Using site-occupancy models to prepare for the spread of chytridiomyosis and identify factors affecting detectability of a cryptic susceptible species, the Tasmanian tree frog
Scott D. Cashins A , Annie Philips B and Lee F. Skerratt A C
+ Author Affiliations
- Author Affiliations
A One Health Research Group, College of Public Health, Medical and Veterinary Sciences, James Cook University, Townsville, Qld 4811, Australia.
B Resource Management and Conservation Division of the Department of Primary Industries, Parks, Water and Environment, PO Box 44, Hobart, Tas. 7000, Australia.
C Corresponding author. Email: lee.skerratt@jcu.edu.au
Wildlife Research 42(5) 405-413 https://doi.org/10.1071/WR14183
Submitted: 11 September 2014 Accepted: 6 July 2015 Published: 9 September 2015
Abstract
Context: The global reduction of amphibian biodiversity as a result of the disease chytridiomycosis (caused by the fungus Batrachochytrium dendrobatidis; Bd) has highlighted the need to accurately detect local population declines in association with Bd presence. Although Bd has spread globally, some remote regions such as the Tasmanian Wilderness World Heritage Area (1.40 million ha; TWWHA) in Australia, remain largely, but not entirely, disease free. The Tasmanian tree frog (Litoria burrowsae) resides primarily within TWWHA boundaries, and is believed to be susceptible to chytridiomycosis.
Aims: In the absence of historical abundance data, we used a single-season multi-state site-occupancy model to investigate the impact of Bd on L. burrowsae populations, on factors affecting species detection and to inform ongoing surveillance and conservation.
Methods: We recorded frog detection and ranked call intensity (estimation of population size) from repeated independent surveys within a season to estimate the role of covariates, such as presence of Bd and environmental variables, on species occupancy and detection probability.
Key results: Modelling revealed large frog populations are more likely to be present at naturally formed than human-formed ponds, strong winds negatively affect detection of populations, and time after sunset affects detection of large populations. Large frog populations were more likely to be Bd-negative; however, models including Bd presence were not well supported, in part a result of the small number of Bd-positive sites recorded.
Conclusions and Implications: The utility of site-occupancy modelling in understanding the impact of disease on populations is little known, but has the potential to improve the accuracy and efficiency of many conservation programs.
Additional keywords: amphibian decline, Batrachochytrium dendrobatidis, disease monitoring, ecological monitoring, Litoria burrowsae.
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