Defining habitat covariates in camera-trap based occupancy studies

Occupancy of the Ethiopian endemic Moorland Francolin in pristine and degraded Afroalpine biome using a camera trap approach

Occupancy modeling is an essential tool for understanding species-habitat associations, thereby helping to plan the conservation of rare and threatened wildlife species. The conservation status and ecology of several avian species, particularly ground-dwelling birds, are poorly known in Ethiopia. We used camera trap-based occupancy modeling to investigate habitat covariate influence on occupancy (Ψ) and detection probability (ρ) estimates of Moorland Francolins Scleroptila psilolaema from spatially replicated surveys across both relatively pristine and disturbed landscapes in the Afroalpine biome of Ethiopia. Model-averaged estimate of ψ ^ across all sites was 0.76 (SD = 0.28) and ρ ^ was 0.77 (SD = 0.13) in the pristine landscape. The ψ ^ of the species in the disturbed landscape was 0.56 (SD = 0.19) and ρ ^ was 0.48 (SD = 0.06). As hypothesized, based on our model-averaged beta coefficient estimates (βmean ± SE), predators significantly negatively influenced the occupancy of Moorland Francolins in pristine habitat. We also found a significant positive association of occupancy with herb species richness. Contrary to our prediction, distance to road significantly negatively influence the occupancy of the species, suggesting that occupancy probability was highest in proximity to roadsides and trails in the pristine habitat. There was no significant influence of habitat covariates on the occupancy of the species in the disturbed habitat. The most important covariates that significantly influence the detectability of the species in pristine habitat included sampling occasion and precipitation. The greater occupancy and detectability of this endemic species in the pristine habitat could be linked with the particular conservation status and management of this biodiversity hotspot in the central highlands of Ethiopia. Our results suggest that strict legal enforcement is required to sustainably preserve Moorland Francolins and the ecological integrity of the entire Afroalpine biome. We recommend using camera traps in order to develop realistic and effective conservation and management strategies for rare, sensitive, cryptic, and ground-dwelling animals in the region.

Age Structure, Development and Population Viability of Banteng (Bos javanicus) in Captive Breeding for Ex-Situ Conservation and Reintroduction

Captive breeding is important for ex-situ conservation and the future reintroduction of bovids that become extinct in the wild. The age structure, development, and viability of captive-bred bantengs (Bos javanicus) are important to sustain the long-term reintroduction program in Salakphra Wildlife Sanctuary (SWF) and other areas. This research conducted a long-term population viability analysis (PVA) using height, weight, body condition scores (BSC), age structure, and development in captivity for a sustainable reintroduction program of bantengs in Thailand. Monthly development photographs of 23 founder individuals (12 males and 11 females) were assessed by three banteng experts, two researchers, and three members of the general public. The assessments of weight and BCS were not significantly different among the three groups, while height was underestimated by the general public. The PVA showed that the time to reach the maximum population in a captive banteng program is dependent on the carrying capacity of the habitat. The reduction of a small banteng founder group by the reintroduction of animals into the wild can negatively affect the population growth of the captive group. This information can be used to maintain the population viability of bantengs and sustain ex-situ conservation and the reintroduction program in Thailand and elsewhere.

The effect of habitat and human disturbance on the spatiotemporal activity of two urban carnivores: The results of an intensive camera trap study

With rising urbanization, the presence of urban wildlife is becoming more common, increasing the need for wildlife-friendly spaces in urban planning. Despite this, understanding is limited to how wildlife exploits urban environments and interacts with human populations, and this is vital to our ability to manage and conserve wildlife in urban habitats. Here, we investigate how two urban mammal species, the red fox (Vulpes vulpes) and the European badger (Meles meles), exploit urban environments. Using intensive camera trap surveys, we assessed how habitat and human disturbance influenced the spatiotemporal activity of these species across south-west London. Firstly, we found elevated activity levels of both species at boundaries and within built-up areas, suggesting movement paths follow anthropogenic features. However, badgers were most active in woodland, indicating the importance of high cover habitats suitable for setts and foraging. Secondly, we found badger activity levels were negatively affected by human activity, whilst foxes were unaffected. Further investigation suggested foxes may adapt their activity patterns to avoid human disturbance, with badger activity patterns less plastic. Whilst the results of this study are useful for both the conservation and management of urban wildlife populations, these results also show potential factors which either facilitate or limit wildlife from fully exploiting urban environments.

The Role of Remote Sensing Data in Habitat Suitability and Connectivity Modeling: Insights from the Cantabrian Brown Bear

Ecological modeling requires sufficient spatial resolution and a careful selection of environmental variables to achieve good predictive performance. Although national and international administrations offer fine-scale environmental data, they usually have limited spatial coverage (country or continent). Alternatively, optical and radar satellite imagery is available with high resolutions, global coverage and frequent revisit intervals. Here, we compared the performance of ecological models trained with free satellite data with models fitted using regionally restricted spatial datasets. We developed brown bear habitat suitability and connectivity models from three datasets with different spatial coverage and accessibility. These datasets comprised (1) a Sentinel-1 and 2 land cover map (global coverage); (2) pan-European vegetation and land cover layers (continental coverage); and (3) LiDAR data and the Forest Map of Spain (national coverage). Results show that Sentinel imagery and pan-European datasets are powerful sources to estimate vegetation variables for habitat and connectivity modeling. However, Sentinel data could be limited for understanding precise habitat–species associations if the derived discrete variables do not distinguish a wide range of vegetation types. Therefore, more effort should be taken to improving the thematic resolution of satellite-derived vegetation variables. Our findings support the application of ecological modeling worldwide and can help select spatial datasets according to their coverage and resolution for habitat suitability and connectivity modeling.

A little-known endemic caught in the South-east Asian extinction crisis: the Annamite striped rabbit Nesolagus timminsi

The Annamite mountains of Viet Nam and the Lao People's Democratic Republic (Lao) are an area of exceptional mammalian endemism but intensive poaching has defaunated much of the region, creating an extinction crisis for the endemic species. To make efficient use of limited conservation resources, it is imperative that conservation stakeholders obtain basic information about poorly known and threatened endemics. We present the first comprehensive information on the ecology, distribution and status of the little-known endemic Annamite striped rabbit Nesolagus timminsi. We used a systematic camera-trapping design to study the species in five areas in Viet Nam and Lao. In 29,180 camera-trap-nights we recorded 152 independent events at 36 of 266 stations. We obtained an additional 143 independent detections across 12 stations from a supplementary non-systematic survey. We analysed activity patterns and social behaviour. We also used single-species occupancy models to assess factors that influence occupancy at the landscape scale. We used N-mixture models to obtain local abundance estimates in one target area. The Annamite striped rabbit was found to be nocturnal and primarily solitary. Species occupancy was best explained by a proxy for past hunting pressure, with no significant relationships to current anthropogenic or environmental factors. Local abundance was 0.57 individuals per camera-trap station for one of our sites, and estimated to be zero at the other site where hunting appears to have been more intense. Our results provide information on priority areas for targeted anti-poaching efforts and give the first conservation baseline for the species.

Dynamic occupancy modeling of temperate marine fish in area-based closures

Species distribution models (SDMs) are commonly used to model the spatial structure of species in the marine environment, however, most fail to account for detectability of the target species. This can result in underestimates of occupancy, where nondetection is conflated with absence. The site occupancy model (SOM) overcomes this failure by treating occupancy as a latent variable of the model and incorporates a detection submodel to account for variability in detection rates. These have rarely been applied in the context of marine fish and never for the multiseason dynamic occupancy model (DOM). In this study, a DOM is developed for a designated species of concern, cusk (Brosme brosme), over a four-season period. Making novel use of a high-resolution 3-dimensional hydrodynamic model, detectability of cusk is considered as a function of current speed and algae cover. Algal cover on the seabed is measured from video surveys to divide the study area into two distinct regions: those with canopy forming species of algae and those without (henceforth bottom types). Modeled estimates of the proportion of sites occupied in each season are 0.88, 0.45, 0.74, and 0.83. These are significantly greater than the proportion of occupied sites measured from underwater video observations which are 0.57, 0.28, 0.43, and 0.57. Individual fish are detected more frequently with increasing current speed in areas lacking canopy and less frequently with increasing current speed in areas with canopy. The results indicate that, where possible, SDM studies for all marine species should take account of detectability to avoid underestimating the proportion of sites occupied at a given study area. Sampling closed areas or areas of conservation often requires the use of nonphysical, low impact sampling methods like camera surveys. These methods inherently result in detection probabilities less than one, an issue compounded by time-varying features of the environment that are rarely accounted for marine studies. This work highlights the use of modeled hydrodynamics as a tool to correct some of this imbalance.

Demarcation of Prime Farmland Protection Areas around a Metropolis Based on High-Resolution Satellite Imagery

Prime farmland (PF) is defined as high-quality farmland and a prime farmland protection area (PFPA, including related roads, waters and facilities) is a region designated for the special protection of PF. However, rapid urbanization in China has led to a tremendous farmland loss and to the degradation of farmland quality. Based on remote sensing and geographic information system technology, this study developed a semiautomatic procedure for designating PFPAs using high-resolution satellite imagery (HRSI), which involved object-based image analysis, farmland composite evaluation, and spatial analysis. It was found that the HRSIs can provide elaborate land-use information, and the PFPA demarcation showed strong correlation with the farmland area and patch distance. For the benefit of spatial planning and management, different demarcation rules should be applied for suburban and exurban areas around a metropolis. Finally, the overall accuracy of HRSI classification was about 80% for the study area, and high-quality farmlands from evaluation results were selected as PFs. About 95% of the PFs were demarcated within the PFPAs. The results of this study will be useful for PFPA planning and the methods outlined could help in the automatic designation of PFPAs from the perspective of the spatial science.