Climate space changes Terrain Region

Species distribution models were fitted using the presence-only algorithm Maxent (Phillips) in collaboration with other projects [full methods can be found in Reside et al (NCCARF 2013)]. In brief, species data were accessed from the Atlas of Living Australia (, Queensland Museum  (, Centre for Tropical Biodiversity and Climate Change ( species data base (Williams et al., 2010), and CSIRO.Species distribution models incorporating baseline climate (average across 1976 to 2005) data at 0.01 degree (~1x1km) resolution. Climate data was accessed from Australian Water Availability Project (Jones et al., 2007, Grant et al., 2008), and the bioclimatic variables annual mean temperature, temperature seasonality, maximum temperature of the warmest period, annual precipitation, precipitation of the driest period, precipitation of the wettest period and precipitation seasonality were derived using the “climates” package in R (VanDerWal et al., 2011). 

Species’ future distributions were modelled using future climate projections sourced from the Tyndall Centre (  Eighteen general circulation models (GCMs), and the most severe representative concentration pathway, RCP8.5, were used for the year 2085. To add realism to future projections of species distributions, only suitable areas into the future that were within a reasonable dispersal distance were retained; areas beyond this extent were clipped out. A conservative but reasonable dispersal distance used was 4km/year for birds and mammals and 1km/year for amphibians and reptiles.

Lemuroid Ringtail Possum

Musky Rat Kangaroo

Macleays Honeyeater

Northern Leaf Tailed Gecko

Lumholtz Tree Kangaroo

Green Ringtail Possum

Mahogany Glider



Detailed Descriptions
Geographic and Temporal Extents
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Attributions and Constraints
James Cook University