{"title":"南非金门高地国家公园林地群落的空间分布及其环境驱动因素","authors":"M. E. Daemane, A. Ramoelo, S. Adelabu","doi":"10.4102/koedoe.v63i1.1672","DOIUrl":null,"url":null,"abstract":"The extreme variability in the topography, altitude and climatic conditions in the temperate Grassland Mountains of Southern Africa is associated with the complex mosaic of grassland communities with pockets of woodland patches. Understanding the relationships between plant communities and environmental parameters is essential in biodiversity conservation, especially for current and future climate change predictions. This article focused on the spatial distribution of woodland communities and their associated environmental drivers in the Golden Gate Highlands (GGHNP) National Park in South Africa. A generalized linear model (GLM) assuming a binomial distribution, was used to determine the optimal environmental variables influencing the spatial distribution of the woodland communities. The Coefficient of Variation (CV) was relatively higher for the topographic ruggedness index (68.78%), topographic roughness index (68.03), aspect (60.04%), coarse fragments (37.46%) and the topographic wetness index (31.33) whereas soil pH, bulk density, sandy and clay contents had relatively less variation (2.39%, 3.23%, 7.56% and 8.46% respectively). In determining the optimal number of environmental variables influencing the spatial distribution of woodland communities, roughness index, topographic wetness index, soil coarse fragments, soil organic carbon, soil cation exchange capacity and remote-sensing based vegetation condition index were significant (p 0.05) and positively correlated with the woodland communities. Soil nitrogen, clay content, soil pH, fire and elevation were also significant but negatively correlated with the woodland communities. The area under the curve (AUC) of the receiver operating characteristics (ROC) was 0.81. This was indicative of a Parsimonious Model with explanatory predictive power for determination of optimal environmental variables in vegetation ecology.Conservation implications: The isolated woodland communities are sources of floristic diversity and important biogeographical links between larger forest areas in the wider Drakensberg region. They provide suitable habitats for a larger number of forest species and harbour some of the endemic tree species of South Africa. They also provide watershed protection and other important ecosystem services. Understanding the drivers influencing the spatial distribution and persistence of these woodland communities is therefore key to conservation planning in the area.","PeriodicalId":48892,"journal":{"name":"Koedoe","volume":"4 1","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The spatial distribution of the woodland communities and their associated environmental drivers in the Golden Gate Highlands National Park, South Africa\",\"authors\":\"M. E. Daemane, A. Ramoelo, S. Adelabu\",\"doi\":\"10.4102/koedoe.v63i1.1672\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The extreme variability in the topography, altitude and climatic conditions in the temperate Grassland Mountains of Southern Africa is associated with the complex mosaic of grassland communities with pockets of woodland patches. Understanding the relationships between plant communities and environmental parameters is essential in biodiversity conservation, especially for current and future climate change predictions. This article focused on the spatial distribution of woodland communities and their associated environmental drivers in the Golden Gate Highlands (GGHNP) National Park in South Africa. A generalized linear model (GLM) assuming a binomial distribution, was used to determine the optimal environmental variables influencing the spatial distribution of the woodland communities. The Coefficient of Variation (CV) was relatively higher for the topographic ruggedness index (68.78%), topographic roughness index (68.03), aspect (60.04%), coarse fragments (37.46%) and the topographic wetness index (31.33) whereas soil pH, bulk density, sandy and clay contents had relatively less variation (2.39%, 3.23%, 7.56% and 8.46% respectively). In determining the optimal number of environmental variables influencing the spatial distribution of woodland communities, roughness index, topographic wetness index, soil coarse fragments, soil organic carbon, soil cation exchange capacity and remote-sensing based vegetation condition index were significant (p 0.05) and positively correlated with the woodland communities. Soil nitrogen, clay content, soil pH, fire and elevation were also significant but negatively correlated with the woodland communities. The area under the curve (AUC) of the receiver operating characteristics (ROC) was 0.81. This was indicative of a Parsimonious Model with explanatory predictive power for determination of optimal environmental variables in vegetation ecology.Conservation implications: The isolated woodland communities are sources of floristic diversity and important biogeographical links between larger forest areas in the wider Drakensberg region. They provide suitable habitats for a larger number of forest species and harbour some of the endemic tree species of South Africa. They also provide watershed protection and other important ecosystem services. Understanding the drivers influencing the spatial distribution and persistence of these woodland communities is therefore key to conservation planning in the area.\",\"PeriodicalId\":48892,\"journal\":{\"name\":\"Koedoe\",\"volume\":\"4 1\",\"pages\":\"\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2021-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Koedoe\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.4102/koedoe.v63i1.1672\",\"RegionNum\":4,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BIODIVERSITY CONSERVATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Koedoe","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.4102/koedoe.v63i1.1672","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIODIVERSITY CONSERVATION","Score":null,"Total":0}
The spatial distribution of the woodland communities and their associated environmental drivers in the Golden Gate Highlands National Park, South Africa
The extreme variability in the topography, altitude and climatic conditions in the temperate Grassland Mountains of Southern Africa is associated with the complex mosaic of grassland communities with pockets of woodland patches. Understanding the relationships between plant communities and environmental parameters is essential in biodiversity conservation, especially for current and future climate change predictions. This article focused on the spatial distribution of woodland communities and their associated environmental drivers in the Golden Gate Highlands (GGHNP) National Park in South Africa. A generalized linear model (GLM) assuming a binomial distribution, was used to determine the optimal environmental variables influencing the spatial distribution of the woodland communities. The Coefficient of Variation (CV) was relatively higher for the topographic ruggedness index (68.78%), topographic roughness index (68.03), aspect (60.04%), coarse fragments (37.46%) and the topographic wetness index (31.33) whereas soil pH, bulk density, sandy and clay contents had relatively less variation (2.39%, 3.23%, 7.56% and 8.46% respectively). In determining the optimal number of environmental variables influencing the spatial distribution of woodland communities, roughness index, topographic wetness index, soil coarse fragments, soil organic carbon, soil cation exchange capacity and remote-sensing based vegetation condition index were significant (p 0.05) and positively correlated with the woodland communities. Soil nitrogen, clay content, soil pH, fire and elevation were also significant but negatively correlated with the woodland communities. The area under the curve (AUC) of the receiver operating characteristics (ROC) was 0.81. This was indicative of a Parsimonious Model with explanatory predictive power for determination of optimal environmental variables in vegetation ecology.Conservation implications: The isolated woodland communities are sources of floristic diversity and important biogeographical links between larger forest areas in the wider Drakensberg region. They provide suitable habitats for a larger number of forest species and harbour some of the endemic tree species of South Africa. They also provide watershed protection and other important ecosystem services. Understanding the drivers influencing the spatial distribution and persistence of these woodland communities is therefore key to conservation planning in the area.
期刊介绍:
Koedoe, with the subtitle ''African Protected Area Conservation and Science'', promotes and contributes to the scientific (biological) and environmental (ecological and biodiversity) conservation practices of Africa by defining the key disciplines that will ensure the existence of a wide variety of plant and animal species in their natural environments (biological diversity) in Africa.