Chironomus plumosus is a pest with the potential to cause hygiene and safety issues within agricultural processing facilities. Assessing the potential distribution of agricultural facilities in advance could provide valuable data for effectively addressing these concerns. In this study, we used MaxEnt, a correlative species distribution modeling (SDM) algorithm, to assess the spatial distribution of C. plumosus in South Korea. This analysis incorporated climate change scenarios and environmental layers representing the locational density of agricultural processing facilities, thereby providing insights into the potential distribution patterns of pests. The model performance was 0.896, as evaluated using true skill statistics. It indicated a gradual shift in habitat towards the north, extending from the current potential occurrence regions along the coast. This study underscored the critical impact of climatic factors, such as temperature and precipitation, on pest habitat suitability. Furthermore, it demonstrated the effectiveness of combining environmental variables with agricultural facility distribution for accurate risk mapping. These findings provide a scientific basis for targeted monitoring and pest management strategies to enhance the efficiency of post-harvest processing, minimize pest-related risks, and ensure food safety in agricultural product processing centers (APCs).
{"title":"Spatial Evaluation of Chironomus plumosus Distribution Around Agricultural Processing Facilities in Response to Climate Change","authors":"Tae-Hyeon Kim, Jae-Min Jung, Wang-Hee Lee","doi":"10.1111/1748-5967.70048","DOIUrl":"https://doi.org/10.1111/1748-5967.70048","url":null,"abstract":"<p><i>Chironomus plumosus</i> is a pest with the potential to cause hygiene and safety issues within agricultural processing facilities. Assessing the potential distribution of agricultural facilities in advance could provide valuable data for effectively addressing these concerns. In this study, we used MaxEnt, a correlative species distribution modeling (SDM) algorithm, to assess the spatial distribution of <i>C. plumosus</i> in South Korea. This analysis incorporated climate change scenarios and environmental layers representing the locational density of agricultural processing facilities, thereby providing insights into the potential distribution patterns of pests. The model performance was 0.896, as evaluated using true skill statistics. It indicated a gradual shift in habitat towards the north, extending from the current potential occurrence regions along the coast. This study underscored the critical impact of climatic factors, such as temperature and precipitation, on pest habitat suitability. Furthermore, it demonstrated the effectiveness of combining environmental variables with agricultural facility distribution for accurate risk mapping. These findings provide a scientific basis for targeted monitoring and pest management strategies to enhance the efficiency of post-harvest processing, minimize pest-related risks, and ensure food safety in agricultural product processing centers (APCs).</p>","PeriodicalId":11776,"journal":{"name":"Entomological Research","volume":"55 5","pages":""},"PeriodicalIF":1.2,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1748-5967.70048","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144118140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}