Finite mixtures in capture-recapture surveys for modeling residency patterns in marine wildlife populations

This work aims to show how prior knowledge about the structure of a heterogeneous animal population can be leveraged to improve the abundance estimation from capture-recapture survey data. We combine the Open Jolly-Seber model with finite mixtures and propose a parsimonious specification tailored to the residency patterns of the common bottlenose dolphin. We employ a Bayesian framework for our inference, discussing the appropriate choice of priors to mitigate label-switching and nonidentifiability issues, commonly associated with finite mixture models. We conduct a series of simulation experiments to illustrate the competitive advantage of our proposal over less specific alternatives. The proposed approach is applied to data collected on the common bottlenose dolphin population inhabiting the Tiber River estuary (Mediterranean Sea). Our results provide novel insights into this population's size and structure, shedding light on some of the ecological processes governing its dynamics.

Will climate change affect the survival of tropical and subtropical species? Predictions based on Bulwer's petrel populations in the NE Atlantic Ocean

Climate change has repeatedly been shown to impact the demography and survival of marine top predators. However, most evidence comes from single populations of widely distributed species, limited mainly to polar and subpolar environments. Here, we aimed to evaluate the influence of environmental conditions on the survival of a tropical and migratory seabird over the course of its annual cycle. We used capture-mark-recapture data from three populations of Bulwer's petrel (Bulweria bulwerii) spread across the NE Atlantic Ocean, from the Azores, Canary, and Cabo Verde Islands (including temperate to tropical zones). We also inferred how the survival of this seabird might be affected under different climatic scenarios, defined by the Intergovernmental Panel on Climate Change. Among the environmental variables whose effect we evaluated (North Atlantic Oscillation index, Southern Oscillation Index, Sea Surface Temperature [SST] and wind speed), SST estimated for the breeding area and season was the variable with the greatest influence on adult survival. Negative effects of SST increase emerged across the three populations, most likely through indirect trophic web interactions. Unfortunately, our study also shows that the survival of Bulwer's petrel will be profoundly affected by the different scenarios of climate change, even with the most optimistic trajectory involving the lowest greenhouse gas emission. Furthermore, for the first time, our study predicts stronger impacts of climate change on tropical populations than on subtropical and temperate ones. This result highlights the devastating effect that climate change may also have on tropical areas, and the importance of considering multi-population approaches when evaluating its impacts which may differ across species distributions.

Breeding stage and tissue isotopic consistency suggests colony-level flexibility in niche breadth of an Arctic marine bird

Organisms must overcome environmental limitations to optimize their investment in life history stages to maximize fitness. Human-induced climate change is generating increasingly variable environmental conditions, impacting the demography of prey items and, therefore, the ability of consumers to successfully access resources to fuel reproduction. While climate change effects are especially pronounced in the Arctic, it is unknown whether organisms can adjust foraging decisions to match such changes. We used a 9-year blood plasma δ¹³C and δ¹⁵N data set from over 700 pre-breeding Arctic common eiders (Somateria mollissima) to assess breeding-stage and inter-annual variation in isotopic niche, and whether inferred trophic flexibility was related to colony-level breeding parameters and environmental variation. Eider blood isotope values varied both across years and breeding stages, and combined with only weak relationships between isotopic metrics and environmental conditions suggests that pre-breeding eiders can make flexible foraging decisions to overcome constraints imposed by local abiotic conditions. From an investment perspective, an inshore, smaller isotopic niche predicted a greater probability to invest in reproduction, but was not related to laying phenology. Proximately, our results provide evidence that eiders breeding in the Arctic can alter their diet at the onset of reproductive investment to overcome increases in the energetic demand of egg production. Ultimately, Arctic pre-breeding common eiders may have the stage- and year-related foraging flexibility to respond to abiotic variation to reproduce successfully.

Broad-scale climate variation drives the dynamics of animal populations: a global multi-taxa analysis

Climate is a major extrinsic factor affecting the population dynamics of many organisms. The Broad-Scale Climate Hypothesis (BSCH) was proposed by Elton to explain the large-scale synchronous population cycles of animals, but the extent of support and whether it differs among taxa and geographical regions is unclear. We reviewed publications examining the relationship between the population dynamics of multiple taxa worldwide and the two most commonly used broad-scale climate indices, El Niño-Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO). Our review and synthesis (based on 561 species from 221 papers) reveals that population changes of mammals, birds and insects are strongly affected by major oceanic shifts or irregular oceanic changes, particularly in ENSO- and NAO-influenced regions (Pacific and Atlantic, respectively), providing clear evidence supporting Elton's BSCH. Mammal and insect populations tended to increase during positive ENSO phases. Bird populations tended to increase in positive NAO phases. Some species showed dual associations with both positive and negative phases of the same climate index (ENSO or NAO). These findings indicate that some taxa or regions are more or less vulnerable to climate fluctuations and that some geographical areas show multiple weather effects related to ENSO or NAO phases. Beyond confirming that animal populations are influenced by broad-scale climate variation, we document extensive patterns of variation among taxa and observe that the direct biotic and abiotic mechanisms for these broad-scale climate factors affecting animal populations are very poorly understood. A practical implication of our research is that changes in ENSO or NAO can be used as early signals for pest management and wildlife conservation. We advocate integrative studies at both broad and local scales to unravel the omnipresent effects of climate on animal populations to help address the challenge of conserving biodiversity in this era of accelerated climate change.

Covariate and multinomial: Accounting for distance in movement in capture-recapture analyses

Many biological quantities cannot be measured directly but rather need to be estimated from models. Estimates from models are statistical objects with variance and, when derived simultaneously, covariance. It is well known that their variance-covariance (VC) matrix must be considered in subsequent analyses. Although it is always preferable to carry out the proposed analyses on the raw data themselves, a two-step approach cannot always be avoided. This situation arises when the parameters of a multinomial must be regressed against a covariate. The Delta method is an appropriate and frequently recommended way of deriving variance approximations of transformed and correlated variables. Implementing the Delta method is not trivial, and there is a lack of a detailed information on the procedure in the literature for complex situations such as those involved in constraining the parameters of a multinomial distribution. This paper proposes a how-to guide for calculating the correct VC matrices of dependant estimates involved in multinomial distributions and how to use them for testing the effects of covariates in post hoc analyses when the integration of these analyses directly into a model is not possible. For illustrative purpose, we focus on variables calculated in capture-recapture models, but the same procedure can be applied to all analyses dealing with correlated estimates with multinomial distribution and their variances and covariances.