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Challenging the status quo in invasive species assessment using mechanistic physiologically based demographic modeling
Challenging the status quo in invasive species assessment using mechanistic physiologically based demographic modeling
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Challenging the status quo in invasive species assessment using mechanistic physiologically based demographic modeling
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Challenging the status quo in invasive species assessment using mechanistic physiologically based demographic modeling
Challenging the status quo in invasive species assessment using mechanistic physiologically based demographic modeling
Journal Article

Challenging the status quo in invasive species assessment using mechanistic physiologically based demographic modeling

2024
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Overview
The increased incidence of invasive species introductions is a hallmark of global change, but their associated environmental and economic impacts are vastly underestimated. Assessing and managing the impact of invasive species requires understanding their weather driven dynamics as a basis for predicting their potential geographic distribution and relative abundance. Current de-facto standards for invasive species assessment are correlative approaches lacking mechanistic underpinnings, and hence fail to capture the weather driven biology limiting their explanatory and predictive capacity to forewarn policy makers of species invasiveness (i.e., its potential geographic distribution and relative abundance under extant and/or climate change weather). The idiosyncratic time-place nature of biological invasions and the inability of correlative approaches to incorporate biological information call for development of a unifying prospective approach across species. Physiologically based demographic models (PBDMs) provide a holistic basis for assessment of invasive species addressing many limitations of correlative approaches while accommodating higher level of biological complexity using a similar number of parameters. We use the South American tomato pinworm Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae) as a case study in the Palearctic and compare the predictions of our PBDM model to those of three analyses based on the correlative CLIMEX model. The PBDM outperformed CLIMEX with comparable CLIMEX predictions only after the pest had reached its potential geographic distribution (i.e., post hoc), using 6–10 vs. 13 parameters, respectively. We suggest creating dedicated laboratories to gather appropriate biological data and developing generalized software to build mechanistic models for assessing invasive species of any taxa.