Disturbance-mediated changes to boreal mammal spatial networks in industrializing landscapes.

Compound effects of anthropogenic disturbances on wildlife emerge through a complex network of direct responses and species interactions. Land-use changes driven by energy and forestry industries are known to disrupt predator-prey dynamics in boreal ecosystems, yet how these disturbance effects propagate across mammal communities remains uncertain. Using structural equation modeling, we tested disturbance-mediated pathways governing the spatial structure of multipredator multiprey boreal mammal networks across a landscape-scale disturbance gradient within Canada's Athabasca oil sands region. Linear disturbances had pervasive direct effects, increasing site use for all focal species, except black bears and threatened caribou, in at least one landscape. Conversely, block (polygonal) disturbance effects were negative but less common. Indirect disturbance effects were widespread and mediated by caribou avoidance of wolves, tracking of primary prey by subordinate predators, and intraguild dependencies among predators and large prey. Context-dependent responses to linear disturbances were most common among prey and within the landscape with intermediate disturbance. Our research suggests that industrial disturbances directly affect a suite of boreal mammals by altering forage availability and movement, leading to indirect effects across a range of interacting predators and prey, including the keystone snowshoe hare. The complexity of network-level direct and indirect disturbance effects reinforces calls for increased investment in addressing habitat degradation as the root cause of threatened species declines and broader ecosystem change.

Using global remote camera data of a solitary species complex to evaluate the drivers of group formation.

The social system of animals involves a complex interplay between physiology, natural history, and the environment. Long relied upon discrete categorizations of "social" and "solitary" inhibit our capacity to understand species and their interactions with the world around them. Here, we use a globally distributed camera trapping dataset to test the drivers of aggregating into groups in a species complex (martens and relatives, family Mustelidae, Order Carnivora) assumed to be obligately solitary. We use a simple quantification, the probability of being detected in a group, that was applied across our globally derived camera trap dataset. Using a series of binomial generalized mixed-effects models applied to a dataset of 16,483 independent detections across 17 countries on four continents we test explicit hypotheses about potential drivers of group formation. We observe a wide range of probabilities of being detected in groups within the solitary model system, with the probability of aggregating in groups varying by more than an order of magnitude. We demonstrate that a species' context-dependent proclivity toward aggregating in groups is underpinned by a range of resource-related factors, primarily the distribution of resources, with increasing patchiness of resources facilitating group formation, as well as interactions between environmental conditions (resource constancy/winter severity) and physiology (energy storage capabilities). The wide variation in propensities to aggregate with conspecifics observed here highlights how continued failure to recognize complexities in the social behaviors of apparently solitary species limits our understanding not only of the individual species but also the causes and consequences of group formation.

Public perceptions of trophy hunting are pragmatic, not dogmatic.

Fierce international debates rage over whether trophy hunting is socially acceptable, especially when people from the Global North hunt well-known animals in sub-Saharan Africa. We used an online vignette experiment to investigate public perceptions of the acceptability of trophy hunting in sub-Saharan Africa among people who live in urban areas of the USA, UK and South Africa. Acceptability depended on specific attributes of different hunts as well as participants' characteristics. Zebra hunts were more acceptable than elephant hunts, hunts that would provide meat to local people were more acceptable than hunts in which meat would be left for wildlife, and hunts in which revenues would support wildlife conservation were more acceptable than hunts in which revenues would support either economic development or hunting enterprises. Acceptability was generally lower among participants from the UK and those who more strongly identified as an animal protectionist, but higher among participants with more formal education, who more strongly identified as a hunter, or who would more strongly prioritize people over wild animals. Overall, acceptability was higher when hunts would produce tangible benefits for local people, suggesting that members of three urban publics adopt more pragmatic positions than are typically evident in polarized international debates.

Practical advice on variable selection and reporting using Akaike information criterion.

The various debates around model selection paradigms are important, but in lieu of a consensus, there is a demonstrable need for a deeper appreciation of existing approaches, at least among the end-users of statistics and model selection tools. In the ecological literature, the Akaike information criterion (AIC) dominates model selection practices, and while it is a relatively straightforward concept, there exists what we perceive to be some common misunderstandings around its application. Two specific questions arise with surprising regularity among colleagues and students when interpreting and reporting AIC model tables. The first is related to the issue of 'pretending' variables, and specifically a muddled understanding of what this means. The second is related to p-values and what constitutes statistical support when using AIC. There exists a wealth of technical literature describing AIC and the relationship between p-values and AIC differences. Here, we complement this technical treatment and use simulation to develop some intuition around these important concepts. In doing so we aim to promote better statistical practices when it comes to using, interpreting and reporting models selected when using AIC.

Patterns and drivers of vector-borne microparasites in a classic metapopulation.

Many organisms live in fragmented populations, which has profound consequences on the dynamics of associated parasites. Metapopulation theory offers a canonical framework for predicting the effects of fragmentation on spatiotemporal host­parasite dynamics. However, empirical studies of parasites in classical metapopulations remain rare, particularly for vector-borne parasites. Here, we quantify spatiotemporal patterns and possible drivers of infection probability for several ectoparasites (fleas, Ixodes trianguliceps and Ixodes ricinus) and vector-borne microparasites (Babesia microti, Bartonella spp., Hepatozoon spp.) in a classically functioning metapopulation of water vole hosts. Results suggest that the relative importance of vector or host dynamics on microparasite infection probabilities is related to parasite life-histories. Bartonella, a microparasite with a fast life-history, was positively associated with both host and vector abundances at several spatial and temporal scales. In contrast, B. microti, a tick-borne parasite with a slow life-history, was only associated with vector dynamics. Further, we provide evidence that life-history shaped parasite dynamics, including occupancy and colonization rates, in the metapopulation. Lastly, our findings were consistent with the hypothesis that landscape connectivity was determined by distance-based dispersal of the focal hosts. We provide essential empirical evidence that contributes to the development of a comprehensive theory of metapopulation processes of vector-borne parasites.

Projected northward shifts in eastern red-backed salamanders due to changing climate.

Many species' distributions are being impacted by the acceleration of climate change. Amphibians in particular serve numerous ecosystem functions and are useful indicators of environmental change. Understanding how their distributions have been impacted by climate change and will continue to be impacted is thus important to overall ecosystem health. Plethodon cinereus (Eastern Red-Backed Salamander) is a widespread species of lungless salamander (Plethodontidae) that ranges across northeastern North America. To better understand future potential lungless salamander range shifts, we quantify environmental favorability, the likelihood of membership in a set of sites where environmental conditions are favorable for a species, for P. cinereus in multiple time periods, and examine shifts in the species' distribution. First, utilizing a large data set of georeferenced records, we assessed which bioclimatic variables were associated with environmental favorability in P. cinereus. We then used species distribution modeling for two time periods (1961-1980 and 2001-2020) to determine whether there was a regional shift in environmental favorability in the past 60 years. Models were then used to project future distributions under eight climate change scenarios to quantify potential range shifts. Shifts were assessed using fuzzy logic, avoiding thresholds that oversimplify model predictions into artificial binary outputs. We found that P. cinereus presence is strongly associated with environmental stability. There has been a substantial northward shift in environmental favorability for P. cinereus between 1961-1980 and 2001-2020. This shift is predicted to continue by 2070, with larger shifts under higher greenhouse gas emission scenarios. As climate change accelerates, it is differentially impacting species but has especially strong impacts on dispersal-limited species. Our results show substantial northward shifts in climatic favorability in the last 60 years for P. cinereus, which are likely to be exacerbated by ongoing climate change. Since P. cinereus is dispersal-limited, these models may imply local extirpations along the southern modern range with limited northward dispersal. Continued monitoring of amphibians in the field will reveal microclimatic effects associated with climate change and the accuracy of the model predictions presented here.

Factors affecting spatiotemporal patterns of nest site selection and abundance in diamondback terrapins.

Determining what factors influence the distribution and abundance of wildlife populations is crucial for implementing effective conservation and management actions. Yet, for species with dynamic seasonal, sex-, and age-specific spatial ecology, like the diamondback terrapin (Malaclemys terrapin; DBT), doing so can be challenging. Moreover, environmental factors that influence the distribution and abundance of DBT in their northernmost range have not been quantitatively characterized. We investigated proximity to nesting habitat as one potential driver of spatiotemporal variation in abundance in a three-step analytical approach. First, we used a scale selection resource selection function (RSF) approach based on landcover data from the National Landcover Database (NLCD) to identify the scale at which DBT are selecting for (or avoiding) landcover types to nest. Next, we used RSF to predict areas of suitable nesting habitat and created an index of nest suitability (NSI). Finally, analyzing visual count data using a generalized linear mixed model (GLMM), we investigate spatiotemporal drivers of relative abundance, with a specific focus on whether similar factors affect offshore abundance and onshore nest site selection. We found the scale of selection for developed and saltmarsh land use classes to be 550 and 600 m and open water land use classes to be 100. Selection was positive for nesting areas proximal to saltmarsh habitat and negative for developed and open water. Expected relative abundance was best explained by the interaction between NSI and day of season, where expected relative abundance was greater within high NSI areas during the nesting season (2.20 individuals, CI: 1.19-3.93) compared to areas of low NSI (1.84 individuals, CI: 1.10-3.10). Our results provide evidence that inferred spatial patterns of suitable nesting habitats explain spatiotemporal patterns of terrapin movement and abundance.

Context-dependency in carnivore co-occurrence across a multi-use conservation landscape.

Carnivore intraguild dynamics depend on a complex interplay of environmental affinities and interspecific interactions. Context-dependency is commonly expected with varying suites of interacting species and environmental conditions but seldom empirically described. In South Africa, decentralized approaches to conservation and the resulting multi-tenure conservation landscapes have markedly altered the environmental stage that shapes the structure of local carnivore assemblages. We explored assemblage-wide patterns of carnivore spatial (residual occupancy probability) and temporal (diel activity overlap) co-occurrence across three adjacent wildlife-oriented management contexts-a provincial protected area, a private ecotourism reserve, and commercial game ranches. We found that carnivores were generally distributed independently across space, but existing spatial dependencies were context-specific. Spatial overlap was most common in the protected area, where species occur at higher relative abundances, and in game ranches, where predator persecution presumably narrows the scope for spatial asymmetries. In the private reserve, spatial co-occurrence patterns were more heterogeneous but did not follow a dominance hierarchy associated with higher apex predator densities. Pair-specific variability suggests that subordinate carnivores may alternate between pre-emptive behavioral strategies and fine-scale co-occurrence with dominant competitors. Consistency in species-pairs diel activity asynchrony suggested that temporal overlap patterns in our study areas mostly depend on species' endogenous clock rather than the local context. Collectively, our research highlights the complexity and context-dependency of guild-level implications of current management and conservation paradigms; specifically, the unheeded potential for interventions to influence the local network of carnivore interactions with unknown population-level and cascading effects.

Spatiotemporal connectivity dynamics in spatially structured populations.

Connectivity is a fundamental concept linking dispersal to the emergent dynamics and persistence of spatially structured populations. Functional measures of connectivity typically seek to integrate aspects of landscape structure and animal movement to describe ecologically meaningful connectedness at the landscape and population scale. Despite this focus on function, traditional measures of landscape connectivity assume it is a static property of the landscape, hence abstracting out the underlying spatiotemporal population dynamics. Connectivity is, arguably, a dynamic property of landscapes, and is inherently related to the spatial distribution of individuals and populations across the landscape. Static representations of connectivity potentially overlook this variation and therefore adopting a dynamic approach should offer improved insights about connectivity and associated ecological processes. Using a large-scale, long-term time series of occupancy data from a metapopulation of water voles Arvicola amphibius, we tested competing hypotheses about how considering the dynamic nature of connectivity improves the ability of spatially explicit occupancy models to recover population dynamics. Iteratively relaxing standing assumptions of connectivity metrics, these models ranged from spatially and temporally fixed connectivity metrics that are widely applied, to the more flexible, but lesser used model that allowed temporally varying connectivity measures that incorporate spatiotemporally dynamic patch occupancy states. Our results provide empirical evidence that demographic weighting using patch occupancy dynamics and temporal variability in connectivity measures are important for describing metapopulation dynamics. We highlight the implications of commonly held assumption in connectivity modelling and demonstrate how they result in different and highly variable predictions of metapopulation capacity. Thus, we argue that the concept of connectivity and its potential applications would benefit from recognizing inherent spatiotemporal variation in connectivity that is explicitly linked to underlying ecological state variables.

Rhesus macaques compensate for reproductive delay following ecological adversity early in life.

Adversity early in life can shape the reproductive potential of individuals through negative effects on health and life span. However, long-lived populations with multiple reproductive events may present alternative life history strategies to optimize reproductive schedules and compensate for shorter life spans. Here, we quantify the effects of major hurricanes and density dependence as sources of early-life ecological adversity on Cayo Santiago rhesus macaque female reproduction and decompose their effects onto the mean age-specific fertility, reproductive pace, and lifetime reproductive success (LRS). Females experiencing major hurricanes exhibit a delayed reproductive debut but maintain the pace of reproduction past debut and show a higher mean fertility during prime reproductive ages, relative to unaffected females. Increasing density at birth is associated to a decrease in mean fertility and reproductive pace, but such association is absent at intermediate densities. When combined, our study reveals that hurricanes early in life predict a delay-overshoot pattern in mean age-specific fertility that supports the maintenance of LRS. In contrast to predictive adaptive response models of accelerated reproduction, this long-lived population presents a novel reproductive strategy where females who experience major natural disasters early in life ultimately overcome their initial reproductive penalty with no major negative fitness outcomes. Density presents a more complex relation with reproduction that suggests females experiencing a population regulated at intermediate densities early in life will escape density dependence and show optimized reproductive schedules. Our results support hypotheses about life history trade-offs in which adversity-affected females ensure their future reproductive potential by allocating more energy to growth or maintenance processes at younger adult ages.

Habitat mediates coevolved but not novel species interactions.

Ongoing recovery of native predators has the potential to alter species interactions, with community and ecosystem wide implications. We estimated the co-occurrence of three species of conservation and management interest from a multi-species citizen science camera trap survey. We demonstrate fundamental differences in novel and coevolved predator-prey interactions that are mediated by habitat. Specifically, we demonstrate that anthropogenic habitat modification had no influence on the expansion of the recovering native pine marten in Ireland, nor does it affect the predator's suppressive influence on an invasive prey species, the grey squirrel. By contrast, the direction of the interaction between the pine marten and a native prey species, the red squirrel, is dependent on habitat. Pine martens had a positive influence on red squirrel occurrence at a landscape scale, especially in native broadleaf woodlands. However, in areas dominated by non-native conifer plantations, the pine marten reduced red squirrel occurrence. These findings suggest that following the recovery of a native predator, the benefits of competitive release are spatially structured and habitat-specific. The potential for past and future landscape modification to alter established interactions between predators and prey has global implications in the context of the ongoing recovery of predator populations in human-modified landscapes.

Improved inferences about landscape connectivity from spatial capture-recapture by integration of a movement model.

Understanding how broad-scale patterns in animal populations emerge from individual-level processes is an enduring challenge in ecology that requires investigation at multiple scales and perspectives. Complementary to this need for diverse approaches is the recent focus on integrated modeling in statistical ecology. Population-level processes represent the core of spatial capture-recapture (SCR), with many methodological extensions that have been motivated by standing ecological theory and data-integration opportunities. The extent to which these recent advances offer inferential improvements can be limited by the data requirements for quantifying individual-level processes. This is especially true for SCR models that use non-Euclidean distance to relax the restrictive assumption that individual space use is stationary and symmetrical to make inferences about landscape connectivity. To meet the challenges of scale and data quality, we propose integrating an explicit movement model with non-Euclidean SCR for joint estimation of a shared cost parameter between individual and population processes. Here, we define a movement kernel for step selection that uses "ecological distance" instead of Euclidean distance to quantify availability for each movement step in terms of landscape cost. We compare performance of our integrated model to that of existing SCR models using realistic animal movement simulations and data collected on black bears. We demonstrate that an integrated approach offers improvements both in terms of bias and precision in estimating the shared cost parameter over models fit to spatial encounters alone. Simulations suggest these gains were only realized when step lengths were small relative to home range size, and estimates of density were insensitive to whether or not an integrated approach was used. By combining the fine spatiotemporal scale of individual movement processes with the estimation of population density in SCR, integrated approaches such as the one we develop here have the potential to unify the fields of movement, population, and landscape ecology and improve our understanding of landscape connectivity.

Broad aggressive interactions among African carnivores suggest intraguild killing is driven by more than competition.

Theory on intraguild killing (IGK) is central to mammalian carnivore community ecology and top-down ecosystem regulation. Yet, the cryptic nature of IGK hinders empirical evaluations. Using a novel data source - online photographs of interspecific aggression between African carnivores - we revisited existing predictions about the extent and drivers of IGK. Compared with seminal reviews, our constructed IGK network yielded 10 more species and nearly twice as many interactions. The extent of interactions increased 37% when considering intraguild aggression (direct attack) as a precursor of killing events. We show that IGK occurs over a wider range of body-mass ratios than predicted by standing competition-based views, with highly asymmetrical interactions being pervasive. Evidence that large species, particularly hypercarnivore felids, target sympatric carnivores with a wide range of body sizes suggests that current IGK theory is incomplete, underestimating alternative competition pathways and the role of predatory and incidental killing. Our findings reinforce the potential for IGK-mediated cascades in species-rich assemblages and community-wide suppressive effects of large carnivores.

Defining dual-axis landscape gradients of human influence for studying ecological processes.

Ecological processes are strongly shaped by human landscape modification, and understanding the reciprocal relationship between ecosystems and modified landscapes is critical for informed conservation. Single axis measures of spatial heterogeneity proliferate in the contemporary gradient ecology literature, though they are unlikely to capture the complexity of ecological responses. Here, we develop a standardized approach for defining multi-dimensional gradients of human influence in heterogeneous landscapes and demonstrate this approach to analyze landscape characteristics of ten ecologically distinct US cities. Using occupancy data of a common human-adaptive songbird collected in each of the cities, we then use our dual-axis gradients to evaluate the utility of our approach. Spatial analysis of landscapes surrounding ten US cities revealed two important axes of variation that are intuitively consistent with the characteristics of multi-use landscapes, but are often confounded in single axis gradients. These were, a hard-to-soft gradient, representing transition from developed areas to non-structural soft areas; and brown-to-green, differentiating between two dominant types of soft landscapes: agriculture (brown) and natural areas (green). Analysis of American robin occurrence data demonstrated that occupancy responds to both hard-to-soft (decreasing with development intensity) and brown-to-green gradient (increasing with more natural area). Overall, our results reveal striking consistency in the dominant sources of variation across ten geographically distinct cities and suggests that our approach advances how we relate variation in ecological responses to human influence. Our case study demonstrates this: robins show a remarkably consistent response to a gradient differentiating agricultural and natural areas, but city-specific responses to the more traditional gradient of development intensity, which would be overlooked with a single gradient approach. Managing ecological communities in human dominated landscapes is extremely challenging due to a lack of standardized approaches and a general understanding of how socio-ecological systems function, and our approach offers promising solutions.

Experimental evaluation of spatial capture-recapture study design.

A principal challenge impeding strong inference in analyses of wild populations is the lack of robust and long-term data sets. Recent advancements in analytical tools used in wildlife science may increase our ability to integrate smaller data sets and enhance the statistical power of population estimates. One such advancement, the development of spatial capture-recapture (SCR) methods, explicitly accounts for differences in spatial study designs, making it possible to equate multiple study designs in one analysis. SCR has been shown to be robust to variation in design as long as minimal sampling guidance is adhered to. However, these expectations are based on simulation and have yet to be evaluated in wild populations. Here we conduct a rigorously designed field experiment by manipulating the arrangement of artificial cover objects (ACOs) used to collect data on red-backed salamanders (Plethodon cinereus) to empirically evaluate the effects of design configuration on inference made using SCR. Our results suggest that, using SCR, estimates of space use and detectability are sensitive to study design configuration, namely the spacing and extent of the array, and that caution is warranted when assigning biological interpretation to these parameters. However, estimates of population density remain robust to design except when the configuration of detectors grossly violates existing recommendations.

An empirical demonstration of the effect of study design on density estimations.

The simultaneous development of technology (e.g. camera traps) and statistical methods, particularly spatially capture-recapture (SCR), has improved monitoring of large mammals in recent years. SCR estimates are known to be sensitive to sampling design, yet existing recommendations about trap spacing and coverage are often not achieved, particularly for sampling wide-ranging and rare species in landscapes that allow for limited accessibility. Consequently, most camera trap studies on large wide-ranging carnivores relies on convenience or judgmental sampling, and often yields compromised results. This study attempts to highlight the importance of carefully considered sampling design for large carnivores that, because of low densities and elusive behavior, are challenging to monitor. As a motivating example, we use two years of snow leopard camera trapping data from the same areas in the high mountains of Pakistan but with vastly different camera configurations, to demonstrate that estimates of density and space use are indeed sensitive to the trapping array. A compact design, one in which cameras were placed much closer together than generally recommended and therefore have lower spatial coverage, resulted in fewer individuals observed, but more recaptures, and estimates of density and space use were inconsistent with expectations for the region. In contrast, a diffuse design, one with larger spacing and spatial coverage and more consistent with general recommendations, detected more individuals, had fewer recaptures, but generated estimates of density and space use that were in line with expectations. Researchers often opt for compact camera configurations while monitoring wide-ranging and rare species, in an attempt to maximize the encounter probabilities. We empirically demonstrate the potential for biases when sampling a small area approximately the size of a single home range-this arises from exposing fewer individuals than deemed sufficient for estimation. The smaller trapping array may also underestimate density by significantly inflating [Formula: see text]. On the other hand, larger trapping array with fewer detectors and poor design induces uncertainties in the estimates. We conclude that existing design recommendations have limited utility on practical grounds for devising feasible sampling designs for large ranging species, and more research on SCR designs is required that allows for integrating biological and habitat traits of large carnivores in sampling framework. We also suggest that caution should be exercised when there is a reliance on convenience sampling.

Mesocarnivore community structuring in the presence of Africa's apex predator.

Apex predator reintroductions have proliferated across southern Africa, yet their ecological effects and proposed umbrella benefits of associated management lack empirical evaluations. Despite a rich theory on top-down ecosystem regulation via mesopredator suppression, a knowledge gap exists relating to the influence of lions (Panthera leo) over Africa's diverse mesocarnivore (less than 20 kg) communities. We investigate how geographical variation in mesocarnivore community richness and occupancy across South African reserves is associated with the presence of lions. An interesting duality emerged: lion reserves held more mesocarnivore-rich communities, yet mesocarnivore occupancy rates and evenness-weighted diversity were lower in the presence of lions. Human population density in the reserve surroundings had a similarly ubiquitous negative effect on mesocarnivore occupancy. The positive association between species richness and lion presence corroborated the umbrella species concept but translated into small differences in community size. Distributional contractions of mesocarnivore species within lion reserves, and potentially corresponding numerical reductions, suggest within-community mesopredator suppression by lions, probably as a result of lethal encounters and responses to a landscape of fear. Our findings offer empirical support for the theoretical understanding of processes underpinning carnivore community assembly and are of conservation relevance under current large-predator orientated management and conservation paradigms.

Optimal sampling design for spatial capture-recapture.

Spatial capture-recapture (SCR) has emerged as the industry standard for estimating population density by leveraging information from spatial locations of repeat encounters of individuals. The precision of density estimates depends fundamentally on the number and spatial configuration of traps. Despite this knowledge, existing sampling design recommendations are heuristic and their performance remains untested for most practical applications. To address this issue, we propose a genetic algorithm that minimizes any sensible, criteria-based objective function to produce near-optimal sampling designs. To motivate the idea of optimality, we compare the performance of designs optimized using three model-based criteria related to the probability of capture. We use simulation to show that these designs outperform those based on existing recommendations in terms of bias, precision, and accuracy in the estimation of population size. Our approach, available as a function in the R package oSCR, allows conservation practitioners and researchers to generate customized and improved sampling designs for wildlife monitoring.

Landscape- and local-scale habitat influences on occurrence and detection probability of Clark's nutcrackers: Implications for conservation.

Whitebark pine (Pinus albicaulis), a keystone species and an obligate mutualist of the Clark's nutcracker (Nucifraga columbiana), is rapidly declining throughout its range. Evidence suggests this decline is leading to a downward trend in local nutcracker populations, which would in-turn decrease whitebark pine regeneration. Our objectives were to (1) evaluate temporal variation in nutcracker habitat use as a function of whitebark pine and Douglas-fir (Pseudotsuga menziesii) habitat, at local and landscape scales, (2) develop metrics for predicting when whitebark pine communities require intervention to sustain nutcracker visitation, and (3) test McKinney et al. (2009) and Barringer et al.'s (2012) models predicting nutcracker occurrence. Between 2009 and 2013, we carried out 3,135 audio-visual Clark's nutcracker surveys at 238 random points in the southern Greater Yellowstone Ecosystem. Using Bayesian occupancy models and cross-product model selection, we evaluated the association between nutcracker occurrence and habitat variables during five stages of the nutcracker annual cycle, while accounting for imperfect detection. Nutcracker occurrence was most strongly associated with the presence of cone-bearing whitebark pine trees (rather than cone density) and the area of whitebark pine on the landscape. To promote a high, >75%, probability of occurrence at a site within the study area, we recommend a management plan that achieves a landscape composed of a minimum of 12,500-25,000 ha of cone-bearing whitebark pine habitat within a 32.6 km radius. Additionally, an optimal habitat mosaic includes moderate levels of Douglas-fir habitat. Models currently used to guide whitebark pine management strategies underpredicted nutcracker occurrence in our study area, suggesting these strategies may not be appropriate in the region. We cannot predict how this mutualistic relationship will change as the population density of each species shifts. We therefore suggest conducting periodic surveys to re-evaluate the relationship as the environment changes and management strategies are implemented.

Author Correction: Large-scale variation in density of an aquatic ecosystem indicator species.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.