Australia’s Dengue Risk: Human Adaptation to Climate Change - Recent Advances and Issues in Environmental Science - page 135

and 2005 from southeast Queensland (P. Mottram, unpub. data), and the Northern
Territory (P. Whelan, unpub. data).
Base Climate Layers
Raster ASCII grids were generated for Australia at a spatial resolution of 0.025° (ap-
proximately 2.5 km) for eight climate variables plus elevation. These included an-
nual mean rainfall and annual mean temperature produced by BIOCLIM using the
ANUCLIM software package [19] as well as mean values of maximum temperatures
and minimum temperatures for the months of January and July produced by the ESO-
CLIM component of ANUCLIM. This procedure involved the use of monthly mean
climate surface coefficients, generated by the thin plate smoothing spline technique
ANUSPLIN [20] from Australian Bureau of Meteorology climate data between 1921
and 1995 [21]. The geographic coordinates of the meteorological stations were used as
independent spline variables together with a 0.025° digital elevation model (DEM) for
Australia generated with ANUDEM [22] which acted as a third independent variable.
As atmospheric moisture is known to be an important factor in terms of the survival
and longevity of adult mosquitoes, mean values of dewpoint for January and July were
generated with ESOCLIM to provide this.
Climate Change Layers
A further series of ASCII grids were generated from climate change scenarios using
OzClim version 2 software [23, 24] at a spatial resolution of 0.25° (approximately 25
km). The scenarios used for this study were for 2030 and 2050 using CSIRO: Mk2
Climate Change Pattern with SRES Marker Scenario A1B and mid climate sensitivity.
The output variables corresponded to the predicted change from the base climate for
the rainfall and temperature parameters generated with ANUCLIM.
This version of OzClim outputs vapor pressure rather than dewpoint as a measure
of atmospheric moisture. For the present study vapor pressure grids for the predicted
change from base climate for January and July were generated and the grid cell values
were converted to dewpoint by applying the inverse of Tetens' equation [dp = (241.88
× ln(vp/610.78))/(17.558 − ln(vp/610.78)]. This mathematical procedure was imple-
mented with the use of ImageJ software (publicly available at http://rsbweb.info.nih.
gov/ij) together with the raster operations of TNTmips (MicroImages Inc., Lincoln,
Nebraska).
The environmental layers used for climate change modeling were prepared by
resampling the OzClim outputs to the geographical extents and grid cell size of the
ANUCLIM grids using TNTmips. The resampled outputs were then added to the cor-
responding ANUCLIM base climate layers to produce the environmental layers pre-
dicted for the chosen climate change scenarios.
Ecological Niche Modeling
DesktopGarp version 1_1_6 [25] was used for ecological niche modeling in a manner
similar to our earlier studies [26]. Models derived from the historical climate data were
generated using the record sites for Ae. aegypti as inputs together with the eight base