Sexual segregation results in pronounced sex-specific density gradients in the mountain ungulate, Rupicapra rupicapra.

Sex-specific differences in habitat selection and space use are common in ungulates. Yet, it is largely unknown how this behavioral dimorphism, ultimately leading to sexual segregation, translates to population-level patterns and density gradients across landscapes. Alpine chamois (Rupicapra rupicapra r.) predominantly occupy habitat above tree line, yet especially males may also take advantage of forested habitats. To estimate male and female chamois density and determinants thereof, we applied Bayesian spatial capture-recapture (SCR) models in two contrasting study areas in the Alps, Germany, during autumn. We fitted SCR models to non-invasive individual encounter data derived from genotyped feces. Sex-specific densities were modeled as a function of terrain ruggedness, forest canopy cover, proportion of barren ground, and site severity. We detected pronounced differences in male and female density patterns, driven primarily by terrain ruggedness, rather than by sex-specific effects of canopy cover. The positive effect of ruggedness on density was weaker for males which translated into a higher proportion of males occupying less variable terrain, frequently located in forests, compared to females. By estimating sex-specific variation in both detection probabilities and density, we were able to quantify and map how individual behavioral differences scale up and shape spatial patterns in population density.

A multidisciplinary approach to estimating wolf population size for long-term conservation.

The wolf (Canis lupus) is among the most controversial of wildlife species. Abundance estimates are required to inform public debate and policy decisions, but obtaining them at biologically relevant scales is challenging. We developed a system for comprehensive population estimation across the Italian alpine region (100,000 km2 ), involving 1513 trained operators representing 160 institutions. This extensive network allowed for coordinated genetic sample collection and landscape-level spatial capture-recapture analyses that transcended administrative boundaries to produce the first estimates of key parameters for wolf population status assessment. Wolf abundance was estimated at 952 individuals (95% credible interval 816-1120) and 135 reproductive units (i.e., packs) (95% credible interval 112-165). We also estimated that mature individuals accounted for 33-45% of the entire population. The monitoring effort was spatially estimated thereby overcoming an important limitation of citizen science data. This is an important approach for promoting wolf-human coexistence based on wolf abundance monitoring and an endorsement of large-scale harmonized conservation practices.

Una estrategia multidisciplinaria para la estimación del tamaño poblacional de los lobos para la conservación a largo plazo Resumen El lobo (Canis lupus) está entre las especies de fauna más controversiales. Se requieren estimaciones de abundancia para informar al debate público y las decisiones políticas, pero es un reto obtenerlos en escalas con relevancia biológica. Desarrollamos un sistema para la estimación completa de la población en la región alpina de Italia (100,000 km2 ), con la participación de 1,513 operadores entrenados que representan a 160 instituciones. Esta red extensa permitió una colecta coordinada de muestras genéticas y análisis de captura-recaptura espacial que trascendieron las fronteras administrativas para así producir las primeras estimaciones de los parámetros clave para la evaluación del estado de la población de los lobos. Se estimó la abundancia en 952 individuos (95% intervalo de confianza 816-1120) y 135 unidades reproductivas (es decir, manadas) (95% intervalo de confianza 112-165). También estimamos que los individuos maduros representaban el 33-45% de toda la población. El esfuerzo de monitoreo se estimó espacialmente, por lo que sobrepasó una limitación importante de la ciencia ciudadana. Esta estrategia es importante para promover la coexistencia entre lobos y humanos con base en el monitoreo de la abundancia y el apoyo a las prácticas armonizadas de conservación a gran escala.

Occurrence dynamics of mammals in protected tropical forests respond to human presence and activities.

Protected areas (PAs) play a vital role in wildlife conservation. Nonetheless there is concern and uncertainty regarding how and at what spatial scales anthropogenic stressors influence the occurrence dynamics of wildlife populations inside PAs. Here we assessed how anthropogenic stressors influence occurrence dynamics of 159 mammal species in 16 tropical PAs from three biogeographic regions. We quantified these relationships for species groups (habitat specialists and generalists) and individual species. We used long-term camera-trap data (1,002 sites) and fitted Bayesian dynamic multispecies occupancy models to estimate local colonization (the probability that a previously empty site is colonized) and local survival (the probability that an occupied site remains occupied). Multiple covariates at both the local scale and landscape scale influenced mammal occurrence dynamics, although responses differed among species groups. Colonization by specialists increased with local-scale forest cover when landscape-scale fragmentation was low. Survival probability of generalists was higher near the edge than in the core of the PA when landscape-scale human population density was low but the opposite occurred when population density was high. We conclude that mammal occurrence dynamics are impacted by anthropogenic stressors acting at multiple scales including outside the PA itself.

Spatial variation in red deer density in a transboundary forest ecosystem.

Forests in Europe are exposed to increasingly frequent and severe disturbances. The resulting changes in the structure and composition of forests can have profound consequences for the wildlife inhabiting them. Moreover, wildlife populations in Europe are often subjected to differential management regimes as they regularly extend across multiple national and administrative borders. The red deer Cervus elaphus population in the Bohemian Forest Ecosystem, straddling the Czech-German border, has experienced forest disturbances, primarily caused by windfalls and bark beetle Ips typographus outbreaks during the past decades. To adapt local management strategies to the changing environmental conditions and to coordinate them across the international border, reliable estimates of red deer density and abundance are highly sought-after by policymakers, wildlife managers, and stakeholders. Covering a 1081-km2 study area, we conducted a transnational non-invasive DNA sampling study in 2018 that yielded 1578 genotyped DNA samples from 1120 individual red deer. Using spatial capture-recapture models, we estimated total and jurisdiction-specific abundance of red deer throughout the ecosystem and quantified the role of forest disturbance and differential management strategies in shaping spatial heterogeneity in red deer density. We hypothesised that (a) forest disturbances provide favourable habitat conditions (e.g., forage and cover), and (b) contrasting red deer management regimes in different jurisdictions create a differential risk landscape, ultimately shaping density distributions. Overall, we estimated that 2851 red deer (95% Credible Interval = 2609-3119) resided in the study area during the sampling period, with a relatively even overall sex ratio (1406 females, 95% CI = 1229-1612 and 1445 males, 95% CI = 1288-1626). The average red deer density was higher in Czechia (3.5 km-2, 95% CI = 1.2-12.3) compared to Germany (2 km-2, 95% CI = 0.2-11). The effect of forest disturbances on red deer density was context-dependent. Forest disturbances had a positive effect on red deer density at higher elevations and a negative effect at lower elevations, which could be explained by partial migration and its drivers in this population. Density of red deer was generally higher in management units where hunting is prohibited. In addition, we found that sex ratios differed between administrative units and were more balanced in the non-intervention zones. Our results show that the effect of forest disturbances on wild ungulates is modulated by additional factors, such as elevation and ungulate management practices. Overall density patterns and sex ratios suggested strong gradients in density between administrative units. With climate change increasing the severity and frequency of forest disturbances, population-level monitoring and management are becoming increasingly important, especially for wide-ranging species as both wildlife and global change transcend administrative boundaries.

A flexible and efficient Bayesian implementation of point process models for spatial capture-recapture data.

Spatial capture-recapture (SCR) is now routinely used for estimating abundance and density of wildlife populations. A standard SCR model includes sub-models for the distribution of individual activity centers (ACs) and for individual detections conditional on the locations of these ACs. Both sub-models can be expressed as point processes taking place in continuous space, but there is a lack of accessible and efficient tools to fit such models in a Bayesian paradigm. Here, we describe a set of custom functions and distributions to achieve this. Our work allows for more efficient model fitting with spatial covariates on population density, offers the option to fit SCR models using the semi-complete data likelihood (SCDL) approach instead of data augmentation, and better reflects the spatially continuous detection process in SCR studies that use area searches. In addition, the SCDL approach is more efficient than data augmentation for simple SCR models while losing its advantages for more complicated models that account for spatial variation in either population density or detection. We present the model formulation, test it with simulations, quantify computational efficiency gains, and conclude with a real-life example using non-invasive genetic sampling data for an elusive large carnivore, the wolverine (Gulo gulo) in Norway.

Estimating spatially variable and density-dependent survival using open-population spatial capture-recapture models.

Open-population spatial capture-recapture (OPSCR) models use the spatial information contained in individual detections collected over multiple consecutive occasions to estimate not only occasion-specific density, but also demographic parameters. OPSCR models can also estimate spatial variation in vital rates, but such models are neither widely used nor thoroughly tested. We developed a Bayesian OPSCR model that not only accounts for spatial variation in survival using spatial covariates but also estimates local density-dependent effects on survival within a unified framework. Using simulations, we show that OPSCR models provide sound inferences on the effect of spatial covariates on survival, including multiple competing sources of mortality, each with potentially different spatial determinants. Estimation of local density-dependent survival was possible but required more data due to the greater complexity of the model. Not accounting for spatial heterogeneity in survival led to up to 10% positive bias in abundance estimates. We provide an empirical demonstration of the model by estimating the effect of country and density on cause-specific mortality of female wolverines (Gulo gulo) in central Sweden and Norway. The ability to make population-level inferences on spatial variation in survival is an essential step toward a fully spatially explicit OPSCR model capable of disentangling the role of multiple spatial drivers of population dynamics.

Consistent diel activity patterns of forest mammals among tropical regions.

An animal's daily use of time (their "diel activity") reflects their adaptations, requirements, and interactions, yet we know little about the underlying processes governing diel activity within and among communities. Here we examine whether community-level activity patterns differ among biogeographic regions, and explore the roles of top-down versus bottom-up processes and thermoregulatory constraints. Using data from systematic camera-trap networks in 16 protected forests across the tropics, we examine the relationships of mammals' diel activity to body mass and trophic guild. Also, we assess the activity relationships within and among guilds. Apart from Neotropical insectivores, guilds exhibited consistent cross-regional activity in relation to body mass. Results indicate that thermoregulation constrains herbivore and insectivore activity (e.g., larger Afrotropical herbivores are ~7 times more likely to be nocturnal than smaller herbivores), while bottom-up processes constrain the activity of carnivores in relation to herbivores, and top-down processes constrain the activity of small omnivores and insectivores in relation to large carnivores' activity. Overall, diel activity of tropical mammal communities appears shaped by similar processes and constraints among regions reflecting body mass and trophic guilds.

Occupancy winners in tropical protected forests: a pantropical analysis.

The structure of forest mammal communities appears surprisingly consistent across the continental tropics, presumably due to convergent evolution in similar environments. Whether such consistency extends to mammal occupancy, despite variation in species characteristics and context, remains unclear. Here we ask whether we can predict occupancy patterns and, if so, whether these relationships are consistent across biogeographic regions. Specifically, we assessed how mammal feeding guild, body mass and ecological specialization relate to occupancy in protected forests across the tropics. We used standardized camera-trap data (1002 camera-trap locations and 2-10 years of data) and a hierarchical Bayesian occupancy model. We found that occupancy varied by regions, and certain species characteristics explained much of this variation. Herbivores consistently had the highest occupancy. However, only in the Neotropics did we detect a significant effect of body mass on occupancy: large mammals had lowest occupancy. Importantly, habitat specialists generally had higher occupancy than generalists, though this was reversed in the Indo-Malayan sites. We conclude that habitat specialization is key for understanding variation in mammal occupancy across regions, and that habitat specialists often benefit more from protected areas, than do generalists. The contrasting examples seen in the Indo-Malayan region probably reflect distinct anthropogenic pressures.

Mapping the "catscape" formed by a population of pet cats with outdoor access.

The domestic cat (Felis catus) is among the most popular companion animals and most abundant carnivores globally. It is also a pet with an immense ecological footprint because even non-feral and food-subsidized cats can be prolific predators. Whereas knowledge about the spatial behavior of individual domestic cats is growing, we still know little about how a local population of free-ranging pet cats occupies the landscape. Using a citizen science approach, we GPS-tagged 92 pet cats with outdoor access living in a residential area in southern Norway. The resulting position data allowed us to construct both individual home range kernels and a population-level utilization distribution. Our results reveal a dense predatory blanket that outdoor cats drape over and beyond the urban landscape. It is this population-level intensity surface-the "catscape"-that potential prey have to navigate. There were few gaps in the catscape within our residential study area and therefore few terrestrial refuges from potential cat predation. However, cats spent on average 79% of their outdoor time within 50 m to their owner's home, which suggests that the primary impact is local and most acute for wildlife in the vicinity to homes with cats. We discuss the catscape as a conceptual and quantitative tool for better understanding and mitigating the environmental impact of domestic cats.

Smartphone app reveals that lynx avoid human recreationists on local scale, but not home range scale.

Outdoor recreation is increasing and affects habitat use and selection by wildlife. These effects are challenging to study, especially for elusive species with large spatial requirements, as it is hard to obtain reliable proxies of recreational intensity over extensive areas. Commonly used proxies, such as the density of, or distance to, hiking paths, ignore outdoor recreation occurring on other linear feature types. Here we utilized crowdsourced data from the Strava training app to obtain a large-scale proxy for pedestrian outdoor recreation intensity in southeast Norway. We used the proxy and GPS-tracking data from collared Eurasian lynx (Lynx lynx) to investigate how recreation affects habitat selection at the home range scale and local scale by lynx during summer. We fitted resource selection functions at the two scales using conditional logistic regression. Our analysis revealed that lynx avoided areas of recreational activity at the local scale, but not at home range scale. Nonetheless, lynx frequently used areas associated with recreation, and to a greater degree at night than during the day. Our results suggest that local-scale avoidance of recreation and temporal adjustments of habitat use by lynx mitigate the need for a home range-scale response towards recreation. Scale-dependent responses and temporal adjustments in habitat use may facilitate coexistence between humans and large carnivores.

Does the punishment fit the crime? Consequences and diagnosis of misspecified detection functions in Bayesian spatial capture-recapture modeling.

Spatial capture-recapture (SCR) analysis is now used routinely to inform wildlife management and conservation decisions. It is therefore imperative that we understand the implications of and can diagnose common SCR model misspecifications, as flawed inferences could propagate to policy and interventions. The detection function of an SCR model describes how an individual's detections are distributed in space. Despite the detection function's central role in SCR, little is known about the robustness of SCR-derived abundance estimates and home range size estimates to misspecifications. Here, we set out to (a) determine whether abundance estimates are robust to a wider range of misspecifications of the detection function than previously explored, (b) quantify the sensitivity of home range size estimates to the choice of detection function, and (c) evaluate commonly used Bayesian p-values for detecting misspecifications thereof. We simulated SCR data using different circular detection functions to emulate a wide range of space use patterns. We then fit Bayesian SCR models with three detection functions (half-normal, exponential, and half-normal plateau) to each simulated data set. While abundance estimates were very robust, estimates of home range size were sensitive to misspecifications of the detection function. When misspecified, SCR models with the half-normal plateau and exponential detection functions produced the most and least reliable home range size, respectively. Misspecifications with the strongest impact on parameter estimates were easily detected by Bayesian p-values. Practitioners using SCR exclusively for density estimation are unlikely to be impacted by misspecifications of the detection function. However, the choice of detection function can have substantial consequences for the reliability of inferences about space use. Although Bayesian p-values can aid the diagnosis of detection function misspecification under certain conditions, we urge the development of additional custom goodness-of-fit diagnostics for Bayesian SCR models to identify a wider range of model misspecifications.

Estimating red fox density using non-invasive genetic sampling and spatial capture-recapture modelling.

Spatial capture-recapture modelling (SCR) is a powerful tool for estimating density, population size, and space use of elusive animals. Here, we applied SCR modelling to non-invasive genetic sampling (NGS) data to estimate red fox (Vulpes vulpes) densities in two areas of boreal forest in central (2016-2018) and southern Norway (2017-2018). Estimated densities were overall lower in the central study area (mean = 0.04 foxes per km2 in 2016, 0.10 in 2017, and 0.06 in 2018) compared to the southern study area (0.16 in 2017 and 0.09 in 2018). We found a positive effect of forest cover on density in the central, but not the southern study area. The absence of an effect in the southern area may reflect a paucity of evidence caused by low variation in forest cover. Estimated mean home-range size in the central study area was 45 km2 [95%CI 34-60] for females and 88 km2 [69-113] for males. Mean home-range sizes were smaller in the southern study area (26 km2 [16-42] for females and 56 km2 [35-91] for males). In both study areas, detection probability was session-dependent and affected by sampling effort. This study highlights how SCR modelling in combination with NGS can be used to efficiently monitor red fox populations, and simultaneously incorporate ecological factors and estimate their effects on population density and space use.

Context-dependent fitness costs of reproduction despite stable body mass costs in an Arctic herbivore.

The cost of reproduction on demographic rates is often assumed to operate through changing body condition. Several studies have found that reproduction depresses body mass more if the current conditions are severe, such as high population densities or adverse weather, than under benign environmental conditions. However, few studies have investigated the association between the fitness components and body mass costs of reproduction. Using 25 years of individual-based capture-recapture data from Svalbard reindeer Rangifer tarandus platyrhynchus, we built a novel Bayesian state-space model that jointly estimated interannual change in mass, annual reproductive success and survival, while accounting for incomplete observations. The model allowed us to partition the differential effects of intrinsic and extrinsic factors on both non-reproductive mass change and the body mass cost of reproduction, and to quantify their consequences on demographic rates. Contrary to our expectation, the body mass cost of reproduction (mean = -5.8 kg) varied little between years (CV = 0.08), whereas the between-year variation in body mass changes, that were independent of the previous year's reproductive state, varied substantially (CV = 0.4) in relation to autumn temperature and the amount of rain-on-snow in winter. This body mass loss led to a cost of reproduction on the next reproduction, which was amplified by the same environmental covariates, from a 10% reduction in reproductive success in benign years, to a 50% reduction in harsh years. The reproductive mass loss also resulted in a small reduction in survival. Our results show how demographic costs of reproduction, driven by interannual fluctuations in individual body condition, result from the balance between body mass costs of reproduction and body mass changes that are independent of previous reproductive state. We illustrate how a strong context-dependent fitness cost of reproduction can occur, despite a relatively fixed body mass cost of reproduction. This suggests that female reindeer display a very conservative energy allocation strategy, either aborting their reproductive attempt at an early stage or weaning at a relatively constant cost. Such a strategy might be common in species living in a highly stochastic and food limited environment.

The interplay between hunting rate, hunting selectivity, and reproductive strategies shapes population dynamics of a large carnivore.

Harvest, through its intensity and regulation, often results in selection on female reproductive traits. Changes in female traits can have demographic consequences, as they are fundamental in shaping population dynamics. It is thus imperative to understand and quantify the demographic consequences of changes in female reproductive traits to better understand and anticipate population trajectories under different harvest intensities and regulations. Here, using a dynamic, frequency-dependent, population model of the intensively hunted brown bear (Ursus arctos) population in Sweden, we quantify and compare population responses to changes in four reproductive traits susceptible to harvest-induced selection: litter size, weaning age, age at first reproduction, and annual probability to reproduce. We did so for different hunting quotas and under four possible hunting regulations: (i) no individuals are protected, (ii) mothers but not dependent offspring are protected, (iii) mothers and dependent offspring of the year (cubs) are protected, and (iv) entire family groups are protected (i.e., mothers and dependent offspring of any age). We found that population growth rate declines sharply with increasing hunting quotas. Increases in litter size and the probability to reproduce have the greatest potential to affect population growth rate. Population growth rate increases the most when mothers are protected. Adding protection on offspring (of any age), however, reduces the availability of bears for hunting, which feeds back to increase hunting pressure on the nonprotected categories of individuals, leading to reduced population growth. Finally, we found that changes in reproductive traits can dampen population declines at very high hunting quotas, but only when protecting mothers. Our results illustrate that changes in female reproductive traits may have context-dependent consequences for demography. Thus, to predict population consequences of harvest-induced selection in wild populations, it is critical to integrate both hunting intensity and regulation, especially if hunting selectivity targets female reproductive strategies.

GPS collars have an apparent positive effect on the survival of a large carnivore.

Are instrumented animals representative of the population, given the potential bias caused by selective sampling and the influence of capture, handling and wearing bio-loggers? The answer is elusive owing to the challenges of obtaining comparable data from individuals with and without bio-loggers. Using non-invasive genetic data of a large carnivore, the wolverine (Gulo gulo) in Scandinavia, and an open-population spatial capture-recapture model, we found a 16 (credible interval: 4-30) percentage points lower mortality probability for GPS-collared individuals compared with individuals without GPS collars. While the risk of dying from legal culling was comparable for collared and non-collared wolverines, the former experienced lower probability of mortality due to causes other than legal culling. The aforementioned effect was pronounced despite a potentially lower age-and therefore likely higher natural mortality-of collared individuals. Reports of positive effects of bio-loggers on the survival of individuals are uncommon and we argue that GPS collars could shield animals from poaching. Our results highlight the challenges of drawing population-level inferences for populations subjected to poaching when using data from instrumented individuals.

Identifying priority landscapes for conservation of snow leopards in Pakistan.

Pakistan's total estimated snow leopard habitat is about 80,000 km2 of which about half is considered prime habitat. However, this preliminary demarcation was not always in close agreement with the actual distribution-the discrepancy may be huge at the local and regional level. Recent technological developments like camera trapping and molecular genetics allow for collecting reliable presence records that could be used to construct realistic species distribution based on empirical data and advanced mathematical approaches like MaxEnt. The current study followed this approach to construct an accurate distribution of the species in Pakistan. Moreover, movement corridors, among different landscapes, were also identified through circuit theory. The probability of habitat suitability, generated from 98 presence points and 11 environmental variables, scored the snow leopard's assumed range in Pakistan, from 0 to 0.97. A large portion of the known range represented low-quality habitat, including areas in lower Chitral, Swat, Astore, and Kashmir. Conversely, Khunjerab, Misgar, Chapursan, Qurumber, Broghil, and Central Karakoram represented high-quality habitats. Variables with higher contributions in the MaxEnt model were precipitation during the driest month (34%), annual mean temperature (19.5%), mean diurnal range of temperature (9.8%), annual precipitation (9.4%), and river density (9.2). The model was validated through receiver operating characteristic (ROC) plots and defined thresholds. The average test AUC in Maxent for the replicate runs was 0.933 while the value of AUC by ROC curve calculated at 0.15 threshold was 1.00. These validation tests suggested a good model fit and strong predictive power. The connectivity analysis revealed that the population in the Hindukush landscape appears to be more connected with the population in Afghanistan as compared to other populations in Pakistan. Similarly, the Pamir-Karakoram population is better connected with China and Tajikistan, while the Himalayan population was connected with the population in India. Based on our findings we propose three model landscapes to be considered under the Global Snow Leopard Ecosystem Protection Program (GSLEP) agenda as regional priority areas, to safeguard the future of the snow leopard in Pakistan and the region. These landscapes fall within mountain ranges of the Himalaya, Hindu Kush and Karakoram-Pamir, respectively. We also identified gaps in the existing protected areas network and suggest new protected areas in Chitral and Gilgit-Baltistan to protect critical habitats of snow leopard in Pakistan.

Estimating and forecasting spatial population dynamics of apex predators using transnational genetic monitoring.

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.

Multiple observation processes in spatial capture-recapture models: How much do we gain?

Population monitoring data may originate from multiple methods and are often sparse and fraught with incomplete information due to practical and economic constraints. Models that can integrate multiple survey methods and are able to cope with incomplete data may help investigators exploit available information more thoroughly. Here, we developed an integrated spatial capture-recapture (SCR) model to incorporate multiple data sources with imperfect individual identification. We contrast inferences drawn from this model with alternate models incorporating only subsets of the data available. Using extensive simulations and an empirical example of multi-method brown bear (Ursus arctos) monitoring data from northern Pakistan, we quantified the benefits of including multiple sources of information in SCR models in terms of parameter precision and bias. Our multiple observation processes SCR model (MOP) yielded a more complete picture of the underlying processes, reduced bias, and led to more precise parameter estimates. Our results suggest that the greatest gains from integrated SCR models can be expected in situations where detection probability is low, a large proportion of detections is not attributable to individuals, and the degree of overlap between individual home ranges is low.

Silver spoon effects are constrained under extreme adult environmental conditions.

Early-life environmental conditions may generate cohort differences in individual fitness, subsequently affecting population growth rates. Three, nonmutually exclusive hypotheses predict the nature of these fitness differences: (1) silver spoon effects, where individuals born in good conditions perform better across the range of adult environments; (2) the "environmental saturation" hypothesis, where fitness differences only occur in intermediate adult environmental conditions; and (3) the "environmental matching" or "predictive adaptive response" (PAR) hypothesis, where fitness is highest when adult environmental conditions match those experienced in early life. We quantified the context-dependent effect of early-life environment on subsequent reproductive success, survival, and population growth rate (λ) of Svalbard reindeer, and explored how well it was explained by the three hypotheses. We found that good early-life conditions increased reproductive success compared to poor early-life conditions, but only when experiencing intermediate adult environmental conditions. This is the first example of what appears to be both "beneficial" and "detrimental environmental saturation" in a natural system. Despite weak early-life effects on survival, cohorts experiencing good early-life conditions contributed to higher population growth rates, when simulating realistic variation in adult environmental conditions. Our results show how the combination of a highly variable environment and biological constraints on fitness components can suppress silver spoon effects at both extremes of the adult environmental gradient.

Heritability of head size in a hunted large carnivore, the brown bear (Ursus arctos).

Wild animal populations experience selection pressures from both natural and anthropogenic sources. The availability of extensive pedigrees is increasing along with our ability to quantify the heritability and evolvability of phenotypic traits and thus the speed and potential for evolutionary change in wild populations. The environment may also affect gene expressions in individuals, which may in turn affect the potential of phenotypic traits to respond to selection. Knowledge about the relationship between the genetic and environmental components of phenotypic variation is particularly relevant, given ongoing anthropogenically driven global change. Using a quantitative genetic mixed model, we disentangled the genetic and environmental components of phenotypic variance in a large carnivore, the brown bear (Ursus arctos). We combined a pedigree covering ~1,500 individual bears over seven generations with location data from 413 bears, as well as data on bear density, habitat characteristics, and climatic conditions. We found a narrow-sense heritability of 0.24 (95% CrI: 0.06-0.38) for brown bear head size, showing that the trait can respond to selection at a moderate speed. The environment contributed substantially to phenotypic variation, and we partitioned this into birth year (5.9%), nonadditive among-individual genetic (15.0%), and residual (50.4%) environmental effects. Brown bear head circumference showed an evolvability of 0.2%, which can generate large changes in the trait mean over some hundreds of generations. Our study is among the first to quantify heritability of a trait in a hunted large carnivore population. Such knowledge about the degree to which species experiencing hunting can respond to selection is crucial for conservation and to make informed management decisions. We show that including important environmental variables when analyzing heritability is key to understanding the dynamics of the evolutionary potential of phenotypic traits.