Occupancy modelling reveals a highly restricted and fragmented distribution in a threatened montane frog (Philoria kundagungan) in subtropical Australian rainforests

Abstract

In the last several decades, habitat loss, overexploitation, invasive organisms, disease, pollution and, more recently, climate change have led to catastrophic declines in amphibian biodiversity. Montane amphibian species, particularly those with narrow distributions and specific habitat requirements are likely to be at particular risk under future climate change scenarios. Despite this, fundamental ecological data are lacking for most of these species. Philoria kundagungan is a poorly known representative of a range-restricted genus of montane amphibians from eastern Australia. Using an occupancy framework, we conducted repeated call playback surveys at 32 sites across the mountainous regions of south-east Queensland and north-eastern New South Wales, Australia, to investigate: (1) the current extent of this species’ geographic range, and (2) environmental predictors of this species’ presence. We found that P. kundagungan has a highly restricted and fragmented distribution, being limited to ~11 km2 of potentially suitable habitat, and that its presence is strongly associated with high elevation (>800 m). Our survey protocol resulted in a high probability of detection (>70%) at occupied sites from relatively few visits. From these baseline data, future studies will have the ability to determine changes in this species’ geographic range and occupancy rate in response to the ever-increasing threats faced by P. kundagungan, thereby supporting more effective conservation strategies and policy decisions.

Extensive range contraction predicted under climate warming for two endangered mountaintop frogs from the rainforests of subtropical Australia

“…Uncertainty in distribution modelling is unavoidable in this study as modelling was based only on climatic and elevation data, and ignored other factors contributing to each species' full ecological niche, such as vegetation type. However, our SDMs for current distribution covered all known populations of P. kundagungan and P. richmondensis and were similar to core habitat identified in previous studies 45 , 46 , which were based on presence-absence, vegetation and elevation data, and did not include bioclimatic variables generated from aggregating three decades of monthly climatic data used in this study. This broad consensus with previous studies and our models' high AUC model scores suggests this study accurately identifies the current distribution of P. kundagungan and P. richmondensis .…”

“…The performance of the current habitat model for P. kundagungan was excellent with a mean AUC value of 0.995. This model identified 73.2% of the distribution and 83.1% of the core habitat that was modelled by Bolitho et al 45 . The mean temperature of the wettest quarter (BIO_08) had the strongest influence on P. kundagungan distribution followed by minimum temperature of the coldest month (BIO_06) and then mean temperature of the coldest quarter (BIO_11); (Table 1 ).…”

“…Philoria richmondensis was only described in 2004 and only six localities existed for P. kundagungan 43 . Due to this limitation, records for P. kundagungan and P. richmondensis were also obtained from survey data collected by Bolitho et al 45 and Heard et al 46 . Occurrence records were converted to a 1-km resolution raster dataset to align with the bioclimatic data used in the SDM.…”

“…To further validate our species distribution models (SDMs), we compared current species distribution models (SDMs) generated by this study with a P. kundagungan SDM developed by Bolitho et al 45 and a P. richmondensis SDM developed by Heard et al 46 . These were based on presence-absence field data collected across the full range of each species using a patch occupancy survey approach 54 .…”

“…The restriction of P. kundagungan and P. richmondensis to rainforest and adjoining wet forest, and the specific reliance of these frogs on moist or saturated microhabitats, suggest that they may be particularly sensitive to increasing temperatures and rainfall variability predicted under future climate change scenarios 20 . The geographic distribution of both species was recently modelled in order to produce high-resolution mapping outputs of their current distributions 45 , 46 , however, the approach used could not predict changes to a species' geographic range in response to future climate change scenarios. These recent estimates gave us an opportunity to further validate our species distribution model and in turn, our estimates of the impact of projected climate change on their future distribution.…”