Abstract

Abstract: We used a relatively simple and direct remote‐sensing approach to determine biodiversity values in arid ecosystems and thus identify potential conservation sites. We developed indices based on regression models between grass, shrub, litter, exposed‐soil groundcover components, and Landsat thematic mapper satellite imagery reflectance values over a reference site in the northern Chihuahuan Desert in New Mexico. This site supports low‐disturbance desert grasslands that have been excluded from livestock grazing for 55 years and moderate‐disturbance grasslands that have been under a continuous grazing regime for over 100 years. Greater richness and abundance of noninvasive and nonruderal plant species were associated with the low‐disturbance grasslands that had lower shrub abundance, increased litter and grass cover, and lower exposed soil. Using the thematic mapper indices, we computed an additive grassland biodiversity index such that, as exposed soil and shrub values go down, litter and grass values go up, as does the biodiversity index. When the biodiversity index was applied to the reference‐site landscape, grasslands previously identified for their high conservation value were detected. As a further test, we applied the indices to a site in Chihuahua, Mexico, that supports similar grasslands but for which there are few other data on condition and conservation values. The soil, grass, and shrub indices were moderately effective in describing the range of variation at the Mexico site, but the litter equation was not. Still, higher biodiversity value in terms of nonruderal plant diversity tended to correspond to higher grass cover and lower soil exposure and a higher overall biodiversity index. Some localized calibration with geologic substrate may be required along with an assessment of the temporal constraints, but generally the index shows promise for quickly and efficiently detecting desert grasslands of high biodiversity conservation value.

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