A framework for understanding climate change impacts through non-compensatory intra- and interspecific climate change responses.

Understanding and predicting population responses to climate change is a crucial challenge. A key component of population responses to climate change are cases in which focal biological rates (e.g., population growth rates) change in response to climate change due to non-compensatory effects of changes in the underlying components (e.g., birth and death rates) determining the focal rates. We refer to these responses as non-compensatory climate change effects. As differential responses of biological rates to climate change have been documented in a variety of systems and arise at multiple levels of organization within and across species, non-compensatory effects may be nearly ubiquitous. Yet, how non-compensatory climate change responses combine and scale to influence the demographics of populations is often unclear and requires mapping them to the birth and death rates underlying population change. We provide a flexible framework for incorporating non-compensatory changes in upstream rates within and among species and mapping their consequences for additional downstream rates across scales to their eventual effects on population growth rates. Throughout, we provide specific examples and potential applications of the framework. We hope this framework helps to enhance our understanding of and unify research on population responses to climate change.

Predator feeding rates may often be unsaturated under typical prey densities.

Predator feeding rates (described by their functional response) must saturate at high prey densities. Although thousands of manipulative functional response experiments show feeding rate saturation at high densities under controlled conditions, it remains unclear how saturated feeding rates are at natural prey densities. The general degree of feeding rate saturation has important implications for the processes determining feeding rates and how they respond to changes in prey density. To address this, we linked two databases-one of functional response parameters and one on mass-abundance scaling-through prey mass to calculate a feeding rate saturation index. We find that: (1) feeding rates may commonly be unsaturated and (2) the degree of saturation varies with predator and prey taxonomic identities and body sizes, habitat, interaction dimension and temperature. These results reshape our conceptualisation of predator-prey interactions in nature and suggest new research on the ecological and evolutionary implications of unsaturated feeding rates.

An Empiricist's Guide to Using Ecological Theory.

AbstractA scientific understanding of the biological world arises when ideas about how nature works are formalized, tested, refined, and then tested again. Although the benefits of feedback between theoretical and empirical research are widely acknowledged by ecologists, this link is still not as strong as it could be in ecological research. This is in part because theory, particularly when expressed mathematically, can feel inaccessible to empiricists who may have little formal training in advanced math. To address this persistent barrier, we provide a general and accessible guide that covers the basic, step-by-step process of how to approach, understand, and use ecological theory in empirical work. We first give an overview of how and why mathematical theory is created, then outline four specific ways to use both mathematical and verbal theory to motivate empirical work, and finally present a practical tool kit for reading and understanding the mathematical aspects of ecological theory. We hope that empowering empiricists to embrace theory in their work will help move the field closer to a full integration of theoretical and empirical research.

Quantifying predator functional responses under field conditions reveals interactive effects of temperature and interference with sex and stage.

Predator functional responses describe predator feeding rates and are central to predator-prey theory. Originally defined as the relationship between predator feeding rates and prey densities, it is now well known that functional responses are shaped by a multitude of factors. However, much of our knowledge about how these factors influence functional responses is based on laboratory studies that are generally logistically constrained to examining only a few factors simultaneously and that have unclear links to the conditions organisms experience in the field. We apply an observational approach for measuring functional responses to understand how sex/stage differences, temperature and predator densities interact to influence the functional response of zebra jumping spiders on midges under natural conditions. We used field surveys of jumping spiders to infer their feeding rates and examine the relationships between feeding rates, sex/stage, midge density, predator density and temperature using generalized additive models. We then used the relationships supported by the models to fit parametric functional responses to the data. We find that feeding rates of zebra jumping spiders follow some expectations from previous laboratory studies such as increasing feeding rates with body size and decreasing feeding rates with predator densities. However, in contrast to previous results, our results also show a lack of temperature response in spider feeding rates and differential decreases in the feeding rates of females and juveniles with densities of different spider sexes/stages. Our results illustrate the multidimensional nature of functional responses in natural settings and reveal how factors influencing functional responses can interact with one another through behaviour and morphology. Further studies investigating the influence of multiple mechanisms on predator functional responses under field conditions will increase our understanding of the drivers of predator-prey interaction strengths and their consequences for communities and ecosystems.

Fundamental contradictions among observational and experimental estimates of non-trophic species interactions.

The difficulty of experimentally quantifying non-trophic species interactions has long troubled ecologists. Increasingly, a new application of the classic "checkerboard distribution" approach is used to infer interactions by examining the pairwise frequency at which species are found to spatially co-occur. However, the link between spatial associations, as estimated from observational co-occurrence, and species interactions has not been tested. Here we used nine common statistical methods to estimate associations from surveys of rocky intertidal communities in the Northeast Pacific Ocean. We compared those inferred associations with a new data set of experimentally determined net and direct species interactions. Although association methods generated networks with aggregate structure similar to previously published interaction networks, each method detected a different set of species associations from the same data set. Moreover, although association methods generally performed better than a random model, associations rarely matched empirical net or direct species interactions, with high rates of false positives and true positives, and many false negatives. Our findings cast doubt on studies that equate species co-occurrences to species interactions and highlight a persistent, unanswered question: how do we interpret spatial patterns in communities? We suggest future research directions to unify the observational and experimental study of species interactions, and discuss the need for community standards and best practices in association analysis.

Quantifying predator dependence in the functional response of generalist predators.

A long-standing debate concerns how functional responses are best described. Theory suggests that ratio dependence is consistent with many food web patterns left unexplained by the simplest prey-dependent models. However, for logistical reasons, ratio dependence and predator dependence more generally have seen infrequent empirical evaluation and then only so in specialist predators, which are rare in nature. Here we develop an approach to simultaneously estimate the prey-specific attack rates and predator-specific interference (facilitation) rates of predators interacting with arbitrary numbers of prey and predator species in the field. We apply the approach to surveys and experiments involving two intertidal whelks and their full suite of potential prey. Our study provides strong evidence for predator dependence that is poorly described by the ratio dependent model over manipulated and natural ranges of species abundances. It also indicates how, for generalist predators, even the qualitative nature of predator dependence can be prey-specific.

The application of Bayesian hierarchical models to quantify individual diet specialization.

Intraspecific variation in ecologically relevant traits is widespread. In generalist predators in particular, individual diet specialization is likely to have important consequences for food webs. Understanding individual diet specialization empirically requires the ability to quantify individual diet preferences accurately. Here we compare the currently used frequentist maximum likelihood approach, which infers individual preferences using the observed prey proportions to Bayesian hierarchical models that instead estimate these proportions. Using simulated and empirical data, we find that the approach of using observed prey proportions consistently overestimates diet specialization relative to the Bayesian hierarchical approach when the number of prey observations per individual is low or the number of prey observations vary among individuals, two common features of empirical data. Furthermore, the Bayesian hierarchical approach permits the estimation of point estimates for both prey proportions and their variability within and among levels of organization (i.e., individuals, experimental treatments, populations), while also characterizing the uncertainty of these estimates in ways inaccessible to frequentist methods. The Bayesian hierarchical approach provides a useful framework for improving the quantification and understanding of intraspecific variation in diet specialization studies.

Temperature and predators as interactive drivers of community properties.

The effects of warming on ecological communities emerge from a range of potentially asymmetric impacts on individual physiology and development. Understanding these responses, however, is limited by our ability to connect mechanisms or emergent patterns across the many processes that drive variation in demography. Further complicating this understanding is the gain or loss of predators to many communities, which may interact with changes in temperature to drive community change. Here we conducted a factorial warming and predation experiment to test generalized predictions about responses to warming. We used microcosms with a range of protists, rotifers, and a gastrotrich, with and without the predator Actinosphaerium, to assess changes in diversity, body size, function, and composition in response to warming. We find that community respiration and predator:prey biovolume ratios peak at intermediate temperatures, while species richness declined with temperature. We also found that overall biomass increased with species richness, driven by the effect of temperature on richness. There was little evidence of an interaction between predation and temperature change, likely because the predator was mostly limited to the intermediate temperatures. Overall, our results suggest that general predictions about community change are still challenging to make but may benefit by considering multiple dimensions of community patterns in an integrated way.

Estimating predator functional responses using the times between prey captures.

Predator functional responses describe predator feeding rates and are central to predator-prey theory. Ecologists have measured thousands of predator functional responses using the same basic experimental method. However, this design is ill-suited to address many current questions regarding functional responses. We derive a new experimental design and statistical analysis that quantifies functional responses using the times between a predators' feeding events requiring only one or a few trials. We examine the feasibility of the experimental method and analysis using simulations to assess the ability of the statistical model to estimate functional response parameters and perform a proof-of-concept experiment estimating the functional responses of two individual jumping spiders. Our simulations show that the statistical method reliably estimates functional response parameters. Our proof-of-concept experiment illustrates that the method provides reasonable estimates of functional response parameters. By virtue of the fewer number of trials required to measure a functional response, the method derived here promises to expand the questions that can be addressed using functional response experiments and the systems in which they can be measured. Thus, we hope that our method will refine our understanding of functional responses and predator-prey interactions more generally.

Relative prey abundance and predator preference predict individual diet variation in prey-switching experiments.

Individual diet specialization appears widespread and has several ecological ramifications. Hypotheses on the causes of diet specialization generally assume prey preferences differ among predator individuals. They then predict how the magnitude of diet variation should change when ecological factors (e.g., intraspecific competition) alter prey abundances. However, the magnitude of diet variation is expected to change with prey abundances due to stochasticity in the foraging process even if all predators share the same prey preferences. Here I show that the relative prey abundance where diet variation is maximized and the magnitudes of diet variation in prey switching experiments are predicted well by a simple stochastic foraging model based only on relative prey abundances and a shared relative prey preference among predators. These results suggest that the effects of stochasticity during foraging may confound studies of individual diet specialization if these effects are not accounted for in experimental design or interpretation. Furthermore, the stochastic foraging model provides simple baseline expectations for theoretical studies on the ecological consequences of diet variation and offers a way forward on quantitative predictions of how ecological factors influence the magnitude of diet variation when stochasticity during foraging and diet specialization occur simultaneously. Last, this study highlights the continued importance of integrating stochasticity into mechanistic ecological hypotheses.

Influence of sediment characteristics on the composition of soft-sediment intertidal communities in the northern Gulf of Mexico.

Benthic infaunal communities are important components of coastal ecosystems. Understanding the relationships between the structure of these communities and characteristics of the habitat in which they live is becoming progressively more important as coastal systems face increasing stress from anthropogenic impacts and changes in climate. To examine how sediment characteristics and infaunal community composition were related along the northern Gulf of Mexico coast, we sampled intertidal infaunal communities at seven sites covering common habitat types at a regional scale. Across 69 samples, the communities clustered into four distinct groups on the basis of faunal composition. Nearly 70% of the variation in the composition of the communities was explained by salinity, median grain size, and total organic content. Our results suggest that at a regional level coarse habitat characteristics are able to explain a large amount of the variation among sites in infaunal community structure. By examining the relationships between infaunal communities and their sedimentary habitats, we take a necessary first step that will allow the exploration of how changes in habitat and community composition influence higher trophic levels and ecosystem scale processes.