Owen L. Petchey

Environmental warming alters food-web structure and ecosystem function

We know little about how ecosystems of different complexity will respond to global warming. Microcosms permit experimental control over species composition and rates of environmental change. Here we show using microcosm experiments that extinction risk in warming environments depends on trophic position but remains unaffected by biodiversity. Warmed communities disproportionately lose top predators and herbivores, and become increasingly dominated by autotrophs and bacterivores. Changes in the relative distribution of organisms among trophically defined functional groups lead to differences in ecosystem function beyond those expected from temperature-dependent physiological rates. Diverse communities retain more species than depauperate ones, as predicted by the insurance hypothesis, which suggests that high biodiversity buffers against the effects of environmental variation because tolerant species are more likely to be found. Studies of single trophic levels clearly show that warming can affect the distribution and abundance of species, but complex responses generated in entire food webs greatly complicate inferences based on single functional groups.

Size, foraging, and food web structure

Understanding what structures ecological communities is vital to answering questions about extinctions, environmental change, trophic cascades, and ecosystem functioning. Optimal foraging theory was conceived to increase such understanding by providing a framework with which to predict species interactions and resulting community structure. Here, we use an optimal foraging model and allometries of foraging variables to predict the structure of real food webs. The qualitative structure of the resulting model provides a more mechanistic basis for the phenomenological rules of previous models. Quantitative analyses show that the model predicts up to 65% of the links in real food webs. The deterministic nature of the model allows analysis of the models successes and failures in predicting particular interactions. Predacious and herbivorous feeding interactions are better predicted than pathogenic, parasitoid, and parasitic interactions. Results also indicate that accurate prediction and modeling of some food webs will require incorporating traits other than body size and diet choice models specific to different types of feeding interaction. The model results support the hypothesis that individual behavior, subject to natural selection, determines individual diets and that food web structure is the sum of these individual decisions.

HOW DO DIFFERENT MEASURES OF FUNCTIONAL DIVERSITY PERFORM

Biodiversity can influence ecosystem functioning through changes in the amount of resource use complementary among species. Functional diversity is a measure of biodiversity that aims to quantify resource use complementarity and thereby explain and predict ecosystem functioning. The primary goal of this article is to compare the explanatory power of four measures of functional diversity: species richness, functional group richness, functional attribute diversity, and FD. The secondary goal is to showcase the novel methods required for calculating functional attribute diversity and FD. We find that species richness and functional group richness explain the least variation in above- ground biomass production within and across grassland biodiversity manipulations at six European locations; functional attribute diversity and FD explain greater variation. Rea- sons for differences in explanatory power are discussed, such as the relatively greater amount of information and fewer assumptions included in functional attribute diversity and FD. We explore the opportunities and limitations of the particular methods we used to calculate functional attribute diversity and FD. These mainly concern how best to select the information used to calculate them.

Biodiversity Conservation and the Millennium Development Goals

Any near-term gains in reducing extreme poverty will be maintained only if environmental sustainability is also achieved. The Millennium Development Goals (MDGs) are designed to inspire efforts to improve peoples lives by, among other priorities, halving extreme poverty by 2015 (1). Analogously, concern about global decline in biodiversity and degradation of ecosystem services (2) gave rise in 1992 to the Convention on Biological Diversity (CBD). The CBD target “to achieve by 2010 a significant reduction of the current rate of biodiversity loss” was incorporated into the MDGs in 2002. Our lack of progress toward the 2010 target (3, 4) could undermine achievement of the MDGs and poverty reduction in the long term. With increasing global challenges, such as population growth, climate change, and overconsumption of ecosystem services, we need further integration of the poverty alleviation and biodiversity conservation agendas.

Foraging biology predicts food web complexity

Food webs, the networks of feeding links between species, are central to our understanding of ecosystem structure, stability, and function. One of the key aspects of food web structure is complexity, or connectance, the number of links expressed as a proportion of the total possible number of links. Connectance (complexity) is linked to the stability of webs and is a key parameter in recent models of other aspects of web structure. However, there is still no fundamental biological explanation for connectance in food webs. Here, we propose that constraints on diet breadth, driven by optimal foraging, provide such an explanation. We show that a simple diet breadth model predicts highly constrained values of connectance as an emergent consequence of individual foraging behavior. When combined with features of real food web data, such as taxonomic and trophic aggregation and cumulative sampling of diets, the model predicts well the levels of connectance and scaling of connectance with species richness, seen in real food webs. This result is a previously undescribed synthesis of foraging theory and food web theory, in which network properties emerge from the behavior of individuals and, as such, provides a mechanistic explanation of connectance currently lacking in food web models.

More than a meal… integrating non‐feeding interactions into food webs

Organisms eating each other are only one of many types of well documented and important interactions among species. Other such types include habitat modification, predator interference and facilitation. However, ecological network research has been typically limited to either pure food webs or to networks of only a few (<3) interaction types. The great diversity of non-trophic interactions observed in nature has been poorly addressed by ecologists and largely excluded from network theory. Herein, we propose a conceptual framework that organises this diversity into three main functional classes defined by how they modify specific parameters in a dynamic food web model. This approach provides a path forward for incorporating non-trophic interactions in traditional food web models and offers a new perspective on tackling ecological complexity that should stimulate both theoretical and empirical approaches to understanding the patterns and dynamics of diverse species interactions in nature.

Universal temperature and body-mass scaling of feeding rates

Knowledge of feeding rates is the basis to understand interaction strength and subsequently the stability of ecosystems and biodiversity. Feeding rates, as all biological rates, depend on consumer and resource body masses and environmental temperature. Despite five decades of research on functional responses as quantitative models of feeding rates, a unifying framework of how they scale with body masses and temperature is still lacking. This is perplexing, considering that the strength of functional responses (i.e. interaction strengths) is crucially important for the stability of simple consumer–resource systems and the persistence, sustainability and biodiversity of complex communities. Here, we present the largest currently available database on functional response parameters and their scaling with body mass and temperature. Moreover, these data are integrated across ecosystems and metabolic types of species. Surprisingly, we found general temperature dependencies that differed from the Arrhenius terms predicted by metabolic models. Additionally, the body-mass-scaling relationships were more complex than expected and differed across ecosystems and metabolic types. At local scales (taxonomically narrow groups of consumer–resource pairs), we found hump-shaped deviations from the temperature and body-mass-scaling relationships. Despite the complexity of our results, these body-mass- and temperature-scaling models remain useful as a mechanistic basis for predicting the consequences of warming for interaction strengths, population dynamics and network stability across communities differing in their size structure.

Extinction and the loss of functional diversity

Although it is widely thought to influence ecosystem processes, there is little consensus on an appropriate measure of functional diversity. The two major perspectives, to date, are to assume that every species is functionally unique, or to assume that some species are functionally identical, such that functional groups exist. Using a continuous measure of functional diversity (FD) derived from the quantitative functional traits of species, we show that the loss of functional diversity from six natural assemblages was rapid compared with rates of loss from comparable simulated assemblages. Loss of FD occurred faster than loss of functional–group diversity in four of the six natural assemblages. Patterns of functional–group diversity loss depended on the number of functional groups and the number of species in an assemblage. Extinctions that occurred first for species with particular traits (e.g. low leaf nitrogen concentration, deep roots and large body size) caused greater loss of FD than expected by chance in four of the six natural assemblages. In two real assemblages, these trait–dependent extinctions had more severe effects on FD than our simulated worst–case extinction scenario. These data suggest that conserving a large proportion of the functional traits of species requires conserving a large proportion of all species.

Ecological Networks in a Changing Climate

Summary Attempts to gauge the biological impacts of climate change have typically focussed on the lower levels of organization (individuals to populations), rather than considering more complex multi-species systems, such as entire ecological networks (food webs, mutualistic and host–parasitoid networks). We evaluate the possibility that a few principal drivers underpin network-level responses to climate change, and that these drivers can be studied to develop a more coherent theoretical framework than is currently provided by phenomenological approaches. For instance, warming will elevate individual ectotherm metabolic rates, and direct and indirect effects of changes in atmospheric conditions are expected to alter the stoichiometry of interactions between primary consumers and basal resources; these effects are general and pervasive, and will permeate through the entire networks that they affect. In addition, changes in the density and viscosity of aqueous media could alter interactions among very small organisms and disrupt the pycnoclines that currently compartmentalize many aquatic networks in time and space. We identify a range of approaches and potential model systems that are particularly well suited to network-level studies within the context of climate change. We also highlight potentially fruitful areas of research with a view to improving our predictive power regarding climate change impacts on networks. We focus throughout on mechanistic approaches rooted in first principles that demonstrate potential for application across a wide range of taxa and systems.

Effects on population persistence: the interaction between environmental noise colour, intraspecific competition and space

It is accepted that accurate estimation of risk of population extinction, or persistence time, requires prediction of the effect of fluctuations in the environment on population dynamics. Generally, the greater the magnitude, or variance, of environmental stochasticity, the greater the risk of population extinction. Another characteristic of environmental stochasticity, its colour, has been found to affect population persistence. This is important because real environmental variables, such as temperature, are reddened or positively temporally autocorrelated. However, recent work has disagreed about the effect of reddening environmental stochasticity. Ripa and Lundberg (1996) found increasing temporal autocorrelation (reddening) decreased the risk of extinction, whereas a simple and powerful intuitive argument (Lawton 1988) predicts increased risk of extinction with reddening. This study resolves the apparent contradiction, in two ways, first, by altering the dynamic behaviour of the population models. Overcompensatory dynamics result in persistence times increasing with increased temporal autocorrelation; undercompensatory dynamics result in persistence times decreasing with increased temporal autocorrelation. Secondly, in a spatially subdivided population, with a reasonable degree of spatial heterogeneity in patch quality, increasing temporal autocorrelation in the environment results in decreasing persistence time for both types of competition. Thus, the inclusion of coloured noise into ecological models can have subtle interactions with population dynamics.