Landscape Ecol (2021) 36:1281–1309 https://doi.org/10.1007/s10980-021-01225-7 RESEARCH ARTICLE Prioritizing areas for conservation outside the existing protected area network in Bhutan: the use of multi‑species, multi‑scale habitat suitability models Ugyen Penjor · Żaneta Kaszta · David W. Macdonald · Samuel A. Cushman Received: 21 October 2020 / Accepted: 22 February 2021 / Published online: 15 March 2021 © The Author(s) 2021 Abstract Objectives To determine the efect of multiple Context Understanding the environmental and scales of environmental/topographic and anthropo- anthropogenic factors infuencing habitat selection genic variables and landscape patterns on habitat suit- of multiple species is a foundation for quantifying ability of terrestrial mammals in Bhutan, assess the human impacts on biodiversity and developing efec- efectiveness of the current protected area network, tive conservation measures. identify areas of high species richness outside of the existing protected area, and evaluate the potential efectiveness of indicator and umbrella species for conservation planning. Supplementary Information The online version Methods We modelled multi-scale habitat selec- contains supplementary material available at https:// doi. tion of sixteen species of terrestrial mammals across org/ 10. 1007/ s10980- 021- 01225-7. Bhutan using data from a nation-wide camera trap U. Penjor (*) · Ż. Kaszta · D. W. Macdonald · survey. We used the predicted species distribution S. A. Cushman maps to assess the multi-species conservation efec- Wildlife Conservation Research Unit, Department tiveness of the existing protected area network. We of Zoology, University of Oxford, Recanati-Kaplan Centre, performed simulations to identify high priority areas Tubney House, Abingdon Road, Oxfordshire OX13 5QL, UK for multiple species based on their habitat suitabil- e-mail: [email protected] ity, proximity to existing protected areas and overall Ż. Kaszta connectivity within the predicted distribution of spe- e-mail: [email protected] cies. We used correlation analysis among predicted D. W. Macdonald occurrence maps and multivariate cluster analysis to e-mail: [email protected] identify potential indicator species. We evaluated the S. A. Cushman potential utility of each species as umbrella species e-mail: [email protected] by assessing how well optimal protected areas for that species would protect suitable habitat for all 16 spe- U. Penjor cies simultaneously. Nature Conservation Division, Department of Forests and Park Services, Ministry of Agriculture and Forests, Results Protected areas and forest cover were 11001 Thimphu, Bhutan strongly associated with habitat use of most mod- elled species. Additionally, topographical features, S. A. Cushman like terrain roughness and slope position, contributed USDA, Rocky Mountain Research Station, 2500 S. Pine Knoll Dr, Flagstaf, AZ 86001, USA to habitat selection of multiple species, but often in Vol.:(0123456789)1 3 1282 Landscape Ecol (2021) 36:1281–1309 diferent ways. Environmental and topographical vari- Aichi Biodiversity Targets 2020 aims not only to ables were mostly selected at medium to broad scales. reduce species loss but also to safeguard habitat and Anthropogenic variables (agriculture and built-up acknowledge ecosystem services, while also improv- areas) were negatively associated with habitat suit- ing the management and sustainable use of natural ability of most species at both fne and broad scales. resources (Tittensor et al. 2014). Despite such eforts, Conservation efectiveness assessment of existing the rate of global biodiversity loss has likely acceler- protected areas found protected areas in south-cen- ated substantially in recent decades (Tittensor et al. tral Bhutan have high efectiveness in terms of both 2014). Therefore, more efective conservation pro- mean and total richness protected. Similarly, biologi- grams that optimize protection of critical habitat are cal corridors in the south-central region ofered high essential to stem biodiversity loss and enhance spe- mean richness protection. Our simulation of optimal cies recovery (Venter et al. 2014). areas for additional protection found areas abutting Animals have varied requirements for habitat protected areas in southern Bhutan ofered high rela- extents, patterns and characteristics (Torres-Contreras tive species richness protection. Our umbrella species et al. 1997; Kelt et al. 1999; Finlayson et al. 2008) analysis found muntjac, wild pig, serow, sambar and and their habitat use and distribution are infuenced Asian golden cat are the most efective umbrella spe- by biotic and abiotic factors, such as food avail- cies for broader biodiversity protection. Our indica- ability, predation, guild interaction and competition tor species analysis found tiger, gaur, dhole, clouded (Falkenberg and Clarke 1998). Thus, knowledge of leopard, Asian black bear and common leopard as factors infuencing species habitat use is a prerequi- efective indicator species. site to habitat protection, conservation and manage- Conclusions This study highlights the need to pro- ment. Further, species respond to environmental, tect optimally located species-rich areas outside the topographical and anthropogenic features at diferent current protected areas. This kind of multi-species scales (Wiens 1989; Collingham et al. 2000; McGari- habitat assessment provides important information to gal et al. 2016). Specifcally, scale plays an important optimize future conservation and development plans role in resource and space use of organisms in het- at national and regional scales. erogeneous landscapes (Kotliar and Wiens 1990; Hol- ling 1992). Diferent species select habitat at diferent Keywords Habitat suitability · Multi-scale · Multi- scales (Roland and Taylor 1997), and a given spe- species · Priority conservation areas · Priority species cies may select diferent resources at diferent scales (Grand et al. 2004; Wasserman et al. 2012). There- fore, it is critical to incorporate the efects of scale in Introduction species-habitat relationships and more importantly in planning and designing reserves (Thompson and Humans have impacted biodiversity for millennia McGarigal 2002). and are linked to the decline of megafauna and pre- To stem species loss and habitat conversion, global historic extinctions (Bartlett et al. 2016). However, protected area (PA) designations have increased in the recent explosion in human populations, coupled extent and number in the last few decades (Watson with increasing per capita resource consumption, et al. 2014). However, PAs have often been desig- has accelerated these impacts, with more than 50% nated without sufcient strategic planning, and as a of global land cover now altered by human activities result, existing PAs are often inadequate or inefcient (McGill et al. 2015). These rapid land-use changes in their protection of critical biodiversity and their have driven large declines in wildlife populations habitats (Jenkins et al. 2015; Chundawat et al. 2016; worldwide (WWF 2016). As a result, it is estimated Johansson et al. 2016). Assessment of the biodiversity that current extinction rates are as much as 1000 efectiveness of existing PAs is often lacking (Chape times the background rate in the fossil record (John- et al. 2005). It is largely unknown whether PAs ade- son et al. 2017). quately represent biodiversity and ensure sustainable Global initiatives to address the extinction cri- protection (Margules et al. 2002). Pragmatically, it is sis and improve biodiversity conservation have impossible to protect all wilderness areas; hence, it is produced ambitious visions. Amongst them, the important to identify critical biodiversity areas and 1 3 Landscape Ecol (2021) 36:1281–1309 1283 prioritize them for intensive conservation (Waldron of the national area, 19,581 km2), the efcacy of the et al. 2013). protected area network in protecting wildlife, particu- When prioritizing land use and protected area larly megafauna, is largely unknown. Further, rapid establishment, past studies have frequently intersected human infrastructure development calls for identif- connectivity models with protected areas and prior- cation and urgent protection of key biodiversity areas itized areas for protection based on the strength, cen- outside the PAN for the sustainability of conserva- trality or connectedness of areas outside the existing tion eforts. Lastly, there is a general interest in the connectivity network (Cushman et al. 2018; Kaszta conservation and scientifc community regarding the et al. 2020; Ahmadi et al. 2020; Ashrafzadeh et al. use of indicator and umbrella species in conservation 2020). These approaches, however, don’t use formal planning (Dufrêne and Legendre 1997; Roberge and optimization to select or prioritize new areas for pro- Angelstam 2004). In this paper, we defne indicator tection and often have been limited to one (Cushman species as those whose presence indicates (by high et al. 2018) or a few (Cushman et al. 2013) species. correlation with) the presence or absence of other Formal optimization approaches, such as MARXAN species, and umbrella species as those whose protec- (Ball et al. 2009), have the advantage of being objec- tion would simultaneously protect optimal habitat for tive, stochastic and replicable, which can improve the many other species. efcacy and robustness of predictions. However, past To address these knowledge gaps and management optimization approaches