Diversity and Distributions · 2008 · 245 citations · 69 references
Natural ResourcesEcologyInvasion EcologyInvasive Species ManagementPlant EcologyEcological ModelingHabitat Suitability AssessmentHabitat Suitability ModelingInvasive Plant EcologyInvasive Plant ManagementPlant Invasion EcologyEcological Niche DistributionEnvironmental Niche ModelingHabitat Niche ModelingInvasion Ecology ModelsInvasive SpeciesInvasive Species ModelsInvasiveness PredictionNiche Modeling
ABSTRACT Predicting suitable habitat and the potential distribution of invasive species is a high priority for resource managers and systems ecologists. Most models are designed to identify habitat characteristics that define the ecological niche of a species with little consideration to individual species’ traits. We tested five commonly used modelling methods on two invasive plant species, the habitat generalist Bromus tectorum and habitat specialist Tamarix chinensis , to compare model performances, evaluate predictability, and relate results to distribution traits associated with each species. Most of the tested models performed similarly for each species; however, the generalist species proved to be more difficult to predict than the specialist species. The highest area under the receiver‐operating characteristic curve values with independent validation data sets of B. tectorum and T. chinensis was 0.503 and 0.885, respectively. Similarly, a confusion matrix for B. tectorum had the highest overall accuracy of 55%, while the overall accuracy for T. chinensis was 85%. Models for the generalist species had varying performances, poor evaluations, and inconsistent results. This may be a result of a generalist's capability to persist in a wide range of environmental conditions that are not easily defined by the data, independent variables or model design. Models for the specialist species had consistently strong performances, high evaluations, and similar results among different model applications. This is likely a consequence of the specialist's requirement for explicit environmental resources and ecological barriers that are easily defined by predictive models. Although defining new invaders as generalist or specialist species can be challenging, model performances and evaluations may provide valuable information on a species’ potential invasiveness.
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The Measurement of Observer Agreement for Categorical Data
J. Richard Landis, Gary G. Koch · Biometrics · 1977 · 78.9K citations · Full text
Classification and Regression Trees.
Alexander Gordon, Leo Breiman, Jerome H. Friedman et al. · Biometrics · 1984 · 23.9K citations
Classification and Regression Trees.
John Van Ryzin, Leo Breiman, Jerome H. Friedman et al. · Journal of the American Statistical Association · 1986 · 21K citations