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This study aimed to identify the global risk of invasion and establishment of Bedellia somnulentella, a pest of the sweet potato crop, for the present and future time, to develop policies and prevent future outbreaks. Current climate projections and future (2030, 2050, 2070, and 2100) of the insect B. somnulentella were carried out using CLIMEX. The projections showed that climate change could reduce areas of high aptitude for B. somnulentella in the parallel range of latitude 0°, the equator. On the other hand, temperate regions in the parallels with latitudes above 30°S and 30°N can increase hot and humid stress and become more suitable for the pest. This survey is based on weather data only. Data on land use and types, biotic interactions, diseases, natural enemies, alternative hosts, and competition were not considered for this model. Another uncertainty is associated with future levels of greenhouse gas emissions. The data presented here are helpful for the development of policies, studies, and strategies for the management of the B. somnulentella pest in the field. We encourage agricultural organizations in various countries to make strategic and long-term plans to avoid losses of millions of dollars through B. somnulentella. [ABSTRACT FROM AUTHOR]

A sensitivity analysis can categorize levels of parameter influence on a model's output. Identifying parameters having the most influence facilitates establishing the best values for parameters of models, providing useful implications in species modelling of crops and associated insect pests. The aim of this study was to quantify the response of species models through a CLIMEX sensitivity analysis. Using openfield Solanum lycopersicum and Neoleucinodes elegantalis distribution records, and 17 fitting parameters, including growth and stress parameters, comparisons were made in model performance by altering one parameter value at a time, in comparison to the best-fit parameter values. Parameters that were found to have a greater effect on the model results are termed Bsensitive^. Through the use of two species, we show that even when the Ecoclimatic Index has a major change through upward or downward parameter value alterations, the effect on the species is dependent on the selection of suitability categories and regions of modelling. Two parameters were shown to have the greatest sensitivity, dependent on the suitability categories of each species in the study. Results enhance user understanding of which climatic factors had a greater impact on both species distributions in our model, in terms of suitability categories and areas, when parameter values were perturbed by higher or lower values, compared to the best-fit parameter values. Thus, the sensitivity analyses have the potential to provide additional information for end users, in terms of improving management, by identifying the climatic variables that are most sensitive. [ABSTRACT FROM AUTHOR]

In economic terms, invasive species pose risks to human interests in management systems related to agriculture, animal health, and forestry, as they cause damage and change the composition of native species. Through modeling, ecological studies can help identify favorable climatic environments for species. Using biological factors and climate data, the CLIMEX software can forecast a species' seasonal phenology and dispersal locations across time. The Caribbean fruit fly, Anastrepha suspensa (Diptera: Tephritidae), was modeled using CLIMEX to assess the variables affecting its population and dispersal processes. The results show A. suspensa climatic suitability in South America, Central America, Africa, and Oceania. The most critical adaptation happens in the Caribbean and Central America between September and December, while it happens in South America between February and April. The sensitivity analysis showed that the species is more sensitive to temperature changes. Our results were validated through field data reports. Modeling has significant implications since it may be used to develop control and monitoring methods in situations and locations with favorable climates for A. suspensa, particularly in cases when the pest is not present. [ABSTRACT FROM AUTHOR]

Macaúba (Acrocomia aculeata) is a palm tree with a high potential for plant-based raw material production, particularly bioenergy production; it is one of the most promising species for cultivation on marginal lands. This study aimed to determine the distribution of A. aculeata species worldwide and verify the Köppen–Geiger climatic classifications of its locations. Research on the global occurrence of A. aculeata was conducted to characterize the geographic dispersal of macaúba. Based on the distribution points of the species, the Köppen–Geiger classification was determined for each occurrence point. Subsequently, a map was created that showed the regions with potential for the introduction of macaúba based on the climatic data compiled. Macaúba is distributed throughout the American continents, with the highest occurrence rates in Latin America (followed by those in North America and finally Central America). Particularly, Brazil and Mexico exhibit the highest occurrence rates. According to the distribution, the Köppen–Geiger climatic classification determined the predominance of macaúba in the savanna climate. Some countries located in Central Africa, Southern Asia, and Northern Australia showed the potential to introduce macaúba as a bioenergetic source. [ABSTRACT FROM AUTHOR]