Estimating vertebrate diversity using comprehensive multi-method surveys in the Masembo watershed of the Mekongga Mountains region in Southeast Sulawesi, Indonesia

Background/Question/Methods

We conducted a multi-year terrestrial vertebrate (2009-2011) survey along an elevational gradient in the Masembo River watershed of the Mekongga Mtns. region in Southeast Sulawesi, Indonesia.  This area has never been comprehensively surveyed for vertebrate diversity before. Sulawesi supports the highest level of vertebrate endemism and has one of the most fascinating and unique fauna found in Indonesia.  For example, it is second only to New Guinea in the number of endemic birds.  Our objective was to estimate vertebrate biodiversity and to identify landscape and forest structure parameters that significantly affect those estimates of diversity.  We used a repeated sampling design that would account for differences in detectability as well as incorporate multiple detection methods. These data consisted of presence-absence survey information of all four vertebrate taxa (birds, mammals, reptiles and amphibians) from sites each elevation class (300m-600m), (700m-1200m), (1300m-2000m) and  (2100m-2600m). Climatic, temporal and method of survey data was also recorded as these variables have been known to influence detection. At each site we also recorded forest structure variables including canopy height, canopy diversity, percent shrub cover, mid-canopy cover. Our standardized sampling design combined mistnet arrays with aural and visual observations to obtain a more complete survey of the avifauna of this area and to determine probability of occupancy along an elevational gradient.

Results/Conclusions

We detected over 150 species of birds (collected specimens as well as visual and aural detections) of which 50 species are endemic to Sulawesi.  We detected ~50 species of amphibians and reptiles some of which may be undescribed species.  We detected ~19 species of volant mammals and ~16 species of non-volant mammals.  Detection probabilities differed among species and also among detection methods. Maximum likelihood estimates of diversity were significantly higher than naïve estimates. A priori models of occupancy show that forest type and elevation are major factors in the estimates and distribution of diversity.  Surveys that incorporate estimation of detectability and multiple detection methods are critical to characterizing overall bio-diversity especially in remote and difficult areas to survey as well as estimating diversity more accurately when species are present but not detected.  In addition, surveys of this type can be used to determine species-habitat relationships in order to better understand the distributions of these poorly studied species.  Results from surveys of this type can be used to develop conservation and management strategies for stakeholders and conservation planners.