Early‐life demographic traits are poorly known, impeding our understanding of population processes and sensitivity to climate change. Survival of immature individuals is a critical component of ...population dynamics and recruitment in particular. However, obtaining reliable estimates of juvenile survival (i.e., from independence to first year) remains challenging, as immatures are often difficult to observe and to monitor individually in the field. This is particularly acute for seabirds, in which juveniles stay at sea and remain undetectable for several years. In this work, we developed a Bayesian integrated population model to estimate the juvenile survival of emperor penguins (Aptenodytes forsteri), and other demographic parameters including adult survival and fecundity of the species. Using this statistical method, we simultaneously analyzed capture–recapture data of adults, the annual number of breeding females, and the number of fledglings of emperor penguins collected at Dumont d'Urville, Antarctica, for the period 1971–1998. We also assessed how climate covariates known to affect the species foraging habitats and prey southern annular mode (SAM), sea ice concentration (SIC) affect juvenile survival. Our analyses revealed that there was a strong evidence for the positive effect of SAM during the rearing period (SAMR) on juvenile survival. Our findings suggest that this large‐scale climate index affects juvenile emperor penguins body condition and survival through its influence on wind patterns, fast ice extent, and distance to open water. Estimating the influence of environmental covariates on juvenile survival is of major importance to understand the impacts of climate variability and change on the population dynamics of emperor penguins and seabirds in general and to make robust predictions on the impact of climate change on marine predators.
Populations of large carnivores are recovering in Europe and incur increasing conflict interactions with human activities. According to the agenda-setting theory, the media dissemination of ...information on these interactions is likely to contribute to shaping public perceptions of large carnivores. We conducted a content analysis of printed media coverage of wolf recovery in France over the period 1993–2014, ever since its natural return to southeast France. To do so, we used a recently developed statistical method – structural topic modeling – that allows to generate topics from large amount of texts and formulate new or assess existing hypotheses. This method formally includes covariates to explain variation in topic prevalence and content in a way that is similar to standard regression analyses. We contrasted content variation between articles in a regional (Nice-Matin; N = 742) and a national (Le Monde; N = 148) newspaper and analyzed time trends in topic prevalence. The most represented topics were mainly related to the management issues regarding wolf recovery. We found that Le Monde represented management issues in a generic manner associated with a perspective centred on carnivore species. In contrast, articles in Nice-Matin were about factual issues and associated with a human-centred viewpoint. This contrasted framing emphasizes the gap in representations of wolf management between citizens who directly interact with the wolf and favor detailed information content, centred on human views, and citizens who do not interact or only indirectly with the wolf who will focus on less detailed news, with a more ecological approach. We suggest that increased communication between local and national stakeholders and institutions could provide the context for a more balanced media content of interactions between carnivore species and human activities. This combination could attenuate the gap between regional and national representations.
Assessing the quality of fit of a statistical model to data is a necessary step for conducting safe inference.
We introduce R2ucare, an r package to perform goodness‐of‐fit tests for open single‐ and ...multi‐state capture–recapture models. R2ucare also has various functions to manipulate capture–recapture data.
We remind the basics and provide guidelines to navigate towards testing the fit of capture–recapture models. We demonstrate the functionality of R2ucare through its application to real data.
The ongoing recovery of terrestrial large carnivores in North America and Europe is accompanied by intense controversy. On the one hand, reestablishment of large carnivores entails a recovery of ...their most important ecological role, predation. On the other hand, societies are struggling to relearn how to live with apex predators that kill livestock, compete for game species, and occasionally injure or kill people. Those responsible for managing these species and mitigating conflict often lack fundamental information due to a long-standing challenge in ecology: How do we draw robust population-level inferences for elusive animals spread over immense areas? Here we showcase the application of an effective tool for spatially explicit tracking and forecasting of wildlife population dynamics at scales that are relevant to management and conservation. We analyzed the world’s largest dataset on carnivores comprising more than 35,000 noninvasively obtained DNA samples from over 6,000 individual brown bears (Ursus arctos), gray wolves (Canis lupus), and wolverines (Gulo gulo). Our analyses took into account that not all individuals are detected and, even if detected, their fates are not always known. We show unequivocal quantitative evidence of large carnivore recovery in northern Europe, juxtaposed with the finding that humans are the single-most important factor driving the dynamics of these apex predators. We present maps and forecasts of the spatiotemporal dynamics of large carnivore populations, transcending national boundaries and management regimes.
Understanding population dynamics requires accurate estimates of demographic rates. Integrated population models combine demographic and survey data into a single, comprehensive analysis and provide ...more coherent estimates of vital rates. Integrated population models rely on the assumption that different data sets are independent, which is frequently violated in practice. Moreover, the precision that can be gained using integrated modeling compared to conventional modeling is only known from empirical studies. The present study used simulation methods to assess how the violation of the assumption of independence affects the statistical properties of the parameter estimators. Further, the gains in precision and accuracy from the model were explored under varying sample sizes. For capture–recapture, population survey, and reproductive success, we generated independent and dependent data that were analyzed with integrated and conventional models. We found only a minimal impact of the violation of the assumption of independence on the parameter estimates. Furthermore, we observed an overall gain in precision and accuracy when all three data sets were analyzed simultaneously. This was particularly pronounced when the sample size was small. These findings contribute to clearing the way for the application of integrated population models in practice.
In marine ecosystems top predator populations are shaped by environmental factors affecting their prey abundance. Coupling top predators’ population studies with independent records of prey abundance ...suggests that prey fluctuations affect fecundity parameters and abundance of their predators. However, prey may be abundant but inaccessible to their predators and a major challenge is to determine the relative importance of prey accessibility in shaping seabird populations. In addition, disentangling the effects of prey abundance and accessibility from the effects of prey removal by fisheries, while accounting for density dependence, remains challenging for marine top predators. Here, we investigate how climate, population density, and the accessibility and removal of prey (the Peruvian anchovy Engraulis ringens) by fisheries influence the population dynamics of the largest sedentary seabird community (≈ 4 million individuals belonging to guanay cormorant Phalacrocorax bougainvillii, Peruvian booby Sula variegata and Peruvian pelican Pelecanus thagus) of the northern Humboldt Current System over the past half‐century. Using Gompertz state–space models we found strong evidence for density dependence in abundance for the three seabird species. After accounting for density dependence, sea surface temperature, prey accessibility (defined by the depth of the upper limit of the subsurface oxygen minimum zone) and prey removal by fisheries were retained as the best predictors of annual population size across species. These factors affected seabird abundance the current year and with year lags, suggesting effects on several demographic parameters including breeding propensity and adult survival. These findings highlight the effects of prey accessibility and fishery removals on seabird populations in marine ecosystems. This will help refine management objectives of marine ecosystems in order to ensure sufficient biomass of forage fish to avoid constraining seabird population dynamics, while taking into account of the effects of environmental variability.
Capture–recapture models for estimating demographic parameters allow covariates to be incorporated to better understand population dynamics. However, high-dimensionality and multicollinearity can ...hamper estimation and inference. Principal component analysis is incorporated within capture–recapture models and used to reduce the number of predictors into uncorrelated synthetic new variables. Principal components are selected by sequentially assessing their statistical significance. We provide an example on seabird survival to illustrate our approach. Our method requires standard statistical tools, which permits an efficient and easy implementation using standard software.
Social networks are tied to population dynamics; interactions are driven by population density and demographic structure, while social relationships can be key determinants of survival and ...reproductive success. However, difficulties integrating models used in demography and network analysis have limited research at this interface. We introduce the R package genNetDem for simulating integrated network–demographic datasets. It can be used to create longitudinal social network and/or capture–recapture datasets with known properties. It incorporates the ability to generate populations and their social networks, generate grouping events using these networks, simulate social network effects on individual survival, and flexibly sample these longitudinal datasets of social associations. By generating co‐capture data with known statistical relationships, it provides functionality for methodological research. We demonstrate its use with case studies testing how imputation and sampling design influence the success of adding network traits to conventional Cormack–Jolly–Seber (CJS) models. We show that incorporating social network effects into CJS models generates qualitatively accurate results, but with downward‐biased parameter estimates when network position influences survival. Biases are greater when fewer interactions are sampled or fewer individuals observed in each interaction. While our results indicate the potential of incorporating social effects within demographic models, they show that imputing missing network measures alone is insufficient to accurately estimate social effects on survival, pointing to the importance of incorporating network imputation approaches. genNetDem provides a flexible tool to aid these methodological advancements and help researchers testing other sampling considerations in social network studies.
Difficulties integrating models used in demography and network analysis have limited research at the interface of social and population ecology. Here, we introduce the R package genNetDem for simulating integrated network–demographic datasets for methodological research. We demonstrate its use with case studies testing how imputation and sampling design influence our ability to estimate social network effects on survival in capture–recapture data.
REVIEW: Predictive ecology in a changing world Mouquet, Nicolas; Lagadeuc, Yvan; Devictor, Vincent ...
The Journal of applied ecology,
October 2015, Letnik:
52, Številka:
5
Journal Article
Recenzirano
Odprti dostop
In a rapidly changing world, ecology has the potential to move from empirical and conceptual stages to application and management issues. It is now possible to make large‐scale predictions up to ...continental or global scales, ranging from the future distribution of biological diversity to changes in ecosystem functioning and services. With these recent developments, ecology has a historical opportunity to become a major actor in the development of a sustainable human society. With this opportunity, however, also comes an important responsibility in developing appropriate predictive models, correctly interpreting their outcomes and communicating their limitations. There is also a danger that predictions grow faster than our understanding of ecological systems, resulting in a gap between the scientists generating the predictions and stakeholders using them (conservation biologists, environmental managers, journalists, policymakers). Here, we use the context provided by the current surge of ecological predictions on the future of biodiversity to clarify what prediction means, and to pinpoint the challenges that should be addressed in order to improve predictive ecological models and the way they are understood and used. Synthesis and applications. Ecologists face several challenges to ensure the healthy development of an operational predictive ecological science: (i) clarity on the distinction between explanatory and anticipatory predictions; (ii) developing new theories at the interface between explanatory and anticipatory predictions; (iii) open data to test and validate predictions; (iv) making predictions operational; and (v) developing a genuine ethics of prediction.
While large carnivores are recovering in Europe, assessing their distributions can help to predict and mitigate conflicts with human activities. Because they are highly mobile, elusive and live at ...very low density, modeling their distributions presents several challenges due to 1) their imperfect detectability, 2) their dynamic ranges over time and 3) their monitoring at large scales consisting mainly of opportunistic data without a formal measure of the sampling effort.
Here, we focused on wolves Canis lupus that have been recolonizing France since the early 1990s. We evaluated the sampling effort a posteriori as the number of observers present per year in a cell based on their location and professional activities. We then assessed wolf range dynamics from 1994 to 2016, while accounting for species imperfect detection and time‐ and space‐varying sampling effort using dynamic site‐occupancy models.
Ignoring the effect of sampling effort on species detectability led to underestimating the number of occupied sites by more than 50% on average. Colonization appeared to be negatively influenced by the proportion of a site with an altitude higher than 2500 m and positively influenced by the number of observed occupied sites at short and long‐distances, forest cover, farmland cover and mean altitude. The expansion rate, defined as the number of occupied sites in a given year divided by the number of occupied sites in the previous year, decreased over the first years of the study, then remained stable from 2000 to 2016. Our work shows that opportunistic data can be analyzed with species distribution models that control for imperfect detection, pending a quantification of sampling effort. Our approach has the potential for being used by decision‐makers to target sites where large carnivores are likely to occur and mitigate conflicts.
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