 29-Oct-2010

ASGLF416-11 BOLD:AAZ0182 Guelph 43.554 -80.264 18-Nov-2010

ASGLF417-11 BOLD:AAU8205 Guelph 43.554 -80.264 18-Nov-2010

ASGLF418-11 BOLD:AAC3876 Guelph 43.554 -80.264 18-Nov-2010






171


ASGLF425-11 BOLD:AAG9191 Guelph 43.554 -80.264 18-Nov-2010




ASGLF431-11 BOLD:AAA4188 Guelph 43.554 -80.264 18-Nov-2010

ASGLF432-11 BOLD:ABA8022 Guelph 43.554 -80.264 18-Nov-2010


ASGLF435-11 BOLD:ABX6808 Guelph 43.554 -80.264 18-Nov-2010

ASGLF436-11 BOLD:ACE4111 Guelph 43.554 -80.264 18-Nov-2010




ASGLF446-11 BOLD:ACD5180 Guelph 43.554 -80.264 18-Nov-2010

ASGLF447-11 BOLD:AAM9117 Guelph 43.554 -80.264 18-Nov-2010



ASGLE458-10 BOLD:AAG3194 Haldimond-

Dunn Townline

42.861 -79.703 20-Sep-2009


Dunn Townline

42.861 -79.703 20-Sep-2009

ASGLE462-10 BOLD:AAU8684 Haldimond-

Dunn Townline

42.861 -79.703 20-Sep-2009

ASGLE463-10 BOLD:AAH2006 Haldimond-

Dunn Townline

42.861 -79.703 20-Sep-2009

ASGLE464-10 BOLD:AAD4214 Haldimond-

Dunn Townline

42.861 -79.703 20-Sep-2009


Dunn Townline

42.861 -79.703 20-Sep-2009


Dunn Townline

42.861 -79.703 20-Sep-2009

ASGLE668-10 BOLD:ABZ7618 Haldimond-

Dunn Townline

42.861 -79.703 20-Sep-2009

ASGLE669-10 BOLD:AAE9438 Haldimond-

Dunn Townline

42.861 -79.703 20-Sep-2009

ASGLE670-10 BOLD:AAU8687 Haldimond- 42.861 -79.703 20-Sep-2009

172

Dunn Townline

ASGLE671-10 BOLD:AAC2392 Haldimond-

Dunn Townline

42.861 -79.703 20-Sep-2009


Dunn Townline

42.861 -79.703 20-Sep-2009


Dunn Townline

42.861 -79.703 20-Sep-2009


Dunn Townline

42.861 -79.703 20-Sep-2009


Dunn Townline

42.861 -79.703 20-Sep-2009


Dunn Townline

42.861 -79.703 20-Sep-2009


Dunn Townline

42.861 -79.703 20-Sep-2009


Dunn Townline

42.861 -79.703 03-Oct-2009


Dunn Townline

42.861 -79.703 03-Oct-2009


Dunn Townline

42.861 -79.703 03-Oct-2009

ASGLE747-10 BOLD:AAN8194 Haldimond-

Dunn Townline

42.861 -79.703 03-Oct-2009


Dunn Townline

42.861 -79.703 03-Oct-2009


Dunn Townline

42.861 -79.703 03-Oct-2009


Dunn Townline

42.861 -79.703 03-Oct-2009


Dunn Townline

42.861 -79.703 03-Oct-2009

173


Dunn Townline

42.861 -79.703 03-Oct-2009


Dunn Townline

42.861 -79.703 03-Oct-2009


Dunn Townline

42.861 -79.703 03-Oct-2009


Dunn Townline

42.861 -79.703 03-Oct-2009


Dunn Townline

42.861 -79.703 03-Oct-2009

ASGLE758-10 BOLD:ABZ2589 Haldimond-

Dunn Townline

42.861 -79.703 03-Oct-2009


Dunn Townline

42.861 -79.703 03-Oct-2009

ASGLE760-10 BOLD:AAN8194 Haldimond-

Dunn Townline

42.861 -79.703 03-Oct-2009


Dunn Townline

42.861 -79.703 20-Sep-2009

ASGLE769-10 BOLD:ACE4814 Haldimond-

Dunn Townline

42.861 -79.703 20-Sep-2009


Dunn Townline

42.861 -79.703 20-Sep-2009


Dunn Townline

42.861 -79.703 20-Sep-2009


Dunn Townline

42.861 -79.703 03-Oct-2009

ASGLE856-10 BOLD:AAP6689 Haldimond-

Dunn Townline

42.861 -79.703 20-Sep-2009


Dunn Townline

42.861 -79.703 20-Sep-2009


Dunn 42.861 -79.703 20-Sep-2009

174

Townline


Dunn Townline

42.861 -79.703 20-Sep-2009


Dunn Townline

42.861 -79.703 20-Sep-2009


Dunn Townline

42.861 -79.703 20-Sep-2009

ASGLE863-10 BOLD:AAF5747 Haldimond-

Dunn Townline

42.861 -79.703 20-Sep-2009


Dunn Townline

42.861 -79.703 20-Sep-2009


Dunn Townline

42.861 -79.703 20-Sep-2009

ASGLE866-10 BOLD:ACH5153 Haldimond-

Dunn Townline

42.861 -79.703 20-Sep-2009

ASGLE867-10 BOLD:AAM7487 Haldimond-

Dunn Townline

42.861 -79.703 20-Sep-2009

ASGLE869-10 BOLD:ACE4000 Haldimond-

Dunn Townline

42.861 -79.703 20-Sep-2009


Dunn Townline

42.861 -79.703 20-Sep-2009


Dunn Townline

42.861 -79.703 03-Oct-2009


Dunn Townline

42.861 -79.703 03-Oct-2009


Dunn Townline

42.861 -79.703 03-Oct-2009


Dunn Townline

42.861 -79.703 03-Oct-2009


Dunn Townline

42.861 -79.703 03-Oct-2009

ASGLE914-10 BOLD:AAG0775 Haldimond- 42.861 -79.703 03-Oct-2009

175

Dunn Townline


Dunn Townline

42.861 -79.703 03-Oct-2009


Dunn Townline

42.861 -79.703 03-Oct-2009


Dunn Townline

42.861 -79.703 03-Oct-2009

ASGLE955-10 BOLD:AAD4214 Haldimond-

Dunn Townline

42.861 -79.703 03-Oct-2009

ASGLF005-11 BOLD:AAG7674 Haldimond-

Dunn Townline

42.861 -79.703 21-Nov-2010

ASGLF006-11 BOLD:AAA9338 Haldimond-

Dunn Townline

42.861 -79.703 21-Nov-2010

ASGLF007-11 BOLD:AAH7259 Haldimond-

Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 19-Sep-2010

ASGLF018-11 BOLD:ACF3458 Haldimond-

Dunn Townline

42.861 -79.703 19-Sep-2010

ASGLF021-11 BOLD:AAB0892 Haldimond-

Dunn Townline

42.861 -79.703 19-Sep-2010

ASGLF025-11 BOLD:ACE4814 Haldimond-

Dunn Townline

42.861 -79.703 01-Aug-2010

ASGLF026-11 BOLD:AAD9441 Haldimond-

Dunn Townline

42.861 -79.703 01-Aug-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 21-Nov-2010

176


Dunn Townline

42.861 -79.703 21-Nov-2010

ASGLF037-11 BOLD:ABA6167 Haldimond-

Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010

ASGLF040-11 BOLD:AAN4205 Haldimond-

Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010

ASGLF043-11 BOLD:ABZ4364 Haldimond-

Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn 42.861 -79.703 21-Nov-2010

177

Townline

ASGLF052-11 BOLD:AAY6849 Haldimond-

Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010

ASGLF056-11 BOLD:AAP2581 Haldimond-

Dunn Townline

42.861 -79.703 21-Nov-2010

ASGLF057-11 BOLD:AAL8266 Haldimond-

Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010

ASGLF068-11 BOLD:ABA6164 Haldimond- 42.861 -79.703 21-Nov-2010

178

Dunn Townline


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010

ASGLF083-11 BOLD:AAC3244 Haldimond-

Dunn Townline

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Dunn Townline

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179

ASGLF102-11 BOLD:ABW3143 Haldimond-

Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010

ASGLF112-11 BOLD:AAU8205 Haldimond-

Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn 42.861 -79.703 21-Nov-2010

180

Townline


Dunn Townline

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Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010

ASGLF126-11 BOLD:ABX2610 Haldimond-

Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010

ASGLF137-11 BOLD:ABV9383 Haldimond- 42.861 -79.703 21-Nov-2010

181

Dunn Townline


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 21-Nov-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010

ASGLF181-11 BOLD:ABV5679 Haldimond-

Dunn Townline

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182


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010

ASGLF184-11 BOLD:ABY8933 Haldimond-

Dunn Townline

42.861 -79.703 19-Sep-2010

ASGLF185-11 BOLD:AAF8320 Haldimond-

Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 23-Oct-2010


Dunn Townline

42.861 -79.703 23-Oct-2010


Dunn Townline

42.861 -79.703 23-Oct-2010


Dunn Townline

42.861 -79.703 23-Oct-2010


Dunn Townline

42.861 -79.703 23-Oct-2010


Dunn 42.861 -79.703 01-Aug-2010

183

Townline


Dunn Townline

42.861 -79.703 01-Aug-2010


Dunn Townline

42.861 -79.703 01-Aug-2010


Dunn Townline

42.861 -79.703 01-Aug-2010


Dunn Townline

42.861 -79.703 01-Aug-2010


Dunn Townline

42.861 -79.703 01-Aug-2010


Dunn Townline

42.861 -79.703 01-Aug-2010


Dunn Townline

42.861 -79.703 01-Aug-2010


Dunn Townline

42.861 -79.703 01-Aug-2010

ASGLF215-11 BOLD:AAZ0238 Haldimond-

Dunn Townline

42.861 -79.703 01-Aug-2010


Dunn Townline

42.861 -79.703 01-Aug-2010


Dunn Townline

42.861 -79.703 01-Aug-2010


Dunn Townline

42.861 -79.703 01-Aug-2010


Dunn Townline

42.861 -79.703 01-Aug-2010


Dunn Townline

42.861 -79.703 01-Aug-2010

ASGLF222-11 BOLD:ABV2673 Haldimond-

Dunn Townline

42.861 -79.703 01-Aug-2010

ASGLF224-11 BOLD:AAG1429 Haldimond- 42.861 -79.703 12-Sep-2010

184

Dunn Townline


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

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Dunn Townline

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185


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010

ASGLF247-11 BOLD:AAW0433 Haldimond-

Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn 42.861 -79.703 19-Sep-2010

186

Townline


Dunn Townline

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Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010

ASGLF329-11 BOLD:AAP6716 Haldimond- 42.861 -79.703 19-Sep-2010

187

Dunn Townline


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 19-Sep-2010


Dunn Townline

42.861 -79.703 23-Oct-2010


Dunn Townline

42.861 -79.703 23-Oct-2010


Dunn Townline

42.861 -79.703 23-Oct-2010


Dunn Townline

42.861 -79.703 01-Aug-2010

188


Dunn Townline

42.861 -79.703 01-Aug-2010


Dunn Townline

42.861 -79.703 01-Aug-2010


Dunn Townline

42.861 -79.703 01-Aug-2010


Dunn Townline

42.861 -79.703 01-Aug-2010


Dunn Townline

42.861 -79.703 01-Aug-2010


Dunn Townline

42.861 -79.703 01-Aug-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010

ASGLF372-11 BOLD:AAM7500 Haldimond-

Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn 42.861 -79.703 12-Sep-2010

189

Townline


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010

ASGLF377-11 BOLD:ACK5169 Haldimond-

Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010

ASGLF388-11 BOLD:ACL1491 Haldimond-

Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010

ASGLF391-11 BOLD:ACF4040 Haldimond- 42.861 -79.703 12-Sep-2010

190

Dunn Townline


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010


Dunn Townline

42.861 -79.703 12-Sep-2010

ASAHY001-12 BOLD:AAG8112 Wilberforce 45.633 -77.07 26-Jun-2011






ASAHY009-12 BOLD:AAD5193 Wilberforce 45.633 -77.07 26-Jun-2011

ASAHY010-12 BOLD:AAW5213 Wilberforce 45.633 -77.07 26-Jun-2011



ASAHY014-12 BOLD:ACL7957 Wilberforce 45.633 -77.07 26-Jun-2011

ASAHY015-12 BOLD:AAU8388 Wilberforce 45.633 -77.07 26-Jun-2011





ASAHY022-12 BOLD:AAC9245 Wilberforce 45.633 -77.07 26-Jun-2011



ASAHY025-12 BOLD:AAH1922 Wilberforce 45.633 -77.07 26-Jun-2011


ASAHY027-12 BOLD:ABZ1196 Wilberforce 45.633 -77.07 26-Jun-2011






191


ASAHY034-12 BOLD:AAN7586 Wilberforce 45.633 -77.07 26-Jun-2011




ASAHY041-12 BOLD:ABX9742 Wilberforce 45.633 -77.07 26-Jun-2011











ASAHY053-12 BOLD:ABY1200 Wilberforce 45.633 -77.07 26-Jun-2011







ASAHY072-12 BOLD:AAI6272 Wilberforce 45.633 -77.07 26-Jun-2011

ASAHY074-12 BOLD:AAA4785 Wilberforce 45.633 -77.07 26-Jun-2011

ASAHY076-12 BOLD:AAK8152 Wilberforce 45.633 -77.07 26-Jun-2011



ASAHY079-12 BOLD:ACE4233 Wilberforce 45.633 -77.07 26-Jun-2011



ASAHY082-12 BOLD:AAB0096 Wilberforce 45.633 -77.07 26-Jun-2011









ASAHY115-13 BOLD:AAE8158 Wilberforce 45.508 -76.974 10-Jul-2011

ASAHY116-13 BOLD:AAG8062 Wilberforce 45.508 -76.974 10-Jul-2011

ASAHY117-13 BOLD:ACE4814 Wilberforce 45.508 -76.974 10-Jul-2011

192

ASAHY119-13 BOLD:AAC5428 Wilberforce 45.508 -76.974 10-Jul-2011





ASAHY126-13 BOLD:AAU8388 Wilberforce 45.508 -76.974 10-Jul-2011




ASAHY130-13 BOLD:AAM7367 Wilberforce 45.508 -76.974 10-Jul-2011

ASAHY131-13 BOLD:ACF2807 Wilberforce 45.508 -76.974 10-Jul-2011





ASAHY136-13 BOLD:AAD5192 Wilberforce 45.508 -76.974 10-Jul-2011






ASAHY142-13 BOLD:ABV2753 Wilberforce 45.508 -76.974 10-Jul-2011












ASAHY158-13 BOLD:AAA9338 Wilberforce 45.508 -76.974 10-Jul-2011

ASAHY160-13 BOLD:AAQ0401 Wilberforce 45.508 -76.974 10-Jul-2011

ASAHY161-13 BOLD:ABZ1196 Wilberforce 45.508 -76.974 10-Jul-2011


ASAHY163-13 BOLD:ABX5695 Wilberforce 45.508 -76.974 10-Jul-2011


ASAHY165-13 BOLD:ABY7035 Wilberforce 45.508 -76.974 10-Jul-2011



ASAHY168-13 BOLD:ACC6514 Wilberforce 45.508 -76.974 10-Jul-2011

193



ASAHY171-13 BOLD:AAH1767 Wilberforce 45.508 -76.974 10-Jul-2011




ASAHY177-13 BOLD:AAX9662 Wilberforce 45.508 -76.974 10-Jul-2011








ASAHY187-13 BOLD:ACB8141 Wilberforce 45.508 -76.974 10-Jul-2011



ASAHY195-13 BOLD:AAY6828 Wilberforce 45.508 -76.974 10-Jul-2011

ASAHY198-13 BOLD:AAY6828 Wilberforce 45.508 -76.974 10-Jul-2011



ASAHY211-13 BOLD:ACL5973 Wilberforce 45.508 -76.974 10-Jul-2011

ASAHY212-13 BOLD:ABA6048 Wilberforce 45.508 -76.974 10-Jul-2011


ASAHY214-13 BOLD:ACA7696 Wilberforce 45.508 -76.974 10-Jul-2011






ASAHY703-13 BOLD:ABW8198 Wilberforce 45.5075 -76.9742 12-Oct-2012

ASAHY704-13 BOLD:AAU8831 Wilberforce 45.5075 -76.9742 12-Oct-2012

ASAHY705-13 BOLD:AAE2749 Wilberforce 45.5075 -76.9742 12-Oct-2012

ASAHY706-13 BOLD:AAD5193 Wilberforce 45.5075 -76.9742 12-Oct-2012

ASAHY707-13 BOLD:AAG7634 Wilberforce 45.5075 -76.9742 12-Oct-2012

ASAHY708-13 BOLD:AAD8806 Wilberforce 45.5075 -76.9742 12-Oct-2012



ASAHY711-13 BOLD:ACL6499 Wilberforce 45.5075 -76.9742 12-Oct-2012

ASAHY712-13 BOLD:ACH0541 Wilberforce 45.5075 -76.9742 12-Oct-2012


ASAHY714-13 BOLD:AAC3220 Wilberforce 45.5075 -76.9742 12-Oct-2012


194

ASAHY716-13 BOLD:ACG4574 Wilberforce 45.5075 -76.9742 12-Oct-2012

ASGLE1046-10 BOLD:AAU8643 Wilberforce 45.509 -76.676 25-Jul-2010

ASGLE1048-10 BOLD:AAE8196 Wilberforce 45.509 -76.676 25-Jul-2010


ASGLE1050-10 BOLD:ACE4571 Wilberforce 45.509 -76.676 25-Jul-2010


ASGLE1052-10 BOLD:AAF4431 Wilberforce 45.509 -76.676 25-Jul-2010





ASGLE1060-10 BOLD:AAG8211 Wilberforce 45.509 -76.676 25-Jul-2010




ASGLE1066-10 BOLD:AAM7454 Wilberforce 45.509 -76.676 25-Jul-2010

ASGLE1067-10 BOLD:AAI6268 Wilberforce 45.509 -76.676 25-Jul-2010


ASGLE1070-10 BOLD:AAA9049 Wilberforce 45.509 -76.676 25-Jul-2010



ASGLE1073-10 BOLD:AAG7797 Wilberforce 45.509 -76.676 01-Aug-2010

ASGLE1074-10 BOLD:AAU8624 Wilberforce 45.509 -76.676 01-Aug-2010

ASGLE1075-10 BOLD:AAM7437 Wilberforce 45.509 -76.676 01-Aug-2010





ASGLE1081-10 BOLD:AAH7274 Wilberforce 45.509 -76.676 01-Aug-2010





ASGLE1086-10 BOLD:AAA1865 Wilberforce 45.509 -76.676 01-Aug-2010



ASGLE1282-10 BOLD:AAA9461 Wilberforce 45.509 -76.676 28-Jun-2010

ASGLE1283-10 BOLD:AAD5192 Wilberforce 45.509 -76.676 28-Jun-2010

ASGLE1284-10 BOLD:AAU8228 Wilberforce 45.509 -76.676 28-Jun-2010


ASGLE1286-10 BOLD:AAQ2728 Wilberforce 45.509 -76.676 28-Jun-2010

ASGLE1287-10 BOLD:AAE5993 Wilberforce 45.509 -76.676 28-Jun-2010

ASGLE1289-10 BOLD:ABX5695 Wilberforce 45.509 -76.676 28-Jun-2010

195




ASGLE1293-10 BOLD:AAG0387 Wilberforce 45.509 -76.676 28-Jun-2010



ASGLE1296-10 BOLD:ABZ1196 Wilberforce 45.509 -76.676 07-Jun-2010

ASGLE1297-10 BOLD:AAH7266 Wilberforce 45.509 -76.676 07-Jun-2010


ASGLE1299-10 BOLD:ABY7035 Wilberforce 45.509 -76.676 07-Jun-2010





ASGLE1304-10 BOLD:AAM7422 Wilberforce 45.509 -76.676 07-Jun-2010

ASGLE1305-10 BOLD:AAU8228 Wilberforce 45.509 -76.676 26-Apr-2010



ASGLE1310-10 BOLD:AAG9189 Wilberforce 45.509 -76.676 26-Apr-2010




ASGLE1315-10 BOLD:ABY4114 Wilberforce 45.509 -76.676 26-Apr-2010

ASGLE1316-10 BOLD:ACE9530 Wilberforce 45.509 -76.676 16-May-2010

ASGLE1317-10 BOLD:AAG3520 Wilberforce 45.509 -76.676 16-May-2010

ASGLE1318-10 BOLD:AAU8228 Wilberforce 45.509 -76.676 16-May-2010

ASGLE1319-10 BOLD:AAD5193 Wilberforce 45.509 -76.676 16-May-2010



ASGLE1322-10 BOLD:AAD8806 Wilberforce 45.509 -76.676 11-Apr-2010



ASGLE1325-10 BOLD:AAK7840 Wilberforce 45.509 -76.676 11-Apr-2010











196







ASGLE1388-10 BOLD:AAF0572 Wilberforce 45.509 -76.676 07-Jun-2010






ASGLE1395-10 BOLD:ACF2697 Wilberforce 45.509 -76.676 26-Apr-2010




ASGLE1399-10 BOLD:ACE3610 Wilberforce 45.509 -76.676 26-Apr-2010








ASGLE1419-10 BOLD:ABZ2750 Wilberforce 45.509 -76.676 31-May-2010

ASGLE1420-10 BOLD:AAH9668 Wilberforce 45.509 -76.676 31-May-2010






ASGLE1426-10 BOLD:AAC3220 Wilberforce 45.509 -76.676 07-Jun-2010

ASGLE1427-10 BOLD:AAN5130 Wilberforce 45.509 -76.676 07-Jun-2010






ASGLE1433-10 BOLD:ACE6874 Wilberforce 45.509 -76.676 07-Jun-2010





197


ASGLE1446-10 BOLD:ABX5161 Wilberforce 45.509 -76.676 26-Apr-2010



ASGLE1449-10 BOLD:AAA9049 Wilberforce 45.509 -76.676 26-Apr-2010


ASGLE1451-10 BOLD:AAM7500 Wilberforce 45.509 -76.676 16-May-2010







ASGLE1458-10 BOLD:ACF4570 Wilberforce 45.509 -76.676 16-May-2010

ASGLE1461-10 BOLD:ABY6861 Wilberforce 45.509 -76.676 16-May-2010





ASGLE1467-10 BOLD:ABX5161 Wilberforce 45.509 -76.676 16-May-2010





ASGLE1503-10 BOLD:AAA7636 Wilberforce 45.509 -76.676 31-May-2010



















198









ASGLE1531-10 BOLD:AAI3361 Wilberforce 45.509 -76.676 26-Apr-2010




ASGLE1536-10 BOLD:AAN7826 Wilberforce 45.509 -76.676 16-May-2010











ASGLE1563-10 BOLD:AAI6347 Wilberforce 45.509 -76.676 31-May-2010




ASGLE1568-10 BOLD:ACB3312 Wilberforce 45.509 -76.676 02-May-2010








ASGLE1576-10 BOLD:AAQ2726 Wilberforce 45.509 -76.676 24-May-2010

ASGLE1577-10 BOLD:AAF4878 Wilberforce 45.509 -76.676 24-May-2010



ASGLE1581-10 BOLD:ACF2807 Wilberforce 45.509 -76.676 24-May-2010


ASGLE1583-10 BOLD:AAI3087 Wilberforce 45.509 -76.676 24-May-2010


199






ASGLE1591-10 BOLD:AAH7266 Wilberforce 45.509 -76.676 12-Jul-2010

ASGLE1592-10 BOLD:AAQ2728 Wilberforce 45.509 -76.676 12-Jul-2010





ASGLE1608-10 BOLD:ACI4751 Wilberforce 45.509 -76.676 21-Jun-2010


ASGLE1611-10 BOLD:AAL0380 Wilberforce 45.509 -76.676 14-Jun-2010







ASGLE1634-10 BOLD:ACL7957 Wilberforce 45.509 -76.676 31-May-2010


ASGLE1636-10 BOLD:AAE5994 Wilberforce 45.509 -76.676 31-May-2010


ASGLE1638-10 BOLD:ACI3231 Wilberforce 45.509 -76.676 31-May-2010














ASGLE1654-10 BOLD:AAK7840 Wilberforce 45.509 -76.676 02-May-2010


ASGLE1656-10 BOLD:ACF2807 Wilberforce 45.509 -76.676 18-Apr-2010



200













ASGLE1676-10 BOLD:AAL5084 Wilberforce 45.509 -76.676 24-May-2010



















ASGLE1717-10 BOLD:ACD0299 Wilberforce 45.509 -76.676 02-May-2010


ASGLE1719-10 BOLD:AAP6710 Wilberforce 45.509 -76.676 02-May-2010

ASGLE1720-10 BOLD:AAB1188 Wilberforce 45.509 -76.676 18-Apr-2010

ASGLE1722-10 BOLD:ACD0281 Wilberforce 45.509 -76.676 18-Apr-2010



ASGLE1725-10 BOLD:ACB2486 Wilberforce 45.509 -76.676 24-May-2010





201


ASGLE1731-10 BOLD:ACD0369 Wilberforce 45.509 -76.676 12-Jul-2010

ASGLE1732-10 BOLD:ACC4158 Wilberforce 45.509 -76.676 12-Jul-2010

ASGLE1733-10 BOLD:ABA8012 Wilberforce 45.509 -76.676 12-Jul-2010

ASGLE1734-10 BOLD:ABY4229 Wilberforce 45.509 -76.676 12-Jul-2010


ASGLE1755-10 BOLD:ACC7201 Wilberforce 45.509 -76.676 21-Jun-2010

ASGLE1756-10 BOLD:ABA6048 Wilberforce 45.509 -76.676 21-Jun-2010


ASGLE1758-10 BOLD:AAB0520 Wilberforce 45.509 -76.676 21-Jun-2010



ASGLE1761-10 BOLD:ACD0383 Wilberforce 45.509 -76.676 21-Jun-2010






ASGLE1769-10 BOLD:ACB2486 Wilberforce 45.509 -76.676 14-Jun-2010








ASGLE1778-10 BOLD:ACB2527 Wilberforce 45.509 -76.676 05-Jul-2010




ASGLE1782-10 BOLD:AAZ0143 Wilberforce 45.509 -76.676 31-May-2010













202



















ASGLE1817-10 BOLD:AAZ0146 Wilberforce 45.509 -76.676 12-Jul-2010














ASGLE1852-10 BOLD:ACK2153 Wilberforce 45.509 -76.676 05-Jul-2010

ASGLE1853-10 BOLD:AAN5120 Wilberforce 45.509 -76.676 05-Jul-2010



ASGLE1856-10 BOLD:ACH3787 Wilberforce 45.509 -76.676 21-Jun-2010







203









ASGLE1871-10 BOLD:AAI5894 Wilberforce 45.509 -76.676 14-Jun-2010



ASGLE1874-10 BOLD:AAX8143 Wilberforce 45.509 -76.676 05-Jul-2010





ASGLE1879-11 BOLD:AAY6832 Wilberforce 45.509 -76.676 05-Jul-2010








ASGLE1887-11 BOLD:AAW5213 Wilberforce 45.509 -76.676 05-Jul-2010







ASGLE1895-11 BOLD:AAD5192 Wilberforce 45.509 -76.676 05-Jul-2010










ASGLE795-10 BOLD:AAQ2723 Wilberforce 45.509 -76.676 01-Aug-2010


204


ASGLE798-10 BOLD:ACE8616 Wilberforce 45.509 -76.676 01-Aug-2010










ASGLE853-10 BOLD:AAO1444 Wilberforce 45.509 -76.676 28-Jun-2010



ASGLE916-10 BOLD:AAP6709 Wilberforce 45.509 -76.676 25-Jul-2010






ASGLE927-10 BOLD:AAP6712 Wilberforce 45.509 -76.676 01-Aug-2010





ASGLE933-10 BOLD:AAM7502 Wilberforce 45.509 -76.676 01-Aug-2010

ASGLE934-10 BOLD:AAA4785 Wilberforce 45.509 -76.676 01-Aug-2010

















205

ASGLE972-10 BOLD:AAB0185 Wilberforce 45.509 -76.676 25-Jul-2010






ASGLE978-10 BOLD:AAJ9641 Wilberforce 45.509 -76.676 01-Aug-2010



ASGLE983-10 BOLD:AAF2914 Wilberforce 45.509 -76.676 01-Aug-2010




ASGLE988-10 BOLD:ABZ1196 Wilberforce 45.509 -76.676 01-Aug-2010




ASGLE993-10 BOLD:AAD8806 Wilberforce 45.509 -76.676 01-Aug-2010



ASGLF015-11 BOLD:AAG8144 Wilberforce 45.509 -76.676 19-Sep-2010

ASGLF016-11 BOLD:AAD5192 Wilberforce 45.509 -76.676 19-Sep-2010

ASGLF022-11 BOLD:AAG7742 Wilberforce 45.509 -76.676 09-Oct-2010

ASGLF023-11 BOLD:AAD5193 Wilberforce 45.509 -76.676 09-Oct-2010




ASGLF195-11 BOLD:AAU9319 Wilberforce 45.509 -76.676 09-Oct-2010


ASGLF197-11 BOLD:ACF2973 Wilberforce 45.509 -76.676 05-Sep-2010



ASGLF200-11 BOLD:ABZ2750 Wilberforce 45.509 -76.676 05-Sep-2010

ASGLF341-11 BOLD:ABA8034 Wilberforce 45.509 -76.676 09-Oct-2010

ASGLF343-11 BOLD:AAM7512 Wilberforce 45.509 -76.676 09-Oct-2010

ASGLF344-11 BOLD:AAU9229 Wilberforce 45.509 -76.676 09-Oct-2010

ASGLF350-11 BOLD:AAD4306 Wilberforce 45.509 -76.676 05-Sep-2010

ASGLF351-11 BOLD:AAB1188 Wilberforce 45.509 -76.676 05-Sep-2010

ASGLF352-11 BOLD:AAC6952 Wilberforce 45.509 -76.676 05-Sep-2010

206

APPENDIX 2. Chapter 2 – Specimen list for the randomly sampled subset (2240). Information

is sorted in alphabetical order of collection site name.

Process ID BIN Site Latitude Longitude Collection

Date

ASAHY202-13 BOLD:AAI5894 Algonquin Park 46.058 -78.484 12-Jul-2011

ASAHY224-13 BOLD:AAG7687 Algonquin Park 45.718 -77.81 13-Jul-2011



ASAHY235-13 BOLD:AAM7454 Algonquin Park 45.897 -77.735 11-Jul-2011

ASAHY237-13 BOLD:ACC7189 Algonquin Park 45.897 -77.735 11-Jul-2011


ASAHY240-13 BOLD:AAU8213 Algonquin Park 45.524 -78.422 08-Jul-2011















ASAHY275-13 BOLD:AAD5193 Algonquin Park 46.058 -78.484 12-Jul-2011



ASAHY286-13 BOLD:ABX6558 Algonquin Park 46.058 -78.484 12-Jul-2011


ASAHY288-13 BOLD:ACB2170 Algonquin Park 46.058 -78.484 12-Jul-2011


ASAHY292-13 BOLD:AAC3876 Algonquin Park 46.058 -78.484 12-Jul-2011


ASAHY294-13 BOLD:AAB0192 Algonquin Park 46.058 -78.484 12-Jul-2011

ASAHY295-13 BOLD:AAF0483 Algonquin Park 46.058 -78.484 12-Jul-2011






207



ASAHY321-13 BOLD:AAY6820 Algonquin Park 46.058 -78.484 12-Jul-2011




ASAHY332-13 BOLD:AAJ5372 Algonquin Park 46.058 -78.484 12-Jul-2011

ASAHY334-13 BOLD:ABW2905 Algonquin Park 46.058 -78.484 12-Jul-2011


ASAHY341-13 BOLD:AAN7578 Algonquin Park 46.058 -78.484 12-Jul-2011




ASAHY352-13 BOLD:ACL6033 Algonquin Park 46.058 -78.484 12-Jul-2011

ASAHY353-13 BOLD:ABA6048 Algonquin Park 46.058 -78.484 12-Jul-2011




ASAHY374-13 BOLD:ACA8377 Algonquin Park 46.058 -78.484 12-Jul-2011









ASAHY400-13 BOLD:AAH3192 Algonquin Park 45.523 -78.422 13-Jul-2011











ASAHY432-13 BOLD:AAK2038 Algonquin Park 46.058 -78.484 12-Jul-2011





208


ASAHY450-13 BOLD:ACL6033 Algonquin Park 45.897 -77.735 11-Jul-2011











ASAHY473-13 BOLD:ACH0655 Algonquin Park 45.897 -77.735 11-Jul-2011


ASAHY482-13 BOLD:ACE2897 Algonquin Park 45.46 -78.796 09-Jul-2011


ASAHY497-13 BOLD:AAA7636 Algonquin Park 45.897 -77.735 05-Jul-2011

ASAHY499-13 BOLD:ACD1925 Algonquin Park 45.897 -77.735 11-Jul-2011


ASAHY505-13 BOLD:ABX5695 Algonquin Park 45.718 -77.81 13-Jul-2011

















ASAHY545-13 BOLD:ACE9710 Algonquin Park 45.633 -77.07 08-Aug-2011

ASAHY546-13 BOLD:AAU8831 Algonquin Park 45.633 -77.07 08-Aug-2011

ASAHY549-13 BOLD:AAG7661 Algonquin Park 45.633 -77.07 08-Aug-2011

ASAHY550-13 BOLD:AAY6794 Algonquin Park 45.633 -77.07 08-Aug-2011


ASAHY558-13 BOLD:AAA5524 Algonquin Park 45.633 -77.07 08-Aug-2011


209

ASAHY561-13 BOLD:ACD1793 Algonquin Park 45.633 -77.07 08-Aug-2011

ASAHY562-13 BOLD:AAH1693 Algonquin Park 45.633 -77.07 29-May-2011

ASAHY563-13 BOLD:AAG7736 Algonquin Park 45.633 -77.07 29-May-2011

ASAHY565-13 BOLD:AAH7266 Algonquin Park 45.633 -77.07 29-May-2011

ASAHY566-13 BOLD:AAG0387 Algonquin Park 45.633 -77.07 29-May-2011

ASAHY569-13 BOLD:AAD8806 Algonquin Park 45.633 -77.07 01-May-2011

ASAHY571-13 BOLD:ACE6264 Algonquin Park 45.633 -77.07 01-May-2011

ASAHY578-13 BOLD:AAU8584 Algonquin Park 45.6334 -77.6182 26-Nov-2012



ASAHY588-13 BOLD:AAG9172 Algonquin Park 45.6334 -77.0697 08-Apr-2012

ASAHY589-13 BOLD:AAD5192 Algonquin Park 45.6334 -77.0697 08-Apr-2012

ASAHY590-13 BOLD:AAM7450 Algonquin Park 45.6334 -77.0697 08-Apr-2012


ASAHY596-13 BOLD:AAD5193 Algonquin Park 45.6334 -77.0697 08-Apr-2012

ASAHY598-13 BOLD:AAM7439 Algonquin Park 45.6334 -77.0697 08-Apr-2012


ASAHY600-13 BOLD:ACH0635 Algonquin Park 45.6334 -77.0697 08-Apr-2012



ASAHY604-13 BOLD:ACH0262 Algonquin Park 45.6334 -77.0697 08-Apr-2012



ASAHY607-13 BOLD:AAH7288 Algonquin Park 45.6334 -77.0697 24-Sep-2012

ASAHY609-13 BOLD:AAG7721 Algonquin Park 45.6334 -77.0697 24-Sep-2012

ASAHY610-13 BOLD:AAC9246 Algonquin Park 45.6334 -77.0697 24-Sep-2012

ASAHY611-13 BOLD:AAG7654 Algonquin Park 45.6334 -77.0697 24-Sep-2012


ASAHY617-13 BOLD:AAU8679 Algonquin Park 45.6334 -77.6182 08-Apr-2012

ASAHY621-13 BOLD:ABZ5161 Algonquin Park 45.6334 -77.6182 08-Apr-2012


ASAHY623-13 BOLD:AAK3185 Algonquin Park 45.6334 -77.6182 08-Apr-2012

ASAHY626-13 BOLD:AAW9549 Algonquin Park 45.6334 -77.6182 08-Apr-2012








ASAHY641-13 BOLD:ABZ1196 Algonquin Park 45.7604 -77.8893 19-Jul-2012



210


ASAHY648-13 BOLD:ACF1442 Algonquin Park 45.7182 -77.811 19-Jul-2012


ASAHY650-13 BOLD:ABA6048 Algonquin Park 45.5218 -78.4293 12-Jun-2012

ASAHY652-13 BOLD:AAD5318 Algonquin Park 45.7181 -77.8106 11-Jun-2012

ASAHY655-13 BOLD:ACH0251 Algonquin Park 45.8948 -77.7309 03-Jun-2012


ASAHY657-13 BOLD:AAG7687 Algonquin Park 45.5235 -78.4209 05-Jun-2012


ASAHY659-13 BOLD:ABZ1196 Algonquin Park 45.5235 -78.4209 05-Jun-2012

ASAHY662-13 BOLD:AAH7288 Algonquin Park 45.7604 -77.8891 11-Jun-2012

ASAHY666-13 BOLD:AAU8389 Algonquin Park 45.8946 -77.7307 10-Jun-2012


ASAHY671-13 BOLD:ACC4612 Algonquin Park 45.8946 -77.7307 03-Jun-2012

ASAHY672-13 BOLD:AAA2372 Algonquin Park 45.4596 -78.7962 08-Jun-2012






ASAHY687-13 BOLD:ACI3601 Algonquin Park 45.8948 -77.7309 10-Jun-2012

ASAHY692-13 BOLD:AAM7454 Algonquin Park 45.5239 -78.4205 05-Jun-2012



ASAHY696-13 BOLD:ACD2023 Algonquin Park 45.6334 -77.0697 19-Aug-2012

ASAHY701-13 BOLD:AAG7735 Algonquin Park 45.6324 -77.0618 09-Oct-2012




ASAHY724-13 BOLD:AAZ0145 Algonquin Park 45.7182 -77.8109 11-Jun-2012





ASAHY734-13 BOLD:AAI5592 Algonquin Park 45.7604 -77.8891 04-Jun-2012







ASAHY749-13 BOLD:AAZ0145 Algonquin Park 45.4601 -78.7967 08-Jul-2012


211




ASAHY757-13 BOLD:ACD3524 Algonquin Park 45.7604 -77.8891 04-Jun-2012



ASAHY763-13 BOLD:ACK5792 Algonquin Park 46.099 -78.431 23-Jul-2012




ASAHY774-13 BOLD:ACK5793 Algonquin Park 46.058 -78.484 09-Jun-2012


ASAHY782-13 BOLD:ACG8925 Algonquin Park 45.894 -77.735 10-Jun-2012



ASAHY788-13 BOLD:ACJ1208 Algonquin Park 45.895 -77.73 18-Jul-2012



ASAHY802-13 BOLD:ABY5242 Algonquin Park 45.524 -78.421 20-Jul-2012



ASAHY816-13 BOLD:ABY2683 Algonquin Park 45.718 -77.811 11-Jun-2012





ASAHY832-13 BOLD:ACE0200 Algonquin Park 45.46 -78.797 22-Jun-2012

ASAHY833-13 BOLD:AAN7576 Algonquin Park 45.46 -78.797 22-Jun-2012




ASAHY850-13 BOLD:ABW3272 Algonquin Park 45.524 -78.421 20-Jul-2012



ASAHY859-14 BOLD:ACE0200 Algonquin Park 46.0992 -78.4311 09-Jun-2012


ASAHY862-14 BOLD:ACL6154 Algonquin Park 46.0992 -78.4311 09-Jun-2012

ASAHY873-14 BOLD:ACL5895 Algonquin Park 45.8944 -77.7348 10-Jun-2012

ASAHY877-14 BOLD:ACA7470 Algonquin Park 45.8945 -77.7351 01-Aug-2012

ASAHY878-14 BOLD:ACJ9210 Algonquin Park 45.8945 -77.7351 01-Aug-2012

ASAHY880-14 BOLD:ACA7470 Algonquin Park 45.8945 -77.7351 01-Aug-2012

ASAHY881-14 BOLD:ACJ1208 Algonquin Park 45.8946 -77.7307 01-Aug-2012

ASAHY882-14 BOLD:ABX2607 Algonquin Park 45.8946 -77.7303 01-Aug-2012

212

ASAHY890-14 BOLD:AAM7509 Algonquin Park 45.6334 -77.0697 09-Oct-2012

ASAHY892-14 BOLD:ACD3194 Algonquin Park 45.6334 -77.0697 09-Oct-2012



ASAHY898-14 BOLD:AAA6281 Algonquin Park 45.6324 -77.0618 24-Oct-2012









ASAHY924-14 BOLD:ACI3323 Algonquin Park 45.5238 -78.4206 12-Jun-2012





ASAHY938-14 BOLD:ACE0200 Algonquin Park 45.4599 -78.7964 22-Jul-2012


ASAHY948-14 BOLD:ACA7412 Algonquin Park 45.4595 -78.7961 08-Jun-2012

ASDHY063-12 BOLD:ABW8247 Algonquin Park 13-Jul-2011

ASDHY064-12 BOLD:AAG7737 Algonquin Park 13-Jul-2011

ASDHY067-12 BOLD:ABW8247 Algonquin Park 45.4599 -78.7961 09-Jul-2011

ASDHY069-12 BOLD:ABW8247 Algonquin Park 45.4599 -78.7961 09-Jul-2011

ASDHY070-12 BOLD:AAG9053 Algonquin Park 45.8968 -77.735 11-Jul-2011

ASDHY071-12 BOLD:AAC0845 Algonquin Park 45.8968 -77.735 11-Jul-2011


ASBZI046-10 BOLD:ACL5555 Belize 17.7507 -88.6539 18-Apr-2010















213




ASBZI074-10 BOLD:ACH1581 Belize 17.7507 -88.6539 18-Apr-2010








































214



















ASBZI176-10 BOLD:ABX5812 Belize 17.7507 -88.6539 18-Apr-2010


ASBZI183-10 BOLD:AAG0936 Belize 17.7507 -88.6539 18-Apr-2010









ASBZI194-10 BOLD:AAE8205 Belize 17.7507 -88.6539 18-Apr-2010














215



ASBZI216-10 BOLD:ABY4069 Belize 17.7507 -88.6539 18-Apr-2010






















ASBZI242-10 BOLD:AAI9312 Belize 17.7507 -88.6539 18-Apr-2010



















216












































217



































ASBZI485-10 BOLD:AAB9372 Belize 17.7507 -88.6539 18-Apr-2010









218


ASBZI497-10 BOLD:AAN7931 Belize 17.7507 -88.6539 18-Apr-2010










































219




ASBZI622-10 BOLD:ABA6156 Belize 17.7507 -88.6539 18-Apr-2010

ASBZI624-10 BOLD:ACD0249 Belize 17.7507 -88.6539 18-Apr-2010

TTSOW560-11 BOLD:AAY6356 Belize 17.751 -88.654 18-Apr-2010


JBHCH342-10 BOLD:AAH7430 Churchill 58.761 -94.012 15-Aug-2010


JBHCH475-10 BOLD:AAG2853 Churchill 58.761 -94.012 15-Aug-2010











JBHCI194-11 BOLD:AAP6735 Churchill 58.676 -94.144 05-Aug-2010























220







JBHCI547-11 BOLD:ACL7889 Churchill 58.754 -93.998 26-Jul-2010






























JBHCI859-11 BOLD:ABX6473 Churchill 58.633 -93.787 02-Aug-2010







221




JBHCI899-11 BOLD:AAJ7918 Churchill 58.633 -93.787 02-Aug-2010








































222












































223












































224




































SAHYM391-10 BOLD:AAM9124 Churchill 58.7306 -93.7804 20-Jul-2009








225













TWHYM037-09 BOLD:AAG5136 Churchill 58.649 -94.193 17-Jul-2008



TWHYM101-09 BOLD:ABU5550 Churchill 58.649 -94.193 17-Jul-2008





TWHYM121-09 BOLD:ACF3994 Churchill 58.755 -93.998 14-Jul-2008







WSPAH042-06 BOLD:AAB0136 Churchill 58.738 -93.819 01-Aug-2005
















226

BBHYA171-12 BOLD:AAK8237 Florida 27.582 -81.044 08-May-2011



BBHYA1730-12 BOLD:ACF2512 Florida 27.582 -81.044 11-May-2011


















BBHYA2899-12 BOLD:ABV2658 Florida 27.246 -82.308 24-May-2011






















227








































BBHYA4125-12 BOLD:ABA8059 Florida 27.582 -81.044 08-May-2011




228







BBHYG743-10 BOLD:AAN7798 Florida 30.3154 -87.4214 01-Apr-2010









BBHYG826-10 BOLD:ACE9668 Florida 30.2932 -87.4677 31-Mar-2010










BBHYH171-10 BOLD:AAK8237 Florida 27.6665 -82.3795 23-Mar-2010











BBHYH196-10 BOLD:ABZ2900 Florida 27.5817 -81.0479 07-Mar-2010





BBHYH203-10 BOLD:AAM4942 Florida 27.5817 -81.0479 07-Mar-2010


229












































230










































BBHYH595-10 BOLD:AAZ1991 Florida 27.2524 -82.2958 21-Mar-2010


231












































232







BBHYH733-10 BOLD:AAU8504 Florida 27.5823 -81.0423 07-Mar-2010

ASNUR007-11 BOLD:AAV0048 French Guiana 4.088 -52.681 29-Jan-2011





ASNUR022-11 BOLD:ABY4175 French Guiana 4.088 -52.681 31-Jan-2011





ASNUR038-11 BOLD:AAU9981 French Guiana 4.088 -52.681 31-Jan-2011







ASNUR056-11 BOLD:ABX5653 French Guiana 4.089 -52.677 31-Jan-2011












ASNUR089-11 BOLD:ABY6803 French Guiana 4.089 -52.677 31-Jan-2011



ASNUR098-11 BOLD:AAU9981 French Guiana 4.088 -52.681 02-Feb-2011

ASNUR100-11 BOLD:AAZ1977 French Guiana 4.088 -52.681 02-Feb-2011

ASNUR101-11 BOLD:AAV6289 French Guiana 4.088 -52.681 02-Feb-2011


233












ASNUR135-11 BOLD:ABX5579 French Guiana 4.089 -52.677 02-Feb-2011
































234




ASNUR206-11 BOLD:ABZ4155 French Guiana 4.088 -52.681 04-Feb-2011









ASNUR227-11 BOLD:AAM9598 French Guiana 4.088 -52.681 04-Feb-2011






























ASNUR281-11 BOLD:ACK8030 French Guiana 4.088 -52.681 03-Feb-2011

235







ASNUR292-11 BOLD:AAA6269 French Guiana 4.088 -52.681 06-Feb-2011









ASNUR322-11 BOLD:AAZ1976 French Guiana 4.088 -52.681 06-Feb-2011




























236












































237












































238













ASQSP654-08 BOLD:AAI5830 French Guiana 4.55556 -52.1386 01-Aug-2005

ASQSP918-08 BOLD:AAV7508 French Guiana 01-May-2005

ASQSP940-08 BOLD:AAH8783 French Guiana 5.14981 -52.7114 01-Jun-2005

ASQSQ133-09 BOLD:AAH6910 French Guiana 01-Oct-2005

ASQSQ435-09 BOLD:AAH8721 French Guiana 01-Aug-2007

ASQSQ800-10 BOLD:ACK0105 French Guiana 01-Aug-2007

ASQSQ810-10 BOLD:AAV7513 French Guiana 01-Dec-2000

ASQSQ813-10 BOLD:ACA7986 French Guiana 01-Dec-2000

ASQSQ814-10 BOLD:AAV7514 French Guiana 18-Jul-2000

ASQSQ817-10 BOLD:AAH8721 French Guiana 13-Dec-2000

ASQSQ818-10 BOLD:AAV7516 French Guiana 30-Oct-1998

ASQSQ819-10 BOLD:AAW1625 French Guiana 01-Dec-2000

ASQSQ820-10 BOLD:ABA9159 French Guiana 30-Aug-2000

ASQSQ827-10 BOLD:AAV7517 French Guiana 4.25001 -52.3585 04-Jan-2003

ASQSQ828-10 BOLD:AAV7518 French Guiana 01-May-1999

ASQSR149-11 BOLD:AAW1624 French Guiana 06-Jul-2000

ASQSR254-11 BOLD:ABA4663 French Guiana 01-Jan-2010















239







ASGLE1012-10 BOLD:AAJ0494 Guelph 43.554 -80.264 18-Aug-2010










ASGLE1098-10 BOLD:AAI1292 Guelph 43.554 -80.264 01-Aug-2010



ASGLE1105-10 BOLD:ABX5489 Guelph 43.554 -80.264 01-Aug-2010




ASGLE1132-10 BOLD:AAC1302 Guelph 43.554 -80.264 18-Aug-2010




















240



















ASGLE1412-10 BOLD:AAI1549 Guelph 43.554 -80.264 25-Jun-2010

















ASGLE1617-10 BOLD:ACK3058 Guelph 43.554 -80.264 25-Jun-2010








241









ASGLE1752-10 BOLD:AAB0096 Guelph 43.554 -80.264 14-Jun-2010

ASGLE177-10 BOLD:ACH5153 Guelph 43.554 -80.264 23-Sep-2009




ASGLE1828-10 BOLD:AAY2114 Guelph 43.554 -80.264 14-Jun-2010






























242












































243




























ASGLE687-10 BOLD:AAQ0459 Guelph 43.554 -80.264 01-Nov-2009






ASGLE704-10 BOLD:AAQ2960 Guelph 43.554 -80.264 09-Oct-2009



ASGLE719-10 BOLD:AAM7494 Guelph 43.554 -80.264 09-Oct-2009







244












































245







ASGLF436-11 BOLD:ACE4111 Guelph 43.554 -80.264 18-Nov-2010


ASGLE458-10 BOLD:AAG3194 Haldimond-Dunn

Townline 42.861 -79.703 20-Sep-2009


Townline 42.861 -79.703 20-Sep-2009

ASGLE462-10 BOLD:AAU8684 Haldimond-Dunn

Townline 42.861 -79.703 20-Sep-2009

ASGLE463-10 BOLD:AAH2006 Haldimond-Dunn

Townline 42.861 -79.703 20-Sep-2009

ASGLE464-10 BOLD:AAD4214 Haldimond-Dunn

Townline 42.861 -79.703 20-Sep-2009


Townline 42.861 -79.703 20-Sep-2009


Townline 42.861 -79.703 20-Sep-2009

ASGLE668-10 BOLD:ABZ7618 Haldimond-Dunn

Townline 42.861 -79.703 20-Sep-2009

ASGLE669-10 BOLD:AAE9438 Haldimond-Dunn

Townline 42.861 -79.703 20-Sep-2009


Townline 42.861 -79.703 20-Sep-2009

ASGLE671-10 BOLD:AAC2392 Haldimond-Dunn

Townline 42.861 -79.703 20-Sep-2009


Townline 42.861 -79.703 20-Sep-2009


Townline 42.861 -79.703 20-Sep-2009


Townline 42.861 -79.703 20-Sep-2009


Townline 42.861 -79.703 20-Sep-2009


Townline 42.861 -79.703 20-Sep-2009


Townline 42.861 -79.703 03-Oct-2009


Townline 42.861 -79.703 03-Oct-2009


Townline 42.861 -79.703 03-Oct-2009

246

ASGLE747-10 BOLD:AAN8194 Haldimond-Dunn

Townline 42.861 -79.703 03-Oct-2009


Townline 42.861 -79.703 03-Oct-2009


Townline 42.861 -79.703 03-Oct-2009


Townline 42.861 -79.703 03-Oct-2009


Townline 42.861 -79.703 03-Oct-2009


Townline 42.861 -79.703 03-Oct-2009


Townline 42.861 -79.703 03-Oct-2009


Townline 42.861 -79.703 03-Oct-2009


Townline 42.861 -79.703 03-Oct-2009

ASGLE758-10 BOLD:ABZ2589 Haldimond-Dunn

Townline 42.861 -79.703 03-Oct-2009


Townline 42.861 -79.703 03-Oct-2009

ASGLE760-10 BOLD:AAN8194 Haldimond-Dunn

Townline 42.861 -79.703 03-Oct-2009


Townline 42.861 -79.703 20-Sep-2009

ASGLE769-10 BOLD:ACE4814 Haldimond-Dunn

Townline 42.861 -79.703 20-Sep-2009


Townline 42.861 -79.703 20-Sep-2009


Townline 42.861 -79.703 03-Oct-2009

ASGLE856-10 BOLD:AAP6689 Haldimond-Dunn

Townline 42.861 -79.703 20-Sep-2009


Townline 42.861 -79.703 20-Sep-2009


Townline 42.861 -79.703 20-Sep-2009


Townline 42.861 -79.703 20-Sep-2009


Townline 42.861 -79.703 20-Sep-2009


Townline 42.861 -79.703 20-Sep-2009

ASGLE863-10 BOLD:AAF5747 Haldimond-Dunn

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ASGLE864-10 BOLD:AAU8202 Haldimond-Dunn 42.861 -79.703 20-Sep-2009

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ASGLE866-10 BOLD:ACH5153 Haldimond-Dunn

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ASGLE867-10 BOLD:AAM7487 Haldimond-Dunn

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ASGLE869-10 BOLD:ACE4000 Haldimond-Dunn

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ASGLE955-10 BOLD:AAD4214 Haldimond-Dunn

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ASGLF005-11 BOLD:AAG7674 Haldimond-Dunn

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ASGLF006-11 BOLD:AAA9338 Haldimond-Dunn

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ASGLF007-11 BOLD:AAH7259 Haldimond-Dunn

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ASGLF018-11 BOLD:ACF3458 Haldimond-Dunn

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ASGLF021-11 BOLD:AAB0892 Haldimond-Dunn

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ASGLF025-11 BOLD:ACE4814 Haldimond-Dunn

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ASGLF026-11 BOLD:AAD9441 Haldimond-Dunn

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248


Townline 42.861 -79.703 12-Sep-2010


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ASGLF037-11 BOLD:ABA6167 Haldimond-Dunn

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ASGLF041-11 BOLD:AAN7740 Haldimond-Dunn

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ASGLF043-11 BOLD:ABZ4364 Haldimond-Dunn

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ASGLF052-11 BOLD:AAY6849 Haldimond-Dunn

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ASGLF056-11 BOLD:AAP2581 Haldimond-Dunn

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ASGLF057-11 BOLD:AAL8266 Haldimond-Dunn

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ASGLF059-11 BOLD:AAG7794 Haldimond-Dunn 42.861 -79.703 21-Nov-2010

249

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ASGLF083-11 BOLD:AAC3244 Haldimond-Dunn

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250

ASGLF102-11 BOLD:ABW3143 Haldimond-Dunn

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ASGLF112-11 BOLD:AAU8205 Haldimond-Dunn

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ASGLF126-11 BOLD:ABX2610 Haldimond-Dunn

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ASGLF130-11 BOLD:ABZ3353 Haldimond-Dunn 42.861 -79.703 21-Nov-2010

251

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ASGLF181-11 BOLD:ABV5679 Haldimond-Dunn

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252

ASGLF184-11 BOLD:ABY8933 Haldimond-Dunn

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ASGLF185-11 BOLD:AAF8320 Haldimond-Dunn

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ASGLF215-11 BOLD:AAZ0238 Haldimond-Dunn

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ASGLF216-11 BOLD:AAH1739 Haldimond-Dunn 42.861 -79.703 01-Aug-2010

253

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ASGLF222-11 BOLD:ABV2673 Haldimond-Dunn

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ASGLF247-11 BOLD:AAW0433 Haldimond-Dunn

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254


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Townline 42.861 -79.703 19-Sep-2010


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ASGLF329-11 BOLD:AAP6716 Haldimond-Dunn 42.861 -79.703 19-Sep-2010

255

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256


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ASGLF372-11 BOLD:AAM7500 Haldimond-Dunn

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ASGLF377-11 BOLD:ACK5169 Haldimond-Dunn

Townline 42.861 -79.703 12-Sep-2010


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ASGLF441-11 BOLD:AAG0387 Haldimond-Dunn 42.861 -79.703 12-Sep-2010

257

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ASAHY115-13 BOLD:AAE8158 Wilberforce 45.508 -76.974 10-Jul-2011














258











ASAHY187-13 BOLD:ACB8141 Wilberforce 45.508 -76.974 10-Jul-2011

ASAHY211-13 BOLD:ACL5973 Wilberforce 45.508 -76.974 10-Jul-2011





ASAHY704-13 BOLD:AAU8831 Wilberforce 45.5075 -76.9742 12-Oct-2012


ASAHY711-13 BOLD:ACL6499 Wilberforce 45.5075 -76.9742 12-Oct-2012


ASAHY714-13 BOLD:AAC3220 Wilberforce 45.5075 -76.9742 12-Oct-2012























259





ASGLE1325-10 BOLD:AAK7840 Wilberforce 45.509 -76.676 11-Apr-2010


























ASGLE1461-10 BOLD:ABY6861 Wilberforce 45.509 -76.676 16-May-2010













260





















ASGLE1577-10 BOLD:AAF4878 Wilberforce 45.509 -76.676 24-May-2010












ASGLE1611-10 BOLD:AAL0380 Wilberforce 45.509 -76.676 14-Jun-2010





ASGLE1638-10 BOLD:ACI3231 Wilberforce 45.509 -76.676 31-May-2010






261






ASGLE1676-10 BOLD:AAL5084 Wilberforce 45.509 -76.676 24-May-2010










ASGLE1722-10 BOLD:ACD0281 Wilberforce 45.509 -76.676 18-Apr-2010








ASGLE1732-10 BOLD:ACC4158 Wilberforce 45.509 -76.676 12-Jul-2010

ASGLE1733-10 BOLD:ABA8012 Wilberforce 45.509 -76.676 12-Jul-2010



ASGLE1756-10 BOLD:ABA6048 Wilberforce 45.509 -76.676 21-Jun-2010




ASGLE1769-10 BOLD:ACB2486 Wilberforce 45.509 -76.676 14-Jun-2010





ASGLE1778-10 BOLD:ACB2527 Wilberforce 45.509 -76.676 05-Jul-2010







262
































ASGLE1895-11 BOLD:AAD5192 Wilberforce 45.509 -76.676 05-Jul-2010












263















ASGLE983-10 BOLD:AAF2914 Wilberforce 45.509 -76.676 01-Aug-2010



ASGLE988-10 BOLD:ABZ1196 Wilberforce 45.509 -76.676 01-Aug-2010

ASGLE993-10 BOLD:AAD8806 Wilberforce 45.509 -76.676 01-Aug-2010




ASGLF197-11 BOLD:ACF2973 Wilberforce 45.509 -76.676 05-Sep-2010

ASGLF200-11 BOLD:ABZ2750 Wilberforce 45.509 -76.676 05-Sep-2010

ASGLF341-11 BOLD:ABA8034 Wilberforce 45.509 -76.676 09-Oct-2010

ASGLF343-11 BOLD:AAM7512 Wilberforce 45.509 -76.676 09-Oct-2010

ASGLF351-11 BOLD:AAB1188 Wilberforce 45.509 -76.676 05-Sep-2010

264

APPENDIX 3. Chapter 2 - Outgroup specimens.

Process ID Sample ID Name Sequence

ALLEP012-13 BIOUG06751-A12 Abagrotis alternata COI-5P

ALLEP529-14 BIOUG09329-E06 Carpatolechia belangerella COI-5P

ALLEP103-13 BIOUG06755-A08 Carpatolechia belangerella COI-5P

GMDAP329-12 BIOUG02695-D08 Chironomidae COI-5P

GMDAP347-12 BIOUG02695-F02 Chironomidae COI-5P

GMDAP042-12 BIOUG01724-D06 Chironomidae COI-5P

ASALC149-12 BIOUG02610-E06 Agonum COI-5P

ASALC152-12 BIOUG02610-E09 Agonum gratiosum COI-5P

ASALC086-12 BIOUG02366-H02 Agonum retractum COI-5P

265

APPENDIX 4. Chapter 3 - Ichneumonidae hind tibia and wind length measurements.

Information is sorted in alphabetical order of collection site name.

Process ID BOLD URI Site Wing length

(mm) Hind tibia

length (mm)

ASAHY318-13 BOLD:AAB1188 Algonquin 2.77 0.74

ASAHY319-13 BOLD:AAC3876 Algonquin 2.90 0.89

ASAHY321-13 BOLD:AAY6820 Algonquin 2.14 0.66

ASAHY323-13 BOLD:AAF0572 Algonquin 2.66 0.51

ASAHY324-13 BOLD:AAG0976 Algonquin 2.43 0.73

ASAHY332-13 BOLD:AAJ5372 Algonquin 2.09 0.73

ASAHY353-13 BOLD:ABA6048 Algonquin N/A 0.72

ASAHY370-13 BOLD:ABA6048 Algonquin 2.96 N/A

ASAHY381-13 BOLD:ACG6485 Algonquin 3.66 1.52

ASAHY382-13 BOLD:ACG6485 Algonquin 3.30 N/A

ASAHY383-13 BOLD:ACC6470 Algonquin 2.83 0.80





ASAHY388-13 BOLD:ACC6470 Algonquin N/A 0.63



ASAHY396-13 BOLD:AAB8765 Algonquin N/A 1.00


ASAHY398-13 BOLD:AAI5592 Algonquin N/A 0.65

ASAHY408-13 BOLD:ACB7963 Algonquin 1.84 0.63

ASAHY413-13 BOLD:AAI5894 Algonquin 4.26 1.08

ASAHY415-13 BOLD:AAH2179 Algonquin 3.61 1.24






ASAHY452-13 BOLD:AAG9189 Algonquin N/A 1.10

ASAHY454-13 BOLD:ACC7149 Algonquin 3.27 N/A

ASAHY455-13 BOLD:AAU8248 Algonquin 5.08 1.93


ASAHY462-13 BOLD:ACC7201 Algonquin 2.74 N/A

ASAHY468-13 BOLD:AAU8389 Algonquin N/A 0.84


ASAHY473-13 BOLD:ACH0655 Algonquin N/A 0.83


266


ASAHY480-13 BOLD:AAU8635 Algonquin N/A 1.25

ASAHY481-13 BOLD:AAM7439 Algonquin 3.98 1.35

ASAHY482-13 BOLD:ACF1843 Algonquin 4.35 1.54





ASAHY505-13 BOLD:ABX5695 Algonquin N/A 1.74

ASAHY507-13 BOLD:ACD1970 Algonquin 2.81 1.33





ASAHY533-13 BOLD:AAA6281 Algonquin N/A 0.70



ASAHY536-13 BOLD:AAH1922 Algonquin 5.72 N/A


ASAHY544-13 BOLD:ACD2023 Algonquin N/A 2.80





ASAHY558-13 BOLD:AAA5524 Algonquin 3.35 1.10







ASAHY567-13 BOLD:AAA5524 Algonquin 3.37 1.18

ASBZI088-10 BOLD:AAP6663 Belize 3.84 1.52






ASBZI126-10 BOLD:AAP6681 Belize N/A 1.70

ASBZI158-10 BOLD:AAW0406 Belize 3.42 1.60


ASBZI192-10 BOLD:AAW0417 Belize N/A 1.38

ASBZI194-10 BOLD:AAE8205 Belize 6.06 3.10

267

ASBZI201-10 BOLD:ACA0907 Belize 1.87 0.52




ASBZI242-10 BOLD:AAI9312 Belize 8.20 3.96

ASBZI441-10 BOLD:AAU8439 Belize 3.43 1.49

ASBZI471-10 BOLD:ACA0907 Belize 2.07 0.60


ASBZI497-10 BOLD:AAN7931 Belize 5.98 1.97

JBHCI168-11 BOLD:AAH1659 Churchill 5.16 1.76


JBHCI173-11 BOLD:AAK3162 Churchill 4.68 1.33

JBHCI186-11 BOLD:AAU8918 Churchill 5.22 1.82


JBHCI198-11 BOLD:AAD5666 Churchill 5.13 1.74

JBHCI199-11 BOLD:ABZ8107 Churchill 3.95 1.22






JBHCI453-11 BOLD:AAG9158 Churchill 4.28 1.39


JBHCI462-11 BOLD:ABY5267 Churchill 5.53 1.81


JBHCI503-11 BOLD:AAF1375 Churchill 5.17 1.96






JBHCI554-11 BOLD:AAH1524 Churchill 2.27 N/A



JBHCI707-11 BOLD:AAI1431 Churchill 4.47 1.65





JBHCI791-11 BOLD:ACE3071 Churchill 6.06 1.90



JBHCI827-11 BOLD:AAE4238 Churchill 3.77 N/A

268



JBHCI843-11 BOLD:ACF1955 Churchill 2.67 0.68







JBHCI898-11 BOLD:AAE2457 Churchill 4.61 1.54

JBHCI899-11 BOLD:AAJ7918 Churchill 3.63 1.22






JBHCI963-11 BOLD:AAC9244 Churchill 5.21 1.87


JBHCJ035-11 BOLD:AAH1553 Churchill 3.13 0.84

JBHCJ085-11 BOLD:AAG8393 Churchill 5.03 1.76



JBHCJ137-11 BOLD:AAU9788 Churchill 5.00 1.43



JBHCJ172-11 BOLD:AAE2456 Churchill 4.87 1.74


JBHCJ178-11 BOLD:AAD7163 Churchill 3.68 1.00


JBHCJ232-11 BOLD:AAA5517 Churchill 3.58 1.10


JBHCJ336-11 BOLD:ACF3300 Churchill 4.34 1.19


JBHCJ343-11 BOLD:AAF1375 Churchill 4.37 1.68










269

JBHCJ485-11 BOLD:AAB3568 Churchill 3.21 1.06

JBHCJ487-11 BOLD:AAK3167 Churchill 3.78 0.94





JBHCJ508-11 BOLD:AAC9075 Churchill 4.73 1.64

JBHCJ512-11 BOLD:ACE3445 Churchill 4.43 1.46


JBHCJ519-11 BOLD:AAB0136 Churchill 5.57 2.13













SAHYM047-10 BOLD:ABY4961 Churchill 4.62 1.35

SAHYM052-10 BOLD:AAN7591 Churchill 3.95 1.55

SAHYM057-10 BOLD:AAE7819 Churchill 4.72 1.67

SAHYM058-10 BOLD:AAH1656 Churchill 3.76 1.29


SAHYM064-10 BOLD:AAG5779 Churchill 5.44 2.17



SAHYM081-10 BOLD:AAH1804 Churchill 4.54 N/A


SAHYM094-10 BOLD:AAA5819 Churchill 4.98 1.59

SAHYM096-10 BOLD:ACE6827 Churchill 3.67 1.18




SAHYM112-10 BOLD:AAD1879 Churchill 5.50 1.28


SAHYM124-10 BOLD:AAB8450 Churchill 5.89 1.49




270








SAHYM198-10 BOLD:AAF0483 Churchill 3.81 1.44

SAHYM213-10 BOLD:ACF2152 Churchill 3.83 1.08





SAHYM263-10 BOLD:AAL8281 Churchill 3.73 1.24












SAHYM384-10 BOLD:AAC1404 Churchill 5.65 1.37

SAHYM387-10 BOLD:AAB1188 Churchill 3.45 1.24

SAHYM390-10 BOLD:AAH1654 Churchill 3.74 N/A

SAHYM391-10 BOLD:AAM9124 Churchill 4.04 1.44






ASNUR013-11 BOLD:AAV4415 French Guiana 4.68 1.90


ASNUR018-11 TIE010 French Guiana 4.04 2.07



ASNUR056-11 BOLD:ABX5653 French Guiana 2.27 0.92



ASNUR077-11 BOLD:AAV4442 French Guiana N/A 1.08

271







ASNUR143-11 BOLD:AAV2850 French Guiana 2.01 N/A





































272




































ASNUR560-11 BOLD:AAB7595 French Guiana N/A 3.12

ASGLE022-10 BOLD:AAG7638 Guelph 4.38 1.41


ASGLE026-10 BOLD:AAH7283 Guelph 4.44 1.41



ASGLE034-10 BOLD:AAU8368 Guelph 3.15 0.99


273







ASGLE1026-10 BOLD:AAG7631 Guelph N/A 1.92



ASGLE1101-10 BOLD:ACG6485 Guelph 4.28 1.88

ASGLE1105-10 BOLD:ABX5489 Guelph 3.64 0.93


ASGLE1111-10 BOLD:ABZ8107 Guelph 4.30 1.62



ASGLE1122-10 BOLD:AAG9184 Guelph 3.40 N/A



ASGLE1146-10 BOLD:AAN8654 Guelph 1.75 0.49





ASGLE1247-10 BOLD:AAI7643 Guelph 4.45 1.69


ASGLE1258-10 BOLD:AAD4214 Guelph 5.03 1.36






ASGLE1339-10 BOLD:ACE7422 Guelph 3.99 1.42


ASGLE1350-10 BOLD:AAG7631 Guelph 1.94 N/A






ASGLE1556-10 BOLD:ACF2039 Guelph 10.11 3.40




274

ASGLE1595-10 BOLD:AAQ2726 Guelph 8.89 N/A

ASGLE1597-10 BOLD:AAF7684 Guelph 7.52 2.49









ASGLE274-10 BOLD:AAM7494 Guelph 2.25 0.58




ASGLE285-10 BOLD:AAP6689 Guelph 2.27 0.89

ASGLE419-10 BOLD:AAU8501 Guelph N/A 2.61




ASGLE447-10 BOLD:AAK3160 Guelph N/A 1.37

ASGLE456-10 BOLD:AAB0892 Guelph 3.73 N/A



















ASGLE697-10 BOLD:ACF3297 Guelph N/A 0.74




275






ASGLF088-11 BOLD:AAG0381 Guelph 5.57 1.62


ASGLF156-11 BOLD:ABA6172 Guelph 3.90 1.17

ASGLF160-11 BOLD:AAO2111 Guelph 3.87 1.44

ASGLF263-11 BOLD:AAU8396 Guelph 2.87 0.96



ASGLF418-11 BOLD:AAC3876 Guelph 3.53 0.89



ASGLF447-11 BOLD:AAM9117 Guelph 3.62 1.10


ASGLE459-10 BOLD:AAG7711 Haldimond 5.23 2.24

ASGLE463-10 BOLD:AAH2006 Haldimond 4.58 1.58

ASGLE669-10 BOLD:AAE9438 Haldimond 3.72 1.24

ASGLE754-10 BOLD:AAU8205 Haldimond 3.01 0.87

ASGLF036-11 BOLD:AAG8275 Haldimond 5.41 2.71

ASGLF038-11 BOLD:ABA6165 Haldimond 3.89 0.85


ASGLF041-11 BOLD:AAN7740 Haldimond 3.25 1.26


ASGLF044-11 BOLD:ABZ4363 Haldimond 4.13 1.77


ASGLF047-11 BOLD:AAH1652 Haldimond 5.49 1.56




ASGLF053-11 TIE013 Haldimond 4.53 1.79

ASGLF056-11 BOLD:AAP2581 Haldimond 3.81 1.23


ASGLF061-11 BOLD:AAN7739 Haldimond 3.85 1.37


ASGLF066-11 BOLD:ABA6165 Haldimond 4.21 N/A






276





ASGLF112-11 BOLD:AAU8205 Haldimond 2.69 0.62




ASGLF138-11 BOLD:AAD7584 Haldimond 2.71 0.74


ASGLF173-11 BOLD:ABX2585 Haldimond 4.66 0.74






ASGLF181-11 BOLD:ABV5679 Haldimond 4.00 1.08



ASGLF185-11 BOLD:AAF8320 Haldimond 3.63 1.17









ASGLF222-11 BOLD:ABV2673 Haldimond 5.40 1.23










ASGLF246-11 BOLD:ACG6485 Haldimond 3.99 1.62

ASGLF247-11 BOLD:AAW0433 Haldimond 4.35 2.02




277






ASGLF368-11 BOLD:AAC0868 Haldimond 2.80 0.82


ASAHY005-12 BOLD:AAG0379 Wilberforce 5.88 2.42


ASAHY009-12 BOLD:AAD5193 Wilberforce 6.02 2.23

ASAHY020-12 BOLD:AAG7706 Wilberforce N/A 2.42

ASAHY021-12 BOLD:ACF0052 Wilberforce 7.40 2.53

ASAHY022-12 BOLD:AAC9245 Wilberforce 7.68 2.53

ASAHY023-12 BOLD:AAC9245 Wilberforce 7.32 2.50



ASAHY038-12 BOLD:ABZ7151 Wilberforce 3.94 1.29

ASAHY044-12 BOLD:ABX9742 Wilberforce 1.17 N/A


ASAHY048-12 BOLD:ABX8713 Wilberforce 6.12 2.35

ASAHY076-12 BOLD:AAK8152 Wilberforce 2.21 0.69

ASAHY079-12 BOLD:ACE4233 Wilberforce 2.75 0.78

ASAHY085-12 BOLD:ABX8297 Wilberforce 2.85 N/A

ASGLE1048-10 BOLD:AAE8196 Wilberforce 2.84 0.80

ASGLE1066-10 BOLD:AAM7454 Wilberforce 2.73 0.76

ASGLE1087-10 BOLD:AAG0387 Wilberforce 4.84 1.65

ASGLE1283-10 BOLD:AAD5192 Wilberforce 7.25 2.54

ASGLE1286-10 BOLD:AAQ2728 Wilberforce 6.88 2.66

ASGLE1290-10 BOLD:ABX5695 Wilberforce 4.68 1.80

ASGLE1291-10 BOLD:AAD1879 Wilberforce 5.32 N/A

ASGLE1296-10 BOLD:ABZ1196 Wilberforce 6.06 1.75

ASGLE1305-10 BOLD:AAU8228 Wilberforce 7.12 2.42

ASGLE1306-10 BOLD:AAU8510 Wilberforce N/A 2.51




ASGLE1321-10 BOLD:AAD5193 Wilberforce 6.68 N/A

ASGLE1322-10 BOLD:ACG6485 Wilberforce 5.34 2.09


ASGLE1328-10 BOLD:ABY4114 Wilberforce 4.79 1.50


ASGLE1382-10 BOLD:AAH1692 Wilberforce 3.60 1.19


278

ASGLE1398-10 BOLD:ABY6771 Wilberforce 3.79 1.32

ASGLE1399-10 BOLD:ACE3610 Wilberforce 3.88 1.47




ASGLE1419-10 BOLD:ABZ2750 Wilberforce 4.46 1.33


ASGLE1423-10 BOLD:AAU8743 Wilberforce 3.09 N/A

ASGLE1425-10 BOLD:AAG7645 Wilberforce N/A 1.81






ASGLE1530-10 BOLD:AAA5819 Wilberforce 7.44 2.75

ASGLE1531-10 BOLD:AAI3361 Wilberforce 15.05 4.29

ASGLE1547-10 BOLD:AAN8172 Wilberforce 9.49 3.49















ASGLE1692-10 BOLD:AAG0387 Wilberforce 6.34 N/A

ASGLE1771-10 BOLD:ACD0380 Wilberforce 2.96 0.91








ASGLE1865-10 BOLD:AAD5192 Wilberforce 6.98 2.55

ASGLE1871-10 BOLD:AAI5894 Wilberforce 5.78 1.88


279





ASGLE963-10 BOLD:AAF2914 Wilberforce 6.25 1.98





ASGLE983-10 BOLD:AAF2914 Wilberforce 7.53 1.65




280

APPENDIX 5. Chapter 3 - Braconidae hind tibia and wing length measurements.

Information is sorted in alphabetical order of collection site name.

Process ID BOLD URI Site Wing length

(mm) Hind tibia

length (mm)


ASAHY246-13 BOLD:ABY4229 Algonquin 3.23 1.00







ASAHY304-13 TIE008 Algonquin 3.14 0.99




ASAHY360-13 BOLD:AAN5119 Algonquin 1.29 0.39

ASAHY390-13 BOLD:ACE3159 Algonquin 3.17 1.37



ASAHY440-13 TIE009 Algonquin 1.74 0.45






ASAHY510-13 BOLD:ABZ5626 Algonquin 1.38 0.40



ASAHY550-13 BOLD:AAY6794 Algonquin 3.77 2.26


ASAHY571-13 BOLD:ACE6264 Algonquin 2.33 N/A



ASBZI062-10 BOLD:ABV2819 Belize 1.63 0.52



ASBZI084-10 BOLD:AAP8572 Belize 0.97 N/A


ASBZI176-10 BOLD:ABX5812 Belize 3.18 0.92



281

ASBZI360-10 BOLD:AAY6772 Belize 1.72 0.63

ASBZI377-10 BOLD:AAY6776 Belize 1.91 N/A



ASBZI479-10 BOLD:AAC5317 Belize 2.18 0.69


ASBZI483-10 BOLD:AAU8425 Belize 2.30 N/A

ASBZI485-10 BOLD:AAB9372 Belize 2.33 0.78




JBHCI302-11 BOLD:AAA6373 Churchill 3.43 0.90


JBHCI389-11 BOLD:AAA7147 Churchill 3.08 N/A


JBHCI681-11 BOLD:ABX6188 Churchill 2.51 N/A


JBHCI761-11 BOLD:AAG1298 Churchill 4.31 N/A

JBHCI763-11 BOLD:AAB2287 Churchill N/A 1.54



JBHCI859-11 BOLD:ABX6473 Churchill 3.25 1.23

JBHCI873-11 BOLD:AAA9378 Churchill 2.39 N/A

JBHCI874-11 BOLD:AAE6216 Churchill 3.68 1.20









JBHCJ214-11 BOLD:AAU9749 Churchill N/A 0.80


JBHCJ217-11 BOLD:AAM7222 Churchill 2.74 0.91

JBHCJ219-11 BOLD:AAJ0884 Churchill 2.44 0.76



JBHCJ253-11 BOLD:AAU9819 Churchill N/A 0.61

JBHCJ254-11 BOLD:AAC9533 Churchill 2.67 N/A

JBHCJ367-11 BOLD:AAI1546 Churchill 3.51 1.10



282

JBHCJ422-11 BOLD:ABZ4485 Churchill 2.66 0.89













SAHYM055-10 BOLD:ABZ2380 Churchill 5.70 1.92





SAHYM127-10 BOLD:AAA4312 Churchill N/A 0.63

SAHYM128-10 BOLD:AAL8286 Churchill 3.31 0.91

SAHYM130-10 BOLD:ABZ0768 Churchill 2.53 0.76

SAHYM137-10 BOLD:ABX4962 Churchill 2.24 0.48


SAHYM152-10 BOLD:AAN7605 Churchill N/A 0.64


SAHYM173-10 BOLD:AAC9130 Churchill 2.70 0.86







SAHYM244-10 BOLD:AAI9645 Churchill 1.97 N/A



SAHYM264-10 BOLD:AAN7623 Churchill 3.22 N/A



SAHYM305-10 BOLD:AAG1248 Churchill N/A 0.65

SAHYM338-10 BOLD:AAG1288 Churchill 3.71 N/A


SAHYM358-10 BOLD:AAB5730 Churchill N/A 0.70


283







SAHYM405-10 BOLD:AAA8401 Churchill 3.26 N/A

SAHYM420-10 BOLD:AAO2089 Churchill 4.00 1.40


TWHYM028-09

BOLD:AAG0698 Churchill 1.62 0.56

TWHYM043-09

BOLD:ACF4318 Churchill 2.37 0.68




ASNUR022-11 BOLD:ABY4175 French Guiana 2.52 0.88



























284






ASNUR180-11 BOLD:AAH8898 French Guiana 3.17 1.14





ASNUR188-11 BOLD:ABZ7672 French Guiana 3.64 N/A








ASNUR206-11 BOLD:ABZ4155 French Guiana 4.26 1.21


ASNUR227-11 BOLD:AAM9598 French Guiana 5.25 2.22



ASNUR274-11 TIE003 French Guiana 3.74 N/A




ASNUR281-11 BOLD:AAA5379 French Guiana 5.17 1.87












ASNUR355-11 BOLD:AAA1265 French Guiana 2.80 1.13




285












ASNUR385-11 BOLD:AAA6269 French Guiana 2.50 N/A








ASNUR426-11 BOLD:ABX5579 French Guiana 6.34 1.85














ASNUR537-11 BOLD:AAH8705 French Guiana 5.45 N/A








ASGLE1089-10 BOLD:AAA7696 Guelph 2.90 1.14


286












ASGLE1333-10 BOLD:AAC2167 Guelph 2.57 0.83




ASGLE144-10 BOLD:AAU8595 Guelph 1.36 N/A


ASGLE1494-10 BOLD:AAQ2892 Guelph 1.10 0.36






ASGLE209-10 BOLD:AAQ2937 Guelph 2.05 0.70

ASGLE215-10 BOLD:AAU8581 Guelph 2.68 N/A


ASGLE228-10 BOLD:ABY7565 Guelph 1.51 0.46

















287






ASGLE684-10 BOLD:ACF1641 Guelph 4.29 1.38





ASGLF151-11 BOLD:AAA4788 Guelph 3.37 1.02

ASGLF164-11 BOLD:ABX2611 Guelph 3.58 1.52


ASGLF266-11 BOLD:AAM7467 Guelph 2.82 0.88

ASGLF272-11 BOLD:AAE0349 Guelph 1.90 0.59

ASGLF277-11 BOLD:ABZ2589 Guelph 2.01 0.49

ASGLF278-11 BOLD:ACF4786 Guelph 1.75 0.48



ASGLF435-11 BOLD:ABX6808 Guelph 2.46 0.71

ASGLF436-11 BOLD:ACE4111 Guelph 2.39 0.79

ASGLF446-11 BOLD:ACD5180 Guelph 3.42 1.56

ASGLE667-10 BOLD:AAG9257 Haldimond 2.53 1.03

ASGLE668-10 BOLD:ABZ7618 Haldimond 2.94 0.71

ASGLE678-10 BOLD:AAU8691 Haldimond 2.44 N/A

ASGLE679-10 BOLD:AAU8369 Haldimond 3.33 0.90

ASGLE858-10 BOLD:AAP6690 Haldimond 2.02 N/A

ASGLF057-11 BOLD:AAL8266 Haldimond 4.16 1.80



ASGLF103-11 BOLD:AAB8493 Haldimond 2.44 0.89




ASGLF133-11 BOLD:ABA5946 Haldimond 1.66 N/A

ASGLF203-11 BOLD:AAB0520 Haldimond 2.10 0.57





ASGLF307-11 BOLD:AAA8770 Haldimond 3.42 N/A

ASGLF308-11 BOLD:AAA9172 Haldimond 2.10 0.61


288


ASGLF323-11 BOLD:ACF1247 Haldimond 3.18 1.01






ASGLF375-11 BOLD:AAY6829 Haldimond 2.19 0.73


ASGLF379-11 BOLD:ACE4302 Haldimond 2.00 0.56




ASAHY056-12 BOLD:ABX6558 Wilbeforce 3.15 0.95

ASAHY072-12 BOLD:AAI6272 Wilbeforce 2.87 0.93

ASAHY083-12 BOLD:AAB0096 Wilbeforce 2.33 0.78

ASAHY092-12 BOLD:ABY1199 Wilbeforce 1.87 N/A

ASGLE1046-10 BOLD:AAU8643 Wilbeforce 1.86 0.69

ASGLE1060-10 BOLD:AAG8211 Wilbeforce 2.47 0.88


ASGLE1067-10 BOLD:AAI6268 Wilbeforce 3.10 0.94









ASGLE1426-10 BOLD:AAC3220 Wilbeforce 2.94 0.80

ASGLE1427-10 BOLD:AAN5130 Wilbeforce 2.30 0.62

ASGLE1428-10 BOLD:AAE4549 Wilbeforce 1.51 0.56


ASGLE1433-10 BOLD:ACE6874 Wilbeforce 2.35 0.73

ASGLE1434-10 BOLD:AAM7443 Wilbeforce 2.04 0.47

ASGLE1446-10 BOLD:ABX5161 Wilbeforce 1.68 0.44


ASGLE1461-10 BOLD:ABY6861 Wilbeforce 2.27 0.62




ASGLE1509-10 BOLD:AAU8722 Wilbeforce 2.29 N/A


289

ASGLE1511-10 BOLD:AAM7479 Wilbeforce 2.09 0.62


ASGLE1516-10 BOLD:AAA4789 Wilbeforce 2.77 N/A




ASGLE1731-10 BOLD:ACD0369 Wilbeforce 2.64 0.87

ASGLE1761-10 BOLD:ACD0383 Wilbeforce 2.26 N/A




ASGLE1851-10 BOLD:AAZ0149 Wilbeforce 3.48 1.46

ASGLE1853-10 BOLD:AAN5120 Wilbeforce 2.70 1.08

ASGLE1864-10 BOLD:AAQ2672 Wilbeforce 3.05 N/A

ASGLE923-10 BOLD:ABY3259 Wilbeforce 2.11 0.67

ASGLE924-10 BOLD:AAH3191 Wilbeforce 1.71 0.31

ASGLE927-10 BOLD:AAP6712 Wilbeforce 1.10 0.38

ASGLE929-10 BOLD:AAP6713 Wilbeforce 2.02 0.73


ASGLE934-10 BOLD:AAA4785 Wilbeforce 2.58 0.81

ASGLE969-10 BOLD:AAI1540 Wilbeforce 4.56 1.76

ASGLE972-10 BOLD:AAB0185 Wilbeforce 3.78 1.10

ASGLE974-10 BOLD:AAU8633 Wilbeforce 3.57 N/A

ASGLF198-11 BOLD:AAG1425 Wilbeforce 4.88 1.87

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Latitudinal Effects on Diversity and Body Size: A Case