Habitat invasion risk assessment based on Landsat 5 data, exemplified by the shrub Rosa rubiginosa in southern Argentina

Abstract

Prediction of invasive species spread helps to plan management actions. We performed a risk assessment by quantifying habitat invasibility, predicted the potential distribution of an invasive species using the Maxent modelling program and confirmed patterns using detailed field studies. Our study was conducted in southern Argentina, Patagonia, where large areas are already invaded by the European shrub Rosa rubiginosa. A total of 163 R. rubiginosa locations served as ground truth data, and predictors were obtained from the spaceborne sensor Landsat 5. Based on the Maxent Method (area under the receiver operating characteristic curve 0.8), the habitat invasibility map covered about 5000 km2. Our model revealed that R. rubiginosa has the potential to invade 36% of the area along a steep precipitation gradient (target region 600–1400 mm per year). The Tasseled Cap brightness index and the normalized vegetation index explained most of the variance in our model, followed by the Tasseled Cap greenness and wetness indices, which can be interpreted as indicators of disturbance. Highest levels of invasibility were predicted for urban areas, along roads and rivers, on pastures, in Austrocedrus chilensis forests and inside Nothofagus dombeyi forest gaps. Detailed field assessments of rose cover performed in seven habitat types supported these results: rose cover significantly decreased with increasing tree cover (P < 0.01). Our data revealed that the occurrence of R. rubiginosa is not connected to a certain habitat type, but that it thrives in open patches following habitat disturbance. Our approach is a widely applicable, cost-free remote sensing method that can serve as a risk assessment tool for alien plant species invasion of habitats.