Identifying transboundary conservation priorities in a biodiversity hotspot of China and Myanmar: Implications for data poor mountainous regions

Abstract

Difficult to study species that inhabit inaccessible terrain, present significant challenges in obtaining accurate ecological, distributional, and conservation information. To address these challenges, we used an effective set of time- and cost-efficient methods including interview-based surveys assisted by Google earth 3D maps to document the distributional range of 32 native animal taxa in the biodiverse but difficult to access Gaoligong Mountains (GLGMS), located on the northern Sino-Myanmar Border. Five threatened flagship species, including the black snub-nosed monkey (Rhinopithecus strykeri), the Skywalker hoolock gibbon (Hoolock tianxing), Shortridge's langur (Trachypithecus shortridgei), Sclater's monal (Lophophorus sclateri) and the Mishmi takin (Budorcas taxicolor) were selected for intensive surveys and used as surrogate taxa to study community biodiversity. Field surveys of each species were conducted to determine their presence/absence and to confirm the reliability of species distribution data obtained from interview-based surveys. Multicriteria Decision Analyses were used along with data on habitat suitability (MAXENT) to prioritize transboundary conservation areas. Our results indicate that approximately 83.4% (10,398.7 km2) of the remaining habitat with high biodiversity conservation value in the GLGMs is unprotected. This includes six large zones located along the northern Sino-Myanmar border, separated by rivers and human settlements. These areas should be designated as a transboundary World Nature Heritage Site, national parks, or wildlife sanctuaries. This study presents a reliable, rapid and integrative method for developing informed policies for conservation prioritization in data poor areas, which can be applied successfully to assess conservation priorities in other mountainous regions where obtaining data on biodiversity is difficult. Key worlds: Flagship species, Local ecological knowledge, MAXENT, Multi-criteria decision analysis, Conservation planning, Transboundary conservation