Evaluation of Mysis partial diel vertical migration

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2019

Evaluation of Mysis partial diel vertical migrationBrian Patrick O'MalleyUniversity of Vermont

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EVALUATION OF MYSIS PARTIAL DIEL VERTICAL MIGRATION

A Dissertation Presented

by

Brian Patrick O’Malley

to

The Faculty of the Graduate College

of

The University of Vermont

In Partial Fulfillment of the Requirements

for the Degree of Doctor of Philosophy

Specializing in Natural Resources

January, 2019

Defense Date: October 23, 2018

Dissertation Examination Committee:

Jason D. Stockwell, Ph.D., Advisor

Sara Helms Cahan, Ph.D., Chairperson

Sture Hansson, Ph.D.

J. Ellen Marsden, Ph.D.

Joe Roman, Ph.D.

Cynthia J. Forehand, Ph.D., Dean of the Graduate College

© Copyright by

Brian Patrick O’Malley

January 2019

ABSTRACT

Mass animal migrations represent large movements of biomass, energy, and

nutrients with predictable patterns and important ecosystem-level consequences. Diel

vertical migration (DVM) in aquatic systems, the daily movement of organisms from

deeper depths during the day to shallower depths in the water column at night, is

widespread in freshwater and marine systems. Recent studies, however, suggest partial

migration behavior, whereby only some portion of a population migrates, is the rule

rather than the exception in a range of migratory fauna, including those that undergo

DVM. Hypotheses to explain why partial migrations occur complicate traditional views

on DVM and challenge conventional theories. I address intraspecific variation in DVM

behavior of an aquatic omnivore, Mysis diluviana, to test several long-standing

assumptions about benthic-pelagic DVM in Mysis. I evaluated the extent of partial DVM

and several potential drivers within a Lake Champlain Mysis population. I used

traditional net-based field observations, a novel deep-water video camera system, and a

laboratory experiment, to compare distributions, demographics, abundance estimates,

hunger-satiation state, and feeding behavior, of migrant and non-migrant Mysis across

multiple seasons, habitats, and different times of the day. Findings from my dissertation

suggest Mysis partial DVM is common, and is associated with body size and

demographic differences among individuals. Partial DVM behavior, however, did not

correspond to strong differences in feeding preference or hunger-satiation state of

individuals. My results contribute toward a more comprehensive understanding of

migration theory and mysid biology, by including the often overlooked, but important,

benthic habitat component of DVM studies, and fills in several ecological knowledge

gaps regarding a key omnivore in many deep lake food webs across North America

where Mysis serve as both predators and prey to many organisms.

ii

CITATIONS

Material from this dissertation has been published in the following form:

O’Malley, B. P., Hansson, S. and Stockwell, J. D.. (2018). Evidence for a size-structured

explanation of partial diel vertical migration in mysids. Journal of Plankton

Research 40: 66-76.

O’Malley, B. P., Dillon, R. A., Paddock, R. W., Hansson, S. and Stockwell, J. D.. (In

Press). An underwater video system to assess abundance and behavior of

epibenthic Mysis. Limnology and Oceanography: Methods. DOI:

10.1002/lom3.10289

iii

ACKNOWLEDGEMENTS

I would like to thank my advisor, Jason Stockwell, for the opportunity to conduct

graduate research at the Rubenstein Ecosystem Science Laboratory. I thank you for the

motivation, guidance, and writing tips you have instilled upon me, and look forward to

future collaborations and beyond.

Perhaps the most crucial element to accomplishing my field work has been

captain Steve Cluett. Steve’s wisdom, expertise, and enthusiasm, was instrumental for all

aspects of my project. Along with Steve, deckhands Krista Hoffsis and Brad Roy were

also critical. I’ll treasure our conversations aboard the R/V Melosira while sipping coffee

and looking back at Burlington on those long nights of Mysis sampling.

I would like to acknowledge several of my past supervisors and colleagues who

continue to motivate me throughout my journey to pursue science as a career.

Conversations with David Bunnell formed the impetus for my interest in Mysis. Mentors

from my Lake Ontario stint (Lars Rudstam, Jim Watkins, and Brian Weidel), were

influential in shaping my career path. Great after-work discussions with friends Bryan

Maitland and Elliot Jackson, while fishing or talking zooplankton, were pivotal in my

motivation to pursue graduate studies. Additionally, I thank members of my committee

(Sure Hansson, Sara Helms Cahan, Ellen Marsden, and Joe Roman) for their help in

shaping my project. I’ve learned so much from collaborating with all of you, and I will

continue to benefit from all these past experiences.

I thank the support of my parents Mark and Ewa O’Malley as they opened the

initial door to research by supporting me as I pursued my undergraduate degree. That

iv

initial launch into undergraduate research and study was how I discovered a career in

aquatic research, and ultimately found my niche in large lake research. None of that

would have been possible without their support.

I thank Rebecca Dillon for her efforts to get the Mysis video camera system up

and running, which helped pave the way for a concept to become a reality. Additionally,

several undergraduates: Pascal Wilkins, Kevin Melman, Hannah Lister, Grace Scorpio,

Jeni Knight, and Jessica Griffin; provided substantial help and provided me with

opportunities to learn about myself and hone my skills as a mentor. I hope the research

experiences were equally rewarding for you as they were for me.

Funding was provided by the Great Lakes Fishery Commission with the

assistance of Senator Patrick Leahy. Additional funding was provided by a University of

Vermont Chrysalis Award, and a scholarship from the International Association for Great

Lakes Research.

Lastly, and most importantly, I would like to thank my girlfriend Nikki Saavedra

for her love and support during our long-distance lifestyle these past several years while

we worked on our degrees. Your support, patience, and laughter throughout this process

has been amazing. I look forward to starting our next chapter in life together.

v

TABLE OF CONTENTS

Page

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

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

LIST OF FIGURES ............................................................................................................ x

CHAPTER 1: DIEL VERTICAL MIGRATION AND MYSID ECOLOGY FROM A

PARTIAL MIGRATION PERSPECTIVE ......................................................................... 1

Diel vertical migration: examples, hypotheses, and conceptual framework .................. 3

Mysis ecology: distribution and vertical migration behavior .......................................... 6

Trophic role of Mysis in food webs .............................................................................. 12

The need for a partial DVM approach to mysid ecology .............................................. 15

Lake Champlain as a study system ............................................................................... 17

Dissertation outline ....................................................................................................... 19

References ..................................................................................................................... 22

CHAPTER 2: EVIDENCE FOR A SIZE-STRUCTURED EXPLANATION OF

PARTIAL DIEL VERTICAL MIGRATION IN MYSIDS.............................................. 34

Abstract ......................................................................................................................... 35

Introduction ................................................................................................................... 36

Methods......................................................................................................................... 39

Results ........................................................................................................................... 43

Discussion ..................................................................................................................... 49

Conclusions ................................................................................................................... 55

Acknowledgements ....................................................................................................... 55

References ..................................................................................................................... 57

vi

CHAPTER 3: AN UNDERWATER VIDEO SYSTEM TO ASSESS ABUNDANCE

AND BEHAVIOR OF EPIBENTHIC MYSIS .................................................................. 65

Abstract ......................................................................................................................... 66

Introduction ................................................................................................................... 67

Materials and Methods .................................................................................................. 72

Description of system ................................................................................................ 72

Spectral intensity and behavior experiment ............................................................... 73

Field deployments and video analysis ....................................................................... 74

Field-based comparisons ........................................................................................... 79

Results ........................................................................................................................... 81

Spectral intensity and behavior experiment ............................................................... 81

Field deployments and video analysis ....................................................................... 83

Field-based comparisons ........................................................................................... 85

Discussion ..................................................................................................................... 89

Acknowledgements ....................................................................................................... 95

References ..................................................................................................................... 96

CHAPTER 4: DIEL FEEDING BEHAVIOR IN A PARTIALLY MIGRANT MYSIS

POPULATION: A BENTHIC-PELAGIC COMPARISON ........................................... 103

Abstract ....................................................................................................................... 104

Introduction ................................................................................................................. 106

Methods....................................................................................................................... 110

Sample collections ................................................................................................... 110

Sample analysis ....................................................................................................... 112

Results ......................................................................................................................... 117

Discussion ................................................................................................................... 129

Conclusion .................................................................................................................. 135

Acknowledgements ..................................................................................................... 136

vii

References ................................................................................................................... 137

CHAPTER 5: COMPARATIVE EVALUATION OF MIGRANT AND NON-

MIGRANT MYSIS FEEDING PREFERENCES .......................................................... 147

Abstract ....................................................................................................................... 148

Introduction ................................................................................................................. 150

Methods....................................................................................................................... 153

Field sampling ......................................................................................................... 153

Experimental setup .................................................................................................. 154

Data analysis ............................................................................................................ 157

Results ......................................................................................................................... 157

Discussion ................................................................................................................... 159

Acknowledgements ..................................................................................................... 164

References ................................................................................................................... 165

COMPREHENSIVE REFERENCES ............................................................................. 169

viii

LIST OF TABLES

Page

Table 1.1: Compilation of studies that document partial migration in Mysis spp. (M.

diluviana, M. mixta, M. relicta, and M. salemaai) at night. Studies that did not

report quantitative values of Mysis spp. on bottom at night were only included

if they reported presence/absence. ........................................................................ 11

Table 2.1: Number of Mysis collected during descent/retrieval of the benthic sled

versus number collected in standard five-minute benthic sled tow, and the

percent of pelagic Mysis in benthic tows in Lake Champlain, 2015. Values are

the mean of two replicates. ................................................................................... 42

Table 2.2: Number of juvenile, female, male, and total mysids counted from night-

benthic and night-pelagic samples by month pooled across both sites, and P-

values of chi-squared tests comparing demographic proportions. ........................ 49

Table 3.1: Qualitative tradeoffs with various sampling methods used to estimate

benthic mysid abundance. ..................................................................................... 71

Table 3.2: Date, time (EDT/EST), and nautical sunset times of benthic video camera

deployments at the same 60-m location in Lake Champlain 2014-15.

Deployment date/time refers to the time of day when the camera touched-

down. Nautical sunset indicates the first time-interval counted, and marks the

start of the night time period class. ....................................................................... 78

Table 4.1: One-way ANOVA results of the number of prey for each category in Mysis

stomach contents over a diel cycle in Lake Champlain. F values that were

significant following a Bonferroni correction (α = 0.05/12) for multiple

comparisons are denoted by asterisks. ................................................................ 125

Table 4.2: Mean size of Mysis and number of prey items, and the minimum and

maximum number observed, in Mysis stomach contents collected at different

times of day and habitat (benthic/pelagic). Grey denotes samples collected at

night (between sunset-sunrise). Bold values denote months when significant

differences in mean number of prey over a diel period were detected after

Bonferroni correction. Superscripts refer to Tukey’s HSD post-hoc comparison

for those cases. .................................................................................................... 126

Supplemental Table 4.3: Sample collection times of four separate trips. Sunset/sunrise

times are listed below each date in parentheses. Grey shading denotes samples

collected during night. Time refers to the midpoint during the time interval of

each sample. ........................................................................................................ 144

Supplemental Table 4.4: Zooplankton taxa, mean length (L in mm), and length-weight

equations used to estimate dry biomass (W in dry µg). Equations follow the

formula ln(W) = lnA + B • ln(L). ....................................................................... 145

Table 5.1: Mean length of Mysis used in feeding experiment. ....................................... 158

ix

Table 5.2: Two-way ANOVA results of Mysis predation rates (No. Daphnia hr-1). ...... 159

x

LIST OF FIGURES

Page

Figure 1.1: (Left) Total or normal DVM where the entire population migrates near

surface at night to feed. (Right) Partial DVM with some portion not migrating.

Gradients of predation risk and growth potential are scaled from high (red) to

low (blue). Predation risk varies with light (daily) while growth potential does

not change within a day. ......................................................................................... 4

Figure 2.1: Map of sampling sites by bottom depth for Mysis collections in Lake

Champlain, USA, in June-November 2015. ......................................................... 40

Figure 2.2: Monthly diel comparison of mean pelagic density of Mysis (top) estimated

from vertical net tows from 2 m above lake bottom to surface tows in Lake

Champlain 2015, and mean benthic Mysis density (bottom) estimated from

benthic sled tows at 60- (left) and 100-m site sites (right). Open bars are day

samples and filled bars are night samples (+ SD). ................................................ 44

Figure 2.3: Mean (± SD) body length (mm) of pelagic (grey circles) and benthic-

caught (black circles) Mysis at 60- and 100-m sites in Lake Champlain 2015 as

a function of month sampled. Note that mesh size (1 mm) was consistent

between the two gear types. Insufficient numbers of Mysis were captured in

the pelagic habitat during the day at the 60-m site to compare mean length of

day-benthic to day-pelagic individuals. ................................................................ 46

Figure 2.4: Frequency of Mysis by size class pooled across all months (June-November

2015) in night-pelagic and night-benthic samples at 60- (top) and 100-m

(bottom) sites in Lake Champlain. ........................................................................ 47

Figure 2.5: Percent composition of juvenile, female, and male Mysis collected in night-

pelagic (top) and night-benthic samples (bottom) at 60- (left) and 100-m (right)

sites in Lake Champlain. ....................................................................................... 48

Supplemental Figure 2.6: Difference between mean lengths of benthic and pelagic

Mysis collected at night by site (60 m = triangles; 100 m = circles) as a function

of day of year. Blue line indicates linear model and grey ribbon represents 95%

confidence intervals. ............................................................................................. 63

Supplemental Figure 2.7: Water temperature isopleths at 60-m (left) and 100-m (right)

where Mysis sampling took place in Lake Champlain. ......................................... 64

Figure 3.1: Benthic camera system during deployment. Labeled components are: (A)

housing for battery pack; (B) housing with DVR; (C) red LED light; (D) video

camera; (E) red lasers. Base of frame is 1.2 x 1.2 m. (photo credit: Maureen

Walsh). .................................................................................................................. 73

xi

Figure 3.2: Map of benthic sled transects, stationary Mysis camera deployments, and

locations of point sampling with the GoPro mounted mini-lander in Lake

Champlain. ............................................................................................................ 75

Figure 3.3: Relative spectral intensity of red LED light (dashed line) and lasers (solid

line) used on the camera system. Spectral sensitivity curve of Mysis eye (dotted

line) from Gal et al. (1999) included for comparison. .......................................... 81

Figure 3.4: Percentage of Mysis observed under the red light half of cooler in the

laboratory experiment. Percentages are the average of two observations every

ten minutes during the first hour (circle), third hour (triangle), and seventh hour

(square) of experiment. ......................................................................................... 82

Figure 3.5: Coefficient of variation for Mysis benthic density as a function of binned

time intervals for 1-hour video segment from June (circles) and October

(triangles) 2015. For each average, N ranged from 60 for the 1-min interval to

2 for the 30-min interval. ...................................................................................... 83

Figure 3.6: Mysis density (No. m-2) estimated from benthic video at 10-minute

intervals for seven separate deployments in 2015 (black points) and one

deployment in 2014 (blue triangles) at the same 60-m site in Lake Champlain.

Grey boxes represent night defined as 1-hr post-sunrise to 1-hr pre-sunrise.

Times are in EDT except for November which is EST. Moon phase and

weather conditions are shown. .............................................................................. 84

Figure 3.7: Mean Mysis density (No. m-2) estimated from benthic video during the

night vs day at the same 60-m site in Lake Champlain 2015. .............................. 86

Figure 3.8: Synchronous change in orientation of Mysis with direction of bottom

current on July 17th 2015 over a 6-hour period. (Left) Screenshots of Mysis at

06:00 (top), 10:00 (middle), and 12:00 EDT (bottom). (Right) Circular

histograms with measurements of the direction individual mysids were facing

in the corresponding image to the left................................................................... 87

Figure 3.9: Mysis mean video density (No. m-2) observed as a function of mean benthic

sled density (No. m-2) collected during the same 1-hr time window. ................... 88

Figure 3.10: (A) Observed Mysis density (No. m-2) by the mini-lander at the time of

landing as a function of distance (m) from the stationary benthic Mysis video

camera. Circles represent July and triangles refer to October 2017 sampling.

(B) Comparison of mean density (± SD) observed on mini-lander (x-axis) to

stationary benthic Mysis video camera (y-axis). ................................................... 88

Supplemental Figure 3.11: Screenshot from deep-water camera system deployed at 60

m bottom depth in Lake Champlain, Vermont, USA. Date/time stamp on the

video follow eastern time (24:00 hr MM/DD/YY format). ................................ 101

Supplemental Figure 3.12: Screenshot of slimy sculpin (Cottus cognatus) interacting

with Mysis from deep-water camera system deployed at 60 m bottom depth in

Lake Champlain, Vermont, USA. Date/time stamp on the video follow eastern

time (24:00 hr MM/DD/YY format). .................................................................. 102

xii

Figure 4.1: Local time of pelagic (P, red triangles) and benthic (B, black circles)

sample collections during four separate trips on Lake Champlain. Sample times

represent the midpoint of the time interval in which the sample was collected.

Grey box is sunset to sunrise (see Supplemental Table 4.3 for exact time

values). ................................................................................................................ 111

Figure 4.2: (A) Mysis cephalic region after separation from the body with thoracic

carapace removed. (B) Close-up view of Mysis cardiac stomach (circled

region) (C-G) Gut scale ranking system for classifying gut fullness

of Mysis stomach contents: (C) 0 = empty; (D) 1 = trace food up to one-quarter

full; (E) 2 = half full; (F) 3 = three-quarters full; (G) 4 = fully gorged. ............. 115

Figure 4.3: Vertical profiles of temperature and chlorophyll-a fluorescence at the 100-

m sampling site in Lake Champlain in June 2016, and April, July, and October

2017..................................................................................................................... 118

Figure 4.4: Crustacean zooplankton biomass (mg/m3) and % composition in 60 m to

surface vertical net tows at the 100-m site in Lake Champlain in June 2016 and

July-October 2017. .............................................................................................. 119

Figure 4.5: Correlation between number of total zooplankton prey (copepods,

cladocerans, and rotifers) in Mysis gut contents (ZP) and gut fullness rank score

from Lake Champlain in June 2016 and July-October 2017. ............................. 120

Figure 4.6: Temporal changes in stomach fullness index (SFI) of benthic- (black

circles) and pelagic-caught (red triangles) mysids by month from Lake

Champlain. Grey box is sunset to sunrise. .......................................................... 121

Figure 4.7: Variation in detritus scores of pelagic and benthic Mysis by time of day in

June 2016 and July and October 2017 in Lake Champlain. ............................... 123

Figure 4.8: Mean (± SE) detritus rank of stomach contents from benthic- and pelagic-

caught Mysis by time of day. Points labelled with the same letter denote no

significant difference among time of day (Dunn test with Bonferroni

correction). Letters are located above for benthic and below for pelagic

samples. * indicates excluded estimate due to small sample size. ...................... 123

Figure 4.9: Frequency of occurrence of prey items by habitat-time sampled (BD =

benthic-day; BN = benthic-night; PN = pelagic-night). Prey items with values

of 0% are not shown as symbols. Pelagic prey items are ordered by decreasing

body size (green font), from Keratella to Senecella; last four prey items of list

(Dinoflagellate.cyst-Detritus.4.only) are strictly benthic prey (brown font). ..... 129

Supplemental Figure 4.10: Variation in the gut fullness ranks assigned to Mysis diets

in pelagic and benthic habitats collected at different times over a diel cycle

from 100-m site in Lake Champlain in June 2016 and April, July, and October

2017. No data were available from the pelagic habitat in April. ........................ 146

Figure 5.1: Schematic of Mysis feeding experiment. For each food treatment

(Daphnia-only, Daphnia-detritus, and Detritus-only), a single Mysis was

xiii

placed in each of 10 1-L jars and allowed to forage on the available food over

the allotted time under darkness. ........................................................................ 155

Figure 5.2: Observed ingestion rates of Mysis on Daphnia as a function of Mysis body

size. ..................................................................................................................... 159

1

CHAPTER 1: DIEL VERTICAL MIGRATION AND MYSID ECOLOGY FROM A

PARTIAL MIGRATION PERSPECTIVE

The wide range of behaviors and spatio-temporal scales used by a wide range of

organisms and across all types of habitat is a remarkable feature of the natural world.

From the cross-hemisphere seasonal migrations of Arctic terns (Egevang et al. 2010) to

the daily rhythmic vertical migrations by freshwater and marine fauna (e.g., Guisande et

al. 1991; Hays 2003; Cartamil and Lowe 2004), migration represents a dynamic array of

tradeoffs and choices to hedge bets for survival and reproduction of individuals.

Migration also connects disparate habitats through movement and exchange of energy

and nutrient subsidies (Gende et al. 2002; Bauer and Hoye 2014; Darnis et al. 2017).

Consequently, animal migration profoundly influences biogeochemical cycles and food

web structure (Longhurst and Harrison 1988; Polis et al. 1997; Jónasdóttir et al. 2015;

Oliver et al. 2015). Understanding how organisms interact within and among landscapes

and the decision-making processes governing their behavior are critical for predicting

future responses to human-related impacts on ecosystems, including climate change,

habitat fragmentation, and species removal.

Migration is the result of evolution working to optimize an animal’s fitness in

response to conflicting biotic and abiotic pressures (Milner-Gulland et al. 2011). More

recently, the concept of partial migration, where some portion of a population does not

migrate, has been recognized as a ubiquitous feature across a range of migratory birds,

fishes, and mammals (Chapman et al. 2011, 2012; Mehner and Kasprzak 2011). Recent

2

work on partial migration shows alternative outcomes and impacts on ecosystem

structure and function that are inconsistent with assumptions of whole-population

movement (Broderson et al. 2008a, 2011; Chapman et al. 2012). For example, the timing

and magnitude of partial migration by planktivorous fish influences alternative stable

states in lakes (Broderson et al. 2008a). Therefore, partial migration challenges

conventional theories of migration because opposing behaviors are unlikely explained by

the same drivers.

Identifying the factors associated with partial migrations and the magnitude or

variation associated with these movements is essential for predicting how organisms will

respond to ecosystem perturbations. Individual tradeoffs between body-condition and

predation risk can act as drivers of partial migrations, among other potential factors

(Chapman et al. 2011). By tracking individual fish over several months, Broderson et al.

(2008b) showed that fish with low energy stores remained in high-risk, high-reward

settings while individuals with sufficient energy stores migrated into low-risk, low-

reward habitat. The findings of Broderson et al. (2008b) provide valuable insights for

how individuals might respond to a future disturbance. For example, if a future

disturbance creates limited food availability or increased competition for food availability

in a fish population, then under the body-condition hypothesis one might expect more

fish with poor-condition and subsequently more of the population to forego migration

away from the high-risk habitat. Researchers and managers could incorporate knowledge

about drivers of animal migrations at the individual level to make informed predictions

about how best to manage populations and evaluate ecosystem consequences of shifts in

migration patterns.

3

Diel vertical migration: examples, hypotheses, and conceptual framework

Diel vertical migration (DVM) in freshwater and marine systems is considered the

largest synchronized mass movement of organisms in the world (Hays 2003). The typical

pattern of DVM, also commonly referred to as normal DVM, is the movement of

organisms from deeper depths where they reside during the day, up to shallower depths

after sunset where they remain throughout the night, followed by descent back down at

sunrise. Organisms across the globe, ranging from algae up to apex predators, partake in

DVM (e.g., Cullen 1985; Guisande et al. 1991; Stockwell et al. 2010). Large fluxes in

biomass distribution brought about by DVM are important to predict to accurately

quantify spatial subsidies of energy or biomass across habitat boundaries (Schindler and

Scheuerell 2002; Haupt et al. 2009; Sierszen et al. 2014). DVM in one species can

influence the migration behavior of another species, which in turn can influence the next

trophic level and so on, thereby leading to cascading effects of DVM behavior on

distributions throughout the food web (Bollens et al. 2010). Understanding the vertical

movements and factors that drive DVM in one species may in turn help with

understanding the behavior and diel distribution patterns of other species within a system

(Bollens et al. 1992; Eshenroder and Burnham-Curtis 1999; Williamson et al. 2011).

Abrupt vertical gradients in temperature, light, food, and predators (Fig. 1 Left) provide a

template to conceptualize energetic tradeoffs in growth and survival with respect to

habitat (Loose and Dawidowicz 1994; Boscarino et al. 2009; Mehner 2012). A substantial

body of evidence suggests DVM has evolved as a mechanism to minimize the ratio of

predation risk () to growth (G) potential (sensu Werner et al. 1983), a framework shared

across marine and freshwater settings (Gliwicz and Pijanowska 1988; Lampert 1993;

4

Hays 2003). DVM theory predicts that /G will be lowest at night in food-rich surface

waters when visual predators are at a disadvantage (low-risk, high-reward), and lowest

during the day down deep where food may be less available but visual predators are still

at a disadvantage (low-risk, low-reward; Fig. 1 Left). Species known to exhibit DVM

have also demonstrated the capacity to undergo reverse migration (e.g., predators

migrating down in the water column at night, Jensen et al. 2011) or partial migration

(Mehner 2014). Deviations from the normal pattern of DVM highlight the flexibility of

the behavior and the importance of considering individual variability in unraveling

migration decision-making processes.

Figure 1.1: (Left) Total or normal DVM where the entire population migrates near

surface at night to feed. (Right) Partial DVM with some portion not migrating. Gradients

of predation risk and growth potential are scaled from high (red) to low (blue). Predation

risk varies with light (daily) while growth potential does not change within a day.

DVM is a theory-rich field with many hypotheses proposed to explain the

adaptive value of DVM behavior. The proximate cause that triggers DVM is generally

accepted to be diel change in light intensity (Cohen and Forward 2009). Conversely,

ultimate causes for the adaptive significance of DVM vary substantially. Mangel and

Clark (1988) compiled thirteen different hypotheses from the literature for DVM, that

5

range from tactics to minimize exposure to harmful UV radiation (Hairston 1976) to

increased energetic efficiency (McLaren 1974). Many of the proposed hypotheses are not

mutually exclusive making it difficult to tease apart the exact mechanisms behind DVM.

Furthermore, while proximate factors can be tested with controlled experiments or

observations (Cohen and Forward 2009), the evolution of ultimate causes responsible for

behavior are more difficult or impossible to test because of difficulties comparing fitness

consequences of alternative phenotypes at present to past forms (Reeve and Sherman

1993; Mehner et al. 2007; Eshenroder and Burnham-Curtis 2001). Nonetheless, the most

widely accepted explanation for DVM in lower trophic-level organisms is that the

behavior has evolved as predator-avoidance mechanism (Zaret and Suffren 1976; Gliwicz

1986; Hays 2003; Ringelberg 2010). Justification for the predator-avoidance hypothesis

comes from quantifying tradeoffs through modelling of predation-risk and growth

potential with respect to vertical gradients of predators, prey, and abiotic conditions

(Zaret and Suffren 1976; Loose and Dawidowicz 1994; Jensen et al. 2006). Field

observations from systems with fluctuations in predator density also indicate support for

predator-avoidance. For example, migration amplitude of zooplankton increased when

predator densities or concentrations of predator-derived kairomones increase suggesting

that DVM is sensitive to predation risk (Ringelberg et al. 1991; von Elert and Pohnert

2000). Similarly, in a study of lakes with and without fish predators, the cyclopoid

copepod Cyclops absorssum only performed DVM in lakes where fish were present

(Gliwicz 1986).

In the case of meroplanktonic organisms (benthic-pelagic life history) that

undergo DVM, such as freshwater mysids (Mauchline 1980), a recurring question about

https://scholar.google.com/citations?user=bu1da3MAAAAJ&hl=en&oi=sra

6

their ecology is: Does DVM represent a daily routine-behavior experienced by all

individuals? A key assumption with DVM is that organisms performing this behavior

would prefer to be at shallow depths under ideal circumstances because of the greater

growth and reproductive advantages associated with shallow depths; they only migrate

because of predators (Kerfoot 1985; Figure 1.1). However, for organisms adapted to

feeding on benthic resources, how certain are we that this assumption is valid to explain

DVM in these organisms? For instance, could the preferred strategy of meroplankton

actually be to stay benthic, and that migration into the pelagia is actually the less

profitable behavior? Similarly, the questions of can meroplanktonic organisms meet

energetic requirements by feeding solely on benthic resources, is rarely evaluated in

species that undergo DVM between pelagic and benthic habitats. Assimilation efficiency

and food quality of detritus is assumed low relative to planktonic resources (Lasenby and

Langford 1973), however this remains untested in mysids.

Mysis ecology: distribution and vertical migration behavior

Members of the Mysis relicta species complex are considered glacial relicts

distributed throughout temperate and boreal zones of North America and Europe (Ricker

1959; Väinölä et al. 1994). They can have large ecological impacts on lakes and

reservoirs when introduced (Lasenby et al. 1986; Spencer et al. 1991). In temperate

regions of North America, the M. relicta complex is restricted to a single species Mysis

diluviana (formerly M. relicta, hereafter referred to as Mysis). Mysis is native to deep

glacial lakes mainly east of the Rockies including the Laurentian Great Lakes, the Finger

Lakes in NY, and several lakes throughout the Canadian provinces of Ontario and

Quebec. In Vermont, Mysis has been reported from lakes Dunmore, Champlain,

1 mm

7

Memphremagog, and St. Catherine (Gutowski 1978). In the western and some eastern

locations of the U.S., Mysis was intentionally introduced via stocking in lakes and

reservoirs (and spread to other water bodies) with the intention of bolstering fish

populations (Brown 1998; Lasenby et al. 1986; Martinez and Bergersen 1989; Johnson et

al. 2018). The practice of stocking Mysis, however, led to undesired outcomes by causing

declines in cladoceran zooplankton and reduced growth rates of kokanee salmon

Oncorhynchus nerka demonstrating the need to understand the ecological roles of Mysis

on food webs (Lasenby et al. 1986; Nesler and Bergersen 1991; Spencer et al. 1991;

Rudstam and Johannsson 2009; Walsh et al. 2012). In native environments, such as the

Laurentian Great Lakes, M. diluviana can be abundant and potentially consume more

zooplankton than fish (Gal et al. 2006; Bunnell et al. 2011). Mysis accounts for

approximately 30% of pelagic crustacean biomass in offshore Lake Ontario (Watkins et

al. 2015) and recent lake-wide surveys of Lake Superior estimated a population of 9.9

trillion individuals (Pratt et al. 2016). Both the Lake Ontario and Superior estimates are

based on night-pelagic sampling of the population during DVM and could be

conservative if pelagic individuals are only part of the total population. Therefore, if even

a small proportion of the population does not migrate at night, the non-migrant portion

could still represent a substantial biomass component in many lakes as evidenced by their

importance in food web models as both predators of plankton and a key prey species of

most fish species (Gamble et al. 2011a,b; Isaac et al. 2012; Kitchell et al. 2000; Rogers et

al. 2014; Stewart and Sprules 2011).

Mysis exhibits extensive DVM, capable of migrating > 100 m in a single night

(Beeton 1960). Based on conventional DVM theory, the ultimate cause of Mysis DVM is

8

considered to be predator avoidance from fish (Beeton 1960; Eshenroder and Burnham-

Curtis 1999; Boscarino et al. 2009) with light as the proximate factor triggering present-

day migrations (Beeton 1960; Teraguchi 1969; Boscarino et al. 2009, 2010). Previous

work on Lake Ontario suggests that light and temperature are more suitable for predicting

the pelagic depth distribution of Mysis densities than predators or food availability

(Boscarino et al. 2009), but this model does not include benthic-dwelling mysids and

therefore may only be useful for predicting the distribution of a select subset of

individuals. During nightly migrations, Mysis vertical distributions generally show peak

densities in the meta- or upper hypolimnion, remaining in water temperatures < 10°C

(Boscarino et al. 2009). Lab experiments have shown that mortality generally increases at

temperatures > 12°C (Rudstam et al. 1999). Lipid accumulation rates are higher at cooler

water temperatures if adequate food supply is available (Chess and Stanford 1999)

suggesting energetic and survival advantages associated with remaining at depth. Mysis

feed by filtering or using raptorial tactics to grab prey (Mauchline 1980). They have

relatively large compound eyes that can be used to sense light and visually locate prey

unlike other zooplankton (e.g., Daphnia) which have less developed eyes not capable of

perceiving prey but rather function only to sense changes in lighting (Ringelberg 2010).

Experimental evidence suggests that foraging rates of Mysis are higher at intermediate

water temperatures and light levels, relative to conditions normally experienced at deeper

lake depths (Ramcharan and Sprules 1986, Rudstam et al. 1999). Ramcharan and Sprules

(1986) observed higher predation rates on zooplankton at low light levels than complete

darkness, and proposed Mysis use visual feeding. Feeding rates follow a Gaussian

distribution, increasing at intermediate water temperatures typically experienced in the

9

lower metalimnion with peak feeding rate at 9°C (Rudstam et al. 1999; Gal et al. 2004).

Thus, Mysis may feed more efficiently on zooplankton prey by migrating into sub-

thermocline habitat where light levels and temperature may be higher than near the lake

bottom, along with greater zooplankton densities.

Sediments in aquatic habitats serve as a sink for settled organic material and

support active areas of nutrient recycling (Baker et al. 1991, den Heyer and Kalff 1998).

Benthic invertebrates play a key role in the resuspension and conversion of particulate

carbon into alternative forms via bioturbation, ingestion, excretion, and egestion (Baker

et al. 1991; Covich et al. 1999; Holker et al. 2015). Under DVM scenarios, mysids can

feed on benthic resources during the day, and transport benthic nutrients back into the

water column at night via excretion and egestion during pelagic foraging at night (Van

Duyn-Henderson and Lasenby 1986; Chipps and Bennett 2000; Sierszen et al. 2011).

Also, during night pelagic foraging, mysids can contribute to nutrient recycling within the

upper layers of the water column or repackage nutrients into fast-sinking fecal pellets that

are expedited to much deeper depths (Madeira et al. 1982; Chipps and Bennett 2000;

Linden and Kuosa 2004; Caldwell 2010). Nutrient recycling is probably higher at night

when mysids are pelagic because egestion rates increase with temperature and feeding

activity (Murtaugh 1984), although results from Lake Superior suggest Mysis

excretion/egestion has little effect on algal production relative to the nutrient regeneration

of zooplankton (Oliver et al. 2015).

Apart from describing Mysis DVM, several studies have also reported Mysis on or

near the lake bottom at night (Table 1.1; Bowers 1988; Shea and Makarewicz 1989), with

some studies proposing that populations actually follow a bimodal vertical distribution at

10

night (Morgan 1980; Bowers 1988; Rudstam et al. 1989). Therefore, Mysis display partial

diel vertical migration with some individuals migrating and some remaining resident

(Figure 1.1 Right). Observations of partial DVM in mysids raise several questions about

the theory of DVM behavior which for invertebrates has largely been described as a

population-level movement driven by predation-risk/growth tradeoffs. Conventional

theory predicts foraging potential to be higher near surface than at depth, however the

basis for this assumption comes from studies of holoplankton which only use pelagic

habitat. However, meroplanktonic organisms such as Mysis can not only occupy both

habitats, but can also feed successfully in both habitats. As a result of a meroplanktonic

niche, Mysis likely have a greater growth potential at depth than strictly holoplanktonic

species, and therefore may not conform to existing constructs for quantifying growth

potential advantages of DVM. Mysis escape tactics from predators can vary between

benthic vs. pelagic habitat (Bowers et al. 1990) leading to habitat-specific differences in

predation vulnerability regardless of light or predator densities. Mysis propels away from

predators with greater acceleration and maximum speed in benthic habitat than in the

water column by pushing-off the sediment surface (Bowers et al. 1990). In summary, the

biological differences in Mysis relative to holoplankton and consequences of benthic and

pelagic strategies create opportunities to challenge unifying constructs of DVM theory

that to date have been largely based on assumptions about vertical gradients relevant to

animals that rely solely on pelagic habitat throughout ontogeny.

11

Table 1.1: Compilation of studies that document partial migration in Mysis spp. (M. diluviana, M. mixta, M. relicta, and M. salemaai) at night.

Studies that did not report quantitative values of Mysis spp. on bottom at night were only included if they reported presence/absence.

Species Site Depth

(m)

Season†, Year % On

Bottom Method‡ Source

M. relicta (diluviana) L. Superior 250 Sum, 1986 50% Submarine; Pel Bowers (1988)

M. relicta L. Snasavatnet

(Norway)

48 Spr-Aut, 1984 23-70% Ben; Pel Moen & Langeland (1989)

M. relicta L. Jonsvatn (Finland) 10-80 Spr-Win, 1986-87 7-84%* Ben; Pel Naesje et al. (2003)

M. mixta Baltic Sea 28-40 Sum-Aut, 1985-86 30% Ben; Pel Rudstam et al. (1989)

M. relicta (diluviana) L. Ontario 35-100 Spr-Aut, 1984 < 5% Ben; Pel Shea & Makarewicz (1989)

M. relicta L. Breiter &

Schmaler Luzin

(Germany)

14-40 Spr-Aut, 2001-04 Present Scuba; Pel Waterstraat et al. (2005)

M. relicta (diluviana) L. Ontario 35-75 Spr-Aut, 1984 Present Predator diet Brandt (1986)

M. relicta (diluviana) L. Ontario 125 Spr-Aut, 1995 Present Ben; Pel Johannsson et al. (2001,

2003)

M. mixta; M.

relicta/salemaii

Baltic Sea 20-40 Spr-Aut,1985-86;

1996-97

15% Camera A. Staaf & S. Hansson

(unpublished data,

Stockholm Univ.)

M. relicta; M. salemaii Baltic Sea 30-35 Aut, 2008 Present Ben Ogonowski et al. (2013)

M. diluviana L. Champlain 70-120 Aut, 2014 Present Ben Euclide et al. (2017)

M. diluviana L. Champlain 60-100 Spr-Aut, 2015 3-46% Ben; Pel O’Malley et al. (2018)

* in terms of biomass † Spr = Spring (April-June), Sum = Summer (July-August), Aut = Autumn (September-November), Win = Winter (December-March) ‡ ‘Ben’ refers to benthic sled, beam trawl, or epibenthic sledge; ‘Pel’ refers to pelagic net towed vertically or horizontally.

12

1

Trophic role of Mysis in food webs

Mysis has been characterized as an opportunistic omnivore that consumes a wide

range of benthic and pelagic prey resources such as zooplankton, phytoplankton,

amphipods, insects, detritus, pollen (Rybock 1978; Grossnickle 1982; Johannsson et al.

2001, 2003; Caldwell et al. 2016), and even other mysids (McWilliam 1970; Nordin et al.

2008). One consistent finding is that Mysis target cladoceran prey when available (e.g.,

Daphnia spp. and Bosmina spp.; Cooper and Goldman 1980; Bowers and Vanderploeg

1982; O’Malley and Bunnell 2014) which Mysis only has access to during migration in

the epi- and metalimnetic zones during summer-fall months. However, studies that

identified preference for cladoceran prey have been restricted to analysis of pelagic-

caught Mysis during DVM or lab feeding experiments in which only pelagic zooplankton

were available, and failed to test preference given the true range of resources actually

available to a Mysis in a lake. A more comprehensive test of diet selectivity would

analyze preference in the presence of benthic and pelagic resources. Mysis alter their diet

when presented with changes in prey availability by incorporating larger-sized, non-

native predatory cladocerans (i.e. the fish-hook water flea, Cercopagis pengoi, and the

spiny water flea, Bythotrephes longimanus) in lakes where they occur (Nordin et al.

2008; O’Malley and Bunnell 2014; O’Malley et al. 2017). Techniques used to describe

mysid diets include: stomach analyses (Viherluoto et al. 2000; Nordin et al. 2008;

O’Malley and Bunnell 2014), stable isotope estimation coupled with mixing models

(Johannsson et al. 2001; Sierszen et al. 2011), estimated clearance rates in contained

13

environments (Bowers and Vanderploeg 1982), gut fluorescence (Grossnickle 1979;

O’Malley et al. 2017) and genetic analyses (Gorokhova 2009).

France (2012) suggested that Mysis tend to be more herbivorous in low

productivity environments, omnivorous at intermediate levels, and mostly

zooplanktivorous in more productive lakes. Other work has indicated that the extent of

Mysis omnivory varies within a lake primarily by body size and season (Branstrator et al.

2000; Johannsson et al. 2003; O’Malley and Bunnell 2014). Overall the degree of

herbivory in Mysis varies with season, mysid size, and likely the environment. In Lake

Ontario, grazing on pelagic phytoplankton appears to be an important feeding strategy of

Mysis during spring when phytoplankton constitute up to 50% of the overall diet, while in

summer through fall, mysids shifted towards a greater reliance on zooplankton and rarely

fed on phytoplankton (Johannsson et al. 2001). While spring may be an important grazing

period, Mysis also feeds on diatoms and other phytoplankton outside of spring potentially

using algae present in the deep chlorophyll layer after the onset of thermal stratification

(Bowers and Grossnickle 1978; Grossnickle 1979; O’Malley and Bunnell 2014). Mysids

select large-sized diatoms that would otherwise be inedible to smaller-sized zooplankton

that can only feed on smaller forms of phytoplankton (Bowers and Grossnickle 1982;

Grossnickle 1982). Ingestion and assimilation efficiency of large diatoms by Mysis is <

100% because they break apart diatoms with their mandibles before ingestion (review by

Takahashi 2004), which benefits copepods that can utilize these smaller fragmented

diatoms as they settle out of the upper water column, creating an indirect benefit/service

of Mysis grazing to primary consumers (Bowers and Grossnickle 1982).

14

Empirical data describing the benthic and pelagic contributions to Mysis diet are

rare. Most studies have focused on pelagic aspects of Mysis foraging by studying diet of

individuals collected during nocturnal migration into the water column (e.g., Whall and

Lasenby 2009; O’Malley and Bunnell 2014; Hyrcik et al. 2015). Mysids are also capable

of consuming benthic invertebrates and detritus during the day when they move

downwards to avoid light or possibly when some mysids remain on or near the bottom at

night (Bowers 1988; Shea and Makarewicz 1989; Johannsson et al. 2001, 2003). Such a

dynamic strategy is important to understand and predict to quantify energy flow in

deepwater habitats given the relatively large biomass and food web importance of Mysis

in lakes where they occur. Mysis have been hypothesized to consume a higher proportion

of benthic resources to compensate for low pelagic production during periods of low

plankton abundance (i.e., winter, Patwa et al. 2007). Consistent with the hypothesis that

seasonality dictates where in a lake Mysis feed, a higher proportion of Mysis are assumed

to remain on the bottom during fall through spring, when food availability is low

compared to summer (Johannsson 1995; Patwa et al. 2007). Mysis can be a predator on

benthic invertebrates such as the amphipod Diporeia (Parker 1980), but the potential

impacts of Mysis predation on benthic invertebrate fauna have only recently been

discussed (Stewart and Sprules 2011). For example, Stewart and Sprules (2011)

suggested that Mysis was likely a main predator on Diporeia in Lake Ontario during the

1990s given the high biomass of Mysis relative to fish in offshore Lake Ontario, and that

the overlap of these two invertebrates could have been even greater as water clarity

increased, forcing more mysids to reside near bottom during the day (Stewart and

15

Rudstam 2012). Similar realizations may occur in other systems as well if quantitative

estimates of non-migratory mysids at night become available to the research community.

The need for a partial DVM approach to mysid ecology

Understanding the population dynamics, behavior, and trophic ecology of key

organisms in food webs is important for depicting energy flow. In food web models, a

species’ ecological variation is often ignored or compressed into a single niche for

simplification (Pimm 1982; Pimm et al. 1991; Polis 1991). In nature, however, this is not

always the case, and in fact, numerous examples of intraspecific variation suggest the

role of a species can be far more complex and dynamic (Bolnick et al. 2003; Bolnick et

al. 2011). In Lake Michigan, Mysis was ranked as the most important keystone functional

group in a recent ecosystem model (Rogers et al. 2014), highlighting the importance to

consider the prevalence of alternative behaviors are and the extent to which such

alternative behaviors modify our perspective compared to a single niche model.

In the case of Mysis, a key forage species for Great Lakes fishes (Gamble et al.

2011a,b), biological monitoring programs have been designed to assume individuals

migrate into the pelagia at night. Consequently, Mysis assessment protocols rely solely on

nocturnal pelagic sampling, which fails to account for non-migrant benthic individuals.

Despite decades of research documenting the profound pelagic effects of mysids on food

webs (Lasenby et al. 1986; Rudstam and Johannsson 2009), very little if any effort has

been made to develop predictive models and sound theories exist to explain why some

mysids remain on bottom at night. If a substantial portion of the population remains

benthic at night, then Mysis may have equally important effects on benthic ecosystems as

they do on pelagic. Assumptions about DVM theory as a whole-population movement

16

and a tradeoff between growth/predation-risk is likely limiting empirical evaluation of

these critical assumptions for deep-water organisms. For example, recent food web

modelling highlighted the potential for Mysis predation as a cause for declines in Lake

Ontario’s Diporeia population (Stewart and Sprules 2011; Stewart and Rudstam 2012).

Equally concerning is whether Mysis may be experiencing increased predation pressure

from fish in the Great Lakes, in response to Diporeia collapse, because both Mysis and

Diporeia were historically major prey items of most Great Lakes fishes (Gamble et al.

2011a,b; Isaac et al. 2012; Bunnell et al. 2015). As a result, the Great Lakes Fisheries

Commission and other agencies have set research priorities to understand the dynamics of

Mysis and monitor their abundance over time throughout the Great Lakes (GLFC 2015;

Jude et al. 2018), including the adaptive capacity of key organisms to respond to

changing conditions (McMeans et al. 2016).

From a lake management perspective, if the proportion of Mysis occupying

benthic habitat at night is low, then pelagic estimates are appropriate for use in

management decisions requiring estimates of Mysis abundance and current pelagic

sampling is sufficient. If benthic contributions are high, then current Mysis biomass and

production estimates are biased low and potentially misleading. A re-evaluation of

profundal food web structure and function and outcomes of management actions would

then be necessary to include more realistic estimates of Mysis biomass, distribution, and

top-down effects on benthic organisms. Moreover, if partial DVM is related to, for

example, seasonality, demographics, feeding, or environmental conditions, then sampling

protocols can be better defined to account for these drivers of Mysis behavior. From a

theoretical perspective, study of partial DVM in Mysis will address several assumptions

17

surrounding DVM theory by evaluating classic views of DVM based on whole-

population rather than individual processes that might explain intraspecific variability in

migration behavior.

Variation in DVM behavior may be a result of a population with specialists

opposed to generalists. Individual specialization has been revealed for many populations

that were assumed to be generalists (Bolnick et al. 2003), leading to substantial progress

in population and community ecology (Bolnick et al. 2003, 2011; Violle et al. 2012).

Specialization can occur in many forms and one widely considered explanation is a

competitive advantage for different resources (Darimont et al. 2007; Svanback and

Bolnick 2007; Araújo et al. 2011). Diets of benthic- and pelagic-caught Mysis at night

have not been thoroughly considered, but one hypothesis is that partial migration is

related to specialized feeding (Chapman et al. 2011 and references therein). A study from

Lake Ontario noted some differences in diet between benthic-caught mysids just before

dawn and pelagic-caught mysids at night from a 125-m station (Johannsson et al. 2001).

Main findings were that benthic individuals contained more amphipod remains and

diatoms in their gut contents, and pelagic individuals had higher frequency of

zooplankton. In summary, partial migration could be due to different feeding behavior,

but as pointed out by Chapman et al. (2011), this hypothesis has not been widely tested.

Lake Champlain as a study system

Lake Champlain is a 170-km long, deep lake (max. depth = 122 m) located along

the borders of New York, Vermont, and Quebec. A majority of the lake by surface area is

classified as oligo-mesotrophic, though the lake is segmented into five distinct segments

(South Lake, Main Lake, Mallets Bay, Northeast Arm, Missiquoi Bay) that range from

18

oligotrophic to eutrophic (Facey et al. 2012; Xu et al. 2015). Mysis are found in the Main

Lake basin where most deep-water habitat occurs (Gutowski 1978; Ball et al. 2015).

Overall, benthic invertebrate biomass in Lake Champlain is low compared to the Great

lakes and other large lakes of the northeast (Myer and Gruendling 1979; Knight et al.

2018). The nearshore benthic region contains invasive zebra mussels (Dreissena

polymorpha) that were first reported in the South Lake in 1993 (Marsden et al. 2013).

The benthic amphipod Diporeia, which was historically abundant in the Great Lakes and

often co-occurs with Mysis in many deep lakes (Dadswell 1974; Nalepa et al. 2009), is

rare in Lake Champlain and has not been a prominent member of the benthos dating back

to historical records from the 1960s (Dermott et al. 2006; Knight et al. 2018). Quagga

mussels (D. rostriformis bugensis), which are similar to zebra mussels, and tend to

dominate the profundal benthos in lakes where they have invaded, have not yet been

detected in Lake Champlain but could invade the lake with potentially large ecosystem-

level effects (Marsden and Hauser 2009; Marsden et al. 2013; Knight et al. 2018).

Since 1992, Mysis abundance has been monitored at deep stations as part of the

Lake Champlain Long-Term Biological Monitoring Project (LTMP). The LTMP dataset

is based on pelagic vertical tows during the day to generate density estimates. Day-

pelagic tows, however, are rarely used for Mysis monitoring programs elsewhere because

Mysis are light-sensitive and population trends derived from day-pelagic tows could be

biased from variability in light intensity or changes in water clarity, in addition to

substantially underestimating true abundance when animals are concentrated on the

bottom during the day. Ball et al. (2015) analyzed trends in mysid abundance from the

LTMP dataset from 1992 to 2008 and identified a drastic decline in pelagic-day Mysis

19

densities after 1995. Mechanisms for the decline are not well understood. One hypothesis

for the decline is that declines in rotifer abundance, a known prey of Mysis, observed

over the same time period created food limitation for Mysis (Mihuc and Recknagel 2018).

However, rotifers are not perceived as a main prey item for Mysis in Champlain or other

lakes (O’Malley and Bunnell 2014; Hrycik et al. 2015), therefore food limitation due to

rotifer declines remains a correlative rather than mechanistic explanation. An alternative

hypothesis is the decline is not actually a change in abundance but rather an artifact due

to a change in vertical distribution if water clarity has increased. Changes in water clarity

of the main lake were not evident over the same time-period (Smeltzer et al. 2012),

suggesting that the population decline is real and not just an artifact of a change in

daytime vertical distribution (Ball et al. 2015). Similar long-term data on night-pelagic

density would be valuable to compare to day-derived population trends and evaluate

changes in vertical distribution. However, historical Mysis abundance estimates at night

are unavailable and a comparison of day vs night pelagic density estimates has not been

evaluated in Lake Champlain.

Dissertation outline

In the following dissertation chapters, I evaluate several aspects of partial

migration in Mysis diluviana from a Lake Champlain population. My aim is to better

define the role of partial vertical migration to understand the benthic and pelagic

distribution and trophic roles of Mysis in lake food webs, and thus contribute to the field

of migration ecology and specifically partial DVM. In the body of my dissertation I

address several research questions including: 1) Do demographic differences exist among

migrant and non-migrant individuals? 2) Does traditional net-based sampling adequately

20

sample the benthic region or are new camera-based techniques more effective? 3) Does

feeding behavior vary over a diel cycle and do diets differ among migrants and non-

migrants? and 4) Are migratory mysids more efficient predators on pelagic zooplankton

prey than benthic non-migrants? Collectively, the following chapters synthesize several

new aspects of partial diel vertical migration and mysid biology.

The second chapter, “Evidence for a size-structured explanation of partial diel

vertical migration in mysids”, addresses questions about demographic differences

between migrants and non-migrants, and potential implications for seasonal abundance

estimates in population assessment programs. Most monitoring programs rely solely on

pelagic sampling at night to estimate mysid stock abundance, growth rates, and assess

long term trends in abundance. However, to date the benthic portion of a population is

most often ignored and assumed negligible in food web models. If large amounts of

individuals remain close to the lake bottom at night and not susceptible to pelagic

sampling methods, then such behavior could lead to major bias in studies that assume

pelagic abundance is representative of the whole-lake population. Accounting for the

proportion of the population that does night migrate in terms of abundance, biomass, size

structure, and sex ratio will lead to more realistic depictions of Mysis population

dynamics in food web models.

In the third chapter, “An underwater video system to assess abundance and

behavior of epibentic Mysis”, a novel underwater video system is described and applied

to observe the abundance and behavior of Mysis near the lake bottom over the diel cycle.

The camera system is a self-contained, stationary unit that was deployed multiple times at

a 60-m site in Lake Champlain. Gear comparisons between the camera, benthic sled, and

21

a more portable video camera device were used to confirm findings that Mysis were

present on the lake bottom throughout the night, and showed little difference in benthic

density, suggesting that Mysis are continuously present near the bottom, throughout the

night. Moreover, density estimates from camera footage were higher than those from

concurrent benthic sled tows, suggesting benthic sled tows may underestimate Mysis

density.

In the fourth chapter, “Diel feeding behavior of a partially migrant population: A

benthic-pelagic comparison”, I used fine-scale sampling over multiple 24-hour periods to

test the hunger-satiation hypothesis for partial DVM. Stomach fullness and composition

was compared in mysid diets sampled from benthic and pelagic habitats at night, and

benthic habitat throughout the day. In general, Mysis diets were rarely empty, regardless

of time of day or habitat, suggesting they feed continuously and do not exhibit a diel

pattern in gut fullness related to the hunger-satiation hypothesis.

In the fifth chapter, “Comparative evaluation of migrant and non-migrant Mysis

feeding preferences”, a lab experiment was used to test the roles of prey availability on

foraging of benthic vs pelagic caught Mysis. I tested the prediction that Mysis caught in

the pelagia at night (migrants) prefer pelagic food, whereas benthic Mysis (non-migrants)

prefer benthic food. Feeding rates and stomach contents of Lake Champlain Mysis were

compared from individuals exposed to one of three treatments: pelagic food only, benthic

food only, or both. Contrary to my prediction, I found that even in the presence of

Daphnia (preferred zooplankton prey), Mysis still readily consumed sedimented detritus

in treatments where Mysis were offered both.

22

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Waterstraat, A., M. Krappe, P. Riel, and M. Rumpf. 2005. Habitat shifts of Mysis relicta

(Decapoda, Mysidacea) in the lakes Breiter and Schmaler Luzin (NE Germany).

Crustaceana 78:685-699.

Watkins, J. M., L. G. Rudstam, M. J. Connerton, T. Schaner, P. G. Rudstam, and K. L.

Bowen. 2015. Abundance and spatial distribution of Mysis diluviana in Lake

Ontario in 2008 estimated with 120 kHz hydroacoustic surveys and net tows.

Aquatic Ecosystem Health & Management 18:63-75.

Werner, E. E., J. F. Gilliam, D. J. Hall, and G. G. Mittelbach. 1983. An experimental test

of the effects of predation risk on habitat use in fish. Ecology 64:1540-1548.

Whall, J. D., and D. C. Lasenby. 2009. Differences in the trophic role of Mysis diluviana

in two intermontane lakes. Aquatic Biology 5:281-292.

Williamson, C. E., J. M. Fischer, S. M. Bollens, E. P., Overholt, and J. K. Breckenridge.

2011. Toward a more comprehensive theory of zooplankton diel vertical

migration: integrating ultraviolet radiation and water transparency into the biotic

paradigm. Limnology and Oceanography, 56:1603-1623.

Zaret, T. M., and J. S. Suffern. 1976. Vertical migration in zooplankton as a predator

avoidance mechanism. Limnology and Oceanography 21:804-813.

34

CHAPTER 2: EVIDENCE FOR A SIZE-STRUCTURED EXPLANATION OF

PARTIAL DIEL VERTICAL MIGRATION IN MYSIDS

Brian P. O’Malley1,*, Sture Hansson2, Jason D. Stockwell1

1 Rubenstein Ecosystem Science Laboratory, University of Vermont, 3 College Street,

Burlington, VT 05401, USA.

2Department of Ecology, Environment and Plant Sciences, Stockholm University, SE-106

91, Stockholm, Sweden

*corresponding author: Tel. 1 + (413) 231-4907; Email address:

[email protected]

Running head: Mysis partial DVM


35

Abstract

Mysids are known for benthic-pelagic diel vertical migration (DVM), where the

population is benthic by day and pelagic by night. However, historical and recent

observations in members of the Mysis relicta complex suggests populations exhibit

partial DVM, with some remaining benthic at night. We used pelagic net and benthic sled

tows to assess diel habitat use by Mysis diluviana at two stations (60 and 100 m deep) in

Lake Champlain, USA, during June-November 2015. At both stations, mysids were on

the bottom both day and night, but the extent of pelagic habitat use by Mysis varied by

site depth. At 60-m, pelagic densities were an order of magnitude lower during the day

compared to at night, indicative of benthic-pelagic DVM. Contrary to expectations, we

found no diel difference between pelagic and benthic sled density estimates at 100-m,

suggesting an equal number of Mysis are benthic day and night, and an equal number are

pelagic day and night at deeper sites. Mean body length of benthic-caught mysids was

greater than pelagic-caught individuals, a pattern that was evident both day and night at

100-m. Our findings indicate Mysis partial DVM is common across seasons and

influenced by body size and depth.

Keywords: Mysis diluviana, diel vertical migration, partial migration, body size, Lake

Champlain, depth

36

Introduction

Diel vertical migration (DVM), the movement of organisms between deep and

shallow habitats from day to night, is a widespread behavior in aquatic organisms ranging

from plankton to large vertebrates across marine and freshwater settings (e.g. Cullen,

1985; Guisande et al., 1991; Stockwell et al., 2010). Lakes and oceans present natural

frameworks for conceptualizing and measuring tradeoffs in migratory behavior due to the

strong vertical gradients of abiotic (temperature, light) and biotic variables (prey,

predators) (Werner et al., 1983; Boscarino et al., 2009; Vanderploeg et al., 2015). The

most common hypothesis for the evolution of DVM in invertebrates is that DVM

represents a strategy to minimize an individual’s predation-risk (µ) relative to its growth

potential (g) (i.e. µ/g ratio) to optimize energetic gains relative to survival probability

(Zaret and Suffren, 1976; Loose and Dawidowicz, 1994; Hays, 2003).

Support for the predator avoidance hypothesis in pelagic plankton has come from

models (Fiksen and Carlotti, 1998; De Robertis, 2002), experiments (Johnsen and

Jakobsen, 1987; Lampert, 2005), and field observations (Ringelberg, 1991; Bollens et al.,

1992). However, DVM behavior can vary within and among populations (Gliwicz, 1986;

Ringelberg, 1991; Ringelberg et al., 1997). For example, species known to exhibit DVM

also demonstrate the capacity to undergo reverse migration (i.e. migrating down in the

water column at night, Jensen et al., 2011) or partial migration (Mehner, 2012), further

highlighting the importance of considering intraspecific variation in unraveling migration

decision-making processes. While variability in DVM behavior has been recognized

(Bollens and Frost, 1989; Hays et al., 2001; Mehner and Kazprak, 2011), the assumption

37

remains that organisms partaking in DVM represent most of the population (Ringelberg,

2010).

Developments in DVM theory for zooplankton have come mainly through studies

of holoplankton (Hays, 2003; Pearre, 2003; Lampert, 2005; Cohen and Forward, 2009;

Ringelberg, 2010). Meroplankton, however, also undergo substantial DVM, shifting from

benthic to pelagic habitats and consuming both benthic and pelagic resources

(Johannsson et al., 2001; Jumars, 2007; Schmidt et al., 2011; Sierszen et al., 2011). In

freshwater lakes, meroplankton in the Mysis relicta complex exhibit some of the most

extensive DVM, migrating hundreds of meters in a single night (Beeton, 1960;

Ahrenstroff et al., 2011). If Mysis follow classic DVM theory, then the population should

migrate into the water column at night to secure necessary resources for growth while

minimizing predation risk from visual predators. Consistent with theory, one assumption

for why Mysis perform DVM is that Mysis require high-energy zooplankton prey, in

comparison to just feeding on presumed low-energy benthic resources. However, benthic

resources can account for a substantial portion of Mysis’ diet (Johannsson et al., 2001;

Sierszen et al., 2011), which challenges the conventional template of a “one-way”

vertical gradient in food potential used in DVM theory (Lampert, 1989, 1993;

Ringelberg, 2010; Mehner, 2012). The benthic environment has been largely ignored

when addressing µ/g tradeoffs hypothesized to dictate Mysis DVM behavior, likely

because of inherent assumptions with the predator avoidance hypothesis for DVM and

vertical structure of food in the pelagic environment (Boscarino et al., 2009; Ahrenstoff

et al., 2011). Equally plausible, yet untested, is the hypothesis that Mysis prefer to remain

benthic and only migrate into the water column when required.

38

Previous studies on diel benthic-pelagic habitat use by Mysis suggest they exhibit

partial DVM, whereby portions of the population occur in both habitats at night (Bowers,

1988; Moen and Langeland, 1989; Rudstam et al., 1989). Existing hypotheses to explain

partial migrations in invertebrates, however, have not yet been widely studied (Chapman

et al., 2011). Insights on partial DVM in other aquatic species provide a starting point to

test for mechanisms in Mysis partial DVM. Variability in DVM within a population could

be related to individual body condition (Hays et al., 2001). The fasting endurance

hypothesis predicts that smaller-sized individuals deplete resource stores faster, and

therefore are more likely to migrate than larger individuals that use resources more

efficiently (Chapman et al., 2011). Size-dependent predation vulnerability could also

explain potential size differences in migrants and non-migrants (Hays, 1995; Hansson

and Hylander, 2009; Skov et al., 2011). Larger individuals in a population remain in

habitats with low risk and low growth potential compared to smaller individuals (Hays,

1995). Under the size predation hypothesis, larger Mysis are more likely to be found on

or near the lake bottom at night to reduce risk of predation compared to smaller Mysis.

Mysis are also cannibalistic (Nordin et al., 2008) and juveniles can detect and avoid

chemical cues of larger mysids (Quirt and Lasenby, 2002). Therefore, an alternative

hypothesis is that DVM is largely a juvenile tactic to avoid cannibalism by benthic adults.

In Lake Champlain, USA, non-migrant mysids (i.e. benthic-caught at night) collected in

late-autumn were larger on average than migrants (Euclide et al., 2017). Because

seasonal dynamics of pelagic production, light levels, and thermal stratification could

create conditions where migration is more or less profitable for some size classes at

39

different times of year, length data on migrant and non-migrant Mysis from other times of

the year are needed to test if body size differences are maintained across seasons.

Here we further test the hypothesis that invertebrates exhibit partial DVM by

exploring partial DVM of Mysis diluviana in Lake Champlain, USA. We used monthly

sampling of benthic and pelagic habitats to identify if Mysis were present on the bottom

and in the water column at night across seasons (June - November 2015), and to test for

differences in day and night density estimates and demographic data (body size, sex, and

life-stage) within and among each habitat type. Because conventional DVM theory

predicts that Mysis should migrate from the bottom, where they reside during day, up into

the water column at night (Grossnickle and Morgan, 1979), we predicted that day-pelagic

densities would be less than night-pelagic densities. Similarly, we expected patterns in

day to night benthic densities to be opposite to pelagic densities – higher densities of

benthic Mysis during the day than at night. Using individual body size and demographic

data, we evaluated if differences existed between migrants and non-migrants across

months. We predicted that non-migrants would be larger and consist of a higher

proportion of females than migrants across all seasons. Based on Mysis life-history, we

predicted differences in mean body size of migrants and non-migrants would decline

from spring to autumn, due to the maturation of a mostly juvenile population in spring to

an adult dominated population by late-autumn.

Methods

Mysis diluviana was sampled monthly from June to November 2015 in the main

basin of Lake Champlain, USA. Collections were made during the day and night from

pelagic and benthic habitats at two sites with bottom depths of 60 and 100 m (Figure 2.1).

40

Visual inspection of substrate indicated fine sediment of similar color at both sites. The

main basin of Lake Champlain is considered mesotrophic with secchi depth ranging from

4-6 m (Smeltzer et al., 2012; Xu et al., 2015). Day samples were collected at least two

hours before sunset, and night samples at least one hour after sunset between 21:00-

01:00. Sampling concluded several hours prior to sunrise. Temperature profiles were

collected using a Seabird CTD.

Figure 2.1: Map of sampling sites by bottom depth for Mysis collections in Lake

Champlain, USA, in June-November 2015.

41

For each site-month, three replicate pelagic samples were collected using a 1 m-2

square-frame net (1000-µm mesh, 250-µm cod-end) towed vertically through the water

column from 2 m above bottom to the surface, following standard collection procedures

for estimating pelagic Mysis density in Lake Champlain and other North American lakes

(Ball et al., 2015; EPA, 2015). Day and night pelagic densities (individuals m-2) for each

site-month were estimated as the mean of the three replicates. Only two replicates were

collected for pelagic sampling at the 60-m site in July during the day. Day and night

benthic densities at each site-month were estimated by the mean of two replicate samples.

Benthic samples were collected using a benthic sled (opening 0.46 m x 0.26 m; 1000-µm

mesh, 250-µm cod-end) towed for 5 minutes along bottom at a vessel speed of 0.8 m sec-

1. Upon retrieval, contents of each replicate were rinsed into a separate jar. Start and end

coordinates were used to estimate tow distance and vessel speed for benthic transects

(mean distance 0.20 km). Beginning in August, a depth sensor (TDR-MK9, Wildlife

Computers) was attached to the benthic sled to measure contact time with the bottom.

The sensor showed that at vessel speeds of 0.8 m sec-1 the sled remained in contact with

the lake bottom for the duration of the benthic tow. Area swept for each benthic sled tow

was estimated as the distance traveled multiplied by the sled opening width, and was used

to estimate benthic density (individuals m-2). All samples were stored in ethanol for

laboratory processing. Nets were not equipped with flowmeters. Due to the large mesh

size of each gear and previous observations, we assumed 100% filtration efficiency when

calculating densities.

Because the benthic sled was open on deployment and retrieval and could

potentially catch pelagic mysids, additional tows were taken to check how many mysids

42

were sampled in the water column by the sled. Immediately after benthic sample

collections in August and September (at night), the benthic sled was deployed using the

same amount of cable as standard tows until it reached bottom, then was immediately

retrieved. Any mysids collected were assumed to be pelagic-caught (sensu Rudstam et

al., 1989) and considered a maximum estimate since some benthic mysids could still be

collected just as the sled reached the bottom. When the mean of two reps was subtracted

from the total catch of benthic sled samples, the difference suggested that only a small

percentage of mysids in benthic samples were captured during descent or ascent (Table

2.1, mean = 5.5%). Because the number of individuals collected was small and likely

even lower during day sampling, we did not adjust total catch of benthic samples for

amount captured in the water column.

Table 2.1: Number of Mysis collected during descent/retrieval of the benthic sled versus

number collected in standard five-minute benthic sled tow, and the percent of pelagic

Mysis in benthic tows in Lake Champlain, 2015. Values are the mean of two replicates.

Month Site depth

(m)

Descent/retrieval 5-min. benthic

sled tow

Percent

August 60 36.5 360.5 10.1%

100 49.0 1107.5 4.4%

September 60 54.0 1144.5 4.7%

100 45.0 1760 2.6%

Mysids were counted and measured from the tip of the rostrum to the tip of the

telson at 10X under an Olympus SZX dissecting scope equipped with a calibrated

digitizing tablet. Sex was determined on mysids > 10 mm. Mysids < 10 mm were

classified as juveniles. Benthic sled catches were occasionally high (exceeding 4,000

43

individuals), thus length measurements were only taken on a subset of 200 randomly

selected individuals per sample.

To test for presence of partial DVM in Lake Champlain, we assessed monthly

estimates of Mysis in the water column and on the bottom, both day and night. During the

day, more mysids should be found on the bottom as migrants return from nightly

foraging. Therefore, we predicted benthic densities from benthic sled tows would be

higher during the day than at night. We used paired t-tests to evaluate the hypothesis that

day density is greater than night density for sled density estimates. Day-night pelagic

sampling should mirror changes observed in the benthos because our pelagic net samples

were towed through nearly the entire water column, from 2 m above the bottom to

surface. We tested if night-pelagic density was greater than day-pelagic density using

paired t-tests.

Mean length of benthic and pelagic individuals collected at night and during the

day were compared using paired t-tests across months for each site, both within (e.g.

benthic day vs. benthic night) and across habitat types (e.g. benthic day vs. pelagic day).

Because day-pelagic Mysis were rare at the 60-m station, we only compared day-night

lengths from our 100-m station. Differences in the proportion of juveniles (< 10 mm),

females, and males between night-benthic and night-pelagic samples were assessed using

chi-squared tests. For all statistical tests, α = 0.05 was used as a cutoff for significance.

Results

We found evidence of partial DVM by Mysis at both sites in Lake Champlain

across all sampled months. Mysids were abundant on the bottom at night each month

sampled (Figure 2.2 bottom). Day-night comparisons of benthic sled data revealed

44

different results depending on site depth (Figure 2.2 bottom). Consistent with predictions

about Mysis DVM, mean (± SD) benthic sled density during the day at 60 m (18.5 ± 13.5

Mysis m-2) was higher than at night (9.7 ± 7.4 Mysis m-2; paired t-test: t5 = 2.83, P <

0.05). However, at 100 m, no difference was observed between mean day (19.3 ± 11.9)

and mean night (17.6 ± 12.6) benthic sled densities (paired t-test: t5 = 0.43, P > 0.05).

Day-night comparisons of pelagic densities (Figure 2.2 top) yielded similar findings to

benthic sled results – no difference at 100 m (paired t-test: t5 = -0.92, P > 0.05) between

pelagic-day (70.5 ± 44.3) and pelagic-night (105.0 ± 91.5), but a significant difference at

60 m (paired t-test: t5 = -7.35, P < 0.01) with an order of magnitude more pelagic Mysis

detected at night (67.8 ± 23.6) than during the day (5.0 ± 5.7).

Figure 2.2: Monthly diel comparison of mean pelagic density of Mysis (top) estimated

from vertical net tows from 2 m above lake bottom to surface tows in Lake Champlain

2015, and mean benthic Mysis density (bottom) estimated from benthic sled tows at 60-

(left) and 100-m site sites (right). Open bars are day samples and filled bars are night

samples (+ SD).

45

Mean body length of Mysis differed between benthic and pelagic individuals at

night (Figure 2.3). At the 60-m site (Figure 2.3 Left), mean (± SD) length of benthic-

caught Mysis (13.4 ± 0.9 mm) was greater than pelagic-caught individuals (10.2 ± 0.7

mm; paired t-test t5 = 6.24, P < 0.01). Similarly, at the 100-m site (Figure 2.3 Mid), mean

length of benthic-caught individuals (15.8 ± 0.6 mm) was greater than pelagic-caught at

night (10.7 ± 2.0 mm; t5 = 5.09, P < 0.01). Overall, the difference between mean length

of night-benthic and night-pelagic individuals decreased as a function of sampling date (P

< 0.01, R2 = 0.54) from a difference of 6.4 mm in June to 1.4 mm in November

(Supplemental Figure 2.6). Pooling lengths across all months, size-frequency

distributions were skewed towards smaller individuals in night-pelagic samples (Figure

2.4). More than 60% to 80% of Mysis encountered in night-benthic sampling, at 60 and

100-m respectively, were individuals > 12 mm in length (Figure 2.4).

Mean body length also differed between benthic and pelagic individuals during

the day at the 100-m site (Figure 2.3 Right). Consistent with our observations at night,

mean length of day-benthic individuals (15.6 ± 0.8 mm) was greater than day-pelagic

(10.1 ± 3.1 mm; t5 = 3.59, P < 0.05). Mean length of pelagic-caught mysids was similar

between day and night collections (day= 10.1 ± 3.1 mm; night = 10.7 ± 2.0 mm; t5 = -

0.75, P > 0.05). Similarly, we found no difference in mean length of benthic-caught

mysids between day and night at 100-m (day = 15.6 ± 0.8 mm; night = 15.8 ± 0.6 mm; t5

= -0.75, P > 0.05). Because too few individuals were collected in day-pelagic samples at

60-m, mean body length from day to night was only compared for benthic sled samples

from this site. Mean body length in benthic sled samples at 60-m was lower during the

46

day compared to at night (day = 12.5 ± 1.2 mm; night = 13.4 ± 0.9 mm; t5 = -3.35, P <

0.05).

Figure 2.3: Mean (± SD) body length (mm) of pelagic (grey circles) and benthic-caught

(black circles) Mysis at 60- and 100-m sites in Lake Champlain 2015 as a function of

month sampled. Note that mesh size (1 mm) was consistent between the two gear types.

Insufficient numbers of Mysis were captured in the pelagic habitat during the day at the

60-m site to compare mean length of day-benthic to day-pelagic individuals.

47

Figure 2.4: Frequency of Mysis by size class pooled across all months (June-November

2015) in night-pelagic and night-benthic samples at 60- (top) and 100-m (bottom) sites in

Lake Champlain.

Chi-squared analyses revealed significant differences in life-stage composition

(juveniles, females, males) between night-benthic and night-pelagic samples for each

month pooled across both sites (Table 2.2). Night-pelagic samples comprised mostly

juvenile mysids (mean across sites = 49.9 ± 16.0 %; Fig. 5), followed by mature females

(29.9 ± 8.4%) and mature males (20.2 ± 12.3%). Night-benthic sled samples comprised

mostly mature female mysids (63.8 ± 13.1%), followed by mature males (26.9 ± 11.4%)

and juveniles (9.4 ± 7.0%; Fig. 5). The proportion of mature males in pelagic samples

48

increased from June to November at 100-m, but at 60-m the difference in males from

June to November was much smaller (Figure 2.5).

Figure 2.5: Percent composition of juvenile, female, and male Mysis collected in night-

pelagic (top) and night-benthic samples (bottom) at 60- (left) and 100-m (right) sites in

Lake Champlain.

49

Table 2.2: Number of juvenile, female, male, and total mysids counted from night-

benthic and night-pelagic samples by month pooled across both sites, and P-values of chi-

squared tests comparing demographic proportions.

Month Habitat Juveniles Males Females M: F Total χ2 p-value

June Benthic 47 89 664 0.13 800

Pelagic 339 47 73 0.64 459 < 0.001

July Benthic 104 123 573 0.21 800

Pelagic 159 41 106 0.39 306 < 0.001

August Benthic 48 246 506 0.49 800

Pelagic 606 213 307 0.69 1126 < 0.001

September Benthic 44 293 463 0.63 800

Pelagic 162 65 94 0.69 321 < 0.001

October Benthic 84 275 441 0.62 800

Pelagic 168 68 142 0.48 378 < 0.001

November Benthic 123 264 413 0.64 800

Pelagic 187 314 200 1.57 701 < 0.001

Discussion

Overall, we found consistent evidence of partial DVM by Mysis across all

sampling dates. Mysis occurred in the water column and on the bottom, each night, which

agrees with similar studies on the vertical distribution of Mysis spp. in other systems

(Moen and Langeland 1989, Rudstam et al. 1989). Our results suggest that Mysis were

not only present on the bottom at night, but that benthic individuals were also larger on

average than pelagic individuals, suggesting that variability in Mysis DVM behavior can

at least be partly explained by body size. The difference in average length between

benthic and pelagic Mysis at night agreed with previous findings in Lake Champlain

(Euclide et al. 2017). In addition, our seasonal sampling revealed the difference in mean

50

length between benthic and pelagic Mysis at night decreased from June to November, and

mean body size of pelagic and benthic Mysis did not change from day to night within a

month. Differences in male to female ratios between migrants and non-migrants were

evident, with proportionally more females found in night-benthic samples than night-

pelagic samples. Length and life-stage differences are consistent with several hypotheses

for partial DVM (Chapman et al., 2011), but difficult to tease apart given the current state

of knowledge.

The difference in mean body size observed between benthic and pelagic

individuals at night became less pronounced as the season progressed, likely reflecting

the maturation of spring recruits in pelagic samples to adult stages. Mysis typically

undergo breeding in late autumn through winter, with spring and summer cohorts

produced annually (Mauchline, 1980). In Lake Champlain, previous Mysis studies using

pelagic-day and pelagic-night sampling found distinct juvenile cohorts in spring and

summer, transitioning to mostly large individuals in autumn (Ball et al., 2015; Hrycik et

al., 2015). Our day and night pelagic sampling revealed a similar life history progression,

with high proportion of juveniles in spring-summer months. In contrast, our benthic

sampling routinely showed high proportions of adult size classes were present even

during summer months.

The mean length of benthic Mysis was consistently greater at our deep site

compared to the shallow site. Similar increases in Mysis size with bathymetric depth have

been reported from the Great Lakes (Johannsson, 1995; Pothoven et al., 2000). Variation

in body size as a function of bottom depth could be related to horizontal migration or

differences in growth and maturity. Horizontal migration of Mysis has been reported from

51

other systems, although interpretation of such patterns seems to vary by system. For

example, Moen and Langeland (1989) reported Mysis horizontal distributions follow a

seasonal pattern with large Mysis occupying shallow waters in spring, likely to release

their young in these shallow waters, then move back to deeper waters. In contrast,

horizontal migration reported by Morgan and Threkheld (1982) indicated that large Mysis

remained deep year-round, and only small Mysis disperse into shallow depth zones. In

total, seasonal differences in body length with bathymetric depth in Lake Champlain

were apparent in our sampling and suggest that larger Mysis remain in deep waters

throughout the year while smaller sizes were found at our shallower site.

Body size differences between benthic and pelagic individuals at night could

relate to multiple hypotheses for partial migration behavior in populations. Several

studies have found evidence for size structured vertical distribution of pelagic Mysis with

smaller individuals higher up in the water column (Boscarino et al., 2009; Ogonowski et

al., 2013). Based on our size-frequency data, we found that the size-structured vertical

distribution of mysids continues from pelagic all the way to benthic habitat as well, with

larger individuals occurring on bottom. Experimental work suggests juvenile Mysis can

tolerate higher temperatures and that adult mysids tend to remain below 6°C during DVM

with increased mortality at temperatures > 12°C (Rudstam et al., 1999; Boscarino et al.,

2009, 2010). If temperature preferences of Lake Ontario Mysis are similar in Lake

Champlain populations, then adult Mysis in Lake Champlain could potentially be seeking

benthic habitat as a thermal refuge during autumn months when hypolimnetic

temperatures exceed 6°C (Supplemental Figure 2.7). Thermal refuge, however, would not

52

explain size-dependent partial DVM in other seasons when hypolimnetic temperatures

are cooler and large individuals were still common on bottom.

Resource and habitat preferences of individuals can shift with ontogeny from

maximizing somatic growth when young to maximizing reproductive output as adults.

Experimental evidence suggests that foraging rates of Mysis are higher at intermediate

water temperatures and light levels, relative to conditions normally experienced at deeper

lake depths (Ramcharan and Sprules, 1986; Rudstam et al., 1999). Furthermore, juvenile

mysids maximize their growth at higher temperatures than adults (Johannsson et al.,

2008) suggesting growth advantages exist for pelagic juveniles. Mysis may feed more

efficiently on plankton prey by migrating into sub-thermocline habitat where light levels,

temperature, and prey densities are higher than near the lake bottom. However, lipid

accumulation rates are greater at cooler water temperatures (Chess and Stanford, 1999)

suggesting alternative growth and survival advantages associated with remaining at depth

if adequate food supply (detritus and benthic invertebrates; Parker 1980) is available,

especially for adult size classes. Moreover, building sufficient lipid reserves is often

critical for winter survival and increased reproductive success (Hagen et al., 1996),

therefore remaining benthic could be an energetic strategy for adults to increase

reproductive success rather than to increase somatic growth. To evaluate growth-related

hypotheses, a comparison of growth rates by different size classes on strict diets of

pelagic or benthic food resources is needed to fully explore Mysis life-history tradeoffs in

resource use.

Our data suggest that during day, the proportion of benthic and pelagic

individuals varies by site depth. At our shallow site, a high degree of benthic-pelagic

53

DVM was evident – that is, pelagic Mysis were rare during day compared to night.

However, at our deeper site, we did not find a difference in day to night pelagic density

suggesting that a similar number of Mysis were pelagic regardless of the time of day.

Such depth-specific differences in DVM patterns could have important consequences for

understanding Mysis DVM – the benthic-pelagic function of Mysis is misrepresented if a

substantial amount remains pelagic during the day. Previous work at 100-m in Lake

Champlain detected Mysis as far as 40 m off bottom during the day, with no apparent

differences in day-night pelagic densities (Ball et al. 2015; Hrycik et al. 2015). At

extremely deep sites, benthic-pelagic DVM might not be energetically feasible for Mysis

if distance from the thermocline to bottom exceeds some energetic threshold (Morgan et

al., 1978). Instead, migrating from deep to shallow pelagic habitat might be advantageous

for some individuals, while remaining benthic is better for others. Therefore, at deep

sites, a working hypothesis for no difference between day-night pelagic density is that

pelagic Mysis during day are the same group of pelagic individuals observed at night.

Likewise, no day-night difference in benthic Mysis density suggests potential for a

benthic population, mainly composed of adult stages that likely use benthic food

resources to a much greater extent than pelagic Mysis. Previous work that identified

differences in C: N ratios between benthic and pelagic Mysis at night (Euclide et al.,

2017) supports our working hypothesis. Future studies that test if day-suspending Mysis

are the same pelagic individuals at night could fill in key assumptions about the benthic-

pelagic nutrient flux by Mysis DVM.

Our sampling method used different gears, which is not necessarily ideal for

comparing across habitat types that vary in structure and dimensions. Several previous

54

studies have reported biases depending on gear types or dimensions (net width, mesh,

tow speed), making comparisons across gear types difficult (De Bernardi, 1984; Pepin

and Shears, 1997). Repeated sampling with the same gear type is useful for diel

comparisons. Thus, to control for net or habitat effects, we restricted our day-night

comparison to within gear types. In comparing benthic-pelagic net-based estimates, we

controlled for net mesh effects by using the same mesh size for both the benthic sled and

pelagic net. The net opening of the benthic sled (0.12 m2), however, was smaller

compared to the 1 m2 pelagic net opening. If nets were size-selective based on their

mouth area then we would have expected to see a higher proportion of larger individuals

in our pelagic net, which was not the case. Studies on benthic/pelagic gear comparisons

are rare, but a recent comparison between large and small diameter nets used to sample

pelagic Mysis revealed no difference in catch rates or composition (Silver et al., 2016).

Measuring the efficiency with which each gear type samples its respective habitat would

greatly improve our ability to estimate the percent on bottom, ultimately leading to

refined theories on partial migration behavior and more holistic population assessments.

Mysid abundance is monitored in many lakes using pelagic sampling at night.

Recent pelagic surveys estimated Mysis accounts for approximately 30% of pelagic

crustacean biomass in offshore Lake Ontario (Watkins et al. 2015), and in Lake Superior,

a population of 9.9 trillion individuals was estimated (Pratt et al. 2016). Both the Lake

Ontario and Superior estimates are based on night-pelagic sampling of the population

during DVM, and could be conservative estimates if migration is only part of the picture

as we found in Lake Champlain. If even a small proportion of a Mysis population does

not migrate at night, that proportion still represents a substantial biomass component in

55

many lakes as evidenced by their importance in food web models as both predators of

plankton and a key prey to most fish species (Kitchell et al., 2000; Stewart and Sprules,

2011; Isaac et al., 2012). Further evaluation of the factors predicting the proportion of

Mysis populations remaining benthic at night, when pelagic surveys are performed, will

allow researchers to better account for sampling biases associated with pelagic methods

that miss benthic individuals.

Conclusions

In summary, our results represent a step towards evaluating Mysis DVM in the

context of partial migration by including benthic distributions with the oft-studied pelagic

distributions. Our findings suggest Mysis undergo an ontogenetic shift in DVM behavior

from using the pelagic environment as juveniles to a greater reliance on benthic habitat

with increasing size. Further, our results suggest depth-specific differences in DVM

behavior should be considered when constructing conceptual frameworks of Mysis DVM.

We suggest that bottom depth and other factors such as water transparency and light,

interact to influence the extent to which Mysis populations exhibit complete benthic-

pelagic DVM. Improvements in benthic and pelagic sampling methods that incorporate a

vertically stratified sampling approach, and simultaneous sampling of benthic and pelagic

habitats, will ultimately lead to greater insights regarding Mysis DVM behavior and

improved estimates of population size and biomass.

Acknowledgements

We thank Captain Steve Cluett and Deckhand Krista Hoffsis for their technical

expertise in field sampling aboard the R/V Melosira, and Jessie Gordon, Kevin Melman,

56

and Pascal Wilkins for help with sample processing. This project was supported by the

Great Lakes Fishery Commission with the assistance of Senator Patrick Leahy.

57

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63

Supplemental Figure 2.6: Difference between mean lengths of benthic and pelagic Mysis

collected at night by site (60 m = triangles; 100 m = circles) as a function of day of year.

Blue line indicates linear model and grey ribbon represents 95% confidence intervals.

64

Supplemental Figure 2.7: Water temperature isopleths at 60-m (left) and 100-m (right)

where Mysis sampling took place in Lake Champlain.

65

CHAPTER 3: AN UNDERWATER VIDEO SYSTEM TO ASSESS ABUNDANCE

AND BEHAVIOR OF EPIBENTHIC MYSIS

Brian P. O’Malley1, 4, *, Rebecca A. Dillon1, 5, Robert W. Paddock2, Sture Hansson3, Jason

D. Stockwell1

1 Rubenstein Ecosystem Science Laboratory, University of Vermont, Burlington, VT,

USA

2 School of Freshwater Sciences, University of Wisconsin-Milwaukee, 600 E Greenfield

Avenue, Milwaukee, WI, USA

3 Department of Ecology, Environment and Plant Sciences, Stockholm University, SE-

106 91, Stockholm, Sweden

4 Present address: USGS Great Lakes Science Center, Lake Ontario Biological Station,

Oswego, NY, USA

5 Present address: Aquatic Ecology Laboratory, Department of Evolution, Ecology, and

Organismal Biology, The Ohio State University, 1314 Kinnear Road, Columbus, OH,

USA

*Corresponding author: [email protected]


66

Abstract

The application of remote video technologies can provide alternative views of in

situ behavior and distributions of aquatic organisms that might be missed with traditional

net-based techniques. We describe a remote benthic video camera system designed to

quantify epibenthic density of the macroinvertebrate Mysis diluviana. We deployed the

camera multiple times during the day and night at a 60-m depth site in Lake Champlain

and quantified Mysis density from the footage using basic methods and readily available

software. Density estimates from the video were on average 43 times higher than

concurrent estimates from benthic sled tows, suggesting sleds may be inefficient at

sampling mysids. Deployment caused initial scattering of individuals, resulting in low

densities immediately after deployment that slowly increased. On some occasions, Mysis

densities on video fluctuated greatly over several hours, consistent with organisms that

have a patchy distribution on the lake bottom. The camera system provided novel insights

on behavior and distribution of Mysis on benthic habitats, demonstrating potential for use

as a tool for studying partial diel vertical migration and predator-prey interactions.

Keywords: mysid, macroinvertebrate, benthic density, video camera, benthic sled, DVM

67

Introduction

Accurate estimates of abundances are crucial in ecological studies, but in practice

can be very difficult to obtain. Abundance assessments require knowledge about when

and where the target species occurs within an ecosystem to ensure an adequate sampling

protocol. Consideration of behavior is especially important for species with spatially

and/or temporally variable distributions, e.g., large seasonal fluctuations in biomass (e.g.,

Daphnia spp.; Straile et al. 2012) or those that aggregate in swarms, in particular if

aggregations vary over the diel cycle (e.g., Euphausia spp.; Everson and Bone 1986). The

methods used to collect data are important to consider because different approaches can

provide different results due to gear biases (e.g., Madenjian and Jude 1985; Pepin and

Shears 1997; Masson et al. 2004; Gorbatenko and Dolganova 2007). Comparing

alternative methods is often necessary to evaluate which gear will produce the most

accurate data or when a combination of different sampling techniques is required to

achieve the complete picture (e.g., Stockwell et al. 2010).

In plankton sampling, a range of instruments and methods have been used to

estimate densities, with most relying on physical collections with nets (De Bernardi 1984;

Wiebe and Benfield 2003; Brenke 2005). Plankton sampling equipment varies in size,

shape, overall design, and towing speed/direction, leading to several potential biases

when comparing data derived from different methods (De Bernardi 1984; Wiebe and

Benfield 2003; Wiebe et al. 2015). For example, some plankton nets are more efficient at

capturing mobile taxa than pump samplers (Masson et al. 2004). Additionally, habitat

structure can impose sampling limitations that lead to knowledge gaps regarding

distributions if a habitat type is impossible to sample (creating a black box) or

68

unknowingly alters sampling efficiency (leading to assumptions). Habitats that are not

sampled or are assumed to not affect sampling efficiencies, can hinder our ability to

accurately depict the role of species within landscapes.

In recent years, more sophisticated instrumentation has provided new views on

plankton ecology and created opportunities to revisit assumptions about distributions and

behavior (Davis et al. 1996, 2004; Grosjean et al. 2004; Herman et al. 2004; Yurista et al.

2009). For plankton that undergo diel vertical migration (DVM), the evolution of

underwater technologies has advanced understanding of this behavior (Ohman et al.

2013; Bianchi and Mislan 2016). In strictly pelagic species (i.e., holoplankton) that

exhibit DVM between shallower and deeper parts of the water column, DVM theory has

benefited from instruments that provide high-resolution vertical profiles of organisms

(e.g., laser optical plankton counters, hydroacoustics). Coupling such high-resolution

observations with other profiling instruments (e.g., CTD, fluorometers) has provided

opportunities to test hypotheses about the mechanisms driving DVM behavior (Boscarino

et al. 2009; Cohen and Forward 2009). However, species that migrate between benthic

and pelagic habitats (i.e., meroplankton) also exhibit DVM, and present methodological

challenges for tracking diel behavior because pelagic equipment cannot sample

individuals when they are benthic (Grossnickle and Morgan 1979; Malley and Reynolds

1979; Schmidt et al. 2011). Rather, separate gear types are typically needed to target

individuals in either the pelagic or benthic habitats.

Partial migration is a result of individual variability in migratory behavior, where

not all individuals in a population migrate (Chapman et al. 2011). Partial DVM has been

the term used to describe invertebrates that demonstrate variability in their DVM

69

behavior within a population (Frost and Bollens 1992; Euclide et al. 2017).

Consequently, population estimates of meroplanktonic species that exhibit partial DVM

need to account for both migrant and non-migrant individuals. A benthic sled is often

used in conjunction with pelagic sampling gear to sample these populations. Such

combined estimates, however, are difficult to obtain and interpret (Moen and Langeland

1989; Rudstam et al. 1989) as benthic sled tows are prone to snagging on the bottom if

substrate is uneven or contains obstacles (e.g., cobble, boulders, logs, etc.). This can lead

to damaged equipment, safety issues, and reduced repeatability of benthic sled sampling

relative to pelagic methods that use nets towed vertically through the water column

(Gregg 1976).

Benthic sled sampling can also involve tradeoffs. Setting the mouth opening close

to the sediment surface is typically desirable to catch specimens but runs the risk of

filling the sled with sediment; while setting the mouth too high reduces the probability of

clogging but may pass over specimens closer to or on the bottom. Similarly, benthic sleds

need to be towed at slow speeds to remain in contact with the sediment surface when

towed to prevent lifting off the bottom (Bergersen and Maiolie 1981). Furthermore, sleds

may scatter individuals directly in the tow path because cables used to tow the sled

disturb the area at some distance in front of the sled, leading to questions regarding the

efficiency or reproducibility of active benthic gear relative to passive observational

techniques for slow swimming animals that may be able to avoid the sled.

We describe a portable, deep-water video system, for use near the lake bottom

that is capable of filming epibenthic organisms for up to 24 continuous hours and is

deployable from a reasonably small boat. The system provides opportunities to

70

continuously assess abundances and behavior and study diel differences in partial

migratory populations. We applied our video system to Mysis diluviana (hereafter Mysis)

in Lake Champlain, where only a single mysid species exists and exhibits partial DVM

(Euclide et al. 2017; O’Malley et al. 2018). The efficacy of measuring benthic Mysis with

continuous video was evaluated by comparing density estimates generated from video

data to those from concurrent benthic sled tows day and night, and point sampling with a

smaller portable camera. We demonstrate how this simple camera system can provide

new views of Mysis behavior and distribution at depth, and can be used as a tool in other

applications requiring remotely-placed technology. In comparison to previously

described techniques (Table 3.1), our method represents a passive rather than active

method for estimating density from continuous observation at a fixed site.

71

Table 3.1: Qualitative tradeoffs with various sampling methods used to estimate benthic mysid abundance.

Gear Type Use in lake

studies

Advantages Disadvantages

Benthic sled Most common Able to sweep large areas along transects

and collect specimens

Prone to snagging, limited to smooth

substrates

Benthic grab

sampler (e.g.

Ponar)

Common Able to be deployed by hand, cost effective Ineffective with hard substrates; small

mouth opening and area sampled reduces

detection probability for sparse organisms

Manned

submersible

Rare Can provide detailed observational accounts

of behavior at great depths

Requires light for illumination, large

research vessel, and is typically cost-

prohibitive

ROV Unknown Might provide detailed accounts of behavior Requires umbilical cord; limited depth

Camera equipped

to sled

Rare Allows for simultaneous comparison

between methods

Substantial image processing required; light

from camera could lead to avoidance

SCUBA Not Common Direct observation yields rapid results Limited to shallow depths and would

require light unless during the day at

shallow depths

72

1

Materials and Methods

Description of system

We designed and built a self-contained, battery-powered video system to record

within 1 m of the lake bottom for at least 24 hours without need for a research vessel to

remain on station. Video camera components were required to withstand depths of at

least 400 m and cold temperatures associated with the hypolimnion (~ 4°C). Additionally,

we intended for the entire unit to be heavy enough to remain fixed at depth during

turbulent conditions without lifting off bottom or creating vibrations in the footage. The

entire unit weighed 56 kg in the air.

The camera system (Figure 3.1) consisted of a black and white fixed focus UWC-

300 HD video camera (Outland Technology, Slidell, LA), a DVR-SD (533 MHz;

Seaviewer Cameras, Tampa, FL) to store recordings, a red LED light for illumination,

and two red lasers positioned 10 cm apart for scale. All components were powered by a

battery pack composed of three 14.8-volt, 20.8-amp lithium-ion batteries connected in

parallel, which allowed for at least 24 hours of continuous recording. The battery pack

and DVR were stored in separate custom-machined aluminum housings, while the light,

lasers, and camera came equipped in their own external housings. All parts were mounted

to a frame made of steel tubing (1.2 m × 1.2 m base; Figure 3.1). Lenses of the camera,

light, and lasers were positioned perpendicular to the lake bottom and 0.5 m from the

bottom of the frame. Upon connecting with the battery, the camera, DVR, light, and

lasers turn on and recording begins and runs until the battery is drained or manually

73

disconnected after retrieval. A rope attached atop the frame tethered to a surface buoy

was used to deploy and retrieve the unit.

Figure 3.1: Benthic camera system during deployment. Labeled components are: (A)

housing for battery pack; (B) housing with DVR; (C) red LED light; (D) video camera;

(E) red lasers. Base of frame is 1.2 x 1.2 m. (photo credit: Maureen Walsh).

Spectral intensity and behavior experiment

Mysis prefers cold-dark conditions and low light levels, but is not sensitive to red

wavelengths (Gal et al. 1999; Boscarino et al. 2009). To assess if the red LED light could

74

attract/repel Mysis, we measured the spectral properties of the lights and laser relative to

Mysis vision, and performed a behavioral experiment. Spectral intensity of the red LED

light and lasers was measured using a calibrated spectrophotometer and compared with a

spectral sensitivity curve of M. diluviana eyes from Cayuga Lake, New York (formerly

M. relicta; Gal et al. 1999). Live Mysis were caught at night using a benthic sled towed

along the bottom nearby the camera site, and stored in a 50 x 30 x 40 cm cooler in a dark

5C walk-in refrigerator for two days. For the experiment, the red light from the video

system was positioned over one-half of the cooler at the same height as assembled on the

steel frame. A piece of cardboard was placed vertically above the middle of the cooler to

block the red light from directly reaching half of the cooler. Another piece of cardboard

was placed over the top half of the cooler that did not have the light. Sixty-four Mysis

were allowed 10 minutes to adjust to the new conditions. Every 10 minutes the number of

Mysis on the side of the cooler with the red light was counted by two individuals for an

hour. The two observations for each 10 min were averaged. A total of 3 hours were

observed, at 12:00, 15:00, and 19:00 EST. The number of Mysis on the side without the

light was calculated as the total number of Mysis in the cooler (N = 64) minus the average

number of Mysis on the light side, and compared to an expected equal distribution using

chi-squared analysis.

Field deployments and video analysis

The camera system was deployed once in October 2014 and seven times during

June-November 2015 at a 60-m deep site in Lake Champlain (Figure 3.2; Table 3.2). The

2014 deployment was from a slightly larger steel frame (2.2 × 2.2 m base). The lake

bottom at this location is composed of fine silt with dark color. Benthic invertebrate

75

biomass is relatively low at this depth in Lake Champlain, relative to other deep lakes in

the region (Knight et al. 2018). On each occasion the camera was deployed during the

day and retrieved within 1-3 days, dependent on weather conditions. Upon retrieval,

video files were downloaded and backed-up to a portable hard drive. Two additional

deployments occurred in 2017 as part of a gear comparison (see Field-based

comparison).

Figure 3.2: Map of benthic sled transects, stationary Mysis camera deployments, and

locations of point sampling with the GoPro mounted mini-lander in Lake Champlain.

76

Still images were rendered from videos at 10-min intervals for counting purposes

using Adobe Premier Pro v9.0 or Quicktime Player on a Dell Optiplex PC with Dell HD

monitor. Images were imported to ImageJ64 (Schneider et al. 2012), and each mysid per

image was marked with a dot and then counted. On a subset of images, the horizontal

direction of up to 100 individuals was also recorded using the segment tool in ImageJ64

to examine the relative orientation of Mysis. Video was played back 10 seconds before or

after the desired screenshot time to help distinguish Mysis. Field of view was determined

in ImageJ64 using the known distance of the lasers (10 cm). The area of lake bottom in

the field of view was 0.12 m2 for the frame used in 2015, and 0.35 m2 for the 2014 frame.

Counts per 10-min interval were scaled to areal densities (No. m-2) by dividing the

number counted by viewing area (0.12 m2 or 0.35 m2). After reviewing the video files, a

“landing effect” was apparent during the first 6-8 hours of video recording where

densities were initially low before increasing. Because we always deployed the camera

during the day, we ignored observations from deployment leading up to nautical sunset

per each deployment in our analysis, therefore allowing adequate time for mysids to

redistribute themselves after the landing disturbance. For each deployment in 2015, the

mean densities of Mysis at night (between 1-hr post-sunset to 1-hr pre-sunrise; Table 3.2)

were compared to mean densities the following day (beginning 1-hr post-sunrise) using a

paired t-test. Our 2014 deployment resulted in only one 10-minute interval that occurred

the following day because of early retrieval before 24 hours in the field, therefore we did

not include this date when comparing mean densities because the mean day-density

would only be based on a single observation. All analyses and figures were carried out in

R (R Core Team 2015).

77

We evaluated if our choice of counting interval (10 min) influenced hourly

density estimates by comparing the coefficient of variation generated at different

intervals over an hour. For two separate hours of video (one from June-night and one

from October-night in 2015) we repeated the counting procedure at 1, 5, 10, 20, and 30

minute intervals, resulting in N = 60 and N = 2 observations hr-1 at 1-min and 30-min

intervals, respectively. We plotted the coefficients of variation for each hourly density

estimate to visually assess whether variability was substantially higher or lower at 10-

minute counting intervals relative to other sampling frequencies.

78

Table 3.2: Date, time (EDT/EST), and nautical sunset times of benthic video camera deployments at the same 60-m location in Lake

Champlain 2014-15. Deployment date/time refers to the time of day when the camera touched-down. Nautical sunset indicates the first

time-interval counted, and marks the start of the night time period class.

Year Date/time deployed – retrieved Time from deployment to initial count Nautical sunset (Start count)

2014 20 Oct 13:47 – 21 Oct 09:15 5 h 13 m 20 Oct 19:00

2015 11 Jun 10:02 – 12 Jun 15:19 11 h 28 m 11 Jun 21:30

16 Jul 15:00 – 17 Jul 12:14 6 h 30 m 16 Jul 21:30

04 Aug 13:35 – 05 Aug 11:41 7 h 45 m 04 Aug 21:20

12 Aug 14:30 – 13 Aug 15:25 7 h 0 m 12 Aug 21:30

07 Oct 10:18 – 08 Oct 09:52 9 h 2 m 07 Oct 19:20

20 Oct 14:04 – 21 Oct 22:13 4 h 56 m 20 Oct 19:00

10 Nov 08:15 – 11 Nov 20:22 9 h 15 m 10 Nov 17:30

79

1

Field-based comparisons

Benthic video density estimates were compared to density estimates derived from

concurrent benthic sled samples at the same location (in 2015 only) to assess the relative

efficiency of each gear. For 5 out of 8 camera deployments, we collected mysids during

the day and night with a benthic sled (opening 0.46 m × 0.26 m; 1000-µm mesh, 250-µm

cod-end) towed for 5 minutes along bottom at a vessel speed of approximately 0.8 m s-1.

The bottom of the net opening was 0.15 m from the bottom of the benthic sled skis to

reduce dredging of and subsequent clogging by sediment. Two replicates samples were

collected on each sampling event. Contents were preserved in ethanol and all mysids

were counted per sample. Total counts were converted to areal density estimates (Mysis

m-2) by dividing the number of mysids per sled tow by area swept (distance traveled ×

sled opening width [0.46 m]). These densities were compared to average video-derived

densities from the same 1-hr time window using linear regression and a paired t-test.

Upon reviewing the video and benthic sled data, large discrepancies in density

estimates were apparent between the two. Because benthic sleds are thought to have low

capture efficiency relative to alternative passive methods of observation (e.g, Bergersen

and Maiolie 1981) we designed a lightweight mini-lander to provide point sample

estimates of Mysis density around the stationary Mysis video camera system during

deployment as an additional means of comparison. We considered that Mysis could be

attracted to the camera structure due to potential for reef effects of introducing a structure

into the benthic landscape, therefore we predicted that if the camera system was attracting

Mysis, then we would expect to see higher densities of Mysis adjacent to the camera, and

80

lower densities further from the camera location. The mini-lander frame was constructed

from steel rebar with a smaller footprint (50 x 50 cm) to minimize disturbance and allow

for immediate counts upon landing. A GoPro camera and dive flashlight (Sea Dragon

Mini 600 LED SeaLife Inc., Moorestown, NJ) fitted with a red filter were mounted to the

mini-lander at similar height as the stationary video camera. Field testing was carried out

in July and October 2017, at two times of day during each month (Figure 3.2). First, we

deployed the stationary Mysis camera and a concrete mooring placed upwind of the

camera to control our location during point sampling. On each occasion the camera and

mooring were set 1-2 hours before sunset. Point sampling started at least 12 hours after

initial deployment. A line from the bow of the vessel to the mooring was used to position

the mini-lander close to the stationary camera. For each point sample, the mini-lander

was lowered by hand until the unit reached bottom, and allowed to rest for 20 seconds

before being raised approximately 5 meters off bottom. Once up, more bow line was paid

out to distance the boat before lowering the mini lander again and repeating the process.

Coordinates and time were recorded each time the mini-lander touched down to calculate

distance from the camera lander using the VTrack package in R (Campbell et al. 2012).

In total, the mini lander touched down 63 times at distances of 14-165 m from the

stationary camera. We counted the number of Mysis in view of the camera right as the

mini-lander touched down. An image of a ruler before deployment was used to scale

images and measure the viewing area (range: 0.2 – 0.35 m2) in Image J64. Densities

observed on the mini-lander were compared to those from the stationary camera for the

same 1 hour interval.

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Results

Spectral intensity and behavior experiment

Spectrophotometric measurements of the red LED light and lasers showed

different spectral intensity curves with little if any overlap with sensitivity of Mysis eyes

(Figure 3.3). The laser had very narrow wavelength intensity, with a peak at 648 nm,

while the LED light had a broader curve with a peak at 631 nm. The spectral sensitivity

curve of Mysis eyes, with a peak at 520 nm (Gal et al. 1999), had limited overlap with the

system’s red LED and no overlap with the laser. The Mysis eye sensitivity curve

intersects the red LED light spectral intensity curve at roughly 1/9th peak intensity, which

falls between the 607-608 nm wavelengths (Figure 3.3).

Figure 3.3: Relative spectral intensity of red LED light (dashed line) and lasers (solid

line) used on the camera system. Spectral sensitivity curve of Mysis eye (dotted line)

from Gal et al. (1999) included for comparison.

82

Only 6 of the 18 observations in the behavior experiment exceeded 50% (max.

54%) of Mysis in the red-light side of the cooler (Figure 3.4). On average, slightly fewer

Mysis were found on the bright side of the cooler under the red light than under the dark

side, but overall, the distribution of individuals was not significantly different from an

equal distribution throughout the experiment (χ2 = 14.03, d.f. = 17, P = 0.66).

More counting intervals per hour generally led to lower variability in hourly

estimates of Mysis density observed on camera for two separate hours of video (Figure

3.5). Coefficients of variation (CV) did not drastically change between counting at 5, 10,

or 20-minute intervals, therefore, 10-min counting intervals served as a sufficient

compromise between replication and processing time. One exception to our prediction

was in the October file when we observed a surprisingly low CV at 30 min. intervals,

though this was likely just by chance.

Figure 3.4: Percentage of Mysis observed under the red light half of cooler in the

laboratory experiment. Percentages are the average of two observations every ten minutes

during the first hour (circle), third hour (triangle), and seventh hour (square) of

experiment.

83

Figure 3.5: Coefficient of variation for Mysis benthic density as a function of binned time

intervals for 1-hour video segment from June (circles) and October (triangles) 2015. For

each average, N ranged from 60 for the 1-min interval to 2 for the 30-min interval.

Field deployments and video analysis

Overall, Mysis was observed on video at all times, day and night, though densities

within video files fluctuated considerably over the course of a day (Figure 3.6;

Supplemental Figure 3.11). No noticeable vibrations or lifting events were seen in the

footage. Maximum densities occurred during night for 2 out of 8 sampling events. On

most dates, Mysis densities steadily increased or steadily decreased over periods of

several hours. At times, Mysis densities exceeded 2000 m-2. Overall mean density

observed during the day was not significantly higher than at night (paired t-test: t6 =

1.885, P = 0.109; Figure 3.7).

Individuals were observed to align themselves parallel to one another on occasion,

facing the same direction (Figure 3.8). The alignment appears to be in response to the

direction of benthic water currents as mysids apparently face into a current based on our

84

observations of drifting particles in view. Analysis of video footage from July 17th 2015

showed a shift in the orientation angle of mysids on camera over the course of several

hours as the current apparently shifted direction (Figure 3.8).

Figure 3.6: Mysis density (No. m-2) estimated from benthic video at 10-minute intervals

for seven separate deployments in 2015 (black points) and one deployment in 2014 (blue

triangles) at the same 60-m site in Lake Champlain. Grey boxes represent night defined

as 1-hr post-sunrise to 1-hr pre-sunrise. Times are in EDT except for November which is

EST. Moon phase and weather conditions are shown.

85

Field-based comparisons

Comparisons of density estimates from different gear types revealed a difference

between the video and benthic sled. Mean (± SD) video density (755.0 ± 645.3 m-2) was

significantly greater than concurrent mean density from the benthic sled (17.7 ± 14.9;

paired t-test: t9 = -3.66, P = 0.005). Video and benthic sled estimates were positively

correlated but this relationship was not significant (Figure 3.9; R = 0.574; P = 0.083),

likely due to low sample size which reduced the probability of detecting a significant

relationship (type II error).

Comparison between the stationary video and our mini-lander point sampling

approach provided mixed results. Point sampling at varying distances around the

stationary camera did not support our prediction of higher values nearest the camera site

if attraction to the structure was real. Distance from the stationary camera to the mini-

lander was a poor predictor of the amount of Mysis observed on the mini-lander (Figure

3.10a, P = 0.807, R2 < 0.01). Mean density observed under the stationary camera system

over the same time period as point sampling however, was higher than in our point

sample estimates when distance from the camera was ignored (Figure 3.10b, paired t-test:

t3 = 3.87, P = 0.03). Density from the stationary camera during our testing in 2017 was

far lower for both camera methods compared to density estimates observed under the

stationary camera for several of the deployments in 2015 (Figure 3.6).

86

Figure 3.7: Mean Mysis density (No. m-2) estimated from benthic video during the night

vs day at the same 60-m site in Lake Champlain 2015.

87

Figure 3.8: Synchronous change in orientation of Mysis with direction of bottom current

on July 17th 2015 over a 6-hour period. (Left) Screenshots of Mysis at 06:00 (top), 10:00

(middle), and 12:00 EDT (bottom). (Right) Circular histograms with measurements of the

direction individual mysids were facing in the corresponding image to the left.

88

Figure 3.9: Mysis mean video density (No. m-2) observed as a function of mean benthic

sled density (No. m-2) collected during the same 1-hr time window.

Figure 3.10: (A) Observed Mysis density (No. m-2) by the mini-lander at the time of

landing as a function of distance (m) from the stationary benthic Mysis video camera.

Circles represent July and triangles refer to October 2017 sampling. (B) Comparison of

mean density (± SD) observed on mini-lander (x-axis) to stationary benthic Mysis video

camera (y-axis).

89

Discussion

A non-migrating benthic portion of Mysis that remains on or near the bottom of

deep lakes, and thus unavailable to pelagic gear at night when Mysis populations are

sampled, could present complications for sampling programs and mass-balance food web

models, especially if the non-migrants represent a large proportion of the population

biomass or a disproportionate fraction of particular life-stages (e.g., adult females;

Euclide et al. 2017; O’Malley et al. 2018). Our results confirm the presence of Mysis in

close contact with the sediment surface throughout the night each month from spring to

autumn, confirming that Mysis partial DVM is common in Lake Champlain (Euclide et

al. 2017; O’Malley et al. 2018). Our results also suggest that Mysis densities may be

much higher on benthic habitats than previously estimated using benthic sleds. Although

benthic density estimates from our videos are high, they are within range of areal density

estimates reported elsewhere in the literature for M. diluviana, regardless of habitat or

sampling method. Maximum reported densities of Mysis collected with pelagic gear

range from 1,500-1,950 Mysis m-2 (Reiman and Falter 1981; Ball et al. 2015), but

densities of < 1,000 m-2 are much more common in the literature (Lasenby 1991;

Rudstam 2009; Rudstam and Johannsson 2009). Therefore, densities observed on video

are on the high end of maximum reported densities for the species, especially considering

the camera only sampled mysids near the bottom.

Previous studies that used benthic sled tows compared to pelagic net sampling to

estimate Mysis densities have suggested benthic sleds are less efficient at capturing

mysids (Grossnickle and Morgan, 1979; Shea and Makarewicz et al. 1989). Furthermore,

comparisons of benthic sled tows to other benthic techniques also suggest benthic sleds

90

may underestimate benthic densities. For example, Bergersen and Maiolie (1981) found

that camera-generated density estimates from the front of a benthic sled were 2.4 times

higher than estimates based on mysids captured in the benthic sled tows. We reached a

similar conclusion, that benthic Mysis are inefficiently sampled via benthic sled, albeit we

found a much greater difference – benthic sled densities were on average 43 times lower

than densities from our video sampling. We did not find a strong relationship between

video and benthic sled density estimates, likely due to limited sample size and high

variance. Video also revealed dense aggregations of Mysis at times exceeding 2000 m-2,

whereas, the maximum density reported by benthic sled (50 m-2) was over an order of

magnitude lower. Expeditions from a manned submersible at bottom depths exceeding

250 m in Lake Superior indicated a substantial number of mysids may remain close to the

bottom at night (Bowers 1988). Given the logistical and financial support required to

operate ROVs or manned submersibles, simple and remote methods as the camera system

in this study are may be essential to gather observational data in deep benthic habitats.

Application of remotely-placed video systems in deep-water habitats is more

common in marine than freshwater studies, and the continued development of such

methods in freshwater could yield new insights for benthic or benthopelagic fauna. The

camera resolution combined with red lighting described in our system is not ideal for

species level identification of small organisms such as mysids. However, separation of

different mysid species was not an objective when designing this system because in Lake

Champlain and other deep North American lakes only one deep-water mysid species is

known to occur. Therefore, use of such a camera system should be planned around pre-

91

defined study goals with prior knowledge of deep-water taxa, and possibly their shapes

and swimming behaviors if recording multiple species is of interest.

Previous work on mysid benthic distributions suggest they exhibit patchy

distribution (Mauchline 1971; Bergersen and Maiolie 1981), which is clearly confirmed

by the variation in densities observed in our camera footage, sometimes with periods of

increasing or decreasing density occurring over several hours. Deployment of the camera

resulted in an initial scattering of individuals, which resulted in low densities

immediately after landing that gradually increased over time, but did not always level-off

at the same maximum density after a standard amount of time. The surprisingly high

densities observed at times under our camera led us to evaluate the potential for our

camera system to act as a Mysis attractant. Although artificial lighting can attract some

underwater organisms (Doherty 1987; Stoner et al. 2008; McConnell et al. 2010), we

demonstrated that our choice of red light should not have been an issue for Mysis, an

extremely photophobic species in freshwater lakes. Collectively, the wavelengths of the

light and lasers, biological properties of Mysis vision, cooler experiment, and fluctuations

in densities observed under the stationary camera all suggest the system is not attracting

Mysis. Standard shipboard protocols call for only red light on research vessels when

sampling Mysis at night. If the camera was an attractant for Mysis, we expected to see

abundance values decrease as the mini-lander was used further away from the stationary

camera location, and higher values nearest the stationary camera. Our follow-up work

with the mini-lander around the stationary camera did not show any effect on densities

with distance from the main stationary camera. Density estimates were higher under the

stationary camera but the range of density estimates for these tests was very limited

92

compared to the range observed when routine monthly sampling was performed in 2015.

Although the mini-lander comparison with the stationary camera was inconclusive, a

preponderance of evidence suggests attraction to the camera is not an issue.

In situ observations from our camera system also provided insights into Mysis

behavior on the bottom. Previous observations from manned submersibles in the Great

Lakes reported that benthic Mysis appeared to align themselves parallel to one another

and face the same direction (Robertson et al. 1968; Bowers et al. 1990). We also

observed this behavior from videos, and show that over a course of several hours Mysis

shift direction, possibly in response to changes in the direction of oncoming currents.

Orienting to the current could prevent displacement by strong currents. Remaining tight

to the sediment surface may be advantageous if feeding conditions at the sediment

surface are more profitable than being off-bottom. Regardless of the reason why mysids

align themselves, knowledge of such in situ behavior was only possible through direct

observation, highlighting the potential for video to provide novel insights on the behavior

of deep-water organisms (Bicknell et al. 2016). Our video files also indicated potential to

quantify predator-prey interactions in situ. Occasionally slimy sculpin (Cottus cognatus)

were seen to strike at individual Mysis or burrow into the sediment likely as a sit-and-

wait tactic (Supplemental Figure 3.12). Lab experiments suggest slimy sculpins have a

low capture efficiency towards Mysis prey (Hondorp 2006). Our video system offers an

alternative field-based approach that could be used to quantify predation metrics (strikes,

captures, reaction distance, etc.) that could benefit development of sculpin-Mysis

foraging models.

93

Contrary to classic expectations about DVM behavior that day benthic densities

would be greater than night benthic densities, we were unable to detect a difference

between day and night densities. Such a result could be an artifact of sampling a

relatively small area (0.12 m2), rather than integrating over a broader spatial range which

could contribute to high variance in average estimates. As a tradeoff to our limited spatial

coverage, night and day density estimates were generated from observations at equal

intervals collected throughout the night and day, rather than just a snapshot at midnight

and midday. Thus, the high number of observations per day and night are likely still

sufficient to allow any apparent difference in diel densities to be revealed, which we did

not detect.

Video data are rapidly generated yet automated processing of raw video files into

data points is still in early phases of development (Pimm et al. 2015). Manual counting

from images is a time-intensive process, especially when numerous individuals occur in

the field of view. Our sensitivity analysis suggests counting Mysis at intervals anywhere

from 1 to 30 minutes per hour provides similar density estimates. We chose 10-minute

intervals as a tradeoff between processing time and number of observations. Automated

image recognition software packages and improved image resolution would likely help

speed up the process.

Insights gained from field testing the camera system and analyzing associated

data will hopefully aid researchers to design or improve upon remote video systems for

use in deep lakes. One design element to improve the video camera system is to configure

a timer that turns the camera on/off at programmed intervals rather than continuous

recording. Such capability would allow the battery to last longer to extend deployment

94

times from one day to potentially weeks. Recording at coarse time intervals over a longer

time-period may be advantageous by allowing researchers to capture day-to-day

variability without having to retrieve and recharge the battery. Similarly, wasted battery

life during the initial hours after placing the camera on bottom (i.e., the landing effect)

could be overcome by programmable start times to delay recording during the landing

effect period.

Our experience suggests an opportunity exists for remote video cameras to

provide alternative perspectives of animal behavior and population assessments in

habitats (particularly in deep lake systems) that are not easily sampled by traditional

methods. Remote camera lander systems similar to ours have been used as early as the

1960s in marine systems (Ewing et al. 1967), yet over 50 years since their inception, such

systems are only starting to be adopted for remote use in deep lakes. In large lakes

research, camera technologies are not widely incorporated in monitoring programs

(Twiss and Stryszowska 2016) and a recent study in Lake Baikal using underwater video

documented for the first time that the pelagic amphipod Macrohectopus branickii occurs

on substrate where previously it was only considered to be pelagic (Karnaukhov et al.

2016), similar to our novel findings for Mysis in Lake Champlain. In the Laurentian Great

Lakes where invasive dreissenids now dominate benthic invertebrate biomass, camera

equipped sleds have recently been incorporated to assess dreissenid patchiness and cover

more area than traditional benthic grab surveys (Karateyev et al. 2018). Thus, despite

similar research goals across freshwater and marine systems, the freshwater research

community seems to be lagging in application of video technologies to investigate

behavior and distributions of benthic invertebrates compared to marine research

95

communities, and will undoubtedly benefit from development and application of deep-

water video technology.

Acknowledgements

We thank captain Steve Cluett R/V Melosira for troubleshooting electrical issues

and Mysis sampling, and Ellis Loew for providing spectral intensity measurements of the

light and lasers. Krista Hoffsis, Kevin Melman, Brady Roy, and Pascal Wilkins and

provided helpful assistance with deploying/retrieving the video system. Greg Barske and

Randy Metzger (UW-Milwaukee School of Freshwater Sciences Instrument Shop)

fabricated the video system housings, Dylan Olson and John Janssen (UW-Milwaukee

SFS) helped with assembly and testing, and Tom Manley (Middlebury College) provided

the initial steel frame. Discussions with Lars Rudstam (Cornell University) helped to

spark the initial idea for the camera system. This project was supported by the Great

Lakes Fishery Commission with the assistance of Senator Patrick Leahy’s office, the

University of Vermont’s Office of Undergraduate Research, and the Kate Svitek

Memorial Foundation to RAD.

96

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Supplemental Figure 3.11: Screenshot from deep-water camera system deployed at 60 m

bottom depth in Lake Champlain, Vermont, USA. Date/time stamp on the video follow

eastern time (24:00 hr MM/DD/YY format).

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Supplemental Figure 3.12: Screenshot of slimy sculpin (Cottus cognatus) interacting with

Mysis from deep-water camera system deployed at 60 m bottom depth in Lake

Champlain, Vermont, USA. Date/time stamp on the video follow eastern time (24:00 hr

MM/DD/YY format).

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CHAPTER 4: DIEL FEEDING BEHAVIOR IN A PARTIALLY MIGRANT MYSIS

POPULATION: A BENTHIC-PELAGIC COMPARISON

Brian P. O’Malley1, 2, *, and Jason D. Stockwell1


USA

2 Current address: USGS Great Lakes Science Center, Lake Ontario Biological Station,

Oswego, NY, USA



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Abstract

Populations that exhibit partial migration include migrants and non-migrants. For

benthopelagic organisms that exhibit partial diel vertical migration (PDVM) in aquatic

systems, migrants and non-migrants spend different amounts of time in benthic and

pelagic foraging arenas over a diel cycle. For example, mysids exhibit PDVM and can

feed on both benthic and pelagic resources. Migratory individuals are assumed to

undergo vertical migration at night to access pelagic food when predation risk is lower in

that arena than during the day. However, feeding behavior of non-migrant benthic

individuals is not well understood. One hypothesis to explain individual variability in

DVM behavior is the hunger-satiation state of individuals (hunger-satiation (HS)

hypothesis), which predicts that migration is driven by hunger and non-migration is a

response to satiation. We assessed diel feeding patterns of benthic- and pelagic-caught

Mysis over a 24-hr cycle from a single site in Lake Champlain on multiple occasions to

evaluate if variation in migration behavior was consistent with predictions of the HS

hypothesis. Stomach fullness and diet composition revealed little diel difference in

stomach contents between time of day or between benthic and pelagic individuals at

night. Pelagic individuals were found to consistently have higher stomach fullness shortly

after sunset compared to closer to midnight. Non-migrant benthic individuals at night and

benthic-caught individuals during the day had similar amounts of detritus in their

stomachs. High stomach fullness and high levels of zooplankton prey in benthic-caught

stomachs suggest Mysis actively feed when they are benthic, regardless of time of day.

Our results suggest that variation in migration behavior in Mysis is not likely due to

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hunger-driven behavior, and highlights the dynamic roles of PDVM in habitat and

resource use by Mysis in deep lakes.

Keywords: Mysis diluviana, hunger-satiation hypothesis, diel vertical migration, feeding

rhythm, benthopelagic, stomach fullness index, partial migration

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Introduction

Diel vertical migration (DVM) is a widespread behavior of many aquatic

organisms (Hutchinson 1967; Hays 2003; Mehner 2012). For organisms that exhibit

normal DVM, that is reside in deeper water during the day and migrate upwards at night,

many exhibit diel patterns of increased feeding at night at shallower depths compared to

the day (Haney and Hall 1975; Ringelberg 2010). While temporal change in light

intensity is widely recognized as the proximate cue that triggers DVM (Cohen and

Forward 2009), the vertical distribution of food and internal state of the organism (sensu

Clarke and Mangel 2000) likely also influence depth selection of individuals in lakes and

may help explain any deviation from the normal DVM pattern within a population. For

example, several krill species (e.g., Euphausia lucens, Meganyctiphanes norvegica, and

Thysanoessa raschi) contain higher amounts of food in their stomachs at night, shortly

after they migrate into shallower food-rich waters, followed by midnight sinking behavior

after intense feeding (Pearre 1979; Simmard et al. 1986; Gibbons 1993). Midnight

sinking varies from normal DVM because downward movement of individuals is not in

response to light. The hunger-satiation hypothesis for DVM (HS, Pearre 2003) attempts

to explain midnight sinking in organisms that exhibit DVM. The HS hypothesis predicts

that individuals migrate to food-rich habitat to feed only when hungry and only return to

deeper, food-deplete habitat when satiated. Therefore, individuals ascending to and at

shallow depths are expected to be less full than descending individuals.

Not all organisms that use DVM are dependent on pelagic resources to meet

nutritional demands (Macquart-Moulin et al. 1987; Wurtsbaugh and Neverman 1988).

Contrary to expectations about foraging gains associated with DVM, some organisms

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feed primarily on or near the lake bottom during the day and ascend into the water

column at night for reasons other than foraging (Wurtsbaugh and Neverman 1988; Levy

1990; Mehner 2012; Harrison et al. 2013). For example, larval Bear Lake sculpin (Cottus

extensus) consume mostly benthic invertebrate prey during the day and migrate into the

water column at night, where they do not feed (Wurtsbaugh and Neverman 1988;

Neverman and Wurtsbaugh 1992; 1994). Alternative forms of DVM, where substantial

foraging occurs in the benthic rather than pelagic arena and are unaligned with feeding

opportunity at night, can lead to increased growth by using warmer pelagic habitat to

enhance digestion (Wurtsbaugh and Neverman 1988). Consequently, for some

benthopelagic organisms which readily consume benthic prey, benthic habitat may be

quantitatively more important for prey consumption over the diel cycle. In this context,

benthic-pelagic DVM could be used as strategy to exploit benthic resources efficiently or

increase bioenergetic efficiency (Ohman 1990; Sims et al. 2006; Mehner et al. 2010),

contrary to the more classic model described for planktonic animals to exploit pelagic

resources at night (Ringelberg 2010).

Mysids are a group of omnivorous aquatic invertebrates that undergo extensive

benthic-pelagic DVM. Members of the Mysis relicta species complex are found

throughout northern North America and Europe, and are generally thought to reside on or

near the lake bottom during the day and migrate into the water column closer to the

surface at night (Mauchline 1980; Väinölä et al. 1994; Rudstam and Johansson 2009).

Mysids feed on detritus, phytoplankton, zooplankton, and benthic invertebrates

(Grossnickle 1982; Takahashi 2004), and through DVM, serve as a trophic linkage for

energy flux between benthic and pelagic habitats (Gamble et al. 2011a,b; Isaac et al.

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2012; Sierszen et al. 2014). In North America, the group is represented by a single

freshwater species, M. diluviana (Covich et al. 2009), with one-way migrations of > 100

m reported from deep lakes because of their photophobicity coupled with high water

clarity in lakes where they are typically found (Beeton 1960; Rybock 1978; Gal et al.

1999).

Although pelagic zooplankton is often assumed to be the main food source of

Mysis (e.g., Hrycik et al. 2015; Caldwell et al. 2016), bioenergetic and stable isotope

mixing models both suggest that consumption of zooplankton alone does not fulfill their

energetic requirements, and as a result, mysids likely use other resources to meet daily

demand (Johannsson et al. 1994; Johannsson et al. 2001, 2003; Sierszen et al. 2011). The

relative contribution of detrital resources to Mysis’ diet is not well known and represents

a key knowledge gap to better understand the role of Mysis in nutrient sources and

recycling in food webs. For example, in oligotrophic Char Lake, where mysids reportedly

fed on shallow, moss-like substrate, mostly inorganic material was observed in stomach

contents, in contrast to the more typical zooplankton-based diet (Lasenby and Langford

1973). Compared to the typical zooplankton-based diet reported in the literature,

observations from Char Lake highlight the dynamic feeding and habitat use demonstrated

by mysids (see also Morgan and Threkheld 1982; Devlin et al. 2016). Furthermore, not

all mysids partake in DVM, termed partial DVM (PDVM), where some individuals

within the population vertically migrate while others remain benthic at night (Bowers

1988; Moen and Langeland 1989; Euclide et al. 2017; O’Malley et al. 2018). Populations

that exhibit PDVM comprise a portion of individuals which have disproportional

foraging access to benthic and pelagic arenas at night (Ahrens et al. 2012). Migratory

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Mysis have greater access to zooplankton prey than non-migrants, and in particular

cladocerans, for which Mysis demonstrate strong selectivity (Grossnickle 1978; Bowers

and Vanderploeg 1982; Vanderploeg et al. 1982; O’Malley and Bunnell 2014).

Conversely, non-migratory benthic Mysis have greater access to sedimented detritus,

harpacticoid copepods, and benthic invertebrates. The diets of pelagic-caught Mysis have

been studied on many occasions (e.g., Grossnickle 1979, 1982; Langeland 1988; Chess

and Stanford 1998; Whall and Lasenby 2009; Caldwell et al. 2016; O’Malley et al. 2017),

but diets of benthic-caught specimens remain a knowledge gap to understand the link

between resource use and variability in migration behavior in mysids. Whether mysids

that remain benthic at night feed continuously throughout the day and night is largely

unknown but seems plausible because of their relatively small gut volume, broad diet

range, and appreciable gut evacuation rate at low temperatures experienced near the lake

bottom (Chipps 1998). Given that mysids can consume benthic material and some

individuals do remain benthic, the contribution of benthic resources to Mysis diet, and

thus support to higher trophic levels and benthic nutrient recycling, could be

underestimated when research is limited to just the pelagic component of populations.

We tested the HS hypothesis to explain PDVM in a M. diluviana population.

Under scenarios of PDVM and consistent with predictions of the HS hypothesis,

individuals that migrate were expected to be hungry (i.e., empty or low stomach fullness),

whereas non-migratory individuals collected on the bottom were expected to be satiated

(i.e., relatively higher amounts of food in their stomach compared to migrants). Because

Mysis are omnivorous, we predicted no difference in stomach fullness of benthic-caught

Mysis across the diel cycle because of continuous access to food supply (i.e., detritus).

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Similarly, for non-migrants captured near bottom at night we predicted diets would be

mostly full and similar in composition to those collected during the day, to reflect the

benthic environment, but different than diets of migratory individuals collected in the

pelagia at night.

Methods

Sample collections

Mysid feeding patterns were assessed at a 100-m deep site in the main basin of

Lake Champlain (44° 28’ N; 73° 18’ W) on four separate occasions: once in 2016 (14-15

June), and three times in 2017 (13-14 April; 18-19 July; 19-20 October). Each occasion

consisted of 5-6 sample collection intervals over a 24-hr period (Figure 4.1;

Supplemental Table 4.3). Pelagic mysid samples were only collected at night; benthic

mysids were collected all times sampled. Sample collections followed protocols

described in O’Malley et al. (2018). Briefly, benthic mysids were collected with a benthic

sled (mesh: 1000 µm) towed for 5 minutes along the bottom. Pelagic mysids were

collected with a 1-m2 plankton net of similar mesh size towed vertically from 5 m above

the bottom to surface. Pelagic mysids were rare in April catches and were not analyzed.

Sample events in June, July, and October contained two separate times the benthic and

pelagic regions were compared at night (post-sunset, and midnight). After each sample

collection, contents were rinsed into a jar, narcotized with alka-seltzer, and preserved in

ethanol for diet analysis.

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Figure 4.1: Local time of pelagic (P, red triangles) and benthic (B, black circles) sample

collections during four separate trips on Lake Champlain. Sample times represent the

midpoint of the time interval in which the sample was collected. Grey box is sunset to

sunrise (see Supplemental Table 4.3 for exact time values).

Vertical profiles and pelagic zooplankton biomass were measured to characterize

pelagic habitat and prey availability across months. Temperature and chlorophyll-a

fluorescence profiles were measured with a SeaBird SBE19 CTD equipped with a

WetLabs fluorometer during the day. Crustacean zooplankton biomass and species

composition were quantified to assess the prey base available to pelagic mysids.

Zooplankton net tows were collected with a 0.5-m diameter 150-µm mesh net towed

vertically from 60 m to surface because most pelagic M. diluviana occupy depths < 60 m

after vertical migration (Boscarino et al. 2009). Zooplankton tows were collected during

sunset, once per month, prior to the start of night Mysis sampling, except in April when

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zooplankton were not sampled. Upon collection, zooplankton were rinsed into a jar,

narcotized, and preserved in ethanol.

Sample analysis

Zooplankton samples were processed under an Olympus SZX12 dissecting scope

equipped with a drawing attachment and digitizing tablet for length measurements. At

least 150 individuals per sample were counted, measured, and identified in a counting

wheel from a known volume of subsample. Adult copepods and cladocerans were

identified to species or genus, while immature copepods were classified as cyclopoid or

calanoid copepodids, except for immature Epischura. Copepods were measured from the

anterior edge of the cephalosome to the distal end of the caudal rami; cladocerans were

measured from the top of the head to the base of the caudal spine or carapace. Nauplii

were not included in counts because the mesh size we used results in underestimates

(Evans and Sell 1985). Individual lengths were converted to dry mass using published

length:mass equations (Bottrell et al. 1976; Burgess et al. 2015; Supplemental Table 4.4).

Zooplankton dry biomass density (mg/m3) was calculated from volume filtered assuming

net filtration efficiency of 1.

Mysis stomach fullness was scored on a semi-quantitative scale derived from

methods used in euphausid diet studies (Nakagawa et al. 2003; Ponomareva 1971;

Simmard et al. 1986) because of the many similarities in biology and feeding between

mysids and euphasids (Mauchline 1980; Rudstam and Johannsson 2009). Direct

examination of the stomach contents prior to tearing open the stomach was possible

because Mysis stomach tissue is thin and transparent (Figure 4.2a-b). Individual mysids

were photographed under an Olympus SZX9 dissecting scope with a digital camera for

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body length measurements in ImageJ. Because Mysis diet varies with body size, only

adult size-classes (≥ 10 mm) were targeted (Branstrator et al. 2000; Johannsson et al.

2003). Sizes were similar across samples overall except for some night-pelagic samples

when slightly smaller individuals were used for analyses because large animals were rare

in catches. Image analysis occurred prior to stomach dissection to avoid bias from

disturbance. Stomach fullness was scored by the same individual with the following

criteria: 0 = empty; 1 = trace food up to one quarter full; 2 = more than one quarter to half

full; 3 = more than half up to three quarter full; 4 = more than three quarter full to gorged

(Figure 4.2c-g). A stomach fullness index (SFI) was calculated according to Nakagawa et

al. (2003) as the mean score among individuals per sample, where the mid-point gut

percentage fullness value of each fullness class (i.e. class 0 = 0; class 1 = 12.5; class 2 =

37.5; class 3 = 62.5; class 4 = 87.5) was used:

SFI = ∑(𝐹𝑝𝑖 ⋅𝐹𝑚𝑖

100)

4

𝑖=0

where Fpi is the percentage of total Mysis examined with fullness class i (%) and Fmi is

the median of each fullness class i.

After scoring a stomach for fullness, stomach contents from a subset of those

adults (up to 10 per sample) were analyzed for diet composition and prey counts.

Stomach contents were removed from an individual stomach, placed in a drop of reverse

osmosis water, and spread on a Sedgewick Rafter cell for identification and enumeration

of ingested prey under an Olympus IX inverted microscope. Ingested rotifer lorica were

mostly intact and were identified to genus level, whereas intact crustacean zooplankton

prey were rare in diets. Therefore, we relied on diagnostic prey remains to quantify

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crustaceans that were fragmented (e.g., mandibles, tail spines, rostra, postabdominal

claws, and caudal rami). Multiple body parts for a single prey taxon were often available

in a gut. For those instances, we relied on structures that yielded the highest number of

prey in the diet after dividing by two for parts that occur naturally in pairs (e.g.

mandibles). Zooplankton remains were identified according to O’Malley and Bunnell

(2014) and unpublished images of dissected zooplankton. Because detritus is not possible

to quantify in stomach contents by counting, we instead relied on a qualitative scoring

method. Relative abundance of detritus in a diet was ranked from 0 to 4 similar to

protocol of Johannsson et al. (2001), with a value of 0 for no detectable amount, 1

representing trace detritus, and 4 indicating a very high amount. All mysid stomachs were

analyzed by the same person. Archived mysids that were experimentally fed sediment in

the laboratory were used as a training set to differentiate between detritus and plankton

remains in stomach contents. Other non-zooplankton prey items that were easily

recognizable in stomach contents (e.g., pollen, ostracods, and dinoflagellate cysts) and

have been reported from mysid diet studies elsewhere were also counted (Viherluoto et

al. 2000; Johannsson et al. 2003; Caldwell et al. 2016).

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Figure 4.2: (A) Mysis cephalic region after separation from the body with thoracic

carapace removed. (B) Close-up view of Mysis cardiac stomach (circled region) (C-G)

Gut scale ranking system for classifying gut fullness of Mysis stomach contents: (C) 0 =

empty; (D) 1 = trace food up to one-quarter full; (E) 2 = half full; (F) 3 = three-quarters

full; (G) 4 = fully gorged.

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Our stomach fullness scale only accounted for the approximate volume and not

the composition. To evaluate if our assigned fullness score equated to more zooplankton

prey ingested, we first tested for a correlation between the number of zooplankton in a

stomach as a function of fullness score. For stomachs that were classified as full (fullness

rank 4), we expected that those stomachs would either contain a high amount of

zooplankton or a high amount of detritus (detritus rank 4), but not both. Stomach fullness

was assigned visually prior to dissecting the stomach and assigning a detritus score or

counting the number of prey. To test for the possibility that a stomach could be full and

have a high amount of detritus or zooplankton independent of each other, we tested for an

inverse relationship between the amount of zooplankton and detritus for only those diets

that were classified as full. For each model, we also evaluated with and without including

habitat as a parameter and used ΔAIC to compare models and assess if habitat improved

the model.

Gut fullness and detritus rank scores were compared using a Kruskal-Wallis rank

sum test for each sample month to test for variation in scores across time of day. Diel

change in SFI was evaluated by visual inspection for increasing or decreasing trends in

SFI values. Diet similarity by abundance of zooplankton and other non-detrital prey items

counted in diets (i.e., daphnid ephippia, dinoflagellate cysts, ostracods, and pollen) was

evaluated using ANOSIM between pelagic and benthic night-samples to test whether diet

composition varied between migrant and non-migrants. ANOSIM produces a global R-

statistic, which is calculated from the ratio of between-group and within-group

dissimilarities, that ranges from 0 (low similarity) to 1 (high similarity; Clarke and

Warwick 1994). Calculations were carried out in the R package vegan using the anosim

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function with a Bray dissimilarity matrix and 999 permutations excluding diets recorded

as empty (Okansen et al. 2018).

To evaluate if reduced access to zooplankton prey in benthic-caught individuals

would result in lower average number of prey in stomach contents compared to diets of

pelagic-caught individuals at night, we used one-way ANOVA with a Bonferroni

correction for multiple comparisons to compare the number of prey observed in gut

contents for select prey categories (cyclopoids, calanoids, cladocerans, and rotifers) in

each month. We assumed zooplankton availability was lower in benthic habitat, and

higher in pelagic habitat. We kept each month separate for analysis because zooplankton

abundance and species composition fluctuate seasonally (Sommer et al. 1986) and thus

conditions were expected to vary enough to warrant separate analyses. Frequency of

occurrence for prey items in diets by day and night benthic samples, and night-pelagic

samples was calculated and graphed by prey type to identify if prey defined as benthic or

pelagic origin occurred at relatively higher frequency in diets consistent with

expectations of the habitat from which the diet was sampled. The percent occurrence of

high detritus in stomachs (detritus rank 4) was included to assess if high detritus was

more common in benthic individuals.

Results

The water column was thermally stratified during three of four sampling months

(Figure 4.3). Temperature and chlorophyll concentrations were uniformly distributed

throughout the water column in April. The strongest temperature gradient observed was

in July and the deepest thermocline depth occurred in October. Chlorophyll profiles

118

showed sub-surface chlorophyll maxima at temperatures of 11-14 °C June-October

(Figure 4.3).

Crustacean zooplankton composition varied from mostly cyclopoid biomass

(80%) in June, to a greater representation of cladocerans (daphnids and bosminids) in

July (46%; Figure 4.4). Calanoids accounted for a greater amount of the community in

October (49%) relative to June (19%) or July (18%). Total zooplankton biomass density

was highest in the month of July (60.8 mg/m3), and lower and more similar in June (9.0

mg/m3) and October (19.0 mg/m3).

Figure 4.3: Vertical profiles of temperature and chlorophyll-a fluorescence at the 100-m

sampling site in Lake Champlain in June 2016, and April, July, and October 2017.

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Figure 4.4: Crustacean zooplankton biomass (mg/m3) and % composition in 60 m to

surface vertical net tows at the 100-m site in Lake Champlain in June 2016 and July-

October 2017.

A total of 754 mysids stomachs were visually examined for fullness. Of those, the

diets of 231 mysids were dissected and examined microscopically. The most frequently

encountered stomach fullness category was the maximum value 4 (N = 459 diets),

followed by 3 (N = 200), 2 (N = 50), and 1 (N = 26). Nineteen stomachs were visually

classified as empty (7 day-benthic, 7 night-benthic, and 5 night-pelagic). Eight of the

stomachs classified as empty were also dissected and contained zero prey except for one

of the diets which yielded one prey part only visible after dissection.

Stomach fullness rankings were positively correlated with the number of

zooplankton in Mysis stomach contents, though only a small amount of the variation was

explained by linear regression (Figure 4.5, N = 231; P < 0.01; R2 = 0.12). The inclusion

of habitat to the model explained more variation (P < 0.01; R2 = 0.19) and resulted in a

more parsimonious model than stomach fullness rank alone (ΔAIC = 19.3). In stomachs

classified as mostly full (rank 4) and those that were also examined for diet composition

(N = 122), we observed a weak inverse relationship between detritus score and the

number of zooplankton in a stomach, as expected. Detritus scores and habitat as

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predictors of the number of zooplankton stomach contents led to a better model compared

to just detritus scores (P < 0.01; R2 = 0.12; ΔAIC = 7.5). The detritus scores alone

explained almost none of the variability (P < 0.01; adj. R2 = 0.05).

Figure 4.5: Correlation between number of total zooplankton prey (copepods,

cladocerans, and rotifers) in Mysis gut contents (ZP) and gut fullness rank score from

Lake Champlain in June 2016 and July-October 2017.

Stomach fullness scores showed little variation with time of day. Benthic SFI

values ranged from 57.5 to 82.5 and did not show clear trends with time of day (mean =

72.3 ± 5.6 SD, Figure 4.6; Supplemental Figure 4.10). Pelagic SFI values varied more

within a night than did benthic samples, and always showed the same pattern where

higher values were first observed shortly after sunset and lower values occurred in

samples close to midnight (Figure 4.6). Empty diets were more frequent in night-pelagic

than day-benthic diets collected close to midnight in all three months (Supplemental

121

Figure 4.10). The distribution of stomach fullness scores was not significantly different

with time of collection in April (Kruskal Wallis, H = 1.43, d.f. = 4, P = 0.84), June (H =

10.92, d.f. = 7, P = 0.14), and October (H = 6.73, d.f. = 7, P = 0.46). A significant

difference in gut fullness scores over the diel cycle was only detected in July samples (H

= 21.06, d.f. = 7, P < 0.01). Post-hoc comparison indicated the July post-sunset and

afternoon benthic sled samples were significantly different from each other (Dunn test, Z

= 0.24, P-value < 0.01) but were not significantly different from the other July samples.

Figure 4.6: Temporal changes in stomach fullness index (SFI) of benthic- (black circles)

and pelagic-caught (red triangles) mysids by month from Lake Champlain. Grey box is

sunset to sunrise.

Detritus scores were mostly consistent across the diel cycle for benthic-caught

mysids, though significant pairwise differences were detected across the diel cycle in

each of the three months (Figures 4.7 and 4.8). In June and July, low detritus scores were

more common in night-pelagic diets than in October. In June (Kruskal Wallis, H = 21.91,

122

d.f. = 7, P < 0.01), detritus scores in diets of individuals collected in night-pelagic

samples were only significantly lower than benthic diets collected in the late-morning the

following day (Dunn test, Z = -3.14, Bonferroni adj. P < 0.05), but were not different

among pairwise comparisons of benthic diets from pre-sunset through dawn (adj. P >

0.05). A similar pattern was observed in July (Kruskal Wallis, H = 33.26, d.f. = 7, P <

0.01), with significantly lower detritus scores in night-pelagic diets shortly after sunset,

compared to benthic diets collected late-morning (Z = -3.67, adj. P < 0.01) and afternoon

(Z = -4.61, adj. P < 0.01) the following day. July night-pelagic diets near midnight were

not significantly different from other observations in that month. In October (Kruskal

Wallis, H = 14.94, d.f. = 7, P < 0.05), detritus scores appeared higher overall relative to

other months. Detritus scores of October night-pelagic stomachs collected close to

midnight were lower compared to those from benthic-day individuals at pre-sunset (Z = -

3.34, adj. P < 0.05) and mid-morning (Z = -3.16, adj. P < 0.05).

Diet composition by number of prey items observed in night-collected stomachs

revealed no significant differences between benthic- and pelagic-caught mysids in June

(ANOSIM, N = 37, R = 0.035, P = 0.13) and July (N = 32, R = 0.047, P = 0.18). October

diets were different between night-benthic and night-pelagic mysids, but were still similar

overall as indicated by a low R statistic (N = 38, R = 0.115, P < 0.01).

123

Figure 4.7: Variation in detritus scores of pelagic and benthic Mysis by time of day in

June 2016 and July and October 2017 in Lake Champlain.

Figure 4.8: Mean (± SE) detritus rank of stomach contents from benthic- and pelagic-

caught Mysis by time of day. Points labelled with the same letter denote no significant

difference among time of day (Dunn test with Bonferroni correction). Letters are located

above for benthic and below for pelagic samples. * indicates excluded estimate due to

small sample size.

124

Comparison of the number of zooplankton prey in stomach contents over the diel

cycle indicated significant differences in 3 of 12 cases (Table 4.1). Significant differences

in the number of cyclopoids in diets were observed in July and October, and in the

number of calanoids in diets in October (Table 4.2). No significant differences in the

number of cladocerans or rotifers in diets through time were detected out of the three

months. In July, more cyclopoids were present in day-benthic diets around mid-morning

after night sampling, a trend that was not evident when other prey types were considered.

In October, the number of calanoids in stomach contents was significantly higher in

night-pelagic diets closer to midnight than during the day for benthic-caught individuals,

and the same was true for cyclopoids. The number of calanoids in night-pelagic diets

closer to midnight was not significantly different from the amount observed in night-

pelagic diets collected a few hours earlier just after sunset, but was greater than in both

night-benthic diet sample collections. In contrast, the number of cyclopoids in night-

pelagic stomachs collected closer to midnight was significantly greater than just after

sunset for both benthic and pelagic samples.

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Table 4.1: One-way ANOVA results of the number of prey for each category in Mysis

stomach contents over a diel cycle in Lake Champlain. F values that were significant

following a Bonferroni correction (α = 0.05/12) for multiple comparisons are denoted by

asterisks.

Date Sampled Prey Category d.f. F P

14/15 June Calanoid 7 1.45 0.20

Cyclopoid 7 1.16 0.34

Cladocera 7 2.61 0.02

Rotifer 7 2.71 0.02

18/19 July Calanoid 7 1.29 0.27

Cyclopoid 7 3.49 < 0.01*


Rotifer 7 0.70 0.67

19/20 October Calanoid 7 4.27 < 0.01*

Cyclopoid 7 4.35 < 0.01*


Rotifer 7 0.87 0.54

126

Table 4.2: Mean size of Mysis and number of prey items, and the minimum and maximum number observed, in Mysis stomach contents collected

at different times of day and habitat (benthic/pelagic). Grey denotes samples collected at night (between sunset-sunrise). Bold values denote

months when significant differences in mean number of prey over a diel period were detected after Bonferroni correction. Superscripts refer to

Tukey’s HSD post-hoc comparison for those cases.

Mysid length (mm) Prey Category

Date Sampled Time (hr) Gear Mean SD N Calanoid Cladocera Cyclopoid Rotifer Other

14/15 June 14:00 Benthic 14.7 1.1 10 2.7 (0-14) 3.2 (2 - 6) 5.4 (1-19) 0.6 (0-3) 7.1 (0-15)

18:00 Benthic 14.2 1.2 10 0.2 (0 - 2) 1.3 (0 - 3) 4.0 (0-10) 0.4 (0-2) 3.4 (0 - 6)

22:00 Benthic 16.6 2.4 10 0.8 (0 - 2) 1.9 (1 - 3) 6.4 (1-17) 0.5 (0-2) 7.7 (0-24)

22:00 Pelagic 14.8 1.3 10 1.8 (0 - 4) 5.3 (0-13) 8.1 (1-16) 2.2 (0-4) 10.8 (2-23)

00:00 Benthic 14.6 0.9 10 1.0 (0 - 3) 2.5 (0 - 6) 5.5 (2 - 8) 2.2 (0-8) 9.0 (1-23)

00:00 Pelagic 11.6 2.2 7 2.9 (0-14) 4.7 (0-12) 3.0 (0-11) 0.9 (0-4) 5.1 (0-16)

06:00 Benthic 14.9 1.5 10 0.9 (0 - 3) 3.3 (1 - 7) 5.4 (2-15) 0.9 (0-2) 1.3 (0-26)

10:00 Benthic 15.8 1.5 10 1.7 (0 - 4) 3.5 (0-10) 4.9 (0 - 7) 0.7 (0-2) 1.1 (0-21)

18/19 July 19:00 Benthic 14.8 1.0 10 1.9 (0 - 5) 12.1 (2-23) 2.4b (1 - 6) 0.3 (0-2) 2.0 (0 - 5)

22:00 Benthic 14.7 1.1 10 1.9 (0 - 6) 11.6 (2-23) 3.0b (0 - 5) 0.8 (0-3) 1.2 (0 - 5)

22:00 Pelagic 11.3 0.5 7 1.0 (0 - 2) 14.1 (8-20) 2.3b (1 - 4) 0.3 (0-1) 0.0 (0 - 0)

00:00 Benthic 14.5 2.2 10 0.8 (0 - 2) 10.5 (0-18) 2.3b (0 - 5) 0.2 (0-1) 1.7 (0 - 4)

127

00:00 Pelagic 16.4 2.3 7 1.4 (0 - 3) 12.0 (0-22) 2.0b (0 - 5) 0.7 (0-3) 0.0 (0 - 0)

07:00 Benthic 14.7 1.2 10 0.8 (0 - 1) 8.8 (0-18) 3.4ab (0 - 7) 0.5 (0-2) 1.3 (0 - 6)

10:00 Benthic 14.5 2.6 10 1.3 (0 - 4) 10.7 (1-18) 6.5a (2-18) 0.6 (0-2) 3.0 (0 - 7)

13:00 Benthic 16.0 1.2 10 1.3 (0 - 3) 15.0 (3-46) 4.0ab (2 - 7) 0.3 (0-2) 1.4 (0 - 3)

19/20 October 17:00 Benthic 14.8 1.4 10 2.0b (0-10) 11.6 (4-26) 4.1b (0-23) 0.5 (0-2) 4.9 (1 - 13)

19:00 Pelagic 16.5 0.9 10 3.3ab (0-16) 13.7 (1-47) 4.5b (0-11) 0.9 (0-4) 3.8 (0 - 12)

20:00 Benthic 15.5 1.8 10 1.6b (0 - 8) 10.1 (4-24) 4.0b (0-16) 1.2 (0-2) 4.8 (0 - 13)

22:00 Benthic 16.6 1.4 10 1.4b (0 - 5) 14.0 (1-44) 6.1ab (1-19) 1.0 (0-4) 8.7 (1-15)

22:00 Pelagic 16.2 1.3 10 8.1a (0-26) 22.2 (0-73) 15.6a (0-41) 0.7 (0-2) 3.5 (0 - 14)

07:00 Benthic 14.9 1.2 10 0.6b (0 - 2) 7.8 (4-14) 1.7b (0 - 3) 0.5 (0-3) 5.6 (1 - 11)

10:00 Benthic 15.5 1.0 10 0.7b (0 - 3) 8.1 (1-13) 2.1b (1 - 4) 0.8 (0-3) 4.1 (0 - 8)

14:00 Benthic 17.0 2.2 10 0.4b (0 - 2) 11.3 (2-44) 2.3b (1 - 9) 0.3 (0-1) 4.7 (0 - 11)

128

1

The occurrence of pelagic prey in stomachs examined did not vary considerably

with habitat or with day/night collections as predicted. Bosminids, daphnids, and

cyclopoids were the most frequently observed zooplankton prey taxa across all months

and were consistent between benthic and pelagic diets within a month (Figure 4.9). Prey

that were frequently observed in night-pelagic diets were also common in benthic diets.

In June and July, prey items designated as benthic prey were observed in benthic-caught

diets both day and night but not in pelagic-caught diets. High detritus (rank 4 exclusively)

occurred in approximately 50% of benthic day-night diets in June and July, and far less

common in night-pelagic diets those months. By October, the pattern was mixed with

high detritus found in 50% of night pelagic, and 60-80% of benthic individuals examined.

Ostracods were present in 2.5% of benthic-day and 10% of benthic-night individuals

examined in June and July. Harpacticoids were the only other benthic prey type observed

in July of benthic-caught diets but were infrequent. In October, resting stages of prey in

the forms of dinoflagellate cysts and daphnid ephippia were frequent in benthic and

pelagic-caught diets. Daphnid ephippia were more common in benthic-day (60%) and

benthic-night diets (65%), than in pelagic-night diets (40%). Occurrence of dinoflagellate

cysts in October diets were not drastically different across benthic and pelagic samples

(60-70%).

129

Figure 4.9: Frequency of occurrence of prey items by habitat-time sampled (BD =

benthic-day; BN = benthic-night; PN = pelagic-night). Prey items with values of 0% are

not shown as symbols. Pelagic prey items are ordered by decreasing body size (green

font), from Keratella to Senecella; last four prey items of list (Dinoflagellate.cyst-

Detritus.4.only) are strictly benthic prey (brown font).

Discussion

We evaluated predictions of the HS hypothesis to explain variability in PDVM

behavior in a Mysis population. We predicted that if migration was driven by hunger,

then mysids with less full stomachs should make up the migrant, pelagic portion of the

population at the start of the night, while satiated, non-migrant benthic individuals would

make up the benthic portion throughout the night. A second prediction was that we would

see declining stomach fullness from morning to evening. Our stomach fullness results

indicated that over a diel cycle, Mysis stomachs were rarely empty, regardless of habitat

or time of day from which they were collected. More than half of all stomachs examined

130

were classified as full, suggesting that mysids likely exhibit continuous and opportunistic

feeding without a clear diel shift in terms of stomach fullness.

Multiple hypotheses have been proposed that could explain PDVM of Mysis. The

hypotheses include differences in demographics, body size, body condition, genetics, and

different feeding behavior among migrants and non-migrants (Ogonowski et al. 2013;

Euclide et al. 2017; O’Malley et al. 2018). Though not mutually exclusive from each

other, the potential hypotheses that have been proposed and evaluated in some instances

are by no means a comprehensive list. Given the current state of knowledge in the field of

partial migration, and especially in invertebrates that have been understudied (Chapman

et al. 2011), much work still remains to rule out certain hypotheses. In the current study,

we rejected the HS hypothesis to explain PDVM in Lake Champlain Mysis. Previous

studies have found support for body size and condition related hypotheses (Euclide et al.

2017; O’Malley et al. 2018) within the Lake Champlain population. A comprehensive

assessment that evaluates the degree of support among multiple competing hypotheses

for Mysis PDVM is needed as a next-step towards explaining PDVM which will

undoubtedly benefit the field of partial migration (Chapman et al. 2011; Betini et al.

2017).

Diet descriptions of benthic-caught Mysis are not as common in the literature as

pelagic-caught specimens. A brief literature search of 21 M. diluviana/relicta diet studies

found only 30% of them examined benthic-caught individuals (JDS, unpublished data).

More time within a day is likely spent on or near the bottom during summer months in

the northern hemisphere, when primary and secondary production are typically greatest,

because of short nights. Inferred diet from stable isotope mixing models of night-pelagic

131

Mysis from Lake Superior suggested that benthic and pelagic contributions to diet were

similar, despite the shorter amount of time available for Mysis to forage in the pelagic

zone at night compared to the day during the summer (Sierszen et al. 2011). Such

disproportionate nutritional contributions relative to the time presumably spent in each

habitat could reflect tradeoffs between food quantity and quality in energy assimilation.

Sedimented detritus is widely available to benthic Mysis during the day and night, but of

low energy value compared to pelagic zooplankton (Cummins and Wuycheck 1971), and

consequently may serve as a subsistence food resource for individuals that remain near

the lake bottom. Abstinence from consuming benthic food while ingested material from a

previous night pelagic foray is slowly digested is a possibility. However, mysids have

several biological constraints including the small volume of their cardiac stomach.

Further, gut evacuation rate of 4.6 hours has been reported for M. diluviana at cold

hypolimnetic temperatures (4°C) with faster rates at higher temperatures (Chipps 1998).

Thus, we would have expected a high frequency of empty guts for benthic-caught Mysis

late in the day prior to sunset if pelagic feeding was solely responsible for maintaining

food in the stomach. Our results clearly demonstrate Mysis fed continuously over the diel

period and use both benthic and pelagic foraging arenas.

The SFI provided semi-quantitative data on feeding history. We found a positive,

albeit somewhat weak, relationship between the fullness index and the amount of

zooplankton in Mysis stomach contents. High variation in the number of zooplankton per

individual was not surprising in stomachs classified as full because animals were

gathered from multiple habitats and times of day. Adding habitat as a variable improved

the amount variability explained, but only slightly. We anticipated that individuals with

132

full guts and low numbers of zooplankton would have high relative scores of detritus to

compensate for low amounts of zooplankton. However, we only observed a weak inverse

relationship between the amount of detritus and the number of zooplankton in stomach

contents. We did not record the relative amount of phytoplankton in stomach contents.

Mysis transition from primarily herbivorous as juveniles to more carnivorous as adults

(Branstrator et al. 2000), and phytoplankton is not considered a major diet component of

adult-sized mysids except possibly in spring (Johannsson et al. 2001, 2003; O’Malley et

al. 2017). Our diet data on large-sized Mysis, along with previous observations that large

mysids account for the majority of the non-migrant portion (Euclide et al. 2017;

O’Malley et al. 2018), suggest that benthic detrivory might also be an important

ontogenetic diet shift to consider. Accounting for phytoplankton and detritus through

qualitative (Johannsson et al. 2001) or quantitative (Grossnickle 1979; O’Malley et al.

2017) metrics could provide a more complete picture in future studies that seek to

combine gut fullness and diet composition measurements from the same individual to

assess feeding. Our results support the need to include benthic Mysis in future studies to

better understand drivers and impacts of PDVM on trophodynamics of deep lakes.

Contrary to the expectation that zooplankton prey would be more abundant in

diets of night-pelagic or dawn-benthic individuals than those from just before sunset, we

only detected diel differences in the amount of zooplankton in Mysis stomachs in a few

instances. In October, results were in-line with predictions about pelagic foraging;

numerically more calanoids and cyclopoids were observed in stomach contents of night-

pelagic caught individuals close to midnight than other times of day. We did not find a

similar result for cladocerans or rotifers. We were unable to detect any diel difference,

133

although zooplankton, and in particular cladocerans and rotifers typically occur at higher

densities in epi/meta-limnetic waters at night than near the lake bottom (Chess and

Stanford 1998; Nowicki et al. 2017; Watkins et al. 2017), and would be more available to

pelagic mysids at night. One caveat with our study and the use of diagnostic prey remains

to quantity zooplankton prey from Mysis stomach contents is that variability in digestion

times for zooplankton hard structures could bias our snapshots of diet composition

through time if some parts degrade more rapidly than others or accumulate in the stomach

over time (e.g., Parker et al. 2001). In mysid diet studies, zooplankton mandibles are

often used because mysids shred their prey and these represent the most rigid structures

with high concentrations of silica to withstand constant grinding. Mandibles can also

persist for longer than other structures in guts of starved mysids (Rybock 1978; Murtaugh

1984). Nonetheless, if substantial feeding activity on zooplankton occurs at night we still

expected to see a decline in the number of zooplankton in stomachs and the relative

fullness given the long window of opportunity for daytime digestion to occur (Rudstam et

al. 1989). The lack of diel difference suggests Mysis capture zooplankton during the day

perhaps by suspending off the lake bottom. Mysis can occur off the bottom during the day

if adequate low-light habitat is available (Robertson et al. 1968; O’Malley et al., 2018).

However, those found suspended off the bottom during the day in Lake Champlain tend

to be mostly juvenile mysids that have higher light and temperature tolerance than the

adults considered in our study (O’Malley et al. 2018). A second possibility is that mysids

ingest zooplankton remains that accumulate at the sediment. Research experiments that

address benthic foraging behavior of mysids are needed. We suggest that fine-scale

videography could provide vital details on how Mysis forage at the sediment interface.

134

Stomach fullness showed a consistent pattern in pelagic Mysis collected just after

sunset and then again around midnight. Each month, fullness was higher in the earlier

post-sunset collection compared to the midnight collection. We expected that Mysis

stomachs would be less full shortly after sunset and then increase by midnight after ample

opportunity to forage in the pelagic zone. Others have shown Mysis migrate up with low

amounts of food in their stomach that increases when Mysis are sampled several hours

later in the night (Grossnickle 1979; Rudstam et al. 1989). We are unsure why our

observations deviated from the expected pattern. One possibility is that Mysis in Lake

Champlain left the bottom with full stomachs. A second possibility is that feeding took

place earlier during vertical ascent and was more rapid than expected in pelagic

individuals. Such a possibility, coupled with our observations that stomachs of benthic-

caught Mysis contained high amounts of food just before sunset, suggests Mysis likely did

not have to start from empty when foraging pelagically at night. We were unable to

assess if pelagic Mysis exhibited midnight sinking with our limited night sampling.

Extended pelagic sampling that includes collections between midnight and pre-dawn and

with finer depth resolution (e.g., acoustics; depth-stratified tows) than our whole-column

tows is needed to evaluate potential for midnight sinking behavior.

One limitation of using diet tracers in stomach contents to identify benthic or

pelagic feeding is that the approach requires different prey types to only occur in one

habitat but not both (Pearre 2003). Although we did not measure the relative abundance

of each prey type from benthic and pelagic habitats, we assumed detritus, ostracods,

harpacticoids, and resting eggs would be representative of benthic feeding because these

groups occur primarily in lake benthos (Vihurelouto et al. 2000; Dussart and Defaye

135

2001; Covich et al. 2009). We acknowledge that crustacean groups such as harpacticoids

and ostracods can swim and occur in the pelagia. However, they are generally rare in

pelagic waters compared to cladocerans, calanoids, and cyclopoids (Balcer et al. 1984;

Chess and Stanford 1998; Rudstam et al. 1989). Similar to our findings, Mysis diets

reported from other studies that investigated benthic diets also reported surprisingly low

amounts of these benthic prey groups (i.e., ostracods, harpacticoids, and resting eggs),

despite their high abundance in benthos (Rudstam et al. 1989). Johannsson et al. (2001,

2003) found body parts of the benthic amphipod Diporeia in more benthic- than pelagic-

caught Mysis diets, and amphipod interactions could be an important benthic energy

source to consider because of the high energetic value of Diporeia (Parker 1980; Stewart

and Sprules 2011). We did not find amphipods in diets likely because they are rare in

profundal waters of Lake Champlain (Dermott et al. 2006; Knight et al. 2018). In

summary, stomach content analysis suggests Mysis do not feed heavily on zoobenthos in

Lake Champlain. Instead, Mysis likely use sedimented detritus when benthic, regardless

of time of day.

Conclusion

Our findings suggest a lack of support for the HS hypothesis to explain PDVM in

mysids because stomach contents were rarely empty and did not display a strong diel

pattern consistent with predictions of the HS hypothesis. We did not find strong evidence

to suggest that adult mysids mainly prey on zooplankton because of high amounts of

detritus observed in stomach contents, especially in benthic non-migrant individuals.

Overall, we found more evidence to reject than support the HS hypothesis for PDVM

because of Mysis’ ability to feed on benthic and pelagic food. Therefore, other drivers

136

likely dictate PDVM. Future studies that seek to evaluate connections between foraging

and PDVM should also consider specialization or tradeoffs in predation as those were not

examined in the present study. We propose that non-migrant benthic individuals could

rely on benthic detritus to a much greater extent than migratory individuals because

Mysis feed continuously. In turn, diet and distribution data presented in this study could

be useful to understand the roles of partial migration behavior in food web energy

dynamics and source contributions that support fish communities reliant on Mysis in

systems such as Great lakes where native fish restoration efforts are underway

(Eshenroder and Burnham-Curtis 1999, Hondorp et al. 2005; Eshenroder 2008;

Zimmerman and Krueger 2009). Aspects of pelagic foraging have long been the focus of

Mysis ecology studies, and our analyses point to a need to better understand the benthic

ecology of Mysis, including the importance of detritus to Mysis energetics, which by

extension could fill in knowledge gaps about the basal energy sources that support both

pelagic and demersal fish communities.

Acknowledgements

We thank captain Steve Cluett and deckhand Brad Roy of the R/V Melosira for

their help with diel Mysis sampling. This project was supported by the Great Lakes

Fishery Commission with the assistance of Senator Patrick Leahy, with additional

support from a University of Vermont Chrysalis Award and a scholarship from the

International Association for Great Lakes Research to BPO.

137

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144

Supplemental Table 4.3: Sample collection times of four separate trips. Sunset/sunrise times are

listed below each date in parentheses. Grey shading denotes samples collected during night. Time

refers to the midpoint during the time interval of each sample.

Date

(sunset; sunrise)

Benthic Pelagic

13/14 April 2017 18:05

(19:35; 06:10) 21:28

00:41

06:43

12:43

14/15 June 2016 14:58

(20:39; 05:08) 18:41

22:07 22:26

00:30 01:05

6:39

10:28

18/19 July 2017 19:43

(20:32; 05:26) 21:57 22:26

0:39 1:07

07:02

10:58

14:02

19/20 October 2017 17:27

(18:01; 07:15) 20:20 19:55

22:30 22:52

07:00

10:08

14:35

145

Supplemental Table 4.4: Zooplankton taxa, mean length (L in mm), and length-weight

equations used to estimate dry biomass (W in dry µg). Equations follow the formula

ln(W) = lnA + B • ln(L).

Major

Group Genus/species L (mm) lnA B Source

Calanoid Calanoid copepodid 0.81 1.59 2.59

Burgess et al.

(2015)

Epischura copepodid 1.05 1.59 2.59

Burgess et al.

(2015)

Epischura lacustris 1.71 1.59 2.59

Burgess et al.

(2015)

Leptodiaptomus minutus 0.90 1.59 2.59

Burgess et al.

(2015)

Leptodiaptomus sicilis 1.20 1.59 2.59

Burgess et al.

(2015)

Limnocalanus macrurus 2.24 1.59 2.59

Burgess et al.

(2015)

Senecella calanoides 2.59 1.59 2.59

Burgess et al.

(2015)

Skistodiaptomus

oregonensis 1.18 1.59 2.59

Burgess et al.

(2015)

Cladocera Bosmina longirostris 0.36 3.09 3.04

Bottrell et al.

(1976)

Ceriodaphnia spp. 0.41 2.562 3.34

Bottrell et al.

(1976)

Daphnia mendotae 1.08 1.468 2.83

Bottrell et al.

(1976)

Daphnia retrocurva 0.87 1.468 2.83

Bottrell et al.

(1976)

Eubosmina coregoni 0.44 3.09 3.04

Bottrell et al.

(1976)

Cyclopoid Acanthocyclops spp. 0.92 1.953 2.4

Bottrell et al.

(1976)

Cyclopoid copepodid 0.75 1.953 2.4

Bottrell et al.

(1976)

Diacyclops thomasi 1.00 1.953 2.4

Bottrell et al.

(1976)

Mesocyclops edax 0.80 1.953 2.4

Bottrell et al.

(1976)

Tropocyclops prasinus 0.57 1.953 2.4

Bottrell et al.

(1976)

146

Supplemental Figure 4.10: Variation in the gut fullness ranks assigned to Mysis diets in

pelagic and benthic habitats collected at different times over a diel cycle from 100-m site

in Lake Champlain in June 2016 and April, July, and October 2017. No data were

available from the pelagic habitat in April.

147

CHAPTER 5: COMPARATIVE EVALUATION OF MIGRANT AND NON-

MIGRANT MYSIS FEEDING PREFERENCES

Brian P. O’Malley1, 2, *, Jessica Griffin1, 3, and Jason D. Stockwell1


USA

2 Current address: USGS Great Lakes Science Center, Lake Ontario Biological Station,

Oswego, NY, USA

3 Current address: Department of Biology, San Diego State University, San Diego,

California, USA



148

Abstract

We conducted a feeding experiment to evaluate predictions of the trophic

polymorphism hypothesis (TPH) for partially migrant Mysis. Specifically, we compared

feeding rates in a Mysis population from Lake Champlain that exhibits partial diel

vertical migration, where one portion of the population remains benthic (non-migrant) at

night and the other migrates into pelagic (migrant) waters. Migrants and non-migrants

experience different foraging arenas (benthic or pelagic) at night, and we hypothesized

individuals are more efficient foragers in their habitat of choice. Experimental food

treatments included a known preferred pelagic prey (Daphnia), a presumed less desirable

benthic resource (detritus), and a combination of both. We tested the hypothesis that

migrant (i.e., pelagic-caught) Mysis prefer Daphnia over detritus and therefore exhibit

higher predation rates on Daphnia than non-migrant (i.e., benthic-caught) Mysis, which

were hypothesized to prefer detritus over Daphnia, consistent with different diet optima

that would reflect their observed migration behavior in the field. Consistent with

assumptions of zooplankton as preferred prey opposed to detritus, we evaluated if

Daphnia presence would result in a lower amount of detritus consumed compared when

only detritus was offered. Experimental results did not support the TPH for partial DVM.

Similar predation rates on Daphnia were observed among migrant and non-migrant

Mysis. However, contrary to our hypothesis, a significant effect of food treatment, but not

habitat-origin, was observed with more Daphnia consumed with the inclusion of detritus

in experimental arenas. Our findings highlight the omnivorous component of Mysis diet,

and suggest Mysis readily consume detritus even in the presence of zooplankton. Overall,

149

results do not support the TPH to explain Mysis partial DVM as similar feeding rates

were observed in migrant and non-migrant individuals.

Keywords: partial migration, detritus, trophic polymorphism hypothesis, omnivory

150

Introduction

Intraspecific niche variation within populations is common and has been

documented for a wide range of animals, and can generally be predicted by three main

effects: sexual dimorphism, ontogenetic shifts, and resource polymorphism

(Roughgarden 1972; Bolnick et al. 2003). In migratory species, the term partial migration

is used to describe populations that exhibit variability in migration behavior among

individuals. Specifically, partial migration describes instances when some individuals

migrate while others remain resident (Chapman et al. 2011, 2012). Several hypotheses

have been proposed to explain the ecological and evolutionary drivers of partial

migration although much work still remains to evaluate partial migration hypotheses for a

range of taxa and ecosystems. Most empirical evaluations of partial migration to date

have focused on larger vertebrate fauna (e.g., birds, mammals, and fish; see Chapman et

al. 2011). However, partial migration is also evident in invertebrate fauna, but has

received less attention. The drivers and consequences of invertebrate partial migration

remain largely unknown.

Mysids are a group of aquatic invertebrates found in lakes, estuaries, and oceans,

and most mysid species exhibit diel vertical migration (DVM; Mauchline 1980; Jumars

2007). The typical form of mysid DVM is described as a population-level movement

where individuals vertically migrate from deep-water habitat in the day, to shallower sub-

surface waters at night (Beeton 1960; Haskell and Stanford 2006; Rudstam 2009). DVM

in lower trophic level organisms including mysids has generally been accepted as a

predator-avoidance strategy, in which animals use DVM to avoid high predation risk

from visual predators during the day, when light intensity is high, by moving downward

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to darker habitat. They then migrate upwards at night to capitalize on feeding and high

growth opportunities at shallower depths under darkness when risk is lower (Lampert

1993; Hays 2003; Boscarino et al. 2009; Ringelberg 2010). Mysids are omnivores that

consume pelagic phyto- and zooplankton at night during their ascent portion of DVM

(Grossnickle 1982; Takahashi 2004). In contrast to strictly planktonic organisms, mysids

can also feed on sedimented detritus in benthic habitat, which they presumably access

during the day (Lasenby and Langford 1973; Lasenby and Shi 2004; Sierszen et al.

2011). Morphological and behavioral adaptations to feed on detritus have been described

for some mysid taxa, in addition to filter or raptorial feeding behavior used to ingest

planktonic organisms in the water column (DeGraeve and Reynolds 1975; Grossnickle

1982; Ramcharan and Sprules 1986). For example, Hemimysis larmonae uses a modified

version of filter feeding in which the animal orients its head down at the sediment surface

to lift surficial detritus into suspension with their thoracic appendages (Cannon and

Manton 1927). Consequently, mysids demonstrate multiple forms of feeding within

species.

In members of the Mysis relicta group (M. diluviana, M. relicta, and M. salemaai;

Audzijonytė and Väinölä 2005), partial DVM occurs within populations in freshwater

(Euclide et al. 2017; O’Malley et al. 2018) and marine systems (Rudstam et al. 1989;

Ogonowski et al. 2013), where some individuals remain benthic at night while others

vertically migrate. Partial DVM in mysids goes against conventional DVM theory

because individuals that remain on bottom forego access to presumably high

concentrations of better-quality prey despite lower predation risk in surface waters at

night compared to day. Given that mysids occupy both pelagic and benthic habitats at

152

night, and can feed on resources from both (Johannsson et al. 2003; Lasenby and Shi

2004; Sierszen et al. 2011), one potential hypothesis for Mysis partial DVM is individuals

exhibit different feeding preferences within a population. The trophic polymorphism

hypothesis (TPH) for partial migration (Chapman et al. 2011) in mysids predicts that

some individuals are specialized feeders on either pelagic plankton or benthic resources,

consistent with their migration behavior. Support for TPH has been identified in some

partially migrant fish species that exhibit specialization on different food types (Svanback

et al. 2008; Chapman et al. 2012). In North American lakes, where M. diluviana has

largely been described as a predator on zooplankton (Cooper and Goldman 1980; Bowers

and Vanderploeg 1982; Hrycik et al. 2015), with a preference for cladocerans over other

prey (Grossnickle 1982; O’Malley and Bunnell 2014), the importance or preference of

sedimented detritus as a food resource for mysids that remain on the bottom (non-

migrants) of the lake at night is unknown. Feeding behavior of M. diluviana on detritus

has largely been undescribed to date because most of the focus on their ecological role in

food webs has been on pelagic behavior and competitive implications of introductions in

non-native environments for fisheries management (Lasenby et al. 1986; Spencer et al.

1991; Ellis et al. 2011).

In this study, we used an experimental approach to evaluate predictions of the

TPH as a potential mechanism to explain partial DVM in a Mysis population. We

hypothesized that migrant Mysis found in pelagic waters at night would be more efficient

predators and exhibit greater preference for pelagic zooplankton prey compared to non-

migrant benthic Mysis. Similarly, we hypothesized that non-migrant benthic Mysis would

exhibit greater preference for detritus over Daphnia compared to migrant Mysis when

153

both food types are present, and therefore the presence of detritus would release Daphnia

from predation by non-migrant Mysis under experimental conditions. Given mysid

preference for Daphnia, we expected that both groups of mysids would feed less on

detritus in the presence of Daphnia relative to scenarios when detritus was the only food

option.

Methods

Feeding experiments were performed at the Rubenstein Ecosystem Science

Laboratory with M. diluviana (hereafter Mysis) from Lake Champlain. The experimental

approach followed a common-garden style experiment to compare behavior of migrant

and non-migrant Mysis exposed to the same conditions. Because Mysis are sensitive to

light, and even brief exposure to bright lights can damage their eyes (Feldmann et al.

2010), all field collections and experimental procedures that involved Mysis were

performed under darkness with limited exposure to only dim red light. Each treatment

level used one individual mysid per container as a replicate because mysids feed less

when more than one individual is held in experimental containers (Hamrén and Hansson

1999) and they can be cannabilistic (Quirt and Lasenby 2002; Nordin et al. 2008).

Field sampling

Live benthic- and pelagic-caught mysids were collected at night on 11 Oct 2016

from a 100-m site in Lake Champlain (44° 28’ N; 73° 18’ W). Pelagic Mysis were

collected with a 1-m2 square framed net towed vertically from 80 m depth to surface.

Benthic Mysis were collected using a benthic sled towed for 5 min along bottom. Upon

retrieval of each net or sled tow, organisms were concentrated to the cod-end and

154

immediately submerged into separate coolers filled with chilled lake water. Sufficient

numbers of individuals were collected in a single 5-min benthic sled tow, whereas

multiple replicate vertical tows were required to collect sufficient numbers of pelagic

individuals. Coolers were transported back to the laboratory within 2 hours of collection

and placed in a dark walk-in refrigerator maintained at 5°C.

Sedimented lake detritus, used as the benthic food resource for the experiment,

was obtained by scraping the top 1-2 cm of surface sediment from Ponar grab samples.

Ponar samples were collected from a nearby 60-m site during sunset to prevent disturbing

benthic Mysis at the 100-m site. Previous work has shown detritus organic matter content

and benthic invertebrate communities are similar between 60 and 100 m depths in Lake

Champlain (Knight et al. 2018; J. C. Knight unpublished data). All detritus was combined

in a single jar, and kept on ice in a dark cooler until transport to the walk-in refrigerator

upon return from field sampling.

Experimental setup

The experiment comprised 60 1-L glass jars as foraging arenas for individual

Mysis (Figure 5.1). All jars were setup on a table in a walk-in refrigerator (held at 5°C)

with replicates for each treatment level arranged in a mixed pattern. Each jar was filled

with 600 mL of chilled dechlorinated water obtained from the municipal water supply

sourced from Lake Champlain. Ten individuals of each habitat-origin (i.e., benthic- or

pelagic-caught) were exposed to one of three food treatment levels, for a total of 30

individuals per habitat-origin. The three food treatment levels included Daphnia-only,

detritus-only, and Daphnia plus detritus (Daphnia-detritus). The scraped detritus samples

were homogenized in a slurry with a small amount of dechlorinated water, then 20 grams

155

(wet weight) of the slurry was placed in each of the 1-L jars with 600 mL of

dechlorinated water for the detritus-only and Daphnia-detritus treatments. The slurry was

added just after arrival to the lab following Mysis collections to allow maximum time to

settle on the bottom of jars before the experiment commenced.

Figure 5.1: Schematic of Mysis feeding experiment. For each food treatment (Daphnia-

only, Daphnia-detritus, and Detritus-only), a single Mysis was placed in each of 10 1-L

jars and allowed to forage on the available food over the allotted time under darkness.

A lab culture of Daphnia magna was used for the Daphnia-only and the Daphnia-

detritus treatments. Mysis select for Daphnia over other zooplankton and Daphnia

represents a major proportion of the diets of pelagic-caught Mysis in summer-fall months

(Grossnickle 1982; O’Malley and Bunnell 2014; O’Malley et al. 2017). D. magna can

reach larger body size than the primary native Daphnia spp. (D. mendotae, and D.

retrocurva) that are available to Mysis in Lake Champlain (Balcer et al. 1984; Mihuc et

al. 2012). However, even large-sized D. magna still fall within the size range of prey

consumed by adult Mysis in lakes (e.g., Bythotrephes – Nordin et al. 2008). We used 30

Daphnia per replicate for each treatment level that included Daphnia. A pipette was used

156

to transfer groups of 30 Daphnia to individual 20 mL scintillation vials filled with

dechlorinated water until the start of the experiment. Daphnia vials were moved into the

walk-in refrigerator 1 hr before the start of the experiment to acclimate the Daphnia

before introducing them to each foraging arena.

After an initial 12 hours of acclimation in the original coolers from field

collections in the walk-in refrigerator, large Mysis (> 10 mm) were individually

transferred, using a table spoon, into separate 100-ml jars filled with chilled dechlorinated

tap water to evacuate their gut contents. Only large Mysis were used to ensure all

individuals tested could feed effectively on D. magna (Ramcharan and Sprules 1986).

After 8 hrs, mysids from 100-mL jars were checked to see if they were alive and

swimming, then placed into respective 1-L foraging arenas along with the 100 mL of

water resulting in a final volume of 700 mL of water per foraging arena for the

experiment. Scintillation vials with Daphnia were added at the same time for treatments

with Daphnia. For the treatments with Daphnia, the final volume was estimated to be

720-725 mL because of the water added from the scintillation vials and two rinses with a

squirt bottle to ensure all Daphnia were transferred from the vial. Additional control

foraging arenas with Daphnia-detritus treatments, but no Mysis, were used to assess our

ability to recover Daphnia from Daphnia-detritus trials (N = 8). The experiment ran for

11 hours overnight in darkness in the walk-in refrigerator, from approximately sunset to

sunrise.

At the end of the experiment, jars were narcotized with alka-seltzer tablets to end

feeding. Next, remaining Daphnia and Mysis from each foraging arena were passed

through a 150 µm sieve and preserved in vials with ethanol for counting. Daphnia were

157

counted and Mysis were measured for body length using a dissecting microscope

equipped with a drawing attachment and digitizing tablet for length measurements.

Missing Daphnia were assumed to have been consumed by Mysis. Stomach contents of

Mysis from detritus-only and Daphnia-detritus treatments were dissected and assessed for

detritus under an inverted microscope. The relative amount of detritus in stomach

contents was scored following a semi-quantitative scale (O’Malley and Stockwell in

review) that ranges from 0 (low) to 4 (high amount).

Data analysis

Ingestion rates of Daphnia prey were compared using a two-way ANOVA with

habitat-origin (benthic- and pelagic-caught) and treatment level (Daphnia-only and

Daphnia-detritus) as factors, followed by Tukey’s HSD comparison if a significant

difference was detected. For detritus consumption we used a Wilcoxon signed rank

analysis to compare detritus scores and habitat-origin treatment levels (detritus-only and

Daphnia-detritus). Because body size of Mysis was not measured prior to the start of the

experiment, and only measured post-mortem, we evaluated potential for body size to

influence ingestion rates within the dataset by linear regression of ingestion rate as a

function of body size. All statistical analyses were carried out in R (R Core Team 2017).

Results

Mysis body sizes ranged from 11.5 to 22.2 mm, the mean length was similar

across all treatments (F5,53 = 2.03, P > 0.05, Table 5.1). One Mysis that originated from

pelagic habitat and was used in the detritus-only treatment type could not be located at

the end of the experiment and the replicate was disregarded from further analysis. Out of

158

the 8 jars used as controls to assess recovery efficiency of Daphnia in the Daphnia-

detritus treatment, 7 jars yielded full recovery of 30 Daphnia per jar, and 1 jar yielded 28

Daphnia.

Table 5.1: Mean length of Mysis used in feeding experiment.

Origin Treatment N Mean length

(mm ± SD)

Benthic Daphnia-only 10 17.6 ± 2.0

Daphnia-detritus 10 17.1 ± 1.3

Detritus-only 10 16.8 ± 1.8

Pelagic Daphnia-only 10 17.9 ± 2.8

Daphnia-detritus 10 16.2 ± 2.7

Detritus-only 9 19.2 ± 2.4

Mean ingestion rate of Daphnia by Mysis (Daphnia hr -1) was significantly

affected by feeding treatment type (two-way ANOVA, F1,36 = 13.40, P < 0.01, Table 5.2)

but not by habitat-origin (benthic- or pelagic-caught) from which the Mysis were

collected (F1,36 = 1.67, P > 0.05). No significant interaction was evident between habitat-

origin and Daphnia treatment level (F1,36 = 0.83, P > 0.05). Post-hoc comparison of

feeding treatments showed mean ingestion rate (Daphnia hr -1) in the Daphnia-only

treatment (N = 20, mean = 0.39 ± 0.08 SE) was significantly lower than in the Daphnia-

detritus treatment (P < 0.001, N = 20, mean = 0.85 ± 0.09). Ingestion rates were not

significantly influenced by Mysis body size over the range of animal sized used in the

experiment (Figure 5.2, P > 0.05).

Comparison of detritus scores in Mysis stomach contents of individuals exposed

to the detritus-only treatment revealed similar scores between benthic- (mean = 2.4 ± 0.4

SE) and pelagic-caught Mysis (3.0 ± 0.5, Wilcoxon signed-rank test, W = 33, P > 0.05).

Similarly, in the Daphnia-detritus treatment, detritus scores of stomach contents between

159

benthic- (2.4 ± 0.5) and pelagic-caught Mysis (1.9 ± 0.4) were not significantly different

(W = 60.5, P > 0.05).

Table 5.2: Two-way ANOVA results of Mysis predation rates (No. Daphnia hr-1).

Factor d.f. Sum-of-Squares F-value P-value

habitat-origin 1 0.27 1.67 0.21

treatment 1 2.15 13.40 < 0.01

habitat-origin: treatment 1 0.01 0.05 0.83

error 36 5.78

Figure 5.2: Observed ingestion rates of Mysis on Daphnia as a function of Mysis body size.

Discussion

We tested predictions of the TPH for partial DVM in a Lake Champlain Mysis

population using an experimental approach. A substantial body of literature on pelagic

foraging behavior of Mysis has emphasized the importance of pelagic resources to Mysis,

although relatively much less is known about the role of benthic feeding. To our

knowledge, studies have yet to assess the relative preference for benthic detritus over

160

other food types available to partially migrant mysids that exhibit different behavior, and

thus have different temporal exposure to benthic or pelagic prey dependent on their

migration behavior. Experimental results confirmed the assumption that Mysis will eat

detritus, and contrary to a common expectation that when offered a choice between

Daphnia or detritus, Mysis continue to feed on detritus even in the presence of their

supposedly preferred prey Daphnia. Overall, the use of detritus as a resource by Mysis

when Daphnia is available supports studies that have suggested Mysis are omnivorous

(Grossnickle 1982; Johannsson et al. 2003; O’Malley and Bunnell 2014), as opposed to

obligate carnivores, and agrees with recent work that suggests benthic feeding may

represent a significant contribution to their diet (Sierszen et al. 2011; O’Malley and

Stockwell in review). Our results did not support our original hypotheses based on

predictions of the TPH that benthic, non-migrant mysids would feed more extensively on

detritus, and pelagic, migrant Mysis would feed more on Daphnia. Similarly, alterations

to feeding treatments by presenting both groups of Mysis with both detritus and Daphnia

did not release Daphnia from predation in either case.

Increased ingestion rate of Daphnia in the presence of detritus may suggest that

the benthic detritus creates a preferred feeding environment for mysids, in which a mysid

more likely to feed or sediment leads to increased feeding efficiency. Survival of

Neomysis intermedia fed plankton in experimental chambers increased when mud or sand

was placed on the bottom to provide a substrate (Murano 1966). However, multiple

studies on predation rates of M. diluviana on zooplankton prey have been performed in

the absence of substrate (e.g., Cooper and Goldman 1980, 1982; Ramcharan and Sprules

1986; Rudstam et al. 1999; Chipps and Bennett 2002), suggesting mysids may still feed

161

at comparable rates in bare experimental containers compared to in situ rates (Bowers

and Vanderploeg 1982). Impacts of detritus presence in experimental chambers on

survival or performance of M. diluviana have not been examined. Alternatively, the

sediment may provide a staging zone in small foraging arenas from which M. diluviana

can attack prey more effectively. Mysis diluviana has been observed to launch off the

sediment by reflexing their abdominal segment against the substrate, which results in a

greater acceleration speed than observed in the water column (Bowers et al. 1990). To

avoid confounding effects of substrate on predation rates, additional control experiments

possibly with inorganic or synthetic substrate with similar composition to sedimented

detritus could be used to test for effects of detritus on zooplanktivory rates in mysids.

Our feeding experiment was run in darkness, and could have could have affected

the ability to detect an effect of habitat origin on ingestion rates if migratory pelagic

Mysis are better adapted to use light to seek out prey than non-migrant Mysis. Mysis have

relatively large compound eyes likely used to perceive prey under low light conditions

(Ringelberg 2010). Previous experimental work showed Mysis exhibit increased

predation rates on Daphnia in the presence of low light levels compared to complete

darkness (Ramcharan and Sprules 1986). Additional experiments that incorporate effects

of low light levels typically experienced by Mysis during DVM into the upper hypo- and

lower metalimnion at night (Beeton 1960; Lehman et al. 1990; Gal et al. 1999; Boscarino

et al. 2009) are needed to explore possible interactions between light and food type on the

usefulness of TPH to explain Mysis partial DVM.

Stable isotope and stomach content analyses of field-collected individuals could

provide further evaluation of the TPH in situ. Our study focused on an experiment to

162

evaluate rates and preferences among individuals, whereas stable isotopes can provide a

long-term picture of feeding history if benthic and pelagic resources vary in isotopic

signatures. In the Baltic Sea, Ogonowski et al. (2013) found significant differences in

carbon (δ13C) and nitrogen (δ15N) isotope ratios in mysids from benthic and pelagic

habitat, suggesting apparent differences in resource use between groups. In Lake

Champlain, previous investigation however did not find a significant difference in δ13C or

δ15N of migrant and non-migrant Mysis (Euclide et al. 2017). Collections in the Lake

Champlain study were limited to the month of November, a time of year when thermal

stratification breaks down and the water column becomes well-mixed compared to

summer periods when thermal gradients limit mixing. One might expect substantial

differences between pelagic and benthic stable isotope baselines during summer when

thermal gradients are stronger. The application of stable isotope ratios to discriminate

trophic differences, at least for δ15N, however, can also be limited because δ15N and

trophic level can be independent of each other (Flynn et al. 2018). Nitrogen isotope ratios

(δ15N) of benthic material generally become enriched with depth as sinking detritus

particles undergo bacterial colonization, while δ15N of planktonic material remains

constant across depths (Sierszen et al. 2006; 2011), biasing detection of trophic

differences if not accounted for in models. Gut content data provides a snapshot of

recently ingested food, and comparisons of benthic- and pelagic-caught mysids in Lake

Champlain indicated higher amounts of detritus in diets of benthic-caught mysids,

although diet differences between groups were not as strong as expected if migrants and

non-migrants exclusively fed on different resource pools (O’Malley and Stockwell in

review). Moreover, both detritus and plankton occur in migrant and non-migrant gut

163

contents (O’Malley and Stockwell in review), which agrees with our experimental results

and suggests only limited evidence for trophic differences to explain partial DVM in

mysids.

We recognize that our classification of migrant and non-migrant mysids relies

only on the habitat from which the individuals were captured, and may not be

representative of long-term behavior of those individuals if migration behavior varies

day-to-day among individuals. Current limitations in tracking technology for small

organisms such as mysids that undergo large vertical changes in depth precludes

inference on whether mysids collected in from a particular habitat at night is indicative of

long-term migration behavior. Developments and advances in such technologies will

undoubtedly benefit the partial migration studies of small aquatic invertebrates including

mysids. Nonetheless, experiments and field studies that compare traits of individuals

from different habitats in the interim of tracking advances, will provide a foundation for

further hypotheses, in addition to insights on food web implications of partial DVM.

In conclusion, results from our study do not suggest support for differences in

feeding preference to explain partial DVM in Mysis from Lake Champlain, nor do

previous field observations from the same system (Euclide et al. 2017; O’Malley and

Stockwell in review). Although support for the TPH in partially migrant mysids from

other systems has been identified (Ogonowski et al. 2013), the lack of support in Lake

Champlain suggests that drivers of mysid partial DVM could vary across systems or

among species. While previous work in Lake Champlain has identified body size

differences among migrant and non-migrants (Euclide et al. 2017; O’Malley et al. 2018),

we controlled for this factor by only using Mysis of similar size in our experiment to limit

164

ontogenetic effects of feeding (Werner and Gilliam 1984), and to maintain focus on

variation in feeding of mysids of similar body size. The lack of difference in Mysis of

different habitat origins, and the significant effect of feeding treatment when detritus was

introduced, does call into question whether Mysis may prefer to be benthic, perhaps by

taking advantage of a more favorable environment when adequate food supply is

available to attack prey or one with less predation risk. However, the potential for

substrate effects to entice Mysis to stay benthic and not migrate into the pelagic

environment requires further evaluation.

Acknowledgements

We thank Steve Cluett and Brad Roy for help with field collections and Hannah

Lister, and Sture Hansson for help executing the experiment. Funding was provided by

the Great Lakes Fishery Commission with the assistance of Senator Patrick Leahy, a

University of Vermont Chrysalis Award, and a scholarship from the International

Association for Great Lakes Research to BPO. Partial support was also provided by the

National Science Foundation Research Experiences for Undergraduates (REU) Program

(DBI-1358838).

165

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Evaluation of Mysis partial diel vertical migration