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In the context of global change, endangered species such as sea turtles undergo strong population dynamics changes. Understanding demographic processes inducing such changes is critical for developing appropriate measures for conservation and management. Nesting females of the French Guiana population of leatherback sea turtles Dermochelys coriacea represented 40% of the world’s total in 2001; today, they represent only 10%. Here, we analyze data from the long-term monitoring program of leatherbacks in French Guiana, based on 28 yr of capture-mark-recapture data from 46051 individuals in northwestern French Guiana. We used multievent models (multistate capture-recapture models with state uncertainty) to represent the main peculiarity of the life cycle, intermittent reproduction, and to take advantage of the use of several different types of marks to account for mark loss and incomplete detection. The average annual adult survival probability (mean ± SE) 0.789 ± 0.009 is low compared to published estimates for this species. By combining the estimates of departure and return probabilities, we provide an estimate of the interval among laying seasons equal to 2.777 ± 0.118 yr, which matches previous findings. Taking survival into account, this interval translates into an average of 1.704 ± 0.034 further reproductive seasons for an adult female having just bred, which is remarkably low compared to other long-lived vertebrates. The representation of the life cycle and mark loss in our models provides a sound structure for broader and richer analyses to extract biological information from marked individuals and offers an invaluable source of demographic information on leatherbacks, a species for which only a small segment of the population is accessible to intermittent sampling.

Life history strategies, which combine schedules of survival, development, and reproduction, shape how natural selection acts on species' heritable traits and organismal fitness. Comparative analyses have historically ranked life histories along a fast-slow continuum, describing a negative association between time allocation to reproduction and development versus survival. However, higher-quality, more representative data and analyses have revealed that life history variation cannot be fully accounted for by this single continuum. Moreover, studies often do not test predictions from existing theories and instead operate as exploratory exercises. To move forward, we offer three recommendations for future investigations: standardizing life history traits, overcoming taxonomic siloes, and using theory to move from describing to understanding life history variation across the Tree of Life., Competing Interests: Declaration of interests The authors have no interests to declare., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Insects appeared more than 400 million years ago and they represent the richest and most diverse taxonomic group with several million species. Yet, under the combined effect of the loss of natural habitats, the intensification of agriculture with massive use of pesticides, global warming and biological invasions, insects show alarming signs of decline. Although difficult to quantify, species extinction and population reductions are confirmed for many ecosystems. This results in a loss of services such as the pollination of plants, including food crops, the recycling of organic matter, the supply of goods such as honey and the stability of food webs. It is therefore urgent to halt the decline of Insects. We recommend implementing long-term monitoring of populations, tackling the causes of insect decline by reducing the use of synthetic insecticides, preserving natural habitats, and reinventing a positive relationship between humans and insects.

In the present context of concerns for biodiversity, the French Academy of Sciences produced in 2017 a report entitled "Mechanisms of adaptation of biodiversity to climate change and their limits". We briefly review here the production process and structure of the report, and summarize its conclusions and recommendations. The conclusions emphasize the role of habitat fragmentation in the expected impact of climate change on biodiversity, in particular for organisms with limited dispersal abilities, and the disparities in species responses which must be taken to understand the future of species assemblages ("communities") under different scenarios of climate change. The recommendations cover the organization of biodiversity research and monitoring (development of observatories, key role of embedded time scales and modeling, integration of Human and Social Sciences), as well as critical domains such as Human, animal and plant health, agriculture and forestry policies, and management of the Environment.

Biodiversity loss is a major challenge. Over the past century, the average rate of vertebrate extinction has been about 100-fold higher than the estimated background rate and population declines continue to increase globally. Birth and death rates determine the pace of population increase or decline, thus driving the expansion or extinction of a species. Design of species conservation policies hence depends on demographic data (e.g., for extinction risk assessments or estimation of harvesting quotas). However, an overview of the accessible data, even for better known taxa, is lacking. Here, we present the Demographic Species Knowledge Index, which classifies the available information for 32,144 (97%) of extant described mammals, birds, reptiles, and amphibians. We show that only 1.3% of the tetrapod species have comprehensive information on birth and death rates. We found no demographic measures, not even crude ones such as maximum life span or typical litter/clutch size, for 65% of threatened tetrapods. More field studies are needed; however, some progress can be made by digitalizing existing knowledge, by imputing data from related species with similar life histories, and by using information from captive populations. We show that data from zoos and aquariums in the Species360 network can significantly improve knowledge for an almost eightfold gain. Assessing the landscape of limited demographic knowledge is essential to prioritize ways to fill data gaps. Such information is urgently needed to implement management strategies to conserve at-risk taxa and to discover new unifying concepts and evolutionary relationships across thousands of tetrapod species., Competing Interests: The authors declare no conflict of interest., (Copyright © 2019 the Author(s). Published by PNAS.)

Predicting the impact of disease epidemics on wildlife populations is one of the twenty-first century's main conservation challenges. The long-term demographic responses of wildlife populations to epidemics and the life history and social traits modulating these responses are generally unknown, particularly for K -selected social species. Here we develop a stage-structured matrix population model to provide a long-term projection of demographic responses by a keystone social predator, the spotted hyena, to a virulent epidemic of canine distemper virus (CDV) in the Serengeti ecosystem in 1993/1994 and predict the recovery time for the population following the epidemic. Using two decades of longitudinal data from 625 known hyenas, we demonstrate that although the reduction in population size was moderate, i.e., the population showed high ecological 'resistance' to the novel CDV genotype present, recovery was slow. Interestingly, high-ranking females accelerated the population's recovery, thereby lessening the impact of the epidemic on the population., Competing Interests: The authors declare no competing interests.

Estimating eco-epidemiological parameters in free-ranging populations can be challenging. As known individuals may be undetected during a field session, or their health status uncertain, the collected data are typically "imperfect". Multi-event capture-mark-recapture (MECMR) models constitute a substantial methodological advance by accounting for such imperfect data. In these models, animals can be "undetected" or "detected" at each time step. Detected animals can be assigned an infection state, such as "susceptible" (S), "infected" (I), or "recovered" (R), or an "unknown" (U) state, when for instance no biological sample could be collected. There may be heterogeneity in the assignment of infection states, depending on the manifestation of the disease in the host or the diagnostic method. For example, if obtaining the samples needed to prove viral infection in a detected animal is difficult, this can result in a low chance of assigning the I state. Currently, it is unknown how much uncertainty MECMR models can tolerate to provide reliable estimates of eco-epidemiological parameters and whether these parameters are sensitive to heterogeneity in the assignment of infection states. We used simulations to assess how estimates of the survival probability of individuals in different infection states and the probabilities of infection and recovery responded to (1) increasing infection state uncertainty (i.e., the proportion of U) from 20 to 90%, and (2) heterogeneity in the probability of assigning infection states. We simulated data, mimicking a highly virulent disease, and used SIR-MECMR models to quantify bias and precision. For most parameter estimates, bias increased and precision decreased gradually with state uncertainty. The probabilities of survival of I and R individuals and of detection of R individuals were very robust to increasing state uncertainty. In contrast, the probabilities of survival and detection of S individuals, and the infection and recovery probabilities showed high biases and low precisions when state uncertainty was >50%, particularly when the assignment of the S state was reduced. Considering this specific disease scenario, SIR-MECMR models are globally robust to state uncertainty and heterogeneity in state assignment, but the previously mentioned parameter estimates should be carefully interpreted if the proportion of U is high.

The extent to which the fitness costs of infection are mediated by key life-history traits such as age or social status is still unclear. Within populations, individual heterogeneity in the outcome of infection is the result of two successive processes; the degree of contact with the pathogen (exposure) and the immune response to infection. In social mammals, because individuals holding high social status typically interact more frequently with group members, they should be more often in contact with infected individuals than those of low social status. However, when access to resources is determined by social status, individuals with a high social status are often better nourished, have a greater opportunity to allocate resources to immune processes and therefore should have a smaller chance of succumbing to infection than individuals with low social status.We investigated the risk and fitness costs of infection during a virulent epidemic of canine distemper virus (CDV) in a social carnivore, the spotted hyena, in the Serengeti National Park. We analysed two decades of detailed life-history data from 625 females and 816 males using a multi-event capture-mark-recapture model that accounts for uncertainty in the assignment of individual infection states.Cubs of mothers with a high social status had a lower probability of CDV infection and were more likely to survive infection than those with low social status. Subadult and adult females with high social status had a higher infection probability than those with low social status. Subadult females and pre-breeder males that had recovered from CDV infection had a lower survival than susceptible ones.Our study disentangles the relative importance of individual exposure and resource allocation to immune processes, demonstrates fitness costs of infection for juveniles, particularly for those with low social status, shows that patterns of infection can be driven by different mechanisms among juveniles and adults and establishes a negative relationship between infection and fitness in a free-ranging mammal. A http://onlinelibrary.wiley.com/doi/10.1111/1365-2435.13059/suppinfo is available for this article., (© 2018 The Authors. Functional Ecology © 2018 British Ecological Society.)

Understanding and modeling population change is urgently needed to predict effects of climate change on biodiversity. High trophic-level organisms are influenced by fluctuations of prey quality and abundance, which themselves may depend on climate oscillations. Modeling effects of such fluctuations is challenging because prey populations may vary with multiple climate oscillations occurring at different time scales. The analysis of a 28-yr time series of capture-recapture data of a tropical seabird, the Nazca Booby (Sula granti), in the Galápagos, Ecuador, allowed us to test for demographic effects of two major ocean oscillations occurring at distinct time-scales: the inter-annual El Niño Southern Oscillation (ENSO) and inter-decadal oscillations. As expected for a tropical seabird, survival of fledgling birds was highly affected by extreme ENSO events; by contrast, neither recruitment nor breeding participation were affected by either ENSO or decadal oscillations. More interesting, adult survival, a demographic trait that canalizes response to environmental variations, was unaffected by inter-annual ENSO oscillations yet was shaped by the Pacific Decadal Oscillation and small pelagic fish regime. Adult survival decreased during oceanic conditions associated with higher breeding success, an association probably mediated in this species by costs of reproduction that reduce survival when breeding attempts end later. To our knowledge, this is the first study suggesting that survival of a vertebrate can be vulnerable to a natural multidecadal oscillation., (© 2018 by the Ecological Society of America.)

The science of complex systems is increasingly asked to forecast the consequences of climate change. As a result, scientists are now engaged in making predictions about an uncertain future, which entails the efficient communication of this uncertainty. Here we show the benefits of hierarchically decomposing the uncertainty in predicted changes in animal population size into its components due to structural uncertainty in climate scenarios (greenhouse gas emissions and global circulation models), structural uncertainty in the demographic model, climatic stochasticity, environmental stochasticity unexplained by climate-demographic trait relationships, and sampling variance in demographic parameter estimates. We quantify components of uncertainty surrounding the future abundance of a migratory bird, the greater snow goose (Chen caeruslescens atlantica), using a process-based demographic model covering their full annual cycle. Our model predicts a slow population increase but with a large prediction uncertainty. As expected from theoretical variance decomposition rules, the contribution of sampling variance to prediction uncertainty rapidly overcomes that of process variance and dominates. Among the sources of process variance, uncertainty in the climate scenarios contributed less than 3% of the total prediction variance over a 40-year period, much less than environmental stochasticity. Our study exemplifies opportunities to improve the forecasting of complex systems using long-term studies and the challenges inherent to predicting the future of stochastic systems., (© 2016 The Author(s).)

Understanding how climate change will affect animal population dynamics remains a major challenge, especially in long-distant migrants exposed to different climatic regimes throughout their annual cycle. We evaluated the effect of temperature throughout the annual cycle on demographic parameters (age-specific survival and recruitment, breeding propensity and fecundity) of the greater snow goose (Chen caerulescens atlantica L.), an arctic-nesting species. As this is a hunted species, we used the theory of exploited populations to estimate hunting mortality separately from natural mortality in order to evaluate climatic effects only on the latter form of mortality. Our analysis was based on a 22-year marking study (n = 27,150 females) and included live recaptures at the breeding colony and dead recoveries from hunters. We tested the effect of climatic covariates by applying a procedure that accounts for unexplained environmental variation in the demographic parameter to a multistate capture-mark-recapture recruitment model. Breeding propensity, clutch size and hatching probability all increased with high temperatures on the breeding grounds. First-year survival to natural causes of mortality increased when temperature was high at the end of the summer, whereas adult survival was not affected by temperature. On the contrary, accession to reproduction decreased with warmer climatic conditions during the non-breeding season. Survival was strongly negatively related to hunting mortality in adults, as expected, but not in first-year birds, which suggests the possibility of compensation between natural and hunting mortality in the latter group. We show that events occurring both at and away from the breeding ground can affect the demography of migratory birds, either directly or through carryover effects, and sometimes in opposite ways. This highlights the need to account for the whole life cycle of an animal when attempting to project the response of populations to future climatic changes., (© 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.)

We examined individual heterogeneity in survival and recruitment of female Pacific black brant (Branta bernicla nigricans) using frailty models adapted to a capture-mark-recapture context. Our main objectives were (1) to quantify levels of heterogeneity and examine factors affecting heterogeneity, and (2) model the effects of individual heterogeneity on harvest dynamics through matrix models. We used 24 years of data on brant marked and recaptured at the Tutakoke River colony, AK. Multievent models were fit as hidden Markov chain using program E-SURGE with an adequate overdispersion coefficient. Annual survival of individuals marked as goslings was heterogeneous among individuals and year specific with about 0.23 difference in survival between "high" (0.73)- and "low" (0.50)-quality individuals at average survival probability. Adult survival (0.85 ± 0.004) was homogeneous and higher than survival of both groups of juveniles. The annual recruitment probability was heterogeneous for brant >1-year-old; 0.56 (±0.21) and 0.31 (±0.03) for high- and low-quality individuals, respectively. Assuming equal clutch sizes for high- and low-quality individuals and that 80% of offspring were in the same quality class as the breeding female resulted in reproductive values about twice as high for high-quality individuals than low-quality individual for a given class of individuals producing differential contributions to population growth among groups. Differences in reproductive values greatly increased when we assumed high-quality individuals had larger clutch sizes. When we assumed that 50% of offspring were in the same quality class as their mothers and clutches were equal, differences in reproductive values between quality classes were greatly reduced or eliminated (breeders [BRs]). We considered several harvest scenarios using the assumption that 80% of offspring were in the same quality class as their mothers. The amount of compensation for harvest mortality declined as the proportion of high-quality individuals in the harvest increased, as differences in clutch sizes between groups decreased and as the proportion of BRs in the harvest increased. Synthesis and applications. Harvest at the same proportional level of the overall population can result in variable responses in population growth rate when heterogeneity is present in a population. λ was <1.0 under every scenario when harvest rates were >10%, and heterogeneity caused as much as +2% difference in growth rates at the highest levels of proportional harvest for low-quality individuals and the greatest differences in qualities between classes of individuals, a critical difference for a population with λ near 1.0 such as the brant. We observed less response in overall survival in the presence of heterogeneity because we did not observe heterogeneity in the annual survival of BRs. This analysis provides a comprehensive view of overall compensation at the population level and also constitutes the first example of a survival-recruitment model with heterogeneity. Individual heterogeneity should be more explicitly considered in harvest management of vertebrates.

Structured population models are widely used in plant and animal demographic studies to assess population dynamics. In matrix population models, populations are described with discrete classes of individuals (age, life history stage or size). To calibrate these models, longitudinal data are collected at the individual level to estimate demographic parameters. However, several sources of uncertainty can complicate parameter estimation, such as imperfect detection of individuals inherent to monitoring in the wild and uncertainty in assigning a state to an individual. Here, we show how recent statistical models can help overcome these issues. We focus on hidden process models that run two time series in parallel, one capturing the dynamics of the true states and the other consisting of observations arising from these underlying possibly unknown states. In a first case study, we illustrate hidden Markov models with an example of how to accommodate state uncertainty using Frequentist theory and maximum likelihood estimation. In a second case study, we illustrate state-space models with an example of how to estimate lifetime reproductive success despite imperfect detection, using a Bayesian framework and Markov Chain Monte Carlo simulation. Hidden process models are a promising tool as they allow population biologists to cope with process variation while simultaneously accounting for observation error., (Copyright © 2012 Elsevier Inc. All rights reserved.)

In this paper we introduce a stochastic model for a population living and migrating between s sites without distinction in the states between residents and immigrants. The evolutionary stable strategies (ESS) is characterized by the maximization of a stochastic growth rate. We obtain that the expectation of reproductive values, normalized by some random quantity, are constant on all sites and that the expectation of the normalized vector population structure is proportional to eigenvector of the dispersion matrix associated to eigenvalue one, which are, in some way, analogous to the results obtained in the deterministic case.

The need to consider in capture-recapture models random effects besides fixed effects such as those of environmental covariates has been widely recognized over the last years. However, formal approaches require involved likelihood integrations, and conceptual and technical difficulties have slowed down the spread of capture-recapture mixed models among biologists. In this article, we evaluate simple procedures to test for the effect of an environmental covariate on parameters such as time-varying survival probabilities in presence of a random effect corresponding to unexplained environmental variation. We show that the usual likelihood ratio test between fixed models is strongly biased, and tends to detect too often a covariate effect. Permutation and analysis of deviance tests are shown to behave properly and are recommended. Permutation tests are implemented in the latest version of program E-SURGE. Our approach also applies to generalized linear mixed models., (© 2011, The International Biometric Society.)

Examples of the impact of human activities on Vertebrate populations abound, with famous cases of extinction. This article reviews how and why Vertebrates are affected by the various components of global change. The effect of direct exploitation, while strong, is currently superseded by changes in use of all sorts, while climate change has started having significant effects on some Vertebrate populations. The low maximum growth rate of Vertebrate populations makes them particularly sensitive to global change, while they contribute relatively modestly to major ecosystem services. One may conclude that unless they are considered as sentinels of the biological consequences of global changes, their situation will go on strongly deteriorating, in particular under the influence of interactions of different components of global change such as changes in use and climate change., (Copyright © 2011 Académie des sciences. Published by Elsevier SAS. All rights reserved.)

Researchers often rely on capture-mark-recapture (CMR) data to study animal dispersal in the wild. Yet their spatial coverage often does not encompass the entire dispersal range of the study individuals, sometimes producing misleading results. Information contained in population surveys and variation in population spatial structure can be used to overcome this issue. We build an integrated model in a multisite context in which CMR data are only collected at a subset of sites, but numbers of breeding pairs are counted at all sites. In a Black-headed Gull Chroicocephalus ridibundus population, the integrated-modeling approach induces an increase in precision for the demographic parameters of interest (variances, on average, were decreased by 20%) and provides a more precise extrapolation of results from the CMR data to the whole population. Patterns of condition-dependent dispersal are therefore made easier to detect, and we obtain evidence for colony-size dependence in recruitment, dispersal, and breeding success. These results suggest that first-time breeders disperse to small colonies in order to recruit earlier. The exchange of experienced breeders between colonies appears as a main determinant of the observed variation in colony sizes.

Whether different sources of mortality are additive, compensatory, or depensatory is a key question in population biology. A way to test for additivity is to calculate the correlation between cause-specific mortality rates obtained from marked animals. However, existing methods to estimate this correlation raise several methodological issues. One difficulty is the existence of an intrinsic bias in the correlation parameter. Although this bias can be formally expressed, it requires knowledge about natural survival without any competing mortality source, which is difficult to assess in most cases. Another difficulty lies in estimating the true process correlation while properly accounting for sampling variation. Using a Bayesian approach, we developed a state-space model to assess the correlation between two competing sources of mortality. By distinguishing the mortality process from its observation through dead recoveries and live recaptures, we estimated the process correlation. To correct for the intrinsic bias, we incorporated experts' opinions on natural survival. We illustrated our approach using data on a hunted population of wild boars. Mortalities were not additive and natural mortality increased with hunting mortality likely as a consequence of non-controlled mortality by crippling loss. Our method opens perspectives for wildlife management and for the conservation of endangered species.

Assessing conservation strategies requires reliable estimates of abundance. Because detecting all individuals is most often impossible in free-ranging populations, estimation procedures have to account for a <1 detection probability. Capture-recapture methods allow biologists to cope with this issue of detectability. Nevertheless, capture-recapture models for open populations are built on the assumption that all individuals share the same detection probability, although detection heterogeneity among individuals has led to underestimating abundance of closed populations. We developed multievent capture-recapture models for an open population and proposed an associated estimator of population size that both account for individual detection heterogeneity (IDH). We considered a two-class mixture model with weakly and highly detectable individuals to account for IDH. In a noninvasive capture-recapture study of wolves we based on genotypes identified in feces and hairs, we found a large underestimation of population size (27% on average) occurred when IDH was ignored.

1. Some species (e.g. migratory species with high movement ability) are unlikely to experience any physical cost when dispersing, at least at the landscape scale. In these species dispersal is nevertheless behaviourally constrained to avoid non-physical costs such as the loss of familiarity with the breeding environment, and these constraints can be maladaptive in a fast-changing environment. 2. We evaluated such constraints using multievent modelling of a 20-year capture-mark-recapture data set from a multisite population of black-headed gull (Chroicocephalus ridibundus). The population undertakes seasonal migrations that are very large compared with the size of the study area. 3. Distances between colonies appeared as a strong predictor of breeding adults' dispersal rates, confirming behavioural constraints on dispersal. In addition, birds that had recruited outside their colony of birth (natal dispersers) tended to return to their colony of birth later in life (long-term memory effect). 4. An attraction for larger colonies was also visible in breeding adult dispersal patterns. The fact that distance and memory still constrained dispersal although the largest colony provided higher breeding success indicated departures from the ideal-free distribution, probably linked with the lack of information about distant colonies. Moreover, the regional population apparently functioned as a meta-colony where individuals frequently bred in suboptimal-choice locations before being able to recruit in their preferred colony.

The stable population theory is classically applicable to populations in which there is a maximum age after which individuals die. Demetrius [1972. On an infinite population matrix. Math. Biosci. 13, 133-137] extended this theory to infinite Leslie matrices, in which the longevity of individuals is potentially infinite. However, Demetrius had to assume that the survival probability per time step tends to 0 with age. We generalise here the conditions of application of the stable population theory to infinite Leslie matrix models and apply these results to two examples, including or not senescence.

There are few analytic tools available to formally integrate information coming from population surveys and demographic studies. The Kalman filter is a procedure that facilitates such integration. Based on a state-space model, we can obtain a likelihood function for the survey data using a Kalman filter, which we may then combine with a likelihood for the demographic data. In this paper, we used this combined approach to analyze the population dynamics of a hunted species, the Greater Snow Goose (Chen caerulescens atlantica), and to examine the extent to which it can improve previous demographic population models. The state equation of the state-space model was a matrix population model with fecundity and regression parameters relating adult survival and harvest rate estimated in a previous capture-recapture study. The observation equation combined the output from this model with estimates from an annual spring photographic survey of the population. The maximum likelihood estimates of the regression parameters from the combined analysis differed little from the values of the original capture-recapture analysis, though their precision improved. The model output was found to be insensitive to a wide range of coefficient of variation (CV) in fecundity parameters. We found a close match between the surveyed and smoothed population size estimates generated by the Kalman filter over an 18-year period, and the estimated CV of the survey (0.078-0.150) was quite compatible with its assumed value (approximately 0.10). When we used the updated parameter values to predict future population size, the model underestimated the surveyed population size by 18% over a three-year period. However, this could be explained by a concurrent change in the survey method. We conclude that the Kalman filter is a promising approach to forecast population change because it incorporates survey information in a formal way compared with ad hoc approaches that either neglect this information or require some parameter or model tuning.

Capture-mark-recapture (CMR) analyses aim primarily at estimating relevant life history parameters, despite the fact that some individuals are not always recaptured, even if alive on the study site. Applying such approaches to species with a complex life cycle, such as insects, remains challenging because each change of stage tends to cause mark loss through molting. We developed a multistate model based on three exclusive events ("dead", "surviving and molting", and "surviving and staying in the same larval stage") to estimate probabilities of survival and mark loss. Estimates of biologically relevant parameters were derived from those of the probabilities of transition between these states. The model was applied to data from radio-tracking diodes glued on grasshoppers. The estimates of recapture probabilities decreased throughout the season for animals remaining alive, while the detection of dead animals and lost diodes was exhaustive. The survival probability was higher for larvae than for adults (0.98 vs. 0.96), and mark loss was stronger in larvae than in adults (0.09 vs. 0.06). We show that the survival rate of a species with a high rate of mark loss can be estimated using multistate models, provided that marks can be recovered after being lost. These models are flexible enough to test for several effects that potentially affect survival and mark loss probabilities.

Population dynamics methodology now powerfully combines discrete time models (with constant parameters, density dependence, random environment, and/or demographic stochasticity) and capture-recapture models for estimating demographic parameters. Vertebrate population dynamics has strongly benefited from this progress: survival estimates have been revised upwards, trade-offs between life history traits have been demonstrated, analyses of population viability and management are more and more realistic. Promising developments concern random effects, multistate and integrated models. Some biological questions (density dependence, links between individual and population levels, and diversification of life histories) can now be efficiently attacked.

1. Global change may strongly affect population dynamics, but mechanisms remain elusive. Several Arctic goose species have increased considerably during the last decades. Climate, and land-use changes outside the breeding area have been invoked as causes but have not been tested. We analysed the relationships between conditions on wintering and migration staging areas, and survival in Svalbard pink-footed geese Anser brachyrhynchus. Using mark-recapture data from 14 winters (1989-2002) we estimated survival rates and tested for time trends, and effects of climate, goose density and land-use. 2. Resighting rates differed for males and females, were higher for birds recorded during the previous winter and changed smoothly over time. Survival rates did not differ between sexes, varied over time with a nonsignificant negative trend, and were higher for the first interval after marking (0.88-0.97) than afterwards (0.74-0.93). Average survival estimates were 0.967 (SE 0.026) for the first and 0.861 (SE 0.023) for all later survival intervals. 3. We combined 16 winter and spring climate covariates into two principal components axes. F1 was related to warm/wet winters and an early spring on the Norwegian staging areas and F2 to dry/cold winters. We expected that F1 would be positively related to survival and F2 negatively. F1 explained 23% of survival variation (F1,10=3.24; one-sided P=0.051) when alone in a model and 28% (F1,9=4.50; one-sided P=0.031) in a model that assumed a trend for survival. In contrast, neither F2 nor density, land-use, or scaring practices on important Norwegian spring staging areas had discernible effects on survival. 4. Climate change may thus affect goose population dynamics, with warmer winters and earlier springs enhancing survival and fecundity. A possible mechanism is increased food availability on Danish wintering and Norwegian staging areas. As geese are among the main herbivores in Arctic ecosystems, climate change, by increasing goose populations, may have important indirect effects on Arctic vegetation. Our study also highlights the importance of events outside the breeding area for the population dynamics of migrant species.

1. A novel capture-mark-recapture (CMR) method was used to build a multistate model of recruitment by young birds to a breeding population of common guillemots Uria aalge on the Isle of May, Scotland. Recruitment of a total of 2757 individually marked guillemots over 17 years was modelled as a process where individuals had to move from an unobservable state at sea, through a nonbreeding state present in the colony, to the breeding state. The probabilities of individuals returning to the colony in a given year, at age 2 and 3-4 years, were positively correlated with an environmental covariate, the winter North Atlantic Oscillation index (WNAO) in the previous years. 2. For 2 year olds, there was a negative relationship with breeding population size, suggesting that density dependence operated in this colony through limitation of food or some other resource. 3. Survival over the first 2 years of life varied with cohort, but was unrelated to the WNAO. Mean survival over this 2-year period was high at 0.576 (95% CI: 0.444; 0.708). 4. This high survival, combined with a low 'local' survival after age 5 years of 0.695 (0-654; 0.733) and observations of Isle of May chicks at other colonies, suggests that most surviving chicks return to the natal colony before deciding whether to recruit there or move elsewhere.

Oli and Dobson proposed that the ratio between the magnitude and the onset of reproduction (F/ alpha ratio) allows one to predict the relative importance of vital rates on population growth rate in mammalian populations and provides a reliable measure of the ranking of mammalian species on the slow-fast continuum of life-history tactics. We show that the choice of the ratio F/ alpha is arbitrary and is not grounded in demographic theory. We estimate the position on the slow-fast continuum using the first axis of a principal components analysis of all life-history variables studied by Oli and Dobson and show that most individual vital rates perform as well as the F/ alpha ratio. Finally, we find, in agreement with previous studies, that the age of first reproduction is a reliable predictor of the ranking of mammalian populations along the slow-fast continuum and that both body mass and phylogeny markedly influence the generation time of mammalian species. We conclude that arbitrary ratios such as F/ alpha correlate with life-history types in mammals simply because life-history variables are highly correlated in response to allometric, phylogenetic, and environmental influences. We suggest that generation time is a reliable metric to measure life-history variation among mammalian populations and should be preferred to any arbitrary combination between vital rates.

We measured genetic differentiation among species of large white-headed gulls using mitochondrial (cytochrome b haplotypes) and nuclear (microsatellites) markers. Additional information was added using a previously published study of allozymes on the same species. Levels of differentiation among species at nuclear markers are much lower than would be expected for avian species and are not concordant with the level of differentiation in mitochondrial markers. This discrepancy is best explained by a combination of recent species origin and interspecific gene flow after speciation. The data also suggest that female-mediated gene flow is reduced compared to male-mediated gene flow, either due to behavioral bias or due to stronger counterselection of female hybrids in accordance with Haldane's rule for ZW species. Whatever the reasons for the low differentiation of the species' nuclear gene pools, the extensive similarity of their nuclear genome demonstrates that selection on a limited number of characters is an important factor in establishing and maintaining clear-cut phenotypic differences between these species and suggests that the number of loci involved in this process is quite low. This situation may not be exceptional in birds, indeed a number of studies have found similarly low level of differentiation in nuclear markers among congeneric bird species, although usually based on a single set of markers. Because hybridization is a widespread phenomenon in birds, many of these cases might be due to interspecific gene flow.

In long-lived colonial birds, age at recruitment is an important life-history character. Variation in this parameter may reflect differences in several factors, including competitive ability and breeding strategies. Further, these differences may be due to timing of hatching (for instance through differences in competitive ability). We investigated the age of first-time breeders in relation to hatching date in a black-headed gull Larus ridibundus colony situated in central France, from 1979 to 1993. Age at first breeding was estimated for four groups of individuals (total n=550) according to their hatching date, using a recent capture-recapture methodology which allowed us to estimate recruitment rate without the limiting assumptions of methods relying on simple return rates. The age at first breeding was negatively correlated with the hatching date of individuals: individuals hatched earlier in the season started breeding at a younger age than individuals born later. Proportionally more 2-year-old late-hatched individuals were seen breeding on small peripheral colonies than young early-hatched individuals. This difference disappeared after age 3 years. These results strongly suggest that individuals hatched late in the season start to breed on peripheral colonies before recruiting to their natal colony. A difference of few weeks in hatching date has consequences which can last for several years.

The effects of food availability and nest predation on several life history traits such as adult survival, dispersal, and reproductive performance were assessed in an Audouin's gull (Larus audouinii) colony during the period 1992-1997. The amounts of fish discarded from trawlers were used as a measure of food availability, and a trawling moratorium which partially overlapped with the breeding season of the gulls was taken into account. The effects of nest predation were assessed in 1994, when a terrestrial predator entered the colony and remained for the whole breeding season preying on both eggs and chicks. Using the moratorium and the predatory event as natural experiments, several hypotheses were tested: (a) food supply would affect breeding performance but not adult survival (independently of age and sex), since gulls are long-lived and adult survival is the most sensitive demographic parameter in their population dynamics; (b) the predator would trigger breeding dispersal (although gulls are mostly philopatric, they are known to abandon their natal colony after breeding failure instigated by events such as this). If breeding dispersal occurs, the rate is expected to be higher in females than in males, and higher in new breeders than in more experienced breeding birds, as is usually recorded in colonial seabirds. Probabilities of resighting and survival were estimated separately, using capture-recapture models. As expected, changes in food availability did not affect adult survival, whereas they influenced egg volume, clutch size, and breeding success. Local adult survival was estimated to be 0.908 (SD = 0.007) for males and females, and it did not change significantly with the age of individuals (range 3-8 years). The predator significantly decreased breeding success, and caused the dispersal of a number of adults probably to breed in another colony; this rate was estimated at an average of 0.10 (SD = 0.02). As expected, inexperienced breeders dispersed significantly more (14%) than more experienced breeders (8%) after the predator event, but dispersal was not sex biased. Recapture probabilities after the predator event suggest that birds that left the colony still had not returned. Results confirm that population dynamics of ground-nesting seabirds are sensitive to terrestrial predation, even when predation caused only a partial breeding failure.

Time- and sex-specific summer survival of roe deer fawns was estimated using capture-mark-recapture methods in two enclosed populations living in contrasting conditions. The population of Trois Fontaines (eastern France) was roughly constant in size throughout the study period, while in Chizé (western France), the population experienced frequent summer droughts and numbers decreased continuously during the study. Early survival of fawns was low and highly variable over the years at both Chizé and Trois Fontaines, and demonstrated marked variations between cohorts that need to be taken into account when modelling roe deer population dynamics. In Trois Fontaines, fawn survival was positively correlated with early body growth and total rainfall in May and June. In Chizé, fawn survival decreased with increasing density and tended to increase with increasing rainfall in May and June and adult female body mass. These factors explained more than 75% of the variability in early survival observed in both populations. Variation between cohorts had different consequences for the two populations. At Trois Fontaines, cohort variation was limited to a numerical effect on early survival. However at Chizé, cohort variation was long-lasting and affected the phenotypic quality of survivors at later ages, and thereby future survival and breeding abilities (both numerical and quality effects). Male and female fawns had similar survival over their first summer in both populations. This result contrasts with the lower survival of young males often observed in ungulates. Two ultimate causes can be proposed to account for the low and variable survival of roe deer fawns over the first summer: the high energy expenditures incurred by does during each breeding attempt and/or the low absolute body size of newborn roe deer fawns.

Le Bras (Theor. Popul. Biol. 2, 100-121, 1971) and Rogers (Demography 11, 473-481, 1974), in two neglected papers, have generalized to the multisite case the Euler-Lotka renewal equation and demographic characteristics such as age structure and reproductive value. The purpose of this paper is twofold: first, to restate the multisite renewal equation in the matrix context; second, to derive results on age structure, net reproduction rate, generation time, and sensitivities, as generalizations of the one site case. The potential of this approach for population biology is illustrated using a model of a black-headed gull Larus ridibundus population.

We provide a statistical framework to estimate age-specific breeding probabilities in vertebrate populations, from recaptures or resightings of individuals marked as young. We consider data collected at one or possibly several points over time, when individual recapture histories are known, leading to models which we call longitudinal models. An example of resightings of black-headed gulls, Larus ridibundus, is considered.

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., (Copyright © 1993. Published by Elsevier Ltd.)

Although most life history traits in birds and mammals show an allometric relationship with body weight (Brody 1945; Lack 1968; Peters 1983; Calder 1984), such studies have failed to show a clear relationship for the components of fecundity: litter size and number of litters per year. By using a functional definition of the fecundity as the product of the number of litters per year with litter size, however we find an allometric relationship with allometric exponents of-0.15 in birds and-0.22 in mammals. the observed value of the allometric exponent for each order is discussed with regard to the theoretical value expected for variables dependent on time according to Lindstedt and Calder (Lindstedt and Calder 1981; Lindstedt et al. 1986). This has direct implications for investigation of demographic strategies.

The discrete-time linear recurrent models proposed by Leslie in 1945 and Usher in 1966 for age-or stage-grouped populations are discussed with emphasis on the random nature, due to sampling variations, of their well-known asymptotic behavior. The statistical properties of the estimated asymptotic multiplication rate, stage, or age stable structures and mean generation time are inspected by both a theoretical approach and a simulation procedure. Illustrative case studies provide some order of magnitudes of the sampling bias and variance of these statistics.