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.

Understanding Species–Habitat Associations: A Case Study with the World’s Bears

Habitat modeling is one of the most common practices in ecology today, aimed at understanding complex associations between species and an array of environmental, bioclimatic, and anthropogenic factors. This review of studies of seven species of terrestrial bears (Ursidae) occupying four continents examines how habitat models have been employed, and the functionality of their predictions for management and conservation. Bear occurrence data have been obtained at the population level, as presence points (e.g., sign surveys or camera trapping), or as locations of individual radio-collared animals. Radio-collars provide greater insights into how bears interact with their environment and variability within populations; they are more commonly used in North America and Europe than in South America and Asia. Salient problematic issues apparent from this review included: biases in presence data; predictor variables being poor surrogates of actual behavioral drivers; predictor variables applied at a biologically inappropriate scale; and over-use of data repositories that tend to detach investigators from the species. In several cases, multiple models in the same area yielded different predictions; new presence data occurred outside the range of predicted suitable habitat; and future range projections, based on where bears presently exist, underestimated their adaptability. Findings here are likely relevant to other taxa.

Conceptual and methodological advances in habitat-selection modeling: guidelines for ecology and evolution

Habitat selection is a fundamental animal behavior that shapes a wide range of ecological processes, including animal movement, nutrient transfer, trophic dynamics and population distribution. Although habitat selection has been a focus of ecological studies for decades, technological, conceptual and methodological advances over the last 20 yr have led to a surge in studies addressing this process. Despite the substantial literature focused on quantifying the habitat-selection patterns of animals, there is a marked lack of guidance on best analytical practices. The conceptual foundations of the most commonly applied modeling frameworks can be confusing even to those well versed in their application. Furthermore, there has yet to be a synthesis of the advances made over the last 20 yr. Therefore, there is a need for both synthesis of the current state of knowledge on habitat selection, and guidance for those seeking to study this process. Here, we provide an approachable overview and synthesis of the literature on habitat-selection analyses (HSAs) conducted using selection functions, which are by far the most applied modeling framework for understanding the habitat-selection process. This review is purposefully non-technical and focused on understanding without heavy mathematical and statistical notation, which can confuse many practitioners. We offer an overview and history of HSAs, describing the tortuous conceptual path to our current understanding. Through this overview, we also aim to address the areas of greatest confusion in the literature. We synthesize the literature outlining the most exciting conceptual advances in the field of habitat-selection modeling, discussing the substantial ecological and evolutionary inference that can be made using contemporary techniques. We aim for this paper to provide clarity for those navigating the complex literature on HSAs while acting as a reference and best practices guide for practitioners.

Lion and spotted hyena distributions within a buffer area of the Serengeti-Mara ecosystem

Most large carnivore populations are declining due to anthropogenic activities including direct persecution, prey depletion, habitat loss and degradation. protected areas (PAs) can help maintain viable large carnivore populations; however, anthropogenic activities occurring near and within PA borders or edges can reduce their effectiveness. We investigated the influence of edge effects on abundance of lions (Panthera leo) and spotted hyenas (Crocuta crocuta) in Maswa Game Reserve (MGR), a part of the Serengeti ecosystem in northern Tanzania. We conducted repeated call-ins to attract and enumerate lions and hyenas at 20 stations in MGR during June–July 2017. We used N-mixture models to estimate hyena and lion abundance in relation to land cover and distance from the south-western MGR borders which are adjacent to villages. We found lowest lion and hyena abundances by the south-western border, with abundance of both species increasing toward the eastern border adjacent to Serengeti National Park. Lions were uniformly distributed among land covers whereas hyenas were more abundant in woodlands. We suggest that reduced lion and hyena abundance near human settlements was in response to depleted prey, due to human actions. We recommend ecologically compatible land uses and effective border patrols to mitigate these adverse effects.

Scale-dependent home range optimality for a solitary omnivore

Spatial and temporal heterogeneity are fundamental mechanisms structuring home ranges. Under optimality, an individual should structure their space use economically to maximize fitness. We evaluated support for three hypotheses related to range optimality in American black bears (Ursus americanus), predicting (a) range location on a landscape will correspond with high vegetation productivity, (b) increasing forest fragmentation will result in larger ranges, and (c) increasing proportion of forest and/or mean vegetation productivity will result in smaller ranges. We used black bear radio telemetry data from Michigan (2009-2015), Missouri (2010-2016), and Mississippi (2008-2017), USA. Annual space use excluded winter, and we separated seasonal space use into spring, summer, and fall. We collected data from 143 bears (80 females, 63 males), resulting in 97 annual and 538 seasonal ranges. We used generalized linear mixed models to evaluate productivity (estimated through Normalized Difference Vegetation Index [NDVI]) selection, and range size (km2) variation between individuals. At the annual scale, black bears consistently selected areas with greater vegetation productivity than the surrounding landscape; yet selection weakened and was more variable seasonally. Opposite to our prediction, we found that increasing fragmentation consistently resulted in smaller ranges; non-forested land covers and forest edges might provide greater abundance or more diverse foods for bears. Ranges with a greater proportion of forest were smaller, likely reflecting an increase in food and cover which could reduce movements, yet there was no support for more productive ranges also being smaller as expected from an area minimizing strategy. Black bears displayed a scale-dependent space use strategy: at larger spatial and temporal scales, productivity acted as the strongest limiting factor and energy maximizing was the dominant strategy, while an area minimizing strategy was exhibited seasonally. We revealed consistent, scale-dependent responses by black bears to environmental conditions, demonstrating the intrinsic plasticity of this adaptable omnivore.

Toward reliable population estimates of wolves by combining spatial capture-recapture models and non-invasive DNA monitoring

Decision-makers in wildlife policy require reliable population size estimates to justify interventions, to build acceptance and support in their decisions and, ultimately, to build trust in managing authorities. Traditional capture-recapture approaches present two main shortcomings, namely, the uncertainty in defining the effective sampling area, and the spatially-induced heterogeneity in encounter probabilities. These limitations are overcome using spatially explicit capture-recapture approaches (SCR). Using wolves as case study, and non-invasive DNA monitoring (faeces), we implemented a SCR with a Poisson observation model in a single survey to estimate wolf density and population size, and identify the locations of individual activity centres, in NW Iberia over 4,378 km². During the breeding period, posterior mean wolf density was 2.55 wolves/100 km² (95%BCI = 1.87–3.51), and the posterior mean population size was 111.6 ± 18.8 wolves (95%BCI = 81.8–153.6). From simulation studies, addressing different scenarios of non-independence and spatial aggregation of individuals, we only found a slight underestimation in population size estimates, supporting the reliability of SCR for social species. The strategy used here (DNA monitoring combined with SCR) may be a cost-effective way to generate reliable population estimates for large carnivores at regional scales, especially for endangered species or populations under game management.

Consequences of severe habitat fragmentation on density, genetics, and spatial capture-recapture analysis of a small bear population

Loss and fragmentation of natural habitats caused by human land uses have subdivided several formerly contiguous large carnivore populations into multiple small and often isolated subpopulations, which can reduce genetic variation and lead to precipitous population declines. Substantial habitat loss and fragmentation from urban development and agriculture expansion relegated the Highlands-Glades subpopulation (HGS) of Florida, USA, black bears (Ursus americanus floridanus) to prolonged isolation; increasing human land development is projected to cause ≥ 50% loss of remaining natural habitats occupied by the HGS in coming decades. We conducted a noninvasive genetic spatial capture-recapture study to quantitatively describe the degree of contemporary habitat fragmentation and investigate the consequences of habitat fragmentation on population density and genetics of the HGS. Remaining natural habitats sustaining the HGS were significantly more fragmented and patchier than those supporting Florida’s largest black bear subpopulation. Genetic diversity was low (A_R = 3.57; H_E = 0.49) and effective population size was small (N_E = 25 bears), both of which remained unchanged over a period spanning one bear generation despite evidence of some immigration. Subpopulation density (0.054 bear/km²) was among the lowest reported for black bears, was significantly female-biased, and corresponded to a subpopulation size of 98 bears in available habitat. Conserving remaining natural habitats in the area occupied by the small, genetically depauperate HGS, possibly through conservation easements and government land acquisition, is likely the most important immediate step to ensuring continued persistence of bears in this area. Our study also provides evidence that preferentially placing detectors (e.g., hair traps or cameras) primarily in quality habitat across fragmented landscapes poses a challenge to estimating density-habitat covariate relationships using spatial capture-recapture models. Because habitat fragmentation and loss are likely to increase in severity globally, further investigation of the influence of habitat fragmentation and detector placement on estimation of this relationship is warranted.