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Data and Code: Increasing global risk of khapra beetle invasion forecasted under diverse environmental conditions

Published by Agricultural Research Service | Department of Agriculture | Metadata Last Checked: January 27, 2026 | Last Modified: 2025-11-21
The khapra beetle, Trogoderma granarium, is a stored product pest of global concern. The pest is readily transported with cargo and has been reported in over 60 countries, several of which have spent millions in USD to eradicate populations. Despite the profound risk to stored grain commodities, nothing is known about the influence of climate change on the potential future distribution of species. We utilize MaxEnt and two datasets representing 1) only the historical range and 2) all global locations where it currently is or was established even if it was later eradicated to model areas of suitability under current climatic conditions and project to the future with the accumulated data under low (SSP126) and high (SSP585) climate change scenarios at close (2040) and distant (2080) time points. The potential distribution using historical data was much reduced compared to the combined model; consequently, all established localities, even if eradicated, change model outcomes and thus are important when building models. An increase of high potential suitability (>75% suitable) is projected with greater time and climatic scenarios, primarily in North America and Europe, which have previously eradicated T. granarium. These areas need greater surveillance for early detection and eradication to prevent expansion of T. granarium inland toward areas of high grain production.The dataset provided includes all occurrence data points used in the manuscript "Increasing global risk of khapra beetle invasion forecasted under diverse environmental conditions" including longitude and latitude and the reference or repository where the data point was obtained. The code provided is the backbone of the MaxEnt modeling procedure used to make distribution predictions for current and future climate change predictions.

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