Abstract:

Delineation of biota into distinct provinces of plant and animal assemblages and the identification of the disjunctions or breaks that separate them is a key focus in macroecology and biogeography and plays an important role in conservation planning. It is also informative to identify the geological, topographic and climatic factors that have influenced the formation of these structures. However, as traditionally defined, bioregions and breaks are characterised as uniform biotic provinces and delineated with solid, linear boundaries. Such representations do not reflect the true nature of the biotic patterns that they are intended to depict. The outer limits of biogeographic boundaries are areas where the distributions of different species groups can blend with one another, such that the breaks between adjacent bioregions are transitional zones. These ‘transitional’ breaks can change gradationally in some locations and more abruptly in others. Moreover, breaks and boundaries can change position over various timescales, e.g. ranging from the seasonal to semi-decadal.

A second issue is that identification of the environmental correlates influencing break formation does not take full account of how species-environment relationships change inconsistently across geographic space contingent upon the environmental nuances that vary between locations (i.e. spatial non-stationarity). Similarly, biophysical relationships exhibit anisotropic variation because ecological and physical processes change in different directions. For instance, anisotropic processes may be driven by both broad and fine-scale topographic and climatic gradients.

I introduce a spatially explicit, moving window analysis technique which can be used to measure the fine-scale, continuous variation in species compositional turnover and turnover in geology, topography and climate. These unidirectional moving window analyses are progressively rotated through 360° in order to capture the anisotropic variation in the rate of biotic and environmental turnover. This enables shared transitional breaks in aggregate biotic distributions to be identified, characterisation of their abrupt versus gradational transitions, as well as quantification of the non-stationary and anisotropic influence of environmental heterogeneity on their formation. I

apply this method to assess whether the biogeographic insights generated by broad-scale studies on the influence of environmental variability on biodiversity generalise to different spatial scales and locations. I then adapt and apply the method to conservation prioritisation.