{"title":"西非贝宁木质素的空间分布、生态位模型以及气候和全球变化背景下的控制根除战略","authors":"Aïkpon Gorgias, Koura Kourouma, Ganglo C. Jean","doi":"10.5897/ijbc2021.1468","DOIUrl":null,"url":null,"abstract":"Benin’s native biodiversity, like other countries in the world, is facing biological invasions through the proliferation of invasive alien species. One of them, the pignut (Mesosphaerum suaveolens (L.) Kuntze, Lamiaceae), represents a serious threat to the biodiversity. The control of its spatial distribution and ecological niche are essential to understand its favorable spatial area and predict its dynamics. The objective of this study was to contribute to the biodiversity conservation. A total of 193 farmers and breeders, were subjected to a questionnaire in order to determine their knowledge with respect to M. suaveolens. The cumulative collection of occurrence data across the literature, the Global Biodiversity Information Facility (GBIF), and field data generated a total of 2900 occurrence points. Modeling across Africa using Maxent (version3.4.1) helped establish the potential and future distribution of this species. The Africlim climatic ensemble model was used with two climatic scenarios of the Intergovernmental Platform on Climate Change (IPCC): rcp4.5 and rcp8.5 horizon 2055. On 24 bioclimatic and environmental parameters tested, four bioclimatic variables who most contributed to the model were selected. Four risk level zones of invasion were identified: limited risk zone, risk zone, high risk zone, and very high risk zone. \n \n \n \n Key words: Maxent, biodiversity, modeling, biological invasions, Benin, Africa.","PeriodicalId":143839,"journal":{"name":"International Journal of Biodiversity and Conservation","volume":"119 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spatial distribution, ecological niche model of pignut and control eradication strategies in the context of climate and global change for Benin, West Africa\",\"authors\":\"Aïkpon Gorgias, Koura Kourouma, Ganglo C. Jean\",\"doi\":\"10.5897/ijbc2021.1468\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Benin’s native biodiversity, like other countries in the world, is facing biological invasions through the proliferation of invasive alien species. One of them, the pignut (Mesosphaerum suaveolens (L.) Kuntze, Lamiaceae), represents a serious threat to the biodiversity. The control of its spatial distribution and ecological niche are essential to understand its favorable spatial area and predict its dynamics. The objective of this study was to contribute to the biodiversity conservation. A total of 193 farmers and breeders, were subjected to a questionnaire in order to determine their knowledge with respect to M. suaveolens. The cumulative collection of occurrence data across the literature, the Global Biodiversity Information Facility (GBIF), and field data generated a total of 2900 occurrence points. Modeling across Africa using Maxent (version3.4.1) helped establish the potential and future distribution of this species. The Africlim climatic ensemble model was used with two climatic scenarios of the Intergovernmental Platform on Climate Change (IPCC): rcp4.5 and rcp8.5 horizon 2055. On 24 bioclimatic and environmental parameters tested, four bioclimatic variables who most contributed to the model were selected. Four risk level zones of invasion were identified: limited risk zone, risk zone, high risk zone, and very high risk zone. \\n \\n \\n \\n Key words: Maxent, biodiversity, modeling, biological invasions, Benin, Africa.\",\"PeriodicalId\":143839,\"journal\":{\"name\":\"International Journal of Biodiversity and Conservation\",\"volume\":\"119 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-07-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Biodiversity and Conservation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5897/ijbc2021.1468\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Biodiversity and Conservation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5897/ijbc2021.1468","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Spatial distribution, ecological niche model of pignut and control eradication strategies in the context of climate and global change for Benin, West Africa
Benin’s native biodiversity, like other countries in the world, is facing biological invasions through the proliferation of invasive alien species. One of them, the pignut (Mesosphaerum suaveolens (L.) Kuntze, Lamiaceae), represents a serious threat to the biodiversity. The control of its spatial distribution and ecological niche are essential to understand its favorable spatial area and predict its dynamics. The objective of this study was to contribute to the biodiversity conservation. A total of 193 farmers and breeders, were subjected to a questionnaire in order to determine their knowledge with respect to M. suaveolens. The cumulative collection of occurrence data across the literature, the Global Biodiversity Information Facility (GBIF), and field data generated a total of 2900 occurrence points. Modeling across Africa using Maxent (version3.4.1) helped establish the potential and future distribution of this species. The Africlim climatic ensemble model was used with two climatic scenarios of the Intergovernmental Platform on Climate Change (IPCC): rcp4.5 and rcp8.5 horizon 2055. On 24 bioclimatic and environmental parameters tested, four bioclimatic variables who most contributed to the model were selected. Four risk level zones of invasion were identified: limited risk zone, risk zone, high risk zone, and very high risk zone.
Key words: Maxent, biodiversity, modeling, biological invasions, Benin, Africa.