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Filling in the gaps: Modelling native species richness and invasions using spatially incomplete data

Diversity and Distributions
By: , , , and 
https://doi.org/10.1111/j.1366-9516.2006.00278.x

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Abstract

Detailed knowledge of patterns of native species richness, an important component of biodiversity, and non-native species invasions is often lacking even though this knowledge is essential to conservation efforts. However, we cannot afford to wait for complete information on the distribution and abundance of native and harmful invasive species. Using information from counties well surveyed for plants across the USA, we developed models to fill data gaps in poorly surveyed areas by estimating the density (number of species km -2) of native and non-native plant species. Here, we show that native plant species density is non-random, predictable, and is the best predictor of non-native plant species density. We found that eastern agricultural sites and coastal areas are among the most invaded in terms of non-native plant species densities, and that the central USA appears to have the greatest ratio of non-native to native species. These large-scale models could also be applied to smaller spatial scales or other taxa to set priorities for conservation and invasion mitigation, prevention, and control efforts. ?? 2006 The Authors.
Publication type Article
Publication Subtype Journal Article
Title Filling in the gaps: Modelling native species richness and invasions using spatially incomplete data
Series title Diversity and Distributions
DOI 10.1111/j.1366-9516.2006.00278.x
Volume 12
Issue 5
Year Published 2006
Language English
Larger Work Type Article
Larger Work Subtype Journal Article
Larger Work Title Diversity and Distributions
First page 511
Last page 520
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