A dynamic multi‐scale occupancy model to estimate temporal dynamics and hierarchical habitat use for nomadic species

Distribution models are increasingly being used to understand how landscape and climatic changes are affecting the processes driving spatial and temporal distributions of plants and animals. However, many modeling efforts ignore the dynamic processes that drive distributional patterns at different scales, which may result in misleading inference about the factors influencing species distributions. Current occupancy models allow estimation of occupancy at different scales and, separately, estimation of immigration and emigration. However, joint estimation of local extinction, colonization, and occupancy within a multi‐scale model is currently unpublished. We extended multi‐scale models to account for the dynamic processes governing species distributions, while concurrently modeling local‐scale availability. We fit the model to data for lark buntings and chestnut‐collared longspurs in the Great Plains, USA, collected under the Integrated Monitoring in Bird Conservation Regions program. We investigate how the amount of grassland and shrubland and annual vegetation conditions affect bird occupancy dynamics and local vegetation structure affects fine‐scale occupancy. Buntings were prevalent and longspurs rare in our study area, but both species were locally prevalent when present. Buntings colonized sites with preferred habitat configurations, longspurs colonized a wider range of landscape conditions, and site persistence of both was higher at sites with greener vegetation. Turnover rates were high for both species, quantifying the nomadic behavior of the species. Our model allows researchers to jointly investigate temporal dynamics of species distributions and hierarchical habitat use. Our results indicate that grassland birds respond to different covariates at landscape and local scales suggesting different conservation goals at each scale. High turnover rates of these species highlight the need to account for the dynamics of nomadic species, and our model can help inform how to coordinate management efforts to provide appropriate habitat configurations at the landscape scale and provide habitat targets for local managers.     

Transient persistence of bobcat (Lynx rufus) occurrence throughout a human-dominated landscape

Human developments have detrimental effects on wildlife populations globally with carnivores being particularly sensitive. The bobcat (Lynx rufus) is often considered an adaptable mesocarnivore that occurs throughout varied landcover types within its wide distribution and may be less susceptible to the negative effects of development. Our objectives were to investigate the landscape occupancy dynamics of bobcats in a highly developed and densely populated region of the northeastern United States to evaluate the sensitivity of bobcat occurrence to natural and anthropogenic landscape features. We established a large-scale camera trapping survey throughout Rhode Island, USA, sampling from 2018 to 2020. Using dynamic occupancy models, we found initial site occupancy was positively influenced by the amount of forested wetland habitat, while increasing road density and shrub cover negatively influenced the probability of site colonization. Surprisingly, we found no hypothesized variables to influence site-level extirpation probability, or any seasonal effects on dynamic parameters. Lastly, we found that forest cover and road density negatively influenced the probability of detection. The probability of occupancy was high, >0.8, throughout much of the study area (49%), but we also found relatively high site transients, with the probability a site would change occurrence status from season to season at ≈0.27 in the majority of the study area (70%). Our results show that although bobcats can persist in human-dominated landscapes, they require contiguous natural areas to do so. Future expansion of road infrastructure may reduce habitat connectivity and increase road mortalities, thus jeopardizing the population.     

Sheoak woodlands: a newly identified habitat for western ringtail possums

Although critically endangered western ringtail possums (Pseudocheirus occidentalis) have been recorded from a variety of vegetation types in southwestern Australia, the extent to which many of these vegetation types are occupied by the species remains unknown. We conducted spotlight surveys for western ringtail possums between March and April 2018 in Albany, southwestern Australia, to determine the species’ occupancy in 2 vegetation types. Using occupancy models, we demonstrated that sheoak (Allocasuarina fraseriana) woodlands, previously unrecognized as providing western ringtail possum habitat, support the species, although the median probability of their occupancy was lower than in marri (Corymbia calophylla) and eucalypt (Eucalyptus marginata and E. staeri) woodlands. Use of trees and other habitat components by western ringtail possums varied within and between vegetation types. Sheoak woodlands are likely critical for western ringtail possums and given the apparent flexibility in vegetation types used by the species, investigation of the potential value of other vegetation types for this species has conservation merit. © 2019 The Wildlife Society.     

Effect of detection heterogeneity in occupancy‐detection models: an experimental test of time‐to‐first‐detection methods

Imperfect detection can bias estimates of site occupancy in ecological surveys but can be corrected by estimating detection probability. Time‐to‐first‐detection (TTD) occupancy models have been proposed as a cost–effective survey method that allows detection probability to be estimated from single site visits. Nevertheless, few studies have validated the performance of occupancy‐detection models by creating a situation where occupancy is known, and model outputs can be compared with the truth. We tested the performance of TTD occupancy models in the face of detection heterogeneity using an experiment based on standard survey methods to monitor koala Phascolarctos cinereus populations in Australia. Known numbers of koala faecal pellets were placed under trees, and observers, uninformed as to which trees had pellets under them, carried out a TTD survey. We fitted five TTD occupancy models to the survey data, each making different assumptions about detectability, to evaluate how well each estimated the true occupancy status. Relative to the truth, all five models produced strongly biased estimates, overestimating detection probability and underestimating the number of occupied trees. Despite this, goodness‐of‐fit tests indicated that some models fitted the data well, with no evidence of model misfit. Hence, TTD occupancy models that appear to perform well with respect to the available data may be performing poorly. The reason for poor model performance was unaccounted for heterogeneity in detection probability, which is known to bias occupancy‐detection models. This poses a problem because unaccounted for heterogeneity could not be detected using goodness‐of‐fit tests and was only revealed because we knew the experimentally determined outcome. A challenge for occupancy‐detection models is to find ways to identify and mitigate the impacts of unobserved heterogeneity, which could unknowingly bias many models.     

Habitat occupancy of sloth bear Melursus ursinus in Chitwan National Park,Nepal

Mammals have experienced a massive decline in their populations and geographic ranges worldwide. The sloth bear, Melursus ursinus (Shaw, 1791), is one of many species facing conservation threats. Despite being endangered in Nepal, decades of inattention to the situation have hindered their conservation and management. We assessed the distribution and patterns of habitat use by sloth bears in Chitwan National Park (CNP), Nepal. We conducted sign surveys from March to June, 2020, in 4 × 4 km grids (n = 45). We collected detection/non‐detection data along a 4‐km trail that was divided into 20 continuous segments of 200 m each. We obtained environmental, ecological, and anthropogenic covariates to understand determinants of sloth bear habitat occupancy. The data were analyzed using the single‐species single‐season occupancy method, with a spatially correlated detection. Using repeated observations, these models accounted for the imperfect detectability of the species to provide robust estimates of habitat occupancy. The model‐averaged occupancy estimate for the sloth bear was 69% and the detection probability was 0.25. The probability of habitat occupancy by sloth bears increased with the presence of termites and fruits and in rugged, dry, open, undisturbed habitats. Our results indicate that the sloth bear is elusive, functionally unique, and widespread in CNP. Future conservation interventions and action plans aimed at sloth bear management must adequately consider their habitat requirements.     

Fine‐scale ecological and anthropogenic variables predict the habitat use and detectability of sloth bears in the Churia habitat of east Nepal

Once widespread throughout the tropical forests of the Indian Subcontinent, the sloth bears have suffered a rapid range collapse and local extirpations in the recent decades. A significant portion of their current distribution range is situated outside of the protected areas (PAs). These unprotected sloth bear populations are under tremendous human pressures, but little is known about the patterns and determinants of their occurrence in most of these regions. The situation is more prevalent in Nepal where virtually no systematic information is available for sloth bears living outside of the PAs. We undertook a spatially replicated sign survey‐based single‐season occupancy study intending to overcome this information gap for the sloth bear populations residing in the Trijuga forest of southeast Nepal. Sloth bear sign detection histories and field‐based covariates data were collected between 2 October and 3 December 2020 at the 74 randomly chosen 4‐km² grid cells. From our results, the model‐averaged site use probability (ψ ± SE) was estimated to be 0.432 ± 0.039, which is a 13% increase from the naïve estimate (0.297) not accounting for imperfect detections of sloth bear signs. The presence of termite mound and the distance to the nearest water source were the most important variables affecting the habitat use probability of sloth bears. The average site‐level detectability (p ± SE) of sloth bear signs was estimated to be 0.195 ± 0.003 and was significantly determined by the index of human disturbances. We recommend considering the importance of fine‐scale ecological and anthropogenic factors in predicting the sloth bear‐habitat relationships across their range in the Churia habitat of Nepal, and more specifically in the unprotected areas.