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Pathogen transmission depends on host density, mobility and contact. These components emerge from host and pathogen movements that themselves arise through interactions with the surrounding environment. The environment, the emergent host and pathogen movements, and the subsequent patterns of density, mobility and contact form an 'epidemiological landscape' connecting the environment to specific locations where transmissions occur. Conventionally, the epidemiological landscape has been described in terms of the geographical coordinates where hosts or pathogens are located. We advocate for an alternative approach that relates those locations to attributes of the local environment. Environmental descriptions can strengthen epidemiological forecasts by allowing for predictions even when local geographical data are not available. Environmental predictions are more accessible than ever thanks to new tools from movement ecology, and we introduce a 'movement-pathogen pace of life' heuristic to help identify aspects of movement that have the most influence on spatial epidemiology. By linking pathogen transmission directly to the environment, the epidemiological landscape offers an efficient path for using environmental information to inform models describing when and where transmission will occur.

Individual variation in habitat selection and movement behaviour is receiving growing attention, but primarily with respect to characterizing behaviours in different contexts as opposed to decomposing structure in behaviour within populations. This focus may be limiting advances in understanding the diversity of individual behaviour and its influence on population organization. We propose a framework for characterizing variation in space-use behaviour with the aim of advancing interpretation of its form and function. Using outputs from integrated step-selection analyses of 20 years of telemetry data from African elephants Loxodonta Africana, we developed four metrics characterizing differentiation in resource selection behaviour within a population (specialization [magnitude of the response independent of direction], heterogeneity [inter-individual variation], consistency [temporal shift in response] and reversal [frequency of directional changes in the response]). We contrasted insight from the developed metrics relative to the mean population response using an example focused on two covariates. We then expanded this contrast by evaluating if the metrics identify structurally important information on seasonal shifts in resource selection behaviours in addition to that provided by mean selection coefficients through principal component analyses (PCAs) and a random forest classification. The simplified example highlighted that for some covariates focusing on the population average failed to capture complex individual variation in behaviours. The PCAs revealed that the developed metrics provided additional information in explaining the patterns in elephant selection beyond that offered by population average covariate values. For elephants, specialization and heterogeneity were informative, with specialization often being a better descriptor of differences in seasonal resource selection behaviour than population average responses. Summarizing these metrics spatially and temporally, we illustrate how these metrics can provide insights on overlooked aspects of animal behaviour. Our work offers a new approach in how we conceptualize variation in space-use behaviour (i.e. habitat selection and movement) by providing ways of encapsulating variation that enables diagnoses of the drivers of individual-level variability in a population. The developed metrics explicitly distil how variation in a behaviour is structured among individuals and over time which could facilitate comparative work across time, populations or strata within populations.

Spatial behavior, including home-ranging behaviors, habitat selection, and movement, can be extremely informative in estimating how animals respond to landscape heterogeneity. Responses in these spatial behaviors to factors such as human modification and resources on the landscape can highlight a species’ spatial strategy to maximize fitness and minimize risk. These strategies can vary on spatial, temporal, and individual scales, and the combination of behaviors on these scales can lead to very different strategies among species. Harnessing the variation present at these scales, we developed a framework for predicting how species may respond to changes in their environments on a gradient ranging from generic, where a species exhibits broad-stroke spatial responses to their environment, to nuanced, in which a species uses a combination of temporal and spatial strategies paired with functional responses in selection behaviors. Using 46 GPS-tracked bobcats and coyotes inhabiting a landscape encompassing a range of human modification, we evaluated where each species falls along the generic-to-nuanced gradient. Bobcats and coyotes studied occupied opposite ends of this gradient, using different strategies in response to human modification in their home ranges, with bobcats broadly expanding their home range with increases in human modification and clearly selecting for or avoiding features on the landscape with temporal consistency. Meanwhile, coyotes did not expand their home ranges with human modification, but instead displayed temporal and spatial adjustments in their functional responses to human modification. These differences in response to habitat, resources, and risk between the two species highlighted the variation in spatial behaviors animals can use to exist in anthropogenic environments influenced by interspecific variation in behavioral plasticity. Categorizing animal spatial behavior based on the generic-to-nuanced gradient can help in predicting how a species will respond to future change based on their current spatial behavior.

Measuring climate change impacts on forest ecosystems can be challenging, as many of these changes are imperceptible within the typical time scale of short-term (e.g., 3–4 years) funding of research projects. Boreal trees are notoriously imperturbable, given their tolerance to harsh conditions and their adaptability. However, the buildup of decades of warming should now translate into measurable alterations of boreal ecosystem processes. The boreal forest is host to numerous northern animals; therefore, any change in boreal forest dynamics should affect wildlife. In this chapter, we aim to provide a nonexhaustive synthesis of documented impacts of climate change on selected key processes driving boreal forest ecosystem dynamics. We focus on the themes of plant and wildlife range shifts and stand growth and death, as they are keystone parameters of boreal forest ecosystem health that are symptomatic of climate change impacts on the boreal biota. For each theme, we introduce the general concepts and processes, convey some of the limitations of current assessments, and suggest future pressing challenges.

Ecologists increasingly recognize the importance of habitat selection as a multi-level, hierarchical process, but individual-level variation in selection patterns have yet to be fully evaluated within populations of large carnivores. We assessed jaguar (Panthera onca) selection of forest across seasonally variable forest availability in the Pantanal region of South America. Using resource selection functions (RSF), we evaluated the importance of forest cover for jaguars in a heterogeneous, dynamic landscape, and how seasonal variability in habitat availability influences habitat selection and predation patterns. A multi-level hierarchical analytical framework revealed that jaguars increasingly selected forest cover as availability of other habitats declined due to seasonal flooding. At the population range level, jaguars selected water, forest, and bushy grassland comparably during the dry season, and bushy grassland, forest, and flat grassland during the wet season. At the home range level, bushy grassland and forest were selected during both seasons. Jaguars killed prey animals with comparable frequency across forest, water, and bushy grasslands during the dry season, with more preference detected for forest and avoidance of grasslands. During the wet season, jaguars killed prey disproportionately to their availability in forest and bushy grasslands. These results clearly indicate that jaguars undergo marked dynamic shifts in habitat and kill site selection in response to seasonal flooding, with forest patches becoming more important as the availability of other habitats decreases. Land conservation efforts need to consider variability in jaguar-landscape dynamics associated with seasonal flooding, given increasing pressure to modify native landscapes to more open livestock grazing areas.

Canada lynx (Lynx canadensis) and snowshoe hares (Lepus americanus) form a keystone predator–prey cycle that has large impacts on the North American boreal forest vertebrate community. Snowshoe hares and lynx are both well-suited for snowy winters, but climate change-associated shifts in snow conditions could lower hare survival and alter cyclic dynamics. Using detailed monitoring of snowshoe hare cause-specific mortality, behaviour and prevailing weather, we demonstrate that hare mortality risk is strongly influenced by variation in snow conditions. Although predation risk from lynx was largely unaffected by snow conditions, coyote (Canis latrans) predation increased in shallow snow. Maximum snow depth in our study area has decreased 33% over the last two decades and predictions based on prolonged shallow snow indicate that future hare survival could resemble that seen during population declines. Our results indicate that climate change could disrupt cyclic dynamics in the boreal forest. Monitoring of snowshoe hare (Lepus americanus) cause-specific mortality and behaviour reveals increased risk of predation from coyote (Canis latrans) in shallow snow. This could disrupt the keystone Canada lynx (Lynx canadensis)–hare predator–prey cycle in North American boreal forests.

Landscape planning that ensures the ecological integrity of ecosystems is critical in the face of rapid human-driven habitat conversion and development pressure. Wildlife tracking data provide unique and valuable information on animal distribution and location-specific behaviors that can serve to increase the efficacy of such planning. Given the spatiotemporal complexity inherent to animal movements, the interaction between movement behavior and a location is often oversimplified in commonly applied analyses of tracking data. We analyzed GPS-tracking-derived metrics of intensity of use, structural properties (based on network theory), and properties of the movement path (speed and directionality) with machine learning to define homogeneous spatial movement types. We applied our approach to a long-term tracking data set of over 130 African elephants (Loxodonta africana) in an area under pressure from infrastructure development. We identified 5 unique location-specific movement categories displayed by elephants, generally defined as high, medium, and low use intensity, and 2 types of connectivity corridors associated with fast and slow movements. High-use and slow-movement corridors were associated with similar landscape characteristics associated with productive areas near water, whereas low-use and fast corridors were characterized by areas of low productivity farther from water. By combining information on intensity of use, properties of movement paths, and structural aspects of movement across the landscape, our approach provides an explicit definition of the functional role of areas for movement across the landscape that we term the movescape. This combined, high-resolution information regarding wildlife space use offers mechanistic information that can improve landscape planning.Caracterización del Paisaje de Movimiento para Identificar Hábitats y Corredores de Fauna Importantes Resumen La planeación de paisajes que asegura la integridad ecológica de los ecosistemas es muy importante de cara a la rápida conversión de hábitats llevada por la acción humana y la presión del desarrollo. Los datos de rastreo de fauna proporcionan información única y valiosa sobre la distribución animal y el comportamiento específico por localidad que puede servir para incrementar la eficiencia de dicha planeación. Dada la complejidad espaciotemporal inherente al movimiento animal, la interacción entre la conducta de movimiento y la ubicación con frecuencia se ve sobre simplificada en los análisis de información de rastreos aplicados comúnmente. Analizamos las medidas derivadas de rastreos por GPS de la intensidad de uso, las propiedades estructurales (basadas en la teoría de redes) y las propiedades de la vía de movimiento (velocidad y direccionalidad) con aprendizaje automatizado para definir los tipos de movimiento espacial homogéneo. Aplicamos nuestra estrategia a un conjunto de datos de rastreo a largo plazo de más de 130 elefantes africanos (Loxodonta africana) en un área bajo presión ocasionada por el desarrollo de infraestructura. Identificamos cinco categorías de movimiento específico por localidad exhibidas por los elefantes, definidas en términos generales como intensidad de uso alta, media y baja. También identificamos dos tipos de corredores de conectividad asociados con movimientos rápidos y lentos. Los corredores de intensidad de uso alta y movimiento lento estuvieron asociados con las características similares de paisaje asociadas a las áreas productivas cercanas a cuerpos de agua, mientras que los corredores de intensidad baja y movimiento rápido estuvieron caracterizados por áreas de baja productividad alejadas de los cuerpos de agua. Con la combinación de la información sobre la intensidad de uso, las propiedades de las vías de movimiento y los aspectos estructurales del movimiento a lo largo del paisaje, nuestra estrategia proporciona una definición explícita del papel funcional que tienen las áreas de movimiento en el paisaje, la cual denominamos paisaje de movimiento (movescape). Esta información combinada y de alta resolución con respecto al uso espacial por la fauna ofrece información mecánica que puede mejorar la planeación del paisaje.在人类驱动的栖息地快速转换和发展压力之下, 确保生态系统生态完整性的景观规划十分重要。野生动物追踪数据可以提供关于动物分布和特定位置行为的独特且有价值的信息, 有助于提高此类规划的有效性。考虑到动物运动固有的时空复杂性, 常用的追踪数据分析方法通常会过度简化运动行为和位置之间的相互作用。我们利用机器学习, 分析了基于 GPS 追踪数据的几个指标, 包括使用强度、结构特性 (基于网络理论) 和运动路径特性 (速度和方向), 以定义同质空间的运动类型。我们将该方法应用于一个长期追踪数据集, 该数据集来自一个受到基础设施建设压力地区的 130 多只非洲草原象 (Loxodonta africana) 。我们确定了大象展示出的五种独特的特定位置运动类型, 并定义为高、中、低使用强度, 还确定了快速、慢速运动的两种连接廊道。高使用强度和慢速运动的廊道有相似的景观特征, 与靠近水源、生产力高的区域相联系, 而低使用强度和快速运动的廊道则以远离水源、生产力低的区域为特征。我们的方法结合了使用强度、运动路径特征和跨景观运动的结构特征, 为跨景观运动区域的功能提供了明确的定义, 我们称之为 “movescape” 。以上这些关于野生动物空间利用的高分辨率综合信息为改进景观规划提供了机理信息。【翻译: 胡怡思; 审校: 聂永刚】.

Oral baiting is used to deliver vaccines to wildlife to prevent, control, and eliminate infectious diseases. A central challenge is how to spatially distribute baits to maximize encounters by target animal populations, particularly in urban and suburban areas where wildlife such as raccoons (Procyon lotor) are abundant and baits are delivered along roads. Methods from movement ecology that quantify movement and habitat selection could help to optimize baiting strategies by more effectively targeting wildlife populations across space. We developed a spatially explicit, individual-based model of raccoon movement and oral rabies vaccine seroconversion to examine whether and when baiting strategies that match raccoon movement patterns perform better than currently used baiting strategies in an oral rabies vaccination zone in greater Burlington, Vermont, USA. Habitat selection patterns estimated from locally radio-collared raccoons were used to parameterize movement simulations. We then used our simulations to estimate raccoon population rabies seroprevalence under currently used baiting strategies (actual baiting) relative to habitat selection-based baiting strategies (habitat baiting). We conducted simulations on the Burlington landscape and artificial landscapes that varied in heterogeneity relative to Burlington in the proportion and patch size of preferred habitats. We found that the benefits of habitat baiting strongly depended on the magnitude and variability of raccoon habitat selection and the degree of landscape heterogeneity within the baiting area. Habitat baiting improved seroprevalence over actual baiting for raccoons characterized as habitat specialists but not for raccoons that displayed weak habitat selection similar to radiocollared individuals, except when baits were delivered off roads where preferred habitat coverage and complexity was more pronounced. In contrast, in artificial landscapes with either more strongly juxtaposed favored habitats and/or higher proportions of favored habitats, habitat baiting performed better than actual baiting, even when raccoons displayed weak habitat preferences and where baiting was constrained to roads. Our results suggest that habitat selection-based baiting could increase raccoon population seroprevalence in urban-suburban areas, where practical, given the heterogeneity and availability of preferred habitat types in those areas. Our novel simulation approach provides a flexible framework to test alternative baiting strategies in multiclass landscapes to optimize bait-distribution strategies.

Environment drives the host movements that shape pathogen transmission through three mediating processes: host density, host mobility, and contact. These processes combine with pathogen life-history to give rise to an “epidemiological landscape” that determines spatial patterns of pathogen transmission. Yet despite its central role in transmission, strategies for predicting the epidemiological landscape from real-world data remain limited. Here, we develop the epidemiological landscape as an interface between movement ecology and spatial epidemiology. We propose a movement-pathogen pace-of-life heuristic for prioritizing the landscape’s central processes by positing that spatial dynamics for fast pace-of-life pathogens are best-approximated by the spatial ecology of host contacts; spatial dynamics for slower pace-of-life pathogens are best approximated by host densities; and spatial dynamics for pathogens with environmental reservoirs reflect a convolution of those densities with the spatial configuration of environmental reservoir sites. We then identify mechanisms that underpin the epidemiological landscape and match each mechanism to emerging tools from movement ecology. Finally, we outline workflows for describing the epidemiological landscape and using it to predict subsequent patterns of pathogen transmission. Our framework links transmission to environmental context, providing a scaffold for mechanistically understanding how environmental context can generate and shift existing patterns in spatial epidemiology.

Oral baiting is used to deliver vaccines to wildlife to prevent, control, and eliminate infectious diseases. A central challenge is how to spatially distribute baits to maximize encounters by target animal populations, particularly in urban and suburban areas where wildlife like raccoons (Procyon lotor) are abundant and baits are delivered along roads. Methods from movement ecology that quantify movement and habitat selection could help to optimize baiting strategies by more effectively targeting wildlife populations across space. We developed a spatially explicit, individual-based model of raccoon movement and oral rabies vaccine seroconversion to examine whether and when baiting strategies that match raccoon movement patterns perform better than currently employed baiting strategies in an oral rabies vaccination zone in greater Burlington, Vermont, USA. Habitat selection patterns estimated from locally radio-collared raccoons were used to parameterize movement simulations. We then used our simulations to estimate raccoon population rabies seroprevalence under currently used baiting strategies (actual baiting) relative to habitat selection-based baiting strategies (habitat baiting). We conducted simulations on the Burlington landscape and artificial landscapes that varied in heterogeneity relative to Burlington in the proportion and patch size of preferred habitats. We found that the benefits of habitat baiting strongly depended on the magnitude and variability of raccoon habitat selection and the degree of landscape heterogeneity within the baiting area. Habitat baiting improved seroprevalence over actual baiting for raccoons characterized as habitat specialists but not for raccoons that displayed weak habitat selection similar to radio-collared individuals—except when baits were delivered off roads where preferred habitat coverage and complexity was more pronounced. In contrast, in artificial landscapes with either more strongly juxtaposed favored habitats and/or higher proportions of favored habitats, habitat baiting performed better than actual baiting, even when raccoons displayed weak habitat preferences and where baiting was constrained to roads. Our results suggest that habitat selection-based baiting could increase raccoon population seroprevalence in urban-suburban areas, where practical, given the heterogeneity and availability of preferred habitat types in those areas. Our novel simulation approach provides a flexible framework to test alternative baiting strategies in multiclass landscapes to optimize bait distribution strategies.

Forecasting ecosystem response to climate change is critical for guiding policymaking but challenging due to: complicated relationships between microclimates and regional climates; species’ responses that are driven by extremes rather than averages; the multifaceted nature of species’ interactions; and the lack of historical analogs to future climates. Given these challenges, even model systems such as the Galapagos Islands, a world‐famous biodiversity hotspot and World Heritage Site, lack clear forecasts for future environmental change. Here, we developed a novel nonparametric method for simulating the ecosystem futures based on observed vegetation productivity (NDVI) during analogous weather observed historically. Using satellite images taken from the past to piece together a simulated future, we projected that productivity of terrestrial vegetation of the Galapagos will increase over the next century by approximately one standard deviation archipelago‐wide, with largest increases during the wet season (January to June) and in the arid zones. Such greening would impact a variety of ecological and evolutionary processes, species of conservation concern, and agricultural practices. Our straightforward approach can be applied to many other regions, particularly those with rapid ecosystem responses to stochastic inter‐annual climatic fluctuations that provide appropriate climate analogs for forecasting.

Increasing interest in the complexity, variation and drivers of movement-related behaviours promise new insight into fundamental components of ecology. Resolving the multidimensionality of spatially explicit behaviour remains a challenge for investigating tactics and their relation to niche construction, but high-resolution movement data are providing unprecedented understanding of the diversity of spatially explicit behaviours. We introduce a framework for investigating individual variation in movement-defined resource selection that integrates the behavioural and ecological niche concepts. We apply it to long-term tracking data of 115 African elephants (Loxodonta africana), illustrating how a behavioural hypervolume can be defined based on differences between individuals and their ecological settings, and applied to explore population heterogeneity. While normative movement behaviour is frequently used to characterise population behaviour, we demonstrate the value of leveraging heterogeneity in the behaviour to gain greater insight into population structure and the mechanisms driving space-use tactics.

Defining the relationship between nutrients and parasitism is complicated by shifts in host physiology and population density, which can both mediate the effects of host diet on parasites and vice versa. We examined the relationship between nutrient availability and an abundant parasite capable of both horizontal and vertical transmission (Hamiltosporidium tvaerminnensis) of a planktonic crustacean, Daphnia magna, in rock pools on Baltic Sea Skerry islands. We found that the relative availability of nutrients directly affected infection prevalence; parasite prevalence was higher in pools with higher particulate N:P ratios. Infection prevalence was not related to Daphnia population densities. A complementary experiment that examined host responses to an N:P gradient in mesocosms indicated that high N:P ratios can increase spore load in the hosts. We surmise that high N:P food increases Daphnia feeding rate, which increases their contact with parasite spores and leads to higher prevalence and more intense infections. We found no direct evidence that parasite-induced changes in host nutrient use affected nutrient dynamics in pools. However, the relationship between diet N:P and the parasite's prevalence and load is consistent with previously documented patterns of this parasite's effect on host nutrient use. Taken together, this study suggests that high N:P ratios in food may benefit the parasite in multiple ways and could create environments that favour horizontal transmission over vertical transmission for parasites capable of both transmission routes. If so, nutrient limitation could have long-term consequences for host-parasite evolution.

BACKGROUND Lethal removal of invasive species, such as wild pigs (Sus scrofa), is often the most efficient approach for reducing their negative impacts. Wild pigs are one of the most widespread and destructive invasive mammals in the USA. Lethal management techniques are a key approach for wild pigs and can alter wild pig spatial behavior, but it is unclear how wild pigs respond to the most common removal technique, trapping. We investigated the spatial behavior of wild pigs following intensive removal of conspecifics via trapping at three sites within the Savannah River Site, SC, USA. We evaluated changes in wild pig densities, estimated temporal shifts in home-range properties, and evaluated fine-scale movement responses of wild pigs to removal. RESULTS We observed a significant reduction in the density of wild pigs in one site following removal via trapping while a qualitative reduction was observed in another site. We found little evidence of shifts in pig home-ranging behavior following removal. However, we did observe a nuanced response in movement behavior of wild pigs to the removal at the scale of the GPS locations (4 h), including increased movement speed and reduced selection for vegetation rich areas. CONCLUSION Our work provides a better understanding of the impact of removal via trapping on wild pig movement and its implications for management. The lack of shift in home-range characteristics observed illustrates how targeted trapping could be used to provide temporary relief for species sensitive to wild pig consumption such as ground nesting birds or agricultural crops.

Network (graph) theory is a popular analytical framework to characterize the structure and dynamics among discrete objects and is particularly effective at identifying critical hubs and patterns of connectivity. The identification of such attributes is a fundamental objective of animal movement research, yet network theory has rarely been applied directly to animal relocation data. We develop an approach that allows the analysis of movement data using network theory by defining occupied pixels as nodes and connection among these pixels as edges. We first quantify node-level (local) metrics and graph-level (system) metrics on simulated movement trajectories to assess the ability of these metrics to pull out known properties in movement paths. We then apply our framework to empirical data from African elephants (Loxodonta africana), giant Galapagos tortoises (Chelonoidis spp.), and mule deer (Odocoileous hemionus). Our results indicate that certain node-level metrics, namely degree, weight, and betweenness, perform well in capturing local patterns of space use, such as the definition of core areas and paths used for inter-patch movement. These metrics were generally applicable across data sets, indicating their robustness to assumptions structuring analysis or strategies of movement. Other metrics capture local patterns effectively, but were sensitive to specified graph properties, indicating case specific applications. Our analysis indicates that graph-level metrics are unlikely to outperform other approaches for the categorization of general movement strategies (central place foraging, migration, nomadism). By identifying critical nodes, our approach provides a robust quantitative framework to identify local properties of space use that can be used to evaluate the effect of the loss of specific nodes on range wide connectivity. Our network approach is intuitive, and can be implemented across imperfectly sampled or large-scale data sets efficiently, providing a framework for conservationists to analyze movement data. Functions created for the analyses are available within the R package moveNT.

Movement influences a myriad of ecological processes operating at multiple spatial and temporal scales. Yet our understanding of animal movement is limited by the resolution of data that can be obtained from individuals. Traditional approaches implicitly assume that movement decisions are made at the spatial and temporal scales of observation, although this scale is typically an artifact of data-gathering technology rather than biological realism. To address this limitation, we used telemetry-based movement data for caribou (Rangifer tarandus) in Newfoundland, Canada, and compared movement decisions estimated at the temporal resolution of GPS relocations (2 hours) to a novel model describing directional movement to areas reachable over an extended period. We showed that this newer model is a better predictor of movement decisions by caribou, with decisions made at the scale of ~2 km, including the strong avoidance of dense coniferous forest, an outcome not detectable at the scale of GPS relocations. These results illustrate the complexity of factors affecting animal movement decisions and the analytical challenges associated with their interpretation. Our novel modelling framework will help support increased accuracy in predictive models of animal space-use, and thereby aid in determining biologically meaningful scales for collecting movement and habitat data. This article is protected by copyright. All rights reserved.

Restoration of damaged ecosystems through invasive species removal and native species conservation is an increasingly common practice in biodiversity conservation. Estimating the degree of ecosystem response attributable specifically to eradication of exotic herbivores versus restoration of native herbivores is often difficult and is complicated by concurrent temporal changes in other factors, especially climate. We investigated the interactive impacts of native mega-herbivores (giant tortoises) and the eradication of large alien herbivores (goats) on vegetation productivity across the Galapagos Archipelago. We examined archipelago-wide patterns of Normalized Difference Vegetation Index (NDVI) as a proxy for vegetation productivity between 2001 and 2015 and evaluated how goat and historical and current tortoise occurrence influenced productivity. We used a breakpoint analysis to detect change in trends in productivity from five targeted areas following goat eradication. We found a positive association between tortoise occurrence and vegetation productivity and a negative association with goat occurrence. We also documented an increase in plant productivity following goat removal with recovery higher in moister regions than in arid region, potentially indicating an alternate stable state has been created in the latter. Climate variation also contributed to the detected improvement in productivity following goat eradication, sometimes obscuring the effect of eradication but more usually magnifying it by up to 300%. Our work offers perspectives regarding the effectiveness and outcomes of eradicating introduced herbivores and re-introducing native herbivores, and the merits of staging them simultaneously in order to restore critical ecosystem processes such as vegetation productivity.

Poaching is the most immediate threat to African elephants (Loxodonta africana). Several continental‐wide surges in poaching have occurred since the latter half of the twentieth century, and the latest surge occurred from 2007 to 2012. The behavioral responses of elephants to poaching risk has not been studied widely because of a lack of high‐resolution movement data collected simultaneously with verified causes of mortality. We managed to collate 2 such datasets from 2004 to 2013. We studied the spatial‐temporal changes in movement behavior of 11 elephants in their core areas. Past studies have focused on elephant movement along corridors. We tested for the effect of poaching risk on their path straightness (i.e., tortuosity) while controlling for other environmental and human activities in the landscape using a set of generalized linear mixed models. To test for temporal variation of tortuosity, we used a time‐series linear model. Elephants turned less frequently while they were in poaching locations and at times with a high level of poaching activity, even though their speed did not change. The variation of tortuosity is a good indicator of differences in poaching risk as perceived by the elephants, which could complement patrol‐based anti‐poaching efforts by wildlife managers, especially in remote, inaccessible landscapes.

Individuals in substandard physical condition are predicted to be more vulnerable to predation. Support for this prediction is inconsistent partly as a result of differences across systems in the life histories of predator and prey species. Our objective was to examine the physical condition of woodland caribou Rangifer tarandus caribou calves depredated by two predators with different life histories in Newfoundland, Canada. Black bears Ursus americanus are capable of chasing calves at high speeds over short distances and primarily prey on calves

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.

De-extinction is becoming potentially feasible for restoring extinct species in the wild, but research is required to determine the likelihood of success in light of contemporary and future environmental change. We assessed 1900–2100 change in suitable climate and land cover in the historic range of Carolina parakeet (Conuropsis carolinensis), ivory-billed woodpecker (Campephilus principalis) and passenger pigeon (Ectopistes migratorius), in North America. Parakeet and woodpecker historic range currently remains climatically-favourable, but intensified land use has broadly reduced habitat in contemporary landscapes. For passenger pigeon, more substantive loss in climate and land cover suitability exists in both the historic full range and primary breeding range. Long-term climate and land cover projections suggest that improved habitat suitability and increased potential future distribution outside historic ranges are likely for each de-extinction candidate. While such changes could improve probability of success for de-extinction programs, extensive mismatch between historic and future habitat suitability highlights the potential risks of reviving species that may colonize novel geographic space. To date, potential long-term negative effects of de-extinction programs to ecosystems outside historic ranges have not been elucidated, making this a priority concern for any serious proposal. To address whether benefits of reinstating extinct species to historic ecosystems outweigh risks to extant species outside their historic range will require extensive ecological, social and economic analyses that extend beyond that conducted to-date for this potentially transformational conservation tool.

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.

Generalist predators typically have broad diets, but their diets may become constrained when one species of prey becomes disproportionately available. Yet there is poor understanding regarding whether generalist predators exhibit stereotypic relationships with pulsed prey resources. We used telemetry data from 959 woodland caribou (Rangifer tarandus caribou (Gmelin, 1788); 146 adult females, 813 calves), 61 coyotes (Canis latrans Say, 1823), and 55 black bears (Ursus americanus Pallas, 1780) to investigate how two generalist predators interacted with caribou neonates on the island of Newfoundland. We examined the similarity of patterns of habitat use between caribou and their predators across time and related this similarity to interspecific spatiotemporal co-occurrence and mortality risk for caribou neonates. The similarity in habitat use between coyotes and caribou mirrored variation in juvenile hazard risk, but had weak association with actual co-occurrence with caribou. Bears and caribou exhibited less similarity in habitat use during the calving season than coyotes and caribou. The relationship between habitat use of bear and caribou did not correspond with either co-occurrence patterns or overall risk for caribou neonates. Our work illustrates how risk for a prey species can be shaped differently based upon differences between the behavioural strategies of generalist predator species.

Ecological theory predicts that the intensity of antipredator responses is dependent upon the spatiotemporal context of predation risk (the risk allocation hypothesis). However, most studies to date have been conducted over small spatial extents, and did not fully take into account gradual responses to predator proximity. We simultaneously collected spatially explicit data on predator and prey to investigate acute responses of a threatened forest ungulate, the boreal caribou (Rangifer tarandus), to the spatiotemporal dynamics of wolf (Canis lupus) distribution during spring. Movement analysis of GPS-collared individuals from both species revealed high plasticity in habitat-selection decisions of caribou. Female caribou avoided open areas and deciduous forests and moved relatively fast and toward foraging areas when wolves were closer than 2.5 km. Caribou also avoided food-rich areas only when wolves were within 1 km. Our results bridge the gap between long-term perceived risk and immediate flight responses by revealing dynamic antipredator tactics in response to predator proximity.

Understanding spatiotemporal variability in prey accessibility is important for disentangling predator-prey interactions and is relevant to management interventions to reduce predation. Recently, caribou (Rangifer tarandus) in Newfoundland declined by 66%, with calf predation by black bears (Ursus americanus) implicated as a major proximate mechanism of the decline. Most predation occurs when calves are aggregated on calving grounds. We used telemetry data from 271 caribou and 45 black bears in 2 caribou herd ranges to examine spatial variability in calf accessibility, identify the distribution of potentially predatory bears, and assess the aggregative response of bears to the calf resource. We predicted whether a bear was a visitor to a calving ground during the calving season (a potentially predatory bear) based upon its sex, the herd range it occupied, its distance to the calving grounds, and the season. The distribution of potentially predatory bears and their degree of segregation from non-predatory bears varied seasonally. The probability of a bear visiting the calving grounds during calving decreased with increasing distance from the calving grounds, and was greater for males than for females in all seasons at distances beyond 2.4 km from the calving grounds. Residency time of bears increased in the calving grounds of 1 herd during calving, suggesting an aggregative response to neonates in that area. For both herds, the estimated distribution of potentially predatory bears was much larger than the calving grounds, illustrating that the relevant scale of predator-prey interactions may extend far beyond the area where lethal encounters occur. Our work highlights the value of examining spatiotemporal dynamics of predator movements prior to implementing ecosystem manipulations designed to reduce predation and provides a modeling framework that can be used to guide management interventions in systems with aggregated prey. © 2015 The Wildlife Society.

Peer review is pivotal to science and academia, as it represents a widely accepted strategy for ensuring quality control in scientific research. Yet, the peer-review system is poorly adapted to recent changes in the discipline and current societal needs. We provide historical context for the cultural lag that governs peer review that has eventually led to the system's current structural weaknesses (voluntary review, unstandardized review criteria, decentralized process). We argue that some current attempts to upgrade or otherwise modify the peer-review system are merely sticking-plaster solutions to these fundamental flaws, and therefore are unlikely to resolve them in the long term. We claim that for peer review to be relevant, effective, and contemporary with today's publishing demands across scientific disciplines, its main components need to be redesigned. We propose directional changes that are likely to improve the quality, rigour, and timeliness of peer review, and thereby ensure that this critical process serves the community it was created for.

Habitat selection is a multi-level, hierarchical process that should be a key component in the balance between food acquisition and predation risk avoidance (food–predation trade-off). However, to date, studies have not fully elucidated how fine- and broad-scale habitat decisions by individual prey can help balance food versus risk. We studied broad-scale habitat selection by Newfoundland caribou Rangifer tarandus, focusing on trade-offs between predation risk versus access to forage during the calving and post-calving period. We improved traditional measures of habitat availability by incorporating fine-scale movement patterns of caribou into the availability kernel, thus enabling separation of broad and fine scales of selection. Remote sensing and field surveys served to create a spatio-temporal model of forage availability, whereas GPS telemetry locations from 66 black bears Ursus americanus and 59 coyotes Canis latrans provided models of predation risk. We then used GPS telemetry locations from 114 female caribou to assess food–predation trade-offs through the prism of our refined model of caribou habitat availability. We noted that migratory movements of caribou were oriented mainly towards habitats with abundant forage and lower risk of bear and (to a lesser extent) coyote encounter. These findings were generally consistent across caribou herds and would not have been evident had we used traditional methods instead of our refined model when estimating habitat availability. We interpret these findings in the context of stereotypical migratory behaviour observed in Newfoundland caribou, which occurs despite the extirpation of wolves Canis lupus nearly a century ago. We submit that caribou are able to balance food acquisition against predation risk using a complex set of factors involving both finer and broader scale selection. Accordingly, our study provides a strong argument for using refined habitat availability estimates when assessing food–predation trade-offs.

Endangered red wolves (Canis rufus) receive intense conservation efforts in the United States, and to date, population recovery has been challenged by hybridization with closely related coyotes (C. latrans) and illegal human-caused mortality. Ongoing review of the red wolf program in the single recovery area in North Carolina prompted us to compare demography (survival, recruitment) and cause of death of red wolves and coyotes/hybrids. In most respects, canids had similar demographic rates, although sterilization was effective in controlling coyote reproduction. Comparison of previous (1999-2007) to contemporary (2009-2014) causes of death revealed that shooting mortality consistently accounted for ∼25% of wolf mortality. As evidenced by the lack of coyote deaths from strife with wolves, and stationary/declining wolf numbers during the last 15 years, current conditions are inadequate to establish a viable self-sustaining wolf population. Accordingly, the program review should determine whether: (1) banning coyote hunting will sufficiently benefit wolf survival or recruitment; (2) the wolf population should be considered conservation-reliant under revised recovery goals; or (3) the recovery program in North Carolina should be abandoned.

Summary There is a growing need for scientific synthesis in ecology and evolution. In many cases, meta-analytic techniques can be used to complement such synthesis. However, missing data are a serious problem for any synthetic efforts and can compromise the integrity of meta-analyses in these and other disciplines. Currently, the prevalence of missing data in meta-analytic data sets in ecology and the efficacy of different remedies for this problem have not been adequately quantified. We generated meta-analytic data sets based on literature reviews of experimental and observational data and found that missing data were prevalent in meta-analytic ecological data sets. We then tested the performance of complete case removal (a widely used method when data are missing) and multiple imputation (an alternative method for data recovery) and assessed model bias, precision and multimodel rankings under a variety of simulated conditions using published meta-regression data sets. We found that complete case removal led to biased and imprecise coefficient estimates and yielded poorly specified models. In contrast, multiple imputation provided unbiased parameter estimates with only a small loss in precision. The performance of multiple imputation, however, was dependent on the type of data missing. It performed best when missing values were weighting variables, but performance was mixed when missing values were predictor variables. Multiple imputation performed poorly when imputing raw data which were then used to calculate effect size and the weighting variable. We conclude that complete case removal should not be used in meta-regression and that multiple imputation has the potential to be an indispensable tool for meta-regression in ecology and evolution. However, we recommend that users assess the performance of multiple imputation by simulating missing data on a subset of their data before implementing it to recover actual missing data.

The recently diminished caribou (Rangifer tarandus) population in insular Newfoundland, Canada, has been severely limited by predation on newborn calves. These neonates are patchily distributed on the landscape; therefore, to adequately understand predator–prey interactions, the temporal and geographic extent of the distribution of caribou calves must be identified so that current areas with calves can be differentiated from areas without calves. We used telemetry locations of 309 caribou calves and 100 adult females from 4 herds, 2008– 2010, to estimate the spatiotemporal distribution of caribou calves during the time when they were most vulnerable to predation, to evaluate the predictability of the calf resource among years, and to assess the degree of aggregation during calving. Patterns of calf distribution were predictable in time and space from year to year, with an average distributional overlap of 68% between years. The dispersion of female caribou during calving varied among herds from highly aggregated (8% and 20% of herd range) to more dispersed (50–70% of herd range). Postcalving (up to 9 weeks) distributions also varied among herds; the 2 more-dispersed herds remained sedentary, whereas both highly aggregated herds migrated away from their calving grounds at the end of June. The most-aggregated herd remained so as it migrated from its calving ground, whereas the less-aggregated herd spread out and moved in a variety of predictable directions. Dispersion and movement patterns varied with forest cover; herds with less forest cover in their range were more aggregated and migratory than herds with more forest cover.

Wildlife tracking is one of the most frequently employed approaches to monitor and study wildlife populations. To date, the application of tracking data to applied objectives has focused largely on the intensity of use by an animal in a location or the type of habitat. While this has provided valuable insights and advanced spatial wildlife management, such interpretation of tracking data does not capture the complexity of spatio-temporal processes inherent to animal behaviour and represented in the movement path. Here, we discuss current and emerging approaches to estimate the behavioural value of spatial locations using movement data, focusing on the nexus of conservation behaviour and movement ecology that can amplify the application of animal tracking research to contemporary conservation challenges. We highlight the importance of applying behavioural ecological approaches to the analysis of tracking data and discuss the utility of comparative approaches, optimization theory and economic valuation to gain understanding of movement strategies and gauge population-level processes. First, we discuss innovations in the most fundamental movement-based valuation of landscapes, the intensity of use of a location, namely dissecting temporal dynamics in and means by which to weight the intensity of use. We then expand our discussion to three less common currencies for behavioural valuation of landscapes, namely the assessment of the functional (i.e. what an individual is doing at a location), structural (i.e. how a location relates to use of the broader landscape) and fitness (i.e. the return from using a location) value of a location. Strengthening the behavioural theoretical underpinnings of movement ecology research promises to provide a deeper, mechanistic understanding of animal movement that can lead to unprecedented insights into the interaction between landscapes and animal behaviour and advance the application of movement research to conservation challenges. This article is part of the theme issue ‘Linking behaviour to dynamics of populations and communities: application of novel approaches in behavioural ecology to conservation’.

Predicting space use patterns of animals from their interactions with the environment is fundamental for understanding the effect of habitat changes on ecosystem functioning. Recent attempts to address this problem have sought to unify resource selection analysis, where animal space use is derived from available habitat quality, and mechanistic movement models, where detailed movement processes of an animal are used to predict its emergent utilization distribution. Such models bias the animal's movement towards patches that are easily available and resource-rich, and the result is a predicted probability density at a given position being a function of the habitat quality at that position. However, in reality, the probability that an animal will use a patch of the terrain tends to be a function of the resource quality in both that patch and the surrounding habitat. We propose a mechanistic model where this non-local effect of resources naturally emerges from the local movement processes, by taking into account the relative utility of both the habitat where the animal currently resides and that of where it is moving. We give statistical techniques to parametrize the model from location data and demonstrate application of these techniques to GPS location data of caribou (Rangifer tarandus) in Newfoundland. Steady-state animal probability distributions arising from the model have complex patterns that cannot be expressed simply as a function of the local quality of the habitat. In particular, large areas of good habitat are used more intensively than smaller patches of equal quality habitat, whereas isolated patches are used less frequently. Both of these are real aspects of animal space use missing from previous mechanistic resource selection models. Whilst we focus on habitats in this study, our modelling framework can be readily used with any environmental covariates and therefore represents a unification of mechanistic modelling and step selection approaches to understanding animal space use.

Prey abundance and prey vulnerability vary across space and time, but we know little about how they mediate predator-prey interactions and predator foraging tactics. To evaluate the interplay between prey abundance, prey vulnerability and predator space use, we examined patterns of black bear (Ursus americanus) predation of caribou (Rangifer tarandus) neonates in Newfoundland, Canada using data from 317 collared individuals (9 bears, 34 adult female caribou, 274 caribou calves). During the caribou calving season, we predicted that landscape features would influence calf vulnerability to bear predation, and that bears would actively hunt calves by selecting areas associated with increased calf vulnerability. Further, we hypothesized that bears would dynamically adjust their foraging tactics in response to spatiotemporal changes in calf abundance and vulnerability (collectively, calf availability). Accordingly, we expected bears to actively hunt calves when they were most abundant and vulnerable, but switch to foraging on other resources as calf availability declined. As predicted, landscape heterogeneity influenced risk of mortality, and bears displayed the strongest selection for areas where they were most likely to kill calves, which suggested they were actively hunting caribou. Initially, the per-capita rate at which bears killed calves followed a type-I functional response, but as the calving season progressed and calf vulnerability declined, kill rates dissociated from calf abundance. In support of our hypothesis, bears adjusted their foraging tactics when they were less efficient at catching calves, highlighting the influence that predation phenology may have on predator space use. Contrary to our expectations, however, bears appeared to continue to hunt caribou as calf availability declined, but switched from a tactic of selecting areas of increased calf vulnerability to a tactic that maximized encounter rates with calves. Our results reveal that generalist predators can dynamically adjust their foraging tactics over short time-scales in response to changing prey abundance and vulnerability. Further, they demonstrate the utility of integrating temporal dynamics of prey availability into investigations of predator-prey interactions, and move towards a mechanistic understanding of the dynamic foraging tactics of a large omnivore.

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

Summary The reasons that lead some animals to seasonally migrate, and others to remain in the same area year-round, are poorly understood. Associations between traits, such as body size, and migration provide clues. For example, larger species and individuals are more likely to migrate. One explanation for this size bias in migration is that larger animals are capable of moving faster (movement hypothesis). However, body size is linked to many other biological processes. For instance, the energetic balances of larger animals are generally more sensitive to variation in food density because of body size effects on foraging and metabolism and this sensitivity could drive migratory decisions (forage hypothesis). Identifying the primary selective forces that drive migration ultimately requires quantifying fitness impacts over the full annual migratory cycle. Here, we develop a full annual migratory cycle model from metabolic and foraging theory to compare the importance of the forage and movement hypotheses. We parameterize the model for Galapagos tortoises, which were recently discovered to be size-dependent altitudinal migrants. The model predicts phenomena not included in model development including maximum body sizes, the body size at which individuals begin to migrate, and the seasonal timing of migration and these predictions generally agree with available data. Scenarios strongly support the forage hypothesis over the movement hypothesis. Furthermore, male Galapagos tortoises on Santa Cruz Island would be unable to grow to their enormous sizes without access to both highlands and lowlands. Whereas recent research has focused on links between traits and the migratory phases of the migratory cycle, we find that effects of body size on the non-migratory phases are far more important determinants of the propensity to migrate. Larger animals are more sensitive to changing forage conditions than smaller animals with implications for maintenance of migration and body size in the face of environmental change.

Omnivores feed on animals with dynamic distributions and on plants with static distributions. The search tactics they adopt will not only define the risk for the targeted prey, but also for other prey that may be consumed when encountered. The potential impact of omnivores on the dynamics of multi-prey systems thus depends on resource selection and on the tactics used to find their prey. We present an approach that can clarify the foraging decisions of omnivores by combining analyses of habitat selection, local residency time, and interpatch movements. We use this framework to evaluate whether predation by omnivorous black bears on ungulate neonates resulted from an active search or from incidental encounters. We monitored 12 bears, 22 forest-dwelling caribou, and 36 moose during calving seasons. We estimated the spatial patterns in relative occurrence probability of ungulate neonates using Resource Selection Functions (RSFs). We also mapped plant abundance from vegetation surveys. RSF were then built to assess the link between bear distribution and the distribution of these three food types (vegetation, moose calves, caribou fawns). We further evaluated the search tactic used by bears that led to this spatial dependency by exploring patterns of residency times and interpatch movements. Bears did not select areas with a high probability of encounter with neonates, but selected areas with abundant vegetation. Surprisingly, bears displayed shorter residency times in vegetation-rich areas. The selection for vegetation-rich areas was therefore achieved by moving preferentially, but frequently, between areas offering abundant vegetation. Such frequent interpatch movements could result in high rates of fortuitous encounters with neonates, even if bears are not actively searching for them. To mitigate the impacts of forest harvesting on threatened caribou populations, vegetation-rich areas selected by bears (e.g. roadsides) should be segregated from large patches of mature conifer forest suitable for caribou.