Abstract
Detecting invasive species and predicting their potential distribution are crucial
to coordinate management responses. Remote sensing data are now available in several
spatial and temporal resolutions and can supply environmental models with additional
information. This study uses the Maximum Entropy algorithm to model the current
distribution of the saltcedar (Tamarix spp.) in the US and Mexico and to identify suitable
habitats, both already inhabited and not yet occupied. Tamarisk is restricted to specific
habitats such as riparian zones, wetlands and agricultural or disturbed areas, which are
typically not only characterized by climate. To describe vegetation phenology and thermal
seasonality in these habitats, the study uses annual metrics of remotely sensed time series
from 2001 to 2008 (Terra-MODIS Enhanced Vegetation Index and Land Surface
Temperature) together with WorldClim bioclimatic data. By using occurrence records
primarily from the US we were able to model predictive maps of tamarisk distribution
correlating very well to the known distribution in the US. For Mexico, where only very few
occurrence records exist, we identified potential tamarisk habitats for substantial areas in
Baja California, in the states of Sonora and Sinaloa and in the Central Mexican Plateau.
These predictive model results can be used to support the early detection and prevention of
Tamarix spp. invasion.
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