1. 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 (λ) 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 λ was 1·242 in the lightly hunted population and 1·115 in the heavily hunted population, while the ratio between the elasticity of adult survival and juvenile survival was 2·63 and 1·27, 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 3·6 years in the lightly hunted population and only 2·3 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.
Animal distribution and abundance are greatly affected by the availability of their food resources, which also depends on landscape structure. Lothar hurricane in 1999 had profoundly modified the ...structure of the forests in France, affecting the habitat quality of ungulates. We tested whether the variations in home-range size of 23 female roe deer were influenced by the fragmentation of the landscape caused by Lothar in the Chizé forest, namely by the increase in heterogeneity associated with the localized massive tree felling. Home-range size was studied in the summers of 2001 and 2002 and we found that variation in home-range size was mainly explained by only one landscape variable: edge density. Home-range size decreased as edge density increased, which is consistent with the fact that edges are good browsing habitats for roe deer. The result of this study suggests that, after 2 years, the hurricane had improved the quality of the home ranges by creating more forest heterogeneity and increasing the contacts between the different vegetation patches within the home range. These results highlight the fact that spatial heterogeneity is likely to be a key factor influencing the distribution and local population density.PUBLICATION ABSTRACT
1. Identifying which factors influence age and size at maturity is crucial for a better understanding of the evolution of life-history strategies. In particular, populations intensively harvested, ...hunted or fished by humans often respond by displaying earlier age and decreased size at first reproduction. 2. Among ungulates wild boar (Sus scrofa scrofa L.) exhibit uncommon life-history traits, such as high fertility and early reproduction, which might increase the demographic impact of varying age at first reproduction. We analysed variation in female reproductive output from a 22-year long study of an intensively hunted population. We assessed how the breeding probability and the onset of oestrus responded to changes of female body mass at different ages under varying conditions of climate and food availability. 3. Wild boar females had to reach a threshold body mass (27-33 kg) before breeding for the first time. This threshold mass was relatively low (33-41% of adult body mass) compared to that reported in most other ungulates (about 80%). 4. Proportions of females breeding peaked when rainfall and temperature were low in spring and high in summer. Climatic conditions might act through the nutritional condition of females. The onset of oestrus varied a lot in relation to resources available at both current and previous years. Between none and up to 90% of females were in oestrus in November depending on the year. 5. Past and current resources accounted for equivalent amount of observed variations in proportions of females breeding. Thus, wild boar rank at an intermediate position along the capital-income continuum rather than close to the capital end where similar-sized ungulates rank. 6. Juvenile females made a major contribution to the yearly reproductive output. Comparisons among wild boar populations facing contrasted hunting pressures indicate that a high demographic contribution of juveniles is a likely consequence of a high hunting pressure rather than a species-specific life-history pattern characterizing wild boar.
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 date—through 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.
1. 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 14·6% was the best option to limit growth rate to a target of 0·90. 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.
We assessed age-specific natural mortality (i.e., excluding hunting mortality) and hunting mortality of 1,175 male and 1,076 female wild boar (Sus scrofa) from Châteauvillain-Arc en Barrois (eastern ...France), using a 22-year dataset (1982–2004) and mark–recapture–recovery methods. Overall yearly mortality was >50% for all sex and age-classes. Low survival was mostly due to high hunting mortality; a wild boar had a >40% of chance of being harvested annually, and this risk was as high as 70% for adult males. Natural mortality rates of wild boar were similar for males and females (approx. 0.15). These rates were comparable to rates typical of male ungulates but high for female ungulates. Wild boar survival did not vary across sex and age-classes. Despite high hunting mortality, we did not detect evidence of compensatory mortality. Whereas natural mortality for males was constant over time, female mortality varied annually, independent of fluctuations in mast availability. Female wild boar survival patterns differed from those reported in other ungulates, with high and variable natural mortality. In other ungulates, natural mortality is typically low and stable across a wide range of environmental conditions. These differences may partly reflect high litter sizes for wild boar, which carries high energetic costs. High hunting mortality may induce a high investment of females in reproduction early in life, at the detriment to survival. Despite high hunting mortality, the study population increased. Effective population control of wild boar should target a high harvest rate of piglets and reproductive females.
For species in which reproductive success is more variable in one sex than the other, the Trivers and Willard model (TWM) predicts that females are able to adjust their offspring sex ratio. ...High-quality mothers should provide greater investment to one sex than the other. Previous tests of the TWM have been inconsistent, and whether the TWM applies to species with several offspring per litter is unclear due to possible trade-offs between size, number, and sex of the offspring. Williams' model (WM) accounts for confounding effects of these trade-offs on sex ratio variation. Lastly, the “extrinsic modification hypothesis” predicts changes in offspring sex ratio in relation to climatic conditions and population density. Using wild boar as a model, we tested 1) whether the WM fitted observed sex ratio variation and 2) whether sex ratio variations were related to maternal attributes (test of the TWM) and/or to resource availability (test of the extrinsic modification hypothesis). Females adjusted their litter size rather than their litter composition, so that the WM was not supported. Likewise, changes in resource availability did not influence the fetal sex ratio, so that the extrinsic modification hypothesis was not supported. The fetal sex ratio was negatively related to increasing litter size, providing some support for the TWM. Sex ratio was male biased for litter sizes up to 6 and then became female biased in larger litters. Our results provide the first case study showing marked changes in sex ratio in relation to litter size in a large mammal.
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 home-range 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.
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 2011–2010 = 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.
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