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Trophic interactions occur when one organism feeds on another. The three main types of trophic interactions are predation (figure (PageIndex{a})), herbivory, or parasitism. During these interactions, one species benefits by gaining food at the expense of the other, which either dies or loses nutrients, tissues, or organs (such as leaves). Trophic interactions involve the flow of energy, and the trophic interactions in a community can be represented by food chains and food webs.

Figure (PageIndex{a}): A hawk (Buteo jamaicensis) eats a vole (Microtus californicus), exemplifying predation, a common trophic interaction. Image by Jrockley (public domain).

Trophic Level

A trophic level is the group of organisms within an ecosystem which occupy the same level in a food chain. There are five main trophic levels within a food chain, each of which differs in its nutritional relationship with the primary energy source. The primary energy source in any ecosystem is the Sun (although there are exceptions in deep sea ecosystems).

The solar radiation from the Sun provides the input of energy which is used by primary producers, also known as autotrophs. Primary producers are usually plants and algae, which perform photosynthesis in order to manufacture their own food source. Primary producers make up the first trophic level.

The rest of the trophic levels are made up of consumers, also known as heterotrophs heterotrophs cannot produce their own food, so must consume other organisms in order to acquire nutrition.

The second trophic level consists of herbivores, these organisms gain energy by eating primary producers and are called primary consumers.

Trophic levels three, four and five consist of carnivores and omnivores. Carnivores are animals that survive only by eating other animals, whereas omnivores eat animals and plant material.

Trophic level three consists of carnivores and omnivores which eat herbivores these are the secondary consumers.

Trophic level four contains carnivores and omnivores which eat secondary consumers and are known as tertiary consumers.

Trophic level five consists of apex predators these animals have no natural predators and are therefore at the top of the food chain.

Due to the way that energy is utilized as it is transferred between levels, the total biomass of organisms on each trophic level decreases from the bottom-up. Only around 10% of energy consumed is converted into biomass, whereas the rest is lost as heat, as well as to movement and other biological functions. Because of this gradual loss of energy, the biomass of each trophic level is often viewed as a pyramid, called a trophic pyramid.

It is important to note that organisms within the trophic levels of natural ecosystems do not generally form a uniform chain, and that many animals can have multiple prey and multiple predators the non-linear interactions of trophic levels can therefore be best viewed as a food web rather than a food chain. However, disruption within one of the trophic levels, for example, the extinction of a predator, or the introduction of a new species, can have a drastic effect on either the lower or higher trophic levels.

Phages Actively Challenge Niche Communities in Antarctic Soils

By modulating the structure, diversity, and trophic outputs of microbial communities, phages play crucial roles in many biomes. In oligotrophic polar deserts, the effects of katabatic winds, constrained nutrients, and low water availability are known to limit microbial activity. Although phages may substantially govern trophic interactions in cold deserts, relatively little is known regarding the precise ecological mechanisms. Here, we provide the first evidence of widespread antiphage innate immunity in Antarctic environments using metagenomic sequence data from hypolith communities as model systems. In particular, immunity systems such as DISARM and BREX are shown to be dominant systems in these communities. Additionally, we show a direct correlation between the CRISPR-Cas adaptive immunity and the metavirome of hypolith communities, suggesting the existence of dynamic host-phage interactions. In addition to providing the first exploration of immune systems in cold deserts, our results suggest that phages actively challenge niche communities in Antarctic polar deserts. We provide evidence suggesting that the regulatory role played by phages in this system is an important determinant of bacterial host interactions in this environment.IMPORTANCE In Antarctic environments, the combination of both abiotic and biotic stressors results in simple trophic levels dominated by microbiomes. Although the past two decades have revealed substantial insights regarding the diversity and structure of microbiomes, we lack mechanistic insights regarding community interactions and how phages may affect these. By providing the first evidence of widespread antiphage innate immunity, we shed light on phage-host dynamics in Antarctic niche communities. Our analyses reveal several antiphage defense systems, including DISARM and BREX, which appear to dominate in cold desert niche communities. In contrast, our analyses revealed that genes which encode antiphage adaptive immunity were underrepresented in these communities, suggesting lower infection frequencies in cold edaphic environments. We propose that by actively challenging niche communities, phages play crucial roles in the diversification of Antarctic communities.

Keywords: Antarctic soils archaea bacteria hypoliths phages viromics.

Copyright © 2020 Bezuidt et al.


The relationship between relative abundances…

The relationship between relative abundances of taxa and defense systems. (A) The distribution…

The relative abundances of the…

The relative abundances of the three CRISPR-Cas types as well as unclassified defense…

The distribution of CRISPR array…

The distribution of CRISPR array sizes in the hypolith metagenome and a groundwater…

Network visualization of the relationship…

Network visualization of the relationship between the hypolith virome, CRISPR-spacers, and reference data…

Gene architecture of the VirSorter…

Gene architecture of the VirSorter contigs with matches to multiple CRISPR array spacers.…


Despite the wide recognition of the coexistence of multiple interaction types linking species in nature [1–3], research on ecological networks has been massively dominated by studies on a single interaction at a time (e.g. trophic, competitive or mutualistic e.g. [4–6]). The implications of the diversity of interactions for ecological community dynamics and resilience remains therefore largely unknown, despite a recent growing interest in the ecological literature [7–10].

Among interaction types, feeding has massively dominated the literature [2], leading to the analysis of the structural properties of food webs on data sets and to the use of modeling to investigate the functional consequences of these structures (e.g. [4, 11–16]). Early on, Arditi and colleagues [17] proposed to integrate non-trophic interactions in such dynamical models as modifications of trophic interactions (so-called ‘rheagogies’). Building on that idea, Goudard and Loreau [18] investigated the effect of rheagogies on the relationship between biodiversity and ecosystem functioning (BEF) in a tri-trophic model. They showed that ecosystem biomass and production depended not only on species richness but also on the connectance and magnitude of the non-trophic interactions.

Several studies have investigated the role of incorporating specific interactions in food webs. For example, incorporating interspecific facilitation in a resource-consumer model allowed species coexistence in communities of plants consuming a single resource [19]. This increase in species diversity also happens in ecological communities with higher trophic levels including both trophic and facilitative interactions [3]. In the same model, intra- and inter-specific predator interference increased species coexistence as well in multi-trophic webs, although to a lesser extent than facilitation among plants [3].

More generally, the joint effect of several interaction types is expected to affect community functioning and stability. Extending May’s work, Allesina and Tang [20] showed that communities including a mixture of mutualistic and competitive interactions with equal probability were less likely to be stable than random ones (i.e. where interactions between species are randomly chosen), themselves being less stable than predator–prey communities (i.e. in which interactions come in pairs of opposite sign). Using a similar approach, Suweis and colleagues [21] explored the effect of mixing mutualistic and predator-prey interactions on stability, and showed that, without making any further hypothesis, increasing the proportion of mutualistic interactions tend to destabilize the community. Conversely, in a spatially explicit model including both mutualism and antagonism, Lurgi et al. [9] found that increasing the proportion of mutualism increased the stability of the communities. Addressing the relationship between structure and stability, Sauve et al. [8] showed that the role of nestedness and modularity—structural properties that were shown to promote stability in their single interaction types networks (more specifically in mutualistic networks for nestedness and in antagonistic networks for modularity)—was weakened in networks combining mutualistic and antagonistic interactions. Note that this result contrasts with Allesina and Tang [20]’s result on community matrices who showed that, for mutualistic interactions, nested matrices were less likely to be stable than unstructured matrices.

Combining dynamical models with an empirical network analysis including all known non-trophic interactions between the species of intertidal communities in central Chile [22], Kéfi et al. [10] found that the specific ways in which the different layers of interactions are structured in the data increased community biomass, species persistence and tend to improve community resilience to species extinction compared to randomized counter-parts. More recently, García-Callejas et al. [23] used a dynamical model to investigate the effect of the relative frequency of different interaction types on species persistence and showed that persistence was more likely in species-poor communities if positive interactions were present, while this role of positive interactions was less important in species-rich communities.

Altogether, these studies suggest that the joint effect of several interaction types could alter fundamental properties of ecological systems—such as species coexistence, production and community stability—with however a clear lack of consensus on how. So far, most studies have addressed these questions with specific subsets of non-trophic interactions [3, 8, 18, 19], in small species modules [24, 25], in networks with limited numbers of trophic levels [19] or with unrealistic trophic structure [18]. Only a few studies have extended these approaches to complex networks of interactions with a diversity of interaction types (see e.g. [9, 23, 26]). We therefore still lack a clear view on the overall role of the diversity of interaction types per se for species diversity and community functioning, and especially how they may affect the relationship between diversity and functioning.

In the 90ies, because of the raising awareness of the increase in species extinction rates, the long-lasting interest on the origin and maintenance of species diversity shifted toward the study of the consequences of biodiversity, and especially of its loss, for ecosystem functioning [27]. This became an entire sub-field of ecology referred to as ‘Biodiversity and Ecosystem Functioning’ (so-called BEF) and lead to decades of experimental and theoretical research investigating how diversity affects functioning (see [28–33] for reviews). Results of experimental studies suggests that more diverse communities generally produce more biomass than less diverse ones [34, 35]. Theoretically, the question has been addressed as well models have long focused on plant communities (i.e. a single trophic level) (e.g. [36]), but have more recently started to expand these investigations to more complex, realistic communities (e.g. [37–39]). Until now, as far as we know, studies had not specifically investigated the role of the diversity of interactions types on the shape of the BEF.

Here, using a bioenergetics resource-consumer model in which broad categories of non-trophic interactions were introduced [3], we systematically investigated the functioning of ‘multiplex’ ecological networks, i.e. how multiple interactions (their abundance and intensity) affect species coexistence, community functioning (biomass and production), and the relationship between diversity and functioning. Our model includes, in addition to the consumer-resource interactions, competition for space among sessile species, predator interference, refuge provisioning, recruitment facilitation as well as effects that increase or decrease mortality.


The data that support these findings were obtained from multiple open access repositories, including WorldClim (, the Global Biodiversity Information Facility ( and the National Space Agency ( We have created an open access repository that includes the files and code used for all analyses (

Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Ecosystems without top predators

In many instances, trophic cascades have been initiated by human persecution and harvesting of top carnivores, such as wolves and big cats in terrestrial ecosystems and sharks, tunas, and game fish in aquatic ecosystems. The removal of top carnivores triggers significant effects on prey populations, primary producers, and ecosystem processes. Therefore, the conservation of top carnivores helps to preserve the structure and processes of ecosystems in which these predators live. The normal functioning of ecosystems provides many services used by people, including food, fibre, and freshwater supplies as well as processes that maintain the quality of air, water, and soil. The preservation or restoration of top carnivores, however, is sometimes controversial because of the risk such predators pose to people, livestock, or pets.

Mesopredator release, a phenomenon in which the populations of medium-sized predators rapidly increase and play greater roles in the ecosystems they inhabit, is caused by the removal of top carnivores. Mesopredators compete poorly with and may be consumed by top carnivores and thus tend to avoid them. The systematic decline of cougars (Puma concolor) and wolves in the conterminous United States and other parts of North America during the 20th century allowed populations of mesopredators such as coyotes (Canis latrans), red foxes (Vulpes vulpes), and raccoons (Procyon lotor) to increase, as food sources, hunting grounds, den sites, and other resources once controlled by top carnivores became available. The decline of leopards (Panthera pardus) in some parts of Africa allowed baboon (Papio) populations to increase. The loss of large sharks in the oceans allowed smaller-bodied sharks and rays to increase. In each case, mesopredator release caused a decline in species consumed by the mesopredator.

In addition, some mesopredators have become nuisance species. Foraging raccoons plunder trash cans and gardens in many urban areas and are noted carriers of the rabies virus. Baboons can invade homes, break into cars to steal food, and in some cases pose a threat to children.


Temperature affects the metabolic rates of all organisms, and per capita responses to temperature of many co-occurring individuals add up to nothing less than the biological component of ecosystem-scale carbon and oxygen flux. Understanding biological responses to temperature change across scales of organization (cells to the biosphere) is a major challenge in ecological research. Meeting this challenge requires joining theoretical frameworks and synthesizing empirical evidence of temperature effects across scales and systems. Despite much progress, there remains a gap between patterns that emerge in community-level experiments and the multiscale theoretical framework (MTE) that links temperature-dependent metabolism to larger-scale patterns for temperature dependence. Here, we aimed to test the hypothesis that the effects of temperature on ecosystem processes that reflect metabolic temperature dependence are not highly sensitive to local differences in the trophic structure of a community (e.g., presence or absence of a predator). This question draws upon ideas supported by the MTE and community ecology theory predicting that species interactions modify the effects of temperature on community structure and function. We found that in aquatic ecosystems characterized by the presence or absence of predator–prey species interactions, temperature-dependent trophic cascades only modestly altered the effects of temperature on net ecosystem oxygen production and consumption (NEP and ER). We found that higher average temperatures increased NEP and ER while total phytoplankton biomass declined, and all ecosystem-level temperature responses were stronger than expected for per capita temperature-dependent oxygen production or consumption.

Our first hypothesis was based on the expectation that our experimental systems would include top-down predator effects that altered phytoplankton standing stock, and possibly interacted with temperature to influence algal size distributions or other traits. We found that trophic structure did modify the effect of temperature on phytoplankton biomass, failing to reject our first hypothesis. The decline in phytoplankton standing stocks that we observed with warming across ecosystems is consistent with theoretical expectations that in closed systems with limited resources, increases in per capita metabolic rates with temperature could lead to declines in standing stocks [15,18,39,46]. Phytoplankton standing stocks responded most strongly to temperature in the communities with grazers but no predators, suggesting that temperature-dependent grazing can exacerbate the temperature dependence of algal standing stocks. Overall, the temperature dependence of phytoplankton standing stocks greatly exceeded expectations based on temperature dependence of per capita photosynthesis or respiration rates (Fig 3). Our hypothesis (Eq 3) allowed for changes in phytoplankton standing stocks to be explained by direct effects of temperature on per capita metabolism, as well as effects of temperature on thermal traits, density, or body size distributions. We suggest that change in per capita metabolic response and density were the primary components of this change. We did not observe clear shifts in the species composition of the phytoplankton assemblage with temperature still, we do not have high-resolution data on phytoplankton cell size or traits, so we cannot reject these mechanisms as contributors to the patterns we observe.

Our second hypothesis, based on recent experimental results in other freshwater and grassland systems, was that the trophic cascade would get stronger as ecosystem temperatures warmed. We found support for this hypothesis in our system, providing the first evidence that trophic cascade strength increases continuously with temperature. Prior to our study, evidence of stronger trophic cascades with warming were from experiments that test two temperature levels, an ambient and a simulated future scenario of approximately +3 °C [29,47,48]. We show here that this pattern continues over a thermal range of 10 °C. The indirect effects of predators on phytoplankton biomass appear to have been mediated by predation on the dominant grazer, Daphnia. Predators reduced Daphnia density and thereby shifted grazer assemblages toward the less effective copepod grazers at all temperatures. This trophic cascade, mediated by shifts in grazer composition as well as total density, is a classic food web motif in freshwater systems [43]. Interestingly, at warmer temperatures grazer density was lowest, yet we still observed declines in biomass of phytoplankton. This pattern could reflect higher per capita grazing by the remaining grazer individuals. Algal productivity rates are an important element of trophic cascade strength [15,34], and higher NEP at warmer temperatures would contribute to a stronger trophic cascade, even as grazer density declines. As with hypothesis 1, we infer that the effect of temperature on the trophic cascade strength reflects not only the effect of temperature on per capita metabolic rate but also shifts in algal traits or body sizes, or both.

We tested a third hypothesis, that the effects of temperature on biomass and trophic cascade strength would lead to distinct relationships between temperature and NEP and ER for each trophic treatment type (e.g., with versus without predators). We found that the effect of temperature on phytoplankton standing stock was much greater than the effects of temperature on NEP or ER. For NEP and ER, there was support for a model with an interaction between trophic structure and mean temperature, but for NEP a model without the interaction was ranked highly (Table 6), and confidence intervals for the pooled estimated temperature dependence do not indicate differences in temperature dependences among trophic treatments. Therefore, the strong effects of temperature on community structure (biomass, trophic cascade strength) did not translate directly to temperature effects on net ecosystem flux rates.

The estimated temperature dependences of NEP and ER were greater than expected based on temperature-dependent per capita, mass-normalized respiration, and photosynthesis metabolic rates. It is well established that temperature dependence of aerobic respiration is approximately ER = 0.65 eV, and that this value explains the temperature dependence of mass-normalized ecosystem metabolism at the ecosystem scale [2–4]. The temperature dependence of photosynthesis at suboptimal temperatures appears to be EPS = 0.32 eV for algal systems (although EPS values of 0.65 eV are also observed), and this can emerge at population [39] and ecosystem scales [4] in aquatic systems, suggesting ENEP = 0.32–0.65 eV [10,20,49]. Across our experimental temperature gradient, we observed values of ER > 0.65 eV for both NEP and ER, although confidence intervals for ER did include this value (Fig 3) for algae-only ecosystems. These results led us to reject the “first-order metabolic theory” hypotheses that temperature dependence of ecosystem functions scales directly with general temperature dependence of metabolism. Our results further suggest that changes in species interactions within communities, such as loss or gain of a predator species, could alter the responses of net ecosystem fluxes to temperature changes.

Temperature had a stronger effect on phytoplankton standing stock than on NEP. This difference in phytoplankton biomass and oxygen-flux responses to temperature could reflect several processes operating at different scales of organization. First, we expect that per capita rates of oxygen flux increase with warming, so that a given biomass of phytoplankton can be more productive at warmer temperatures if resources are not limiting [4,46,50]. Patterns at the ecosystem scale could deviate from expectations based on direct metabolic scaling of per capita metabolism if size distributions shift toward smaller cells, as is common with warming, as described by the temperature size rule [23,51]. The allometric scaling of metabolic rate with body size (Eq 2) predicts greater oxygen flux for a given total biomass comprised of small individuals. The distribution of thermal tolerance phenotypes may have shifted within the phytoplankton communities. Three months may be sufficient time for evolutionary change [52]. We did not see clear evidence of shifts in species composition with temperature, and it is likely that the species we collected to inoculate our ecosystems were able to tolerate our experimental conditions because we collected them from a shallow lake in Vancouver in which the water temperature likely tracks summertime air temperatures, therefore experiencing temperatures between 19 and 30 °C. Our experimental ecosystems likely did not expose zooplankton to temperatures outside what they would have experienced in a natural system, and we therefore assume they were adapted to these conditions.

In addition to the effects of temperature on per capita metabolism and size structure, at the ecosystem scale, effective resource supply may have changed with temperature, violating an implicit assumption of Eqs 1–4. Even though these were closed ecosystems with regard to external influxes of nutrients, and they experienced the same light conditions, internal nutrient processes could have varied with temperature in ways that made nutrients more available in warmer ecosystems. For example, our ecosystems did not include a benthic habitat that can store nutrients and organic material and slow down nutrient cycling. Heterotrophic microbial processes responsible for rapid nutrient turnover would be accelerated by temperature, perhaps making nutrients available in warmer systems more than in colder systems. Another potential, and speculative, explanation for higher productivity than expected in warmer ecosystems is that some algae species are capable of biological nitrogen fixation [53], and this activity is more feasible at higher temperatures. These two biological processes that are themselves temperature dependent could create a resource gradient in parallel with the temperature gradient [15,50], leading to higher than expected NEP at warmer temperatures relative to the same ecosystem at cooler temperatures.

Although there was no benthic sediment in our ecosystems, algae likely colonized the sides and bottom of the tanks. Benthic algae may also have contributed to NEP and ER estimates in our systems [54]. We did not observe notable amounts of accumulated benthic algae, but even small amounts could have contributed to total ecosystem fluxes and led to covariation in total biomass with temperature. If the ratio of phytoplankton to benthic algae was temperature-dependent [54], our primary producer biomass estimates may have increasingly underrepresented total algal biomass at higher temperatures. To be conservative, we did not present mass-normalized NEP estimates because we could not normalize to any benthic algal metabolic biomass. Covariation between biomass and temperature is common across geographic variation in temperature [12,20,53] and therefore present in other estimates of NEP across broad spatial scales when biomass cannot be estimated well.

Across mean ecosystem temperatures of 19–30 °C, we observed no sign of ecosystem collapse or threshold responses to warming. Changes in community structure and the increase in trophic control along the temperature gradient appear to be exponential and monotonic over the 10 °C gradient (Eq 2), suggesting that linear (or additive) models of temperature effects in most warming experiments, which only test two or three temperatures, may underestimate warming effects over broader thermal gradients. We observed little evidence of abrupt transitions that might be expected if thermal stress responses by individual phenotypes drove ecosystem-scale responses. We did observe declines in grazer density with warming even in the absence of predators, suggesting there were direct or indirect negative effects of temperature on grazers. But we did not see clear shifts in algal species composition among treatments, suggesting that no species group was exposed to temperatures above its critical thermal maximum. Another challenging aspect of warming experiments at the population and community scales is interpreting patterns in the context of transient dynamics. Our ecosystems certainly did not reach long-term states, because varying weather conditions and multi-week generation times of zooplankton would have precluded that. Still, we did not observe signs of transient dynamics in these communities over time, such as population cycles or abrupt changes.

In our systems, algal biomass and zooplankton abundance in food webs were more resistant to temperature in the presence of longer food chains. Predators reduced zooplankton density and caused a clear trophic cascade. Trophic control, and therefore any mitigating effects of predators on biomass change, was weak at low temperatures and increasingly strong at higher temperatures (A versus AG treatment, Fig 3). This pattern is consistent with previous findings that ecosystem functions in systems with two (or even numbers of) trophic levels tend to be more sensitive to warming than systems with odd numbers, due to cascading effects of predation on primary producers [48]. Additionally, in our experiment, predators were not dynamically responsive they did not have time to reproduce during the experiment. Consequently, they represent mortality for zooplankton that may have varied with temperature effects on per capita predation rates by predators, but not a dynamic demographic response that could lead to different outcomes for prey [55]. In many systems, predators are subsidized by other habitats and food sources, and their populations are not dynamically coupled to prey [56]. In fact, this decoupling has been shown to be important in thermally stratified lakes [57]. Inferences drawn based on this experiment about how species interactions affect community and ecosystem responses are restricted to systems with dynamics in the primary producers and primary consumers, with predation-related mortality imposed by a third trophic level through per capita consumption effects but not population dynamics of the predators.

The growing literature of experimental tests of how warming affects interacting species aims to reduce uncertainty in projected ecological changes associated with climate change. Warming experiments have shown a wide variety of consequences for species interactions, from shifts in community composition, strengthening top-down control, and shifts in body size [16,18,54]. We have shown that these shifts do alter the effects on the temperature dependence of net ecosystem oxygen production and consumption as modeled by the MTE, but that these models may be extended to consider community-level changes. By measuring community and ecosystem responses over a broad thermal gradient under controlled conditions, we have provided empirical evidence that large effects of temperature on community biomass can occur in the context of less strong effects of temperature on net ecosystem function. This is a step toward closing the gap between patterns observed across ecosystems that appear to reflect effects of temperature on metabolic rates, and observations at intermediate scales that temperature can have large effects on the abundance of species. Taken together, these results suggest our efforts to predict community change with warming may benefit from the general metabolic scaling theory framework to understand even local-scale effects of temperature change at the community level.

Energy Flow in Ecosystems

In every ecosystem, organisms are linked through feeding relationships. There are a great many feeding relationships in any ecosystem, but energy always flows from primary producers to various consumers. These feeding relationships are represented by food chains and food webs.

A food chain is a sequence in which organisms transfer energy by eating and being eaten. Here is an example of a food chain from the video.

Notice that the arrows point in the direction of the energy flow. The point of the arrow goes to who is doing the eating.

In most ecosystems, feeding relationships are much more complicated than the relationships shown in a food chain. The network of feeding interactions is called a food web. View the video to see an example of a food web from the Everglades ecosystem.

Compare and contrast a food chain and a food web on the graphic organizer on page 6 of your OnTRACK Biology Journal. Use the Venn diagram to list the features of a food chain and food web as well as what the two have in common.

Check Your Learning
Drag the circle icon and place it over the arrow that is pointing in the correct direction in the following diagram.

Make Your Own Food Web
Now that you have seen an example of a food web, refer to the ecosystem you researched in the first section of this resource and create a food web to show how matter and energy flow between organisms that are likely to live in that ecosystem. You can show your food web on a poster or through a digital graphic organizer created online such as in Lucidchart or in Google Drive with Google Drawings. Remember to draw the arrows moving in the direction that the matter and energy are flowing.

Once your food web is complete, label each of the following:

  • Producers
  • Consumers
  • Herbivores
  • Omnivore
  • Carnivore
  • Decomposers
  • Scavengers

Additionally, complete the following and post near or on your food web diagram:

Describe the food web and the places on Earth where this ecosystem and these organisms might be found.

Deciphering the trophic interaction between Akkermansia muciniphila and the butyrogenic gut commensal Anaerostipes caccae using a metatranscriptomic approach

Host glycans are paramount in regulating the symbiotic relationship between humans and their gut bacteria. The constant flux of host-secreted mucin at the mucosal layer creates a steady niche for bacterial colonization. Mucin degradation by keystone species subsequently shapes the microbial community. This study investigated the transcriptional response during mucin-driven trophic interaction between the specialised mucin-degrader Akkermansia muciniphila and a butyrogenic gut commensal Anaerostipes caccae. A. muciniphila monocultures and co-cultures with non-mucolytic A. caccae from the Lachnospiraceae family were grown anaerobically in minimal media supplemented with mucin. We analysed for growth, metabolites (HPLC analysis), microbial composition (quantitative reverse transcription PCR), and transcriptional response (RNA-seq). Mucin degradation by A. muciniphila supported the growth of A. caccae and concomitant butyrate production predominantly via the acetyl-CoA pathway. Differential expression analysis (DESeq 2) showed the presence of A. caccae induced changes in the A. muciniphila transcriptional response with increased expression of mucin degradation genes and reduced expression of ribosomal genes. Two putative operons that encode for uncharacterised proteins and an efflux system, and several two-component systems were also differentially regulated. This indicated A. muciniphila changed its transcriptional regulation in response to A. caccae. This study provides insight to understand the mucin-driven microbial ecology using metatranscriptomics. Our findings show that the expression of mucolytic enzymes by A. muciniphila increases upon the presence of a community member. This could indicate its role as a keystone species that supports the microbial community in the mucosal environment by increasing the availability of mucin sugars.

Keywords: Butyrate Cross feeding Keystone species Microbiome Mucin Transcriptional regulation Verrucomicrobia.

Conflict of interest statement

JK is the employee of Nutricia Research. LWC and CB are financially supported by Nutricia Research. There was no involvement of the company in the content of this work.


The importance of functional traits over species identity in controlling patterns of community ecology has been shown in recent studies (McGill et al., 2006 Verberk et al., 2013 Webb et al., 2010). The growing area of functional ecological research incorporates features at the individual level and scales them to make predictions of community-level processes (McGill et al., 2006 Violle et al., 2007). Functional traits are quantifiable characteristics of an organism, measured at the individual level but comparable across species (i.e. maximum body size, metabolic rate, canopy height) (McGill et al., 2006). One of the main concepts of trait-based ecology is that patterns and processes at a community or ecosystem level are determined by the characteristics of the component species, not by their taxonomic identity (Griffin et al., 2009 Gross et al., 2017 Jänes et al., 2017). For example, competition among trees was found to be predictable based on the traits of wood density, specific leaf area, and maximum height (Kunstler et al., 2015), while primary production in certain aquatic biomes was determinable based on the morphological, life history, and tolerance traits of marine macrophytes (Jänes et al., 2017).

Habitat structure in a system provides novel microhabitats, mediates predator-prey interactions, and alters the physical environment (Heck and Crowder, 1991 Jones et al., 1994 Crooks, 2002 Grabowski and Powers, 2004). Macrophytes are some of the most important structure-forming organisms in many ecosystems. The morphology and structure of macrophytes has long been recognized as a key regulating component across a diversity of terrestrial, aquatic, and marine ecosystems (Lawton, 1983 McCoy and Bell, 1991). For example, ecological processes are shaped by the physical structure of forest canopies (MacArthur and MacArthur, 1961 Rotenberry and Wiens, 1980), seagrass beds (Orth et al., 1984 Schmidt et al., 2011), and mangroves (Nagelkerken et al., 2008). Bird species diversity has been shown to be controlled by the foliage height profile (MacArthur and MacArthur, 1961), while the height and complexity of grass appears to modify the strength of top-down control of various arthropods by spiders (Sanders et al., 2008). In some marine and aquatic systems, more complex macrophytes reduce the ability of predators to locate and consume prey (e.g. Holmlund et al., 1990 Warfe and Barmuta, 2004). Large kelps in temperate marine areas create three-dimensional structure, facilitate understory diversity, and protect against physical disturbances (Teagle et al., 2017). Despite the obvious differences between terrestrial and aquatic habitats, the role of biogenic structure is similar whether in land or water. Three-dimensional structure mediates species interactions by providing visual cover, interstitial refuge spaces, and increasing the overall available surface area in an ecosystem.

Due to the intricate connections between biogenic habitat structure and animal ecology, we may expect that the ability of animals to find suitable refuge and food will be impacted in ecosystems in which dominant foundation species have been lost or replaced by morphologically different species. Over the last few decades, there has been drastic human-mediated change in foundation species (McIntyre et al., 2015 Thomson et al., 2015 Wernberg et al., 2016), with concurrent changes in habitat structure (Coleman and Williams, 2002 Ellison et al., 2005 Asner et al., 2008 Thomson et al., 2015 Dijkstra et al., 2017). Some of these architectural changes are caused by extreme climatic events (Wernberg et al., 2013 Thomson et al., 2015) or by direct human removal of foundation species (Coleman and Williams, 2002 Ellison et al., 2005). Another source of architectural change in ecosystems is the proliferation of invasive species. Biogenic structure-forming introductions typically alter physical habitats either by creating novel structure where none existed previously (i.e. Posey, 1988 Wright et al., 2014), or by replacing a morphologically dissimilar native species (Smith and Finch, 2013 Dijkstra et al., 2017). Morphological differences between native and introduced plants has been shown to impact the availability of various seasonal resident bird nesting sites (Smith and Finch, 2013), foraging success, predator avoidance (Barnes et al., 1995), and other community interactions (see Nelson et al., 2017 for review). Regardless of the source of these macrophyte shifts, the impacts on the trophic interactions of other organisms in these systems are complex and understudied.

In the shallow rocky subtidal of the southern Gulf of Maine, habitat structure has historically been provided by large kelps (Order Laminariales). Species such as Saccharina latissima form a relatively tall canopy over a diverse and protected understory (Chapman and Johnson, 1990 Levin et al., 2002 Steneck et al., 2013). However, the Gulf of Maine is one of the fastest warming bodies of water globally (Pershing et al., 2015), and in recent years kelp abundance has begun to decline in this region (Dijkstra et al., 2017 Witman and Lamb, 2018). The benthic community is increasingly dominated by a variety of low-lying turf algae, which are morphologically distinct from the tall flat-bladed kelps, with lower canopy height and increased thallus complexity (Dijkstra et al., 2017). This pattern is similar to that seen in other kelp systems worldwide (Filbee-Dexter and Wernberg, 2018). Mechanistically, increasing thallus complexity may inhibit predation by visual predators such as fish by providing more interstitial refuges for prey (Steneck et al., 2013). A number of the newly dominant turf algae are introduced species, including Dasysiphonia japonica, a complex filamentous red alga which has rapidly spread through New England (Schneider, 2010 Ramsay-Newton et al., 2017).

We coupled field and laboratory studies to investigate how these documented changes in the structure of foundation species will affect the trophic interactions of the demersal wrasse Tautogolabrus adspersus (cunner). Cunner are an ideal study organism to address questions of habitat change in this ecosystem due to their middle trophic position, behavioral reliance on macroalgae, and their abundance in this system. We predicted that cunner would be sensitive to changes in the architecture of the macroalgal assemblage due to their dual role as both predator and prey in this habitat. We investigated the effect of varying macroalgae morphology on two main aspects of cunner ecology: refuge and foraging. These aspects were tested using three related studies: in situ behavioral observations, a refuge choice experiment, and a foraging efficiency experiment. We expected that cunner would prefer taller, broad-bladed macroalgae such as kelps over low-growing turf algae species for refuge in the field and in the laboratory experiment. We also predicted that cunner foraging efficiency would be reduced within turf algae monocultures due to the small-scale complexity of these algae.

Watch the video: Trophic interactions (May 2022).