Applying surrogate species presences to correct sample bias in species distribution models: a case study using the Pilbara population of the Northern Quoll

Abstract

The management of populations of threatened species requires the capacity to identify areas of high habitat value. We developed a high resolution species distribution model (SDM) for the endangered Pilbara northern quoll Dasyurus hallucatus, population using MaxEnt software and a combined suite of bioclimatic and landscape variables. Once common throughout much of northern Australia, this marsupial carnivore has recently declined throughout much of its former range and is listed as endangered by the IUCN. Other than the potential threats presented by climate change, and the invasive cane toad Rhinella marina (which has not yet arrived in the Pilbara). The Pilbara population is also impacted by introduced predators, pastoral and mining activities. To account for sample bias resulting from targeted surveys unevenly spread through the region, a pseudo-absence bias layer was developed from presence records of other critical weight-range non-volant mammals. The resulting model was then tested using the biomod2 package which produces ensemble models from individual models created with different algorithms. This ensemble model supported the distribution determined by the bias compensated MaxEnt model with a covariance of of 86% between models with both models largely identifying the same areas as high priority habitat. The primary product of this exercise is a high resolution SDM which corroborates and elaborates on our understanding of the ecology and habitat preferences of the Pilbara Northern Quoll population thereby improving our capacity to manage this population in the face of future threats.

Topographic ruggedness and rainfall mediate geographic range contraction of a threatened marsupial predator

“…We used a ‘target group’ background sampling approach to generate the bias layers (Phillips et al, ). We defined our target group as all critical weight range (CWR) mammals (including northern quoll) within the study area (following Molloy, Davis, Dunlop, & van Etten, ). These species were selected as survey methods used to detect them would also detect the northern quoll (following Molloy et al, )—typically a highly detectable species (Austin, Tuft, Ramp, Cremona, & Webb, )—thus ensuring both northern quoll presence data and model background data were drawn from a comparable sampling intensity.…”

“…We defined our target group as all critical weight range (CWR) mammals (including northern quoll) within the study area (following Molloy, Davis, Dunlop, & van Etten, ). These species were selected as survey methods used to detect them would also detect the northern quoll (following Molloy et al, )—typically a highly detectable species (Austin, Tuft, Ramp, Cremona, & Webb, )—thus ensuring both northern quoll presence data and model background data were drawn from a comparable sampling intensity. Target group species records were subjected to point density analysis (PDA), masked to a 1 km 2 grid layer using ArcGIS 10.3, creating a layer with cell values that accurately represent survey effort in relation to location.…”

“…We used a 'target group' background sampling approach to generate the bias layers (Phillips et al, 2009). We defined our target group as all critical weight range (CWR) mammals (including northern quoll) within the study area (following Molloy, Davis, Dunlop, & van Etten, 2017). These species were selected as survey methods used to detect them would also detect the northern quoll (following Molloy et al, 2017)-typically TA B L E 1 Study area size and climatic variability in terms of mean coldest and warmest quarter temperature, as well as annual precipitation within both historic and contemporary α-hulls.…”

“…Metres above average sea level Pollack 1999 found northern quolls in central Queensland were typically found at lower elevation. Molloy et al (2017) found elevation was a strong contributor to MAXENT modelling for northern quolls in the Pilbara Geoscience Australia (2018) Annual precipitation Derived from spatially interpolated monthly climate database based on averages between 1950 and 2000…”

“…Studies suggest areas proximate to permanent water are more likely to provide high quality for northern quolls (Begg, 1981;Braithwaite & Griffiths, 1994;Burnett, 1997;Molloy et al, 2017) Derived from 1:100,000 watercourse mapping provided by Geoscience Australia (2018 declines occurred in the Pilbara (0.1%). While substantial niche reduction was also observed in Queensland (49.2%), it was a proportionally smaller reduction compared to range declines (Figure 3).…”