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As local and global disturbances reshape African savannas, an understanding of how animal communities recover and respond to landscape features can inform conservation and restoration. Here, we explored the spatial ecology of a wildlife community in Gorongosa National Park, Mozambique, where conservation efforts have fostered the recovery of large mammal populations after their near-extirpation during Mozambique’s civil war. We deployed a grid of 60 camera traps and used a hierarchical, multi-species occupancy modeling approach to examine patterns of occupancy and its environmental and anthropogenic correlates for different functional groups and species. Our survey provides strong evidence that wildlife in Gorongosa is recovering. Throughout the study area, modeled species richness was comparable to richness in less-disturbed savanna systems in Tanzania and Botswana, and exceeded estimates of richness from a mixed-use landscape outside the park and from postwar (1997–2002) aerial surveys. However, the mammal community in Gorongosa differs from prewar conditions and from those of more intact systems, with few large carnivores, low occupancy probabilities for large ungulate species that were dominant prior to the war, and high occupancy for other ungulates that are now ubiquitous. Associations with tree cover varied among species and guilds. Contrary to our expectation, there was no effect of lake proximity on community and group-level occupancy, and previously dominant floodplain ungulate species now occupy more wooded areas. Mammals were more likely to occupy areas that burned frequently, as post-fire vegetation regrowth provides high-quality forage, highlighting the importance of Gorongosa’s fire regime. Occupancy was lower in areas with more illegal hunting, and higher closer to roads, potentially because roads were established in areas of high wildlife density and facilitate animal movement. Continued multi-species monitoring in Gorongosa can shed light on the different recovery trajectories of ungulate species and the consequences of ongoing large carnivore restoration, guiding conservation interventions.

Armed conflict throughout the world's biodiversity hotspots poses a critical threat to conservation efforts. To date, research and policy have focused more on the ultimate outcomes of conflict for wildlife rather than on the ecological, social, and economic processes that create those outcomes. Yet the militarization that accompanies armed conflict, as well as consequent changes in governance, economies, and human settlement, has diverse influences on wildlife populations and habitats. To better understand these complex dynamics, we summarized 144 case studies from around the world and identified 24 distinct pathways linking armed conflict to wildlife outcomes. The most commonly cited pathways reflect changes to institutional and socioeconomic factors, rather than tactical aspects of conflict. Marked differences in the most salient pathways emerge across geographic regions and wildlife taxa. Our review demonstrates that mitigating the negative effects of conflict on biodiversity conservation requires a nuanced understanding of the ways in which conflict affects wildlife populations and communities.

Human disturbance is contributing to widespread, global changes in the distributions and densities of wild animals. These anthropogenic impacts on wildlife arise from multiple bottom-up and top-down pathways, including habitat loss, resource provisioning, climate change, pollution, infrastructure development, hunting and our direct presence. Animal behaviour is an important mechanism linking these disturbances to population outcomes, although these behavioural pathways are often complex and can remain obscured when different aspects of behaviour are studied in isolation from one another. The spatial-social interface provides a lens for understanding how an animal's spatial and social environments interact to determine its spatial and social phenotype (i.e. measurable characteristics of an individual), and how these phenotypes interact and feed back to reshape environments. Here, we review studies of animal behaviour at the spatial-social interface to understand and predict how human disturbance affects animal movement, distribution and intraspecific interactions, with consequences for the conservation of populations and ecosystems. By understanding the spatial-social mechanisms linking human disturbance to conservation outcomes, we can better design management interventions to mitigate undesired consequences of disturbance.This article is part of the theme issue 'The spatial-social interface: a theoretical and empirical integration'.

When recreating outdoors in remote landscapes, people are encouraged to "leave no trace". However, the mere presence of humans on a trail can elicit changes in animal behavior, potentially compromising the effectiveness of protected areas for wildlife conservation., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Movement plays a key role in allowing animal species to adapt to sudden environmental shifts. Anthropogenic climate and land use change have accelerated the frequency of some of these extreme disturbances, including megafire. These megafires dramatically alter ecosystems and challenge the capacity of several species to adjust to a rapidly changing landscape. Ungulates and their movement behaviors play a central role in the ecosystem functions of fire-prone ecosystems around the world. Previous work has shown behavioral plasticity is an important mechanism underlying whether large ungulates are able to adjust to recent changes in their environments effectively. Ungulates may respond to the immediate effects of megafire by adjusting their movement and behavior, but how these responses persist or change over time following disturbance is poorly understood., Methods: We examined how an ecologically dominant ungulate with strong site fidelity, Columbian black-tailed deer (Odocoileus hemionus columbianus), adjusted its movement and behavior in response to an altered landscape following a megafire. To do so, we collected GPS data from 21 individual female deer over the course of a year to compare changes in home range size over time and used resource selection functions (RSFs) and hidden Markov movement models (HMMs) to assess changes in behavior and habitat selection., Results: We found compelling evidence of adaptive capacity across individual deer in response to megafire. Deer avoided exposed and severely burned areas that lack forage and could be riskier for predation immediately following megafire, but they later altered these behaviors to select areas that burned at higher severities, potentially to take advantage of enhanced forage., Conclusions: These results suggest that despite their high site fidelity, deer can navigate altered landscapes to track rapid shifts in encounter risk with predators and resource availability. This successful adjustment of movement and behavior following extreme disturbance could help facilitate resilience at broader ecological scales., (© 2024. The Author(s).)

Anthropogenic pressures threaten biodiversity, necessitating conservation actions founded on robust ecological models. However, prevailing models inadequately capture the spatiotemporal variation in environmental pressures faced by species with high mobility or complex life histories, as data are often aggregated across species' life histories or spatial distributions. We highlight the limitations of static models for dynamic species and incorporate life history variation and spatial distributions for species and stressors into a trait-based vulnerability and impact model. We use green sea turtles in the Greater Caribbean Region to demonstrate how vulnerability and anthropogenic impact for a dynamic species change across four life stages. By incorporating life stages into a trait-based vulnerability model, we observed life stage-specific vulnerabilities that were otherwise unnoticed when using an aggregated trait value set. Early life stages were more vulnerable to some stressors, such as inorganic pollution or marine heat waves, and less vulnerable to others, such as bycatch. Incorporating spatial distributions of stressors and life stages revealed impacts differ for each life stage across spatial areas, emphasizing the importance of stage-specific conservation measures. Our approach showcases the importance of incorporating dynamic processes into ecological models and will enable better and more targeted conservation actions for species with complex life histories and high mobility., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Fleury et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Wildlife must adapt to human presence to survive in the Anthropocene, so it is critical to understand species responses to humans in different contexts. We used camera trapping as a lens to view mammal responses to changes in human activity during the COVID-19 pandemic. Across 163 species sampled in 102 projects around the world, changes in the amount and timing of animal activity varied widely. Under higher human activity, mammals were less active in undeveloped areas but unexpectedly more active in developed areas while exhibiting greater nocturnality. Carnivores were most sensitive, showing the strongest decreases in activity and greatest increases in nocturnality. Wildlife managers must consider how habituation and uneven sensitivity across species may cause fundamental differences in human-wildlife interactions along gradients of human influence., (© 2024. The Author(s).)

Background: As a globally widespread apex predator, humans have unprecedented lethal and non-lethal effects on prey populations and ecosystems. Yet compared to non-human predators, little is known about the movement ecology of human hunters, including how hunting behavior interacts with the environment., Methods: We characterized the hunting modes, habitat selection, and harvest success of 483 rifle hunters in California using high-resolution GPS data. We used Hidden Markov Models to characterize fine-scale movement behavior, and k-means clustering to group hunters by hunting mode, on the basis of their time spent in each behavioral state. Finally, we used Resource Selection Functions to quantify patterns of habitat selection for successful and unsuccessful hunters of each hunting mode., Results: Hunters exhibited three distinct and successful hunting modes ("coursing", "stalking", and "sit-and-wait"), with coursings as the most successful strategy. Across hunting modes, there was variation in patterns of selection for roads, topography, and habitat cover, with differences in habitat use of successful and unsuccessful hunters across modes., Conclusions: Our study indicates that hunters can successfully employ a diversity of harvest strategies, and that hunting success is mediated by the interacting effects of hunting mode and landscape features. Such results highlight the breadth of human hunting modes, even within a single hunting technique, and lend insight into the varied ways that humans exert predation pressure on wildlife., (© 2024. The Author(s).)

Some animal species shift their activity towards increased nocturnality in disturbed habitats to avoid predominantly diurnal humans. This may alter diel overlap among species, a precondition to most predation and competition interactions that structure food webs. Here, using camera trap data from 10 tropical forest landscapes, we find that hyperdiverse Southeast Asian wildlife communities shift their peak activity from early mornings in intact habitats towards dawn and dusk in disturbed habitats (increased crepuscularity). Our results indicate that anthropogenic disturbances drive opposing behavioural adaptations based on rarity, size and feeding guild, with more nocturnality among the 59 rarer specialists' species, more diurnality for medium-sized generalists, and less diurnality for larger hunted species. Species turnover also played a role in underpinning community- and guild-level responses, with disturbances associated with markedly more detections of diurnal generalists and their medium-sized diurnal predators. However, overlap among predator-prey or competitor guilds does not vary with disturbance, suggesting that net species interactions may be conserved., (© 2024. The Author(s).)

Competition drives community composition and structure in many ecosystems. Spatial and temporal niche partitioning, in which competing species divide the environment in space or time, are mechanisms that may allow for coexistence among ecologically similar species. Such division of resources may be especially important for carnivores in African savannas, which support diverse carnivore assemblages. We used camera traps to explore patterns of spatial and temporal niche partitioning among four mesocarnivore species in Mozambique's Gorongosa National Park: large-spotted genet ( Genetta maculata ), African civet ( Civettictis civetta ), honey badger ( Mellivora capensis ) and marsh mongoose ( Atilax paludinosus ). We applied a multispecies occupancy model to evaluate spatial partitioning among mesocarnivores and to quantify the environmental factors that affect species-specific habitat use, including relative lion ( Panthera leo ) activity. We also analyzed the temporal activity overlap of the four focal species. We identified species-specific habitat covariates that influenced detection probabilities but found no evidence of spatial or temporal partitioning among mesocarnivores in the study system. Indeed, we found some evidence for spatial co-occurrence between two of our focal species: African civet and marsh mongoose. There may be limited competition among mesocarnivores in this system, perhaps due to niche and diet differentiation among these species and an abundance of resources. While we found limited evidence that lion activity impacts mesocarnivores, ongoing monitoring of intraguild interactions is vital as apex predator populations recover in the system. This study adds to a growing understanding of African mesocarnivore ecology and highlights the importance of understanding these dynamics for effective multispecies conservation and restoration., Competing Interests: The authors have no competing interests to declare., (© 2024 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

Classifying specimens is a critical component of ecological research, biodiversity monitoring and conservation. However, manual classification can be prohibitively time-consuming and expensive, limiting how much data a project can afford to process. Computer vision, a form of machine learning, can help overcome these problems by rapidly, automatically and accurately classifying images of specimens. Given the diversity of animal species and contexts in which images are captured, there is no universal classifier for all species and use cases. As such, ecologists often need to train their own models. While numerous software programs exist to support this process, ecologists need a fundamental understanding of how computer vision works to select appropriate model workflows based on their specific use case, data types, computing resources and desired performance capabilities. Ecologists may also face characteristic quirks of ecological datasets, such as long-tail distributions, 'unknown' species, similarity between species and polymorphism within species, which impact the efficacy of computer vision. Despite growing interest in computer vision for ecology, there are few resources available to help ecologists face the challenges they are likely to encounter. Here, we present a gentle introduction for species classification using computer vision. In this manuscript and associated GitHub repository, we demonstrate how to prepare training data, basic model training procedures, and methods for model evaluation and selection. Throughout, we explore specific considerations ecologists should make when training classification models, such as data domains, feature extractors and class imbalances. With these basics, ecologists can adjust their workflows to achieve research goals and/or account for uncertainty in downstream analysis. Our goal is to provide guidance for ecologists for getting started in or improving their use of machine learning for visual classification tasks., (© 2024 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.)

Disruption of key species interactions reverberates across an African savanna.

Predator-prey ecology and the study of animal cognition and culture have emerged as independent disciplines. Research combining these disciplines suggests that both animal cognition and culture can shape the outcomes of predator-prey interactions and their influence on ecosystems. We review the growing body of work that weaves animal cognition or culture into predator-prey ecology, and argue that both cognition and culture are significant but poorly understood mechanisms mediating how predators structure ecosystems. We present a framework exploring how previous experiences with the predation process creates feedback loops that alter the predation sequence. Cognitive and cultural predator-prey ecology offers ecologists new lenses through which to understand species interactions, their ecological consequences, and novel methods to conserve wildlife in a changing world., Competing Interests: Declaration of interests No interests are declared., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Extreme weather events perturb ecosystems and increasingly threaten biodiversity 1 . Ecologists emphasize the need to forecast and mitigate the impacts of these events, which requires knowledge of how risk is distributed among species and environments. However, the scale and unpredictability of extreme events complicate risk assessment 1-4 -especially for large animals (megafauna), which are ecologically important and disproportionately threatened but are wide-ranging and difficult to monitor 5 . Traits such as body size, dispersal ability and habitat affiliation are hypothesized to determine the vulnerability of animals to natural hazards 1,6,7 . Yet it has rarely been possible to test these hypotheses or, more generally, to link the short-term and long-term ecological effects of weather-related disturbance 8,9 . Here we show how large herbivores and carnivores in Mozambique responded to Intense Tropical Cyclone Idai, the deadliest storm on record in Africa, across scales ranging from individual decisions in the hours after landfall to changes in community composition nearly 2 years later. Animals responded behaviourally to rising floodwaters by moving upslope and shifting their diets. Body size and habitat association independently predicted population-level impacts: five of the smallest and most lowland-affiliated herbivore species declined by an average of 28% in the 20 months after landfall, while four of the largest and most upland-affiliated species increased by an average of 26%. We attribute the sensitivity of small-bodied species to their limited mobility and physiological constraints, which restricted their ability to avoid the flood and endure subsequent reductions in the quantity and quality of food. Our results identify general traits that govern animal responses to severe weather, which may help to inform wildlife conservation in a volatile climate., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Although the keystone species concept was conceived of over 50 years ago, contemporary efforts to synthesize related literature have been limited. Our objective was to create a list of keystone animal species identified in the literature and to examine the variation in the traits of species and the ecosystem influences they elicit. We documented 230 species considered keystones. A clustering analysis classified them into five archetypes based on combinations of their taxonomic class, body size, trophic level, and role (consumers, modifiers, or prey). Although conservation and public perception of keystones primarily focuses on large vertebrate consumers, our analysis reveals that researchers have defined a wide diversity of keystone species, with large variation in associated ecosystem processes. Future research may confront ambiguity in the definition of keystone status, as well as clarify the type, abundance, and quality of data required to assign the term. Identifying keystones with increased rigor would not only enrich the literature but also inform intervention to safeguard threatened keystones and their associated influences on ecosystems., (© 2023 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

Despite growing evidence of widespread impacts of humans on animal behaviour, our understanding of how humans reshape species interactions remains limited. Here, we present a framework that draws on key concepts from behavioural and community ecology to outline four primary pathways by which humans can alter predator-prey spatiotemporal overlap. We suggest that predator-prey dyads can exhibit similar or opposite responses to human activity with distinct outcomes for predator diet, predation rates, population demography and trophic cascades. We demonstrate how to assess these behavioural response pathways with hypothesis testing, using temporal activity data for 178 predator-prey dyads from published camera trap studies on terrestrial mammals. We found evidence for each of the proposed pathways, revealing multiple patterns of human influence on predator-prey activity and overlap. Our framework and case study highlight current challenges, gaps, and advances in linking human activity to animal behaviour change and predator-prey dynamics. By using a hypothesis-driven approach to estimate the potential for altered species interactions, researchers can anticipate the ecological consequences of human activities on whole communities., (© 2023 The Authors. Journal of Animal Ecology © 2023 British Ecological Society.)

Amid a growing disciplinary commitment to inclusion in ecology and evolutionary biology (EEB), it is critical to consider how the use of scientific language can harm members of our research community. Here, we outline a path for identifying and revising harmful terminology to foster inclusion in EEB., Competing Interests: Declaration of interests No interests are declared., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The biological sciences community is increasingly recognizing the value of open, reproducible and transparent research practices for science and society at large. Despite this recognition, many researchers fail to share their data and code publicly. This pattern may arise from knowledge barriers about how to archive data and code, concerns about its reuse, and misaligned career incentives. Here, we define, categorize and discuss barriers to data and code sharing that are relevant to many research fields. We explore how real and perceived barriers might be overcome or reframed in the light of the benefits relative to costs. By elucidating these barriers and the contexts in which they arise, we can take steps to mitigate them and align our actions with the goals of open science, both as individual scientists and as a scientific community.

The landscape of fear (LOF) concept posits that prey navigate spatial heterogeneity in perceived predation risk, balancing risk mitigation against other activities necessary for survival and reproduction. These proactive behavioral responses to risk can affect individual fitness, population dynamics, species interactions, and coexistence. Yet, antipredator responses in free-ranging prey often contradict expectations, raising questions about the generality and scalability of the LOF framework and suggesting that a purely spatial, static LOF conceptualization may be inadequate. Here, we outline a 'dynamic' LOF framework that explicitly incorporates time to account for predictable spatiotemporal variation in risk-resource trade-offs. This integrated approach suggests novel predictions about predator effects on prey behaviors to refine understanding of the role predators play in ecological communities., Competing Interests: Declaration of interests No interests are declared., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Spatiotemporal variation in predation risk arises from interactions between landscape heterogeneity, predator densities and predator hunting mode, generating landscapes of fear for prey species that can have important effects on prey behaviour and ecosystem dynamics. As widespread apex predators, humans present a significant source of risk for hunted animal populations. Spatiotemporal patterns of risk from hunters can overlap or contrast with patterns of risk from other predators. Human infrastructure can also reshape spatial patterns of risk by facilitating or impeding hunter or predator movement, or deterring predators that are themselves wary of humans. We examined how anthropogenic and natural landscape features interact with hunting modes of rifle hunters and mountain lions Puma concolor to generate spatiotemporal patterns of risk for their primary prey. We explored the implications of human-modified landscapes of fear for Columbian black-tailed deer Odocoileus hemionus columbianus in Mendocino County, California. We used historical harvest records, hunter GPS trackers and camera trap records of mountain lions to model patterns of risk for deer. We then used camera traps to examine deer spatial and temporal activity patterns in response to this variation in risk. Hunters and mountain lions exhibited distinct, contrasting patterns of spatiotemporal activity. Risk from rifle hunters, who rely on long lines of sight, was highest in open grasslands and near roads and was confined to the daytime. Risk from mountain lions, an ambush predator, was highest in dense shrubland habitat, farther from developed areas, and during the night and crepuscular periods. Areas of human settlement provided a refuge from both hunters and mountain lions. We found no evidence that deer avoided risk in space at the scale of our observations, but deer adjusted their temporal activity patterns to reduce the risk of encounters with humans and mountain lions in areas of higher risk. Our study demonstrates that interactions between human infrastructure, habitat cover and predator hunting mode can result in distinct spatial patterns of predation risk from hunters and other predators that may lead to trade-offs for prey species. However, distinct diel activity patterns of predators may create vacant hunting domains that reduce costly trade-offs for prey. Our study highlights the importance of temporal partitioning as a mechanism of predation risk avoidance., (© 2021 British Ecological Society.)

With rapid global change, the frequency and severity of extreme disturbance events are increasing worldwide. The ability of animal populations to survive these stochastic events depends on how individual animals respond to their altered environments, yet our understanding of the immediate and short-term behavioral responses of animals to acute disturbances remains poor. We focused on animal behavioral responses to the environmental disturbance created by megafire. Specifically, we explored the effects of the 2018 Mendocino Complex Fire in northern California, USA, on the behavior and body condition of black-tailed deer ( Odocoileus hemionus columbianus ). We predicted that deer would be displaced by the disturbance or experience high mortality post-fire if they stayed in the burn area. We used data from GPS collars on 18 individual deer to quantify patterns of home range use, movement, and habitat selection before and after the fire. We assessed changes in body condition using images from a camera trap grid. The fire burned through half of the study area, facilitating a comparison between deer in burned and unburned areas. Despite a dramatic reduction in vegetation in burned areas, deer showed high site fidelity to pre-fire home ranges, returning within hours of the fire. However, mean home range size doubled after the fire and corresponded to increased daily activity in a severely resource-depleted environment. Within their home ranges, deer also selected strongly for patches of surviving vegetation and woodland habitat, as these areas provided forage and cover in an otherwise desolate landscape. Deer body condition significantly decreased after the fire, likely as a result of a reduction in forage within their home ranges, but all collared deer survived for the duration of the study. Understanding the ways in which large mammals respond to disturbances such as wildfire is increasingly important as the extent and severity of such events increases across the world. While many animals are adapted to disturbance regimes, species that exhibit high site fidelity or otherwise fixed behavioral strategies may struggle to cope with increased climate instability and associated extreme disturbance events., Competing Interests: No authors have any conflicts of interest to report., (© 2021 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

Human activity and land use change impact every landscape on Earth, driving declines in many animal species while benefiting others. Species ecological and life history traits may predict success in human-dominated landscapes such that only species with "winning" combinations of traits will persist in disturbed environments. However, this link between species traits and successful coexistence with humans remains obscured by the complexity of anthropogenic disturbances and variability among study systems. We compiled detection data for 24 mammal species from 61 populations across North America to quantify the effects of (1) the direct presence of people and (2) the human footprint (landscape modification) on mammal occurrence and activity levels. Thirty-three percent of mammal species exhibited a net negative response (i.e., reduced occurrence or activity) to increasing human presence and/or footprint across populations, whereas 58% of species were positively associated with increasing disturbance. However, apparent benefits of human presence and footprint tended to decrease or disappear at higher disturbance levels, indicative of thresholds in mammal species' capacity to tolerate disturbance or exploit human-dominated landscapes. Species ecological and life history traits were strong predictors of their responses to human footprint, with increasing footprint favoring smaller, less carnivorous, faster-reproducing species. The positive and negative effects of human presence were distributed more randomly with respect to species trait values, with apparent winners and losers across a range of body sizes and dietary guilds. Differential responses by some species to human presence and human footprint highlight the importance of considering these two forms of human disturbance separately when estimating anthropogenic impacts on wildlife. Our approach provides insights into the complex mechanisms through which human activities shape mammal communities globally, revealing the drivers of the loss of larger predators in human-modified landscapes., (© 2021 John Wiley & Sons Ltd.)

A growing body of literature has documented myriad effects of human activities on animal behaviour, yet the ultimate ecological consequences of these behavioural shifts remain largely uninvestigated. While it is understood that, in the absence of humans, variation in animal behaviour can have cascading effects on species interactions, community structure and ecosystem function, we know little about whether the type or magnitude of human-induced behavioural shifts translate into detectable ecological change. Here we synthesise empirical literature and theory to create a novel framework for examining the range of behaviourally mediated pathways through which human activities may affect different ecosystem functions. We highlight the few empirical studies that show the potential realisation of some of these pathways, but also identify numerous factors that can dampen or prevent ultimate ecosystem consequences. Without a deeper understanding of these pathways, we risk wasting valuable resources on mitigating behavioural effects with little ecological relevance, or conversely mismanaging situations in which behavioural effects do drive ecosystem change. The framework presented here can be used to anticipate the nature and likelihood of ecological outcomes and prioritise management among widespread human-induced behavioural shifts, while also suggesting key priorities for future research linking humans, animal behaviour and ecology., (© 2020 John Wiley & Sons Ltd.)

Camera trap technology has galvanized the study of predator-prey ecology in wild animal communities by expanding the scale and diversity of predator-prey interactions that can be analysed. While observational data from systematic camera arrays have informed inferences on the spatiotemporal outcomes of predator-prey interactions, the capacity for observational studies to identify mechanistic drivers of species interactions is limited. Experimental study designs that utilize camera traps uniquely allow for testing hypothesized mechanisms that drive predator and prey behaviour, incorporating environmental realism not possible in the laboratory while benefiting from the distinct capacity of camera traps to generate large datasets from multiple species with minimal observer interference. However, such pairings of camera traps with experimental methods remain underutilized. We review recent advances in the experimental application of camera traps to investigate fundamental mechanisms underlying predator-prey ecology and present a conceptual guide for designing experimental camera trap studies. Only 9% of camera trap studies on predator-prey ecology in our review use experimental methods, but the application of experimental approaches is increasing. To illustrate the utility of camera trap-based experiments using a case study, we propose a study design that integrates observational and experimental techniques to test a perennial question in predator-prey ecology: how prey balance foraging and safety, as formalized by the risk allocation hypothesis. We discuss applications of camera trap-based experiments to evaluate the diversity of anthropogenic influences on wildlife communities globally. Finally, we review challenges to conducting experimental camera trap studies. Experimental camera trap studies have already begun to play an important role in understanding the predator-prey ecology of free-living animals, and such methods will become increasingly critical to quantifying drivers of community interactions in a rapidly changing world. We recommend increased application of experimental methods in the study of predator and prey responses to humans, synanthropic and invasive species, and other anthropogenic disturbances., (© 2020 British Ecological Society.)

Carnivore predation on livestock is a complex management and policy challenge, yet it is also intrinsically an ecological interaction between predators and prey. Human-wildlife interactions occur in socioecological systems in which human and environmental processes are closely linked. However, underlying human-wildlife conflict and key to unpacking its complexity are concrete and identifiable ecological mechanisms that lead to predation events. To better understand how ecological theory accords with interactions between wild predators and domestic prey, we developed a framework to describe ecological drivers of predation on livestock. We based this framework on foundational ecological theory and current research on interactions between predators and domestic prey. We used this framework to examine ecological mechanisms (e.g., density-mediated effects, behaviorally mediated effects, and optimal foraging theory) through which specific management interventions operate, and we analyzed the ecological determinants of failure and success of management interventions in 3 case studies: snow leopards (Panthera uncia), wolves (Canis lupus), and cougars (Puma concolor). The varied, context-dependent successes and failures of the management interventions in these case studies demonstrated the utility of using an ecological framework to ground research and management of carnivore-livestock conflict. Mitigation of human-wildlife conflict appears to require an understanding of how fundamental ecological theories work within domestic predator-prey systems., (© 2020 Society for Conservation Biology.)

For canid species, scent marking plays a critical role in territoriality, social dynamics, and reproduction. However, due in part to human dependence on vision as our primary sensory modality, research on olfactory communication is hampered by a lack of tractable methods. In this study, we leverage a powerful biologging approach, using accelerometers in concert with GPS loggers to monitor and describe scent-marking events in time and space. We performed a validation experiment with domestic dogs, monitoring them by video concurrently with the novel biologging approach. We attached an accelerometer to the pelvis of 31 dogs (19 males and 12 females), detecting raised-leg and squat posture urinations by monitoring the change in device orientation. We then deployed this technique to describe the scent marking activity of 3 guardian dogs as they defend livestock from coyote depredation in California, providing an example use-case for the technique. During validation, the algorithm correctly classified 92% of accelerometer readings. High performance was partly due to the conspicuous signatures of archetypal raised-leg postures in the accelerometer data. Accuracy did not vary with the weight, age, and sex of the dogs, resulting in a method that is broadly applicable across canid species' morphologies. We also used models trained on each individual to detect scent marking of others to emulate the use of captive surrogates for model training. We observed no relationship between the similarity in body weight between the dog pairs and the overall accuracy of predictions, although models performed best when trained and tested on the same individual. We discuss how existing methods in the field of movement ecology can be extended to use this exciting new data type. This paper represents an important first step in opening new avenues of research by leveraging the power of modern-technologies and machine-learning to this field.

The implementation of intelligent software to identify and classify objects and individuals in visual fields is a technology of growing importance to operatives in many fields, including wildlife conservation and management. To non-experts, the methods can be abstruse and the results mystifying. Here, in the context of applying cutting edge methods to classify wildlife species from camera-trap data, we shed light on the methods themselves and types of features these methods extract to make efficient identifications and reliable classifications. The current state of the art is to employ convolutional neural networks (CNN) encoded within deep-learning algorithms. We outline these methods and present results obtained in training a CNN to classify 20 African wildlife species with an overall accuracy of 87.5% from a dataset containing 111,467 images. We demonstrate the application of a gradient-weighted class-activation-mapping (Grad-CAM) procedure to extract the most salient pixels in the final convolution layer. We show that these pixels highlight features in particular images that in some cases are similar to those used to train humans to identify these species. Further, we used mutual information methods to identify the neurons in the final convolution layer that consistently respond most strongly across a set of images of one particular species. We then interpret the features in the image where the strongest responses occur, and present dataset biases that were revealed by these extracted features. We also used hierarchical clustering of feature vectors (i.e., the state of the final fully-connected layer in the CNN) associated with each image to produce a visual similarity dendrogram of identified species. Finally, we evaluated the relative unfamiliarity of images that were not part of the training set when these images were one of the 20 species "known" to our CNN in contrast to images of the species that were "unknown" to our CNN.

Animals experience varying levels of predation risk as they navigate heterogeneous landscapes, and behavioral responses to perceived risk can structure ecosystems. The concept of the landscape of fear has recently become central to describing this spatial variation in risk, perception, and response. We present a framework linking the landscape of fear, defined as spatial variation in prey perception of risk, to the underlying physical landscape and predation risk, and to resulting patterns of prey distribution and antipredator behavior. By disambiguating the mechanisms through which prey perceive risk and incorporate fear into decision making, we can better quantify the nonlinear relationship between risk and response and evaluate the relative importance of the landscape of fear across taxa and ecosystems., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Rapid expansion of human activity has driven well-documented shifts in the spatial distribution of wildlife, but the cumulative effect of human disturbance on the temporal dynamics of animals has not been quantified. We examined anthropogenic effects on mammal diel activity patterns, conducting a meta-analysis of 76 studies of 62 species from six continents. Our global study revealed a strong effect of humans on daily patterns of wildlife activity. Animals increased their nocturnality by an average factor of 1.36 in response to human disturbance. This finding was consistent across continents, habitats, taxa, and human activities. As the global human footprint expands, temporal avoidance of humans may facilitate human-wildlife coexistence. However, such responses can result in marked shifts away from natural patterns of activity, with consequences for fitness, population persistence, community interactions, and evolution., (Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Molecular markers are powerful tools for studying patterns of relatedness and parentage within populations and for making inferences about social evolution. However, the development of molecular markers for simultaneous study of multiple species presents challenges, particularly when species exhibit genome duplication or polyploidy. We developed microsatellite markers for Synalpheus shrimp, a genus in which species exhibit not only great variation in social organization, but also interspecific variation in genome size and partial genome duplication. From the four primary clades within Synalpheus, we identified microsatellites in the genomes of four species and in the consensus transcriptome of two species. Ultimately, we designed and tested primers for 143 microsatellite markers across 25 species. Although the majority of markers were disomic, many markers were polysomic for certain species. Surprisingly, we found no relationship between genome size and the number of polysomic markers. As expected, markers developed for a given species amplified better for closely related species than for more distant relatives. Finally, the markers developed from the transcriptome were more likely to work successfully and to be disomic than those developed from the genome, suggesting that consensus transcriptomes are likely to be conserved across species. Our findings suggest that the transcriptome, particularly consensus sequences from multiple species, can be a valuable source of molecular markers for taxa with complex, duplicated genomes., (© 2017 John Wiley & Sons Ltd.)