Species specific modelling
When representative data (spatial and taxonomic) is available
species-specific models are always the best approach. Using the same
point data outlined above with the same environmental variables (but at
resolution of 1km (0.008 degrees) rather than 10km (0.08 degrees)).
Species with at least 3 points were modelled (this is too low for
individual species models, but can still be useful in an approach where
only patterns are being examined, though output accuracy can then be
assessed by comparing to the IUCN ranges as whilst ranges within IUCN
are artificial the overall patterns in terms of geographic regions
should be broadly comparable). As noted variables should represent the
conditions likely to delimit species ranges, reflect ecophysiological
thresholds, and other habitat constraints, including habitat structure.
Variable correlation is accounted for within Maxent, and
species-specific variable selection can also be made using various R
packages (i.e. ENMEval).
Once again, we ran models using the default parameters and used 3
replicates, and the average reclassified to a binary map (0:1) using the
10 percentile cloglog threshold. As models will note all environmentally
suitable habitat regardless of biogeographic constraints, to reflect
biogeography we then used the IUCN redlist to note species endemic to
Madagascar, in Madagascar and continental Africa, and those limited to
the African continent. It should be noted that a number of Madagascan
endemic species lacked sufficient data to model, thus richness in
Madagascar may be under-estimated, especially given the small ranges of
some bats, but all models had an AUC exceeding 0.9, additional indicies
such as Boyce index or AIC can be used to give independent measures of
model performance and accuracy. These were then masked in batches using
masks of each of those three regions. The raster calculator was then
used to batch sum groups of 30 species within each of these three groups
and numbered sequentially. We then combined all those species restricted
to continental Africa using the raster calculator, before using the
mosaic to new raster tool to combine the three types of biogeographic
map to refine ranges and map modelled richness.
All maps are provided to show how they note richness patterns across the
African continent.