An assessment of the Tagula Honeyeater Microptilotis vicina, a Data Deficient bird species in a Melanesian endemic hotspot

Abstract

SummaryWe conducted research into the ‘Data Deficient’ and endemic Tagula Honeyeater Microptilotis vicina of the Louisiade Archipelago, Papua New Guinea. This species was only observed on Sudest and Junet Islands. Islands were visited between October and January in the years from 2012–2014 and in 2016. We conducted the first assessment of spatial and habitat use by this species using radio-tracking in 2016. These findings were also used to inform estimates using traditional population density methods. CTMM package in R was used for home-range estimation for the tracked honeyeaters. Our results supported that members of this species display territoriality during the breeding season, occupying a mean of 2.0 ± 0.6 (SE) ha on Junet Island (n = 5). Whether individuals defended defined territories at other times of the year was not known but re-sightings of marked birds confirmed them to be locally resident. Population estimates ranged between 53,000 and 85,000 individuals. However, more conservative estimates nearing 50,000 individuals were considered prudent given lower population densities observed on parts of the larger Sudest Island (0.64/ha). This species utilised the canopy and understorey layers in a range of habitats from mangroves at sea-level, gardens and regrowth of various ages to cloud forest on the highest point of Sudest Island (∼800 m asl). Dietary observations support that like many closely related species, Tagula Honeyeaters have a broad diet of mostly insects supplemented with nectar and fruit. Observations indicated that this species had life history attributes toward the slower end of the spectrum but similar to other congeners. Vocalisations were more diverse in both structure and complexity than those of suspected close relatives the Mimic Microptilotis analogus and Graceful Microptilotis gracilis Honeyeaters. Morphological measures were similarly different, supporting species level recognition.