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| DOI | 10.1016/j.jag.2024.103738 |
| Multi-pronged abundance prediction of bee pests' spatial proliferation in Kenya | |
| 发表日期 | 2024 |
| ISSN | 1569-8432 |
| EISSN | 1872-826X |
| 起始页码 | 128 |
| 卷号 | 128 |
| 英文摘要 | Bee farming and beehealth are threatened by climate change, agricultural and agrochemicals intensification, and bee pests and diseases. Among these threats, bee pests have particularly been identified as a major obstacle to beehealth. Although previous studies have endeavoured to establish bee pests' spatial distribution, their seasonal abundance in the landscape remains poorly understood. Hence, this study sought to determine factors that influence the abundance and spatial proliferation of bee pests in Kenya. Abundance data on Varroa destructor, Oplostomus haroldi, Galleria mellonella and Aethina tumida were collected from apiaries in Kenya during the wet and dry seasons. The abundance data were fitted to non -conflating human footprint datasets, satellite derived vegetation phenological, topographical and bioclimatic variables. The results indicated a significant (p <= 0.05) seasonal influence on bee pests' abundance, while precipitation was the most relevant on most bee pests' abundance prediction models. Topographic and vegetation phenological influence varied across the landscapes while anthropogenic influence was comparatively low. High seasonality in bioclimatic variables influenced the projected (year 2055) spatial and abundance risk levels of bee pests across the study area. The V. destructor and A. tumida prediction models for current and future epochs ranked excellent in their performance, while O. haroldi and G. mellonella were ranked good and fair, respectively. Due to their precision, this study concluded that these models could reliably be used to establish bee pests' high -risk areas for management and mitigation purposes. |
| 英文关键词 | Beehealth; Food security; Climate change; Human footprint; Machine learning; Bee pest abundance |
| 语种 | 英语 |
| WOS研究方向 | Remote Sensing |
| WOS类目 | Remote Sensing |
| WOS记录号 | WOS:001207584200001 |
| 来源期刊 | INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
 |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/288829 |
| 作者单位 | International Centre of Insect Physiology & Ecology (ICIPE); University of Kwazulu Natal |
| 推荐引用方式 GB/T 7714 | . Multi-pronged abundance prediction of bee pests' spatial proliferation in Kenya[J],2024,128. |
| APA | (2024).Multi-pronged abundance prediction of bee pests' spatial proliferation in Kenya.INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,128. |
| MLA | "Multi-pronged abundance prediction of bee pests' spatial proliferation in Kenya".INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 128(2024). |
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