Biological invasion risk assessment of Tuta absoluta: mechanistic versus correlative methods

Abstract

The capacity to assess invasion risk from potential crop pests before invasion of new regions globally would be invaluable, but this requires the ability to predict accurately their potential geographic range and relative abundance in novel areas. This may be unachievable using de facto standard correlative methods as shown for the South American tomato pinworm Tuta absoluta, a serious insect pest of tomato native to South America. Its global invasive potential was not identified until after rapid invasion of Europe, followed by Africa and parts of Asia where it has become a major food security problem on solanaceous crops. Early prospective assessment of its potential range is possible using physiologically based demographic modeling that would have identified knowledge gaps in T. absoluta biology at low temperatures. Physiologically based demographic models (PBDMs) realistically capture the weather-driven biology in a mechanistic way allowing evaluation of invasive risk in novel areas and climes including climate change. PBDMs explain the biological bases for the geographic distribution, are generally applicable to species of any taxa, are not limited to terrestrial ecosystems, and hence can be extended to support ecological risk modeling in aquatic ecosystems. PBDMs address a lack of unified general methods for assessing and managing invasive species that has limited invasion biology from becoming a more predictive science.

Tritrophic analysis of the prospective biological control of brown marmorated stink bug, Halyomorpha halys, under extant weather and climate change

“…PBDMs capture the biology of the interacting species making their predictions independent of time, place, and detection records, and fall under the ambit of time varying life tables (Gutierrez 1996). This bioeconomic modeling paradigm (Regev et al 1998) has a long history in assessing the geographic distribution and relative population dynamics of invasive species (Gutierrez and Baumgärtner 1984;e.g., Gutierrez 1996;Gutierrez and Ponti 2013a;Ponti et al 2021; see supplementary information).…”

Using Species Distribution Models (SDMs) to Estimate the Suitability of European Mediterranean Non-Native Area for the Establishment of Toumeyella Parvicornis (Hemiptera: Coccidae)

“…Based on our study, the annual mean temperature played a fundamental role in explaining the projections of habitat suitability for T. parvicornis in Italy, especially in the GLM, MARS, and MaxEnt models. This information is of fundamental importance in the framework of a climate change scenario, as already stated for other pest species infesting agricultural and forest environments, such as Philaenus spumarius L. (Hemiptera: Aphrophoridae) [ 57 ], Lobesia botrana (Denis & Schiffermüller) (Lepidoptera: Tortricidae) [ 58 ], and Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae) [ 59 ]. Our results are also in line with the findings of Solhjouy-Fard et al [ 60 ] and Yan et al [ 61 ], where the annual mean temperature was the variable best explaining the potential distribution of Ferrisia virgata (Cockerell) (Hemiptera: Pseudococcidae), Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae), Apodiphus amygdali (Germar) (Hemiptera: Pentatomidae), Adelphocoris lineolatus (Goeze) (Hemiptera: Miridae), and Thrips palmi Karny (Thysanoptera: Thripidae).…”

Paninvasion severity assessment of a U.S. grape pest to disrupt the global wine market

“…Because we use MaxEnt, a presence only, correlative SDM method to estimate establishment, we measure suitability for SLF in a way that does not account for how SLF population density and possible plastic and adaptive responses to novel environmental conditions in invaded regions may affect establishment success. Omission of population density and other demographic variables can hinder accurate prediction, especially for SDMs 95 , and whenever possible, priority should be placed on using them alongside models that rely on pest physiology to predict establishment potential 96 . For SLF, two physiologically based models 44 , 45 largely correspond with our SDM-based establishment potentials and thus support the global establishment potential for SLF we report here.…”