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In the Adirondack Park region of northern New York, USA, white-tailed deer (Odocoileus virginianus) and moose (Alces alces) co-occur along a temperate-boreal forest ecotone. In this region, moose exist as a small and vulnerable low-density population and over-browsing by white-tailed deer is known to reduce regeneration, sustainability, and health of forests. Here, we assess the distribution and abundance of white-tailed deer at a broad spatial scale relevant for deer and moose management in northern New York. We used density surface modeling (DSM) under a conventional distance sampling framework, tied to a winter aerial survey, to create a spatially explicit estimate of white-tailed deer abundance and density across a vast, northern forest region. We estimated 16,352 white-tailed deer (95% CI 11,762–22,734) throughout the Adirondack Park with local density ranging between 0.00–5.73 deer/km2. Most of the Adirondack Park (91.2%) supported white-tailed deer densities of ≤2 individuals/km2. White-tailed deer density increased with increasing proximity to anthropogenic land cover such as timber cuts, roads, and agriculture and decreased in areas with increasing elevation and days with snow cover. We conclude that climate change will be more favorable for white-tailed deer than for moose because milder winters and increased growing seasons will likely have a pronounced influence on deer abundance and distribution across the Adirondack Park. Therefore, identifying specific environmental conditions facilitating the expansion of white-tailed deer into areas with low-density moose populations can assist managers in anticipating potential changes in ungulate distribution and abundance and to develop appropriate management actions to mitigate negative consequences such as disease spread and increased competition for limiting resources.

White‐nose syndrome (WNS), caused by the fungal pathogen Pseudogymnoascus destructans (Pd), has driven alarming declines in North American hibernating bats, such as little brown bat (Myotis lucifugus). During hibernation, infected little brown bats are able to initiate anti‐Pd immune responses, indicating pathogen‐mediated selection on the major histocompatibility complex (MHC) genes. However, such immune responses may not be protective as they interrupt torpor, elevate energy costs, and potentially lead to higher mortality rates. To assess whether WNS drives selection on MHC genes, we compared the MHC DRB gene in little brown bats pre‐ (Wisconsin) and post‐ (Michigan, New York, Vermont, and Pennsylvania) WNS (detection spanning 2014–2015). We genotyped 131 individuals and found 45 nucleotide alleles (27 amino acid alleles) indicating a maximum of 3 loci (1–5 alleles per individual). We observed high allelic admixture and a lack of genetic differentiation both among sampling sites and between pre‐ and post‐WNS populations, indicating no signal of selection on MHC genes. However, post‐WNS populations exhibited decreased allelic richness, reflecting effects from bottleneck and drift following rapid population declines. We propose that mechanisms other than adaptive immunity are more likely driving current persistence of little brown bats in affected regions., We tested the hypothesis of white‐nose syndrome (WNS) selection on MHC genes of hibernating bats by comparing the MHC class II DRB gene in little brown bats sampled from sites having different exposure histories to Pd, the fungus that caused WNS. We compared the WNS‐naive population in Wisconsin and the multi‐year post‐WNS population in New York and Vermont and found similar MHC variation, including the same most common alleles, comparable allelic diversity, and insufficient genetic differentiation, all indicating the lack of WNS selection on MHC genes. Our results indicated that the studied little brown bat populations may not rely on adaptive immunity to persist under WNS, and other mechanisms such as the physiological and behavioral changes found in recent studies may be more effective under WNS.

Human–carnivore conflict (HCC) represents one of the greatest threats to rural livelihoods and the persistence of large carnivores. The application of aversive conditioning, the association of unpleasant stimuli with the occurrence of unwanted behaviors, to mitigate HCC has achieved mixed results within and across species, making a better understanding of the factors driving intervention success critical to inform management practices. We explored the degree to which the chasing of African lions (Panthera leo) out of no tolerance zones conditions lion behavior to reduce their rate of return into community lands or rate of repeated livestock killing, providing evidence‐based understanding of program outcomes. We used data from 15 global positioning system (GPS)‐collared lions adjacent to Hwange National Park, Zimbabwe, with each lion receiving 0–17 conditioning treatments, and analyzed the data using recurrent event survival analysis and logistic regression. Chases were most successful (i.e., lion pushed out of the no tolerance zone by sunrise of the following day) in the dry season (i.e., when wild prey were more predictable), in areas closer to the park, and for individuals from smaller and more stable prides (i.e., had not lost a pride male within six months). Adult females and subadult males were more likely than adult males to reenter community lands, and subadult males were most likely to repeatedly depredate livestock. While livestock depredation has decreased since program initiation, the individuals in this study were overall not less likely to enter community lands or depredate livestock in response to chases when chases were considered isolated events. Rather, it was the consistency of deterrence events that proved most important in reducing livestock depredations, likely because of a stronger reinforcement between the undesired behavior and the negative stimulus. However, lions that had previously habitually killed livestock had greater depredation rates even after several conditioning treatments. Aversive conditioning holds promise in the management of carnivores that depredate livestock, but intervention must be consistent, ideally early in the development of problem behaviors, to maximize intervention effectiveness. Methods that separate wildlife from people (i.e., fencing, livestock enclosure fortification), in combination with aversive conditioning, may be needed to provide a sustainable, long‐term solution.

A common yet largely untested assumption in the theory of animal movements is that increased rates and a wider range of movements, such as occurs during breeding, make animals more vulnerable to mortality. We examined mortality among 34 white-tailed deer (Odocoileus virginianus) wearing GPS collars during the autumn breeding season of 2006 and 2007 in a heavily hunted, forest-agricultural landscape of central New York state. We evaluated whether individuals having higher rates of movement incurred higher rates of mortality and whether mortality risk was higher when deer were in less familiar areas. We used a Cox proportional hazards model to analyze how mortality risk changes with movement rates measured over 3 time periods: < 1 day, up to 2 weeks prior to death, and 3–4 weeks prior to death. Overall, deer increased their movement rates as autumn progressed, males more so than females. However, deer that died moved at a slower rate relative to surviving deer up to 2 weeks prior to death (β = −2.22 ± 0.81; 95% confidence interval [CI] = −3.91 to −0.51) and a slower rate on their day of death compared to deer that survived (β = −1.77 ± 0.73; 95% CI = −3.19 to −0.33). Site familiarity was not significantly related to mortality risk. Deer were equally likely to die within their 50% core use area as elsewhere within their autumn home range. We hypothesize that increased sociality associated with breeding may make animals more vulnerable to harvest mortality. Our findings contradict general assumptions about the influences of movement behavior on mortality risk, suggesting that patterns may be sensitive to the spatiotemporal context of the movement analysis.

Evaluating range-wide habitat use by a target species requires information on species occurrence over broad geographic regions, a process made difficult by species rarity, large spatiotemporal sampling domains, and imperfect detection. We address these challenges in an assessment of habitat use for jaguars (Panthera onca) outside protected areas in Central America. Occurrence records were acquired within 12 putative corridors using interviews with knowledgeable corridor residents. We developed a Bayesian hierarchical occupancy model to gain robust inference, allowing for heterogeneity introduced in the sampling process over space and time, using records of jaguar occurrence prone to false positives and false negatives. Probability of false detection of jaguars increased with the number of interviews conducted per unit (from 5.42% to 7.74% given

Summary Atlas data provide biodiversity information at a relatively fine spatial grain over a broad spatial extent and, increasingly, at multiple points in time, which make them invaluable for understanding processes that affect species distributions over time. The effect of survey effort on species detection has long been appreciated and Atlases typically include survey standards and records of effort, but challenges remain in analysing Atlas data that have not been collected using a repeated sampling protocol designed to correct for imperfect detection. We developed a single-visit dynamic occupancy model to quantify the effects of climatic and land-use drivers on local species extinction and colonization while accounting for imperfect detection using repeat Atlas data. We evaluated model stability using data simulated under alternative scenarios and, ultimately, applied the model to empirical data for Canada warbler Cardellina canadensis, a wide-spread species exhibiting a long-term population decline. At sample sizes that are realistic for many Atlases (n = 1000–10 000 independent survey blocks), our models produced unbiased estimates of detection, occupancy, colonization and extinction parameters. Slope estimates for explanatory covariates were somewhat less stable than overall occupancy, colonization and extinction rates, with covariate effects being sensitive to the total number of, and relationships among, explanatory variables. In comparison to other analyses of Canada warbler distributions that indicated minor changes over time, our approach identified a widespread decline in occupancy probability across New York, consistent with the broader population trend, particularly in the areas where it was initially more likely to occur. Synthesis and applications. A single-visit dynamic occupancy model is a novel method for analysing common, ecologically valuable datasets, such as Atlases, that lack repeated sampling necessary to correct for imperfect detection using alternative multi-season occupancy modelling approaches. As a result, using this method can improve understanding of species distributions and factors that shape them over time, thereby providing more accurate information to guide conservation and management.

Overexploitation is a frequently cited driver of species extinction. Throughout the Neotropics, balancing traditional practices and the needs of local people with protection of rare or declining species is challenging, especially given low capacity for control by authorities. We conducted interviews with wildlife professionals and residents, along with a camera-based field survey of wildlife occurrence, to gain insight into recent population trends, relative abundance, and drivers of harvest for large mammals in the northern Dry Chaco of Paraguay including but not limited to, Defensores del Chaco National Park. Although the endangered Chacoan peccary (Catagonus wagneri) was preferred regardless of hunter motivation, harvests of all species appeared largely opportunistic, and limited to immediate family use due to a lack of market forces, and constraints on refrigeration capacity in the region. This pattern may soon change given rapid deforestation, and an associated and growing road network providing greater access both to wildlife resources and commercial bushmeat markets. Notably, public perception of abundance and trends for Chacoan peccary differed from professional opinions—likely due in part to greater use of areas along roads by C. wagneri compared to other, relatively more abundant species. This discordance may pose future challenges if harvest restrictions become a conservation necessity, especially during a process of essentially self-imposed voluntary limitations.

Infanticide is an antagonistic behavior that may provide an evolutionary benefit for the perpetrator. Cases of infanticide have rarely been reported in Neotropical carnivores. The objective of this study was to provide empirical evidence of infanticide in a local jaguar (Panthera onca) population in the Brazilian Pantanal. We present infanticide data from opportunistic sampling. Each month, from 2013 to 2015, we monitored pastures for evidence of livestock carcasses. A remotely triggered camera trap was placed at encountered fresh cattle carcasses. Through this monitoring, two cases of infanticide were recorded. Both cases occurred in close proximity to a cattle carcass, a large prey item that may attract multiple jaguars—including females with cubs around age of weaning—and increase the risk of infanticide. Our observations provide new empirical evidence of jaguar social behavior and intraspecific competitive interactions, potentially driven by locally high population density and resource provision.

Understanding how individual movement scales with body size is of fundamental importance in predicting ecological relationships for diverse species. One-dimensional movement metrics scale consistently with body size yet vary over different temporal scales. Knowing how temporal scale influences the relationship between animal body size and movement would better inform hypotheses about the efficiency of foraging behaviour, the ontogeny of energy budgets, and numerous life-history trade-offs. We investigated how the temporal scaling of allometric patterns in movement varies over the course of a year, specifically during periods of motivated (directional and fast movement) and unmotivated (stationary and tortuous movement) behaviour. We focused on a recently diverged group of species that displays wide variation in movement behaviour - giant Galapagos tortoises (Chelonoidis spp.) - to test how movement metrics estimated on a monthly basis scaled with body size. We used state-space modelling to estimate seven different movement metrics of Galapagos tortoises. We used log-log regression of the power law to evaluate allometric scaling for these movement metrics and contrasted relationships by species and sex. Allometric scaling of movement was more apparent during motivated periods of movement. During this period, allometry was revealed at multiple temporal intervals (hourly, daily and monthly), with values observed at daily and monthly intervals corresponding most closely to the expected one-fourth scaling coefficient, albeit with wide credible intervals. We further detected differences in the magnitude of scaling among taxa uncoupled from observed differences in the temporal structuring of their movement rates. Our results indicate that the definition of temporal scales is fundamental to the detection of allometry of movement and should be given more attention in movement studies. Our approach not only provides new conceptual insights into temporal attributes in one-dimensional scaling of movement, but also generates valuable insights into the movement ecology of iconic yet poorly understood Galapagos giant tortoises.

To understand how migratory behavior evolved and to predict how migratory species will respond to global environmental change it is important to quantify the fitness consequences of intra- and inter-individual variation in migratory behavior. Intra-individual variation includes behavioral responses to changing environmental conditions and hence behavioral plasticity in the context of novel or variable conditions. Inter-individual variation determines the degree of variation on which selection can act and the rate of evolutionary responses to changes in average and extreme environmental conditions. Here we focus on variation in the partial migratory behavior of giant Galapagos tortoises (Chelonoidis spp.) and its energetic consequences. We evaluate the extent and mechanisms by which tortoises adjust migration timing in response to varying annual environmental conditions, and integrate movement data within a bioenergetic model of tortoise migration to quantify the fitness consequences of migration timing. We find strong inter-individual variation in the timing of migration, which was not affected by environmental conditions prevailing at the time of migration but rather by average expectations estimated from multi-annual averaged conditions. This variation is associated with an average annual loss in efficiency of ~15% relative to optimal timing based on year-specific conditions. These results point towards a limited ability of tortoises to adjust the timing of their migrations based on prevailing (and, by extension, future) conditions, suggesting that the adaptability of tortoise migratory behavior to changing conditions is predicated more by past "normal" conditions than responses to prevailing, changing conditions. Our work offers insights into the level of environmental-tuning in migratory behavior and a general framework for future research across taxa.

Establishing protected areas, where human activities and land cover changes are restricted, is among the most widely used strategies for biodiversity conservation. This practice is based on the assumption that protected areas buffer species from processes that drive extinction. However, protected areas can maintain biodiversity in the face of climate change and subsequent shifts in distributions have been questioned. We evaluated the degree to which protected areas influenced colonization and extinction patterns of 97 avian species over 20 years in the northeastern United States. We fitted single-visit dynamic occupancy models to data from Breeding Bird Atlases to quantify the magnitude of the effect of drivers of local colonization and extinction (e.g., climate, land cover, and amount of protected area) in heterogeneous landscapes that varied in the amount of area under protection. Colonization and extinction probabilities improved as the amount of protected area increased, but these effects were conditional on landscape context and species characteristics. In this forest-dominated region, benefits of additional land protection were greatest when both forest cover in a grid square and amount of protected area in neighboring grid squares were low. Effects did not vary with species' migratory habit or conservation status. Increasing the amounts of land protection benefitted the range margins species but not the core range species. The greatest improvements in colonization and extinction rates accrued for forest birds relative to open-habitat or generalist species. Overall, protected areas stemmed extinction more than they promoted colonization. Our results indicate that land protection remains a viable conservation strategy despite changing habitat and climate, as protected areas both reduce the risk of local extinction and facilitate movement into new areas. Our findings suggest conservation in the face of climate change favors creation of new protected areas over enlarging existing ones as the optimal strategy to reduce extinction and provide stepping stones for the greatest number of species.Valor de las Áreas Protegidas para la Persistencia de Aves a lo largo de 20 Años de Cambio Climático y Cambios en el Uso de Suelo Resumen El establecimiento de áreas protegidas, donde las actividades humanas y los cambios en la cobertura de suelo están restringidos, es una de las estrategias más utilizadas para la conservación de la biodiversidad. Esta práctica está basada en la suposición de que las áreas protegidas guarecen a las especies de los procesos que ocasionan la extinción. Sin embargo, se ha cuestionado si las áreas protegidas pueden mantener la biodiversidad de cara al cambio climático y los cambios subsecuentes en su distribución. Evaluamos el grado al cual las áreas protegidas influyeron sobre los patrones de colonización y extinción de 97 especies de aves durante 20 años en el noreste de los Estados Unidos. Ajustamos los modelos de ocupación dinámica de visita única a los datos de los Atlas de Aves Reproductoras para cuantificar la magnitud del efecto de los causantes de colonización y extinción local (p. ej.: clima, cobertura de suelo, tamaño del área protegida) en paisajes heterogéneos que variaron en cantidad de área bajo protección. Las probabilidades de colonización y extinción mejoraron conforme aumentó el tamaño del área protegida, pero estos efectos fueron condicionales con respecto al contexto del paisaje y a las características de la especie. En esta región dominada por bosques, los beneficios de una protección adicional del suelo fueron mayores cuando la cobertura de bosque en una cuadrícula y el tamaño del área protegida en una cuadrícula adyacente fueron bajos. Los efectos no variaron acorde a los hábitos migratorios o al estado de conservación de la especie. El aumento en la cantidad de suelo protegido benefició a las especies en los márgenes de su extensión pero no en la extensión nuclear de la especie. La mayores mejorías en la colonización y en las tasas de extinción se acumularon para las aves de bosque en relación con especies generalistas o de hábitat abierto. En general, las áreas protegidas frenaron la extinción más veces de las que promovieron la colonización. Nuestros resultados indican que la protección de suelo permanece como una estrategia viable de conservación a pesar del cambio que existe en los hábitats y en el clima ya que las áreas protegidas reducen el riesgo de extinción local y facilitan el movimiento hacia zonas nuevas. Nuestros hallazgos sugieren que la conservación de cara al cambio climático favorece la creación de nuevas áreas protegidas por encima del aumento de las ya existentes como la estrategia óptima para reducir la extinción y proporcionar escalones para el mayor número de especies.建立限制人类活动和土地覆盖变化的保护地是生物多样性保护最常用的策略之一。这一策略基于一种假设, 即保护地缓冲了导致物种灭绝的过程。然而, 在气候变化及其引起的物种分布变化的情况下, 保护地是否能维持生物多样性仍存在争议。我们评估了二十年来美国东北部的保护地对 97 种鸟类定殖和灭绝格局的影响情况。我们将单次调查的动态占有模型与繁殖鸟类图谱的数据进行拟合, 来定量受保护面积不同的异质性景观中, 导致局部定殖和灭绝的因素 (如气候、土地覆盖、保护地面积) 的影响程度。随着保护地面积增加, 定殖和灭绝的可能性也有所提高, 但这些影响可能取决于景观环境和物种特性。在以森林为主的研究区域内, 当一个网格的森林覆盖和周围网格的保护地面积都很小时, 增加土地保护带来的效益最高。另外, 物种受到的影响与其迁徙习性或保护现状无关。扩大土地保护面积有利于保护该区域边缘分布的物种, 而不是核心范围的物种。森林鸟种相比于开放生境或广生性的物种, 定殖率和灭绝率得到最大改善。总的来说, 保护地阻止灭绝的作用大于促进定殖。我们的研究结果显示, 尽管生境和气候在发生变化, 土地保护仍然是一个可行的保护策略, 因为保护地既能降低局部灭绝的风险, 又能促进物种迁入新区域。我们的发现还表明, 在气候变化面前, 设立新的保护地比扩大已有保护地更有利于保护, 是减少物种灭绝、为更多物种提供踏脚石的最佳策略。 【翻译: 胡怡思; 审校: 聂永刚】.

Animal movement strategies including migration, dispersal, nomadism, and residency are shaped by broad-scale spatial-temporal structuring of the environment, including factors such as the degrees of spatial variation, seasonality and inter-annual predictability. Animal movement strategies, in turn, interact with the characteristics of individuals and the local distribution of resources to determine local patterns of resource selection with complex and poorly understood implications for animal fitness. Here we present a multi-scale investigation of animal movement strategies and resource selection. We consider the degree to which spatial variation, seasonality, and inter-annual predictability in resources drive migration patterns among different taxa and how movement strategies in turn shape local resource selection patterns. We focus on adult Galapagos giant tortoises Chelonoidis spp. as a model system since they display many movement strategies and evolved in the absence of predators of adults. Specifically, our analysis is based on 63 individuals among four taxa tracked on three islands over six years and almost 106 tortoise re-locations. Tortoises displayed a continuum of movement strategies from migration to sedentarism that were linked to the spatio-temporal scale and predictability of resource distributions. Movement strategies shaped patterns of resource selection. Specifically, migratory individuals displayed stronger selection toward areas where resources were more predictable among years than did non-migratory individuals, which indicates a selective advantage for migrants in seasonally structured, more predictable environments. Our analytical framework combines large-scale predictions for movement strategies, based on environmental structuring, with finer-scale analysis of space-use. Integrating different organizational levels of analysis provides a deeper understanding of the eco-evolutionary dynamics at play in the emergence and maintenance of migration and the critical role of resource predictability. Our results highlight that assessing the potential benefits of differential behavioral responses first requires an understanding of the interactions among movement strategies, resource selection and individual characteristics. published

Distinguishing between non-native species that coexist with native species and those that threaten their persistence is critical for conservation and management. We investigated this distinction for a non-native terrestrial snail (Succinea sp.) (Sp. B) that occurs with the closely-related Chittenango ovate amber snail (Novisuccinea chittenangoensis) (COAS), an endangered species that is restricted to a single, known site. In 2008 and 2009, we performed ex situ competition experiments to examine the effects of density and body size of Sp. B on growth and mortality of COAS. We also conducted mark-recapture surveys from 2002 to 2009 to document trends of the in situ population of COAS and to identify spatio-temporal factors that may mitigate any competitive interactions between COAS and Sp. B. We observed lower growth rates and higher mortality rates of COAS at higher densities and larger sizes of Sp. B, indicating that the species compete. Nevertheless, population trends indicated that COAS population size was fluctuating but not in decline, and the spatial distribution, phenology, and size structure of each species indicated that there were enough mitigating factors to allow COAS to persist in the presence of Sp. B. Collectively, these results suggest that temporal niche partitioning resulting from a trade-off between growth and longevity of each species may enable their coexistence. Our results also suggest that control of Sp. B is unnecessary and, more generally, underscore the importance of conducting research aimed at understanding the effects of non-native species before instituting long-term, costly, and potentially unnecessary control measures.

As the use of short-rotation coppice willow crops increases, this vegetation type will comprise a greater extent of the landscape, yet its attendant effects on biodiversity remain poorly understood. In this study we characterized the avian and small mammal communities of willow crops that were established for phytoremediation and biomass production in industrial settling basins and compared these communities to those of surrounding areas of naturally-established perennial herbaceous-woody vegetation. Overall, we observed 33 bird species and five small mammal species in five focal sites (i.e., areas consisting of willow crops and adjacent vegetation) and 20 bird species and four small mammal species in two reference sites (i.e., areas of the settling basins without willow crops). For birds and small mammals, focal sites supported slightly greater average species richness and average abundances of all species combined than reference sites. Within focal sites, willow crops supported fewer species and similar combined abundances compared to adjacent areas. Importantly, community and individual species responses varied with the duration of time since coppicing. More small mammal species and individuals used willow crops in the year following coppicing because of their herbaceous undergrowth, while more birds tended to use older willow crops. Collectively, these results indicate that willow crops located within areas of perennial herbaceous-woody vegetation provide some benefits to bird and small mammal populations and that promoting a herbaceous layer in willow crops and maintaining multiple age classes of willows in the landscape simultaneously are likely to enhance the value of willow crops for biodiversity.

Human activities around parks can alter vegetation patterns within them, resulting in edge effects that degrade their ability to sustain ecological processes and support biodiversity. We quantified vegetation patterns and edge effects over a large geographic extent in Murchison Falls Conservation Area, Uganda, using freely available remotely sensed data. Over a 13-yr period, we quantified seasonal patterns in productivity using the Normalized Difference Vegetation Index (NDVI), comparing the park exterior, a boundary zone ≤10 km from the border inside the park, and the park interior. To identify the extent of edge effects, we further fit mixed models by vegetation type within 1-km bands within the boundary zone. Productivity was higher in the park interior than exterior in both wet and dry seasons, and in the wet season, it was also lower in the boundary zone than the interior. NDVI variability differed between seasons; it declined from exterior to interior in the wet season, but was highest in the boundary zone and similar between interior and exterior during the dry season. Within the boundary zone, edge effects varied by land cover type and extended 4–6 km into MFCA. Abrupt differences in vegetation patterns between the park and adjacent unprotected areas indicated a “hard edge” in this system. While hard edges are readily apparent, the subtle changes in productivity that extend into and degrade park systems are harder to detect. We demonstrated a low-cost and novel approach to detect such effects using readily available satellite imagery, which indicated human influence affecting 29–40% of the park. As human populations grow, parks will become further isolated, and measuring and managing edge effects may be crucial to achieving conservation objectives.

Little is known about the introduced European woodwasp, Sirex noctilio F. (Hymenoptera: Siricidae), and its hymenopteran parasitoid complex in North America. To assess within-tree and landscape-level densities and distributions of these insects, and develop a more cost effective approach for sampling and monitoring S. noctilio, 18 infested pines (12 P. resinosa Aiton and six P. sylvestris L.) were felled from six stands within three regions in central New York and cut into 0.5-m bolts. Bolts were carefully split to recover all siricids (S. noctilio and native siricids) and parasitoids. In total, 2,558 siricids were recovered; 1,972 siricid larvae and 586 teneral adult S. noctilio. Parasitism of siricids, a majority of which were S. noctilio based on larval rearing results, was 16.4% with Ibalia leucospoides ensiger Norton causing 10.7% of the documented mortality. Numbers of siricids and parasitoids declined 33-86% from the northern to the southern sampling regions, peak insect densities occurred in sections of the bole 15-19 cm in diameter and numbers of insects were generally higher in P. sylvestris than P. resinosa according to the highest ranked zero-inflated poisson and probit regression models. Bark thickness was not correlated with siricid or parasitoid species densities. We also describe sampling plans where as few as two 0.5-m samples from infested trees provided reliable within-tree insect densities.

Efforts in isolating the relative effects of resources and disturbances on animal-distribution patterns remain hindered by the difficulty of accounting for multiple scales of resource selection by animals with seasonally dynamic drivers. We developed multi-scale, seasonal models to explore how local resource selection by the threatened forest-dwelling woodland caribou (Rangifer tarandus caribou) was influenced by both broad-scale landscape context and local resource heterogeneity in the intensively managed region of Charlevoix, Quebec, Canada, located on the southern border of the North American caribou range. We estimated resource selection functions using 23 GPS-collared caribou monitored from 2004 to 2006 and landscape data on vegetation classes, terrain conditions, and roads. We found evidence of thresholds in road “proximity” effects (up to 1.25 km), which underscores the importance of including landscape context variables in addition to locally measured variables, and of fitting seasonal-specific models given temporal variation in the magnitude of selection and optimal scale of measurement. Open lichen woodlands were an important cover type for caribou during winter and spring, whereas deciduous forests, wetlands, and even young disturbed stands became important during calving and summer. Caribou consistently avoided roads and rugged terrain conditions at both local and landscape levels. Landscape context fundamentally constrains the choices available to animals, and we showed that failing to consider landscape context, or arbitrarily choosing an inappropriate scale for measuring covariates, may provide biased inferences with respect to habitat selection patterns. Effective habitat management for rare or declining species should carefully consider the hierarchical nature of habitat selection.

Models of habitat preference are widely used to quantify animal–habitat relationships, to describe and predict differential space use by animals, and to identify habitat that is important to an animal (i.e. that is assumed to influence fitness). Quantifying habitat preference involves the statistical comparison of samples of habitat use and availability. Preference is therefore contingent upon both of these samples. The inferences that can be made from use versus availability designs are influenced by subjectivity in defining what is available to the animal, the problem of quantifying the accessibility of available resources and the framework in which preference is modelled. Here, we describe these issues, document the conditional nature of preference and establish the limits of inferences that can be drawn from these analyses. We argue that preference is not interpretable as reflecting the intrinsic behavioural motivations of the animal, that estimates of preference are not directly comparable among different samples of availability and that preference is not necessarily correlated with the value of habitat to the animal. We also suggest that preference is context-dependent and that functional responses in preference resulting from changing availability are expected. We conclude by describing advances in analytical methods that begin to resolve these issues.

While the mechanistic links between animal movement and population dynamics are ecologically obvious, it is much less clear when knowledge of animal movement is a prerequisite for understanding and predicting population dynamics. GPS and other technologies enable detailed tracking of animal location concurrently with acquisition of landscape data and information on individual physiology. These tools can be used to refine our understanding of the mechanistic links between behaviour and individual condition through ‘spatially informed’ movement models where time allocation to different behaviours affects individual survival and reproduction. For some species, socially informed models that address the movements and average fitness of differently sized groups and how they are affected by fission–fusion processes at relevant temporal scales are required. Furthermore, as most animals revisit some places and avoid others based on their previous experiences, we foresee the incorporation of long-term memory and intention in movement models. The way animals move has important consequences for the degree of mixing that we expect to find both within a population and between individuals of different species. The mixing rate dictates the level of detail required by models to capture the influence of heterogeneity and the dynamics of intra- and interspecific interaction.

With the advent of new technologies, animal locations are being collected at ever finer spatio-temporal scales. We review analytical methods for dealing with correlated data in the context of resource selection, including post hoc variance inflation techniques, ‘two-stage’ approaches based on models fit to each individual, generalized estimating equations and hierarchical mixed-effects models. These methods are applicable to a wide range of correlated data problems, but can be difficult to apply and remain especially challenging for use–availability sampling designs because the correlation structure for combinations of used and available points are not likely to follow common parametric forms. We also review emerging approaches to studying habitat selection that use fine-scale temporal data to arrive at biologically based definitions of available habitat, while naturally accounting for autocorrelation by modelling animal movement between telemetry locations. Sophisticated analyses that explicitly model correlation rather than consider it a nuisance, like mixed effects and state-space models, offer potentially novel insights into the process of resource selection, but additional work is needed to make them more generally applicable to large datasets based on the use–availability designs. Until then, variance inflation techniques and two-stage approaches should offer pragmatic and flexible approaches to modelling correlated data.

Summary 1. The ecological footprint of a road may extend for several kilometres with overlapping effects from neighbouring roads causing a nonlinear accumulation of road effects in the landscape. Availability of preferred habitat, spatial dependencies between roads and habitat types, and fidelity to traditionally used areas further confound our ability to predict population-level responses of animals to growing road networks. 2. To isolate these effects, we developed an individually based movement model using elk Cervus elaphus L. as a model system. Empirically derived movement rules redistributed elk under different amounts of preferred habitat (clearcuts), road densities, and road development schemes. We tracked potential mortality risk (given time spent near roads) and emigration rates (given declining accessibility of foraging habitat). 3. Design of the road network accounted for up to 30‐55% difference in mortality risk and emigration rates, with the largest differences occurring at intermediate road densities (1‐1·5 km km ‐2 ) when road effects began to saturate the landscape. Maintaining roads in association with clearcuts caused a decline in habitat accessibility equivalent to replacing 50‐75% of these foraging patches with conifer forest. A nine-fold difference in potential emigration was observed after varying elk tolerance for declining habitat accessibility despite holding local movement biases constant. 4. Elk responses to growing road networks were non-linear, exposing thresholds for road density that were reflected in the home range occupancy patterns of a large sample of elk in the region. 5. Synthesis and applications . Our approach provides a means of scaling-up complex movement decisions to population-level redistribution, separating the confounding effects of landscape context from road effects, and exposing thresholds in connectivity and mortality risks for wildlife caused by infrastructure growth. Our model indicated that road densities ≤ 0·5 km km ‐2 yielded the highest probability of elk occurrence where elk were hunted (and sensitive to roads), but disassociating roads from foraging habitats or managing human access to roads may maintain effective elk habitat at substantially higher road densities.

To maximize success, reintroduction programs generally select predator-free release areas having high habitat quality. Past studies provide little insight into recovery efforts where multiple, potentially novel, mortality hazards occur. The ability of translocated animals to cope with novel environments can be affected by both pre- and postrelease experiences with habitat and mortality risks. We experimentally released elk (Cervus elaphus) having different background experiences into an area where predators and hunters were prevalent and habitat quality varied. Using a competing risks approach, we predicted the postrelease survival of individuals and their fidelity to release areas as a function of animal source and postrelease encounters with forage resources and areas used by wolves (Canis lupus) or humans. Mortality patterns were consistent with prerelease exposure to mortality risks but not habitat differences among source areas. Wolf predation, poaching, and legal Native hunting were equival...

1. Resource selection estimated by logistic regression is used increasingly in studies to identify critical resources for animal populations and to predict species occurrence. 2. Most frequently, individual animals are monitored and pooled to estimate population-level effects without regard to group or individual-level variation. Pooling assumes that both observations and their errors are independent, and resource selection is constant given individual variation in resource availability. 3. Although researchers have identified ways to minimize autocorrelation, variation between individuals caused by differences in selection or available resources, including functional responses in resource selection, have not been well addressed. 4. Here we review random-effects models and their application to resource selection modelling to overcome these common limitations. We present a simple case study of an analysis of resource selection by grizzly bears in the foothills of the Canadian Rocky Mountains with and without random effects. 5. Both categorical and continuous variables in the grizzly bear model differed in interpretation, both in statistical significance and coefficient sign, depending on how a random effect was included. We used a simulation approach to clarify the application of random effects under three common situations for telemetry studies: (a) discrepancies in sample sizes among individuals; (b) differences among individuals in selection where availability is constant; and (c) differences in availability with and without a functional response in resource selection. 6. We found that random intercepts accounted for unbalanced sample designs, and models with random intercepts and coefficients improved model fit given the variation in selection among individuals and functional responses in selection. Our empirical example and simulations demonstrate how including random effects in resource selection models can aid interpretation and address difficult assumptions limiting their generality. This approach will allow researchers to appropriately estimate marginal (population) and conditional (individual) responses, and account for complex grouping, unbalanced sample designs and autocorrelation.

In northern temperate environments, assessments of ungulate winter range in forested ecosystems commonly focus on measuring availability of browse because the dietary proportion of browse is typically high in winter. In many cases, these efforts ignore reductions in browse availability due to snow burial because this effect is difficult to measure. In this paper, we show how consideration of snow burial can alter the relative availability of browse in 6 forest communities common in the east slopes of the Rocky Mountains of the Alberta, Canada. We developed species-specific allometric relationships of stem diameter and woody twig biomass and height for the common shrub species and used these models to predict the decline in the proportion of total biomass/stem available to ungulates relative to stem height. Based on measures of stem densities, we then compared declines in browse availability for all browse species and for preferred browse species with increasing snow depths. Species compositional differences between forest types influenced the decline in browse availability as snow depth increased. Our stem-based approach is more flexible than previous plot-based approaches because it does not assume a distribution in stem heights but uses local information. Adjustments in browse availability are essential in habitat and food selection studies of ungulates where snow accumulates

Animals may respond to spatial and temporal heterogeneity by altering their movement patterns. The time an animal spends in an area of a given size is termed ȁ8first-passage timeȁ9 and can be used to identify the scales at which different movement processes occur. Using first-passage time and 2-h observations, we identified nested spatial scales representing three movement behaviours for elk (Cervus elaphus) – inactive/resting (moves

It is usually assumed that landscape heterogeneity influences animal movements, but understanding of such processes is limited. Understanding the effects of landscape heterogeneity on the movements of large herbivores such as North American elk is considered very important for their management. Most simulation studies on movements of large herbivores use predetermined behavioral rules based on empirical observations, or simply on what seems reasonable for animals to do. Here we did not impose movement rules but instead we considered that animals had higher fitness (hence better performance) when they managed to avoid predators, and when they acquired important fat reserves before winter. Individual decision-making was modeled with neural networks that received as input those variables suspected to be important in determining movement efficiency. Energetic gains and losses were tracked based on known physiological characteristics of ruminants. A genetic algorithm was used to improve the overall performance of the decision processes in different landscapes and ultimately to select certain movement behaviors. We found more variability in movement patterns in heterogeneous landscapes. Emergent properties of movement paths were concentration of activities in well-defined areas and an alternation between small, localized movement with larger, exploratory movements. Even though our simulated individuals moved shorter distances that actual elk, we found similarities in several aspects of their movement patterns such as in the distributions of distance moved and turning angles, and a tendency to return to previously visited areas.

Summary 1. Compared to traditional radio-collars, global positioning system (GPS) collars provide finer spatial resolution and collect locations across a broader range of spatial and temporal conditions. However, data from GPS collars are biased because vegetation and terrain interfere with the satellite signals necessary to acquire a location. Analyses of habitat selection generally proceed without correcting for this known sampling bias. We documented the effects of bias in resource selection functions (RSF) and compared the effectiveness of two bias-correction techniques. 2. The effects of environmental conditions on the probability of a GPS collar collecting a location were modelled for three brands of collar using data collected in 24-h trials at 194 test locations. The best-supported model was used to create GPS-biased data from unbiased animal locations. These data were used to assess the effects of bias given data losses in the range of 10‐40% at both 1- and 6-h sampling intensities. We compared the sign, value and significance of coefficients derived using biased and unbiased data. 3. With 6-h locations we observed type II error rates of 30‐40% given as little as a 10% data loss. Biased data also produced coefficients that were significantly more negative than unbiased estimates. Increasing the sampling intensity from 6- to 1-h locations eliminated type II errors but increased the magnitude of coefficient bias. No type I errors or changes in sign were observed. 4. We applied sample weighting and iterative simulation given a 30% data loss. For a biased vegetation type, simulation reduced more type II errors than weighting, most probably because the original sample size was re-established. However, selection for areas near trails, which was influenced by a biased vegetation type, showed fewer type II errors after weighting existing animal locations than after simulation. Both techniques corrected 100% and ≥ 80% of the biased coefficients at the 6- and 1-h sampling intensities, respectively. 5. Synthesis and applications. This study demonstrates that GPS error is predictable and biases the coefficients of resource selection models dependant upon the GPS sampling intensity and the level of data loss. We provide effective alternatives for correcting bias and discuss applying corrections under different sampling designs.

We employed stable carbon (δ(13)C) and nitrogen (δ(15)N) isotopes within a hypothetico-deductive framework to explore potential resource partitioning among terrestrial mammalian carnivores. Isotope values were acquired using guard hair samples from bobcat (Lynx rufus), coyote (Canis latrans), gray fox (Urocyon cinereoargenteus), and red fox (Vulpes vulpes) in the Adirondack Park, NY, USA. Enrichment along the δ(13)C axis was expected to reflect the use of human sources of food (reflecting a corn subsidy), and by extension tolerance for human-modified environments, whereas enrichment along the δ(15)N axis was expected to reflect a higher level of carnivory (i.e. amount of animal-based protein in the diet) - two mechanisms by which these now sympatric species may achieve a dynamic coexistence. Although bobcats were the only obligate carnivore, all four species shared a similar δ(15)N space. In contrast, bobcat had a lower and distinct δ(13)C signature compared to foxes, consistent with the a priori expectation of bobcats being the species least tolerant of human activities. Isotope signatures for coyotes, which colonized the region in the 1920s, overlapped all three native carnivores, bobcats the least, gray fox the most, indicating their potential competitive influence on this suite of native carnivores.

Data management, storage, curation, and dissemination are mainstays of computer modeling. Indeed, a traditional view of computer modeling has perpetuated the notion of “garbage in, garbage out” (GIGO), which serves as a constant reminder that, no matter how sophisticated the analysis, computers will “unquestioningly process” whatever type of data are provided regardless of its quality or suitability (Pearson 2007). In ecology, the datasets used in computer modeling are inherently complex and often characterized by missing values, dynamic environmental variables, and other factors leading to numerous data anomalies ( Michener et al. 1997; Michener and Brunt 2000). Ecologists have long recognized, however, that although data quality is undoubtedly important, using different types of data, even messy ones, can still prove informative, and facilitates new questions, methods, and synergies in science and society.

Artikkelen er en postprint av artikkelen utgitt i Philosophical Transactions of the Royal Society of London, Biological Sciences. Den publiserte versjonen av artikkelen kan du finne her: http://rstb.royalsocietypublishing.org/content/365/1550/2279.abstract Quantifying kill rates and sources of variation in kill rates remains an important challenge in linking predators to their prey. We address current approaches to using GPS-based movement data for quantifying key predation components of large carnivores. We review approaches to identify kill sites from GPS-movement data as a means to estimate kill rates and address advantages of using GPS-based data over past approaches. Despite considerable progress, modeling the probability that a cluster of GPS points is a kill site is no substitute for field visits but can guide our field efforts. Once kill sites are identified, time spent at a kill site (handling time) and time between kills (killing time) can be determined. We show how statistical models can be used to investigate the influence of factors such as animal characteristics (e.g., age, sex, group size) and landscape features on either handling time or killing efficiency. If we know the prey densities along paths to a kill, we can quantify the “attack success” parameter in functional response models directly. Problems remain in incorporating the behavioural complexity derived from GPS movement paths into functional response models, particularly in multi-prey systems, but we believe that exploring the details of GPS-movement data has put us on the right path.

Global positioning system (GPS) technologies collect unprecedented volumes of animal location data, providing ever greater insight into animal behaviour. Despite a certain degree of inherent imprecision and bias in GPS locations, little synthesis regarding the predominant causes of these errors, their implications for ecological analysis or solutions exists. Terrestrial deployments report 37 per cent or less non-random data loss and location precision 30 m or less on average, with canopy closure having the predominant effect, and animal behaviour interacting with local habitat conditions to affect errors in unpredictable ways. Home-range estimates appear generally robust to contemporary levels of location imprecision and bias, whereas movement paths and inferences of habitat selection may readily become misleading. There is a critical need for greater understanding of the additive or compounding effects of location imprecision, fix-rate bias, and, in the case of resource selection, map error on ecological insights. Technological advances will help, but at present analysts have a suite of ad hoc statistical corrections and modelling approaches available—tools that vary greatly in analytical complexity and utility. The success of these solutions depends critically on understanding the error-inducing mechanisms, and the biggest gap in our current understanding involves species-specific behavioural effects on GPS performance.

1. Resource selection estimated by logistic regression is used increasingly in studies to identify critical resources for animal populations and to predict species occurrence. 2. Most frequently, individual animals are monitored and pooled to estimate population-level effects without regard to group or individual-level variation. Pooling assumes that both observations and their errors are independent, and resource selection is constant given individual variation in resource availability. 3. Although researchers have identified ways to minimize autocorrelation, variation between individuals caused by differences in selection or available resources, including functional responses in resource selection, have not been well addressed. 4. Here we review random-effects models and their application to resource selection modelling to overcome these common limitations. We present a simple case study of an analysis of resource selection by grizzly bears in the foothills of the Canadian Rocky Mountains with and without random effects. 5. Both categorical and continuous variables in the grizzly bear model differed in interpretation, both in statistical significance and coefficient sign, depending on how a random effect was included. We used a simulation approach to clarify the application of random effects under three common situations for telemetry studies: (a) discrepancies in sample sizes among individuals; (b) differences among individuals in selection where availability is constant; and (c) differences in availability with and without a functional response in resource selection. 6. We found that random intercepts accounted for unbalanced sample designs, and models with random intercepts and coefficients improved model fit given the variation in selection among individuals and functional responses in selection. Our empirical example and simulations demonstrate how including random effects in resource selection models can aid interpretation and address difficult assumptions limiting their generality. This approach will allow researchers to appropriately estimate marginal (population) and conditional (individual) responses, and account for complex grouping, unbalanced sample designs and autocorrelation.