Detectability in Audio-Visual Surveys of Tropical Rainforest Birds: The Influence of Species, Weather and Habitat Characteristics.

Alexander S Anderson,Stephen E Williams,Tiago A Marques,Luke P Shoo,Roberto Ambrosini

doi:10.1371/journal.pone.0128464

Abstract

Indices of relative abundance do not control for variation in detectability, which can bias density estimates such that ecological processes are difficult to infer. Distance sampling methods can be used to correct for detectability, but in rainforest, where dense vegetation and diverse assemblages complicate sampling, information is lacking about factors affecting their application. Rare species present an additional challenge, as data may be too sparse to fit detection functions. We present analyses of distance sampling data collected for a diverse tropical rainforest bird assemblage across broad elevational and latitudinal gradients in North Queensland, Australia. Using audio and visual detections, we assessed the influence of various factors on Effective Strip Width (ESW), an intuitively useful parameter, since it can be used to calculate an estimate of density from count data. Body size and species exerted the most important influence on ESW, with larger species detectable over greater distances than smaller species. Secondarily, wet weather and high shrub density decreased ESW for most species. ESW for several species also differed between summer and winter, possibly due to seasonal differences in calling behavior. Distance sampling proved logistically intensive in these environments, but large differences in ESW between species confirmed the need to correct for detection probability to obtain accurate density estimates. Our results suggest an evidence-based approach to controlling for factors influencing detectability, and avenues for further work including modeling detectability as a function of species characteristics such as body size and call characteristics. Such models may be useful in developing a calibration for non-distance sampling data and for estimating detectability of rare species.

Highlights

Worldwide, many bird species may be at risk of decline or extinction [1]
The detection function is usually modeled via dedicated software [11] and used to estimate the average detection probability P, which allows to scale up the number of detected animals to the total number of animals
We focus on covariates applicable to the first three of these, and evaluate the application of distance sampling in the diverse avian assemblage of the Australian Wet Tropics

Summary

Introduction

Many bird species may be at risk of decline or extinction [1]. This problem is acute in the montane tropics, where high levels of diversity and endemism are coupled with increased vulnerability to changes in climate and land use [2,3]. As a complete census of animal populations is typically unachievable in natural systems [6], most monitoring programs and ecological studies use fixed area or effort counts that generate an index of relative abundance [7] While such indices are popular and relatively simple to apply, detection probability may vary widely between individuals, survey locations, or times [8], biasing estimates of density such that underlying ecological processes are difficult to infer [6,9]. If all animals up to distance ESW were detected we would detect on average as many animals as were detected up to a truncation distance w [11] This makes the correspondence between the actual distance sampling survey and an equivalent strip transect leading to the same number of detections. Complex habitats and difficulty in access can add additional challenges in tropical rainforests [14,15,16]

Methods

Results

Conclusion