Towards understanding the effects of informal harvesting of Sand Forest in Maputaland, South Africa
Indigenous forests and savannah provide numerous benefits for rural communities and are utilised as a source of firewood, building material and for woodcraft production. Currently, there is insufficient information on the magnitude of human pressure affecting one such important forest community, namely Sand Forest, particularly in communal areas. Sand Forest is regarded as being critically endangered and is considered to hold various endemic species. The fragmented patch occurrence of this rare and valuable forest type, combined with the lack of necessary knowledge and prior interest in its management, has resulted in the Sand Forest being subjected to uncontrolled utilisation within communal areas. The temporal monitoring of the spatial structures of forest areas, such as Sand Forest, within landscapes has been recommended in order to detect and model deteriorating trends in the forest structures and functioning. Remote sensing is critical in the generation of data that enables the identification and quantification of degraded and deforested areas. This study aims to contribute towards understanding the effects that could emerge from trends of informal Sand Forest wood harvesting, quantified through a spatial-temporal analysis. Quantifying the impact of a declining canopy closure resulting from selective wood harvesting required the use of remote sensing techniques and procedures that could potentially account for this effect. In addition, the study envisaged predicting the future changes of Sand Forest that will take place as a result of continued informal wood harvesting. The ability of trajectory analysis to predict potential changes based on observed and quantified trends provides a new dynamic to conservation and management strategies. In understanding where and how much Sand Forest will be lost in the forthcoming years, more appropriate and accurate recommendations on conservation and management can be made. Furthermore, priority areas can be more readily identified for both conservation and for management intervention.