Roger Pradel

Assessing the impact of climate variation on survival in vertebrate populations

The impact of the ongoing rapid climate change on natural systems is a major issue for human societies. An important challenge for ecologists is to identify the climatic factors that drive temporal variation in demographic parameters, and, ultimately, the dynamics of natural populations. The analysis of long‐term monitoring data at the individual scale is often the only available approach to estimate reliably demographic parameters of vertebrate populations. We review statistical procedures used in these analyses to study links between climatic factors and survival variation in vertebrate populations.

Program E-SURGE: A Software Application for Fitting Multievent Models

Multievent models (Pradel 2005, 2008) handle state uncertainty, and they therefore cover a range of situations like hidden capture heterogeneity and sex determination from behaviour which cannot be treated in the multistate paradigm. We introduce a new software application called e-surge, built upon the concepts developed in program m-surge (Choquet et al. 2004) to encompass this new class of capture–recapture models. It also improves on m-surge by allowing the decomposition of transitions into several steps. We present the new concepts involved, notably the event and the multistep process, and how they are implemented in e-surge. We then illustrate the use of e-surge with three examples. One example deals with breeding propensity where the breeding state cannot always be ascertained; a further deals with emigration which is considered as a two-step process (Grosbois and Tavecchia 2003) and the last one with a version of a memory model where survival can be handled directly.

Roe Deer Survival Patterns: A Comparative Analysis of Contrasting Populations

From two enclosed populations monitored for 13 and 11 years, time- and age-specific survival rates of roe deer were estimated in relation to age and study site by recent capture-mark-recapture methods. The two populations were very different. Roe deer in Trois Fontaines, a 1360 ha reserve in east France, faced severe winters. The size of this highly productive population was roughly constant during the study period. Conversely, in Chize, a 2660 ha reserve in west France with mild winters, roe deer showed density dependence in reproduction and body weight. As a general rule, females survived better than males, the survival rates of prime-age adults were the highest, and survival decreased after 7 years of age. Only the severe winters affected markedly the survivorship of roe deer

Chapter 3 Modeling Individual Animal Histories with Multistate Capture–Recapture Models

Summary Many fields of science begin with a phase of exploration and description, followed by investigations of the processes that account for observed patterns. The science of ecology is no exception, and recent decades have seen a focus on understanding key processes underlying the dynamics of ecological systems. In population ecology, emphasis has shifted from the state variable of population size to the demographic processes responsible for changes in this state variable: birth, death, immigration, and emigration. In evolutionary ecology, some of these same demographic processes, rates of birth and death, are also the determinants of fitness. In animal population ecology, the estimation of state variables and their associated vital rates is especially problematic because of the difficulties in sampling such populations and detecting individual animals. Indeed, early capture–recapture models were developed for the purpose of estimating population size, given the reality that all animals are not caught or detected at any sampling occasion. More recently, capture–recapture models for open populations were developed to draw inferences about survival in the face of these same sampling problems. The focus of this paper is on multi‐state mark–recapture models (MSMR), which first appeared in the 1970s but have undergone substantial development in the last 15 years. These models were developed to deal explicitly with biological variation, in that animals in different “states” (classes defined by location, physiology, behavior, reproductive status, etc.) may have different probabilities of survival and detection. Animal transitions between states are also stochastic and themselves of interest. These general models have proven to be extremely useful and provide a way of thinking about a remarkably wide range of important ecological processes. These methods are now at a stage of refinement and sophistication where they can readily be used by biologists to tackle a wide range of important issues in ecology. In this paper, we draw together information on the state of the art in multistate mark–recapture methods, explaining the models and illustrating their use. We provide a modeling philosophy and a series of general principles on how to conduct analyses. We cover key issues and features, and we anticipate the ways in which we expect the models to develop in the years ahead. In particular: – MSMR can now be used in a straightforward fashion by population biologists, thanks to the development of sound goodness‐of‐fit procedures, reliable parameter identifiability diagnostics, and robust user‐friendly computer software.Constrained models and model selection procedures can be used in the ANOVA‐like philosophy commonly used over the last 15 years for survival models, to answer a variety of biological questions. We develop as an example a treatment of meadow vole Microtus pennsylvanicus data. – As in survival models, random effects should be an integral part of this philosophy. Some simple approaches to random effects are illustrated. – States can be defined in a very general way, for example, by combining several criteria, such as sites and reproductive states, and can include nonobservable states. We develop as an example a multisite recruitment model of roseate terns Sterna dougallii . – MSMR models appear as a natural framework for combining different sources of information, viewed as different events that can be organized into mutually exclusive alternatives. – With the available developments, MSMR models are becoming a standard tool in population biology, as shown by a rapid growth of their use in the literature. In particular, given the ease with which a variety of constrained models can now be developed, MSMR models appear as less data hungry than was often feared. – MSMR models make it also possible to unify a large array of methodology, and, as such, are both a step towards further unification in a “mother of all” model, and a sound basis for further generalizations. – Future developments concern a variety of generalizations such as the reverse time approach and population size estimation. “Multievent” models, accounting for uncertainty in state determination, and integrated state–space models are key generalizations already in full development.

The statistical analysis of survival in animal populations.

Estimating, comparing and modelling survival rates are central to population biology. However, there are many difficulties in measuring these rates in animal populations in the wild. The most relevant information is based on samples of marked individuals, i.e. capture-recapture data. In recent years, a number of new statistical approaches to the analysis of such data have been developed, permitting more sophisticated and precise measurement of survival rates.

ESTIMATING SURVIVAL AND TEMPORARY EMIGRATION IN THE MULTISTATE CAPTURE–RECAPTURE FRAMEWORK

The open population Cormack-Jolly-Seber (CJS) capture–mark–recapture model for estimating survival allows for random temporary emigration from the sampling area, but Markovian temporary emigration can bias estimates of survival. We explore a multistate capture–recapture model that has been proposed for coping with Markovian temporary emigration. We provide a comprehensive assessment of the performance of this model using computer algebra and simulation. We found that most model parameters were identifiable unless survival, emigration, and immigration were all time dependent. Simulation results showed that intrinsically identifiable parameters were estimated without bias and that precision of survival estimates was always high. When temporary emigration was Markovian, precision of estimates of emigration, immigration, and recapture probabilities was acceptable; otherwise it was not. Test component 2.Ct of the goodness-of-fit test for the CJS model had good power to detect Markovian temporary emigration. We conclude that the multistate model works well when temporary emigration is Markovian (i.e., when the CJS model should not be used) and when survival and recapture probabilities are high.

Sex- and age-related variation in survival and cost of first reproduction in greater flamingos

We analyzed survival of breeding Greater Flamingos, Phoenicopterus ruber roseus, using the capture histories of 2000 breeding birds ringed as chicks and resighted at their natal colony in the Camargue, southern France. As found in previous analyses, recapture probability varied according to year, sex, and age of the bird, and annual survival was strongly affected by winter severity. However, by using a much larger data set than in earlier analyses, we detected previously nonsignificant effects. Indeed, for the first time, sex and age of the bird were found to influence annual survival probability. We tested the hypothesis that the observed sex-related difference in survival corresponded to asymmetric costs of reproduction. A model including a cost of first observed reproduction on survival in young females only provided the best fit to the data and explained the majority of the sex-related difference in survival of birds <7 yr old. Because a cost of reproduction may be partially masked by birds that have already bred undetected, we estimated the proportion of experienced females among those observed breeding for the first time. This proportion varied with the age of the birds and was used to calculate the expected cost of early recruitment. Such a cost of early reproduction may have contributed to the evolution of deferred breeding in females. Survival of experienced females was higher than that of males, with the difference being more pronounced in early age classes. Age had a significant positive effect on survival probability of birds.

King penguin population threatened by Southern Ocean warming

Seabirds are sensitive indicators of changes in marine ecosystems and might integrate and/or amplify the effects of climate forcing on lower levels in food chains. Current knowledge on the impact of climate changes on penguins is primarily based on Antarctic birds identified by using flipper bands. Although flipper bands have helped to answer many questions about penguin biology, they were shown in some penguin species to have a detrimental effect. Here, we present for a Subantarctic species, king penguin (Aptenodytes patagonicus), reliable results on the effect of climate on survival and breeding based on unbanded birds but instead marked by subcutaneous electronic tags. We show that warm events negatively affect both breeding success and adult survival of this seabird. However, the observed effect is complex because it affects penguins at several spatio/temporal levels. Breeding reveals an immediate response to forcing during warm phases of El Niño Southern Oscillation affecting food availability close to the colony. Conversely, adult survival decreases with a remote sea-surface temperature forcing (i.e., a 2-year lag warming taking place at the northern boundary of pack ice, their winter foraging place). We suggest that this time lag may be explained by the delay between the recruitment and abundance of their prey, adjusted to the particular 1-year breeding cycle of the king penguin. The derived population dynamic model suggests a 9% decline in adult survival for a 0.26°C warming. Our findings suggest that king penguin populations are at heavy extinction risk under the current global warming predictions.

SEASONAL SURVIVAL OF GREATER SNOW GEESE AND EFFECT OF HUNTING UNDER DEPENDENCE IN SIGHTING PROBABILITY

Although much of life-history theory assumes increased mortality at certain stages (e.g., migration), survival rates are rarely estimated on a seasonal basis within the annual cycle of migratory species. We estimated variations in seasonal survival rates in a long-lived, hunted species in the presence of short-term (between consecutive seasons) and long-term (between years in the same season) dependence in sighting probabilities. We also tested the two contrasting hypotheses that hunting mortality is either compensatory or additive to natural mortality. This study was conducted on adult female Greater Snow Geese (Chen caerulescens atlantica) from 1990 to 1998, and is based on 3890 neck-banded birds and 13 657 resightings on the northern breeding grounds in summer, and southern staging areas in spring and autumn. Birds were 10-20% more likely to be seen in autumn and spring if they were seen on the previous occasion (summer and autumn, respectively). Birds were 30-40% more likely to be seen in autumn and spring if they were last seen in the same season in the previous year. Differences in behavior according to family status (pres- ence or absence of young) and heterogeneity in site fidelity may explain the dependence in sighting probabilities; failure to account for this may lead to biased survival estimates. Monthly survival rates from spring to summer (3-mo period) and summer to autumn (2.5- mo period) were equal (0.989 ? 0.003, mean ? 1 SE) and showed little variation over the years, even though the two lengthy migratory flights (3000 km each) and breeding occurred during these periods. In contrast, monthly winter survival (from autumn to spring, 6.5 mo) was lower than during the other seasons and varied significantly over the years (range 0.936 ? 0.021 to 0.993 ? 0.008). Mean survival of adult females (corrected for neck band loss) was 0.96 from spring to autumn, 0.86 during winter, and 0.83 ? 0.05 for the whole year. Natural mortality (i.e., excluding hunting) was equal among seasons and did not vary over the years, which suggests that mortality risk is not increased during migration or repro- duction. There was a significant inverse relationship between winter survival and the kill rate (b = -1.21 + 0.56), which suggests that hunting mortality was additive to natural mortality. This is probably a general feature of long-lived species because their low and relatively constant natural mortality rate does not allow them to compensate for an additional source of mortality such as hunting. Contrary to life-history theory, we did not find evidence that migration or reproduction entailed a survival cost in this long-distance migrant bird.

Competing events, mixtures of information and multistratum recapture models

A recent trend in the analysis of capture-recapture data, in the broad sense, is the development of survival models mixing different types of events such as live recapture and dead recoveries. These models are similar to those developed for analysing competing events and multistate life histories in human health studies, which are frequently based on Markov chains. The major difference is that, in the capture-recapture context, every event is subject to a detection probability in general lower than one. Multistratum capture-recapture models are then a natural tool. We show that models for information mixtures easily enter this framework, provided adequate, possibly non-observable, strata are defined. Similarities and differences between such models are then easy to ascertain and understand. A multistratum model for mixtures of live recaptures and dead recoveries is presented and an example of data from the literature is treated, using a prototype MATLAB program named M-SURGE. Further generalizations and e...