{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T13:21:35Z","timestamp":1788268895690,"version":"build-2803163510"},"reference-count":33,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2026,8,29]],"date-time":"2026-08-29T00:00:00Z","timestamp":1787961600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Beijing Natural Science Foundation of China","award":["L251049"],"award-info":[{"award-number":["L251049"]}]},{"name":"Forestry Science and Technology Innovation Project of Jiangxi Forestry Bureau","award":["2026-06"],"award-info":[{"award-number":["2026-06"]}]},{"name":"Longjiang Forest Group Science and Technology Project","award":["KJXM-SQ2025-00093"],"award-info":[{"award-number":["KJXM-SQ2025-00093"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Insects"],"abstract":"<jats:p>The temporal dynamics of forest-associated insects are closely associated with climatic variability, and identifying their temporal patterns and climatic associations is important for understanding insect population dynamics. In this study, automatically recorded Coleoptera and Lepidoptera in Rui\u2019an City, Zhejiang Province, China, were selected as the target insect groups. Based on automatic insect monitoring and meteorological data, the temporal characteristics of recorded insect abundance and their associations with climatic factors were analyzed. Five machine learning models, including Multiple Linear Regression, K-Nearest Neighbors, Random Forest, Support Vector Regression, and Generalized Additive Model, were then developed and compared for predicting recorded insect abundance. The results showed that Coleoptera exhibited periodic fluctuations with cycles of approximately 6\u201320 days, whereas Lepidoptera displayed persistent seasonal variation. Air temperature, specific humidity, and shortwave radiation were significantly and positively correlated with recorded insect abundance, while wind speed showed a weak negative correlation. Among the five models, Random Forest achieved the best prediction performance, with MAE, RMSE, and R2 values of 1.37, 4.85, and 0.82 for Coleoptera and 0.57, 1.16, and 0.84 for Lepidoptera, respectively. Independent-year validation using 2023 data showed reduced predictive performance compared with random validation, indicating limited temporal generalization under the available observation period. These findings demonstrate that integrating temporal characteristics with climatic factors can support the prediction of automatically recorded insect abundance, while longer-term monitoring data are needed to further evaluate model robustness and temporal transferability.<\/jats:p>","DOI":"10.3390\/insects17090906","type":"journal-article","created":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T12:41:18Z","timestamp":1788266478000},"page":"906","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Occurrence Dynamics and Prediction of Coleoptera and Lepidoptera in China Using Multiple Machine Learning Models"],"prefix":"10.3390","volume":"17","author":[{"given":"Hong","family":"Sun","sequence":"first","affiliation":[{"name":"Center for Biological Disaster Prevention and Control, National Forestry and Grassland Administration, Shenyang 110034, China"},{"name":"Key Laboratory of National Forestry and Grassland Administration on Invasive Alien Species Prevention and Control, National Forestry and Grassland Administration, Shenyang 110034, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"data-curation","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"given":"Jiaqi","family":"Zhang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Efficient Production of Forest Resources, Beijing Forestry University, Beijing 100083, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"methodology","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-9913-0561","authenticated-orcid":false,"given":"Xiumei","family":"Mo","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Efficient Production of Forest Resources, Beijing Forestry University, Beijing 100083, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"methodology","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"given":"Chenshu","family":"Zhang","sequence":"additional","affiliation":[{"name":"Center for Biological Disaster Prevention and Control, National Forestry and Grassland Administration, Shenyang 110034, China"},{"name":"Key Laboratory of National Forestry and Grassland Administration on Invasive Alien Species Prevention and Control, National Forestry and Grassland Administration, Shenyang 110034, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"data-curation","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"}]},{"given":"Ziqi","family":"Wang","sequence":"additional","affiliation":[{"name":"Center for Biological Disaster Prevention and Control, National Forestry and Grassland Administration, Shenyang 110034, China"},{"name":"Key Laboratory of National Forestry and Grassland Administration on Invasive Alien Species Prevention and Control, National Forestry and Grassland Administration, Shenyang 110034, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"data-curation","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"}]},{"given":"Jixia","family":"Huang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Efficient Production of Forest Resources, Beijing Forestry University, Beijing 100083, China"},{"name":"Key Laboratory of Land Surface Pattern and Simulation, Chinese Academy of Science, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"project-administration","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"8023","DOI":"10.1002\/ps.70112","article-title":"Considering compound drought and heatwave events significantly improve forest pest occurrence prediction","volume":"81","author":"Huang","year":"2025","journal-title":"Pest Manag. Sci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"122788","DOI":"10.1016\/j.foreco.2025.122788","article-title":"Potential of thinning to increase forest resilience and resistance to drought, pest, windstorm and fire: A meta-analysis","volume":"590","author":"Chagnon","year":"2025","journal-title":"For. Ecol. Manag."},{"key":"ref_3","unstructured":"Masson-Delmotte, V., Zhai, P., P\u00f6rtner, H.-O., Roberts, D., Skea, J., Shukla, P.R., Pirani, A., Moufouma-Okia, W., P\u00e9an, C., and Pidcock, R. (2018). Summary for Policymakers. Global Warming of 1.5\u00b0C: An IPCC Special Report on the Impacts of Global Warming of 1.5\u00b0C Above Pre-Industrial Levels and Related Global Greenhouse Gas Emission Pathways, in the Context of Strengthening the Global Response to the Threat of Climate Change, Sustainable Development, and Efforts to Eradicate Poverty, Cambridge University Press."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"122324","DOI":"10.1016\/j.foreco.2024.122324","article-title":"Uncovering hazards and adaptive capacity: A comprehensive risk assessment study in three conservation areas in Spain","volume":"572","year":"2024","journal-title":"Forest Ecol. Manag."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"107800","DOI":"10.1016\/j.ecolecon.2023.107800","article-title":"The effect of pests and pathogens on forest harvesting regimes: A bioeconomic model","volume":"209","author":"McTaggart","year":"2023","journal-title":"Ecol. Econ."},{"key":"ref_6","first-page":"100865","article-title":"From data to action: MaxEnt-based conservation planning for Buxus hyrcana Pojark in the Hyrcanian forest","volume":"28","author":"Hesabi","year":"2025","journal-title":"Environ. Sustain. Ind."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1111\/icad.70002","article-title":"Spatial prediction of Melanoplus differentialis using an ensemble of multiple species distribution models","volume":"19","author":"Yoon","year":"2026","journal-title":"Insect Conserv. Diver"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2713","DOI":"10.1111\/1365-2745.13196","article-title":"Root-feeding larvae increase their performance by inducing leaf volatiles that attract above-ground conspecific adults","volume":"107","author":"Sun","year":"2019","journal-title":"J. Ecol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"4216","DOI":"10.1002\/ps.8125","article-title":"Light intensity differentially mediates the life cycle of lepidopteran leaf feeders and stem borers","volume":"80","author":"Xu","year":"2024","journal-title":"Pest Manag. Sci."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"118774","DOI":"10.1016\/j.foreco.2020.118774","article-title":"The effect of coppicing on insect biodiversity. Small-scale mosaics of successional stages drive community turnover","volume":"483","author":"Weiss","year":"2021","journal-title":"For. Ecol. Manag."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"9264","DOI":"10.1002\/ps.70970","article-title":"Distribution and seasonal dynamics of two distinct sex pheromone types in Cnaphalocrocis medinalis moths across China","volume":"82","author":"Guo","year":"2026","journal-title":"Pest Manag. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"123172","DOI":"10.1016\/j.foreco.2025.123172","article-title":"Population phase-dependent niche requirements may limit outbreaks of the range-expanding mountain pine beetle in the western boreal forest","volume":"597","author":"Pokorny","year":"2025","journal-title":"For. Ecol. Manag."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Xavier, R.G., Martins, F.B., and Dias, C.G. (2026). Integrated Climate, pest, and Disease Risk Indicators for Pinus Plantations Under Current and Future Climates. Earth Syst. Environ.","DOI":"10.1007\/s41748-026-01195-3"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Zhao, J., Wang, M., Cai, D., Wu, L., Ji, X., Ding, Q., Wang, F., and Wang, M. (2025). Spatiotemporal Changes of Pine Caterpillar Infestation Risk and the Driving Effect of Habitat Factors in Northeast China. Remote Sens., 17.","DOI":"10.3390\/rs17101738"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"142488","DOI":"10.1016\/j.jhazmat.2026.142488","article-title":"An emerging risk to pest biocontrol: Polyethylene microplastic affects the efficacy of Arma chinensis and Beauveria bassiana against Hyphantria cunea","volume":"513","author":"Tan","year":"2026","journal-title":"J. Hazard. Mater."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"6550","DOI":"10.1002\/ps.70008","article-title":"Risk prediction of pine wilt disease based on graphical convolutional network in China","volume":"81","author":"Mo","year":"2025","journal-title":"Pest Manag. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"122875","DOI":"10.1016\/j.foreco.2025.122875","article-title":"Integrating disturbance to improve our understanding of range-wide patterns in tree species abundance and demography","volume":"593","author":"Gougherty","year":"2025","journal-title":"For. Ecol. Manag."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"109283","DOI":"10.1016\/j.compag.2024.109283","article-title":"Fall armyworm habitat analysis in Africa with multi-source earth observation data","volume":"225","author":"Qi","year":"2024","journal-title":"Comput. Electron. Agr."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"128999","DOI":"10.1016\/j.jenvman.2026.128999","article-title":"Pesticide use and climate-driven pest pressure in smallholder agriculture in equatorial Africa","volume":"401","author":"Diem","year":"2026","journal-title":"J. Environ. Manag."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"121872","DOI":"10.1016\/j.foreco.2024.121872","article-title":"Incidence and severity of Phoracantha-induced decline within high-elevation eucalypt woodlands are strongly associated with elevation and land management","volume":"561","author":"Brookhouse","year":"2024","journal-title":"For. Ecol. Manag."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1016\/j.gloplacha.2006.07.028","article-title":"Climate-induced boreal forest change: Predictions versus current observations","volume":"56","author":"Soja","year":"2007","journal-title":"Glob. Planet. Change"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"110763","DOI":"10.1016\/j.ecolmodel.2024.110763","article-title":"Predicting insect population dynamics by linking phenology models and monitoring data","volume":"493","author":"Rincon","year":"2024","journal-title":"Ecol. Model."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"115236","DOI":"10.1016\/j.asoc.2026.115236","article-title":"The role of artificial neural networks in mathematical modeling: From single architecture to hybrid frameworks in environmental system","volume":"198","author":"Singh","year":"2026","journal-title":"Appl. Soft Comput."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"e11833","DOI":"10.1002\/oik.11833","article-title":"Meteorological versus spatial drivers of the spatial synchrony of forest insect pest outbreaks in North America","volume":"2026","author":"Haynes","year":"2026","journal-title":"Oikos"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"103203","DOI":"10.1016\/j.ecoinf.2025.103203","article-title":"Regression analysis and artificial neural networks for predicting pine species volume in community forests","volume":"89","year":"2025","journal-title":"Ecol. Inform."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Dong, L., Yang, X., Jin, X., Liu, X., Gao, M., and Fang, J. (2026). Life History Traits and Developmental Duration of the Yellow Coster Telchinia issoria H\u00fcbner, 1819 (Lepidoptera: Nymphalidae) Under Laboratory Conditions. Insects, 17.","DOI":"10.3390\/insects17020216"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1146\/annurev.en.02.010157.001005","article-title":"Dynamics of Insect Populations","volume":"2","author":"Solomon","year":"1957","journal-title":"Annu. Rev. Entomol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1007\/s10144-005-0239-7","article-title":"How to analyze long-term insect population dynamics under climate change: 50-year data of three insect pests in paddy fields","volume":"48","author":"Yamamura","year":"2006","journal-title":"Popul. Ecol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/j.anbehav.2024.10.015","article-title":"Behavioural thermoregulation compensates for changes in solar insolation in a wild insect","volume":"218","author":"Gardner","year":"2024","journal-title":"Anim. Behav."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"101133","DOI":"10.1016\/j.cois.2023.101133","article-title":"Forecasting insect dynamics in a changing world","volume":"60","author":"Bahlai","year":"2023","journal-title":"Curr. Opin. Insect Sci."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1595","DOI":"10.1111\/gcb.13142","article-title":"Model-specification uncertainty in future forest pest outbreak","volume":"22","author":"Boulanger","year":"2016","journal-title":"Glob. Change Biol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","article-title":"Long short-term memory","volume":"9","author":"Hochreiter","year":"1997","journal-title":"Neural Comput."}],"container-title":["Insects"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2075-4450\/17\/9\/906\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T12:54:21Z","timestamp":1788267261000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2075-4450\/17\/9\/906"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,29]]},"references-count":33,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2026,9]]}},"alternative-id":["insects17090906"],"URL":"https:\/\/doi.org\/10.3390\/insects17090906","relation":{},"ISSN":["2075-4450"],"issn-type":[{"value":"2075-4450","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,29]]}}}