Sophie Smout

The Functional Response of a Generalist Predator

Background Predators can have profound impacts on the dynamics of their prey that depend on how predator consumption is affected by prey density (the predators functional response). Consumption by a generalist predator is expected to depend on the densities of all its major prey species (its multispecies functional response, or MSFR), but most studies of generalists have focussed on their functional response to only one prey species. Methodology and principal findings Using Bayesian methods, we fit an MSFR to field data from an avian predator (the hen harrier Circus cyaneus) feeding on three different prey species. We use a simple graphical approach to show that ignoring the effects of alternative prey can give a misleading impression of the predators effect on the prey of interest. For example, in our system, a “predator pit” for one prey species only occurs when the availability of other prey species is low. Conclusions and significance The Bayesian approach is effective in fitting the MSFR model to field data. It allows flexibility in modelling over-dispersion, incorporates additional biological information into the parameter priors, and generates estimates of uncertainty in the models predictions. These features of robustness and data efficiency make our approach ideal for the study of long-lived predators, for which data may be sparse and management/conservation priorities pressing.

Ecosystem-based management objectives for the North Sea:Riding the forage fish rollercoaster

The North Sea provides a useful model for considering forage fish (FF) within ecosystem-based management as it has a complex assemblage of FF species. This paper is designed to encourage further debate and dialogue between stakeholders about management objectives. Changing the management of fisheries on FF will have economic consequences for all fleets in the North Sea. The predators that are vulnerable to the depletion of FF are Sandwich terns, great skua and common guillemots, and to a lesser extent, marine mammals. Comparative evaluations of management strategies are required to consider whether maintaining the reserves of prey biomass or a more integral approach of monitoring mortality rates across the trophic system is more robust under the ecosystem approach. In terms of trophic energy transfer, stability, and resilience of the ecosystem, FF should be considered as both a sized-based pool of biomass and as species components of the system by managers and modellers. Policy developers should not consider the knowledge base robust enough to embark on major projects of ecosystem engineering. Management plans appear able to maintain sustainable exploitation in the short term. Changes in the productivity of FF populations are inevitable so management should remain responsive and adaptive.

Estimating demographic parameters for capture–recapture data in the presence of multiple mark types

In mark-recapture studies, various techniques can be used to uniquely identify individual animals, such as ringing, tagging or photo-identification using natural markings. In some long-term studies more than one type of marking procedure may be implemented during the study period. In these circumstances, ignoring the different mark types can produce biased survival estimates since the assumption that the different mark types are equally catchable (homogeneous capture probability across mark types) may be incorrect. We implement an integrated approach where we simultaneously analyse data obtained using three different marking techniques, assuming that animals can be cross-classified across the different mark types. We discriminate between competing models using the AIC statistic. This technique also allows us to estimate both relative mark-loss probabilities and relative recapture efficiency rates for the different marking methods. We initially perform a simulation study to explore the different biases that can be introduced if we assume a homogeneous recapture probability over mark type, before applying the method to a real dataset. We make use of data obtained from an intensive long-term observational study of UK female grey seals (Halichoerus grypus) at a single breeding colony, where three different methods are used to identify individuals within a single study: branding, tagging and photo-identification based on seal coat pattern or pelage.

SENSITIVITY TO ASSUMPTIONS IN MODELS OF GENERALIST PREDATION ON A CYCLIC PREY

Ecological theory predicts that generalist predators should damp or suppress long-term periodic fluctuations (cycles) in their prey populations and depress their average densities. However, the magnitude of these impacts is likely to vary depending on the availability of alternative prey species and the nature of ecological mechanisms driving the prey cycles. These multispecies effects can be modeled explicitly if parameterized functions relating prey consumption to prey abundance, and realistic population dynamical models for the prey, are available. These requirements are met by the interaction between the Hen Harrier (Circus cyaneus) and three of its prey species in the United Kingdom, the Meadow Pipit (Anthus pratensis), the field vole (Microtus agrestis), and the Red Grouse (Lagopus lagopus scoticus). We used this system to investigate how the availability of alternative prey and the way in which prey dynamics are modeled might affect the behavior of simple trophic networks. We generated cycles in one of the prey species (Red Grouse) in three different ways: through (1) the interaction between grouse density and macroparasites, (2) the interaction between grouse density and male grouse aggressiveness, and (3) a generic, delayed density-dependent mechanism. Our results confirm that generalist predation can damp or suppress grouse cycles, but only when the densities of alternative prey are low. They also demonstrate that diametrically opposite indirect effects between pairs of prey species can occur together in simple systems. In this case, pipits and grouse are apparent competitors, whereas voles and grouse are apparent facilitators. Finally, we found that the quantitative impacts of the predator on prey density differed among the three models of prey dynamics, and these differences were robust to uncertainty in parameter estimation and environmental stochasticity.

Impact of wild prey availability on livestock predation by snow leopards

An increasing proportion of the worlds poor is rearing livestock today, and the global livestock population is growing. Livestock predation by large carnivores and their retaliatory killing is becoming an economic and conservation concern. A common recommendation for carnivore conservation and for reducing predation on livestock is to increase wild prey populations based on the assumption that the carnivores will consume this alternative food. Livestock predation, however, could either reduce or intensify with increases in wild prey depending on prey choice and trends in carnivore abundance. We show that the extent of livestock predation by the endangered snow leopard Panthera uncia intensifies with increases in the density of wild ungulate prey, and subsequently stabilizes. We found that snow leopard density, estimated at seven sites, was a positive linear function of the density of wild ungulates—the preferred prey—and showed no discernible relationship with livestock density. We also found that modelled livestock predation increased with livestock density. Our results suggest that snow leopard conservation would benefit from an increase in wild ungulates, but that would intensify the problem of livestock predation for pastoralists. The potential benefits of increased wild prey abundance in reducing livestock predation can be overwhelmed by a resultant increase in snow leopard populations. Snow leopard conservation efforts aimed at facilitating increases in wild prey must be accompanied by greater assistance for better livestock protection and offsetting the economic damage caused by carnivores.

The importance of developing modeling frameworks to inform conservation decisions: a response to Lonergan.

Hopefully, this approach represents a process that leads to open and constructive debate, to progress towards a better scientific understanding and to improvements in our ability to manage wildlife. Lonergan has examined our modeling in detail, and his critique raises a series of specific points and also some general questions about how data and expert opinion should be integrated into statistical and modeling frameworks with the aim of advising on conservation methods. we agree with several of Lonergan’s dictums, such as the need for open dialogue between the field biologists collecting data and the modelers subsequently using these data. Indeed, several of his specific points could have been resolved through such dialogue. For example, he queries the lack of data on harbor seal pups after mid-July, but this situation arises because pups cannot be reliably distinguished from juveniles after this time (thompson and Rothery 1987). similarly, detailed evaluation of previous studies from the moray Firth (e.g. thompson et al. 2007) would also call into question Lonergan’s assertion that shooting is the sole driver of historical declines in this population. Lonergan highlights his concerns about the performance and sensitivity of our model to specific assumptions and priors. these are important questions. we hope that in our publication, prior justification was explicit (pp. 155–158), prior sensitivity methodology was described in detail (supplement 3) and the implications of our modeling on our predictions were discussed in full (our points 1–5, pp. 158–159; points 1, 2, p 160). work continues, and our aim is to improve and simplify our modeling—for example, by considering seasonal variation in haulout probability. we are also exploring a question about the mis-match between one datum (2009 population estimate) and model predictions. the sensitivity of our results to these two issues was In his critique of our recent paper (matthiopoulos et al. 2014) on the population dynamics of harbor seals, Lonergan (2014a) argues that although our state–space modeling approach represents an interesting academic exercise, it nevertheless risks misleading those attempting to understand and manage observed declines of this species in UK waters. we argue that approaches like ours need not be misleading as long as information is provided on the assumptions and simplifications used. when such information is available, all assumptions (such as the shape and parameters of prior distributions in a Bayesian analysis) can then be subjected to scrutiny [such as that performed by Lonergan (2014a)], inevitably leading to future improvements.