The application of statistical modelling on invasive alien species risk assessment: a systematic review

• Autor(a) principal: Félix, Ana Cristina Rodrigues
• Data de Publicação: 2019
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10773/28383
• topic: Invasive alien plants; Risk assessment; Statistical modelling; Species distribution models; Systematic review

Either deliberately or by accident, humans have been introducing exotic species into novel habitats at an alarming rate and the ongoing climate change can synergistically promote this phenomenon, at times. Risk assessment of exotic species is essential to support the prevention of new introductions in the case of species that represent negative impacts on the various components of ecosystems. Over the last 20 years, statistical modelling has been recognized as a useful tool in predicting invasion risks specifically for exotic plants. In this systematic review, the application of statistical models to the risk assessment of alien plant species was analyzed to assess how the application of these tools has evolved over time, as well as to identify the approaches used and finally the current limitations inherent to these studies. The results support that static and spatially explicit machine learning models that predict potential species distribution are the most commonly used techniques, although some pertinent limitations related to these models have also been identified. It has been concluded that a formalization of risk assessment protocols should include the standardized use of species distribution models, and both techniques and approaches should be scientifically proven to maximize accuracy and reduce errors in results.