Prioritizing areas for conservation outside the existing protected area network in Bhutan: the use of multi-species, multi-scale habitat suitability models

Abstract

Context Understanding the environmental and anthropogenic factors influencing habitat selection of multiple species is a foundation for quantifying human impacts on biodiversity and developing effective conservation measures. Objectives To determine the effect of multiple scales of environmental/topographic and anthropogenic variables and landscape patterns on habitat suitability of terrestrial mammals in Bhutan, assess the effectiveness of the current protected area network, identify areas of high species richness outside of the existing protected area, and evaluate the potential effectiveness of indicator and umbrella species for conservation planning. Methods We modelled multi-scale habitat selection of sixteen species of terrestrial mammals across Bhutan using data from a nation-wide camera trap survey. We used the predicted species distribution maps to assess the multi-species conservation effectiveness of the existing protected area network. We performed simulations to identify high priority areas for multiple species based on their habitat suitability, proximity to existing protected areas and overall connectivity within the predicted distribution of species. We used correlation analysis among predicted occurrence maps and multivariate cluster analysis to identify potential indicator species. We evaluated the potential utility of each species as umbrella species by assessing how well optimal protected areas for that species would protect suitable habitat for all 16 species simultaneously. Results Protected areas and forest cover were strongly associated with habitat use of most modelled species. Additionally, topographical features, like terrain roughness and slope position, contributed to habitat selection of multiple species, but often in different ways. Environmental and topographical variables were mostly selected at medium to broad scales. Anthropogenic variables (agriculture and built-up areas) were negatively associated with habitat suitability of most species at both fine and broad scales. Conservation effectiveness assessment of existing protected areas found protected areas in south-central Bhutan have high effectiveness in terms of both mean and total richness protected. Similarly, biological corridors in the south-central region offered high mean richness protection. Our simulation of optimal areas for additional protection found areas abutting protected areas in southern Bhutan offered high relative species richness protection. Our umbrella species analysis found muntjac, wild pig, serow, sambar and Asian golden cat are the most effective umbrella species for broader biodiversity protection. Our indicator species analysis found tiger, gaur, dhole, clouded leopard, Asian black bear and common leopard as effective indicator species. Conclusions This study highlights the need to protect optimally located species-rich areas outside the current protected areas. This kind of multi-species habitat assessment provides important information to optimize future conservation and development plans at national and regional scales.

Urban expansion and infrastructure development reduce habitat suitability for Asian elephants in southwestern China

“…Scales used in species‐distribution modeling affected the elephant response (reflected by presence) to environmental variables and measurement of variables at coarse scales (8 km, 16 km) are more likely to reveal their links with elephant habitat selection, especially in the case of anthropogenic variables. Scale is important when exploring elephant environment relationships and its optimization is required, which has been emphasized in a case study of African savanna elephants (De Knegt et al 2011), though only 2 recent studies of Asian elephants (de la Torre et al 2021, Penjor et al 2021) account for scale optimization. The 8‐ and 16‐km radii cover areas of approximately 200 km 2 and 804 km 2 , respectively, equivalent to home‐range sizes commonly recorded for Asian elephants (Fernando et al 2008, Moßbrucker et al 2016), and are likely to account the coarse scales at which elephant presence was influenced by environmental variables.…”

“…The same effects of roads and buildings at a coarse scale have been reported for a variety of large mammals. For example, road density and buildings had the largest influence on presence of snow leopard at scales of between 19 km and 29 km in Gansu Province and Tibet (Atzeni et al 2020), and affected presence at even larger scales of 32 km for the common leopard ( Panthera pardus ), clouded leopard, and Himalaya serow ( Capricornis thar ) in Bhutan (Penjor et al 2021).…”

“…Such variability is likely to apply also to the Asian elephant, which has daily travel (displacement) distances up to 10 km (Alfred et al 2012), and home ranges sizes that can extend over hundreds of square kilometers (e.g., 34–400 km 2 in Sri Lanka and 210–997 km 2 in Sumatra; Fernando et al 2008, Moßbrucker et al 2016). Though few studies of Asian elephants have adopted a multiple‐scale approach, 2 examples reveal that water availability influenced elephant presence in Peninsular Malaysia at the 4‐km scale (de la Torre et al 2021) but at a much larger (16 km) scale in Bhutan (Penjor et al 2021).…”

Multi‐scale, multivariate community models improve designation of biodiversity hotspots in the Sunda Islands

“…Cushman et al, 2010). However, Carroll et al (2001), Roberge & Angelstam (2004), Cushman & Landguth (2012) and Penjor et al (2021) demonstrated that conservation strategies based on combinations of multiple umbrella species cover broader ranges of habitat gradients, and can effectively ensure the protection of a higher fraction of sympatric species. Our analysis confirms the importance of carnivores as proxies of biodiversity and, in particular, of the more common and less specialized ones, such as Sunda stink-badger Mydaus javanensis in Borneo and Sunda leopard cat Prionailurus javanensis in Sumatra.…”

Habitat Suitability Modeling to Inform Seascape Connectivity Conservation and Management

“…As the integration of three-dimensional surfaces alongside standard twodimensional predictors becomes more common in spatial modeling [28,29], the value of HSMs and HSM-derived cost surfaces for connectivity analysis will likely increase. Although realistic HSMs can help bridge the gap between connectivity modeling and conservation planning, applications of this multi-step approach have been applied only to terrestrial landscapes [26,30,31].…”