Abstract
The objective of this paper was to evaluate the performance of crisp and fuzzy classification criteria in the construction of deductive potential distribution models of exotic insects. As case studies, Bactrocera oleae (Gmelin) (Diptera: Tephritidae) and Cerotoma arcuatus (Olivier) (Coleoptera: Chrysomelidae) were selected. Considering crisp and fuzzy classification for raster layers of maximum, average and minimum daily temperature, a relative bioclimatic risk index was generated. The number of days with optimal conditions for pests' development was considered. Sensitivity analyses of both models were performed. Considering each case evaluated and the variables used, deductive pest distribution models made by fuzzy classification was more robust and less conservative in the determination of potential phytosanitary risk areas than those made with crisp classification criteria. This last case was more sensitive and would have a greater capacity to discriminate areas with different environmental risk profiles
Highlights
IntroductionAgriculture, forestry, trade and other human activities have a determining role in the voluntary or accidental dispersion of species towards areas that they could not have reached without human assistance (Hlasny & Livingston, 2008)
Considering each case evaluated and the variables used, deductive pest distribution models made by fuzzy classification was more robust and less conservative in the determination of potential phytosanitary risk areas than those made with crisp classification criteria
This study supplemented the lack of data from meteorological stations located in high altitude sites, based on surface temperature values of 30 randomly selected points along the Andean mountain range, monthly average 2008-2012, from the information generated by the National Oceanic and Atmospheric Administration's (NOAA) meteorological satellite
Summary
Agriculture, forestry, trade and other human activities have a determining role in the voluntary or accidental dispersion of species towards areas that they could not have reached without human assistance (Hlasny & Livingston, 2008). Countries worldwide make great efforts to avoid dispersion of invasive species, regulating the phytosanitary condition of plant products on international trade (Levine & D'Antonio, 2003; Brenton-Rule et al, 2016). Qualitative risk assessments often provide sufficient technical solutions to perform pest risk analysis for a particular route of import, there are situations in which the use of species distribution models can help in decision-making, in order to identify areas at risk of invasion or to design monitoring protocols in the field in support of eradication programs for a new quarantine pest (Baker, 2012; Cardador et al, 2016). The challenge of estimating spatial distribution patterns of species has been addressed through different methodological approaches, which have been described and compared in several bibliographic reviews (Venette et al, 2010; Zimmermann et al, 2010; Mateo et al, 2011). Venette et al (2010) grouped the sets of techniques into two differential methodological approaches, called "deductive" or "inductive" approaches, the latter require information on the presence sites of the species
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