William W. Hargrove

Learn More
Lacunarity analysis is a multiscaled method for describing patterns of spatial dispersion. It can be used with both binary and quantitative data in one, two, and three dimensions. Although originally developed for fractal objects, the method is more general and can be readily used to describe nonfractal and multifractal patterns. Lacunarity analysis is(More)
Multivariate clustering based on fine spatial resolution maps of elevation, temperature, precipitation, soil characteristics, and solar inputs has been used at several specified levels of division to produce a spectrum of quantitative ecoregion maps for the conterminous United States. The coarse ecoregion divisions accurately capture intuitively-understood(More)
Changes in Earth's climate in response to atmospheric greenhouse gas buildup impact the health of terrestrial ecosystems and the hydro-logic cycle. The environmental conditions influential to plant and animal life are often mapped as ecoregions, which are land areas having similar combinations of environmental characteristics. This idea is extended to(More)
All global circulation models based on Intergovernmental Panel on Climate Change (IPCC) scenarios project profound changes, but there is no consensus on how to map their environmental consequences. Our multivariate representation of environmental space combines stable topographic and edaphic attributes with dynamic climatic attributes. We divide that(More)
We describe the Pathway Analysis Through Habitat (PATH) tool, which can predict the location of potential corridors of animal movement between patches of habitat within any map. The algorithm works by launching virtual entities that we call 'walkers' from each patch of habitat in the map, simulating their travel as they journey through land cover types in(More)
Aim Theoretical work suggests that species' ecological niches should remain relatively constant over long-term ecological time periods, but empirical tests are few. We present longitudinal studies of 23 extant mammal species, modelling ecological niches and predicting geographical distributions reciprocally between the Last Glacial Maximum and present to(More)
[1] Remote sensing of vegetation phenology is an important method with which to monitor terrestrial responses to climate change, but most approaches include signals from multiple forcings, such as mixed phenological signals from multiple biomes, urbanization, political changes, shifts in agricultural practices, and disturbances. Consequently, it is(More)
The authors present a metacomputing application of multivariate, nonhierarchical statistical clustering to geographic environmental data from the 48 conterminous United States in order to produce maps of regions of ecological similarity, called ecoregions. These maps represent finer scale regionalizations than do those generated by the traditional(More)