Changes in the abundance and distribution of wildlife populations are common consequences of historic and contemporary climate change. Some Arctic marine mammals, such as the polar bear (Ursus maritimus), may be particularly vulnerable to such changes due to the loss of Arctic sea ice. We evaluated the impacts of environmental variation on demographic rates for the Western Hudson Bay (WH), polar bear subpopulation from 1984 to 2011 using live-recapture and dead-recovery data in a Bayesian implementation of multistate capture-recapture models. We found that survival of female polar bears was related to the annual timing of sea ice break-up and formation. Using estimated vital rates (e.g., survival and reproduction) in matrix projection models, we calculated the growth rate of the WH subpopulation and projected population responses under different environmental scenarios while accounting for parametric uncertainty, temporal variation, and demographic stochasticity. Our analysis suggested a long-term decline in the number of bears from 1185 (95% Bayesian credible interval [BCI] = 993-1411) in 1987 to 806 (95% BCI = 653-984) in 2011. In the last 10 yr of the study, the number of bears appeared stable due to temporary stability in sea ice conditions (mean population growth rate for the period 2001-2010 = 1.02, 95% BCI = 0.98-1.06). Looking forward, we estimated long-term growth rates for the WH subpopulation of ~1.02 (95% BCI = 1.00-1.05) and 0.97 (95% BCI = 0.92-1.01) under hypothetical high and low sea ice conditions, respectively. Our findings support previous evidence for a demographic linkage between sea ice conditions and polar bear population dynamics. Furthermore, we present a robust framework for sensitivity analysis with respect to continued climate change (e.g., to inform scenario planning) and for evaluating the combined effects of climate change and management actions on the status of wildlife populations.

Summary1. Demographic tactics within animal populations are shaped by selective pressures. Exploitation exerts additional pressures so that differing demographic tactics might be expected among populations with differences in levels of exploitation. Yet little has been done so far to assess the possible consequences of exploitation on the demographic tactics of mammals, even though such information could influence the choice of effective management strategies. 2. Compared with similar-sized ungulate species, wild boar Sus scrofa has high reproductive capabilities, which complicates population management. Using a perturbation analysis, we investigated how population growth rates (k) and critical life-history stages differed between two wild boar populations monitored for several years, one of which was heavily harvested and the other lightly harvested. 3. Asymptotic k was 1AE242 in the lightly hunted population and 1AE115 in the heavily hunted population, while the ratio between the elasticity of adult survival and juvenile survival was 2AE63 and 1AE27, respectively. A comparative analysis including 21 other ungulate species showed that the elasticity ratio in the heavily hunted population was the lowest ever observed. 4. Compared with expected generation times of similar-sized ungulates (more than 6 years), wild boar has a fast life-history speed, especially when facing high hunting pressure. This is well illustrated by our results, where generation times were 3AE6 years in the lightly hunted population and only 2AE3 years in the heavily hunted population. High human-induced mortality combined with non-limiting food resources accounted for the accelerated life history of the hunted population because of earlier reproduction. 5. Synthesis and applications. For wild boar, we show that when a population is facing a high hunting pressure, increasing the mortality in only one age-class (e.g. adults or juveniles) may not allow managers to limit population growth. We suggest that simulations of management strategies based on context-specific demographic models are useful for selecting interventions for population control. This type of approach allows the assessment of population response to exploitation by considering a range of plausible scenarios, improving the chance of selecting appropriate management actions.

No abstract

Exploitation by humans affects the size and structure of populations. This has evolutionary and demographic consequences that have typically being studied independent of one another. We here applied a framework recently developed applying quantitative tools from population ecology and selection gradient analysis to quantify the selection on a quantitative trait-birth datethrough its association with multiple fitness components. From the long-term monitoring (22 years) of a wild boar (Sus scrofa scrofa) population subject to markedly increasing hunting pressure, we found that birth dates have advanced by up to 12 days throughout the study period. During the period of low hunting pressure, there was no detectable selection. However, during the period of high hunting pressure, the selection gradient linking breeding probability in the first year of life to birth date was negative, supporting current life-history theory predicting selection for early births to reproduce within the first year of life with increasing adult mortality.

Abstract. 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.

Summary1. Harvest models are often built to explore the sustainability of the dynamics of exploited populations and to help evaluate hunting management scenarios. Age-structured models are commonly used for ungulate population dynamics. However, the age of hunted individuals is usually not recorded, and hunting data often only include body weight and sex limiting the usefulness of traditional models. 2. We propose a new modelling approach that fits data collected by hunters to develop management rules when age is not available. Using wild boar Sus scrofa scrofa as a case study, we built a matrix model structured according to sex and body weight whose output can be directly compared with the observed distribution of hunted individuals among sex and body weight classes. 3. In the face of the current wide scale increase in populations of wild boar, the best feasible option to stop or slow down population growth involves targeting the hunting effort to specific sex and body weight classes. The optimal harvest proportion in the target body weight classes is estimated using sensitivity analyses. 4. The number of individuals shot in each sex and body weight class predicted by our model was closely associated with those recorded in the hunting bag. Increasing the hunting pressure on medium-sized females by 14AE6% was the best option to limit growth rate to a target of 0AE90. 5. Synthesis and applications. We demonstrate that targeting hunting effort to specific body weight classes could reliably control population growth. Our modelling approach can be applied to any game species where group composition, phenotypic traits or coat colour allows hunters to easily identify sex and body weight classes. This offers a promising tool for applying selective hunting to the management of game species.

Data on 22 radio-collared adult female roe deer Capreolus capreolus in the Chizé forest were used to test whether their home-range size was influenced by resource availability and reproductive status. As roe deer females are income breeders and invest heavily in each reproductive attempt, they should be limited by energetic constraints. Thus it was expected that: (1) heavier females should have larger home ranges; (2) that home-range size should decrease with increasing vegetation biomass; (3) home-range size should increase with increasing reproductive effort (i.e. females with two fawns at heel should have larger home ranges than those with one fawn, which should have larger home range than females without fawns). To test these predictions, variation in spring-summer homerange size was studied in 2001 and 2002, using 95% kernel home-range estimation. Results showed that females do not adjust their home-range size in response to body mass or age. Home-range size increased with increasing reproductive success, but the magnitude of the change varied over the period of maternal care. Finally, although their home-range size decreased with increasing plant biomass (slope = − 0.11, SE = 0.065), female roe deer at Chizé did not fully compensate for declines in food availability by increasing home-range size.

No abstract