Fitting models of multiple hypotheses to partial population data: investigating the causes of cycles in red grouse

There are two postulated causes for the observed periodic fluctuations (cycles) in red grouse (Lagopus lagopus scoticus). The first involves interaction with the parasitic nematode Trichostrongylus tenuis. The second invokes delayed regulation through the effect of male aggressiveness on territoriality. Empirical evidence exists to support both hypotheses, and each hypothesis has been modeled deterministically. However, little effort has gone into looking at the combined effects of the two mechanisms or formally fitting the corresponding models to field data. Here we present a model for red grouse dynamics that includes both parasites and territoriality. To explore the single and combined hypotheses, we specify three versions of this model and fit them to data using Bayesian state‐space modeling, a method that allows statistical inference to be performed on mechanistic models such as ours. Output from the three models is then examined to determine their goodness of fit and the biological plausibility of the parameter values required by each to fit the population data. While all three models are capable of emulating the observed cyclic dynamics, only the model including both aggression and parasites does so under consistently realistic parameter values, providing theoretical support for the idea that both mechanisms shape red grouse cycles

Flexible and practical modeling of animal telemetry data: hidden Markov models and extensions

We discuss hidden Markov-type models for fitting a variety of multistate random walks to wildlife movement data. Discrete-time hidden Markov models (HMMs) achieve considerable computational gains by focusing on observations that are regularly spaced in time, and for which the measurement error is negligible. These conditions are often met, in particular for data related to terrestrial animals, so that a likelihood-based HMM approach is feasible. We describe a number of extensions of HMMs for animal movement modeling, including more flexible state transition models and individual random effects (fitted in a non-Bayesian framework). In particular we consider so-called hidden semi-Markov models, which may substantially improve the goodness of fit and provide important insights into the behavioral state switching dynamics. To showcase the expediency of these methods, we consider an application of a hierarchical hidden semi-Markov model to multiple bison movement paths

Human-wildlife conflict, benefit sharing and the survival of lions in pastoralist community-based conservancies

No abstract available

Drivers of intrapopulation variation in resource use in a generalist predator, the macaroni penguin

Intrapopulation variation in resource use occurs in many populations of generalist predators with important community and evolutionary implications. One of the hypothesised mechanisms for such widespread variation is ecological opportunity, i.e. resource availability determined by intrinsic constraints and extrinsic conditions. We combined tracking data and stable isotope analysis to examine how breeding constraints and prey conditions influenced intrapopulation variation in resource use among macaroni penguins Eudyptes chrysolophus. Isotopic variation was also examined as a function of breeding success, individual traits and individual specialisation. Variation in isotope ratios was greatest across multiple tissue types when birds were able to undertake mid-range foraging trips (i.e. during incubation and pre-moult). This variation was highly consistent between years that spanned a 3-fold difference in local krill Euphausia superba density and was also highly consistent at the individual level between 2 years that had similar krill densities. However, by comparing our results with previous work on the same population, it appeared that a decrease in local prey availability can increase intrapopulation variation in resource use during periods with more restricted foraging ranges (i.e. during brood-guard and crèche). This study highlights the importance of considering ecological interactions that operate on multiple spatio-temporal scales when examining the drivers of resource use in populations of generalist predators

Unravelling the relative roles of top-down and bottom-up forces driving population change in an oceanic predator

In the open ocean ecosystem, climate and anthropogenic changes have driven biological change at both ends of the food chain. Understanding how the population dynamics of pelagic predators are simultaneously influenced by nutrient-driven processes acting from the “bottom-up” and predator-driven processes acting from the “top-down” is therefore considered an urgent task. Using a state-space demographic model, we evaluated the population trajectory of an oceanic predator, the macaroni penguin (Eudyptes chrysolophus), and numerically assessed the relative importance of bottom-up and top-down drivers acting through different demographic rates. The population trajectory was considerably more sensitive to changes in top-down control of survival compared to bottom-up control of survival or productivity. This study integrates a unique set of demographic and covariate data and highlights the benefits of using a single estimation framework to examine the links between covariates, demographic rates and population dynamic

Wind field and sex constrain the flight speeds of central-place foraging albatrosses

By extracting energy from the highly dynamic wind and wave fields that typify pelagic habitats, albatrosses are able to proceed almost exclusively by gliding flight. Although energetic costs of gliding are low, enabling breeding albatrosses to forage hundreds to thousands of kilometers from their colonies, these and time costs vary with relative wind direction. This causes albatrosses in some areas to route provisioning trips to avoid headwind flight, potentially limiting habitat accessibility during the breeding season. In addition, because female albatrosses have lower wing loadings than males, it has been argued that they are better adapted to flight in light winds, leading to sexual segregation of foraging areas. We used satellite telemetry and immersion logger data to quantify the effects of relative wind speed, sex, breeding stage, and trip stage on the ground speeds (Vg) of four species of Southern Ocean albatrosses breeding at South Georgia. Vg was linearly related to the wind speed component in the direction of flight (Vwf), its effect being greatest on Wandering Albatrosses Diomedea exulans, followed by Black-browed Albatrosses Thalassarche melanophrys, Light-mantled Sooty Albatrosses Phoebatria palpebrata, and Gray-headed Albatrosses T. chrysostoma. Ground speeds at Vwf = 0 were similar to airspeeds predicted by aerodynamic theory and were higher in males than in females. However, we found no evidence that this led to sexual segregation, as males and females experienced comparable wind speeds during foraging trips. Black-browed, Gray-headed, and Light-mantled Sooty Albatrosses did not engage in direct, uninterrupted bouts of flight on moonless nights, but Wandering Albatrosses attained comparable Vg night and day, regardless of lunar phase. Relative flight direction was more important in determining Vg than absolute wind speed. When birds were less constrained in the middle stage of foraging trips, all species flew predominantly across the wind. However, in some instances, commuting birds encountered headwinds during outward trips and tail winds on their return, with the result that Vg was 1.0–3.4 m/s faster during return trips. This, we hypothesize, could result from constraints imposed by the location of prey resources relative to the colony at South Georgia or could represent an energy optimization strategy

Drivers of intrapopulation variation in resource use in a generalist predator, the macaroni penguin

Intrapopulation variation in resource use occurs in many populations of generalist predators with important community and evolutionary implications. One of the hypothesised mechanisms for such widespread variation is ecological opportunity, i.e. resource availability determined by intrinsic constraints and extrinsic conditions. In this study, we combined tracking data and stable isotope analysis to examine how breeding constraints and prey conditions influenced intrapopulation variation in resource use in a generalist predator, the macaroni penguin Eudyptes chrysolophus. Isotopic variation was also examined as a function of breeding success, individual traits and individual specialisation. Variation in isotope ratios was greatest across multiple tissue types when birds were able to undertake mid-range foraging trips (i.e. during incubation and pre-moult). This variation was highly consistent between years that spanned a 3-fold difference in local prey Euphausia superba density, and was also highly consistent at the individual level between 2 years that had similar prey densities. Furthermore, by comparing our results with previous work on the same population, it appeared that a decrease in local prey availability can also increase intrapopulation variation in resource use during periods with more restricted foraging ranges (i.e. during brood-guard and crèche). This study highlights the importance of considering ecological interactions that operate on multiple spatio-temporal scales when examining the drivers of resource use in populations of generalist predator

The functional response of a generalist predator

Peer reviewedPublisher PD

Combining survey and remotely sensed environmental data to estimate the habitat associations, abundance and distribution of breeding thin-billed prions Pachyptila belcheri and Wilson’s storm-petrels Oceanites oceanicus on a South Atlantic tussac island

Small petrels are the most abundant seabirds in the Southern Ocean. However, because they breed in burrows on remote and often densely vegetated islands, their colony sizes and conservation status remain poorly known. To estimate the abundance of these species on Bird Island in the Falkland archipelago, we systematically surveyed their breeding burrow density and occupancy across this near-pristine tussac (Poa flabellata)-covered island. By modelling burrow density as functions of topography and Sentinel 2 satellite-derived Normalised Difference Vegetation Index data, we inferred habitat associations and predicted burrow abundance of the commonest species—Thin-billed Prions (Pachyptila belcheri) and Wilson’s Storm-petrels (Oceanites oceanicus). We estimate that there are 631,000 Thin-billed Prion burrows on the island (95% CI 496,000–904,000 burrows). Assuming that burrow occupancy lies between 12 and 97%, this equates to around 76,000–612,000 breeding pairs, making Bird Island the second or third largest P. belcheri colony in the world, holding approximately 3–27% of the species’ breeding population. We estimate that 8200–9800 (95% CI 5,200–18,300 pairs) pairs of Wilson’s Storm-petrels also breed on the island. Notably, the latter burrowed predominantly under and within tussac pedestals, whereas they are usually assumed to breed in rock cavities. Thin-billed Prions are declining in the Kerguelen archipelago, but their population trends in the Falklands are unknown. Given the wide confidence intervals around our own and other population estimates for these cryptic species, we recommend that their populations should be monitored regularly, at multiple sites.Fundação para a Ciência e Tecnologia - FCTinfo:eu-repo/semantics/publishedVersio

Inference in MCMC step selection models

Habitat selection models are used in ecology to link the spatial distribution of animals to environmental covariates, and identify preferred habitats. The most widely used models of this type, resource selection functions, aim to capture the steady‐state distribution of space use of the animal, but they assume independence between the observed locations of an animal. This is unrealistic when location data display temporal autocorrelation. The alternative approach of step selection functions embed habitat selection in a model of animal movement, to account for the autocorrelation. However, inferences from step selection functions depend on the underlying movement model, and they do not readily predict steady‐state space use. We suggest an analogy between parameter updates and target distributions in Markov chain Monte Carlo (MCMC) algorithms, and step selection and steady‐state distributions in movement ecology, leading to a step selection model with an explicit steady‐state distribution. In this framework, we explain how maximum likelihood estimation can be used for simultaneous inference about movement and habitat selection. We describe the local Gibbs sampler, a novel rejection‐free MCMC scheme, use it as the basis of a flexible class of animal movement models, and derive its likelihood function for several important special cases. In a simulation study, we verify that maximum likelihood estimation can recover all model parameters. We illustrate the application of the method with data from a zebra