Evaluating consumptive and nonconsumptive predator effects on prey density using field time-series data

A skewed literature: Few studies evaluate the contribution of predation-risk effects to natural field patterns

A narrative in ecology is that prey modify traits to reduce predation risk, and the trait modification has costs large enough to cause ensuing demographic, trophic and ecosystem consequences, with implications for conservation, management and agriculture. But ecology has a long history of emphasising that quantifying the importance of an ecological process ultimately requires evidence linking a process to unmanipulated field patterns. We suspected that such process-linked-to-pattern (PLP) studies were poorly represented in the predation risk literature, which conflicts with the confidence often given to the importance of risk effects. We reviewed 29 years of the ecological literature which revealed that there are well over 4000 articles on risk effects. Of those, 349 studies examined risk effects on prey fitness measures or abundance (i.e., non-consumptive effects) of which only 26 were PLP studies, while 275 studies examined effects on other interacting species (i.e., trait-mediated indirect effects) of which only 35 were PLP studies. PLP studies were narrowly focused taxonomically and included only three that examined unmanipulated patterns of prey abundance. Before concluding a widespread and influential role of predation-risk effects, more attention must be given to linking the process of risk effects to unmanipulated patterns observed across diverse ecosystems.

Bagged filters for partially observed interacting systems

Bagging (i.e., bootstrap aggregating) involves combining an ensemble of bootstrap estimators. We consider bagging for inference from noisy or incomplete measurements on a collection of interacting stochastic dynamic systems. Each system is called a unit, and each unit is associated with a spatial location. A motivating example arises in epidemiology, where each unit is a city: the majority of transmission occurs within a city, with smaller yet epidemiologically important interactions arising from disease transmission between cities. Monte Carlo filtering methods used for inference on nonlinear non-Gaussian systems can suffer from a curse of dimensionality as the number of units increases. We introduce bagged filter (BF) methodology which combines an ensemble of Monte Carlo filters, using spatiotemporally localized weights to select successful filters at each unit and time. We obtain conditions under which likelihood evaluation using a BF algorithm can beat a curse of dimensionality, and we demonstrate applicability even when these conditions do not hold. BF can out-perform an ensemble Kalman filter on a coupled population dynamics model describing infectious disease transmission. A block particle filter also performs well on this task, though the bagged filter respects smoothness and conservation laws that a block particle filter can violate.

Direct effects influence larval salamander size and density more than indirect effects

Direct and indirect effects both influence population and community dynamics. The relative strengths of these pathways are often compared using experimental approaches, but their evaluation in situ has been less frequent. We examined how individual and aggregate impacts of direct and indirect effects of species densities, proxies for competition and predation pressure, and habitat variables influenced patterns of larval density and body size of ringed (Ambystoma annulatum) and spotted salamanders (A. maculatum). We surveyed > 150 ponds in Missouri, USA, from 2012 to 2014 to measure the density and body size of each focal species, the density of co-occurring pond food web members, and select habitat features. We used structural equation modeling to quantify the relative importance of direct and indirect pathways on both body size and larval density. Overall, both responses were explained through a combination of direct and indirect effects. However, the magnitudes of direct effects were often greater than indirect effects. Some of the direct and indirect relationships with larval salamander size and density were also consistent with results from experimental studies. Finally, total direct and indirect effects were often weaker due to habitat and density variables negating each other's impacts. Overall, our study shows that direct effects were equivalent to, or more important than, indirect effects. We also demonstrate that the effects stemming from individual relationships can sum to produce net patterns that are negligible in magnitude. Further work on direct and indirect effects with observational data are needed to examine their magnitudes in natural communities.