Abundance and habitat associations of the globally endangered Giant Nuthatch Sitta magna in Southern Shan State, Myanmar

Abstract

Summary The Giant Nuthatch Sitta magna is a globally endangered species presumed to be declining, for which basic parameters of population and habitat associations remain largely unquantified. We focused on Myanmar, which potentially constitutes ~30% of the Giant Nuthatch global range and yet lacks recently published records. Our objectives were to survey key potential Giant Nuthatch localities in, or near, historical locations in Southern Shan State, assess its population status, and quantify habitat associations. Preliminary locality surveys focused on four potential forest patches, assessed by walking approximately 40 km of trails. The species was found in only one of the four localities (Mt. Ashae Myin Anauk Myin [AMAM]), an 18 km2 forest patch in Pindaya and Lawksawk Townships. Here, point counts and vegetation surveys were conducted at 46 locations using an adaptive cluster sampling design. N-mixture models were applied to estimate abundance and identify habitat variables correlated with abundance and detection probability. We also conducted a brief quantitative assessment of tree use and foraging behaviour during one breeding season. Our population estimate for AMAM was 56 individuals (95% CI 25–128) based on a sampled area of 3.25 km2. Abundance was positively associated with larger diameter trees, a higher proportion of pine and oak combined based on their total basal area, and negatively correlated with elevation. Foraging data suggested that Giant Nuthatch preferred to feed on trunks and large branches of larger diameter pines and Fagaceae trees. Based on the estimated population size, AMAM is probably a globally significant locality for Giant Nuthatch and the only confirmed locality in Myanmar since 1992 but is threatened by agricultural expansion. More detailed understanding of the habitat requirements of this endangered species and an assessment of its distribution at the landscape-level, especially in Shan State, would increase the precision of global population estimates.