Rangeland Ecology & Management

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The South African National Vegetation Database: History, development, applications, problems and future
Author
Rutherford, M C
L, Mucina
Powrie, L W
Publisher
South African Journal of Science
Publication Year
2012
Body

Southern Africa has been recognised as one of the most interesting and important areas of the world from an ecological and evolutionary point of view. The establishment and development of the National Vegetation Database (NVD) of South Africa enabled South Africa to contribute to environmental planning and conservation management in this floristically unique region. In this paper, we aim to provide an update on the development of the NVD since it was last described, near its inception, more than a decade ago. The NVD was developed using the Turboveg software environment, and currently comprises 46 697 vegetation plots (relevés) sharing 11 690 plant taxa and containing 968 943 species occurrence records. The NVD was primarily founded to serve vegetation classification and mapping goals but soon became recognised as an important tool in conservation assessment and target setting. The NVD has directly helped produce the National Vegetation Map, National Forest Type Classification, South African National Biodiversity Assessment and Forest Type Conservation Assessment. With further development of the NVD and more consistent handling of the legacy data (old data sets), the current limitations regarding certain types of application of the data should be significantly reduced. However, the use of the current NVD in multidisciplinary research has certainly not been fully explored. With the availability of new pools of well-trained vegetation surveyors, the NVD will continue to be purpose driven and serve the needs of biological survey in pursuit of sustainable use of the vegetation and flora resources of the southern African subcontinent.

Language
English
Resource Type
Text
Document Type
Journal Issue/Article
Journal Name
South African Journal of Science
Keywords
conservation targets
data combinations
ecoinformatics
locality confidence
species bias
Turboveg
South Africa