A mechanistic understanding of the response of metabolic rate to temperature is essential for understanding thermal ecology and metabolic adaptation. Although the Arrhenius equation has been used to describe the effects of temperature on reaction rates and metabolic traits, it does not adequately describe two aspects of the thermal performance curve (TPC) for metabolic rate—that metabolic rate is a unimodal function of temperature often with maximal values in the biologically relevant temperature range and that activation energies are temperature dependent. We show that the temperature dependence of metabolic rate in ectotherms is well described by an enzyme‐assisted Arrhenius (EAAR) model that accounts for the temperature‐dependent contribution of enzymes to decreasing the activation energy required for reactions to occur. The model is mechanistically derived using the thermodynamic rules that govern protein stability. We contrast our model with other unimodal functions that also can be used to describe the temperature dependence of metabolic rate to show how the EAAR model provides an important advance over previous work. We fit the EAAR model to metabolic rate data for a variety of taxa to demonstrate the model's utility in describing metabolic rate TPCs while revealing significant differences in thermodynamic properties across species and acclimation temperatures. Our model advances our ability to understand the metabolic and ecological consequences of increases in the mean and variance of temperature associated with global climate change. In addition, the model suggests avenues by which organisms can acclimate and adapt to changing thermal environments. Furthermore, the parameters in the EAAR model generate links between organismal level performance and underlying molecular processes that can be tested for in future work.
The increased temperature associated with climate change may have important effects on body size and predator-prey interactions. The consequences of these effects for food web structure are unclear because the relationships between temperature and aspects of food web structure such as predatorprey body-size relationships are unknown. Here, we use the largest reported dataset for marine predator-prey interactions to assess how temperature affects predator-prey body-size relationships among different habitats ranging from the tropics to the poles. We found that prey size selection depends on predator body size, temperature and the interaction between the two. Our results indicate that (i) predator-prey body-size ratios decrease with predator size at below-average temperatures and increase with predator size at above-average temperatures, and (ii) that the effect of temperature on predator-prey body-size structure will be stronger at small and large body sizes and relatively weak at intermediate sizes. This systematic interaction may help to simplify forecasting the potentially complex consequences of warming on interaction strengths and food web stability.
Natural populations often show variation in traits that can affect the strength of interspecific interactions. Interaction strengths in turn influence the fate of pairwise interacting populations and the stability of food webs. Understanding the mechanisms relating individual phenotypic variation to interaction strengths is thus central to assess how trait variation affects population and community dynamics. We incorporated nonheritable variation in attack rates and handling times into a classical consumer–resource model to investigate how variation may alter interaction strengths, population dynamics, species persistence, and invasiveness. We found that individual variation influences species persistence through its effect on interaction strengths. In many scenarios, interaction strengths decrease with variation, which in turn affects species coexistence and stability. Because environmental change alters the direction and strength of selection acting upon phenotypic traits, our results have implications for species coexistence in a context of habitat fragmentation, climate change, and the arrival of exotic species to native ecosystems.
.Disentangling the processes that shape the organization of ecological assemblages and its implications for species coexistence is one of the foremost challenges of ecology. Although insightful advances have recently related community composition and structure with species coexistence in mutualistic and antagonistic networks, little is known regarding other species assemblages, such as those of scavengers exploiting carrion. Here we studied seven assemblages of scavengers feeding on ungulate carcasses in mainland Spain. We used dynamical models to investigate if community composition, species richness and structure (nestedness) affect species coexistence at carcasses. Scavenging networks showed a nested pattern in sites where highly effi cient, obligate scavengers (i.e., vultures) were present and a non-nested pattern everywhere else. Griffon Vulture ( Gyps fulvus ) and certain meso-facultative mammalian scavengers (i.e., red fox, Vulpes vulpes , and stone marten, Martes foina ) were the main species contributing to nestedness. Assemblages with vultures were also the richest ones in species. Nested species-rich assemblages with vulture presence were associated with high carcass consumption rates, indicating higher interspecifi c competition at the local scale. However, the proportion of species stopping the consumption of carrion (as derived from the competitive dynamic model) stabilized at high richness and nestedness levels. This suggests that high species richness and nestedness may characterize scavenging networks that are robust to high levels of interspecifi c competition for carrion. Some facilitative interactions driven by vultures and major facultative scavengers could be behind these observations. Our fi ndings are relevant for understanding species' coexistence in highly competitive systems.
Understanding whether and how environmental conditions may impact food web structure at a global scale is central to our ability to predict how food webs will respond to climate change. However, such an understanding is nascent. Using the best resolved available food webs to date, I address whether latitude, temperature, or both, explain the number of species and feeding interactions, the proportion of basal and top species, as well as the degree of omnivory, connectance and the number of trophic levels across food webs. I found that temperature is a more parsimonious predictor of food web structure than latitude. Temperature directly reduces the number of species, the proportion of basal species and the number of interactions while it indirectly increases omnivory levels, connectance and trophic level through its direct effects on the fraction and number of basal species. While direct impacts of temperature are routinely taken into account to predict how ecosystems may respond to global climate change, indirect effects have been largely overlooked. These results thus suggest that food webs may be affected by a combination of biotic and abiotic conditions, both directly and indirectly, in a changing world.
Microbial communities regulate ecosystem responses to climate change. However, predicting these responses is challenging because of complex interactions among processes at multiple levels of organization. Organismal traits that determine individual performance and ecological interactions are essential for scaling up environmental responses from individuals to ecosystems. We combine protist microcosm experiments and mathematical models to show that key traits—cell size, shape, and contents—each explain different aspects of species’ demographic responses to changes in temperature. These differences in species’ temperature responses have complex cascading effects across levels of organization—causing nonlinear shifts in total community respiration rates across temperatures via coordinated changes in community composition, equilibrium densities, and community–mean species mass in experimental protist communities that tightly match theoretical predictions. Our results suggest that traits explain variation in population growth, and together, these two factors scale up to influence community- and ecosystem-level processes across temperatures. Connecting the multilevel microbial processes that ultimately influence climate in this way will help refine predictions about complex ecosystem–climate feedbacks and the pace of climate change itself.
It is increasingly recognized that evolution may occur in ecological time. It is not clear, however, how fast evolution – or phenotypic change more generally – may be in comparison with the associated ecology, or whether systems with fast ecological dynamics generally have relatively fast rates of phenotypic change. We developed a new dataset on standardized rates of change in population size and phenotypic traits for a wide range of species and taxonomic groups. We show that rates of change in phenotypes are generally no more than 2/3, and on average about 1/4, the concurrent rates of change in population size. There was no relationship between rates of population change and rates of phenotypic change across systems. We also found that the variance of both phenotypic and ecological rates increased with the mean across studies following a power law with an exponent of two, while temporal variation in phenotypic rates was lower than in ecological rates. Our results are consistent with the view that ecology and evolution may occur at similar time scales, but clarify that only rarely do populations change as fast in traits as they do in abundance.
Food webs (i.e., networks of species and their feeding interactions) share multiple structural features across ecosystems. The factors explaining such similarities are still debated, and the role played by most organismal traits and their intraspecific variation is unknown. Here, we assess how variation in traits controlling predator-prey interactions (e.g., body size) affects food web structure. We show that larger phenotypic variation increases connectivity among predators and their prey as well as total food intake rate. For predators able to eat only a few species (i.e., specialists), low phenotypic variation maximizes intake rates, while the opposite is true for consumers with broader diets (i.e., generalists). We also show that variation sets predator trophic level by determining interaction strengths with prey at different trophic levels. Merging these results, we make two general predictions about the structure of food webs: () trophic level should increase with predator connectivity, and () interaction strengths should decrease with prey trophic level. We confirm these predictions empirically using a global dataset of well-resolved food webs. Our results provide understanding of the processes structuring food webs that include functional traits and their naturally occurring variation.
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