ArticleEnvironmental entomology2025
A proposed method for estimating habitat suitability of weed biological control agents with experimentally derived thermal injury and weather data.
Article in Environmental entomology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Ecological niche modelling provides a tool for making a priori predictions of habitat suitability for biological control agents. Current approaches may be limited by available data but improved by the incorporation of physiological data. Alligatorweed, Alternanthera philoxeroides (Mart.) Griseb. (Caryophyllales: Ameranthaceae), is controlled across much of its introduced range in the United States of America by the alligatorweed flea beetle, Agasicles hygrophila Selman and Vogt (Coleoptera: Chrysomelidae); however, insufficient control is observed at temperate latitudes. Investigations into alligatorweed thrips, Amynothrips andersoni O'Neill (Thysanoptera: Phlaeothripidae), indicate that they are more cold-tolerant with a broader predicted range. The upper limit of the chill injury zone (ULCIZ) and the sum of injurious temperatures (SIT) are measures that can be used to compare relative cold tolerance among biocontrol agents. Here we propose a method for integrating these parameters with weather data to predict overwintering mortality. The ULCIZ and SIT of Am. andersoni and Ag. hygrophila were experimentally determined, then habitat suitability for each species was modeled using the proposed method and 20 yr of weather data. ULCIZ was -2.94 and 4.52 °C, and SIT was 307.19 and 251.27 for Am. andersoni and Ag. hygrophila, respectively, indicating that Am. andersoni begins accumulating chill injury at a lower temperature than Ag. hygrophila and does so at a slower rate. Using this method, 91.8% of Al. philoxeroides's range in the USA was predicted to fall within highly or moderately suitable habitat for Am. andersoni, compared to 15.9% for Ag. hygrophila. Ranges predicted by the proposed method are similar to previous correlative ENMs.
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