| Autor: |
Xinle Guo, Kunyuan Wanghe, Shahid Ahmad, Ghulam Nabi, Ke Zhang, Linghong Zhu, Dengguo Lu, Dezhong Han, Kai Zhou, Ivan Igorevich Strelnikov, Tauheed Ullah Khan, Kai Li, Kai Zhao |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
Journal of King Saud University: Science, Vol 34, Iss 3, Pp 101905- (2022) |
| Druh dokumentu: |
article |
| ISSN: |
1018-3647 |
| DOI: |
10.1016/j.jksus.2022.101905 |
| Popis: |
Insecticide application is still a standard method in pest management. However, the current regions for insecticide application usually focus on the host of the pest but ignore the migration pathways, continually resulting in pests’ periodic outbreaks. This research provides a valuable modeling framework to identify optimal regions for insecticide application to solve this problem. This modeling framework optimizes insecticide areas based on habitat suitability and landscape connectivity, combining the MaxEnt and circuit theory. We conducted a case study in Beijing, China, to elucidate the application of this modeling framework. The input data included 517 occurrence points of Semiothisa cinerearia collected in the fieldwork and the environmental variables related to the eco-physiological characteristics of this species. The results indicated that the Chinese scholar tree (Styphnolobium japonicum) was the most vulnerable species. Increasing the pesticide region by 11.9% at some crucial corridors of the target species, the pest management effectiveness increased by 27.7%, compared with the pesticide applied only to the Chinese scholar trees. In summary, this study proposed a convenient and efficient modeling methodology for planning optimal regions for insecticide application. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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