Changes in feeding selectivity of freshwater invertebrates ...9f4a4752-806f... · 1. Freshwater invertebrates will have a more specialist feeding strategy in warmer environments

Article

Changes in feeding selectivity of freshwater

invertebrates across a natural thermal gradient

Timothy A. C. GORDONa,b, Joana NETO-CEREJEIRA

a, Paula C. FUREYc, and

Eoin J. O’GORMANa,*

aImperial College London, Silwood Park Campus, Buckhurst Road, Ascot, Berkshire, SL5 7PY, UK, bBiosciences,

College of Life and Environmental Sciences, University of Exeter, Stocker Road, Exeter, EX4 4QD, UK andcDepartment of Biology, Saint Catherine University, St Paul, MN 55105, USA

*Address correspondence to Eoin J. O’Gorman. E-mail: [email protected].

Received on 29 September 2017; accepted on 22 January 2018

Abstract

Environmental warming places physiological constraints on organisms, which may be mitigated by

their feeding behavior. Theory predicts that consumers should increase their feeding selectivity for

more energetically valuable resources in warmer environments to offset the disproportionate increase

in metabolic demand relative to ingestion rate. This may also result in a change in feeding strategy or a

shift towards a more specialist diet. This study used a natural warming experiment to investigate tem-

perature effects on the feeding selectivity of three freshwater invertebrate grazers: the snail Radix balth-

ica, the blackfly larva Simulium aureum, and the midgefly larva Eukiefferiella minor. Chesson’s

Selectivity Index was used to compare the proportional abundance of diatom species in the guts of

each invertebrate species with corresponding rock biofilms sampled from streams of different tem-

perature. The snails became more selective in warmer streams, choosing high profile epilithic diatoms

over other guilds and feeding on a lower diversity of diatom species. The blackfly larvae appeared to

switch from active collector gathering of sessile high profile diatoms to more passive filter feeding of

motile diatoms in warmer streams. No changes in selectivity were observed for the midgefly larvae,

whose diet was representative of resource availability in the environment. These results suggest that

key primary consumers in freshwater streams, which constitute a major portion of invertebrate bio-

mass, can change their feeding behavior in warmer waters in a range of different ways. These patterns

could potentially lead to fundamental changes in the flow of energy through freshwater food webs.

Key words: climate change, global warming, diet, Lymnaea peregra, Simuliidae, Chironomidae

Anthropogenic climate change has caused global surface temperatures

to rise dramatically over the last century. Warming projections fore-

cast a minimum increase of 1.5–2�C by 2100, with the Arctic region

likely to experience the highest levels of warming (IPCC 2014).

Environmental warming alters the physiology, phenology, and geo-

graphic range of species in different ways, according to their thermal

tolerances (Parmesan 2006; Chen et al. 2011; Ohlberger 2013). This

can lead to the extinction of some species and the introduction of

others, altering community structure through changes to the identity,

metabolic demand, and activity levels of interacting species (Walther

et al. 2002; Root et al. 2003; Urban et al. 2013).

Warming-induced changes to trophic interactions are particu-

larly important because they can dramatically affect whole com-

munities. The highly connected nature of food webs facilitates

widespread effects via trophic cascades, where a direct effect on one

species also has indirect effects on its consumers and resources (Polis

et al. 1996; Pace et al. 1999). For example, temperature-regulated

vernal blooms of freshwater diatoms in a large, temperate North

American lake advanced by up to 3 weeks in the past 50 years in re-

sponse to warming, causing a temporal mismatch with the

photoperiod-regulated annual emergence of diapausing zooplankton

eggs (Winder and Schindler 2004). This resulted in a long-term

VC The Author(s) (2018). Published by Oxford University Press. 1This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/),

which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact

[email protected]

Current Zoology, 2018, 1–12

doi: 10.1093/cz/zoy011

Advance Access Publication Date: 27 January 2018

Article

Downloaded from https://academic.oup.com/cz/advance-article-abstract/doi/10.1093/cz/zoy011/4827691by University of Exeter useron 27 February 2018

I will be presenting results centered on algal responses to climate warming and eutrophication. This research stems from some collaborative research efforts in Iceland. The papers attached here will introduce you to the system and some of the broader ecological considerations at play. I will set the stage with highlights from the second paper (authored by members of the collaborative team; page 14), before transitioning to a focus on the algae (results not yet published).

decline in zooplankton populations, which depend on the diatoms

for food during the crucial development phase; in turn, energy flow

to higher trophic levels was reduced. Similarly, experimental warm-

ing of ponds has been shown to alter the degree to which both

bottom-up and top-down control determine community structure,

causing widespread impacts on multiple species throughout the food

web (Shurin et al. 2012).

Freshwater communities are thought to be especially vulnerable

to such changes for several reasons (Woodward et al. 2010a). First,

many freshwater organisms are limited in their dispersal ability by

both physiological constraints and a lack of connectivity between

freshwater habitats (Finn et al. 2006; Evans et al. 2009), meaning

that it is difficult to respond to warming by migrating to areas with

more favorable climates. Further, many freshwater ecosystems are

simultaneously threatened by other anthropogenic stressors, which

can interact with and exacerbate the impacts of warming

(Kundzewicz et al. 2008; Arthington et al. 2010). Additionally, it

has been suggested that trophic cascades can be particularly strong

in freshwater ecosystems compared to other biomes (Halaj and Wise

2001; Shurin et al. 2002), although this idea is controversial and not

universally accepted (Schmitz et al. 2000).

Methods used to study the effects of warming on freshwater

food webs include theoretical modelling (Petchey et al. 2010; Binzer

et al. 2015), mesocosm-based experiments (Petchey et al. 1999;

Shurin et al. 2012), whole-ecosystem manipulations (Hogg and

Williams 1996), and natural thermal gradients (O’Gorman et al.

2014). Such studies are increasingly focused on general responses

across species and changes in the topological structure of the food

web (Petchey et al. 2010; O’Gorman et al. 2012; Shurin et al. 2012).

However, individual-based responses are also important in this area

as they reveal patterns that are not described by species-averaged

data (Woodward et al. 2010b).

Individual foraging-related behavioral responses play important

roles in determining food web dynamics (Ings et al. 2009), with

models based on foraging characteristics such as dietary niche width

accurately predicting food web structure (Beckerman et al. 2006;

Petchey et al. 2008). Feeding selectivity represents one such example

of an individual-based response that impacts community-level dy-

namics. Changes in consumer selectivity have been shown to affect

the selection pressures they exert on different resource species

(Lankau 2007; Castillo et al. 2014), the transfer of material through

food chains (Zhang et al. 2013), and community structure as a

whole (Drenner 1982; Drenner et al. 1984). Indeed, the feeding se-

lectivity of an individual species can be used as a predictor of its

likely impacts on the dynamics of ecosystems to which it is newly

introduced (Dodd et al. 2014).

Many invertebrate consumer species alter their feeding selectivity

in response to a variety of selection pressures. For example, grass-

hoppers exposed to predation risk switch to a diet with higher

carbohydrate content relative to unstressed individuals (Hawlena

and Schmitz 2010), and pathogen-infected caterpillars increase their

dietary protein intake relative to healthy individuals (Lee et al.

2006). A consumer’s feeding selectivity can be thought of in terms of

either its overall strategy (i.e. whether it is a generalist or a special-

ist), or its preference for a particular resource group or species.

Empirically, the latter is commonly tested through comparisons of

the proportional representation of a resource species in a consumer’s

diet and in the environment (e.g., Berumen & Pratchett 2008;

O’Gorman et al. 2016). The former can be tested either by analyzing

the average value of such calculations for all resource species in the

diet (e.g. Blackwood et al. 2001) or by using alternative methods

such as comparisons of dietary composition and diversity (e.g.

Jonsen and Fahrig 1997) or stable isotope analysis of dietary niche

width (e.g. O’Gorman et al. 2016).

Theoretical work has suggested that both of these aspects of

feeding selectivity may be affected by warming. The rate at which

metabolic demand increases with temperature is thought to outpace

the accompanying increase in ingestion rate, resulting in a decreased

ingestion efficiency (defined as the ratio of ingestion, i.e., energy in-

take, to metabolism, i.e., energy demand) in warmer environments

(Rall et al. 2010). This may lead to consumers increasing their se-

lectivity for higher quality food items to offset temperature-

associated ingestion inefficiency. For example, laboratory choice

tests on a herbivorous beetle revealed that increased feeding on

nitrogen-rich plant species at higher temperatures resulted in a more

specialised diet overall (Lemoine et al. 2013), and brown trout have

been shown to choose prey with a higher energetic value as part of a

more selective diet at higher stream temperatures (O’Gorman et al.

2016).

This study examines the effects of stream temperature on the

feeding selectivity of three freshwater invertebrates as primary con-

sumers in a natural warming experiment, testing two main

hypotheses:

1. Freshwater invertebrates will have a more specialist feeding

strategy in warmer environments. Logic: feeding on a smaller,

higher quality subset of the available resource species at higher

temperatures may help consumers to mitigate the effects of

decreasing ingestion efficiency (Rall et al. 2010).

2. Freshwater invertebrates will have different preferences for re-

source taxa in warmer environments. Logic: diatoms differ in

their nutritional content and ease of acquisition, thus a switch in

resource preference or feeding mode may be more efficient at

higher temperatures as resource availability or other selection

pressures change.

Materials and Methods

Study siteSamples were collected in August 2008 from the Hengill geothermal

system in southwest Iceland (64�030N, 021�180W). This system

contains numerous spring-fed tributaries of the river Hengladalsa,

which are differentially warmed by indirect geothermal heating of

the bedrock that the groundwater flows over (Arnason et al. 1969).

All of the streams are connected via the main stem and are within

2 km of each other, meaning that biotic dispersal constraints are low

and the physical and chemical characteristics of the streams are very

similar (Friberg et al. 2009; Adams et al. 2013). This lack of other

sources of environmental variation makes Hengill an ideal natural

experiment for studying the effects of stream temperature on aquatic

communities in situ. Eight streams spanning a temperature range of

19.5�C were chosen for this study (Figure 1).

Invertebrates were collected in benthic Surber samples

(25�20 cm quadrat; 200mm mesh; five samples per stream) and

preserved in 70% ethanol. Surveys of the benthos were performed

during the same time period to quantify epilithic algal assemblages,

consisting of three stone scrapes per stream. Diatom frustules from

the stone scrapes were cleared of organic matter with nitric acid,

dried, and mounted on slides with naphrax. Relative abundances

were estimated by counting the number of individuals of each spe-

cies along a 15�0.1 mm transect of each slide, ensuring that a tran-

sect contained at least 300 individuals. Full details of stream

2 Current Zoology, 2018, Vol. 0, No. 0


benthos survey methods and results are reported by O’Gorman et al.

(2012), including yield-effort curves which show that these sample

numbers were sufficient to accurately describe the composition of

both the invertebrate and diatom communities (Appendix C in

O’Gorman et al. 2012).

Study speciesThree prominent primary consumers from the Hengill system, each

with a different functional feeding mode, were chosen for dietary

analyses. The snail Radix balthica Linnaeus, 1758, is the dominant

scraping grazer in the Hengill system (O’Gorman et al. 2012). The

blackfly larva Simulium aureum Fries, 1824, may traditionally be

thought of as a strict filter feeder, but has congeners that are able to

collect small algal particles from the biofilm, i.e. collector gatherers

(Burton 1973; Walsh 1985; Alder and McCreadie 1997), and this

behaviour has been regularly observed in the Hengill system (per-

sonal observation). The midgefly larva Eukiefferiella minor

Edwards, 1929, is thought to be a largely generalist collector gath-

erer (Henriques-Oliveira et al. 2003), as for most chironomids dur-

ing some part of their larval lifespan (Berg 1995). These invertebrate

consumer species are likely to play important ecological roles in

both the bottom-up regulation of secondary consumers and the top-

down control of epilithic algal assemblages in freshwater stream sys-

tems (Ledger et al. 2006; Gudmundsdottir et al. 2011; Sturt et al.

2011; O’Gorman et al. 2012).

Gut content analysesDietary selectivity for epilithic diatom species at different tempera-

tures was investigated using gut content analyses from all three in-

vertebrate consumers. Diatoms were chosen for these assays as

previous research from the system suggests that>90% of inverte-

brate diets are composed of diatoms and fine particulate organic

matter, with virtually no allochthonous inputs and minimal preda-

tory behavior among invertebrates (O’Gorman et al. 2017). Gut

content analyses were carried out on individuals representing an

even spread across the body size distributions present in the samples.

Invertebrates were acid-digested for 18 h in 1.5 mL of 62% nitric

acid (HNO3) at 65�C, in order to remove all organic matter except

for silicate diatom frustules in the guts. Step-wise dilutions with dis-

tilled water were then carried out to achieve a minimum pH of 4.5

prior to slide mounting. One milliliter sub-samples of the resulting

suspensions of diatom frustules were pipetted onto glass coverslips

and allowed to dry overnight. Once dry, cover slips were fixed to

glass slides by adding a drop of naphrax (Brunel Microscopes Ltd.,

Chippenham, UK) and heating to 60�C on a hotplate, before allow-

ing the naphrax to dry for slide analysis.

Diatoms were identified using the species definitions of

Krammer and Lange-Bertalot (1986–1991), in the same manner as

the quantification of epilithic algal assemblages (O’Gorman et al.

2012; Adams et al. 2013). The relative abundance of individual dia-

tom species in each gut was determined by recording the species

identity of the first 100 diatom individuals encountered in a continu-

ous, non-overlapping 100mm-wide transect following a fixed route

across the slide. Transects were continued until 100 individuals

were encountered or the entire slide had been examined. To ensure

that no additional diatom species were missed by only examining

the first 100 individuals, the entirety of each slide was checked for

novel species. This procedure never yielded extra species not present

in the initial transect, suggesting that identifying the first 100 diatom

individuals was enough to accurately characterize the species present

on each slide.

The number of invertebrates per stream required to accurately

quantify the diet was determined using yield-effort curves. The cu-

mulative number of diatom species identified was used as an indica-

tor of diet characterisation, and plotted against the number of

invertebrate gut content slides examined. For each stream, cumula-

tive diatom species count data were used to plot asymptotic curves

(“SSasymp” function in the “stats” package of R 3.4.0; R Core

Team 2017) of the form:

y ¼ Aþ ðR0 � AÞe�eln ðcÞx; (1)

where A is the horizontal asymptote, R0 is the response when x¼0,

and c is the rate constant. Curves were fitted for 1,000 randomiza-

tions of the sample order, and the median parameters of the 1,000

curves were used to calculate an overall yield-effort curve for each

consumer species in each stream (Figure 2). The horizontal asymp-

tote of these overall curves was taken to represent a theoretical max-

imum for the number of diatom species making up the diet of

consumers in that stream. The difference between the theoretical

and observed number of diatom species in the diet for a given stream

never exceeded 3.7 for E. minor, 0.4 for R. balthica, and 2.3 for S.

aureum (Figure 2). It was therefore assumed that the accuracy of

diet characterization was adequate for this study.

Quantifying selectivity strategyThe level of generality or speciality of invertebrate feeding on dia-

tom species was first assessed using diversity metrics of the dietary

composition. Species richness, Pielou’s evenness, and Shannon diver-

sity metrics were calculated for the diatom communities present in

each consumer’s gut contents. A lower richness, evenness, or diver-

sity of diatom species in the guts would indicate a more specialized

feeding strategy.

To account for variation in diatom communities in each stream,

the Chesson Selectivity Index (CSI; Chesson 1983) was used to

Figure 1. Map of the study site. Schematic of the Hengill geothermal streams,

with labels indicating the eight streams used in this study and their associ-

ated mean temperatures in August 2008. Stream names are in keeping with

the labelling system used in previous studies (e.g., O’Gorman et al. 2012).

Gordon et al. � Temperature and invertebrate feeding selectivity 3


compare the proportional representation of each diatom species in

the gut contents with its proportional representation in the stream

benthos. The CSI was calculated as follows:

CSI ¼gi=biPnj¼1

gj=bj

; i ¼ 1; . . .; n; (2)

where n is the total number of diatom species in the gut contents,

and g and b are the proportional representation of diatom species i

or j in the gut contents and stream benthos, respectively. The CSI

value for a given diatom species i reflects its presence in the gut con-

tents relative to the stream benthos, divided by the sum of the

equivalent calculation for all diatom species in the gut. This is there-

fore a proportional indicator of the level of selectivity for each spe-

cies in the diet, with 0 indicating complete absence from the diet and

1 indicating exclusive feeding on that species. The distribution of

CSI values for each resource species in a single consumer’s gut was

taken as a proxy for its overall selectivity strategy, with the median

value for each individual consumer indicating its level of generality

or speciality. A higher median CSI value would indicate a more

specialist feeding strategy, with consumers feeding heavily on a few

species, rather than feeding weakly on many species.

Quantifying preference for diatom taxaDiatom species composition was different for each stream

(O’Gorman et al. 2012; Adams et al. 2013), making it difficult to

objectively assess preference for individual species. As such, diatom

species were classified into three distinct ecological guilds (low pro-

file, high profile, and motile) based on morphology and accessibility

to consumers, following previous work by Fore and Grafe (2002),

Passy (2007), and Rimet and Bouchez (2012). Diatom classifications

are broadly similar in all three approaches, but this study most

closely resembled Passy (2007) as it resulted in an even spread of the

diatom species in this dataset across the three guilds (e.g., there are

only two species from the Hengill streams that would fit in the add-

itional planktonic guild of Rimet and Bouchez 2012). All guild des-

ignations were made on a species-by-species basis using trait

information sourced from the “Diatoms of the United States” online

guide (https://westerndiatoms.colorado.edu).

Figure 2. Yield-effort curves for invertebrate gut contents in each stream. Gray lines represent asymptotic curves fitted to 1,000 sample order randomizations of

the cumulative species count; black lines represent the overall curve based on median parameters of the 1,000 randomized curves. Asymptote values for the

overall curves were taken as theoretical maxima for the number of diatoms in each consumer’s diet, and are given alongside the actual number of diatoms identi-

fied in each case.



Low profile diatoms comprise slow-moving or non-motile spe-

cies that attach directly and closely to the substrate without forming

branches or colonies. This guild is characterized by a short stature,

potentially making them difficult for grazing or filter-feeding con-

sumers to acquire, and includes diatoms from the genera

Achnanthes Bory de Saint-Vincent, 1822, Amphora Ehrenberg ex

Kutzing, 1844, Aulacoseira Thwaites, 1848, Cocconeis Ehrenberg,

1837, Cyclotella (Kutzing) Brebbisson, 1838, Hannaea Patrick,

1961, Karayevia Round et Bukhtiyarova ex Round, 1998, Meridion

Agardh, 1824, and Planothidium Round et Bukhtiyarova, 1996.

High profile diatoms comprise species that attach to the substrate

and either have stalks or form long, branching colonies extending

beyond the boundary layer. This guild is characterized by a tall stat-

ure, potentially making them more accessible to grazing consumers,

and includes diatoms from the genera Cymbella Agardh, 1830,

Diatoma Bory de Saint Vincent, 1824, Encyonema Kutzing, 1849,

Eunotia Ehrenberg, 1837, Fragilaria Lynbye, 1819, Gomphonema

Ehrenberg, 1832, Melosira Agardh, 1824, Rhoicosphenia Grunow,

1860, Staurosirella Williams et Round, 1987, and Ulnaria (Kutzing)

Compere, 2001. Motile diatoms comprise comparatively fast-

moving species with well-developed raphe structures. This guild is

characterised by its movements over surfaces, potentially making it

more accessible to less motile, filter-feeding consumers, and includes

diatoms from the genera Caloneis Cleve, 1894, Cavinula Mann et

Stickle ex Round et al, 1990, Diploneis (Ehrenberg) Cleve, 1894,

Eolimna Lange-Bertalot et Schiller, 1997, Epithemia Kutzing, 1844,

Frustulia Rabenhorst, 1853, Mayamaea Lange-Bertalot, 1997,

Navicula Bory de Saint Vincent, 1822, Nitzschia Hassall, 1845,

Pinnularia Ehrenberg, 1843, Placoneis Mereschkowsky, 1903,

Rhopalodia Muller, 1895, and Surirella Turpin, 1828.

The proportional representation of each diatom guild in the gut

contents of invertebrate consumers was calculated and used in place

of species identity in Equation 2 to estimate CSI at the guild-level.

All diatom guilds were present in the guts of all consumer species in

all of the streams, facilitating a less biased comparison of preference

for the various guilds across the stream temperature gradient.

Statistical analysisAll statistical analysis and figure plotting was carried out in R 3.4.0

(R Core Team 2017). Response variables included the species rich-

ness, Pielou’s evenness, and Shannon diversity of diatom species in

the guts, the median CSI value for diatom species, and the CSI for

low profile, high profile, and motile diatom guilds. All response

Figure 3. Diversity of diatom species in the guts of invertebrate consumers. Box plots display species richness, Pielou’s evenness, and Shannon diversity of dia-

tom species in the guts of (A–C) Radix balthica, (D–F) Simulium aureum, and (G–I) Eukiefferiella minor in different streams. Boxes represent the median 6 inter-

quartile range; whiskers represent the 5–95% range; single points represent outliers. Bars not sharing a common letter (a, b, or c) were significantly different from

each other (Tukey test: P< 0.05), while “ns” indicates no significant difference between streams.



variables were analysed separately using one-way Analysis of

Variance (ANOVA; “aov” function in the “stats” package; R Core

Team 2017). In each case, stream identity was treated as a categor-

ical explanatory variable with three levels and a separate analysis

was performed for each consumer species. Tukey’s HSD post-hoc

test was used to assess which streams were significantly different

from each other (“TukeyHSD” function in the “stats” package; R

Core Team 2017). Assumptions of normality and heteroscedasticity

were confirmed using visual analyses of residual plots and the

Fisher–Pearson standardised third moment coefficient, with no

transformation of the data required. Differences in each of the re-

sponse variables across streams and consumer species were visual-

ised with boxplots. To help inform the species-level investigation of

CSI values, a probability density function was fitted to the distribu-

tion of CSI values for each diatom species in a single consumer gut.

To help inform the guild-level investigation of CSI values, the rela-

tive abundance of diatom guilds in the stream benthos and in the gut

contents were plotted alongside the CSI values for each diatom

guild.

Results

Selectivity strategyThe three invertebrate consumers exhibited different changes in se-

lectivity strategy for diatom species along the stream temperature

gradient (Figure 3). There was a significant reduction in the species

richness, Pielou’s evenness, and Shannon diversity of diatom species

in the diet of R. balthica in the warmer streams (Figure 3A–C;

Table 1). In contrast, there was a significant increase in the species

richness and Shannon diversity of diatom species in the diet of S.

aureum in the intermediate-temperature stream (i.e., IS3), although

there was no significant difference in Pielou’s evenness (Figure 3D–

F; Table 1). There was a significant increase in the species richness

of E. minor in the warmer streams, but no significant differences in

Pielou’s evenness or Shannon diversity (Figure 3G–I; Table 1).

Distributions of CSI values were generally skewed towards lower

values for all three invertebrate consumers, suggesting they fed quite

generally on all diatom species (Figure 4). There was a significant in-

crease in the median CSI value for R. balthica in the warmer streams

(Figure 4D; Table 1). There was no significant change in the median

CSI value of either S. aureum or E. minor across the stream tempera-

ture gradient (Figure 4H and L, Table 1).

Preference for diatom taxaRadix balthica had a significantly stronger preference for high pro-

file diatoms and a significantly weaker preference for low profile

diatoms in the warmest stream, with no significant change in prefer-

ence for motile diatoms (Figure 5A–C; Table 1). Simulium aureum

had a significantly weaker preference for high profile diatoms as

stream temperature increased and a significantly stronger preference

for both low profile diatoms and motile diatoms in the warmest

stream (Figure 5D–F; Table 1). Eukiefferiella minor exhibited no

change in preference for high profile diatoms, low profile diatoms,

or motile diatoms (Figure 5G–I; Table 1).

Comparison of the relative abundances of diatom guilds in the

stream benthos and gut contents revealed further insights into the

feeding behavior of the invertebrate consumers (Figure 6). For R.

balthica, the weaker preference for low profile diatoms in the warm-

est stream (Figure 6G) was unrelated to their environmental avail-

ability, with a similar relative abundance of low profile diatoms in

all streams (Figure 6A). Instead, R. balthica appeared to increase its

preference for high profile diatoms in the warmest stream

(Figure 6G), perhaps due to their ubiquity in that stream

(Figure 6A). In contrast, the decreasing preference for high profile

diatoms with increasing stream temperature in S. aureum

(Figure 6H) occurred despite a large increase in their availability in

Table 1. Statistical outputs from ANOVA and Tukey’s HSD tests comparing the gut content diversity metrics presented in Figure 3, the

Chesson Selectivity Index (CSI) values presented in Figure 4, and the preference for different diatom guilds presented in Figure 5 for the

three study organisms (R. balthica, S. aureum, and E. minor) across the various study streams

Radix balthica Simulium aureum Eukiefferiella minor

Metric Figure ANOVA Tukey’s HSD ANOVA Tukey’s HSD ANOVA Tukey’s HSD

Species richness 3 F2,41 ¼ 5.58

P ¼ 0.006

IS6–IS12 P ¼ 0.050

IS8–IS12 P ¼ 0.004

IS8–IS6 P ¼ 0.685

F2,58 ¼ 10.70

P < 0.001

IS3–IS1 P < 0.001

IS8–IS1 P ¼ 0.997

IS8–IS3 P < 0.001

F2,41 ¼ 10.54

P < 0.001

IS11–IS10 P ¼ 0.002

IS14–IS10 P < 0.001

IS14–IS11 P ¼ 0.960

Pielou’s evenness 3 F2,41 ¼ 21.11

P ¼ 0.006

IS6–IS12 P ¼ 0.001

IS8–IS12 P < 0.001

IS8–IS6 P ¼ 0.018

F2,58 ¼ 1.99

P ¼ 0.148

NA F2,41 ¼ 3.23

P ¼ 0.062

NA

Shannon diversity 3 F2,67 ¼ 46.15

P < 0.001

IS6–IS12 P < 0.001

IS8–IS12 P < 0.001

IS8–IS6 P < 0.001

F2,58 ¼ 31.77

P < 0.001

IS3–IS1 P < 0.001

IS8–IS1 P ¼ 0.628

IS8–IS3 P < 0.001

F2,41 ¼ 1.59

P ¼ 0.216

NA

Median CSI value 4 F2,67 ¼ 10.89

P < 0.001

IS6–IS12 P ¼ 0.001

IS8–IS12 P < 0.001

IS8–IS6 P ¼ 0.781

F2,58 ¼ 0.33

P ¼0.724

NA F2,41 ¼ 1.64

P ¼ 0.206

NA

CSI: High profile 5 F2,67 ¼ 19.11

P < 0.001

IS6–IS12 P ¼ 0.702

IS8–IS12 P < 0.001

IS8–IS6 P < 0.001

F2,58 ¼ 99.48

P < 0.001

IS3–IS1 P < 0.001

IS8–IS1 P < 0.001

IS8–IS3 P < 0.001

F2,41 ¼ 0.52

P ¼ 0.596

NA

CSI: Low profile 5 F2,67 ¼ 14.68

P < 0.001

IS6–IS12 P ¼ 0.943

IS8–IS12 P < 0.001

IS8–IS6 P < 0.001

F2,58 ¼ 33.43

P < 0.001

IS3–IS1 P < 0.001

IS8–IS1 P ¼ 0.004

IS8–IS3 P ¼ 0.823

F2,41 ¼ 0.96

P ¼ 0.393

NA

CSI: Motile 5 F2,67 ¼ 2.50

P ¼ 0.090

NA F2,58 ¼ 8.56

P < 0.001

IS3–IS1 P ¼ 0.068

IS8–IS1 P < 0.001

IS8–IS3 P < 0.001

F2,41 ¼ 1.54

P ¼ 0.226

NA



the stream benthos (Figure 6B), with the opposite trend occurring

for motile diatoms. The composition of diatom guilds in the guts of

E. minor (Figure 6F) mirrored the availability of resources in the

stream benthos (Figure 6C) and thus the lack of any effects on feed-

ing selectivity (Figure 6I).

Discussion

This study compared the relative abundance of diatom species in the

guts of invertebrate consumers with their relative abundance in the

benthos of geothermally heated streams to investigate feeding select-

ivity at different temperatures in a natural setting. Multiple aspects

of feeding selectivity were considered, with results suggesting that

different invertebrate species exhibit contrasting changes to their

feeding selectivity in different thermal regimes. The use of the

Hengill geothermal system facilitated ecological validity in natural

conditions, but these results would now benefit from additional ex-

periments and research on other naturally heated systems to achieve

increased control, replication, and geographic coverage.

The scraping grazer R. balthica fed more selectively in warmer

streams, as shown by a decline in gut content diversity (Figure 3A–

C) and an increase in the median value of its CSI distribution

(Figure 4D). This suggests a shift towards a more specialist diet at

warmer temperatures, in agreement with the first hypothesis.

Similar effects have been shown for brown trout in the same study

system, who select for more energetically valuable prey at higher

temperatures (O’Gorman et al. 2016) and in latitudinal shifts in the

dominance of omnivorous and herbivorous fish due to the higher

nutrient quality of plant material in warmer waters (Behrens and

Lafferty 2007). Specifically, R. balthica exhibited a greater prefer-

ence for high profile over low profile diatoms in the warmest stream

studied here (Figure 5A–B), supporting the second hypothesis. These

patterns occurred despite a similar proportional representation of its

most selectively consumed resource in each stream, suggesting that

the snails actively switched their feeding to the more prevalent high

profile diatom guild (Figure 6A). Benthic diatoms can exhibit both

species-specific depth zonation (Cantonati et al. 2009) and form

dense assemblages of varying degrees of heterospecificity in response

to environmental parameters such as salinity and nutrient availabil-

ity (Snoeijs and Murasi 2004; Hausler et al. 2014). Similarly, the

warmest stream here was dominated by dense patches of high profile

diatoms and so it may have been energetically more favorable for R.

balthica to feed on those, rather than seeking out its preferred low

profile resource. Indeed, previous laboratory studies have shown

that R. balthica feeds unselectively on whatever resources are widely

available to it (Brendelberger 1997).

Simulium aureum showed relatively little change in overall feed-

ing strategy in different streams (Figure 4E–H), despite indications

Figure 4. Feeding selectivity of invertebrate consumers for diatom species. Chesson Selectivity Index (CSI) metrics are shown for (A–D) Radix balthica, (E–H)

Simulium aureum, and (I–L) Eukiefferiella minor. The first three columns display CSI distributions for consumers in different streams; gray lines represent prob-

ability density functions for each individual consumer’s diet, black lines represent a probability density function of all individuals’ diets combined. The last col-

umn displays boxplots of the median CSI value for each consumer in each stream; boxes represent the median 6 interquartile range; whiskers represent the 5–

95% range; single points represent outliers. Bars not sharing a common letter (a, b, or c) were significantly different from each other (Tukey test: P< 0.05), while

“ns” indicates no significant difference between streams.



of elevated diversity of diatom species in the diet in the

intermediate-temperature stream (Figure 3D–F). This is in contrast

to the first hypothesis, indicating that S. aureum is quite a generalist

feeder in all the studied streams. Analyses of diatom guilds, how-

ever, revealed a shift in preference from high profile to motile dia-

toms in the warmer stream (Figure 5E–H), offering support for the

second hypothesis. The lack of agreement between the environmen-

tal composition, gut contents, and CSI values for S. aureum

(Figure 6) seems to suggest active selection by the consumer, in con-

trast with previous studies indicating that gut contents of blackfly

larvae typically reflect the composition of their environment

(Wotton 1977; Wallace and Merrit 1980; Thompson 1987). The

mechanism underpinning this contradictory finding, however, may

lie in the feeding mode employed by the blackfly larvae. The switch

from feeding on sessile high profile to motile diatoms suggests a shift

from active collector gathering to filter feeding behavior. Indeed,

previous studies suggest that other Simulium species have the cap-

ability to feed by both collector gathering and filter feeding (Burton

1973; Walsh 1985; Alder and McCreadie 1997). The latter may be a

more energetically efficient feeding strategy in warmer environments

because it is a more passive mode of capturing prey, thus expending

less energy through movement and contributing to Simuliidae hav-

ing one of the highest growth conversion efficiencies among fresh-

water invertebrates (Cummins and Klug 1979).

There was little evidence for altered feeding strategy in the larvae

of the collector gatherer E. minor in the studied streams, in contrast

to the first hypothesis. The increased species richness of diatoms in

the guts (Figure 3G) suggests that E. minor may be feeding on a

broader selection of diatom species in the warmer streams, but there

were no concurrent changes in evenness or diversity (Figure 3H–I),

and the distribution of CSI values suggested a highly generalist diet

(Figure 4I–L). Indeed, many other chironomid larvae are shown to

exhibit generalist feeding behaviour (Berg 1995; Henriques-Oliveira

et al. 2003; Butakka et al. 2016). There was also no evidence to sug-

gest that E. minor changed its preference for any of the diatom

guilds (Figure 5G–I), in contrast to the second hypothesis. Further,

the relative abundance of diatom guilds in the environment closely

mirrored the relative abundance in the gut contents, suggesting that

Figure 5. Preference of invertebrate consumers for diatom guilds. Box plots display Chesson Selectivity Index (CSI) values of (A–C) Radix balthica, (D–F)

Simulium aureum, and (G–I) Eukiefferiella minor for high profile, low profile, and motile diatoms in different streams. Boxes represent the median 6 interquartile

range; whiskers represent the 5–95% range; single points represent outliers. Bars not sharing a common letter (a, b, or c) were significantly different from each

other (Tukey test: P<0.05), while “ns” indicates no significant difference between streams.



this species exhibits very little selectivity in its diet (Figure 6). Given

the ability of E. minor to survive in a much wider temperature range

than that covered by this study (Hannesdottir et al. 2012), it is pos-

sible that its feeding strategy is altered at higher or lower tempera-

tures than in the streams examined here. Alternatively, E. minor

might be altering its feeding strategy by mechanisms other than se-

lection for different diatom species or guilds. Variables such as for-

aging intensity, size-selection, ingestion rate, and egestion rate are

known to vary with temperature in other invertebrate consumers

(Hylleberg 1975; Kingsley-Smith et al. 2003; Yee and Murray

2004), and are likely to play an important role in this stream system

as well. For example, R. balthica has been shown to have higher

overall grazing rates in warmer streams at Hengill (O’Gorman et al.

2012). It is important to note, however, that the number of diatom

species identified in the diet of E. minor was below the asymptote of

the yield-effort curve for each stream. Thus, interpretation of the

dietary analyses for E. minor should be treated with caution due to

slight under-sampling.

Feeding efficiency can be increased by either targeting resources

that require less effort to assimilate, or by targeting resources of

higher nutritional value. Both of these options are possible explan-

ations for the differences in feeding selectivity observed in R. balth-

ica and S. aureum here. The observed shifts in the diatom guilds that

were targeted may reflect a switch in preference for diatoms that

were easier to acquire at higher temperatures (i.e., high profile dia-

toms as more prominent and easily grazed material for R. balthica

than low profile diatoms; filter feeding as a less energetically

expensive feeding mechanism for S. aureum than collector gather-

ing). However, diatoms are also known to have considerable inter-

specific variation in their cellular concentrations of carbon,

nitrogen, and other nutrients (Moal et al. 1987; Menden-Deuer and

Lessard 2000), and epithemoids such as Rhopalodia gibba

(Ehrenberg) Muller, 1895, are known to fix atmospheric nitrogen

via cyanobacterial endosymbionts (Prechtl et al. 2004). Further,

both the ratios of cellular nutrients within individual diatom species

and the rates of nitrogen fixation by R. gibba are known to change

with temperature (Montagnes and Franklin 2001; Marcarelli and

Wurtsbaugh 2006). It may be that the observed changes in feeding

selectivity are due to consumers varying their preferences for indi-

vidual species based on changing nutritional values of different dia-

tom species with temperature. Further, it is important to note that

these two potential mechanisms are not mutually exclusive, and

may be working in combination or as a trade-off.

We also cannot definitively say whether a more selective diet is

due to direct effects of temperature on the target organism or indirect

effects via the predators, competitors, and resources that it interacts

with. There is increasing top-down control by the brown trout, Salmo

trutta Linnaeus, 1758, on each of the three invertebrates studied here

as stream temperature increases (O’Gorman et al. 2012, 2016). Thus,

changes in the feeding behavior of invertebrates may be an indirect

consequence of altered habitat use as a predator avoidance mechan-

ism (Werner and Peacor 2003). Similarly, resource production has

been shown to increase with stream temperature in the Hengill system

(O’Gorman et al. 2012). This raises the possibility that the standing

Figure 6. Key drivers of feeding preferences for different diatom guilds. Stacked barplots display relative abundances of diatom guilds (A–C) in the environment

and (D–F) in the guts of invertebrate consumers. Chesson Selectivity Index values in (G–I) are the median values shown in Figure 5.



stock of certain diatoms may be low, but rapid replenishment after

consumption may make them more readily available to invertebrates.

Such uncertainties are part of a necessary trade-off in studies that uti-

lize natural gradients, which forsake the control of laboratory experi-

ments for the realism of natural ecosystems. A tightly controlled

laboratory experiment could exclude all predators and competitors of

the target organism and standardize the biofilm available for con-

sumption to give greater mechanistic insight, however, the conditions

would be so unrealistic as to cast doubt on the relevance of the find-

ings for the real world. In contrast, the changes in feeding behavior

observed in the current study will not just be a consequence of the aut-

ecological response of the target organism, but also the synecological

response of the entire community of which it is a part. This complex-

ity is an inherent part of the ecological changes we will see as a result

of planetary warming in the coming decades.

In conclusion, this study demonstrates that invertebrate con-

sumers can alter their feeding selectivity in streams of different tem-

perature, in species-specific ways. Developing a more specialist

feeding strategy by targeting the most ubiquitous resource items and

altering feeding mode to preferentially consume more optimal re-

sources are both potential mechanisms for the changes observed

here. Environmental warming exerts selection pressures on organ-

isms, including the need to increase feeding efficiency to mitigate the

disproportionate increase in metabolic demand relative to ingestion

rate (Rall et al. 2010). The changes in feeding selectivity observed

along the stream temperature gradient here suggest that species may

express different behavioural adaptations to meet the higher ener-

getic demands of a warmer environment. The subsequent impacts

on the abundance and composition of the diatom community could

lead to altered nutrient cycling (e.g., through changes in nitrogen

fixation) and thus cascading effects throughout the food web (Furey

et al. 2012, 2014). Caution should be taken before applying the re-

sults presented here to other systems, as the lack of experimental

control or spatial replication precludes mechanistic insights or gen-

eral conclusions. Further consideration of individual-based changes

in feeding strategy and their effects on community dynamics are

thus essential to increase our understanding of how future environ-

mental warming will alter freshwater ecosystems.

Acknowledgements

The authors would like to thank Haoran Wang and Georgina Adams for their

advice on diatom species identification, and Ellie Bowler and Peter Gleeson

for assistance with figure preparation.

Funding

This work was funded by NERC (NE/L011840/1, NE/M020843/1) and

Imperial College London’s MRes in Ecology, Evolution & Conservation.

References

Adams GL, Pichler DE, Cox EJ, O’Gorman EJ, Seeney A et al., 2013. Diatoms

can be an important exception to temperature-size rules at species and com-

munity levels of organization. Glob Change Biol 19:3540–3552.

Alder PH, McCreadie JW, 1997. Insect life: the hidden ecology of black flies:

sibling species and ecological scale. Am Entomol 43:153–162.

Arnason B, Theodorsson P, Bjornsson S, Saemundsson K, 1969. Hengill, a

high temperature thermal area in Iceland. Bull Volcanol 33:245–259.

Arthington AH, Naiman RJ, McClain ME, Nilsson C, 2010. Preserving the

biodiversity and ecological services of rivers: new challenges and research

opportunities. Freshwater Biol 55:1–16.

Beckerman AP, Petchey OL, Warren PH, 2006. Foraging biology predicts

food web complexity. PNAS 103:13745–13749.

Behrens MD, Lafferty KD, 2007. Temperature and diet effects on omnivorous

fish performance: implications for the latitudinal diversity gradient in herb-

ivorous fishes. Can J Fish Aquat Sci 64:867–873.

Berg MB, 1995. Larval food and feeding behaviour. In: Armitage PD,

Cranston PS, Pinder LCV, editors. The Chironomidae. Dordrecht: Springer.

Berumen ML, Pratchett MS, 2008. Trade-offs associated with dietary special-

ization in corallivorous butterflyfishes (Chaetodontidae: Chaetodon). Behav

Ecol Sociobiol 62:989–994.

Binzer A, Guill C, Rall BC, Brose U, 2015. Interactive effects of warming, eu-

trophication and size-structure: impacts on biodiversity and food-web struc-

ture. Glob Change Biol 22:220–227.

Blackwood JS, Schausberger P, Croft BA, 2001. Prey-stage preference in gener-

alist and specialist phytoseiid mites (Acari: Phytoseiidae) when offered

Tetranychus urticae (Acari: Tetranychidae) eggs and larvae. Environ

Entomol 30:1103–1111.

Brendelberger H, 1997. Contrasting feeding strategies of two freshwater

gastropods Radix peregra (Lymnaeidae) and Bithynia tentaculata

(Bithyniidae). Arch Hydrobiol 140:1–21.

Burton GJ, 1973. Feeding of Simulium hargreavesi Gibbins larvae on

Oedegonium algal filaments in Ghana. J Med Entomol 10:101–106.

Butakka CMM, Ragonha FH, Train S, Pinha GD, Takeda AM, 2016.

Chironomidae feeding habits in different habitats from a Neotropical flood-

plain: exploring patterns in aquatic food webs. Braz J Biol 76:117–125.

Cantonati M, Scola S, Angeli N, Guella G, Frassanito R, 2009. Environmental

controls of epilithic diatom depth-distribution in an oligotrophic lake char-

acterized by marked water-level fluctuations. Eur J Phycol 44:15–29.

Castillo G, Cruz LL, Tapia-Lopez R, Olmedo-Vicente E, Carmona D et al.,

2014. Selection mosaic exerted by specialist and generalist herbivores on

chemical and physical defense of Datura stramonium. PLoS ONE 9:

e102478.,

Chen IC, Hill JK, Ohlemuller R, Roy DB, Thomas CD, 2011. Rapid range

shifts of species associated with high levels of climate warming. Science 333:

1024–1026.

Chesson J, 1983. The estimation and analysis of preference and its relationship

to foraging models. Ecology 64:1297–1304.

Cummins KW, Klug MJ, 1979. Feeding ecology of stream invertebrates. Annu

Rev Ecol Syst 10:147–172.

Dodd JA, Dick JTA, Alexander ME, Macneil C, Dunn A et al., 2014.

Predicting the ecological impacts of a new freshwater invader: functional re-

sponses and prey selectivity of the “killer shrimp”, Dikerogammarus vil-

losus, compared to the native Gammarus pulex. Freshwater Biol 59:

337–352.

Drenner RW, 1982. Selective impact of filter-feeding gizzard shad on zoo-

plankton community structure. Limnol Oceanogr 27:965–968.

Drenner RW, Mummert JR, Denoyelles F, Kettle D, 1984. Selective particle in-

gestion by a filter-feeding fish and its impact on phytoplankton community

structure. Limnol Oceanogr 29:941–948.

Evans KM, Chepurnov VA, Sluiman HJ, Thomas SJ, Spears BM et al., 2009.

Highly differentiated populations of the freshwater diatom Sellaphora capi-

tata suggest limited dispersal and opportunities for allopatric speciation.

Protist 160:386–396.

Finn DS, Theobald DM, Black WC, Poff NL, 2006. Spatial population genetic

structure and limited dispersal in a rocky mountain alpine stream insect.

Mol Ecol 15:3553–3566.

Fore LS, Grafe C, 2002. Using diatoms to assess the biological condition of

large rivers in Idaho (U.S.A.). Freshwater Biol 47:2015–2037.

Friberg N, Dybkjær JB, Olafsson JS, Gıslason GM, Larsen SE et al., 2009.

Relationships between structure and function in streams contrasting in tem-

perature. Freshwater Biol 54:2051–2068.

Furey PC, Power ME, Lowe RL, Campbell-Craven A, 2012. Midges,

Cladophora and epiphytes: shifting interactions through succession. Freshw

Sci 31:93–107.

Furey PC, Kupferberg SJ, Lind AJ, 2014. The perils of unpalatable periphyton:

Didymosphenia and other mucilaginous stalked diatoms as food for tad-

poles. Diatom Res 29:267–280.



Gudmundsdottir R, Gıslason GM, Palsson S, Olafsson JS, Schomacker A

et al., 2011. Effects of temperature regime on primary producers in

Icelandic geothermal streams. Aquat Bot 95:278–286.

Halaj J, Wise DH, 2001. Terrestrial trophic cascades: how much do they

trickle? Am Nat 157:262–281.

Hannesdottir ER, Gıslason GM, Olafsson JS, 2012. Life cycles of

Eukiefferiella claripennis (Lundbeck 1898) and Eukiefferiella minor

(Edwards 1929) (Diptera: chironomidae) in spring-fed streams of different

temperatures with reference to climate change. Proceedings of the 18th

International Symposium on Chironomidae Fauna Norvegica 31:35–46.

Hausler S, Weber M, de Beer D, Ionescu D, 2014. Spatial distribution of dia-

tom and cyanobacterial mats in the Dead Sea is determined by response to

rapid salinity fluctuations. Extremophiles 18:1085–1094.

Hawlena D, Schmitz OJ, 2010. Herbivore physiological response to predation risk

and implications for ecosystem nutrient dynamics. PNAS 107:15503–15507.

Henriques-Oliveira AL, Nessimian JL, Dorville LFM, 2003. Feeding habits of

Chironomid larvae (Insecta: diptera) from a stream in the Floresta da

Tijuca, Rio de Janeiro, Brazil. Braz J Biol 63:269–281.

Hogg ID, Williams DD, 1996. Response of stream invertebrates to a global

warming thermal regime: an ecosystem level manipulation. Ecology 77:

395–407.

Hylleberg J, 1975. Effect of salinity and temperature on egestion in mud

snails (Gastropoda: hydrobiidae): study on niche overlap. Oecologia 21:

279–289.

Ings TC, Montoya JM, Bascompte J, Bluthgen N, Brown L et al., 2009.

Ecological networks: beyond food webs. J Anim Ecol 78:253–269.

IPCC, 2014. Climate Change 2014: Synthesis Report. Contribution of

Working Groups I, II and III to the Fifth Assessment Report of the

Intergovernmental Panel on Climate Change. IPCC, Geneva, Switzerland.

Jonsen ID, Fahrig L, 1997. Response of generalist and specialist insect herbi-

vores to landscape spatial structure. Landscape Ecol 12: 185–197.

Kingsley-Smith PR, Richardson CA, Seed R, 2003. Stereotypic and

size-selective predation in Polinices pulchellus (Gastropoda: Naticidae)

Risso 1826. J Exp Mar Biol Ecol 295:173–190.

Krammer K, Lange-Bertalot H, 1986–1991. Sußwasserflora Von

Mitteleuropa, vol. 2/1–2/4. Stuttgart: Gustav Fischer.

Kundzewicz ZW, Mata LJ, Arnell NW, Doll P, Jimenez P et al., 2008. The im-

plications of projected climate change for freshwater resources and their

management. Hydrolog Sci J 53:37–41.

Lankau RA, 2007. Specialist and generalist herbivores exert opposing selec-

tion on a chemical defense. New Phytol 175:176–184.

Ledger ME, Harris RML, Milner AM, Armitage PD, 2006. Disturbance, bio-

logical legacies and community development in stream mesocosms.

Oecologia 148:682–691.

Lee KP, Cory JS, Wilson K, Raubenheimer D, Simpson SJ, 2006. Flexible diet

choice offsets protein costs of pathogen resistance in a caterpillar. Proc Roy

Soc B 273:823–829.

Lemoine NP, Drews WA, Burkepile DE, Parker JD, 2013. Increased tempera-

ture alters feeding behavior of a generalist herbivore. Oikos 122:

1669–1678.

Marcarelli AM, Wurtsbaugh WA, 2006. Temperature and nutrient supply

interact to control nitrogen fixation in oligotrophic streams: an experimen-

tal examination. Limnol Oceanogr 51:2278–2289.

Menden-Deuer S, Lessard EJ, 2000. Carbon to volume relationships for dinofla-

gellates, diatoms, and other protist plankton. Limnol Oceanogr 45:569–579.

Moal J, Martin-Jezequel V, Harris RP, Samain J, Poulet SA, 1987.

Interspecific and intraspecific variability of the chemical composition of

marine phytoplankton. Oceanol Acta 10:339–346.

Montagnes DJS, Franklin DJ, 2001. Effect of temperature on diatom volume,

growth rate, and carbon and nitrogen content: reconsidering some para-

digms. Limnol Oceanogr 46:2008–2018.

O’Gorman EJ, Pichler DE, Adams G, Benstead JP, Cohen H et al., 2012.

Impacts of warming on the structure and functioning of aquatic commun-

ities: individual- to ecosystem-level responses. Adv Ecol Res 47:81–176.

O’Gorman EJ, Benstead JP, Cross WF, Friberg N, Hood JM et al., 2014.

Climate change and geothermal ecosystems: natural laboratories, sentinel

systems, and future refugia. Glob Change Biol 20:3291–3299.

O’Gorman EJ, Olafsson OP, Demars BOL, Friberg N, Gudbergsson G et al.,

2016. Temperature effects on fish production across a natural thermal gradi-

ent. Glob Change Biol 22:3206–3220.

O’Gorman EJ, Zhao L, Pichler DE, Adams G, Friberg N et al., 2017.

Unexpected changes in community size structure in a natural warming ex-

periment. Nat Climate Change 7:659–663.

Ohlberger J, 2013. Climate warming and ectotherm body size: from individual

physiology to community ecology. Funct Ecol 27:991–1001.

Pace ML, Cole JJ, Carpenter SR, Kitchell JF, 1999. Trophic cascades revealed

in diverse ecosystems. Trends Ecol Evol 14:483–488.

Parmesan C, 2006. Ecological and evolutionary responses to recent climate

change. Annu Rev Ecol Syst 37:637–669.

Passy SI, 2007. Diatom ecological guilds display distinct and predictable

behavior along nutrient and disturbance gradients in running waters. Aquat

Bot 86:171–178.

Petchey OL, McPhearson PT, Casey TM, Morin PJ, 1999. Environmental

warming alters food-web structure and ecosystem function. Nature 402:

69–72.

Petchey OL, Beckerman AP, Riede JO, Warren PH, 2008. Size, foraging, and

food web structure. PNAS 105:4191–4196.

Petchey OL, Brose U, Rall BC, 2010. Predicting the effects of temperature on

food web connectance. Philos Roy Soc B 365:2081–2091.

Polis GA, Strong DR, May N, 1996. Food web complexity and community dy-

namics. Am Nat 147: 813–846.

Prechtl J, Kneip C, Lockhart P, Wenderoth K, Maier U, 2004. Intracellular

spheroid bodies of Rhopalodia gibba have nitrogen-fixing apparatus of

cyanobacterial origin. Mol Biol Evol 21:1477–1481.

R Core Team, 2017. R: A Language and Environment for Statistical

Computing. Vienna: R Foundation for Statistical Computing. https://www.

R–project.org/.

Rall BC, Vucic-Pestic O, Ehnes RB, Emmerson M, Brose U, 2010.

Temperature, predator–prey interaction strength and population stability.

Glob Change Biol 16:2145–2157.

Rimet F, Bouchez A, 2012. Life-forms, cell-sizes and ecological guilds of

diatoms in European Rivers. Knowledge Manage Aquatic Ecosyst 406:

1–14.

Root TL, Price JT, Hall KR, Schneider SR, Rosenzweig C et al., 2003.

Fingerprints of global warming on wild animals and plants. Nature 421:

57–60.

Schmitz OJ, Hamback PA, Beckerman AP, 2000. Trophic cascades in terres-

trial systems: a review of the effects of carnivore removals on plants. Am

Nat 155:141–153.

Shurin J, Borer E, Seabloom EW, Anderson K, Blanchette CA et al., 2002. A

cross-ecosystem comparison of the strength of trophic cascades. Ecol Lett 5:

785–791.

Shurin JB, Clasen JL, Greig HS, Kratina P, Thompson PL, 2012. Warming

shifts top-down and bottom-up control of pond food web structure and

function. Philos Roy Soc B 367:3008–3017.

Snoeijs P, Murasi LW, 2004. Symbiosis between diatoms and cyanobacterial

colonies. Vie Milieu 54:163–170.

Sturt MM, Jansen MAK, Harrison SSC, 2011. Invertebrate grazing and ripar-

ian shade as controllers of nuisance algae in a eutrophic river. Freshwater

Biol 56:2580–2593.

Thompson BH, 1987. The use of algae as food by larval Simuliidae (Diptera)

of Newfoundland streams I. Feeding selectivity. Arch Hydrobiol 76:

425–442.

Urban MC, Zarnetske PL, Skelly DK, 2013. Moving forward: dispersal and

species interactions determine biotic responses to climate change. Ann NY

Acad Sci 1297:44–60.

Wallace JB, Merrit RW, 1980. Filter-feeding ecology of aquatic insects. Annu

Rev Entomol 25:103–132.

Walsh JF, 1985. The feeding behaviour of Simulium larvae, and the develop-

ment, testing and monitoring of the use of larvicides, with special reference

to the control of Simulium damnosum Theobald s.l. (Diptera: Simuliidae): a

review. Bull Entomol Res 75:549–594.

Walther G, Post E, Convey P, Menzel A, Parmesan C et al., 2002. Ecological

responses to recent climate change. Nature 416:389–395.



Werner EE, Peacor SD, 2003. A review of trait-mediated indirect interactions

in ecological communities. Ecology 84:1083–1100.

Winder M, Schindler DE, 2004. Climate change uncouples trophic inter-

actions in an aquatic ecosystem. Ecology 85:2100–2106.

Wotton RS, 1977. The size of particles ingested by moorland stream blackfly

larvae (Simuliidae). Oikos 29:332–335.

Woodward G, Dybkjær JB, Olafsson JS, Gıslason GM, Hannesdottir ER et al.,

2010a. Sentinel systems on the razor’s edge: effects of warming on Arctic

geothermal stream ecosystems. Glob Change Biol 16:1979–1991.

Woodward G, Blanchard J, Lauridsen RB, Edwards FK, Jones JI et al., 2010b.

Individual-based food webs: species identity, body size and sampling effects.

Adv Ecol Res 43:211–266.

Yee EH, Murray SN, 2004. Effects of temperature on activity, food consump-

tion rates, and gut passage times of seaweed-eating Tegule species

(Trochidae) from California. Mar Biol 145:895–903.

Zhang P, Sun J, Chen J, Wei J, Zhao W et al., 2013. Effect of feeding selectivity

on the transfer of methylmercury through experimental marine food chains.

Mar Environ Res 89:39–44.


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ReportsEcology, 96(3), 2015, pp. 603–610� 2015 by the Ecological Society of America

Does N2 fixation amplify the temperature dependenceof ecosystem metabolism?

JILL R. WELTER,1,5 JONATHAN P. BENSTEAD,2 WYATT F. CROSS,3 JAMES M. HOOD,3 ALEXANDER D. HURYN,2

PHILIP W. JOHNSON,4 AND TANNER J. WILLIAMSON3

1Department of Biology, St. Catherine University, Saint Paul, Minnesota 55105 USA2Department of Biological Sciences, University of Alabama, Tuscaloosa, Alabama 35487 USA

3Department of Ecology, Montana State University, Bozeman, Montana 59717 USA4Department of Civil, Construction and Environmental Engineering, University of Alabama, Tuscaloosa, Alabama 35487 USA

Abstract. Variation in resource supply can cause variation in temperature dependences ofmetabolic processes (e.g., photosynthesis and respiration). Understanding such divergence isparticularly important when using metabolic theory to predict ecosystem responses to climatewarming. Few studies, however, have assessed the effect of temperature–resource interactionson metabolic processes, particularly in cases where the supply of limiting resources exhibitstemperature dependence. We investigated the responses of biomass accrual, gross primaryproduction (GPP), community respiration (CR), and N2 fixation to warming during biofilmdevelopment in a streamside channel experiment. Areal rates of GPP, CR, biomass accrual,and N2 fixation scaled positively with temperature, showing a 32- to 71-fold range across thetemperature gradient (;78–248C). Areal N2-fixation rates exhibited apparent activationenergies (1.5–2.0 eV; 1 eV ¼ ;1.6 3 10�19 J) approximating the activation energy of thenitrogenase reaction. In contrast, mean apparent activation energies for areal rates of GPP(2.1–2.2 eV) and CR (1.6–1.9 eV) were 6.5- and 2.7-fold higher than estimates based onmetabolic theory predictions (i.e., 0.32 and 0.65 eV, respectively) and did not significantlydiffer from the apparent activation energy observed for N2 fixation. Mass-specific activationenergies for N2 fixation (1.4–1.6 eV), GPP (0.3–0.5 eV), and CR (no observed temperaturerelationship) were near or lower than theoretical predictions. We attribute the divergence ofareal activation energies from those predicted by metabolic theory to increases in N2 fixationwith temperature, leading to amplified temperature dependences of biomass accrual and arealrates of GPP and R. Such interactions between temperature dependences must beincorporated into metabolic models to improve predictions of ecosystem responses to climatechange.

Key words: activation energy; amplification; Arrhenius; biofilm; climate change; Hengladalsa River,Iceland; metabolic theory; nitrogen fixation; nutrient cycling; resource supply; temperature.

INTRODUCTION

Since 1880, global mean surface temperatures have

risen by 0.858C, and most models predict an increase of

;48C by 2100 (IPCC 2013). Elevated temperatures have

altered the species composition and biogeochemistry of

Earth’s ecosystems (Grimm et al. 2013), with largely

unknown consequences. One of the greatest challenges

for this century is to understand and predict how

warming will affect the physical, chemical, and biolog-

ical processes governing ecosystem fluxes of carbon and

essential nutrients.

The metabolic theory of ecology (MTE; Brown et al.

2004, Sibly et al. 2012) offers one approach for

developing predictions about how temperature influences

ecosystem processes. The MTE argues that the relation-

ship between ecosystem metabolism and temperature can

be predicted from the temperature dependences of

subcellular reactions, such as photosynthesis and cellular

respiration. The rate of most subcellular reactions

increases exponentially with temperature following the

Van’t Hoff-Arrhenius relationship e�E/(kT), where k is the

Boltzmann constant (8.61 3 10�5 eV/K; 1 eV ¼ ;1.6 3

10�19 J), T is temperature (K), and E is the activation

Manuscript received 30 August 2014; accepted 4 November2014. Corresponding Editor: S. Findlay.

5 E-mail: [email protected]

603

energy (AE; in eV), which quantifies the change in

reaction rate with temperature (Boltzmann 1872, Ar-rhenius 1889). Over a biologically relevant range of

temperatures (e.g., 0–308C), the AEs for respiration andgross primary production for both cells and ecosystems

are predicted to be ;0.65 and ;0.32 eV, respectively(Gillooly et al. 2001, Allen et al. 2005). Research in avariety of ecosystems has generally supported this

prediction, suggesting that the MTE may help forecastecosystem responses to warming (Enquist et al. 2003,

Demars et al. 2011, Perkins et al. 2012, Yvon-Durocher etal. 2012). However, broad application of the MTE is

currently hindered by a lack of information about how itspredictions are influenced by resource supply (Anderson-

Teixeira and Vitousek 2012).Since its conception, there has been considerable

effort to incorporate the effects of resource supply intothe MTE (Brown et al. 2004, Sterner 2004, Kaspari

2012). Such efforts have been motivated by a growingliterature demonstrating both independent and interact-

ing effects of temperature and resource availability onecosystem processes (Pomeroy and Wiebe 2001, Lopez-

Urrutia and Moran 2007, Davidson et al. 2012). Indeed,recent models that explicitly incorporate these factors

have refined predictions about how ecosystems respondto global change (e.g., Davidson et al. 2012). Neverthe-less, few models incorporate the dynamics of tempera-

ture–resource availability relationships.

Rates of many physiological and geochemicalprocesses that control resource supply (e.g., enzymeactivity, weathering) increase with temperature (Rennie

and Kemp 1986, Bland and Rolls 1998). Thus, warmingcan increase resource supply, leading to ‘‘apparent’’ AEs

that diverge from canonical (i.e., intrinsic) predictions(Anderson-Teixeira and Vitousek 2012) that are based

on temperature alone. Nitrogen (N2) fixation is oneprocess of particular interest, as it provides an addi-

tional source of N to ecosystems (Howarth 1988,Marcarelli et al. 2008, Scott et al. 2009) and has a

strong biphasic temperature dependence at the enzy-matic level (AE of nitrogenase ¼ 2.18 eV below 228C,

0.65 eV above 228C; Ceuterick et al. 1978). As such,increases in N2-fixation rates with temperature can

increase the availability of a limiting resource (i.e., N),potentially leading to temperature dependences of

whole-community primary production and respirationthat are higher than those predicted by the MTE(Anderson-Teixeira et al. 2008). To test this prediction,

we experimentally manipulated temperature understrongly N-limited conditions and quantified responses

of N2 fixation, primary production, and communityrespiration during stream biofilm development.

METHODS

Temperature manipulation and experimental channels

We used experimental stream channels to examinethe effect of temperature on biofilms. Our infrastruc-

ture was installed in a grassland watershed draining the

Hengill volcanic area, 30 km east of Reykjavık, Iceland

(64803 02300 N, 21817 00100 W). Hengill is an active

geothermal landscape with streams and hot springs

that vary in temperature (annual mean temperature

range¼;6–1008C) due to localized warming (Arnason

et al. 1969). Our experimental temperature gradient

was achieved using three gravity-fed heat exchangers

that were deployed in geothermal pools. These devices

heated stream water from an unnamed tributary of

Hengladalsa River (mean temperature ¼ 7.58C) to

;108C and ;208C above ambient (see Plate 1 and the

Appendix: Figs. A1 and A2; O’Gorman et al. 2014).

Water from the two heat exchangers was then mixed

with unheated stream water to produce five water-

temperature treatments that were supplied to 15

experimental stream channels (mean 6 SD; 7.58 6

1.88, 11.28 6 1.88, 15.58 6 1.98, 19.08 6 1.88, 23.68 6

2.08 C; n¼ 3 channels per temperature and divided into

three blocks with the five temperatures randomized

within each block; Appendix: Table A1 and Fig. A3).

The bed of each channel was lined with ;110 25 3 25

mm basalt tiles (Deko Tile, Carson, California, USA)

that were leached in tap water for 18 d and boiled for 5

min prior to deployment on 20 May 2013. Channels

were colonized for 42 d before our first measurement

period. We did not prevent macroinvertebrates from

colonizing the channels, but very few invertebrates

were observed on tiles during the study.

Metabolism and biofilm mass accrual

We measured biofilm metabolism in 0.3-L recirculat-

ing chambers constructed from clear Plexiglas (Arkema,

Colombes, France; Appendix: Fig. A4). Biofilm metab-

olism, as change in dissolved oxygen (O2) concentration,

was measured simultaneously for all treatments within

each randomly chosen block at days 42 and 58.

Incubations were typically conducted between 10:00

and 16:00 during sunny conditions.

Each chamber measurement was based on four tiles

randomly selected from a single channel. Tiles were

sampled without replacement, placed in chambers filled

with sieved (250-lm) water from the respective treat-

ment, and incubated in a water bath at the appropriate

temperature. We measured net ecosystem production

(NEP) under ambient light conditions and community

respiration (CR) in the dark. The same tiles were used

for both measurements but chamber water was ex-

changed between measurements. O2 and chamber

temperatures were recorded at 1-min intervals (YSI

Pro-ODO, Yellow Springs, Ohio, USA). Incubations

were terminated after O2 changed by .1 mg/L or at 1.5

h (mean ¼ 1.1 h, range ¼ 0.3–1.7 h). Net ecosystem

production and community respiration (mg O2�m�2�h�1)were calculated as

ðNEPÞ or ðCRÞ ¼ DO2 3 V 3 S�1

where DO2 is the slope of the relationship between O2

concentration and time (mg O2�L�1�h�1), V is chamber

JILL R. WELTER ET AL.604 Ecology, Vol. 96, No. 3R

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volume (L), and S is the active surface area of the tiles

(m2). Gross primary production (GPP) was calculated as

GPP¼NEPþCR (Bott 2006). We corrected for water-

column metabolism by subtracting rates measured in

blank chambers without tiles.

Tiles were scrubbed with a toothbrush following

incubations and the resulting slurry was aggregated in

125 mL of water in amber bottles. A subsample was then

filtered onto a pre-ashed, Whatman GF/F filter (Sigma-

Aldrich, St. Louis, Missouri, USA), dried (558C, �72 h),

weighed and ashed at 5008C for 2 h and reweighed to

determine biomass as ash-free dry mass (AFDM).

Biomass accrual (mg AFDM�m�2�d�1) was calculated

as the mean channel AFDM divided by the number of

days incubated.

Nitrogen fixation

N2-fixation rates were measured using acetylene

reduction assays (Flett et al. 1976, Capone 1993) during

2-h midday incubations at 41 and 53 days post-

deployment, using the sampling design and chambers

described. Twenty mL of acetylene gas was injected

directly into each chamber and mixed vigorously for 5

min prior to incubation. Gas samples were collected

from each chamber at the beginning and end of the

incubation. All gas samples, including field standards,

were analyzed for ethylene concentration on an 8610 gas

chromatograph (SRI Instruments, Torrance, California,

USA) with a flame ionization detector (Hayesep T

column, 80/100 mesh; Restek Corporation, Bellefonte,

Pennsylvania, USA) within 48 h of collection. The rate

of ethylene production in each chamber was calculated

and a 3:1 N2 : ethylene conversion ratio (Capone 1993)

was used to estimate N2-fixation rates.

Activation energies and statistical analysis

AEs were estimated for areal and mass-specific rates

of GPP, CR, N2 fixation, and biomass accrual using the

Van’t Hoff-Arrhenius relationship. We used linear least-

squares regression to fit a relationship between ln-

transformed process rates and 1/kT (R Core Team

2013). The AE is the absolute value of the slope; 95%

confidence intervals were calculated with the confint

function in the R package stats (R Core Team 2013). We

tested for differences in AE among GPP, N2 fixation,

and CR, as well as between areal and mass-specific rates,

PLATE 1. (Top) Representative images ofalgal biomass in experimental stream channels47 days post-deployment. The experimentaltemperature gradient was achieved by heatingstream water from an unnamed tributary of theHengladalsa River, Iceland (mean temperature ¼7.58C) using gravity-fed heat exchangers de-ployed in geothermal pools. Values representmean temperature (6SD) in each treatment (n ¼3 channels per temperature, divided into threeblocks with the five temperatures randomizedwithin each block) over the course of theexperiment. (Bottom) Experimental stream chan-nel study site in the Hengill region of Iceland.Photo credits: top, T. J. Williamson; bottom,Jackie Goldschmidt.

March 2015 605NITROGEN FIXATION AND METABOLIC ECOLOGYR

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using a linear model that predicted flux rate using 1/kT

and the flux identity. A significant (a¼ 0.05) interaction

between 1/kT and the flux type indicated a significant

difference among slopes. The mean channel temperature

prior to the sampling day was used to calculate the AE

of biomass accrual, while mean chamber incubation

temperatures were used for the other flux measurements.

Incubation temperatures during GPP, CR, and N2-

fixation measurements were strongly related to mean

channel temperature prior to the sampling date (8Ci ¼4.04 þ 0.818Cc; R2 ¼ 0.92, P , 0.001); however,

incubation temperatures were slightly warmer because

incubations generally occurred near maximum daily

temperature (Appendix: Fig. A5).

To assess whether temperature or biomass best

predicted ecosystem flux rates, we first compared the

AEs of mass-specific and areal GPP and CR to

canonical expectations. Second, we used repeated-

measures mixed-effects models (lme function in the R

package nlme [Pinheiro et al. 2014]; fixed effects of

sampling day and either 1/kT or ln[biomass], the random

intercept was channel ID, the random slope was

sampling day) and compared the resulting AICc scores

(Burnham and Anderson 2002) to identify whether

temperature (1/kT ) or biomass (ln-transformed AFDM)

best predicted ln(areal GPP) and ln(CR). Tests for

multicollinearity indicated a strong correlation between

temperature and biomass (e.g., for areal GPP: R2¼ 0.79,

P , 0.001); thus, we used a model selection approach to

examine models containing only one of these terms.

RESULTS

Our temperature manipulations were effective and

relatively consistent throughout the experiment (Appen-

dix: Table A1 and Fig. A5). The daily ranges of

temperature were similar both among treatments (Ap-

pendix: Table A1) and to those observed in nearby

streams (W. F. Cross and J. P. Benstead, unpublished

data). Biofilm mass accrual was strongly and positively

related to temperature, varying on average ;18-fold

over the 178C range in mean temperature (Fig. 1a and

Table 1; see Plate 1). Areal rates of GPP, CR, and N2

FIG. 1. Temperature dependence of (a) biomass (originally measured in mg ash-free dry mass (AFDM)�m�2�d�1), (b) grossprimary production (originally measured in mg O2�m�2�h�1), (c) community respiration (originally measured in mg O2�m�2�h�1),and (d) N2 fixation (originally measured in mg N�m�2�h�1) plotted as the relationship between ln-transformed biomass or areal ratesand inverse temperature (1/kT ), where k is the Boltzmann constant (8.613 10�5 eV/K; 1 eV¼;1.63 10�19 J) and T is temperature(K). The estimated activation energy (in eV) and 95% confidence intervals (in parentheses) are displayed for each measurement andsampling day when the slope differed significantly from zero (a¼ 0.10). Lines were fit with least-squares regression.


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fixation were also strongly and positively related to

temperature. Areal rates of GPP varied on average 53-

fold across the treatments on both measurement dates,while areal rates of CR and N2 fixation varied on

average 32- and 71-fold, respectively. On both measure-

ment dates, apparent AEs for the different flux rates(i.e., areal GPP, CR, and N2 fixation) were statistically

indistinguishable (P . 0.2). Mean apparent AEs for

areal GPP and CR were 6.5- and 2.7-fold higher than

values predicted by the MTE on both measurement days(Fig. 1 and Table 1). In contrast, the AE of areal N2-

fixation rates, although more variable across measure-

ments, was similar to expectations (Fig. 1d and Table 1),

based on the AE of nitrogenase when isolated in thelaboratory (2.18 eV below 228C; Ceuterick et al. 1978).

In contrast to areal rates, the AEs of mass-specific

rates differed among flux types (P , 0.05). Mass-specific

GPP varied 3.8-fold across the thermal gradient andshowed a relatively weak positive relationship (P ¼0.065) with temperature (Fig. 2a and Table 1). The

apparent AE of mass-specific GPP approached canon-

ical expectations (i.e., 0.32 eV; Fig. 1a, Table 1) and wasmuch lower than that of areal GPP (both dates: P ,

0.001). Mass-specific CR rates were not related to

temperature (Fig. 2b) and strongly differed from thoseof areal CR (both dates: P , 0.001). Mass-specific N2-

fixation rates increased ;36-fold over the 178C range

and showed mean apparent AEs (i.e., 1.39 eV at day 41

and 1.64 eV at day 53) that were similar to AEs for areal

N2-fixation rates (both dates: P . 0.05). Models that

contained temperature, rather than biomass, best

predicted both areal GPP (temperature model AICc ¼38.9, biomass model AICc ¼ 41.8), and areal CR

(temperature model AICc ¼ 38.7, biomass model AICc

¼ 47.1); however, models predicting ecosystem flux ratesusing only biomass still performed exceptionally well

(Appendix: Table A2).

DISCUSSION

Our experiment revealed several patterns in the

relationships between temperature and the development

and metabolic activity of stream biofilms. Chief among

these was the frequent divergence of apparent areal AEsfrom their expected canonical values. In our study,

amplification of the apparent AEs for biomass accrual,

and areal GPP and CR, was associated with the

dominance of N2 fixers, a key functional group, whichdeveloped across the temperature gradient (.90% of

total biomass in all treatments was comprised of N2

fixers; Williamson 2014). This can be explained by thehigh canonical AE of N2 fixation compared with GPP

and CR, which results in substantive increases in N

supply and, therefore, metabolic activity associated with

reduced N limitation of GPP and biomass accrual alongthe temperature gradient. Although such amplification

has been described in terrestrial systems, typically in the

context of soil carbon decomposition (Davidson and

Janssens 2006, Yvon-Durocher et al. 2012) or forest

TABLE 1. Estimates of the intercept, slope, P value, and R2 from least-squares regression of the relationship between several ln-transformed measures (units) and 1/kT.

Measure and day Intercept Slope P R2

Areal rates

Biofilm mass accrual (mg AFDM�m�2�d�1)42 59.1 (5.91) �1.34 (0.15) ,0.001 0.8658 58.28 (3.36) �1.32 (0.08) ,0.001 0.95

Gross primary production (mg O2�m�2�h�1)42 88.68 (10.09) �2.11 (0.25) ,0.001 0.8758 91.26 (6.15) �2.15 (0.15) ,0.001 0.95

Respiration (mg O2�m�2�h�1)42 67.24 (6.39) �1.60 (0.16) ,0.001 0.9058 78.17 (9.44) �1.86 (0.24) ,0.001 0.85

N2 fixation (mg N�m�2�h�1)41 62.89 (8.52) �1.57 (0.21) ,0.001 0.8153 81.57 (13.55) �2.04 (0.34) ,0.001 0.74

Mass-specific rates

Gross primary production (mg O2�[mg AFDM]�1�h�1)42 14.00 (9.05) �0.47 (0.23) 0.065 0.3058 6.70 (7.12) �0.27 (0.18) 0.065 0.18

Respiration (mg O2�[mg AFDM]�1�h�1)42 �3.3 (7.06) �0.07 (0.18) 0.712 0.0158 �0.88 (8.33) �0.13 (0.21) 0.555 0.03

N2-fixation (mg N�[mg AFDM]�1�h�1)41 46.81 (16.3) �1.39 (0.4) 0.004 0.4853 56.47 (22.04) �1.64 (0.55) 0.011 0.41

Note: The apparent activation energy for each measure is the product of�1 and the slope. AFDM stands for ash-free dry mass.Standard error is given in parentheses for intercept and slope. In 1/kT, k is the Boltzmann constant (8.613 10�5 eV/K; 1 eV¼;1.63 10�19 J) and T is temperature (K).


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primary succession (Anderson-Teixeira et al. 2008), our

study highlights the potential for N2 fixation to also

amplify the temperature dependence of ecosystem

processes.

Our hypothesis that amplified AEs of areal GPP and

CR are driven by increased N supply is supported by the

patterns in N2 fixation measured in our experiment. Areal

N2 fixation rates exhibited an AE that was close to

expectations for the nitrogenase enzyme (i.e., 2.18 eV

below 228C, 0.65 eV above 228C; Ceuterick et al. 1978),

while the temperature dependences of GPP and CR were

much higher than canonical values (i.e., AE for areal GPP

¼ 2.11–2.15 eV vs. canonical value of 0.32 eV; AE for CR

¼ 1.60–1.86 eV vs. canonical value of 0.60–0.70 eV; Allen

et al. 2005). Importantly, the apparent AEs of areal GPP

and CR paralleled the AE of N2 fixation, suggesting the

observed amplification of GPP and CR was driven by a

new source of N supplied by elevated rates of N2 fixation

at warm temperatures. This interpretation is consistent

with a growing body of literature demonstrating that

temperature dependences of resource supply rates can

influence the response of ecosystem processes to warming

(Anderson-Teixeira et al. 2008, Yvon-Durocher et al.

2012). In essence, the AE of the supply rate of the limiting

resource should dictate the apparent AEs of GPP and CR.

Thus, in N-poor environments, we might expect signifi-

cant amplification of ecosystemmetabolism in response to

warming when N2 fixers dominate.

The amplified temperature dependences observed in our

study could result from two different, non-mutually

exclusive mechanisms. First, temperature could directly

influence subcellular rates of N2 fixation, resulting in

higher N supply and subsequent increases in rates of

photosynthesis and cellular respiration on a per-cell basis

(e.g., Rhee and Gotham 1981, Robarts and Zohary 1987).

Such a response should be reflected in amplified AEs of

mass-specific rates of GPP and CR. Second, increased

temperature and N supply (via N2 fixation) could amplify

rates of biomass accrual, based simply on the addition of

more metabolically active cells per area. While the strong

correlation between temperature and biomass observed in

our study (R2¼0.79, P , 0.001) precludes us from clearly

distinguishing these direct (subcellular reactions) and

indirect (biomass accrual) effects, the strongly amplified

AEs of areal GPP and CR vs. the AEs of mass-specific

rates, which encompassed canonical expectations (e.g., AE

formass-specificGPP: 0.27–0.47 eV), suggest that biomass

accrual was a key driver of the amplified response. Such

indirect effects of temperature have been largely underap-

preciated but may help explain why temperature per se

may not directly predict large-scale patterns of primary

production (e.g., Michaletz et al. 2014).

It is possible that amplified temperature dependence of

biomass accrual alone can lead to higher ecosystem-level

AEs for metabolism, but results from previous studies are

mixed. For instance, Anderson-Teixeira et al. (2008)

showed that amplified temperature dependence of forest

primary succession resulted, in part, from positive effects

of warming on accrual and storage of soil and leaf

biomass. In contrast, Yvon-Durocher et al. (2010, 2011)

demonstrated that warming actually reduced storage of

photosynthetic biomass in experimental ponds, while

FIG. 2. The temperature dependence of mass-specific ratesof (a) gross primary production (originally measured in mgO2�[mg AFDM]�1�h�1), (b) community respiration (originallymeasured in mg O2�[mg AFDM]�1�h�1), and (c) N2 fixation(originally measured in mg N�[mg AFDM]�1�h�1) plotted as therelationship between ln-transformed rates and inverse temper-ature (1/kT ). The estimated activation energy and 95%confidence intervals (in parentheses) are displayed for eachmeasurement and sampling day when the slope differedsignificantly from zero (a ¼ 0.10). Lines were fit with least-squares regression. Mass-specific respiration rates were notrelated to temperature.


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biomass accrual (as net primary production) roughly

followed MTE predictions (AE ¼ 0.41 eV). Such

discrepancies may be explained by how temperature

influences the supply rate of limiting nutrients or

reactants, as well as how nutrients are utilized and stored

(e.g., assimilation and cell stoichiometry), or transformed

(e.g., dissimilatory processes) as they become available.

Our study indicates that warming may elevate N2 fixation

in aquatic systems and alleviate N limitation of biomass

accrual, leading to amplified temperature dependence of

metabolism in stream biofilms. However, whether or not

this amplification also occurs at the whole-stream scale

depends on the total flux and fate of N introduced to the

ecosystem from N2 fixation. Interestingly, previous

measurements of whole-stream metabolism across a

natural thermal gradient in the Hengill area (Demars et

al. 2011) showed that AEs of GPP and ER were not

amplified, but relatively close to MTE predictions,

suggesting that the temperature-dependent N supplement

to the biofilm is either not sufficient to amplify

metabolism at the ecosystem scale or is unaccounted for

in whole-stream metabolism as a result of increases in N

loss via denitrification, downstream export, or transfer to

the terrestrial environment.

In contrast to patterns in areal fluxes, the AEs of

mass-specific flux rates were often near or lower than

predictions based on MTE. We attribute these results to

the differential rate of biofilm accrual across the

experimental temperature gradient and its effect on

biofilm thickness and associated shifts in cell physiology.

The negative effect of biofilm thickness on mass-specific

process rates is well documented, with potential

mechanisms including self-shading and limitation by

nutrients or inorganic carbon supply (Lamberti and

Resh 1983). Such limitation would have become

progressively more severe with warming in our experi-

ment, as cells deep in the biofilm experienced reduced

access to resources, including light. The suppression of

temperature dependence due to resource limitation of

cell activity in the higher temperature treatments, where

biofilm biomass was high, is consistent with our

hypothesis of amplified temperature dependences of

areal rates being driven by increased N supply.

Although anthropogenic N inputs have significantly

altered N cycling on a global scale (Galloway et al.

2008), the supply of N, in addition to phosphorus, can

still limit productivity in terrestrial, marine, and

freshwater ecosystems worldwide (Smith et al. 1999,

Elser et al. 2007, LeBauer and Treseder 2008). Thus,

amplified responses of ecosystem metabolism to warm-

ing, in response to increased N2 fixation, could

conceivably be widespread. The ability to scale up or

otherwise extrapolate the results of our experiment to

different systems is difficult, however, because despite

the high AE of nitrogenase activity (Ceuterick et al.

1978), empirical estimates of the AE of N2 fixation are

quite variable (e.g., Brouzes and Knowles 1973,

Kashyap et al. 1991), potentially due to intrinsic factors

such as temperature-dependent resource limitation of N2

fixation itself (e.g., by phosphorus, iron, or molybde-

num). Nevertheless, amplified responses of ecosystemmetabolism to warming may be significant worldwide,

but particularly within the acutely nutrient-limited

ecosystems of the Arctic and sub-Arctic, where warmingis expected to be most severe (e.g., Slavik et al. 2004,

Weintraub and Schimel 2005).

ACKNOWLEDGMENTS

This study was funded by the National Science Foundation(DEB-0949774 and DEB-0949726) and additional supportfrom St. Catherine University to J. R. Welter. We thank ChauTran for assisting in the construction of the heat exchangers,and undergraduate students Aimee Ahles, Jackie Goldschmidt,and Ellie Zignego for their collaboration in the development ofmethods and assistance with all field and laboratory workassociated with this project. We also thank Jon Olafsson, GısliMar Gıslason, and the scientists and staff at the Institute ofFreshwater Fisheries in Iceland for their knowledge, support,and laboratory facilities that made this work possible.

LITERATURE CITED

Allen, A. P., J. F. Gillooly, and J. H. Brown. 2005. Linking theglobal carbon cycle to individual metabolism. FunctionalEcology 19:202–213.

Anderson-Teixeira, K. J., and P. M. Vitousek. 2012. Ecosys-tems. Pages 99–111 in R. M. Sibly, J. H. Brown, and A.Kodric-Brown, editors. Metabolic ecology. Wiley-Blackwell,London, UK.

Anderson-Teixeira, K. J., P. M. Vitousek, and J. H. Brown.2008. Amplified temperature dependence in ecosystemsdeveloping on the lava flows of Mauna Loa, Hawai’i.Proceedings of the National Academy of Sciences USA105:228–223.

Arnason, B., P. Theodorsson, S. Bjornsson, and K. Saemunds-son. 1969. Hengill, a high temperature thermal area inIceland. Bulletin of Volcanology 33:245–259.

Arrhenius, S. 1889. Uber die Reaktionsgeschwindigkeit bei derInversion von Rohrzucker durch Sauren. Zeitschrift furPhysikalische Chemie 4:266–248.

Bland, W., and D. Rolls. 1998. Weathering. Arnold, London,UK.

Boltzmann, L. 1872. Weitere Studien uber das Warmegleichge-wicht unter Gasmolekulen. Sitzungsberichte der kaiserlichenAkademie der Wissenschaften 66:275–370.

Bott, T. 2006. Primary production and community respiration.Pages 533–556 in F. Hauer and G. Lamberti, editors.Methods in stream ecology. Elsevier, New York, New York,USA.

Brouzes, R., and R. Knowles. 1973. Kinetics of nitrogenfixation in a glucose-amended, anaerobically incubated soil.Soil Biology and Biochemistry 5:223–229.

Brown, J. H., J. F. Gillooly, A. P. Allen, V. M. Savage, andG. B. West. 2004. Toward a metabolic theory of ecology.Ecology 85:1771–1789.

Burnham, K. P., and D. R. Anderson. 2002. Model selectionand multimodel inference: a practical information-theoreticapproach. Springer, New York, New York, USA.

Capone, D. G. 1993. Determination of nitrogenase activity inaquatic samples using the acetylene reduction procedure.Pages 621–623 in P. F. Kemp, B. F. Sherr, E. B. Sherr, andJ. J. Cole, editors. Handbook of methods in microbialecology. Lewis Publishers, Chelsea, Michigan, USA.

Ceuterick, F., J. Peeters, K. Heremans, H. De Smedt, and H.Olbrechts. 1978. Effect of high pressure, detergents andphospholipase on the break in the Arrhenius plot ofAzotobacter nitrogenase. European Journal of Biochemistry87:401–407.


eports

Davidson, E. A., and I. A. Janssens. 2006. Temperaturesensitivity of soil carbon decomposition and feedbacks toclimate change. Nature 440:165–173.

Davidson, E. A., S. Samanta, S. S. Caramori, and K. Savage.2012. The Dual Arrhenius and Michaelis-Menten kineticsmodel for decomposition of soil organic matter at hourly toseasonal time scales. Global Change Biology 18:371–384.

Demars, B. O. L., J. R. Manson, J. S. Olafsson, G. M.Gıslason, R. Gudmundsdottir, G. Woodward, J. Reiss, D. E.Pichler, J. J. Rasmussen, and N. Friberg. 2011. Temperatureand the metabolic balance of streams. Freshwater Biology 56:1106–1121.

Elser, J. J., M. E. S. Bracken, E. E. Cleland, D. S. Gruner, W. S.Harpole, H. Hillebrand, J. T. Ngai, E. W. Seabloom, J. B.Shurin, and J. E. Smith. 2007. Global analysis of nitrogenand phosphorus limitation of primary producers in freshwa-ter, marine and terrestrial ecosystems. Ecology Letters 10:1135–1142.

Enquist, B. J., E. P. Economo, T. E. Huxman, A. P. Allen,D. D. Ignace, and J. F. Gillooly. 2003. Scaling metabolismfrom organisms to ecosystems. Nature 423:639–642.

Flett, R. J., R. D. Hamilton, and N. E. R. Campbell. 1976.Aquatic acetylene-reduction techniques: solutions to severalproblems. Canadian Journal of Microbiology 22:43–51.

Galloway, J. N., A. R. Townsend, J.W. Erisman,M. Bekunda, Z.Cai, J. R. Freney, L. A. Martinelli, S. P. Seitzinger, and M. A.Sutton. 2008. Transformation of the nitrogen cycle: recenttrends, questions, and potential solutions. Science 320:889–892.

Gillooly, J. F., J. H. Brown, G. B. West, V. M. Savage, andE. L. Charnov. 2001. Effects of size and temperature onmetabolic rate. Science 293:2248–2251.

Grimm, N. B., et al. 2013. The impacts of climate change onecosystem structure and function. Frontiers in Ecology andthe Environment 11:474–482.

Howarth, R. W. 1988. Nutrient limitation of net primaryproduction in marine ecosystems. Annual Review of Ecologyand Systematics 19:89–110.

IPCC. 2013. Climate change 2013: the physical science basis.Contribution of Working Group I to the Fifth AssessmentReport of the Intergovernmental Panel on Climate Change.Cambridge University Press, New York, New York, USA.

Kashyap, A. K., K. D. Pandey, and R. K. Gupta. 1991.Nitrogenase activity of the Antarctic cyanobacterium Nostoccommune: influence of temperature. Folia Microbiologica 36:557–560.

Kaspari, M. 2012. Stoichiometry. Pages 34–47 in R. M. Sibly,J. H. Brown, and A. Kodric-Brown, editors. Metabolicecology. Wiley-Blackwell, London, UK.

Lamberti, G. A., and V. H. Resh. 1983. Stream periphyton andinsect herbivores: an experimental study of grazing by acaddisfly population. Ecology 64:1124–1135.

LeBauer, D. S., and K. K. Treseder. 2008. Nitrogen limitationof net primary productivity in terrestrial ecosystems isglobally distributed. Ecology 89:371–379.

Lopez-Urrutia, A., and X. A. Moran. 2007. Resource limitationof bacterial production distorts the temperature dependenceof oceanic carbon cycling. Ecology 88:817–822.

Marcarelli, A. M., M. A. Baker, and W. A. Wurtsbaugh. 2008.Is in-stream N2 fixation an important N source for benthiccommunities in stream ecosystems? Journal of the NorthAmerican Benthological Society 27:186–211.

Michaletz, S. T., D. Cheng, A. J. Kerkhoff, and B. J. Enquist.2014. Convergence of terrestrial plant production acrossglobal climate gradients. Nature 512:39–43.

O’Gorman, E. J. O., J. P. Benstead, W. F. Cross, N. Friberg,J. M. Hood, P. W. Johnson, B. D. Sigurdsson, and G.Woodward. 2014. Climate change and geothermal ecosys-tems: natural laboratories, sentinel systems, and futurerefugia. Global Change Biology 20:3291–3299

Perkins, D. M., G. Yvon-Durocher, B. O. L. Demars, J. Reiss,D. E. Pichler, N. Friberg, M. Trimmer, and G. Woodward.2012. Consistent temperature dependence of respirationacross ecosystems contrasting in thermal history. GlobalChange Biology 18:1300–1311.

Pinheiro J., D. Bates, S. DebRoy, D. Sarkar, and R Core Team.2014. nlme: linear and nonlinear mixed effects models. Rpackage version 3.1-117. http://cran.r-project.org/web/packages/nlme/index.html

Pomeroy, L. R., and W. J. Wiebe. 2001. Temperature andsubstrates as interactive limiting factors for marine hetero-trophic bacteria. Aquatic Microbial Ecology 23:187–204.

R Core Team. 2013. R: a language and environment forstatistical computing. R Foundation for Statistical Comput-ing, Vienna, Austria. www.r-project.org

Rennie, R. J., and G. A. Kemp. 1986. Temperature-sensitivenodulation andN2 fixation ofRhizobium leguminosarum biovarphaseoli strains. Canadian Journal of Soil Science 66:217–224.

Rhee, G. Y., and I. J. Gotham. 1981. The effect ofenvironmental factors on phytoplankton growth: tempera-ture and the interactions of temperature with nutrientlimitation. Limnology and Oceanography 26:635–648.

Robarts, R. D., and T. Zohary. 1987. Temperature effects onphotosynthetic capacity, respiration, and growth rates ofbloom-forming cyanobacteria. New Zealand Journal ofMarine and Freshwater Research 21:391–399.

Scott, J. T., D. A. Lang, R. S. King, and R. D. Doyle. 2009.Nitrogen fixation and phosphatase activity in periphytongrowing on nutrient diffusing substrata: evidence fordifferential nutrient limitation of stream periphyton. Journalof the North American Benthological Society 28:57–68.

Sibly, R. M., J. H. Brown, and A. Kodric-Brown, editors. 2012.Metabolic ecology. Wiley-Blackwell, London, UK.

Slavik, K., B. J. Peterson, L. A. Deegan, W. B. Bowden, A. E.Hershey, and J. E. Hobbie. 2004. Long-term responses of theKuparuk River ecosystem to phosphorus fertilization.Ecology 85:939–954.

Smith, V. H., G. D. Tilman, and J. C. Nekola. 1999.Eutrophication: impacts of excess nutrient inputs on fresh-water, marine, and terrestrial ecosystems. EnvironmentalPollution 100:179–196.

Sterner, R. W. 2004. A one-resource ‘‘stoichiometry’’? Ecology85:1813–1816.

Weintraub, M. N., and J. P. Schimel. 2005. Nitrogen cyclingand the spread of shrubs control changes in the carbonbalance of arctic tundra ecosystems. BioScience 55:408–415.

Williamson, T. J. 2014. Coupling energy and elements in awarming world: how temperature shapes biofilm ecosystemstructure and function. Thesis. Montana State University,Bozeman, Montana, USA.

Yvon-Durocher, G., et al. 2012. Reconciling the temperaturedependence of respiration across timescales and ecosystemtypes. Nature 487:472–476.

Yvon-Durocher, G., J. I. Jones, M. Trimmer, G. Woodward,and J. M. Montoya. 2010. Warming alters the metabolicbalance of ecosystems. Philosophical Transactions of theRoyal Society B 365:2117–2126.

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Changes in feeding selectivity of freshwater invertebrates ...9f4a4752-806f... · 1. Freshwater invertebrates will have a more specialist feeding strategy in warmer environments