Density-dependent allometric functional response models

Disentangling the nonlinear effects of habitat complexity on functional responses

Structural complexity of habitats modifies trophic interactions by providing refuges and altering predator and prey behaviour. Nonlinear effects on trophic interaction strengths driven by these mechanisms may alter food web dynamics and community structure in response to habitat modifications. However, changes in functional response, the relationship between prey density and feeding rate, along habitat complexity (HC) gradients are little understood. We quantified functional responses along a HC gradient from an entirely unstructured to highly structured habitat in a freshwater system, using dragonfly larvae (Aeshna cyanea) preying on Chaoborus obscuripes larvae. To disentangle mechanisms by which changes in HC affect functional responses, we used two different approaches-a population-level and a behavioural experiment-applied an information theoretic approach to identify plausible links between HC and functional response parameters, and compared our results to previous studies. Functional response shape did not change, but we found strong evidence for nonlinear dependence of attack rate and handling time on HC in our study. Combined results from both experiments imply that attack rate increased stepwise between the unstructured and structured habitats in line with the threshold hypothesis, because the predators gained better access to the prey. Handling time was lowest at an intermediate HC level in the population-level experiment while the direct estimate of handling time did not vary with HC in the behavioural experiment. These differences point towards HC-driven changes in foraging activity and other predator and prey behaviour. Most previous studies reported stepwise decrease in attack rate in line with the threshold hypothesis or no change with increasing HC. Moreover, changes in the handling time parameter with HC appear to be relatively common but not conforming to the threshold hypothesis. Overall, increased HC appears to, respectively, weaken and strengthen trophic links in 2D and 3D predator-prey interactions. We conclude that detailed understanding of HC effects on food webs requires complementary experimental approaches across HC gradients that consider predator foraging strategies and predator and prey behaviour. Such studies can also help guide conservation efforts as addition of structural elements is frequently used for restoration of degraded aquatic habitats.

Optimal experimental design for predator-prey functional response experiments

Functional response models are important in understanding predator-prey interactions. The development of functional response methodology has progressed from mechanistic models to more statistically motivated models that can account for variance and the over-dispersion commonly seen in the datasets collected from functional response experiments. However, little information seems to be available for those wishing to prepare optimal parameter estimation designs for functional response experiments. It is worth noting that optimally designed experiments may require smaller sample sizes to achieve the same statistical outcomes as non-optimally designed experiments. In this paper, we develop a model-based approach to optimal experimental design for functional response experiments in the presence of parameter uncertainty (also known as a robust optimal design approach). Further, we develop and compare new utility functions which better focus on the statistical efficiency of the designs; these utilities are generally applicable for robust optimal design in other applications (not just in functional response). The methods are illustrated using a beta-binomial functional response model for two published datasets: an experiment involving the freshwater predator Notonecta glauca (an aquatic insect) preying on Asellus aquaticus (a small crustacean), and another experiment involving a ladybird beetle (Propylea quatuordecimpunctata L.) preying on the black bean aphid (Aphis fabae Scopoli). As a by-product, we also derive necessary quantities to perform optimal design for beta-binomial regression models, which may be useful in other applications.

Landscape variation influences trophic cascades in dengue vector food webs

The epidemiology of vector-borne diseases is governed by a structured array of correlative and causative factors, including landscape (for example, rural versus urban), abiotic (for example, weather), and biotic (for example, food web) factors. Studies of mosquito-borne diseases rarely address these multiple factors at large spatial scales, which limits insights into how human alterations of landscapes and food webs alter mosquito abundance. We used structural equation modeling to identify the relative magnitude and direction of landscape, abiotic, and food web factors on Aedes larvae and adults across 70 sites in northern Thailand. Food web factors were modeled as mosquito-predator trophic cascades. Landscape context affected mosquito-predator communities in aquatic and terrestrial environments via cascading food web interactions. Several mosquito predators within these food webs showed potential as biocontrol agents in mosquito population control, but their potentials for control were landscape-dependent. In terrestrial food webs, the habitat-sensitive tokay gecko structured mosquito-predator communities, indicating that a conservation approach to vector control could be a useful addition to existing control efforts.