Water and Environmental Studies

Department of Thematic Studies

Linköping University

Food web structure of a Pantanal shallow

lake revealed by stable isotopes

Love-Raoul Nteziryayo

Master’s programme

Science for Sustainable Development

Master’s Thesis, 30 ECTS credits

ISRN: LIU-TEMAV/MPSSD-A--09/XXX--SE

Linköpings Universitet

i

Water and Environmental Studies

Department of Thematic Studies

Linköping University

Food web structure of a Pantanal shallow

lake revealed by stable isotopes

Love-Raoul Nteziryayo

Master’s programme

Science for Sustainable Development

Master’s Thesis, 30 ECTS credits

Supervisor: David Bastviken

2013

ii

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iii

Table of contents Abstract ................................................................................................................................................... 1

1. Introduction ..................................................................................................................................... 1

A short historical brief about the development of food web research .............................................. 2

Food web studies in limnology ............................................................................................................ 2

Lentic systems ................................................................................................................................. 2

Nutrient cycling ............................................................................................................................... 4

Energy flow ...................................................................................................................................... 4

Trophic interactions ........................................................................................................................ 5

Keystones species ............................................................................................................................ 5

The significance of the food web in productive sectors.................................................................. 5

Stable isotopes analysis in food web studies ...................................................................................... 6

Problem formulation and research questions .................................................................................... 7

2. Material and method ...................................................................................................................... 8

Study Area ........................................................................................................................................... 8

Methods ............................................................................................................................................ 10

Sample collection and pretreatments ........................................................................................... 10

Stable isotope analysis .................................................................................................................. 10

Data analysis .................................................................................................................................. 11

Limitation ...................................................................................................................................... 12

3. Results and discussion ................................................................................................................... 13

Carbon and nitrogen isotopic signatures .......................................................................................... 13

Trophic positions ............................................................................................................................... 14

Cluster analysis .................................................................................................................................. 16

Principal component analysis ............................................................................................................ 23

4. Conclusions .................................................................................................................................... 24

5. Acknowledgements ....................................................................................................................... 25

6. References ..................................................................................................................................... 25

Appendices ............................................................................................................................................... i

1

Abstract Food webs are good ecological macro-descriptors and their study is important in ecology in

understanding nutrient cycles, tracing and quantifying energy and in describing trophic

interactions within an ecosystem. The knowledge of food web finds applications in various

natural sciences disciplines but also in many productive sectors. This study investigated the

structure of the food web of a shallow lake in the Pantanal flood plain. The food web included

two macrophytes, six aquatic insects, four crustaceans and 24 fish species. Sources of carbon

for the various organisms living in the lake were identified through the values of δ13

C

exhibited by the organisms. The δ15

N signature was used to estimate the trophic position of

each organism. A cluster analysis based on the two isotopic signatures revealed six different

feeding guilds and emphasized on the broad occurrence of omnivory among animals living in

the lake. This study revealed that the use of food carbon was the most important factor that

structured the lake community. Very low values of δ13

C in zooplankton, benthic dwellers and

bottom-feeder organisms as well as similarities between the gradient of δ13

C and that of use of

methane oxidizing bacteria informed on the possible use of biogenic methane as a source

carbon and energy for the lake biota.

Key words. Cluster analysis; food webs, Pantanal; stable isotopes.

“If we turned to the sea, or a fresh-water pond, or the inside of a horse, we

should find similar communities of animals, and in every case we should

notice that food is the factor which plays the biggest part in their lives, and that

it forms the connecting link between members of the communities.”

(Elton, 1927)

1. Introduction Food is one of the most important factors in the animal life, and in most communities the

organisms are linked by food relations (Elton, 1927). A food web can be defined as “the

pattern of flows of energy and materials among organisms that results when some organisms

eat or consume other living organisms or their parts. A food web sometimes incorporates

flows between organisms and the abiotic or dead biotic environment, including decomposers

and detritus” (Cohen et al., 1993: 252). Paine (1980) and Sabo et al. (2009) among others

classify food webs into three major groups. Traditional food webs which depict the feeding

relationships among organisms without providing any information about the relative rates of

energy flow or the strength of the relationship between the consumer and the prey are called

connectedness webs (Paine, 1980) or connectance webs (Sabo et al. 2009). To this group of

food webs belong community food webs which describe feeding relations among all

organisms that are found in a well-defined habitat (Cohen & Briand, 1984). A second group

of food webs is termed energy webs and describe the flow of energy from primary producers

to top predator by using arrows whose sizes reflect the estimated amount of energy that flows

between each resource and consumer. A third group of food webs is functional or interaction

webs (Sabo et al. 2009) which are based on the idea that species affect differently the

abundance of other species in their ecosystem (Berlow et al., 1999). Functional food webs

describe therefore how the strengths of species interaction are distributed among organisms.

Food webs are good ecological macrodescriptors (Winemiller, 1990) and their study is

important in ecology as an initial step in understanding an ecosystem (Link, 2002).

2

A short historical brief about the development of food web research

Food web research is fairly recent and is still developing. Dunne (2006) identifies three major

phase in the development of food web research. The first phase started in the late 1800s with

the pioneering research of Camorano and Forbes who were the first to publish a food web, in

1880 and 1887 respectively (Thompson et al., 2012). This phase includes also the work of

Pierce, Shelford and Elton who produced in the early 1900s images of food webs that are

quite similar to nowadays food web images. Elton was the first to coin the term “food chain”

(Elton, 1927). This phase lasted up to the 1980s and focused on understanding the properties

of food webs that might determine the stability of ecosystems and on identifying general

structural characteristics of food webs (Thompson et al., 2012a). Various laws are formulated

to describe the network structures of food webs, and simple theoretic models are designed in

order to predict the phenomenology of food-web patterns (Dunne, 2006).

The second phase is a reflexive reassessment of the knowledge created during the first phase.

With improved data and advances in empirical methodology focused on food webs such as

stable isotopes analysis, the knowledge of food webs produced during the first phase was

scrutinized. Criticism about the very low diversity and poor resolution of food webs analyzed

during the first phase, as well as methodological inconsistencies, casted doubts on many

conventionally accepted patterns of food-web structure, the so-called scale-invariant scaling

laws and the predictive models developed during the first phase. As a result, the whole

research program on food web was questioned (Dunne, 2006).

In 1991, 24 prominent food web researchers suggested ways of “improving food webs”

(Cohen et al., 1993). Their proposition focused on how to improve data collection. With high

resolution data and improved empirical and analyses methods, the current phase re-explores

food webs in order to reassess the old laws and theory and provide alternative hypotheses on

structural network. New food web structure models such as the niche model, the nested

hierarchy model and modified cascade model are under experimentation. A regain of interest

is also observed since 2000 in research on general or universal aspects of food-web network

structure. It is now generally accepted that food webs have a heuristic value for ecology

theory (Link, 2002) and a potential to reconcile observed patterns in biodiversity with

evolutionary mechanisms that underpin coexistence (Thompson et al., 2012b).

Food web studies in limnology

Lentic systems

Winemiller (1990) claims that food webs are a good ecological macrodescriptor and Fretwell

(1987) goes even further and argues that food chains dynamics is the central theory in

ecology. Food web study is therefore central in Limnology (Fetahi et al 2011). Lentic systems

in general and lakes in particular have received much attention from the research of food webs

in inland waters (Brönmark & Hansson, 2005; Rigler & Peters, 1995). Reasons explaining

this choice may be historical, logistical and methodological. In the foreword to the book of

Brönmark & Hansson (2005), Nelson Hairston Jr. identifies two major reasons. First, the

Forbesian’s view of a lake as a microcosm has stimulated research in Limnology as well as

other disciplines related to ecology. As a microcosm, a lake is regarded as an isolated, small

but yet diversified ecosystem that can be easily studied and from which knowledge can be

generalized to bigger ecosystems. Second, the physical, chemical and biological worlds are

tightly coupled in lakes, thus providing to limnologists an opportunity of undertaking a

whole-ecosystem approach studies. A third reason is that the problem of system boundaries

that is common in ecology research is less pronounced in lake than in lotic systems (Sabo et

al. 2009). Finally, Woodward & Hildrew (2002) observe that logistic constraints impose that

3

food webs studies be carried out at small scales, thus making lakes the best sites for research

from this point of view.

The understanding of lake ecosystems has developed since Forbes time. It is now known that

lakes present an internal heterogeneity (Schindler & Scheuerell, 2002) and are not as isolated

as Forbes claims (France 1996). Indeed four zones with different abiotic conditions and biota

are observed in lakes (Schindler & Scheuerell, 2002), the benthic habitat, the littoral zone, the

pelagic habitat and the profoundal zone. The benthic habitat is associated with the bottom

substrate in the lake. The littoral zone is the nearshore shallow region with depth water less

than the compensation depth, i.e. is the depth at which there is sufficient light for

photosynthesis to balance respiration (Schindler and Scheuerell, 2002). The littoral and the

benthic zones are frequently considered as one type of habitat and referred as the

benthic/littoral habitat (Kalff, 2002) or simply the benthic habitat. The pelagic zone is the

open water region (Vander Zanden et al. 2011). The profoundal zone is only present in

extremely deep lakes and is located in the water column below the compensation depth. In

shallow lakes, sunlight reaches the benthic/littoral habitat from surface to bottom whereas in

deep lakes, the profoundal zone receives low or not at all sunlight. The benthic/littoral and

pelagic zones of lakes are in the photic zone, that is the zone that receives sunlight whereas

the profoundal zone is in the aphotic zone (Brown 1987). Depending on the depth of the lake,

the pelagic zone can have a thermal stratification and present two layers of different average

temperatures; the upper layer being warmer than the lowest layer. The warmer layer is thus

called epilimnion and the cool lowest layer is called hypolimnion (Jorgensen et al. 2012). The

epilimnion is rich in oxygen because it is in contact with the atmosphere and because water is

constantly moving due to the effect of wind. On the contrary the hypolimnion can have lower

oxygen levels due to the lack of direct contact with the atmosphere and due to limited or

absent photosynthesis (Brown, 1987).

These abiotic factors influence the distribution of organisms in the different habitats of a lake.

In the benthic habitat (understood as both the littoral and the bottom zones), primary

producers include algae (periphyton and metaphyton), macrophytes and bacteria (Schindler &

Scheuerell, 2002). It is worth noting that there is a body of evidence that macrophytes

negatively affect the abundance of phytoplankton in the littoral zone (e.g. Jeppesen et al.

2002; Søndergaard & Moss, 1997; Booker & Cheruvelil 2011). Consumers organisms in this

habitat include protozoa, various species of insects such as midges (Diptera), mayflies

(Ephemeroptera), caddisflies (Trichoptera), other invertebrates including macrocrustaceans

such as crabs, shrimps, molluscs and snails, and different worms such as flat worms, leeches,

tubificid worms (Brönmark & Hansson 2005). Most aquatic insects are benthic and live in or

on the sediment surface but there are species that live on the macrophytes and other that live

on the water surface (Brönmark & Hansson 2005). The benthic zone hosts also fishes and

other vertebrates (amphibians, reptiles, birds and mammals). In the pelagic habitat, the biota

includes virus, microscopic bacteria, protozoa, phytoplankton, zooplankton, planktonic life

stage of insects and fishes. Primary producers in the pelagic habitat are mainly phytoplankton

and bacteria (Schindler & Scheuerell, 2002).

Despite the zonation of a lake there is a continuous exchange of energy and nutrients among

the different habitats of a lake and even between the lake and the terrestrial systems around

(Polis &Strong 1996; Grey et al. 2001; Pace et al. 2004). After highlighting the complex links

that integrate the benthic and the pelagic food chains, Vadeboncoeur et al. (2002) conclude

that there is a “benthic-pelagic coupling”. The cycling of nutrients and the flow of energy are

typical processes that connect, on one hand the lake and its surrounding environment and, on

the other hand the different zones within a lake.

4

Nutrient cycling

The study of food webs has improved the understanding of nutrient cycles. Kalff (2002)

observes for example that the traditional Phosphorous cycle was mainly based on chemical

processes. The consideration of the biological components has significantly improved the

understanding of the Phosphorous cycle. Obviously differences exist among detailed cycles of

Phosphorous, Nitrogen, Carbon, Silicon and other elements. However there are also

interrelations among the cycles of nutrients (Schindler 1981) which allow the following

“general nutrient cycle” that most of elements follow (Brönmark & Hansson 2005). Basically

all nutrients entering in the lake are delivered by the terrestrial drainage basins, in surface

runoffs and groundwater, the atmosphere, as windblown soil dust, aerosol particles, gases and

rain (Kalff 2002; Brönmark &Hansson 2005) or as plant and animal material falling into the

lake (Cole et al , 2006). Macrophytes, algae and bacteria take up the incoming nutrients. The

uptake can be direct if nutrients are in an accessible form; otherwise a prior mineralization by

bacteria is necessary. Part of the macrophytes, algae and bacteria is grazed by herbivorous and

bacteriophagous organisms which are eaten by carnivorous organisms, thus passing part of

the nutrients into the food chains. A second part of the nutrients is respired or excreted in the

water column or out in the atmosphere. A last part of the nutrients contained in macrophytes,

algae and bacteria join the detritus made of other autochtonous and allochthonous material.

This detritus is either suspended in the water column or sink to the sediment at the bottom of

the lake. Part of the detritus is ingested by detritivorous organisms. Another part of the

detritus is mineralized by bacteria and nutrients are released back again in the water column

or passed to bacteriophagous organisms, thus availing nutrients to higher trophic levels

through this “microbial loop” (Azam et al. 1983). Nutrients can also be released by the lake

into its surrounding environment through a creek or a river (Brönmark &Hansson 2005).

From this simplified general nutrient cycle, it is clear that nutrients flow from one habitat of

the lake to another (Polis & Strong 1996). Nutrients from the benthic/littoral habitat are taken

up by pelagic organisms (Grey et al. 2001; Pace et al. 2004) while from the pelagic habitat

nutrients trickle to the benthic and conversely nutrients from the benthic reach the pelagic

habitat with the upwelling water or though bacterial pathways (Vander Zanden &

Vadeboncoeur, 2002).

Energy flow

Food web knowledge allows tracing and quantifying energy flow in ecosystems (Thompson et

al. 2012a). Conversely, tracing and quantifying energy flows in an ecosystem can yield

knowledge on food webs existing in the ecosystem. Energy may enter ecosystems as solar

radiation or as organic matter (Fisher & Likens 1973). Solar energy is then captured by

photosynthetic autotrophs in the lake, namely macrophytes, algae and bacteria, and

transformed in chemical energy through the photosynthesis process. Besides photosynthesis,

chemosynthesis is another mechanisms of availing energy to the lake biota (Camacho et al.,

2001). In this process, chemoautotrophic bacteria fix CO2 or methane and transform it into

organic matter. The energy necessary to this transformation comes from the oxidation of

reducing substances such as hydrogen sulfide or methane (Hadas et al. 2001; Kalff, 2002). In

both cases part of the transformed chemical energy by the autotrophs will be respired, another

part will be stored either in living tissues of the autotrophs or in their dead tissues as detritus.

The energy in living autotrophs is transferred to primary consumers through the trophic link

(Fisher & Likens 1973). Energy is successively transferred from primary consumers to

secondary consumers up to top predators. At each level of the food web, at each stage, part of

the energy is transpired and another part is released in the habitat as detritus (Schmid-Araya

& Schmid, 2000). Decomposers in general and bacteria in particular reintegrate part of the

detrital energy into the food webs as they are eaten by other consumers. With the insight

5

gained from the study of food webs, whole-system energy budgets can be calculated (e.g.

Teal 1962, Fisher & Likens, 1973) and new light is shaded on the role of consumers as

maximizers of energy flow in ecosystems (Loreau, 1994).

Trophic interactions

The structure of food webs informs on trophic interactions in an ecosystem. A dominant

discourse in Limnology claims that trophic interactions determine the distribution and

abundance of organisms (Power 1992). Various theories have been developed to explain

population patterns in ecosystems. Theory of the “bottom-up” processes claims that resources

such as food and habitat are the primary regulator of populations (Fretwell 1987). A second

theory known as the “top-down” theory, argues that abundance at each trophic level is

controlled directly or indirectly by consumers at the top of the chain (Polis & Strong 1996).

From the “top-down” theory, different hypotheses have been developed. The green world

hypothesis for example, also known as the HSS model in reference to its founders Hairston,

Smith and Slobodkin, claims that predation plays an equal role to that of resources in

regulating organisms populations (Fretwell 1987) and that the principal factor limiting growth

of a population depends on which trophic level the population is positioned, with predators

being limited by resources, herbivores by predation and producers by resources (Brönmark &

Hansson, 2005).

Another theory built from the top-down theory is the cascading trophic interactions which

states that an increase of apex predator such as piscivores in a lake has cascading effects on

lower trophic levels as it decreases the population of planktivores, this leads to an increase in

zooplankton; an increase in zooplankton leads to a decrease in phytoplankton due to grazing.

Ultimately, an increase in the top predator’s biomass results therefore into a decrease of

primary producers (Carpenter et al. 1985). From the “bottom-up” and “top-down” theories, a

hybrid theory was formulated and it is known as the “bottom-up:top-down” theory. According

to Brönmark & Hansson (2005), “bottom-up:top-down” theory predicts that trophic levels

near the base of the food chain are primarily affected by bottom-up processes whereas these

bottom-up processes are weaker in the higher trophic levels; on the contrary top-down

processes are significant at the top of the trophic chain while they have a weaker effect on the

lower trophic levels.

Keystones species

All species influence the structure of their communities to a degree, but some of them have a

greater effect on the structure than others (Begon et al. 2006). Food web study allows

identifying potential keystones species of a specific ecosystem. A keystone species is a

species that has a disproportionately large effect on its environment relative to its abundance

(Paine, 1995). Keystone species are crucial in maintaining the organization and diversity of

their ecological communities as their loss would trigger the extinction of many other species

in their communities (Mills et al. 1993). Estes et al. (2011) among others provide various

examples of keystone species including sea otter, arctic fox, the Amazonian jaguar,

wildebeest in the savanna, etc. The concept of keystone species has direct application in

biodiversity conservation and habitat restoration as it has the potential to improve the

effectiveness and efficiency of conservation and restoration action (Mills et al. 1993; Chapin

et al 2000).

The significance of the food web in productive sectors

The knowledge of food web finds applications in various natural sciences disciplines but also

in many productive sectors. In environment management, the knowledge of food web helps

understand severe acute and subtle chronic effects of chemicals and other stressors in the

6

environment (Preziosi and Pastorok, 2008). Cohen et al. (1993) claim that a better

understanding of food web would improve predictions about biological concentration of

toxins and pollutants and strategies for integrated pest management, control of disease

vectors, industrial waste-water treatment, and wildlife conservation. In fisheries, food web is

used to model and predict changes in harvested fish (Pauly & Palomares, 2005). In agriculture

and forestry, food web knowledge helps understanding and managing the health of soil

communities and their potential link to crop yields (Brussaard et al., 1988). Food web

understanding is also crucial for the protection and management of endangered species (Mills

et al., 1993; Chapin et al. 2000).

Stable isotopes analysis in food web studies

Isotopes are atoms with the same number of protons and electrons but differing numbers of

neutrons. Many elements have isotopes as only 21 elements are known to have only one

isotope (Sulzman, 2007). All the isotopes of an element are not equally stable. Radioactive

isotopes generally decay more or less rapidly whereas stable isotopes are those that are

energetically stable and do not decay (Sulzman, 2007). There are roughly 300 stable isotopes,

over 1200 radioactive isotopes.

Light isotopes of an element are more abundant than heavy isotopes in biological compounds

and many reactions fractionate stable isotopes, or in other words physicochemical reactions

alter the ratio of heavy to light isotopes between the source and products compounds of a

reaction (Sulzman 2007). Because light isotopes have higher velocity than heavier isotopes,

they tend to accumulate in the products of a reaction or in the lighter phase of a substance, for

example in the vapor phase more than the liquid phase (Sulzman, 2007). On the contrary

heavy isotopes tend to accumulate in the reactants, in the denser phase or in the phase that has

the highest oxidation state for example in CH4 more than CO2. The predictability of the

change in isotopic composition leads to the use of stable isotopes in archaeology, climate

research and in various disciplines of ecology (Petereson & Fry 1987). In ecology for

instance, stable isotopes have been used to study physiological processes such as

photosynthesis pathways (O’Leary, 1988), to assess anthropogenic nutrient inputs in

ecosystems (Cabana & Rasmussen, 1996), to trace the origin and migration of wildlife

(Hobson, 1999), etc.

In food web research stable isotopes are used to identify and measure sources of organic

matter (e.g.: Bunn & Boon 1993; Cole et al. 2002; Roach et al. 2009) and to estimate trophic

positions of consumers (Vander Zanden & Rasmussen 1999). Stable isotopes of carbon (13

C

and 12

C), nitrogen (15

N and 14

N) are the most commonly used in food web studies but isotope

of sulfur (34

S and 32

S), oxygen (18

O and 16

O) and deuterium are also used in some cases

(Layman et al. 2012). In food web analysis and most of ecological studies the isotopic

composition is usually given in terms of δ values, which are the ratio of the heavier isotope to

the lighter isotope in a sample expressed relative to the same ratio of a standard (Layman et

al. 2012).

Standard reference materials are carbon in the PeeDee limestone and nitrogen gas in the

atmosphere (Peterson & Fry, 1987).

The use of stable isotopes in food web studies originates from the observation that the

isotopic composition of the whole body of an animal reflects the isotopic composition of its

diet except a slight fractionation (DeNiro & Epstein, 1978). Ratio of carbon isotopes for

instance vary significantly among primary producers with different photosynthetic pathways

(O’Leary 1988) but change little with trophic transfers as the δ13

C enrichment between two

successive trophic levels is less than 1‰ (DeNiro & Epstein, 1978; Peterson & Fry, 1987;

7

Post 2002). It is therefore possible to determine the original source of carbon from the δ13

C

signature of an animal. The procedure consists of two steps (DeNiro & Epstein, 1978). First

the δ13

C value of the diet is estimated from the δ13

C value of the animal. The second step

consists in combining potential diet sources of known δ13

C values in adequate proportions in

order to produce the δ13

C of the diet as estimated in the first step. The ratio of 15

N to 14

N in

animals shows a stepwise enrichment relative to their diet equal to 3.4‰ on average (Cabana

& Rasmussen, 1996; Peterson & Fry, 1987; Post, 2002). This nitrogen isotopic variation is

thus used in determining the trophic position of organisms in a food web.

Stable isotope analysis allows overcome some shortcomings of the classic methods used to

analyze the diet of animals. These methods, which consist in observing animals and analyzing

the undigested food fragments in the guts or in the feces (DeNiro & Epstein, 1978), are time

consuming and difficult to perform with animals that are hard to observe. Moreover, the gut

content analysis is subject to errors because all food material that is in the gut of an animal

cannot be identified and all food material in the gut is not necessarily part of the animal’s diet

(Woodward & Hildrew, 2002; Peterson & Fry, 1987). Stable isotopes are increasingly used in

studies that evaluate the importance of non-photosynthetic carbon sources in aquatic food

webs. Particularly, different studies using stable isotopes assess how significant is the role

that methane plays in whole aquatic food webs (e.g.: Camacho et al. 2001; Bastviken et al.

2003; Kankaala et al. 2006, Jones et al. 2008; Sanseverino et al. 2012). However, it is still

unclear under what conditions methane is important as a food source of carbon and energy.

The use of nitrogen stable isotopes provides a method to assign organisms to a trophic

position thus avoiding the classic simplification of discrete trophic levels (Vander Zanden &

Rasmussen 1999; Post 2002). The concept of trophic levels is indeed questioned by different

authors (e.g.: Paine, 1980; Polis & Strong, 1996; Williams & Martinez, 2000). The general

argument against discrete trophic levels is that omnivory, that is feeding on more than one

trophic level, cannibalism, diet shifts due to environmental changes, geographical and

temporal diet heterogeneity are some of phenomena that occur in nature and that lead to rather

reticulate food webs (Polis & Strong, 1996). From this point of view, the concept of trophic

spectra is more appropriate than the trophic level (Darnell, 1961).

Problem formulation and research questions

Studies on food webs in general are much fewer in tropical regions than in temperate regions

(Sarmento, 2012). Most of the highly detailed and comprehensive food web studies have been

conducted in the temperate regions. These include for example the study of the Coachella

Valley desert in California by Polis (1991), the detailed description of the community food

web for Little Rock Lake in Wisconsin by Martinez (Dunne, 2006), the Broadstone Stream

food web in England by Hildrew et al. in 1985 and Schmid-Araya & Schmid in 2000, the

Skipwith Pond food web in Australia by Warren in 1989 (Thompson et al., 2012a), and many

more other studies in Europe and Canada. To the best of my knowledge, there is no such

highly resolved food web studies published for tropical regions. The problem of resolution in

food web studies generally originates from the consideration of a low number of species

compared to what really exist in the ecosystem under study (Martinez, 1991). Poor resolution

is also caused by the arbitrary choice of temporal and spatial boundaries and the aggregation

of species into trophic species, i.e. organisms that are assumed to share the same set of prey

and predators (Martinez, 1993). Consequently many food web studies fail to represent the

richness of community species and trophic interactions (Martinez, 1993).

The food webs of the Pantanal, a flood plain in South America that covers 160000 km2 and

that was declared Biosphere Reserve by UNESCO in 2000 (Alho & Silva, 2012), are still

poorly studied as it is the case for most of subtropical south American systems (Junk et al.,

8

2006; Junk & Cunha, 2005; Wantzen et al., 2008). Few studies about the food webs of the

Pantanal flood plain have been published as per now (e.g.: Forsberg et al., 1993; Benedito-

Cecilio et al., 2000; Brito et al., 2006; Wantzen et al., 2002). The general scarcity of studies

of food webs in tropical regions would not be a problem if knowledge gained in the temperate

regions could be generalized to the tropical food webs. Although common features to all food

webs exist (Pimm, 1991), there are fundamental structural variations in food webs of the

tropical regions compared to food webs of the temperate regions (Sarmento, 2012). These

include notably the composition of autotrophic and consumer communities. Moreover

Winemiller & Jepsen (1998) observe for example that the degree of trophic diversification is

greater in tropical fish assemblages compared to fish assemblage of same habitat in temperate

regions and some tropical feeding niches are absent in temperate fish assemblages.. In

addition to these regional differences, high variability among and within lakes are common,

as Sarmento (2012) puts it “every lake is a lake!” Such variability may hinder extrapolation

and generalization to tropical food webs of patterns observed in temperate food webs. Even

within the same region caution is needed before generalizing the knowledge drawn from the

food web of one ecosystem to another.

There are two opposed views about the occurrence of omnivory in food webs. On one hand,

some writers claim that omnivory is a rare phenomenon in food webs (e.g.: Pimm et al., 1991;

Hairston & Hairston, 1993; Cohen et al., 1990). This opinion has influenced the construction

of theories and models used to describe and predict community dynamics. Such theories and

models include, among others, the trophic cascade model (Polis & Strong, 1996;

Vadeboncoeur et al., 2005). From this perspective, lake food webs are described as simple

linear chains based on phytoplankton-derived energy (Vadeboncoeur et al., 2005). On the

other hand, there are writers who argue that omnivory is prevalent in food webs (e.g.: Polis,

1991; Martinez, 1991; William & Martinez, 2000). One of the arguments provided by the

supporter of this view is that low resolved data and weak methodology in classic food web

studies led to oversimplifications and thus failed to represent the complexity that exists in

natural food webs (Polis, 1991; Dunne, 2006). The use of stable isotopes provides a novel

method for integrating omnivory in the study of food webs (Vander Zanden & Rasmussen

1999; Post 2002).

The aim of this study is to investigate the structure of the food web of a shallow lake in the

Pantanal flood plain. Using a new extensive set of isotopic data from a shallow lake in the

Pantanal flood plain, the study specifically tests two hypotheses:

i) tropical lacustrine food webs tend to exhibit a high occurrence of detritivory and

omnivory;

ii) the isotopic signature of lacustrine animals is influenced by the habitat from which

animals get their food.

2. Material and method

Study Area

The Pantanal floodplain is the largest freshwater wetland in the world (Florentino & Penha,

2011). It is situated between 16-20oS and 55-58

oW in the depression of the upper Paraguay

River and covers an area of about 160,000 km2, of which 140,000 km2 are in Brazil, 15,000

km2 are in Bolivia and 5,000 km2 are in Paraguay (Junk et al., 2006). The Pantanal has a

tropical and semi-humid climate which is characterized by a rainy season, from October to

April, and a pronounced dry season, from May to September (Junk et al., 2006). During the

9

rainy season, the Pantanal Bassin receives between 1000 and 1250 mm annually (Junk et al.,

2006). These rains lead to the flooding of the Pantanal. The water will recess during the dry

season when the Pantanal experiences then a drought (Wantzen et al., 2008). This annual

monomodal floodpulse is the major driving force for ecological processes and biodiversity

patterns in the Pantanal Basin (Junk & daSilva, 1995; de Oliveira & Calheiros, 2000). Mean

temperature is 25oC, with December being the hottest month when temperature averages

27.4oC. (Alho and Vieira, 1997). The coldest month is July when temperature averages

21.4oC.

The Pantanal ecosystem plays a key role in the climate and hydrology of the whole region, as

well as in the productivity and nutrient cycling of terrestrial and aquatic food webs. The

Pantanal region is very important in terms of global methane fluxes because of high methane

production (Conrad et al. 2011) and emission (Bastviken et al. 2010) rates from its aquatic

environments. Besides, the Pantanal wetland sustains a large diversity of fauna, flora and

microorganisms. Wantzen et al. (2008) identified five ecosystem services that are offered by

the Pantanal: 1) Buffering of hydrological changes; 2) Water purification; 3) Fish production;

4) Terrestrial productivity; and 5) Biodiversity.

During the flood, the Pantanal Basin stores large portions of the water from the rain and from

the Paraguay River and, as a result, the flood amplitude in Pantanal cities is significantly

reduced. Moreover, being a large infiltration area for groundwater, the Pantanal is assumed to

provide substantial amount of water to the regional aquifers (Wantzen et al., 2008).

Furthermore, the Pantanal is considered as “the largest evapotranspiration window in Central

South America” (Wantzen et al., 2008) since about 90% of rainwater is evaporated (Junk et

al. 2005). It can therefore be assumed that the Pantanal contributes significantly to buffering

the temperature in this region of South America even though the extent of this contribution is

not yet assessed.

Wantzen et al. (2008) pointed out that the low organic pollution of water that is observed

below the cities neighbouring the Pantanal is a result of the autopurification capacity of the

Pantanal rivers. These rivers contain dense macrophytes mats that process all kinds of

dissolved organic and inorganic substances.

The production of fish which is an important source of protein for the human population

living in the Pantanal region, and the seasonal grasslands have made pastures available for up

to 8 million cattle head (Alho & Vieira, 1997).

Junk and Cunha (2005) observed that most soils of the Pantanal are acidic and of low fertility.

However, Wantzen et al. (2008) argued that the alternation of flood and drought facilitates the

decomposition and mineralization of aquatic organisms and results in the release of important

nutrients. These nutrients are used by terrestrial vegetation which in turn, contributes to

feeding herbivores in general and most particularly cattle.

This mosaic of terrestrial, flooded and aquatic environments harbor 174 species of mammals

(Alho et al. 2011), 463 registered bird species (Alho, 2008), 177 of reptiles (Alho, 2008), 41

amphibians (Alho, 2008), 263 fish species (Britski et al. 1999 cited by Wantzen et al., 2008),

337 of algae (Junk et al. 2006) and 1903 recorded higher plant species (Junk et al. 2006).

Furthermore, there is a lack of inventories and surveys on the numerous species of aquatic and

terrestrial invertebrates living in Pantanal. Due to the integrity of its ecosystem, the Pantanal

is a refuge zone for many rare species or species that are already extinct in other areas of

South America. This is why the Pantanal is sometimes referred as a “Noah’s Ark” (e.g.,

Wantzen et al., 2008).

10

Because of these ecosystem services that are offered by the Pantanal, the Brazilian

constitution declared the Pantanal in 1988 as a National Heritage. The UNESCO declared it in

2000 as a World Biosphere Reserve and granted it the World Heritage Certificate (Junk and

Nunes da Cunha, 2005). The Pantanal wetland has been impacted by economic activities as

cattle ranching, fishery, agriculture, mining, urbanization and tourism (Alho, 2008), and

therefore requires highest priority in environmental protection (Junk et al. 2006).

Methods

Sample collection and pretreatments

Different species of fishes, zooplankton, aquatic invertebrates and plants were collected from

a shallow lake (average depth 1.8 m) in the Paraguay River flood plain near the city of

Ladário, Mato Grosso do Sul state, Brazil (Figures 1 & 2). The organisms were chosen to

represent different trophic levels as well as different compartments of an aquatic food web in

Pantanal. The fishes were sampled with nets in the shore area and middle of the lake. A piece

of fish dorsal muscle was cut out and freeze dried. Zooplankton were collected with a

zooplankton net (150 µm mesh), rinsed thoroughly with deionized water, handpicked into 2

ml sterile Eppendorf tubes, and freeze dried. The Grassy plants (Gramineum sp.) and the

totally dominating macrophyte in and around the lake (Eichhornia crassipes) were also

sampled (whole plants including roots). The plants were rinsed in water and biofilms were

removed from their surfaces. Sediment was collected by diving and sieved for sampling of

benthic invertebrates. All benthic invertebrates were kept in filtered (Whatman GF/F) lake

water for 24 hours for gut clearance, and were then rinsed and freeze dried.

Freeze dried samples of biomass were ground into fine powder prior to the stable isotopes

measurements. Sediment samples were pre-acidified to remove carbonates before carbon

stable isotopes measurements. For N-stable isotopes measurements, no pretreatment was done

on sediments samples.

Stable isotope analysis

For stable isotope analysis, samples were combusted with a Carlo Erba NC2500 analyzer

connected to a Finnigan MAT Delta plus mass spectrometer. Stable isotope ratios were

expressed as a per mil (‰) deviation according to the equation:

[(

) ]

where X is the heavier isotope (e.g. 13

C or 15

N), and R is the corresponding ratio of the

heavier isotope to the light isotope (13

C/12

C or 15

N/14

N).

δ13

C = [(δ13

C/ δ12

C)sample / (δ13

C/ δ12

C)standard – 1] x 1000

δ15

N = [(δ15

N/ δ14

N)sample / (δ15

N/ δ14

N)standard – 1] x 1000

Limit of detection was 20 µg N and 100 µg C The 13

C and 15

N values were reproducible to

within 0.2‰ and 0.3‰ respectively.

Samples with higher isotope values are relatively enriched in the heavy isotope 13

C or 15

N

while samples with lower isotope signatures are relatively depleted in 13

C or 15

N and enriched

in the light isotope 12

C or 14

N. Stable isotope ratios of carbon and nitrogen were reported

relative to VPDB (Vienna PeeDee Belemnite) standard and nitrogen gas in the atmosphere,

respectively.

11

Figure 1. Map of the Pantanal showing the localisation of the lake from which animal

samples were taken (modified from Bastviken et al., 2010).

Figure 2: two views of the lake under study. Note the surrounding forest (left) and the

dominant cover of the shore by the water hyacinth Eichhornia crassipes (right)

Data analysis

A cluster analysis was performed to recognize grouping of organisms according to their

isotopic signatures and to identify resemblances among those groups. The hierarchical

12

clustering was carried out on a Gower similarity matrix (organisms as objects and isotopic

signatures as descriptors) and represented by a dendrogram produced by UPGMA

(Unweighted Pair-Group Method with Arithmetic averages) clustering of the resultant matrix.

The cluster analysis was performed using the software package PAST version 2.12 (Hammer

et al., 2001). A Kruskal-Wallis test was performed to test the null hypothesis that the

identified clusters had statistically equal median δ13

C values. In case the null hypothesis was

rejected, a pairwise comparison of clusters would be done in order to identify the clusters that

had significantly different median δ13

C values.

The trophic position of the sampled animals was estimated by using the formula proposed by

Post (2002):

Trophic position = λ + [(δ15

Nsecondary consumer - δ15

Nbase)/ n]

where λ is the trophic position of the organism representing δ15

Nbase, δ15

Nsecondary consumer (or

any higher consumer) is measured directly, and ∆n is the enrichment in δ15

N per trophic level.

A trophic enrichment of 3.4‰ for δ15

N was assumed (Vander Zanden et al. 1997, Post 2002).

Jepsen & Winemiller (2002) argue that the 3.4‰ enrichment for δ15

N derived from laboratory

studies. They suggest therefore that an estimated 2.8‰ mean trophic enrichment of δ15

N

between fish and their food source is more appropriate for tropical regions. For comparability

purpose, the 3.4‰ trophic enrichment will be used in this study because most studies still use

the same trophic enrichment (e.g.: Manetta et al., 2003; Pound et al., 2010).

Trophic positions were estimated relative to that of Chironomidae instead of that of primary

producers. The reason for this choice was that primary producers generally exhibit a high

variability in their δ15

N value, rendering their use in estimating trophic position problematic

(Vander Zanden et al. 1997). Chironomidae, on the contrary, show a stable nitrogen isotopic

signature over the seasons (Wantzen et al. 2002). Moreover Chironomidae are abundant in the

Pantanal throughout the year and ubiquitous over different lentic systems. The mean δ15

N

value of Chironomidae (4.8‰) was considered as the lake’s "baseline" δ15

N signature

(Vander-Zanden et al. 1997). The trophic position of Chironomidae (λ) was therefore

considered to be equal to 2 according to the classification proposed by Vander-Zanden &

Rasmussen 1996. Thereby the trophic position of the animals in the lake was finally estimated

by the expression:

Trophic position = 2 + (δ15

Nsecondary consumer – 4.8)/3.4

A Principal Component Analysis (PCA) allowed ordinate the isotopic signatures of the

organisms in an orthogonal system with the aim of identifying a potential correlation between

taxa based on the stable isotopic composition. The PCA also estimated to what extent δ13

C

and δ15

N accounted for the variability observed in the structure of the community under study

(Jolliffe 2002).

Limitation

Birds, mammals and reptiles were not sampled because permission could not be obtained

from the Ministry of Environment during the time of field work. Only organisms living in the

water and in the sediment were sampled except phytoplankton and periphyton. These algae

were not analyzed because sampling them is laborious and time consuming (Hecky &

Hesslein, 1995; Wantzen et al., 2002; Marker, 1976; Biggs & Smith, 2002). The carbon and

nitrogen isotopic signatures of phytoplankton and periphyton were therefore assumed from

results of other studies in the Pantanal.

13

3. Results and discussion

Carbon and nitrogen isotopic signatures

The values of 13

C ranged from -42 to -27.7‰ (Figure 3, see also Table 1 in appendix).

Zooplankton and the aquatic insect Chaoboridae presented the lowest 13

C values (-42‰ and

-40.2‰, respectively). Depletions in 13

C were also observed in the ephemeropteran

Campsurus sp. and the dipterans Ceratopogonidae and Chironomidae sp.2 and sp.3 (δ13

C < -

36‰). Some fish species also exhibited low 13

C signatures. Potamorhina squamoralevis,

Cyphocharax sp., Anadoras grypus, Leporinus friderici and Steindachnerina brevipinna

exhibited 13

C values lower than -36‰. On the other hand, the taxa known to be pelagic or

associated to aquatic plants (Tetragonopterus argenteus, Astyanax cf. bimaculatus and

Parauchenipterus galeatus) were substantially less depleted in 13

C (δ13

C > -29‰). The water

hyacinth Eichhornia crassipes and the Gramineum presented an isotopic value of -27.9‰ and

-29.1‰ respectively.

As for δ15

N values, they ranged from 4.3 to 10.0‰. The benthic insects Campsurus sp.,

Ceratopogonidae and the three Chironomidae species along with the Gramineum and the fish

Hypostomus sp. presented the lowest δ15

N values varying from 4.3 to 5.8‰. The crab

Trichodactylus sp. and the fish species S. brevipinna, P. squamoralevis and Cyphocharax sp.

presented also low δ15

N values inferior to 7‰. The piscivore fish species Serrasalmus sp.,

Acestrorhynchus pantaneiro, Pygocentrus nattereri and Serrasalmus marginatus had the

highest δ15

N values between 8.7 to 10‰. Zooplankton and the Chaoboridae had a slightly

inferior δ15

N value (8.6‰) than the piscivore fish species.

A pattern in the isotopic signatures of animals seemed to emerge from the scatter plot (Figure

3). Group 1 was composed of detritivorous animals (except P. paraguayensis) had generally

the lowest δ13

C values. Animal living in the littoral habitat and close to macrophytes (group

2) exhibited generally the highest δ13

C values. This was particularly the case for T. argenteus,

A. bimaculatus and P. galeatus which are all omnivorous fish with a tendency to herbivory-

invertivory (Correa et al., 2011). Gymnogeophagus balzanii, Trichodactylus sp. and

Hypostomus sp. seemed to be exceptions as they were more depleted in 13

C than the other

animals in this group. These three species are mainly bottom-feeders and consume detritus

and algae (Correa et al., 2011; Burress & Gangloff, 2013; Venancio & Leme, 2010; da Silva

et al., 2012). Except Macrobrachium sp.1 which is a bottom feeder associated to

macrophytes, all pelagic animals were in group 3 and exhibited intermediate δ13

C values

between those of the detritivore (group 1) and of the littoral feeding animals.

The bottom-feeders in group 1 and the littoral dwellers seemed to have lower δ15

N values

compared to those of the pelagic feeding animals of group 3. This could originate from the

diet of animals in goup 1 and group 2 which were dominated by primary producers (detritus ,

benthic algae, macrophytes ) and invertebrates (terrestrial and aquatic). Animals in group 3

relied more on a carnivory diet than the first two groups and had thus a higher nitrogen

isotopic signature.

Zooplankton and Chaoborus sp. seemed to make a distinct group. They were the most

depleted in 13C but had a δ15

N value broadly similar to that of the carnivorous animals in

group3. This seemed to indicate that zooplankton and Chaoborus sp. though generally feeding

in the water column, they probably used a food resource which was depleted in 13

C.

It is worth to note that the scatter plot in figure 3 did not show clearly a potential correlation

between the δ13

C and δ15

N values. The Pearson’s correlation coefficient was found to be 0.24

14

suggesting that there was no linear association between δ13

C and δ15

N values. The spread in

the plotted points indicated that animals in the lake had different carbon sources.

Consequently, the enrichment in the isotopic ratio between the consumer relative to its diet

was not straightforward. In particular, the δ15

N values seemed to indicate that most animals

were omnivorous feeding on different trophic levels.

-

Figure 4: δ13

C and δ15

N values of organisms

Trophic positions

The estimated trophic positions of the animals ranged from 1.8 to 3.5 (Figure 5, see also

Table 2 in appendix). The ephemeropterans Campsurus sp. and the dipterans Chironomidae

and Ceratopogonidae along with the fish Hypostomus sp had the lowest trophic positions

varying from 1.8 to 2.3. The majority of species occupied trophic positions that ranged from

2.5 to 3.0. With a trophic position of 3.1, zooplankton and the Chaoboridae were among

animals with higher trophic position. The Serrasalmidae fishes had trophic positions that

ranged from 3.2 to 3.5. Serrasalmus marginatus had the highest trophic position (3.5) and

could thus be considered as the top predator of the considered food web.

By combining the trophic position and the feeding habit of the animals, it was possible to

regroup the animals in three trophic levels (Figure 5). Detritivore-herbivore animals occupied

the lowest trophic level among the lake animals. In this trophic level were all animals whose

trophic position was not higher than 2.3. Predators occupied the highest trophic level and

included all animals with trophic positions superior to 3.0. Between these two trophic levels

were omnivore animals which made the majority of animals living in the lake. Omnivory was

therefore prevalent in the lake under study.

Group 3

Group 2

Group 4 I corrected the page numbering and the numbering of figures.

I added a glossary of terms and a conclusion section.

Group 1

15

Omnivory reflects consumers’ flexibility in energy acquisition (Vadeboncoeur et al., 2005). In

this lake submitted to the flood pulse of the Pantanal, omnivory was an adaptation to the

seasonal changes in the availability of food resources. Omnivorous fish and other animals

found their prey in different habitats (benthic/littoral and pelagic) of the lake. The prevalence

of omnivory has some theoretical and practical implications.From a theoretical perspective,

top-down control models used to study and predict community dynamics are based on the

assumption that omnivory is rare (Vadeboncoeur et al., 2005). Such models need therefore to

be adapted for tropical food webs in order to take into account the complexity caused by

omnivory. From a practical perspective, the management of the lake and similar ecosystems

needs to reserve special care for omnivorous animals. Because of the critical importance of

omnivore in animals communities, their removal is susceptible of reducing the persistence

and resilience of the ecosystem (Emmerson & Yearsley, 2004).

Figure 5: trophic levels in the lake animal community. In the detritivore-herbivore trophic

level were included, from the lowest trophic position to the highest, Campsurus sp.,

Chironomidae (3 species with trophic position 2), Hypostomus sp.and Ceratopogonidae. The

omnivore trophic level included, from the lowest trophic position to the highest,

Trichodactylus sp., P. squamoralevis, S. brevipinna, Cyphocharax sp.; T. argenteus, L.

friderichi, L. macrocephalus, H. temporalis, Brachyhypopomus sp., A. bimaculatus, Loricaria

sp., , G. balzanii, Macrobrachium sp.2, P. galeatus, P. paraguayensis, S. macrurus, A.

grypus, T. pantanensis, P. australis and Macrobrachium sp.1.The predator trophic level

included, from the lowest trophic position to highest, Hemigramus sp., Crenicichla sp.,

zooplankton, Chaoborus sp., Serrasalmus sp., A. pantaneiro, P. nattereri and S. marginatus.

1,50

2,00

2,50

3,00

3,50

4,00

4,00 5,00 6,00 7,00 8,00 9,00 10,00 11,00

Tro

ph

ic p

osi

tio

n

δ15N

Detritivore-herbivore

Omnivore

Predator

16

Cluster analysis

The dendrogram in Figure 6 illustrates the clustering of organisms based on δ13

C and δ15

N

signatures. Three arbitrary ‘‘cutoff’’ lines, at Gower similarities of 0.41, 0.35, 0.25 and 0.15

were used as reference points for identifying clusters. At a distance of 0.41, two distinct

clusters were formed:

Cluster 1 grouped the aquatic insects of the food web, i.e. three Chironomidae species (non-

biting midges), the ephemeropteran Campsurus sp. and Ceratopogonidae (biting midges).

These organisms are all benthic and detritivorous. Some Chironomidae species live in

galleries burrowed in the sediment and feed generally by browsing the surface of the sediment

and collecting benthic algae and detritus (Lindegaard 1993). Moreover, there is evidence that

Chironomidae feeds also on methane oxidizing bacteria (Molineri & Emmerich 2010;

McCafferty 1975). Ceratopogonidae also feeds mainly on detritus (Braverman 1994).

The average δ13

C value of these benthic insects is -37.3‰ while detritus (particulate organic

material), their main source of food, usually has δ13

C values ranging from -32 to - 26‰

(Wantzen et al., 2002). The other food source for these organisms is benthic algae whose δ13

C

range is on the order of 20‰ in tropical lakes (Hecky & Hesslein 1995; France 1995).

Because the benthic insects were much more depleted in 13

C than detritus and benthic algae, it

is possible to assume that they consumed another source of carbon which had at least an equal

δ13

C value or lower if the 1‰ enrichment between food and consumer is considered. Methane

oxidizing bacteria (MOB) were probably the other source of carbon for the benthic insect

larvae as Chironomidae are known to feed on (Molineri & Emmerich 2010; McCafferty 1975,

Kiyashko et al. 2001). MOB have a δ13

C that can be as low as -80 to -50 ‰ (Jones & Grey

2004); Yasumo et al. (2012) report a contribution of 45.3% from MOB to the diet of

Chironomidae. A contribution of MOB to the diet of the three Chironomidae species,

Campsurus sp. and Ceratopogonidae would thus provide a plausible explanation of the δ13

C

values that were estimated for these benthic insects.

Cluster 2 was composed of the remaining organisms and at a distance of 0.35 it is divided into

two clusters; cluster 3, formed by zooplankton and Chaoborus sp. and cluster 4 which

grouped all fish, aquatic plants and crustaceans. Zooplankton includes different genera that

live in pelagic and benthic habitats and that have different feeding habits (Brönmark &

Hansson, 2005). However zooplankton feeds generally on algae, on zooplankton of smaller

size (Turner 1987) and on bacteria (Karlsson et al. 2004). The low δ13

C value exhibited by

zooplankton could not be explained by zooplankton receiving in its diet carbon of

photoautrophic origin. In fact even if it were assumed that the sampled zooplankton was

herbivore feeding exclusively on phytoplankton and particulate organic material (Grey and

Jones, 1999), their δ13

C value would reflect that of phytoplankton and particulate organic

material with a maximum enrichment of 1‰. The δ13

C of phytoplankton could not be

measured in this study due to methodological constraints. However the carbon isotopic

signature for dissolved inorganic carbon (DIC) was -12.8 ±0.4‰. Using numbers of average

fractionation of -14.4 ± 3.5‰ (Smyntek et al., 2012), the average δ13

C value for

phytoplankton in the lake could be assumed to be -27.2±3.9‰. Other studies in the Pantanal

estimate the average δ13

C value for phytoplankton to range from -37±3‰ to -29.7±3.59‰

(Leite et al., 2002; Lopes et al., 2006; Manetta et al., 2003). If zooplankton were assumed to

be predators, their carbon isotopic signature would be more enriched in 13

C relative to that of

primary consumers due to the successive fractionations from primary photoautotrophs to

primary consumers. The low carbon isotopic signature of zooplankton (-42‰) indicated

therefore that zooplankton was consuming preferably food sources that were more depleted in 13

C than the photoautotrophs in the lake. A possible source of carbon which is much depleted

and which could likely lead to the low carbon isotopic signature exhibited by zooplankton and

17

Chaoborus sp. was most probably MOB. There is indeed increasing evidence that

zooplankton feeds on MOB (e.g. Kankaala et al. 2006; Bastviken et al. 2003; Sanseverino et

al. 2012). Zooplankton can in fact reach MOB in the bottom of the lake by diving (Maddrell

1998). Alternatively, MOB can be a source of organic carbon and energy to zooplankton

through protozoans that feeds on these bacteria and that are in turn eaten by zooplankton

(Karlsson et al. 2004). As for Chaoborus sp. larvae, they live in the bottom sediment but

ascend into the water column (Wedmann & Richte 2007; Maddrell 1998) where they prey on

zooplankton and small insect larvae (Lewis 1997, Brömark & Jansson 2005). They can

consume also algae (Arcifa 2000). Considering the 1‰ maximum enrichment of δ13

C value

between a consumer and its diet (De Niro & Epstein, 1978; Peterson & Fry 1987), the δ13

C

value of Chaoborus sp. (-40.23‰) was consistent with the predation of Chaoborus sp. on

zooplankton (-42‰) and indicated that zooplankton was the major diet of Chaoborus sp.

whereas other organisms such as insects larvae made a marginal portion of the diet of

Chaoborus sp. in the studied lake.

Within cluster 4, three clusters were identified at a distance of 0.25. The first one (cluster 5)

was composed of S. marginatus, Serrasalmus sp., A. pantaneiro and P. nattereri. All these

four species are carnivorous fish whose diet consists mainly of fish (Kinski 2010; Peretti &

Andrian 2007; Correa et al. 2011). Insects, worms, crustaceans and other invertebrates are

also part of their diet. These four species had the highest δ15

N values among the organisms

that were analyzed, with S. marginatus having the highest δ15

N signature.

The second (cluster 6) included Trichodactylus sp., Hypostomus sp., T. argenteus, A.

bimaculatus, P. galeatus, H. temporalis and the plants E. crassipes and Gramineum. Most of

these organisms feed on plant material and terrestrial or aquatic insects and other invertebrates

as well as on detritus. Tetragonopterus argenteus, A. bimaculatus and P. galeatus are

omnivore with tendency to herbivory-invertivory (Leite et al. 2002; Correa et al. 2011; Peretti & Andrian 2008; Claro-Jr et al. 2004). Trichodactylus sp. and Hypostomus sp. are herbivore-

detritivorous (Burress & Gangloff 2013; Venancio & Leme 2010, da Silva et al. 2012; Pound

et al. 2010; Winemiller & Jepsen 1998). Both consume mainly detritus but Hypostomus sp.

feeds also on algae (Pound et al. 2010; daSilva et al. 2012; Winemiller & Jepsen, 1998). T.

argenteus and P. galeatus can also feed on fish (Pereira et al. 2007; Correa et al. 2009; Claro-

Jr et al., 2004).

The third (cluster 7) could be further divided at a distance of 0.15 into 2 clusters. The first

(cluster 8) comprised Loricaria sp., Brachyhypopomus sp., L. cf macrocephalus, S. macrurus,

Macrobrachium sp.2, A. gripus, P. squamoralevis, Cyphocharax sp., S. brevipinna and L.

friderici. The common characteristic of the organisms in this cluster is that all are benthic

dwellers feeding totally or partially on detritus and benthic invertebrates. Potamorhina.

squamoralevis, Cyphocharax sp. and S. brevipinna are iliophagous (Lopes et al. 2009; Pereira

et al. 2007). These three species feed also on detritus and algae. Anadora gripus is invertivore

(Correa 2005). The remaining species in this cluster consume, in addition to detritus, dead or

living benthic invertebrate. Sternopygus macrurus for instance is a predator of aquatic insect

larvae (Marrero & Winemiller 1993; Merona & Merona 2004). Chironomids were found in

the gut of L. cf macrocephalus. Leporinus friderici preys on microcrustaceans, insect larvae

and zooplankton but feeds also on benthic algae (Albrecht & Caramaschi 2003).

Cluster 9 was composed of G. balzani, P. australis, T. pantanensis, P. paraguayensis,

Macrobrachium sp.1, Hemigramus sp. and Crenicichla sp. Most of the fish species in this

sub-cluster are omnivore with a tendency to invertivory. Poptella paraguayensis, G. balzani,

Hemigramus sp. and T. pantanensis for instance feed mainly on aquatic and terrestrial

invertebrates and a small portion of the diet is made of detritus (Correa et al. 2011; Carvalho

18

et al. 2013). It is worth to note that zooplankton is part of the diet of P. paraguayensis and G.

balzani especially during the low water season (Correa et al. 2011). Some of these organisms

prey also on fish of smaller size. Macrobrachium sp. is a predator of Astyanax fasciatus

(Wilson et al. 2004) but its diet is primarily composed of aquatic invertebrates and periphytic

algae attached on the roots of macrophytes (Montoya 2003). Crenicichla sp. and G. balzanii

adapt their feeding behavior and shift from a fish dominated diet (Jepsen & Winemiller 2002)

to an invertebrate-based diet according to the seasonal availability of food resources (Gibran

et al. 2001, Correa et al. 2011).

Cluster 1

Cluster 9

Cluster 6

Cluster 5

Cluster 8Cluster 2

Cluster 3

Cluster 7

Cluster 4

Figure 6: dendrogram from UPGMA cluster analysis based on a Gower similarity matrix

19

A Kruskal-Wallis test allowed to reject the null hypothesis (df = 5, p < 0.01 at a significance

level of 0.05) stating that all the six clusters had statistically similar δ13

C. Table 2 shows the

results of the pairwise comparisons among clusters based on δ13

C values of the organisms that

were in each cluster.

Table 3: P-values of pairwise comparison among clusters based on del δ13

C values

cluster 1 Cluster3 cluster 5 cluster 6 cluster 8

cluster 1 Cluster 3 0.525 cluster 5 0.002 0.002 cluster 6 0.000 0.000 0.650 cluster 8 0.305 0.158 0.009 0.000 cluster 9 0.025 0.021 0.206 0.051 0.129 The significance level is 0.05

Organisms in cluster 1 had a similar median δ13

C as organisms in cluster 3. Organisms in

these two clusters consumed food resources that were depleted in 13

C which led to low δ13

C

values compared to the rest of organisms in the studied lake. Organisms in both clusters fed

on MOB which are usually much depleted in 13

C (Jones & Grey 2004). However, the diet

composition was probably different for the two clusters. Zooplankton and Chaoborus sp.

consumed probably a lower proportion of MOB than the benthic insects did. In fact Jones et

al. (2008) report that the portion of MOB in Chironomidae diet can be as high as 50% while

this portion for zooplankton and Chaoborus sp. is estimated to be inferior to 30%

(Sanseverino et al.. 2012, Yasuno et al., 2012). Zooplankton feeds also on phytoplankton

which is more depleted in 13

C than benthic algae (Manetta et al. 2002; Lopes et al 2006) that

benthic insects consume. A mixed diet composed of MOB and phytoplankton for

zooplankton, and MOB and benthic algae for benthic insects, could therefore lead to a similar

carbon isotopic signature for zooplankton and benthic insects.

Organisms in cluster 1 and cluster 3 occupied however different trophic positions. The trophic

position of zooplankton and Chaoborus sp. was estimated at 3.1; this supports the previous

suggestion that the zooplankton collected were primarily predators. The average trophic

position of the five benthic insects was 2.04 consistent with their herbivory-detritivory

feeding habit (Fry 1991). The difference in the trophic positions of zooplankton and

Chaoborus sp. and that of the benthic insect, combined with a similar carbon isotopic

signature could indicate that zooplankton and Chaoborus sp. fed on Chironomidae, the

Ceratopogonidae and Campsurus sp.

Cluster 1 and cluster 8 had statistically similar median δ13

C values. The similar median δ13

C

could be explained by both clusters having overlapping diet as organisms in both clusters fed

on detritus, sediment and benthic algae. However a more likely explanation would be that

organisms in cluster 1 contributed to the diet of organisms in cluster 8. In fact all organisms in

cluster 8 were omnivore and consumed benthic invertebrates in addition to detritus/sediment

and benthic algae. The only exceptions were P. squamoralevis and S. brevipinna which are

specialized iliophagous that eat mud (Castro & Vari 2004; Lopes et al. 2009). Moreover, the

average trophic position of organisms in cluster 8 was estimated at 2.7 confirming that these

organisms were omnivore (Fry 1991). Furthermore, the average δ15

N value of animals in

cluster 8 was 2.24‰ higher than that of animals in cluster 1 or en equivalent of 0.6 trophic

20

level if the 3.4‰ enrichment of 15

N between two successive trophic levels is considered (Post

2002).

The δ13

C signature of cluster 1 was different from that of clusters 5, 6 and 9, indicating that

organisms in cluster 1 had a different diet composition than that of the three clusters. Indeed,

organisms in cluster 5 were mainly piscivore, while animals in cluster 9 were mainly

invertivore and organisms in cluster 6 relied on various littoral food resources such as fruits

and seeds from high plants, periphyton, terrestrial and aquatic insects and detritus. The

average trophic position of animals in cluster 6 was 2.6 indicating that these animals occupied

trophic positions between the 5 benthic insects of cluster 1 and the bottom-feeders in cluster

8.

Cluster 3 had a similar median δ13

C value as cluster 8. This could indicate that organisms in

both clusters had overlapping diets as both consumed benthic insect larvae and algae.

Alternatively zooplankton and Chaoborus sp. could be part of the diet of animals in cluster 8

which consumed also invertebrates. However the calculated trophic position for zooplankton

and Chaoborus sp (3.1) was higher than that of animals in cluster 8 (2.7). The calculated

trophic position of zooplankton and Chaoborus sp. did not reflect the the actual trophic

position of zooplankton and Chaoborus sp. in the lake under study. It indicated that these

organisms were among top predators in the lake meaning that their trophic position was

superior to the average trophic position of the invertivore cluster 9 (3.0). This was surprising

because cluster 9 included omnivore animals which had a strong tendency to invertivory,

some fish species in this cluster being even predators of other fishes as previously mentioned.

Only the carnivorous fish in cluster 5 had indeed an average trophic position (3.3) higher than

that of zooplankton and Chaoborus sp.. Vander Zanden & Rasmussen (1999) hypothesize that

denitrification and ammonification produce high δ15

N values in profundal organisms. A

higher δ15

N signature in profundal organisms would thus be translated in higher δ15

N up in

the food web. Obviously, this explanation did not apply to the lake food web as

Chironomidae, Ceratopogonidae, Campsurus sp. and the iliophagous fishes for example

exhibited conservative δ15

N values that were consistent with their feeding habits and their

trophic position in the food web. Another explanation for a high δ15

N signature in

zooplankton would be that the lake received allochthonous nitrates inputs thus leading to high

δ15

N values in primary producers on which zooplankton grazed (Mullin et al. 1984). The two

plants that were sampled in this study, E. crassipes and Gramineum exhibited significantly

different δ15

N values (8.2 and 5.6‰ respectively) making it difficult to confirm the possible

effect of allochthonous nitrates. Moreover, Wantzen et al. (2002) report that high δ15

N values

in macrophytes are regionally common in the Pantanal.

Cluster 5 had a similar median δ13

C as that of clusters 6 and 9 indicating diet overlap as

organisms in the three clusters prey on invertebrates. However all organisms in clusters 5

were fish species whose diet is composed mainly of fish (Peretti & Andrian, 2008; Correa et

al. 2011). Moreover fish species in cluster 5 occupied the highest trophic position (3.3 in

average) among the sampled organisms in the lake under study. A similar median δ13

C of

cluster 5 on one hand and cluster 5 and 9 on the other hand meant most probably that fish in

cluster 5 consumed organisms belonging to clusters 6 and 9.

Cluster 6 had a similar median δ13

C value as organisms in cluster 9 indicating also overlap in

their diets as animals in both clusters consumed terrestrial and aquatic invertebrates and

detritus. Moreover some species such as G. balzanii and Crenicichla sp. in cluster 9 and T.

argenteus in cluster 6 could also be fish predators. Even though both clusters seemed to rely

on the same food resources, their rather different trophic positions indicated that organisms in

21

clusters 9 (average trophic position 3.0) relied more on a predatory feeding strategy and thus

on invertebrates than animals in cluster 6 (trophic position 2.6).

Cluster 6 had different median δ13

C compared to that of cluster 8 but their trophic positions

were similar, 2.6 and 2.7 in average for cluster 6 and cluster 8 respectively. This meant that

animals in the two clusters consumed organisms that had different C isotopes signatures but

that occupied equivalent trophic positions in the food web. In fact, animals in both clusters

consumed producers, primary and secondary consumers; this explained why the two clusters

had similar trophic positions. However, the producers consumed by animals in cluster 6 were

not the same as those consumed by animals in cluster 8 and had likely different C isotopic

signatures. In the case of animals in cluster 6, the producers were composed of macrophytes,

terrestrial fruits and seeds whereas in the case of animals in cluster 9, the consumed producers

included benthic algae, detritus and MOB. MOB are more depleted in 13

C (δ13

C values

ranging from -80 to -50‰) than other phototrophs such as macrophytes and algae (δ13

C

values ranging from -37 to -26‰). As for primary and secondary consumers eaten by animals

in the two clusters, animals in cluster 6 preyed mainly on terrestrial and aquatic insects

whereas animals in cluster 8 consumed mainly benthic insects and zooplankton which tend to

be the most depleted in 13

C among the invertebrates living the lake. As a result animals in

cluster 8 exhibited lower δ13

C values than animals in cluster 6.

Cluster 8 and cluster 9 had similar median δ13

C value which may be explained by animals in

both clusters feeding on similarly 13

C-depleted food resources such as benthic insects, algae

and detritus (for some species in cluster 9). But the slightly higher average trophic position of

cluster 9 than cluster 8 indicated that the former cluster included more predators than the last

cluster.

After allocating a trophic position to each animal and in combination with results of the

cluster analysis, it was possible to disentangle the trophic relations among the lacustrine

organisms and to represent the food web of the lake as shown in Figure 6. This diagram

reproduce in a more visual way what the isotopic ratio already revealed about the lake food

web: omnivory is prevalent in this food web. Animals in the lake relied generally on a mixed

diet and most particularly they fed on different trophic levels. A detailed study on the

composition of the diet of the animals and the use of a source mixing model would estimate

more accurately the contribution of autochthonous and allochthonous photoautotrophic

carbon and other source of carbon such as biogenic methane.

Figure 7 (a and b) shows the central role played by detritus in supporting the lake food web.

Detritus was the main source of food for Chironomidae, Ceratopogonidae, Campsurus sp. and

the mud-eater fish species. It was also a significant part of the diet of other bottom-feeding

animals. Even omnivorous fish with a tendency to invertivory had a portion of detritus in their

diet. The mineralization of detritus by bacteria avail nutrients to macrophytes and algae which

support herbivorous animals (Alvim & Peret, 2004).

The sustainability of a food web similar to that of the lake under study would therefore

requires among other measures safeguarding the supply in quantity and quality of detritus in

the lake. This raises the question of the management of the lake and of the floodplain as a

whole. In fact the material that supplies a lake detritus is generally composed of

autochthonous organic material from macrophytes, algae and animals living in the lake and

also of allochthonous organic material from the surrounding vegetation (Alvim & Peret, 2004;

Gratton & Vander-Zanden, 2009). In the context of the Pantanal, the Amazonian forest and

the flooding pulse are considered as essential for the production and transport of detritus to

aquatic food webs (Wantzen et al., 2008; Alvim & Peret, 2004). Some human activities can

have adverse consequences on the production and transport of detritus. Deforestation reduces

22

the amount of terrestrial organic material entering into the lake. Damming of rivers hinders

the transfer of sediment rich in organic material to lakes, the pollution of water bodies by

domestic and industrial waste may interfere with the decomposition of detritus by destroying

the decomposers and fertilizers from intensive agriculture may cause eutrophication of lakes

(Wantzen et al., 2008; Alvim & Peret, 2004).

Nutrients and energy contained in detritus enter the lake food web through detritivorous and

herbivorous animals as these animals are consumed by carnivorous species. The exploitation

of a lake should therefore reserve special protection for detritivorous animals of commercial

importance because their removal for human consumption may trigger cascading effects

which would ultimately result into the decline of the carnivore which generally include

economically important species (Wantzen et al., 2008).

Figure 7a: schematic representation of the lake food web. Carnivorous fish were the

Sarrasalmidae species in cluster 5. Omnivore fishes with tendency to herbivory-invertivory

were fish species in cluster 6. Detritivore-invertivore fishes were omnivore bottom-feeder

fishes belonging to cluster 8. Omnivore fish with tendency to invertivory were fish species in

cluster 9. Arrows represent the relation “ eaten by”.

23

Figure 7b: schematic illustration of the food web in the shallow lake. Arrows represent the

relation “eaten by”. Detritus is composed of organic matter from autochthonous and

allochthonous origin

Principal component analysis

The most important component was δ13

C signature as it explained 89% of the variation in the

structure of the community while δ15

N accounted for the remaining 11% (Alisauskas, 1998).

The carbon isotopic ratio revealed a gradient in the use of 13

C-depleted food resources in the

ecosystem as organisms were ordinated from the least depleted (at the far right) to the most

depleted (far left) as indicated by the arrow on Figure 8. Following this gradient, animals

feeding in the water column or on the surface were the least depleted. (e.g. A. bimaculatus and

T. argenteus) whereas zooplankton, all the benthic insects and bottom-feeder animals were

the most depleted in 13

C. .

There seemed to be similarities between the gradient of δ13

C and that of the use of biogenic

methane by lentic biota. In fact, the importance of biogenic methane as a source of carbon and

energy seems to increase from animals feeding on the water surface to animals feeding in the

benthic habitat. This was highlighted by Sanseverino et al. (2012) in their analysis of MOB

fatty acids markers in different animals including fish species. The contributions of biogenic

methane in the lake under study was confirmed by the δ13

C value of sediment which was -

75‰, consistent with the range of -80 to -50‰ generally exhibited by biogenic methane

(Sansone et al., 1999). However this gradient of use of biogenic methane is yet to be

confirmed because the pathways of methane as a food source of carbon and energy are not yet

fully understood. If this gradient were confirmed, it would emphasize the important

contribution of biogenic methane to the food web of the lake under study. Consequently

modeling energy flow in the food web of the lake would need to consider biogenic methane as

another energy pathway in addition to the traditional phototrophic primary source of energy.

24

Figure 8: Principal component analysis:principal component 1 is δ13

C and principal

component 2 is δ15

N. The arrow shows the gradient in δ13

C (from the least to the most

depleted in 13

C)

4. Conclusions This study described the structure of a food web in a shallow lake of the Pantanal flood plain

in Brazil by using carbon and nitrogen stable isotopes. Six trophic groups were described.

Potential sources of food were identified and discussed for each trophic group and trophic

relations among the six trophic groups were described, for each organism in the food web a

trophic position were allocated.

Omnivory was found to be prevalent in the food web of the lake. Omnivorous organisms in

this lake had different sources of food, fed on different trophic levels and find their food in

different habitats of the lake. The prevalence of omnivory has theoretical implications on the

design of model used to study and predict community dynamics in general. Particularly top-

down control models, that are based on the assumption that omnivory is a rare phenomenon,

need to be adjusted when applied to this lake and other ecosystems presenting similar

features. From a practical perspective, the prevalence of omnivory implies that the

management of the lake should reserve special care for omnivorous species as their removal

would have adverse impact on the persistence and resilience of the ecosystem.

Detritus played a central role in supporting the food web of the lake. Therefore, the

sustainability of the lake food web would require among other measures safeguarding the

supply in quantity and quality of detritus in the lake. This calls for appropriate management of

the lake and of the Pantanal flood plain as a whole.

The carbon isotopic ratios of animals in the lake indicated that biogenic methane is probably a

source of carbon and energy used by animals living in the lake, especially animals feeding in

the benthic habitat. If this result were confirmed, then modeling energy flow in the similar

25

lakes should take into consideration that primary sources of energy in the lake include

biogenic methane in addition to the traditional phototrophic sources.

It would be interesting to investigate, with source mixing models, the contribution of

autochthonous and allochthonous carbon sources to the lake detritus and the contribution of

biogenic methane to the diet of the animals living in the lake.

5. Acknowledgements I am grateful to Dr Sanseverino of the University Federal of Rio de Janeiro, Brazil who

guided me in the field of stable isotope analysis. She provided valuable comments that helped

me interpret the results of this study in the context of the Pantanal floodplain. She always

managed to find time to discuss and answer my many questions despite her ongoing research

work. I thank my supervisor David Bastviken for having sparked my curiosity about the

potential importance of methane for food webs. His inputs allowed also improve the structure

and content of this document. A special thanks to my wife who provided supports and

encouragements during times of doubts.

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i

Appendices Table 1: δ

13C and δ

15N values of organisms and their foraging habits

Organism Species δ

13C vs

PDB

δ15

N vs

air

Feeding habit and

main food items1

Foraging behavior Reference

Macrophyte Eichornia crassipes -27.9 8.1 n.a n.a

Macrophyte Gramineum -29.1 5.7 n.a n.a

Insect Chironomidae sp.3 -35.4 4.5 Detritivore and

herbivore (periphyton)

benthivorous, scrapers, collector-

gatherers, engulfers

Merritt & Cummins 1996

Lindegaard, 1993

Grey et al., 2004

Insect Chironomidae sp.2 -36.2 5.5 Detritivore and

herbivore

benthivorous, scrapers, collector-

gatherers, engulfers

Merritt & Cummins 1996

Lindegaard, 1993

Insect Chironomidae sp.1 -37.1 4.3 Detritivore and

herbivore

benthivorous, scrapers, collector-

gatherers, engulfers

Merritt & Cummins 1996

Lindegaard, 1993

Insect Ceratopogonidae -38.1 5.8 Detritivoreand

herbivore .benthivorous, scraper-collector

Merritt & Cummins 1996

Ronderos et al. 2004

Braverman 1994

Insect Campsurus sp. -39.7 4.3 Detritivore (detritus in

sediment) bottom collector-gatherer

Zilli, 2012

Leal & Esteves, 2000

Insect Chaoborus sp. -40.2 8.6 carnivore(zooplankton) predator

Wedmann and Richter. 2007

Swift & Fedorenko, 1975

Arcifa, 2000

Castilho-Noll & Arcifa, 2007

1 Feeding habit and main food items for each organisms in this column are from the literature provided in the last column of the table

ii

Crustacean Zooplankton -42.0 8.6

Omnivore (algae,

microzooplankton,

detritus)

Filter feeders; grazers

Kleppel et al. 1988

Turner, 1987

Calheiros, 2003

Crustacean Trichodactylus sp. -31.5 6.5 herbivore-detritivore Collector-gatherers Burress &Gangloff, 2013

Calheiros 2003

Crustacean Macrobrachium sp.1 -33.7 8.1

.Omnivore (aquatic

invertebrates, periphytic

algae attached on the

roots of aquatic

macrophytes, detritus);

Collector-gatherers

Montoya, 2003

Wilson et al., 2004

Calheiros 2003

Brito et al., 2006

Crustacean Macrobrachium sp.2 -35.3 7.5

Omnivore (aquatic

invertebrates, periphytic

algae attached on the

roots of aquatic

macrophytes, detritus);

Collector-gatherers

Montoya, 2003

Wilson et al., 2004

Calheiros 2003

Brito et al., 2006

iii

Fish Tetragonopterus argenteus

Cuvier, 1817 -27.7 7.1

Omnivore with

tendency to herbivory-

invertivory (terrestrial

insects,

microcrustaceans and

detritus)

Shallow-water, middle

Leite et al., 2007

Pereira et al., 2007

Corrêa et al., 2009

Resende et al., 2000

Fish Astyanax cf. bimaculatus

Reinhardt, 1874 -28.0 7.2

Omnivorous with

tendency to herbivory-

invertivory ( plant

debris,

microcrustaceans,

insects and detritus)

collector in the water column

Neiff et al., 2000

Vilella et al. 2002

Arcifa et al., 1991

daSilva et al. 2012

Fish Parauchenipterus galeatus

Linnaeus, 1766 -29.6 7.7

Omnivorous with

tendency to herbivory-

invertivory (fruits,

seeds and terrestrial

invertebrates; also

aquatic insects and

other invertebrates

(crustaceans and

mollusks) but also

detritus

Collector in all the compartments of

the water bodies, from surface to

bottom

Claro-Jr et al:, 2004

Peretti & Andrian, 2008

iv

Fish Pygocentrus nattereri(Kner,

1860) -29.9 9.2

Carnivore (fishes,

insects) Lurking predator, scavenger Machado, 2003

Fish Hypselecara temporalis

(Gunther, 1862) -29.9 7.2

Authochtonous

insectivore Predator Carvalho et al., 2013

Fish Acestrorhynchus pantaneiro

Menezes, 1992 -30.0 9.0

Carnivore (mainly fish,

but also shrimps) Motile stalkers, wait predador

Machado, 2003

Hahan et al., 2000

Krinski, 2010

Fish Hypostomussp. -31.0 5.6

Omnivore with

tendency to herbivory-

invertivory (benthic

algae, detritus, and

microorganisms)

Grazer; collector-sucker

Winemiller & Jepsen 1998

daSilva et al., 2012

Pound et al., 2010

Fish Serrasalmus sp. -31.0 8.7 Carnivore (mainly fish

but also invertebrates)

Lurking predator, scavenger; predator,

mutilator

Machado, 2003

Peretti & Andrian 2008

Fish Serrasalmus marginatus

Valenciennes, 1847 (young) -31.9 10.0

Carnivore (mainly fish

but alsoinvertebrates

and detritus)

Lurking predator, scavenger; predator,

mutilator

Manetta et al., 2003

Peretti & Andrian 2008

v

Fish Gymnogeophagus balzanii

(Perugia, 1891) -31.9 7.5

Omnivore with

tendency to invertivory

(mainly insects but also

fish) t

Bottom-feeder Corrêa et al., 2011

Fish

Pyrrhulina australis

(Eigenmann & Eigenmann,

1889)

-32.4 8.1

Omnivore with

tendency to invertivory

(insects but also algae,)

Surface-feeder Machado, 2003

Fish Triportheus pantanensis

Malabarba, 2004 -33.0 8.1

Omnivore with

tendency to herbivory-

invertivory (terrestrial

insects, algae, fruits)

Collector at the water surface or in the

water column

Corrêa et al. 2011;

Costa-Pereira et al. 2011

Corrêa et al., 2009

Fish Hemigramus sp. -33.5 8.5

Omnivore with

tendency to invertivory

(mainly insects but

alsodetritus,)

Collector-gatherer Machado, 2003

Fish Loricaria sp. -33.6 7.3

Omnivore with

tendency to detritivory-

invertivory (detritus,

insect larvae)

Bottom-feeder

Salvador-Jr et al. 2009

Thomas & Rapp Py-Daniel,

2008

Fish Poptella paraguayensis

(Eigenmann, 1907) -33.7 7.7

Omnivore with

tendency to invertivory

( terrestrial and aquatic

insects, zooplankton,

detritus)

Surface-feeder Pereira et al., 2007

Corrêa et al., 2011

Fish Brachyhypopomus sp. -34.6 7.2

Omnivore with

tendency to detritivory-

invertivory (insects,

detritus)

Scavenger Machado, 2003

vi

Fish Leporinus cf. macrocephalus

Garavello & Britsk, 1988 -34.7 7.1

Omnivore with

tendency to detritivory-

invertivory

(macrophytes,

crustaceans)

Collector-gatherer (bottom-feeder), Giora et al., 2008

Machado, 2003

Fish Sternopygus macrurus(Bloch

& Schneider, 1801) -34.8 7.8

Omnivore with

tendency to detritivory-

invertivory (benthic

invertebrates, aquatic

insect larvae).

Predator,.grasp-sucker

Marrero&Winemiller1993

Merona&Merona2004

Fish Crenicichla sp. -35.5 8.5

Omnivore with

tendency to invertivory

(mainly insects but also

fish)

Lurking predator, scavenger Gibran et al., 2001

Sazima 1986

Fish Potamorhina squamoralevis

(Braga & Azpelicueta, 1983) -36.1 6.5 Detritivore, (detritus) Grazer, burrower (bottom-feeder) Castro & Vari, 2004

Fish Cyphocharax sp. -36.1 6.8

Omnivore with

tendency to detritivory-

invertivory (detritus,

algae, zooplankton)

Grazer, burrower (bottom-feeder)

Lopes et al., 2009

Vari, 1992

Pereira et al., 2007

Fish Anadoras grypus (Cope, 1872) -36.5 7.8

Omnivore with

tendency to detritivory-

invertivory (detritus and

bottom invertebrates)

Grazer, burrower (bottom-feeder) Corrêa, 2005

vii

Fish Leporinus friderici Bloch,

1794 -36.6 7.1

Omnivore with

tendency to detritivory-

invertivory (items

associated to bottom

substrates, i.e. benthic

filamentous algae,

microcrustaceans, insect

larvae and

detrituszooplankton

Grazer, burrower, fin-biting and

nibbler

Albrecht & Caramaschi, 2003

Manetta et al., 2003

Fish

Steindachnerina brevipinna

(Eingenmann & Eingenmann,

1889)

-36.7 6.6

Omnivore with

tendency to detritivory

(plant detritus,;.algae,

detritus and sediment;

Grazer, burrower, bottom-feeder

Winemiller & Jepsen, 1998

Pereira et al., 2007

Lopes et al., 2009

viii

Table 2: Trophic position of the sampled animals

Species δ15N Trophic position

Campsurus sp. 4.3 1.8

Chironomidae spp. 4.8 2.0

Hypostomussp. 5.6 2.2

Ceratopogonidae 5.8 2.3

Trichodactylus sp. 6.5 2.5

Potamorhina squamoralevis (Braga & Azpelicueta, 1983) 6.5 2.5

Steindachnerina brevipinna (Eingenmann & Eingenmann, 1889) 6.6 2.5

Cyphocharax sp. 6.8 2.6

Tetragonopterus argenteus Cuvier, 1817 7.1 2.7

Leporinus friderici Bloch, 1794 7.1 2.7

Leporinus cf. macrocephalus Garavello & Britsk, 1988 7.1 2.7

Hypselecara temporalis (Gunther, 1862) 7.2 2.7

Brachyhypopomus sp. 7.2 2.7

Astyanax cf. bimaculatus Reinhardt, 1874 7.2 2.7

Loricaria sp. 7.3 2.7

Gymnogeophagus balzanii (Perugia, 1891) 7.5 2.8

Macrobrachium sp.2 7.5 2.8

Parauchenipterus galeatus Linnaeus, 1766 7.7 2.8

Poptella paraguayensis (Eigenmann, 1907) 7.7 2.9

Sternopygus macrurus(Bloch & Schneider, 1801) 7.8 2.9

Anadoras grypus (Cope, 1872) 7.8 2.9

Triportheus pantanensis Malabarba, 2004 8.1 3.0

Pyrrhulina australis (Eigenmann & Eigenmann, 1889) 8.1 3.0

Macrobrachium sp.1 8.1 3.0

Hemigramus sp. 8.5 3.1

Crenicichla sp. 8.5 3.1

Zooplankton 8.6 3.1

Chaoborus sp. 8.6 3.1

Serrasalmus sp. 8.7 3.2

Acestrorhynchus pantaneiro Menezes, 1992 9.0 3.2

Pygocentrus nattereri(Kner, 1860) 9.2 3.3

Serrasalmus marginatus Valenciennes, 1847 (young) 10.0 3.5

ix

Glossary

This section includes words that are in the text and that are commonly used in aquatic

ecology. Definitions are mainly from Brönmark & Hansson (2005) and Wetzel (2001).

Abiotic factors: physical and chemical factors

Algivore: an organism that eats algae

Allochthonous material: organic material produced outside a water body such as a lake

Aphotic zone: zone of a water body where light availability is insufficient to allow

photosynthesis.

Autochtonous material: organic material produced within a water body such as a lake

Autotrophic organism: organism that have the ability to synthesize nutritive organic

molecules from inorganic materials (e.g. carbon dioxide and nitrogen) using light or chemical

energy.

Benthic: part of a water body comprising the bottom, the sediment surface, and some sub-

surface layers.

Biodiversity: the extent of genetic, taxonomic and ecological variability over all spatial and

temporal scales

Biomass: total mass of living organisms per unit of surface or volume

Biota: the plant and animal life of a specific location

Carnivore: an organism that derives its energy and nutrient requirements from a diet

consisting mainly or exclusively of animal tissue

Compensation depth: the depth at which there is sufficient light for photosynthesis to

balance respiration

Decomposer: an organism that breaks down dead or decaying organisms using biochemical

reactions that convert the prey tissue into metabolically useful chemical products.

Decomposers include bacteria, fungi and worms.

Detritivore: an organism that feeds on detritus

Detritus: dead organic material

Ecosystem: all organisms and their environment in a specific location.

Epilimnion: the stratum of warm, well mixed water above the thermocline

Food web: the pattern of flows of energy and materials among organisms that results when

some organisms eat or consume other living organisms or their parts.

Herbivore: organisms that feed exclusively on primary producers

Hypolimnion: the stratum of cool water below the thermocline

Iliophagous: an organism that feeds on mud at the bottom of a lake or pond

Invertivore: organism that feeds on invertebrates such as insects or crustaceans

Isotopes: atoms with the same number of protons and electrons but differing numbers of

neutrons

x

Keystone species: a species that has a disproportionately strong effect on other species and

plays a crucial role in maintaining the organization and diversity of their ecological

communities.

Lentic: pertaining or living in still water such as lake, pond, swamp

Limnology: the study f freshwater communities and their interactions with physical, chemical

and biotic environmental variables

Littoral zone: the shallow nearshore part of a lake or pond characterized by light penetration

to the bottom

Lotic: relating or living in rapidly flowing water

Macrophytes: macroscopic forms of aquatic vegetation

Metaphyton: a group of algae found aggregated in the littoral zone which is neither strictly

attached to substrata nor truly suspended. The metaphyton commonly originates from true

floating algal populations that aggregate among macrophytes and debris of the littoral zone as

a result of wind-induced water movements.

Nitrification: bacterial transformation of ammonium to nitrate

Omnivore: an organism that feeds on organisms from different trophic levels

Pelagic zone: the open water part of a lake of pond

Periphyton: microorganisms that live attached to surfaces projecting from the bottom of a

freshwater aquatic environment

Photic zone: zone of a water body where light availability is enough to allow photosynthesis

Phototrophic: an organism using photosynthesis as carbon source

Phytoplankton: primary producers that float freely in the water

Piscivore: an organism that eats fish

Predator: an organism that feeds on living animals

Profundal zone: the sediment zone at depths beyond where phototrophic organism can live

Sediment: material that settles to the bottom of a water body

Thermocline: the stratum between the epilimnion and hypolimnion exhibiting a marked

thermal change.

Trophic level: functional classification of organisms in a food web with respect to their

feeding relationships.

Zooplankton: animals suspended in water with limited powers of locomotion. Freshwater

zooplankton are dominated by four major groups of animals: protozoa, rotifers, and two

subclasses of the Crustacea, the cladocerans and copepods.