KWA-NIBELA PENINSULA, ST LUCIA IN SOUTH AFRICA
B.M. Corrigan1*, B-E Van Wyk1 and C.J. Geldenhuys2
1Department of Botany and Plant Biotechnology, University of Johannesburg, Auckland Park, Johannesburg, South Africa
2Forestwood cc, Pretoria & Department of Forest and Wood Science, University of Stellenbosch, Stellenbosch, South Africa
*Corresponding author: [email protected]
Abstract
The KwaNibela Peninsula is situated at the northern-most part of Lake St Lucia in KwaZulu-Natal, South Africa and is covered by patches of forest, which are utilised rather heavily by the inhabitants of this area. The aims of this study were to map the current and historical extent of the forest patches and quantify the changes, using structural and compositional data gathered in the field. The reasons for doing so were to determine whether the forest patches have increased or decreased in extent, whether the changes can be attributed to both natural and anthropogenic factors, whether intervention is necessary to promote sustainable harvesting practices, and to develop a basis for developing a conservation management plan for KwaNibela. The forested area in KwaNibela is classified as either Sand Forest or Maputaland Coastal Forest. The compositional data was used to verify or refute these classifications and determine whether Sand Forest exists in KwaNibela. Seven series of aerial photos from 1937, 1960, 1969, 1979, 1990, 2002 and 2008 were used to track the changes in cover type. The photos were digitized, georeferenced, image-processed and mosaiced in TNTMips 7.0. Filters were run in ArcView 9.2 to classify the cover types into core forest, transitional thicket, woodland/grassland and disturbed areas. The percentages of each cover type were compared, for each year, to determine the overall changes in vegetation. Structural and compositional data were collected from sample plots along nine transects, to represent different stages of forest succession. The data were analysed, using TWINSPAN and CANOCO, to quantify the floristic and structural changes in the vegetation.
Introduction
Deforestation is a trend of global significance as the reduction in forest-based carbon-sink is considered to have a detrimental impact on climate change. Burgeoning human populations in forested areas have led to increased pressure on timber and non-timber forest products and in many cases, wide-scale degradation and depletion of previously forested areas.
At a loc
and building and handcraft materials. This resource use is currently unmonitored and unmanaged and the sustainability thereof is questionable.
This study determined the spatial changes of the land cover types on the peninsula over the last 71 years to give an indication of the reference conditions of the area as other historical data, such as fixed point photography, previous fauna and flora surveys or historical records, was not available for KwaNibela. The spatial data also specify the nature of the change, which can be attributed to natural oscillations and/or anthropogenic influences. The vegetation structure of the different cover types was determined to assess regeneration potential of the forest patches as old-growth forest patches (core forest) are more likely to remain stable, whereas the re-growth forest (transitional thicket) is the more dynamic buffer zone in which regeneration and bush encroachment occur. The open areas (grassland/woodland and disturbed patches) are only briefly discussed. Species composition for each land cover type was determined to assess species diversity and abundances as well as to assess the current classification of the forest patches on KwaNibela as Licuati Sand Forest (Von Maltitz et al.
2003). Ultimately, this study will contribute towards informing a participatory management plan for the KwaNibela Peninsula, in which the interests of the KwaNibela inhabitants are melded with the conservation of this valuable resource.
Methodology
Past and present distribution of forest patches
8-bit Greyscale aerial photographs of varying scales and resolutions were obtained from the Chief Surveyor General (Mowbray, RSA) and were used to map the spatial-temporal changes in forest cover of the KwaNibela Peninsula. A series of six years, spaced approximately 10 years apart, was available: 1937, 1960, 1969, 1979, 1990 and 2002 and a 2008 Google Earth image was studied to represent the most current state of forest cover on the peninsula (Google Corporation 2008).
The aerial photographs were digitized, geo-referenced to a topographical map and mosaiced in TNTMips 7.0 to create spatially-accurate single images for each year. The images were then processed in Corel PHOTO-PAINT to reduce the disparities at join lines and imported into ArcView 9.2. Each image was adjusted with a majority filter to reduce the effect of light reflectivity variation. A low pass filter was then run on each image to further reduce resolution and classify the image into three classes, based on the greyscale variation. The number of pixels per class was used to calculate the percentage each class occupies on the peninsula and the size of each pixel was used to calculate area, in hectares. The Landscape Shape Index (LSI), as described by Limpitlaw and Woldai (2004), was used to measure the fragmentation of the core forest patches and the open areas. Fragmentation of the landscape can be related to human presence, such as homesteads, croplands, roads, etc. and the LSI provides a measure of disturbance in KwaNibela.
Vegetation structure and species composition of the forest patches
The areas of core forest were identified by comparing the earliest aerial photograph of the peninsula (1937) with the most recent Google Earth (2008) image. Vegetation was sampled according to Mucina and Geldenhuys (2006). Transects were then extended from core forest to the forest margin and 33 circular 400 m2 plots were sampled at different stages of succession along each transect. The following information was recorded on each plot:
diameter at breast height (DBH) measurements of all trees 5-9 cm DBH within a 200 m2 subplot and all trees ≥10 cm DBH within the 400 m2 plot, by species; height of the canopy;
Braun Blanquet cover-abundance values for each species in each layer to determine dominance. This information was collected to quantify changes in the structure of the forest patches, in diversity and dominance between core forest, transitional thicket and open areas, and to assess the current classification of KwaNibela as Licuati Sand Forest (Von Maltitz et al. 2003, Matthews 2005).
A two-way hierarchical analysis was performed in TWINSPAN (Hill 1979), using stem-count per species per plot to distinguish community types and provide descriptions and indicator species for each type. CANOCO (Ter Braak and Similauer 2003) was used to relate the differences in species composition to environmental variables, such as multi-stemness, total basal area, number of species per plot and canopy height.
Results and discussion
Past and present distribution of forest patches
The earliest aerial photograph image of the KwaNibela Peninsula shows a wide expanse of open area in the centre of the peninsula and relatively intact areas of core forest. The absence of small geometrical gaps in the forest and thicket is apparent, when comparing the 1937 image to the 2002 image (Figures 2 and 3). These small geometrical gaps are likely to be human-induced as the inhabitants cleared small areas for homesteads, croplands, etc. The 2002 image also shows quite extensive bush encroachment as former open areas are now covered by core forest or transitional thicket (Figures 2a and 2b).
The LSI results (FFigure 3) shhow that thee degree off fragmentattion of the core forestt patches
vegetati
A grea
Acknowledgements
The authors wish to express their gratitude to Melanie Kneen and Professor Harold Annegarn of the Geography, Environmental Management and Energy Studies (GEMES) Unit at the University of Johannesburg for the use of the GIS facilities as well as technical assistance with the GIS programmes and encouragement throughout the study. We are also very thankful to Sarel and Melani van der Westhuizen and all the staff at Nibela Lake Lodge for providing accommodation during the main field trip. Finally, thank you to Goodenough Mdluli, Lucky Ngubane, Induna Mdluli and the community of KwaNibela for their technical assistance and enthusiasm for the study.
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