{"title":"创新地理信息科学(GIS)和遥感工具用于模拟中生代保护区非洲草原象(Loxodonta africana)的巡游行为和栖息地动态","authors":"Nobert Tafadzwa Mukomberanwa, Phillip Taru, Beaven Utete, Patmore Ngorima","doi":"10.1111/aje.70000","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>Transboundary wildlife species like the African savannah elephant (<i>Loxodonta africana</i>) requires a comprehensive regional approach to monitoring and effective conservation. This requires a thorough understanding of their ecology, ranging behaviour and the distribution of suitable habitats. In diverse landscapes, the management and conservation of the African savannah elephant are critical, particularly in dry protected areas where water and food resources are limited. The use of innovative Geographic Information Science (GIS) and remote sensing tools is revolutionising the understanding of the ranging behaviour and habitat dynamics of the African savannah elephant. When adopting GIS and remote sensing tools, park managers and conservationists must remember that: (i) the African savannah elephant has a determinate movement pattern and clusters around dominant vegetation types, (ii) the soil-adjusted vegetation index (SAVI) performs better relative to other indices in modelling the distribution of the African savannah elephant in arid areas, (iii) cellular automata–artificial neural network (CA-ANN) is a robust technique in modelling future landscapes, (iv) landscapes or environments near water points are significantly utilised by the African savannah elephant and vegetation performance is usually better far from the piosphere, (v) significant difference in the size of the home ranges and habitat selection by the African savannah elephant is mostly influenced by vegetation type and seasonal variations of resources, (vi) hyperslender stems in forest gaps confirms minimal damage in African savannah elephant dominated landscapes (satellite data confirms evidence of high tree regeneration) and (vii) the dynamic Brownian Bridge Movement Model (dBBMM) is a smart technique for home range and utilisation distribution construction in different protected zones.</p>\n </div>","PeriodicalId":7844,"journal":{"name":"African Journal of Ecology","volume":"62 4","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Innovative Geographic Information Science (GIS) and Remote Sensing Tools for Modelling the Ranging Behaviour and Habitat Dynamics of the African Savannah Elephant (Loxodonta africana) in Mesic Protected Areas\",\"authors\":\"Nobert Tafadzwa Mukomberanwa, Phillip Taru, Beaven Utete, Patmore Ngorima\",\"doi\":\"10.1111/aje.70000\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <p>Transboundary wildlife species like the African savannah elephant (<i>Loxodonta africana</i>) requires a comprehensive regional approach to monitoring and effective conservation. This requires a thorough understanding of their ecology, ranging behaviour and the distribution of suitable habitats. In diverse landscapes, the management and conservation of the African savannah elephant are critical, particularly in dry protected areas where water and food resources are limited. The use of innovative Geographic Information Science (GIS) and remote sensing tools is revolutionising the understanding of the ranging behaviour and habitat dynamics of the African savannah elephant. When adopting GIS and remote sensing tools, park managers and conservationists must remember that: (i) the African savannah elephant has a determinate movement pattern and clusters around dominant vegetation types, (ii) the soil-adjusted vegetation index (SAVI) performs better relative to other indices in modelling the distribution of the African savannah elephant in arid areas, (iii) cellular automata–artificial neural network (CA-ANN) is a robust technique in modelling future landscapes, (iv) landscapes or environments near water points are significantly utilised by the African savannah elephant and vegetation performance is usually better far from the piosphere, (v) significant difference in the size of the home ranges and habitat selection by the African savannah elephant is mostly influenced by vegetation type and seasonal variations of resources, (vi) hyperslender stems in forest gaps confirms minimal damage in African savannah elephant dominated landscapes (satellite data confirms evidence of high tree regeneration) and (vii) the dynamic Brownian Bridge Movement Model (dBBMM) is a smart technique for home range and utilisation distribution construction in different protected zones.</p>\\n </div>\",\"PeriodicalId\":7844,\"journal\":{\"name\":\"African Journal of Ecology\",\"volume\":\"62 4\",\"pages\":\"\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2024-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"African Journal of Ecology\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/aje.70000\",\"RegionNum\":4,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ECOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"African Journal of Ecology","FirstCategoryId":"93","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/aje.70000","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ECOLOGY","Score":null,"Total":0}
Innovative Geographic Information Science (GIS) and Remote Sensing Tools for Modelling the Ranging Behaviour and Habitat Dynamics of the African Savannah Elephant (Loxodonta africana) in Mesic Protected Areas
Transboundary wildlife species like the African savannah elephant (Loxodonta africana) requires a comprehensive regional approach to monitoring and effective conservation. This requires a thorough understanding of their ecology, ranging behaviour and the distribution of suitable habitats. In diverse landscapes, the management and conservation of the African savannah elephant are critical, particularly in dry protected areas where water and food resources are limited. The use of innovative Geographic Information Science (GIS) and remote sensing tools is revolutionising the understanding of the ranging behaviour and habitat dynamics of the African savannah elephant. When adopting GIS and remote sensing tools, park managers and conservationists must remember that: (i) the African savannah elephant has a determinate movement pattern and clusters around dominant vegetation types, (ii) the soil-adjusted vegetation index (SAVI) performs better relative to other indices in modelling the distribution of the African savannah elephant in arid areas, (iii) cellular automata–artificial neural network (CA-ANN) is a robust technique in modelling future landscapes, (iv) landscapes or environments near water points are significantly utilised by the African savannah elephant and vegetation performance is usually better far from the piosphere, (v) significant difference in the size of the home ranges and habitat selection by the African savannah elephant is mostly influenced by vegetation type and seasonal variations of resources, (vi) hyperslender stems in forest gaps confirms minimal damage in African savannah elephant dominated landscapes (satellite data confirms evidence of high tree regeneration) and (vii) the dynamic Brownian Bridge Movement Model (dBBMM) is a smart technique for home range and utilisation distribution construction in different protected zones.
期刊介绍:
African Journal of Ecology (formerly East African Wildlife Journal) publishes original scientific research into the ecology and conservation of the animals and plants of Africa. It has a wide circulation both within and outside Africa and is the foremost research journal on the ecology of the continent. In addition to original articles, the Journal publishes comprehensive reviews on topical subjects and brief communications of preliminary results.