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Identifying and understanding ecological drivers that influence wildlife populations is challenging but critical for conservation. This typically requires integrating long‐term data on both the population and potential drivers within statistical models that are suitable for analysing these complex relationships. State‐space models offer one method for integrating such data. Once implemented within a Bayesian framework, these analyses can control for multifactorial influences on populations, allowing one to extract otherwise undetectable correlations between the environment and the underlying, inferred demography.In the Moray Firth, Scotland, harbour seals have been counted annually for 30 years (1988–2018). A Bayesian state‐space model was used to explore whether patterns in vital rates were correlated to changes in prey abundance, inter‐specific competition (grey seal abundance), environmental variables [the North Atlantic Oscillation (NAO) and sea‐surface temperature], or level of biotoxins (saxitoxin and domoic acid) in the Moray Firth waters.The credible interval of the posterior distributions of three of these covariate coefficients (sandeel proxy, NAO and grey seal abundance) suggested that there was a relationship between those covariates and vital rates. Both the sandeel proxy and NAO showed a positive correlation with fecundity, whereas grey seal abundance had a negative impact on pup survival.This work demonstrates how an integrated state‐space modelling approach can bring together diverse data sets and point to important interactions with prey, and with other predators in the system. This suggests that the wider‐scale management of UK harbour seal populations with their contrasting temporal trends needs to account for variation in the marine ecosystem at appropriate spatial scales, in line with current policy concerning spatial planning in the marine environment. [ABSTRACT FROM AUTHOR]

Understanding the demographic response of free-living animal populations to different drivers is the first step towards reliable prediction of population trends., Penguins have exhibited dramatic declines in population size, and many studies have linked this to bottom-up processes altering the abundance of prey species. The effects of individual traits have been considered to a lesser extent, and top-down regulation through predation has been largely overlooked due to the difficulties in empirically measuring this at sea where it usually occurs., For 10 years (2003-2012), macaroni penguins ( Eudyptes chrysolophus) were marked with subcutaneous electronic transponder tags and re-encountered using an automated gateway system fitted at the entrance to the colony. We used multistate mark-recapture modelling to identify the different drivers influencing survival rates and a sensitivity analysis to assess their relative importance across different life stages., Survival rates were low and variable during the fledging year (mean = 0·33), increasing to much higher levels from age 1 onwards (mean = 0·89). We show that survival of macaroni penguins is driven by a combination of individual quality, top-down predation pressure and bottom-up environmental forces. The relative importance of these covariates was age specific. During the fledging year, survival rates were most sensitive to top-down predation pressure, followed by individual fledging mass, and finally bottom-up environmental effects. In contrast, birds older than 1 year showed a similar response to bottom-up environmental effects and top-down predation pressure., We infer from our results that macaroni penguins will most likely be negatively impacted by an increase in the local population size of giant petrels. Furthermore, this population is, at least in the short term, likely to be positively influenced by local warming. More broadly, our results highlight the importance of considering multiple causal effects across different life stages when examining the survival rates of seabirds. [ABSTRACT FROM AUTHOR]

Smout, S., Rindorf, A., Hammond, P. S., Harwood, J., and Matthiopoulos, J. Modelling prey consumption and switching by UK grey seals. – ICES Journal of Marine Science, 71: .Grey seals (Halichoerus grypus) are adaptable generalist predators whose diet includes commercial fish species such as cod. Consumption by the seals may reduce the size of some fish stocks or have an adverse effect on stock recovery programmes, especially because predation may trap sparse prey populations in a “predator pit”. To assess the likely impact of such effects, it is important to know how consumption and consequent predation mortality respond to the changing availability of prey. We present a model of grey seal consumption as a function of the availability of multiple prey types [a Multi-Species Functional Response (MSFR)]. We fit this MSFR to data on seal diet and prey availability (based on the overlap between the distributions of predators and prey). Bayesian methodology was employed to account for uncertainties in both dependent and independent variables, improve estimation convergence by the use of informative priors, and allow the estimation of missing data on prey availability. Both hyperbolic (Type 2) and sigmoidal (Type 3) functional response models were fitted to the data and the Type 3 model was clearly favoured during model selection, supporting the conclusion that seal–prey encounter rates change with prey abundance (sometimes referred to as “switching”). This suggests that some prey species may be vulnerable to predator pit effects. The fitted model reproduced contrasts in diet observed between different regions/years and, importantly, added information to the prior distributions of prey abundance in areas where the availability of some prey species (such as sandeels) was not known. This suggests that the diet of predators such as seals could provide information about the abundance and distribution of prey in areas that are not covered by fisheries and research surveys. [ABSTRACT FROM PUBLISHER]

Summary 1. The impact of hen harriers Circus cyaneus on red grouse Lagopus lagopus scoticus populations has received much attention. However, little has been done to model the population dynamics of the hen harrier alone. Such a model is needed to help inform the differing aims of conserving harriers and managing grouse moors, which serves as a reflection of human-wildlife conflicts around the globe. 2. On Langholm estate in Scotland, intensive studies have resulted in harrier numbers being known without error. We fit a Bayesian population model to these data, using a super-population model to permit inference in the presence of demographic and environmental stochasticity and in the absence of observation error. 3. Hen harriers have a straightforward life history. After fledging, juveniles show little natal site fidelity, often dispersing long distances into breeding areas rich in their preferred prey, the field vole Microtus agrestis and meadow pipit Anthus pratensis. Therefore, any increase in a local population is largely because of recruitment into the area as opposed to fledging success. Once birds have settled in an area, harriers are generally site faithful, with year-to-year survival depending, in part, on the density of meadow pipits. 4. Our model suggests that temporal patterns in harrier numbers on managed grouse moors, in the absence of illegal persecution, are influenced by vole numbers, whereas meadow pipit density appears to have a limited effect. 5. Synthesis and applications. Our modelling approach is a useful way to infer population processes, and the effects of the environment on these processes, for populations censused without error. When used to predict future harrier numbers under alternate management scenarios, our model indicates that harrier numbers on Langholm estate, Scotland, could be reduced without any direct human intervention if the estate can be managed in a way that reduces vole populations. In contrast, there appears little to gain from managing meadow pipit densities. If these conclusions apply to other harrier populations, then management to reduce vole numbers, while maintaining grouse densities, may help alleviate the conflict between conservationists and managers of grouse moors. [ABSTRACT FROM AUTHOR]

Background: Predators can have profound impacts on the dynamics of their prey that depend on how predator consumption is affected by prey density (the predator's 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 predator's 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 model's 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. [ABSTRACT FROM AUTHOR]

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 ease, 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. [ABSTRACT FROM AUTHOR]

In the UK, resolving conflicts between the conservation of grey seals, the management of fish stocks and marine exploitation requires knowledge of the seals' use of space. We present a map of grey seal usage around the British Isles based on satellite telemetry data from adult animals and haul-out survey data. Our approach combined modelling and interpolation. To model the seals' association with particular coastal sites (the haul-outs), we divided the population into subpopulations associated with 24 haul-out groups. Haul-out-specific maps of accessibility were used to supervise usage estimation from satellite telemetry. The mean and variance of seal numbers at each haul-out group were obtained from haul-out counts. The aggregate map of usage for the entire population was produced by adding together the haul-out-specific usage maps, weighted by mean number of animals using that haul-out. Seal usage was primarily concentrated (i) off the northern coasts of the British Isles, (ii) closer to the coast than might be expected purely on the basis of accessibility from the haul-outs and (iii) in a limited number of marine hot-spots. Although our results currently represent the best estimate of how grey seals use the marine environment around Britain, they are neither definitive nor equally precise for all haul-outs. Further data collection should focus in the south-west of the British isles and aerial counts should be repeated for all haul-outs. This work provides environmental managers with current estimates of grey seal usage and describes a methodology for maximizing data efficiency. Our results could guide government departments in licensing marine exploitation by the oil industry, in estimating grey seal predation pressure on vulnerable or economically important prey and in delineating marine special areas of conservation(SAC).Our finding that grey seal usage is characterized by a limited number of hot-spots means that the species is particularly suited to localized conservation efforts. [ABSTRACT FROM AUTHOR]

We develop a theory of generalist predation showing how alternative prey species are affected by changes in both mean abundance and variability (coefficient of variation) of their predator’s primary prey. The theory is motivated by the indirect effects of cyclic rodent populations on ground-breeding birds, and developed through progressive analytic simplifications of an empirically-based model. It applies nonetheless to many other systems where primary prey have fast life-histories and can become superabundant, thus facilitating impact on alternative prey species and generating highly asymmetric interactions. Our results suggest that predator effects on alternative prey should generally decrease with mean primary prey abundance, and increase with primary prey variability (low to high CV)—unless predators have strong aggregative responses, in which case these results can be reversed. Approximations of models including predator dynamics (general numerical response with possible delays) confirm these results but further suggest that negative temporal correlation between predator and primary prey is harmful to alternative prey. Finally, we find that measurements of predator numerical responses are crucial to predict–even qualitatively–the response of ecosystems to changes in the dynamics of outbreaking prey species. [ABSTRACT FROM AUTHOR]