Predicting distributions of invasive species

By Jane Elith. 2013

110 citations recorded by the source corpus.

This chapter aims to inform a practitioner about current methods for predicting potential distributions of invasive species. It mostly addresses single species models, covering the conceptual bases, touching on mechanistic models, and then focusing on methods using species distribution records and environmental data to predict distributions. The commentary in this last section is oriented towards key issues that arise in fitting, and predicting with, these models (which include CLIMEX, MaxEnt and other regression methods). In other words, it is more about the process of thinking about the data and the modelling problem (which is a challenging one) than it is about one technique versus another. The discussion helps clarify the necessary steps and expertise for predicting distributions. Some researchers are optimistic that correlative models will predict with high precision; while that may be true for some species at some scales of evaluation, I believe that the issues discussed in this chapter show that substantial errors are reasonably likely. I am hopeful that ongoing developments will produce models better suited to the task and tools to help practitioners to better understand predictions and their uncertainties.

Subfields: Ecological Modeling, Ecology

View Paper: https://www.semanticscholar.org/paper/47ebfd946f066e21d467f75e98596ae727f6f20b

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Citations in the corpus

Scientists' warning on invasive alien species (2020, background): “Despite intensive research directed at modelling potential changes in the distribution of terrestrial, freshwater, and marine species owing to climate and land-use change, there is still much uncertainty in predictions of which species will colonize new regions and habitats and what their impacts wi”
Evaluating correlative and mechanistic niche models for assessing the risk of pest establishment (2014, background): “…is considered a process-based mechanistic niche model (Kriticos and Leriche 2010); however, it can also be a correlative model if species-specific phenological thresholds are not used in defining model parameters, but instead parameters are estimated using species’ known occurrences (Elith 2014).”
A standard protocol for reporting species distribution models (2020, background): “…is encompassed by data, 4) the correlation structure between predictors does not change between source and target landscape and 5) if extrapolation is involved, that the model extrapolates in a biologically sensible manner (Dormann et al. 2013, Elith 2017, Guisan et al. 2017, Feng et al. 2019).”