The spatial distribution of the woodland communities and their associated environmental drivers in the Golden Gate Highlands National Park, South Africa

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dc.contributor.author Daemane, Mahlomola E.
dc.contributor.author Ramoelo, Abel
dc.contributor.author Adelabu, Samuel
dc.date.accessioned 2022-05-17T03:43:19Z
dc.date.available 2022-05-17T03:43:19Z
dc.date.issued 2021-09-23
dc.description.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. en_US
dc.description.department Geography, Geoinformatics and Meteorology en_US
dc.description.librarian am2022 en_US
dc.description.uri http://www.koedoe.co.za en_US
dc.identifier.citation Daemane, M.E., Ramoelo, A. & Adelabu, S., 2021, ‘The spatial distribution of the woodland communities and their associated environmental drivers in the Golden Gate Highlands National Park, South Africa’, Koedoe 63(1), a1672. https://DOI.org/10.4102/koedoe.v63i1.1672. en_US
dc.identifier.issn 0075-6458 (print)
dc.identifier.issn 2071-0771 (online)
dc.identifier.other 10.4102/koedoe.v63i1.1672
dc.identifier.uri https://repository.up.ac.za/handle/2263/85221
dc.language.iso en en_US
dc.publisher AOSIS en_US
dc.rights © 2021. The Authors. Licensee: AOSIS. This work is licensed under the Creative Commons Attribution License. en_US
dc.subject Afromontane en_US
dc.subject Environmental parameters en_US
dc.subject Conservation en_US
dc.subject Biodiversity en_US
dc.subject Golden Gate Highlands National Park (GGHNP) en_US
dc.subject Generalized linear model (GLM) en_US
dc.title The spatial distribution of the woodland communities and their associated environmental drivers in the Golden Gate Highlands National Park, South Africa en_US
dc.type Article en_US


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