Biology subjects

Brose, U.

Publications and source records attributed to Brose, U..

At least 19 recordsLinked to original sources

bioRxiv2026

Forest degradation reshapes trophic functioning in vertebrate food webs across Amazonian forests

The Amazon is a mosaic of ecosystems, accounting for 13% of all known species globally, and responsible for providing a variety of ecosystem services, including a key role in global climate regulation. However, 18% of the Amazon forest cover has been lost completely and a further 38% degraded, threatening biodiversity and millions of local livelihoods. Currently, little is known about how this impacts the functioning of ecological communities. Here, we combine an energetic approach with biodiversity metrics to quantify ecosystem functioning in mammal and bird food webs across Amazonia, along a gradient of forest degradation linked to road proximity. We show that even under relatively low disturbance, ecosystem functions shift: carnivory increases closer to roads, driven by generalist species that persist under these conditions, whereas herbivory declines mainly due to reduced herbivore biomass and species richness. This suggests that processes associated with forest degradation can alter energy flow even where biodiversity metrics remain relatively unchanged, highlighting energetic approaches as sensitive indicators of ecosystem disruption.

ecology↗

bioRxiv2026

Mitigating consecutive drought impacts on forest productivity through strategic tree species spatial design

The rising frequency and severity of multiyear droughts due to climate change poses a serious threat to tree growth and survival, compromising our terrestrial carbon sink. Although tree diversity is known to enhance forest biomass production, its role in mediating drought impacts remains elusive due to inconsistent evidence and limited understanding of species interactions. Using empirically parameterized pairwise interactions among eight tree species, we show that tree diversity buffers forest communities against repeated drought-induced biomass loss. This buffering arises from heterogeneous neighborhoods that promote both niche differentiation and facilitative interactions among species. We further demonstrate that strategic planting designs, such as random or single-line spatial arrangements, amplify these benefits by maximizing neighborhood heterogeneity, with single-line being more plausible when balancing management effort. Our simulation results suggest that increasing diversity could raise carbon sequestration rates by 18.8%. These findings corroborate tree diversity and spatial heterogeneity as actionable, climate-adaptive tools that simultaneously enhance forest productivity, drought resilience, and long-term carbon sequestration.

ecology↗

bioRxiv2024

Degradation of fish food webs in the anthropocene

The Anthropocene is marked by profound changes in biodiversity and the ecosystems in which species live 1-4. A primary signature of this change is the often rapid change in species composition through time (i.e., species turnover) rather than changes in the numbers of species per se 5-7. Less well known, however, is which types of species are winning and which are losing as ecosystems change through time 8,9, as well as whether and how these changes influence higher-level processes in the food webs in which species are embedded 10,11. Here, we combine a compilation of long-term observations of [~]15,000 freshwater and marine fish communities surveyed for 1949-2019 years, together with information about their diets and trophic status in order to evaluate how the food webs in which these fish communities are embedded are changing through time. We found widespread alteration to fish food web topology and functioning. This includes an increase in connectance and generalism in food webs, which has led to greater predation pressure, as indicated by higher diet overlap and increased prey vulnerability. We also identified a decrease in modularity, which has reduced the compartmentalization within local networks. These changes extend across the trophic structure of food webs, causing a cascading shift in the proportion of species across trophic levels. Our study highlights the complex responses of biodiversity change of fish food webs in the Anthropocene, which can ultimately influence the functions of these ecosystems and human well-being 12,13.

ecology↗

bioRxiv2024

Body size is a better predictor of intra- than interspecific variation of animal stoichiometry across realms

Animal stoichiometry affects fundamental processes ranging from organismal physiology to global element cycles. However, it is unknown whether animal stoichiometry follows predictable scaling relationships with body mass and whether adaptation to life on land or water constrains patterns of elemental allocation. To test both interspecific and intraspecific body-size scaling relationships of the nitrogen (N), phosphorus (P), and N:P content of animals, we used a subset of the StoichLife database encompassing 9,933 individual animals (vertebrates and invertebrates) belonging to 1,543 species spanning 10 orders of magnitude of body size from terrestrial, freshwater, and marine realms. Across species, body mass did not explain much variation in %N and %P composition, although the %P of invertebrates decreased with size. The effects of body size on species elemental content were small in comparison to the effects of taxonomy. Body size was a better predictor of intraspecific than interspecific elemental patterns. Between 42 to 45% in intraspecific stoichiometric variation was explained by body size for 27% of vertebrate species and 35% of invertebrate species. Further, differences between organisms inhabiting aquatic and terrestrial realms were observed only in invertebrate interspecific %N, suggesting that the realm does not play an important role in determining elemental allocation of animals. Based on our analysis of the most comprehensive animal stoichiometry database, we conclude that (i) both body size and realm are relatively weak predictors of animal stoichiometry across taxa, and (ii) body size is a good predictor of intraspecific variation in animal elemental content, which is consistent with tissue-scaling relationships that hold broadly across large groups of animals. This research reveals a lack of general scaling patterns in the elemental content across animals and instead points to a large variation in scaling relationships within and among lineages.

ecology↗

bioRxiv2023

Understanding interactions in a complex world: Design and analysis of multi-species functional response experiments

O_LIThe functional response describes feeding rates of consumers as a function of resource density. While models for feeding on a single resource species are well studied and supported by a large body of empirical research, consumers feeding on multiple resource species are ubiquitous in nature. However, laboratory experiments designed for parameterizing multi-species functional responses (MSFR) are extremely rare, mainly due to logistical challenges and the non-trivial nature of their statistical analysis. C_LIO_LIHere, we describe how these models can be fitted to empirical data in a Bayesian framework. Specifically, we address the problem of prey depletion during experiments, which can be accounted for through dynamical modeling. In a comprehensive simulation study, we test the effects of experimental design, sample size and noise level on the identifiability of four distinct MSFR models. Additionally, we demonstrate the methods versatility by applying it to a list of empirical datasets. C_LIO_LIWe identify experimental designs for feeding trials that produce the most accurate parameter estimates in two- and three-prey scenarios. Although noise introduces systematic bias in parameter estimates, model selection performs surprisingly well for the four MSFRs, almost always identifying the correct model even for small datasets. C_LIO_LIThis flexible framework allows the simultaneous analysis of feeding experiments from both single- and multi-prey scenarios, either with or without prey depletion. This will help to elucidate mechanisms such as prey selectivity, prey switching and their implications for food web stability and biodiversity. Our approach equips researchers with the appropriate statistical tools to improve the understanding of feeding interactions in complex ecosystems. C_LI

ecology↗

bioRxiv2023

Quantitative description of six fish species' gut contents and abundances of their prey in the benthic food web of the Baltic Sea (1968-1978)

The dataset presents a compilation of stomach contents from six demersal fish species from two functional groups inhabiting the Baltic Sea. It includes detailed information on prey identities, body masses, and biomasses recovered from both the fishs digestive systems and their surrounding environment. Environmental parameters, such as salinity and temperature levels, have been integrated to enrich this dataset. The juxtaposition of information on prey found in stomachs and in the environment provides an opportunity to quantify trophic interactions across different environmental contexts and investigate how fish foraging behaviour adapts to changes in their environment, such as an increase in temperature. The compilation of body mass and taxonomic information for all species allows approaching these new questions using either a taxonomic (based on species identity) or functional trait (based on body mass) approach.

ecology↗

bioRxiv2022

Biodiversity and local interaction complexity promote sustainable fisheries in large food webs

On a global scale, fisheries harvest an estimated 96 million tonnes of fish biomass annually, making them one of the most important drivers of marine ecosystem biodiversity. Yet little is known about the interactions between fisheries and the dynamics of complex food webs in which the harvested species are embedded. We have developed a synthetic model that combines resource economics with complex food webs to examine the direct effects of fishing on exploited species and the indirect impact on other species in the same community. Our model analyses show that the sensitivity of the targeted species increases with its trophic level and decreases with its local interaction complexity (i.e. its number of interactions with prey, predators, and competitors). In addition, we also document a strikingly positive effect of community species richness on the resilience of the harvested species to this disturbance. The indirect effects on other species show specific patterns of spreading across trophic modules that differ systematically from how other disturbances spread across ecological networks. While these results call for further research on how human resource exploitation in general and fishery in particular affect ecological dynamics and biodiversity in naturally complex systems, they also allow for some cautious conclusions. Taken together, our results suggest that the sustainability concerning fishery yield and ecosystem integrity can be maximised by focusing the harvest on low trophic level species with a high local interaction complexity in high biodiversity ecosystems. In this sense, our complex network approach offers a promising avenue for integrating the necessities of generating economic revenue with the protection of natural biodiversity.

ecology↗

bioRxiv2022

Heat dissipation drives the hump-shaped scaling of animal dispersal speed with body mass

Dispersal is critical to animal survival and thus biodiversity in fragmented landscapes. Increasing fragmentation in the Anthropocene necessitates predictions about the dispersal capabilities of the many species that inhabit natural ecosystems. This requires mechanistic, trait-based models of animal dispersal which are sufficiently general as well as biologically realistic. While larger animals should generally be able to travel greater distances, reported trends in their speeds across a range of body sizes suggest limited locomotor capacities among the largest species. Here, we show that this also applies to dispersal speeds and that this arises because of their limited heat-dissipation capacities. We derive a model considering how fundamental biophysical constraints of animal body mass associated with energy utilisation (i.e. larger animals have a lower metabolic energy cost of locomotion) and heat-dissipation (i.e. larger animals require more time to dissipate metabolic heat) limit sustained (i.e. aerobic) dispersal speeds. Using an extensive empirical dataset of animal dispersal speeds (531 species), we show that this allometric heat-dissipation model best captures the hump-shaped trends in dispersal speed with body mass for flying, running and swimming animals. This implies that the inability to dissipate metabolic heat leads to the saturation and eventual decrease in dispersal speed with increasing body mass as larger animals must reduce their realised dispersal speeds in order to avoid hyperthermia during extended dispersal bouts. As a result, the highest dispersal speeds are achieved by animals of intermediate body mass, whereas the largest species might suffer from stronger dispersal limitations in fragmented landscapes than previously anticipated. Consequently, we provide a mechanistic understanding of animal dispersal speed that can be generalised across species, even when the details of an individual species biology are unknown, to facilitate more realistic predictions of biodiversity dynamics in fragmented landscapes.

ecology↗

bioRxiv2022

ATNr : Allometric trophic models in R

O_LIUnderstanding and predicting how densities of interacting species change over time has been one of the main goals of community ecology, which has become a pressing challenge in the context of global change. C_LIO_LIWe present the R package ATNr, which provides an implementation of different versions of Allometric Trophic Network models (Yodzis and Innes (1992)) that simulate the biomass dynamics of trophically interacting species. C_LIO_LIRelying on C++ routines, the ATNr proposes an efficient and standardized implementation of the different ATNs models. C_LIO_LIBy proposing a set of built in functions ready to use in a language widely used in the community of ecologists, the ATNr package offers an easy access to ATN models. C_LI

ecology↗

bioRxiv2022

Global environmental drivers of local abundance-mass scaling in soil animal communities

The relationship between species body masses and densities is strongly conserved around a three-quarter power law when pooling data across communities. However, studies of local within-community relationships have revealed major deviations from this general pattern, which has profound implications for their stability and functioning. Despite multiple contributions of soil communities to people, there is limited knowledge on the drivers of body mass-abundance relationship in these communities. We compiled a dataset comprising 155 soil-animal communities across four countries (Canada, Germany, Indonesia, USA), all sampled using the same methodology. We tested if variation in local climatic and edaphic conditions drives differences in local body mass-abundance scaling relationships. We found substantial variation in the slopes of this power-law relationship across local communities. Structural equation modeling showed that soil temperature and water content have a positive and negative net effect, respectively, on soil communities. These effects are mediated by changes in local edaphic conditions (soil pH and carbon content) and the body-mass range of the communities. These results highlight ways in which alterations of soil climatic and edaphic conditions interactively impact the distribution of abundance, and thus energy, between populations of small and large animals. These quantitative mechanistic relationships facilitate our understanding of how global changes in environmental conditions, such as temperature and precipitation, will affect community-abundance distributions and thus the stability and functioning of soil-animal communities.

ecology↗

bioRxiv2021

Adaptive foraging behaviour increases vulnerability to climate change

Higher temperatures are expected to reduce species coexistence by increasing energetic demands. However, flexible foraging behaviour could balance this effect by allowing predators to target specific prey species to maximize their energy intake, according to principles of optimal foraging theory. We test these assumptions using a large dataset comprising 2,487 stomach contents from six fish species with different feeding strategies, sampled across environments with varying prey availability over 12 years in Kiel Bay (Baltic Sea). Our results show that foraging shifts from trait-to density-dependent prey selectivity in warmer and more productive environments. This behavioural change leads to lower consumption efficiency at higher temperature as fish select more abundant but less energetically rewarding prey, thereby undermining species persistence and biodiversity. By integrating this behaviour into dynamic food web models, our study reveals that flexible foraging leads to lower species coexistence and biodiversity in communities under global warming.

ecology↗

bioRxiv2020

Emergence of stable motifs in consumer-resource communities

Understanding how and why complex communities can be stable has preoccupied ecologists for over a century. Data show that real communities tend to exhibit characteristic motifs and topologies. Despite a large body of theory investigating both ecological (niche partitioning) and evolutionary (speciation and extinction) mechanisms, a general explanation for why particular motifs are more common than others remains elusive. Here we develop a mechanistic framework that investigates the set of possible motifs that can emerge under minimal conditions of a nutrient-limited system with no external inputs, and no spatial heterogeneity. Focusing on consumer-resource communities structured by competition and predation, we find that the emergent motifs under these minimal conditions are vertical trophic chains that maximize energy transfer and biomass production. Not only are such motifs stable to perturbations of species abundances, but they are also robust to species additions and removals. Our findings provide a mechanistic explanation for why tri-trophic chains are overrepresented in real food webs. They suggest that, because they maximize energy transfer, and can emerge and persist under minimal conditions, vertical trophic chains may constitute the fundamental architecture of consumer-resource communities.

ecology↗

bioRxiv2020

Landscape heterogeneity buffers biodiversity of meta-food-webs under global change through rescue and drainage effects

The impacts of habitat fragmentation and eutrophication on biodiversity have been studied in different scientific realms. Metacommunity research1-5 has shown that reduction in landscape connectivity may cause biodiversity loss in fragmentated landscapes. Food-web research addressed how eutrophication increases biomass accumulations at high trophic levels causing the breakdown of local biodiversity 6-9. However, there is very limited understanding of their cumulative impacts as they could amplify or cancel each other. Here, we show with simulations of meta-food-webs that landscape heterogeneity provides a buffering capacity against increasing nutrient eutrophication. An interaction between eutrophication and landscape homogenization precipitates the decline of biodiversity. We attribute our results to two complementary mechanisms related to source and sink dynamics. First, the "rescue effect" maintains local biodiversity by rapid recolonization after a local crash in population densities. Second, the "drainage effect" allows a more uniform spreading of biomass across the landscape, reducing overall interaction strengths and therefore stabilizing dynamics. In complex food webs on large spatial networks of habitat patches, these effects yield systematically higher biodiversity in heterogeneous than in homogeneous landscapes. Our meta-food-web approach reveals a strong interaction between habitat fragmentation and eutrophication and provides a mechanistic explanation of how landscape heterogeneity promotes biodiversity.

ecology↗

bioRxiv2019

Global distribution of earthworm diversity

Soil organisms provide crucial ecosystem services that support human life. However, little is known about their diversity, distribution, and the threats affecting them. Here, we compiled a global dataset of sampled earthworm communities from over 7000 sites in 56 countries to predict patterns in earthworm diversity, abundance, and biomass. We identify the environmental drivers shaping these patterns. Local species richness and abundance typically peaked at higher latitudes, while biomass peaked in the tropics, patterns opposite to those observed in aboveground organisms. Similar to many aboveground taxa, climate variables were more important in shaping earthworm communities than soil properties or habitat cover. These findings highlight that, while the environmental drivers are similar, conservation strategies to conserve aboveground biodiversity might not be appropriate for earthworm diversity, especially in a changing climate.\n\nOne sentence summaryGlobal patterns of earthworm diversity, abundance and biomass are driven by climate but patterns differ from many aboveground taxa.

ecology↗

bioRxiv2018

The biggest losers: Habitat isolation deconstructs complex food webs from top to bottom

Habitat fragmentation is threatening global biodiversity. To date, there is only limited understanding of how habitat fragmentation or any alteration to the spatial structure of a landscape in general, affects species diversity within complex ecological networks such as food webs. Here, we present a dynamic and spatially-explicit food web model which integrates complex food web dynamics at the local scale and species-specific dispersal dynamics at the landscape scale, allowing us to study the interplay of local and spatial processes in metacommunities. We explore how habitat fragmentation, defined as a decrease of habitat availability and an increase of habitat isolation, affects the species diversity patterns of complex food webs (-, {beta}-,{gamma} -diversity), and specifically test whether there is a trophic dependency in the effect of habitat fragmentation on species diversity. In our model, habitat isolation is the main driver causing species loss and diversity decline. Our results emphasise that large-bodied consumer species at high trophic positions go extinct faster than smaller species at lower trophic levels, despite being superior dispersers that connect fragmented landscapes better. We attribute the loss of top species to a combined effect of higher biomass loss during dispersal with increasing habitat isolation in general, and the associated energy limitation in highly fragmented landscapes, preventing higher trophic levels to persist. To maintain trophic-complex and species-rich communities calls for effective conservation planning which considers the interdependence of trophic and spatial dynamics as well as the spatial context of a landscape and its energy availability.

ecology↗

bioRxiv2018

The intrinsic predictability of ecological time series and its potential to guide forecasting

Successfully predicting the future states of systems that are complex, stochastic and potentially chaotic is a major challenge. Model forecasting error (FE) is the usual measure of success; however model predictions provide no insights into the potential for improvement. In short, the realized predictability of a specific model is uninformative about whether the system is inherently predictable or whether the chosen model is a poor match for the system and our observations thereof. Ideally, model proficiency would be judged with respect to the systems intrinsic predictability - the highest achievable predictability given the degree to which system dynamics are the result of deterministic v. stochastic processes. Intrinsic predictability may be quantified with permutation entropy (PE), a model-free, information-theoretic measure of the complexity of a time series. By means of simulations we show that a correlation exists between estimated PE and FE and show how stochasticity, process error, and chaotic dynamics affect the relationship. This relationship is verified for a dataset of 461 empirical ecological time series. We show how deviations from the expected PE-FE relationship are related to covariates of data quality and the nonlinearity of ecological dynamics.\n\nThese results demonstrate a theoretically-grounded basis for a model-free evaluation of a systems intrinsic predictability. Identifying the gap between the intrinsic and realized predictability of time series will enable researchers to understand whether forecasting proficiency is limited by the quality and quantity of their data or the ability of the chosen forecasting model to explain the data. Intrinsic predictability also provides a model-free baseline of forecasting proficiency against which modeling efforts can be evaluated.\n\nGlossaryActive information: The amount of information that is available to forecasting models (redundant information minus lost information; Fig. 1).\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=45 SRC=\"FIGDIR/small/350017_fig1a.gif\" ALT=\"Figure 1A\">\nView larger version (9K):\norg.highwire.dtl.DTLVardef@934d9eorg.highwire.dtl.DTLVardef@ccdc10org.highwire.dtl.DTLVardef@1839ed9org.highwire.dtl.DTLVardef@31bd70_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1A.C_FLOATNO The total information content of an observation of a system at a given state in time, St, is depicted by filled circles with past states (St-1 and St-2) represented by shades of grey, i) lack of overlap between past and present states illustrating a case where no information is transmitted from past states (i.e. a purely stochastic system), with low redundancy and high Shannon entropy rate, ii) intermediate overlap indicating a case when some information is transferred from past to present (i.e. a deterministic system strongly driven by stochastic forcing), with intermediate redundancy and Shannon entropy rate, iii) large overlap indicating a case when the current state is mostly determined by the previous state (i.e. a highly deterministic system), with high redundancy and low Shannon entropy rate. Note that both the redundancy and Shannon entropy rate of a system are intrinsic properties of the system and will only change if the system itself changes.\n\nC_FIG Forecasting error (FE): A measure of the discrepancy between a models forecasts and the observed dynamics of a system. Common measures of forecast error are root mean squared error and mean absolute error.\n\nEntropy: Measures the average amount of information in the outcome of a stochastic process.\n\nInformation: Any entity that provides answers and resolves uncertainty about a process. When information is calculated using logarithms to the base two (i.e. information in bits), it is the minimum number of yes/no questions required, on average, to determine the identity of the symbol (Jost 2006). The information in an observation consists of information inherited from the past (redundant information), and of new information.\n\nIntrinsic predictability: the maximum achievable predictability of a system (Beckage et al. 2011).\n\nLost information: The part of the redundant information lost due to measurement or sampling error, or transformations of the data (Fig. 1).\n\nNew information, Shannon entropy rate: The Shannon entropy rate quantifies the average amount of information per observation in a time series that is unrelated to the past, i.e., the new information (Fig. 1).\n\nNonlinearity: When the deterministic processes governing system dynamics depend on the state of the system.\n\nPermutation entropy (PE): permutation entropy is a measure of the complexity of a time series (Bandt & Pompe, 2002) that is negatively correlated with a systems predictability (Garland et al. 2015). Permutation entropy quantifies the combined new and lost information. PE is scaled to range between a minimum of 0 and a maximum of 1.\n\nRealized predictability: the achieved predictability of a system from a given forecasting model.\n\nRedundant information: The information inherited from the past, and thus the maximum amount of information available for use in forecasting (Fig. 1).\n\nSymbols, words, permutations: symbols are simply the smallest unit in a formal language such as the letters in the English alphabet i.e., {\"A\", \"B\",..., \"Z\"}. In information theory the alphabet is more abstract, such as elements in the set {\"up\", \"down\"} or {\"1\", \"2\", \"3\"}. Words, of length m refer to concatenations of the symbols (e.g., up-down-down) in a set. Permutations are the possible orderings of symbols in a set. In this manuscript, the words are the permutations that arise from the numerical ordering of m data points in a time series.\n\nWeighted permutation entropy (WPE): a modification of permutation entropy (Fadlallah et al., 2013) that distinguishes between small-scale, noise-driven variation and large-scale, system-driven variation by considering the magnitudes of changes in addition to the rank-order patterns of PE.

ecology↗

bioRxiv2018

Applying generalised allometric regressions to predict live body mass of tropical and temperate arthropods

1. The ecological implications of body size extend from the biology of individual organisms to ecosystem-level processes. Measuring body mass for high numbers of invertebrates can be logistically challenging, making length-mass regressions useful for predicting body mass with minimal effort. However, standardised sets of scaling relationships covering a large range in body length, taxonomic groups, and multiple geographical regions are scarce.\n\n2. We collected 6293 arthropods from 19 higher-level taxa in both temperate and tropical locations to compile a comprehensive set of linear models relating live body mass to a range of predictor variables. For each individual, we measured live weight (hereafter, body mass), body length and width, and conducted linear regressions to predict body mass using body length, body width, taxonomic group and geographic region. Additionally, we quantified prediction error when using parameters from arthropods of a different geographic region.\n\n3. Incorporating body width into taxon- and region-specific length-mass regressions yielded the highest prediction accuracy for body mass. Using regression parameters from a different geographic location increased prediction error, causing over- or underestimation of body mass depending on geographical origin and whether body width was included.\n\n4. We present a comprehensive range of parameters for predicting arthropod body mass and provide guidance for selecting optimal scaling relationships. Given the importance of body mass for functional invertebrate ecology and a paucity of adequate regressions to predict arthropod body mass from different geographical regions, our study provides a long-needed resource for quantifying live body mass in invertebrate ecology research.

zoology↗

bioRxiv2018

Metabolic adjustment enhances food web stability

Understanding ecosystem stability is one of the greatest challenges of ecology. Over several decades, it has been shown that allometric scaling of biological rates and feeding interactions provide stability to complex food web models. Moreover, introducing adaptive responses of organisms to environmental changes (e.g. like adaptive foraging that enables organisms to adapt their diets depending on resources abundance) improved species per-sistence in food webs. Here, we introduce the concept of metabolic adjustment, i.e. the ability of species to slow down their metabolic rates when facing starvation and to increase it in time of plenty. We study the reactions of such a model to nutrient enrichment and the adjustment speed of metabolic rates. We found that increasing nutrient enrichment leads to a paradox of enrichment (increase in biomasses and oscillation amplitudes and ultimately extinction of species) but metabolic adjustment stabilises the system by dampening the oscillations. Metabolic adjustment also increases the average biomass of the top predator in a tri-trophic food chain. In complex food webs, metabolic adjustment has a stabilising effect as it promotes species survival by creating a large diversity of metabolic rates. However, this stabilising effect is mitigated in enriched ecosystems. Phenotypic plasticity of organisms must be considered in food web models to better understand the response of organisms to their environment. As metabolic rate is central in describing biological rates, we must pay attention to its variations to fully understand the population dynamics of natural communities.

ecology↗