Resource Selection Functions Research Articles

GRIZZLY BEAR DENNING HABITAT AND DEMOGRAPHIC CONNECTIVITY IN NORTHERN IDAHO AND WESTERN MONTANA

Grizzly Bears (Ursus arctos) are protected in the contiguous United States under the federal Endangered Species Act. The conservation strategy for the species encourages population connectivity between isolated Grizzly Bear Recovery Areas through Demographic Connectivity Areas. Another goal is reestablishment of a breeding population in the Bitterroot ecosystem through natural immigration. Using the locations of 362 verified Grizzly Bear den sites and Maxent as a resource selection function, we predicted 21,091 km2 of suitable denning habitats. Terrain features, distance to roads, and land cover best explained suitable denning habitats in northern Idaho and western Montana. The results support the demographic model for population connectivity, and independent of other factors there is suitable denning habitat for hundreds of Grizzly Bears in the Bitterroot analysis area. We suggest additions to the Bitterroot Grizzly Bear Recovery Area, and that more effective motorized-access management be applied to demographic connectivity areas.

Unintended consequences of species translocations: changes in distribution and habitat selection of mule deer following introduction of elk

Translocation of animals for conservation has a long history of successes and failures since humans began intervening with species distributions in the early part of the 20th century. Effects of translocations on other species occupying the area of introduction are rarely considered in species management plans. We hypothesized that the introduction of a large-bodied ungulate, Rocky Mountain elk (Cervus canadensis nelsoni), would cause a shift in the spatial distribution and winter habitat selection of a smaller-bodied ungulate, Rocky Mountain mule deer (Odocoileus hemionus hemionus), already occupying the study area in northeastern Nevada. We examined mule deer survey locations during an 8-year time interval from 1993 to 2001 to test hypotheses related to potential competition with or displacement of mule deer following introduction of elk in 1997. We used geospatial statistics to quantify changes in seasonal distributions of mule deer and a resource selection function (RSF) framework to model changes in selection of resources by mule deer before and after elk were translocated into our study area. Our results indicated that mule deer exhibited a shift in their core distribution by approximately 5.72 km after the introduction of elk. Mule deer changed their use of habitat by selecting shallower slopes, more north-facing aspects, and areas farther from the elk release site, where most of the elk congregated. Mule deer selected habitats with more pinyon-juniper tree cover and mixed shrublands prior to the elk translocation, indicating a potential tradeoff in thermal cover and forage quality. This research is one of the few empirical studies to describe competitive interactions between elk and mule deer on a shared winter range in North America. Implications of this research have importance for managers concerned with restoring communities to their native conditions especially where the potential for competition with non-indigenous species or other competing species with similar niche requirements exists.

Microhabitat use and selection by Pristidactylus scapulatus (Squamata Leiosauridae) in the Puna region of the Central Andes in Argentina

Understanding a species use of space is important as it provides information about the potential resources available in its habitat. The objective of this work was to evaluate the use and selection of microhabitat as it relates to availability for Pristidactylus scapulatus in the Puna region of the Central Andes in Argentina. The work was carried out at Quebrada de La Puerta in the province of San Juan and data recorded for the species included microhabitat use and availability according to established categories. To assess microhabitat selection, we applied a design of usage vs availability and calculated the Manly index to obtain a function of resource selection. The species utilised the rock microhabitat in greater proportion with respect to its availability, and in lesser measure utilised shrub and bare soil, whereas it rejected the use of cactus and dead leaves substrate. The Manly index showed that the selection of rock substrate was significant with respect to the other microhabitats. We conclude that this population of P. scapulatus has clearly saxicolous habits, though it is necessary to be aware of other aspects of its natural history to truly understand how its microhabitat selection relates to feeding or reproduction in hostile environments like the Puna. In this way we contribute to the scarce existing knowledge of its biology and we provide an information basis for the creation of future priority areas for conservation and for habitat management plans in Puna environments.

Early nest initiation and vegetation density enhance nest survival in Wild Turkeys

Abstract The theory of adaptive habitat selection suggests resource selection by animals should reflect underlying quality, such that individual selection confers an adaptive advantage via increased fitness. Using resource selection functions and nest survival models, we demonstrated that visual obstruction at the nest site was adaptively significant but timing of nest initiation had the greatest effect on nest survival for eastern Wild Turkeys (Meleagris gallopavo silvestris). Predation risk is a selective pressure, and if individuals can perceive predation risk, they may respond by altering the selection of nest site characteristics based on prior experience. We evaluated patterns in nest site selection of 387 Wild Turkeys and the consequences of selection on reproductive success across the southeastern United States from 2014 to 2019. We monitored 549 nest sites and found that nest initiation date had the strongest effect on daily nest survival rates, wherein adult females at our earliest nest initiation date were ~4 times more likely to successfully nest than females at our latest nest initiation date. Selection of nest sites with greater visual obstruction also increased daily nest survival rates, and females were 1.17 (95% CI: 1.100–1.234) and 1.37 (95% CI: 1.258–1.486) times more likely to select sites for every 10-cm increase in visual obstruction and maximum vegetation height, respectively. Collectively, our results indicate that nest initiation date is likely the critical parameter driving Wild Turkey nest success, whereas vegetative conditions play a lesser role in influencing nest success. Females nesting earlier may be in better body condition and show increased nest attentiveness, which may mediate nest success more than vegetation conditions around nest sites. Our work indicates that increasing the reproductive success of Wild Turkeys may hinge on females being able to nest as early as possible within the reproductive season.

Effects of grazing strategy on facultative grassland bird nesting on native grassland pastures of the Mid-South USA.

Understanding how livestock grazing strategies of native warm season grasses (NWSG) can impact facultative grassland bird nesting can provide insight for conservation efforts. We compared pre and post treatment effects of rotational grazing (ROT) and patch-burn grazing (PBG) for facultative grassland bird species nest success and nest-site selection on NWSG pastures at three Mid-South research sites. We established 14, 9.7 ha NWSG pastures and randomly assigned each to either ROT or PBG and monitored avian nest-site selection and nest success, 2014–2016. We collected nesting and vegetation data in 2014, before treatment implementation, as an experimental pre-treatment. We implemented treatments across all research sites in spring 2015. We used a step-wise model selection framework to estimate treatment effect for ROT or PBG on avian nest daily survival rate (DSR) and resource selection function (RSF) at the temporal scale and within-field variables. Daily survival rates were 0.93% (SE = 0.006) for field sparrow (Spizella pusilla), 0.96% (SE = 0.008) for red-winged blackbird (Agelaius phoeniceus), and 0.92% (SE = 0.01) for indigo bunting (Passerina cyanea). Model support for PBG treatment and vegetation height were indicated as negative and positive influences for field sparrow DSR, respectively. Red-winged blackbirds’ DSR were negatively influenced by ROT while vegetation height positively affected DSR, and DSR for indigo bunting did not differ among treatments. Combined RSF models indicated nest-site selection for all species was positively related to vegetation height and only weakly associated with other within-field variables. We provide evidence that ROT and/or PBG effects vary by species for DSR for these three facultative grassland birds, and vegetation characteristics affected their nest-site selection in the Mid-South USA. A lack of disturbance in Mid-South grasslands can lead to higher successional stages (i.e., mix shrub-grassland), but some combination of ROT, PBG, and unburned/ungrazed areas can provide adequate nesting habitat on small pasture lands (∼1.8 –7.8 ha) for various facultative grassland birds and potentially offer the opportunity to simultaneously maintain livestock production and grassland bird nesting habitat.

Influence of interspecific competition on mule deer birthing and rearing site selection

AbstractUngulates often alter behavior and space use in response to interspecific competition. Despite observable changes in behavior caused by competitive interactions, research describing the effects of competition on survival or growth is lacking. We used spatial modeling to determine if habitat use by female mule deer (Odocoileus hemionus) was affected by other ungulate species prior to, during, and after parturition. We conducted our study in the Book Cliffs region of eastern Utah, USA, during 2019 and 2020. We used resource selection function (RSF) analysis to model space use of 4 ungulate species that potentially competed with mule deer: bison (Bos bison), cattle, elk (Cervus canadensis), and feral horses. We incorporated RSF models for competing species into a random forest analysis to determine if space use by mule deer was influenced by these other ungulate species. We used survival and growth data from neonate mule deer to directly assess potential negative effects of other ungulates. Habitat use by elk was an important variable in predicting use locations of mule deer during birthing and rearing. The relationship was positive, suggesting interference competition was not occurring. Survival of neonate mule deer increased as the probability of use by elk increased (hazard ratio = 0.185 ± 0.497 [SE]). Further, probability of use by elk in rearing habitat had no influence on growth of neonate mule deer from birth to 6 months of age, suggesting that exploitative competition was not occurring.

Predator avoidance influences selection of neonatal lambing habitat by Sierra Nevada bighorn sheep

AbstractTo improve lifetime reproductive success, maternal ungulates should pursue behavioral strategies that reduce risk of offspring mortality. Predation is a leading cause of neonatal mortality; thus, maternal ungulates should select habitat that reduces risk of predation on vulnerable neonates. We examined selection of habitat across subpopulations of federally endangered Sierra Nevada bighorn sheep (Ovis canadensis sierrae) within Sierra Nevada, California, USA, 2008–2018. Our objectives were to understand how maternal Sierra Nevada bighorn minimize risk of predation through selection of habitat and to quantify current and future potential neonatal habitat across the Sierra Nevada. Mountain lions (Puma concolor) are the predominant predators of adult Sierra Nevada bighorn; thus, we hypothesized females would select habitat that minimized risk of predation from mountain lions. We developed a used‐available resource selection function to quantify patterns of habitat selection and produced predictive maps identifying highly selected lambing habitat across the Sierra Nevada. Our top model demonstrated females selected habitat where the relative probability of encountering mountain lions was low and near escape terrain. Selection for vegetation type was dependent on risk of encounter with mountain lions; when risk of encounter was low, females selected shrub cover. This suggests that when risk of encountering mountain lions was low, females may have selected areas with dense shrubs to reduce risk of being detected by other predators such as coyotes (Canis latrans) and golden eagles (Aquila chrysaetos). As risk of encountering mountain lions increased, females avoided all vegetation types other than barren, suggesting that despite increased risk of encounter, females may have been able to mitigate overall mortality risk by selecting habitat where approaching mountain lions could be detected and avoided. Our predictive models and resulting maps demonstrate differences in prevalence and connectivity of highly selected lambing habitat across subpopulations, which may explain differences in lamb recruitment and adequacy of lambing habitat observed among subpopulations. Recolonization into historical ranges and increasing connectivity between Sierra Nevada bighorn subpopulations is an important conservation need for species recovery and long‐term viability of fragmented subpopulations.

Resource selection functions of black‐tailed prairie dogs in Native nations of Montana

AbstractThe black‐tailed prairie dog (Cynomys ludovicianus) is a keystone species of North American short‐ and mixed‐grass temperate grasslands with critical importance for multiple species of conservation concern. Low population numbers due to habitat and social constraints as well as disease require conservation and management actions. To identify potential habitat and future relocation sites, we evaluated 6 statistical techniques to predict the optimal resource selection function model for black‐tailed prairie dog habitat in 3 Native nations of Montana. Random forest models performed best across our study area and included grass coverage and climatic and topographic variables as the most important predictors of prairie dog occupancy. Using predictive habitat models in conjunction with land‐use designations can refine conservation planning to support wildlife population objectives where there are foundations for long‐term success. Our analysis also serves as a guide for assessing habitat suitability, connectivity, and restoration for additional species dependent or interconnected with black‐tailed prairie dogs.

Invasion of annual grasses following wildfire corresponds to maladaptive habitat selection by a sagebrush ecosystem indicator species

Numerous wildlife species within semi-arid shrubland ecosystems across western North America are experiencing substantial habitat loss and fragmentation. These changes in habitat are often attributed to a diverse suite of factors including prolonged and increasingly severe droughts, conifer expansion, anthropogenic development, domestic and feral livestock grazing, and invasion of exotic annual grasses, which promotes increased wildfire frequency and severity. Greater sage-grouse ( Centrocercus urophasianus ; hereafter, sage-grouse) are considered an indicator of sagebrush ecosystem health and have experienced widespread population decline associated with habitat loss and degradation, as well as changes in predator communities. Our objectives were to model and map sage-grouse habitat selection and survival during the important brood-rearing life stage in relation to landscape-scale environmental predictors. Furthermore, we sought to understand impacts of wildfire and annual grass invasion on brood habitat, as these accelerated disturbance regimes are a primary cause of habitat loss within the Great Basin region of the USA. We used a hierarchical Bayesian modeling framework to estimate resource selection functions and survival for early and late brood-rearing stages of sage-grouse in relation to a broad suite of habitat characteristics evaluated at multiple spatial scales within the Great Basin from 2009 to 2019. Sage-grouse selected for greater perennial grass cover, higher relative elevations, and areas closer to springs and wet meadows during both early and late brood-rearing. Terrain characteristics, including heat load and aspect, were important in survival models, as was variation in shrub height. We also found strong evidence for higher survival for both early and late broods within previously burned areas, but survival within burned areas decreased as annual grass cover (i.e. cheatgrass, Bromus tectorum ) increased. This interaction effect demonstrates how invasion of annual grasses into burned areas, which has become prevalent in Great Basin sagebrush ecosystems, can lead to maladaptive habitat selection by brood-rearing greater sage-grouse. Understanding these complex relationships aids wildlife conservation and habitat management as wildfire and annual grass cycles continue to accelerate across western ecosystems.

Temporal mismatch in space use by a sagebrush obligate species after large‐scale wildfire

AbstractThe increase in size and frequency of wildfires in sagebrush steppe ecosystems has significant impacts on sagebrush obligate species. We modeled seasonal habitat use by female greater sage‐grouse (Centrocercus urophasianus) in the Trout Creek Mountains of Oregon and Nevada, USA, to identify landscape characteristics that influenced sage‐grouse habitat selection and to create predictive surfaces of seasonal use 1 and 7 years postfire. We developed three resource selection function models using GPS location data from 2013 to 2019 for three biologically distinct seasons (breeding, n = 149 individuals: 8 March–12 June; summer, n = 140 individuals: 13 June–20 October; and winter, n = 94 individuals: 21 October–7 March). For all seasons, by the fourth or fifth year postfire, sage‐grouse selected for unburned patches more than all other burn severity patches and the use of unburned areas in comparison with burned areas increased through time. During the breeding season, sage‐grouse selected for low‐sagebrush (Artemisia arbuscula)‐dominated ecosystems and areas with low biomass (normalized difference vegetation index). During summer, sage‐grouse selected for areas with higher annual and perennial grasses and forb cover, and areas that had higher biomass. During winter, sage‐grouse selected for areas of intact sagebrush on less rugged terrain. For the winter and breeding season, there was a positive linear relationship between annual grasses and forb cover through time. Seven years postfire (2019), the area predicted to have a high probability of use in each seasonal range decreased (breeding: 16.4%; summer: 12.2%; and winter: 4.2%), while the area predicted to have low or low‐medium probability of use increased (breeding: 14.5%; summer: 22.5%; and winter: 22.8%) when compared to the first year following the wildfire (2013). Our results demonstrated a 4‐ to 5‐year time lag before female sage‐grouse adapted to a disturbed landscape began avoiding burned areas more than intact, unburned habitats. This mismatch in ecological response may imply declines in habitat availability for sage‐grouse and may destabilize population vital rates. Spatially explicit models can aid in identifying priority areas for restoration efforts and conservation actions to mitigate the impacts of future disturbances.

Modeling the spatial and temporal dynamics of land‐based polar bear denning in Alaska

AbstractAlthough polar bears (Ursus maritimus) of the Southern Beaufort Sea (SBS) subpopulation have commonly created maternal dens on sea ice in the past, maternal dens on land have become increasingly prevalent as sea ice declines. This trend creates conditions for increased human–bear interactions associated with local communities and industrial activity. Maternal denning is a vulnerable period in the polar bear life cycle, and den disturbance could lead to den abandonment, cub mortality, and negative population impacts. We used published long‐term data to parameterize a Bayesian hierarchical model of annual land den abundance during 2000–2015, in 4 regions of northern Alaska, USA, with current or potential future oil and gas activity. We also estimated long‐term (1982–2015) shifts in the spatial distribution of land dens within and among regions using kernel density estimation and assessed the influence of local and regional sea ice and snow conditions on den site selection using a random forest resource selection function. Our objectives were to quantify current den distribution and abundance, test for distributional shifts over time, and investigate if those shifts could be attributed to environmental variables related to den habitat. We estimated that between 2000 and 2015, the SBS contained a median 123 dens in a typical year, of which 68 occurred on land. The region between the Colville and Canning rivers, where most current oil and gas activity occurred, also contained the largest fraction of land dens. Overall, land dens were disproportionately concentrated on barrier islands and on land within 30 km of the coast. The probability of dens occurring on land varied from 1982–1999 to 2000–2015 in all regions, and the overall distribution of land dens shifted west between those periods. This regional‐scale change in den distribution was predictable based on spatial and temporal heterogeneity in snow and sea ice conditions within 50 km of individual den locations. Land denning is likely to become increasingly common with continued sea ice loss, and our results and modeling framework could be used to design additional mitigation strategies for reducing the risk of incidental take due to den disturbance.

Displacement Effects of Conservation Grazing on Red Deer (Cervus elaphus) Spatial Behaviour

Conservation grazing uses semi-feral or domesticated herbivores to limit encroachment in open areas and to promote biodiversity. However, we are still unaware of its effects on wild herbivores. This study investigates the influence of herded sheep and goats on red deer (Cervus elaphus) spatial behavior by testing three a-priori hypotheses: (i) red deer are expected to avoid areas used by livestock, as well as adjacent areas, when livestock are present, albeit (ii) red deer increase the use of these areas when sheep and goats are temporarily absent and (iii) there is a time-lagged disruption in red deer spatial behavior when conservation grazing practice ends. Using GPS-telemetry data on red deer from a German heathland area, we modelled their use of areas grazed by sheep and goats, using mixed-effect logistic regression. Additionally, we developed seasonal resource selection functions (use-availability design) to depict habitat selection by red deer before, during, and after conservation grazing. Red deer used areas less during conservation grazing throughout all times of the day and there was no compensatory use during nighttime. This effect mostly persisted within 21 days after conservation grazing. Effects on habitat selection of red deer were detectable up to 3000 meters away from the conservation grazing sites, with no signs of either habituation or adaption. For the first time, we demonstrate that conservation grazing can affect the spatio-temporal behavior of wild herbivores. Our findings are relevant for optimizing landscape and wildlife management when conservation grazing is used in areas where wild herbivores are present.

Resource Selection of Domestic Sheep on Mountainous Summer Habitat in Utah, United States

Past research has documented livestock grazing patterns and dynamics across pastoral landscapes. We used spatial locations of domestic range sheep (Ovis aries) obtained from Global Positioning System collars to study habitat selection on summer mountain habitat North of Scofield Reservoir Utah, United States. Data were collected between the months of July to September 2020. We developed a resource selection function to determine the influence of slope, distance to water, aspect, ruggedness, elevation, and vegetation types on habitat selection by sheep while grazing on summer mountain habitat. We found sheep selected for sites closer to water, with more gentle terrain, higher in elevation, and north-facing slopes. Vegetation types were less predictive, ostensibly due to the lack of species composition information in available geographic information system layers and the possibility of sheep being herded to avoid areas of overuse. Although it is often assumed that sheep use slopes more than their heavier and larger cattle counterparts, overall they tended to avoid steep slopes compared with all other predictor variables. This information on selection for higher elevations and avoidance of steep slopes can be used to improve livestock management practices including flock management that increases sheep foraging patterns and energy efficiency.

Brown Bear Food-Probability Models in West-European Russia: On the Way to the Real Resource Selection Function

Most habitat suitability models and resource selection functions (RSFs) use indirect variables and habitat surrogates. However, it is known that in order to adequately reflect the habitat requirements of a species, it is necessary to use proximal resource variables. Direct predictors should be used to construct a real RSF that reflects the real influence of main resources on species habitat use. In this work, we model the spatial distribution of the main food resources of brown bear Ursus arctos L. within the natural and human-modified landscapes of the Central Forest State Nature Reserve (CFNR) for further RSF construction. Food-probability models were built for Apiaceae spp. (Angelica sylvestris L., Aegopodium podagraria L., Chaerophyllum aromaticum L.), Populus tremula L., Vaccinium myrtillus L., V. microcarpum (Turcz. ex Rupr.) Schmalh., V. oxycoccos L., Corylus avellana L., Sorbus aucuparia L., Malus domestica Borkh., anthills, xylobiont insects, social wasps and Alces alces L. using the MaxEnt algorithm. For model evaluation, we used spatial block cross-validation and held apart fully independent data. The true skill statistic (TSS) estimates ranged from 0.34 to 0.95. Distribution of Apiaceae forbs was associated with areas having rich phytomass and moist conditions on southeastern slopes. Populus tremula preferred areas with phytomass abundance on elevated sites. Vaccinium myrtillus was confined to wet boreal spruce forests. V. microcarpum and V. oxycoccos were associated with raised bogs in depressions of the terrain. Corylus avellana and Sorbus aucuparia preferred mixed forests on elevated sites. Distribution of Malus domestica was associated with meadows with dry soils in places of abandoned cultural landscapes. Anthills were common on the dry soils of meadows, and the periphery of forest areas with high illumination and low percent cover of tree canopy. Moose preferred riverine flood meadows rich in herbaceous vegetation and sparse mixed forests in spring and early summer. The territory of the human-modified CFNR buffer zone was shown to contain a higher variety of food resources than the strictly protected CFNR core area.

Habitat selection in a fluctuating ground squirrel population: Density-dependence and fitness consequences.

Investigating individual‐based habitat settlement decisions is a central theme in ecology, yet studies that quantify density‐dependent habitat selection or tie fitness to resource selection decisions remain rare. We quantified habitat selection in golden‐mantled ground squirrels (Callospermophilus lateralis) across two spatial scales (home‐range placement, and occurrence within the home range) by using 11 consecutive years of data on individual space use, and we used resource selection functions and multilevel modeling to address how habitat preferences may be influenced by density or linked to fitness outcomes. Squirrels preferred dry meadow over other habitat types (wet meadow, aspen, spruce, and willow) at both spatial scales. Squirrels were more likely to use dry meadow that contained shorter vegetation and vision‐enhancing prominences such as rocks (“perches”). The use of dry meadow at each scale was not influenced by changes in density. The use of dry meadow did not lead to increased litter size, pre‐hibernation mass, or survival. However, squirrels that experienced a greater number of perches or lower local densities had higher survival rates. Our results suggest that a lack of visual obstruction, probably facilitating detection of predators, drives habitat selection in this system. Surprisingly, squirrels maintained their preference for dry meadow as density increased, and they experienced reduced survival as a result. This work furthers our understanding about the causes and consequences of changes in habitat use, informing wildlife management and conservation.

Comparing Methods of Defining Priority Areas for Greater Sage-Grouse

Wildlife managers delineate priority areas for species to define critical habitat and to prioritize management efforts. Each method used to identify priority areas involves data that can be unavailable or expensive to obtain. Therefore, it is of interest to compare spatial efficiency between methods used for defining priority areas. We compared priority areas created using different methods and data types. We used resource selection function (RSF) models to predict areas of high use and generated a map depicting ≥ 90% predicted use in three seasons; it was 1,143 km2, encompassed 91% of nests, 68% of summer locations, and 71% of winter locations. We compared the RSF priority area to priority areas developed using two alternative methods: (1) modified conservation buffer, and (2) utilization distribution (UD) models. The modified conservation buffer method was used by South Dakota Game, Fish and Parks in 2014 to delineate a priority area by buffering active lek sites by 6.4 km, including connectivity corridors defined via expert opinion, and known high use areas. The priority area generated by the modified conservation buffer method was 3,977 km2, encompassed 95% of nest locations, 92% of spring/summer locations, and 99% of winter locations. Lastly, we developed a priority area using combined UDs from radio-tracking data gathered during spring/summer, and winter and included a lek buffer encompassing 90% of known nest-sites. This priority area was 3,498 km2, encompassed 99% of nests, 98% of spring/summer locations, and 97% of winter locations. The priority area generated by RSF models was the smallest and encompassed the least number of nests and spring/summer and winter locations but was considered the most spatially efficient; it had the most nests, spring/summer locations, and winter locations per 100 km2. The UD and modified conservation buffer methods created priority areas that were similar in size and spatial efficiency. The modified conservation buffer method encompassed >90% of known sage-grouse locations and nests, indicating that in the absence of detailed movement data and more sophisticated modeling, the method can be sufficient in developing an adequate priority area.

High dependence on protected areas by the endangered giant armadillo in Argentina

A combination of technics was used to assess landscape variables associated with the presence of the globally vulnerable giant armadillo (Priodontes maximus) in its southernmost distribution in the Chaco region of Argentina. Between 2017 and 2019, 369 km of foot and vehicle transects were run to search and record indirect evidence of the species (burrows and feeding excavations) in areas with different level of protection, including two national parks, three provincial parks, and non-protected areas. Distance sampling was used to estimate density of excavations and effective strip width sampled to estimate the surveyed area. Resource selection functions (RSFs) were used to assess the variables associated to its presence by comparing locations of excavations with available habitat within surveyed areas. In these RSF models covariates that may affect habitat use and survival of giant armadillos were included: three categorical ones: soil type, vegetation cover (forests vs. grasslands), protection level (national park, provincial park, non-protected), and five continuous variables: distance to nearest river, distance to nearest national park, distance to closest protected area, distance to nearest transformed area, and distance to natural grasslands. Habitat use was modelled pooling together burrows and feeding excavations, and models were validated with a pool of records previously excluded from the analysis. A total of 104 records of burrows and 344 of feeding excavations were recorded. The probability of occurrence of giant armadillo excavations was much higher within forests, within or near protected areas, and increased with the distance to rivers, to transformed areas, and to grasslands. In the study area, only 10% of the landscape surveyed has good- to high-probability of occurrence of giant armadillos. The maintenance of large surfaces of native forests and the consolidation, improvement, and connectivity among protected areas seem to be essential for the long-term survival of the endangered giant armadillo in Argentina.

Modelling potential habitat suitability for critically endangered Arabian leopards (Panthera pardus nimr) across their historical range in Saudi Arabia

Camera trapping can detect and monitor rare species in landscapes spanning thousands of square kilometres but placement of cameras in areas where the animals most likely occur will increase detection success. This vital information is lacking for the critically endangered Arabian leopard (Panthera pardus nimr) that has undergone a 90% decline across its range in Saudi Arabia. We aimed to identify suitable Arabian leopard habitat and potential population capacity in Saudi Arabia using data from leopards living in ecologically analogous habitat in South Africa and Oman. We developed a resource selection function (RSF) from 14 leopards’ GPS data in the Cederberg, South Africa, and validated the model using three leopards in the Little Karoo, and two Arabian leopards in Oman. We then projected the model to the historical range of Arabian leopards in Saudi Arabia to estimate likely leopard locations and potential population sizes based on home range metrics. The RSF successfully discriminated between used and available locations (specificity = 96.7%) and had high predictive ability (Rho > 0.9). Leopards selectively used areas away from human settlements and roads, with high enhanced vegetation index, and intermediate slopes and elevations. Saudi Arabia could theoretically host 4 distinct populations totalling 162–362 Arabian leopard females, depending on home range size. Camera traps deployed in the south-western mountains of Saudi Arabia may be most likely to detect remnant populations of Arabian leopards. Further research is needed into the local abundance of prey species and human activity to ensure the persistence of suitable leopard ranges and inform conservation actions.

Environmental drivers of beluga whale distribution in a changing climate: a case study of summering aggregations in the Mackenzie Estuary and Tarium Niryutait Marine Protected Area

During summer, the Eastern Beaufort Sea beluga whale ( Delphinapterus leucas (Pallas, 1776)) population aggregates in the waters of the Mackenzie Estuary and Tarium Niryutait Marine Protected Area (TNMPA). Guided by local communities’ priorities, this study aimed to better understand beluga summer habitat selection and to examine whether shifts in beluga distribution are expected under a changing climate. We used a resource selection function (RSF) based on aerial survey data and satellite remote sensing images to estimate the likelihood of beluga presence as a function of environmental conditions. The RSF revealed that belugas selected warm and turbid waters, with suspended particulate matter concentrations and sea surface temperatures ranging above average estuarine values. These specific conditions support hypotheses on the ecological roles of estuaries for belugas such as providing a thermal advantage for their calves or for beluga epidermal moulting. Using a diachronic analysis, we found a distribution shift towards coastal and inshore waters, areas already experiencing effects of climate change. Thus, the current distribution may reflect beluga responses to a changing climate, selecting warmer and more turbid areas. Our finding provides insight into current and evolving beluga habitat and habitat selection under a changing climate, which may help inform beluga management in the TNMPA.

Beyond resource selection: emergent spatio–temporal distributions from animal movements and stigmergent interactions

A principal concern of ecological research is to unveil the causes behind observed spatio–temporal distributions of species. A key tactic is to correlate observed locations with environmental features, in the form of resource selection functions or other correlative species distribution models. In reality, however, the distribution of any population both affects and is affected by those surrounding it, creating a complex network of feedbacks causing emergent spatio–temporal features that may not correlate with any particular aspect of the underlying environment. Here, we study the way in which the movements of populations in response to one another can affect the spatio–temporal distributions of ecosystems. We construct a stochastic individual‐based modelling (IBM) framework, based on stigmergent interactions (i.e. organisms leave marks which cause others to alter their movements) between and within populations. We show how to gain insight into this IBM via mathematical analysis of a partial differential equation (PDE) system given by a continuum limit. We show how the combination of stochastic simulations of the IBM and mathematical analysis of PDEs can be used to categorise emergent patterns into homogeneous versus heterogeneous, stationary versus perpetually‐fluctuating and aggregation versus segregation. In doing so, we develop techniques for understanding spatial bifurcations in stochastic IBMs, grounded in mathematical analysis. Finally, we demonstrate through a simple example how the interplay between environmental features and between‐population stigmergent interactions can give rise to predicted spatial distributions that are quite different to those predicted purely by accounting for environmental covariates.