Combining two probability maps

[Liza Storey]

Hello,

I would like some advice on whether anyone has combined two 'probability of occurrence' maps generated from two maxent analyses.
In my case, one map is from a national-scale climate-only analysis (projected from a global scale model to the regional landscape) and the second map, is a landuse-related analysis at the landscape level. I can combine these in ArcGIS, by assigning them new combined category types (however, then the resulting map does not have probability of occurrence values), as outlined in (Vincente et al., 2011, Biological Invasions 13: 1209-1227).
Has anyone used any other approaches ?
thanks for your help,

[John B]

The following extract from p.7 of Stanton et al. 2011 includes a couple of suggestions for combining multiple probability maps (refs given at bottom).

"

A fourth option that we did not test is to create a separate

suitability layer based on the static variable (e.g. by assigning a

separate suitability value to each soil type or running a separate

SDM with the static variables only) and multiplying this map

with the probabilitymap that is output from the SDM with the

climatic variables. This is similar to masking, albeit with more

than two values for the ‘mask’ layer, and the multiplication

assumes that the two layers are independent or non-interacting;

thus, we believe the implications for bioclimatic modelling

are the same as masking.

A related approach, which has been used to integrate data at

different spatial scales (Pearson, Dawson & Liu 2004), is to

combine dynamic climate and static land cover data in a two step

process: (i) a climate-only model is built and shifts under

future climate scenarios are predicted; (ii) the output from the

climate-only model is used alongside land cover as inputs to a

second model. This approach uses both static and dynamic

variables in the same model, which is supported by our results

here, and may be a useful way to integrate the large scale effects

of climate with the more local effects of land cover (Pearson,

Dawson & Liu 2004).

"

Stanton, J. C., Pearson, R. G., Horning, N., Ersts, P. and Reşit Akçakaya, H. (2011), Combining static and dynamic variables in species distribution models under climate change. Methods in Ecology and Evolution. doi: 10.1111/j.2041-210X.2011.00157.x 

Pearson, R. G., Dawson, T. P. and Liu, C. (2004), Modelling species distributions in Britain: a hierarchical integration of climate and land-cover data. Ecography, 27: 285–298.