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Stohlgren, Thomas J.

Publications and source records attributed to Stohlgren, Thomas J..

Regional Distribution Models with Lack of Proximate Predictors: Africanized Honeybees Expanding North

Species distribution models have often been hampered by poor local species data, reliance on coarse-scale climate predictors and the assumption that species-environment relationships, even with non-proximate predictors, are consistent across geographical space. Yet locally accurate maps of invasive species, such as the Africanized honeybee (AHB) in North America, are needed to support conservation efforts. Current AHB range maps are relatively coarse and are inconsistent with observed data. Our aim was to improve distribution maps using more proximate predictors (phenology) and using regional models rather than one across the entire range of interest to explore potential differences in drivers.

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Bounding Species Distribution Models

Species distribution models are increasing in popularity for mapping suitable habitat for species of management concern. Many investigators now recognize that extrapolations of these models with geographic information systems (GIS) might be sensitive to the environmental bounds of the data used in their development, yet there is no recommended best practice for "clamping" model extrapolations. We relied on two commonly used modeling approaches: classification and regression tree (CART) and maximum entropy (Maxent) models, and we tested a simple alteration of the model extrapolations, bounding extrapolations to the maximum and minimum values of primary environmental predictors, to provide a more realistic map of suitable habitat of hybridized Africanized honey bees in the southwestern United States. Findings suggest that multiple models of bounding, and the most conservative bounding of species distribution models, like those presented here, should probably replace the unbounded or loosely bounded techniques currently used [Current Zoology 57 (5): 642-647, 2011].

Stohlgren, Thomas J.

A Tamarisk Habitat Suitability Map for the Continental US

This paper presents a national-scale map of habitat suitability for a high-priority invasive species, Tamarisk (Tamarisk spp., salt cedar). We successfully integrate satellite data and tens of thousands of field sampling points through logistic regression modeling to create a habitat suitability map that is 90% accurate. This interagency effort uses field data collected and coordinated through the US Geological Survey and nation-wide environmental data layers derived from NASA s MODerate Resolution Imaging Spectroradiometer (MODIS). We demonstrate the utilization of the map by ranking the lower 48 US states (and the District of Columbia) based upon their absolute, as well as proportional, areas of highly likely and moderately likely habitat for Tamarisk. The interagency effort and modeling approach presented here could be applied to map other harmful species in the US and globally.

Morisette, Jeffrey T.