Wetlands Ecology and Management

, Volume 25, Issue 3, pp 313–330 | Cite as

Mapping ephemeral wetlands: manual digitisation and logistic regression modelling in Nelson Mandela Bay Municipality, South Africa

  • Brigitte L. Melly
  • Denise M. Schael
  • Nick Rivers-Moore
  • Phumelele T. Gama
Original Paper

Abstract

Until recently, little research has been conducted on the distribution and structure of ephemeral systems in semi-arid areas. This information is critical for appropriate wetland management and conservation. The Nelson Mandela Bay Municipality is a semi-arid area along the south-eastern coastline of the Eastern Cape Province of South Africa. The Municipality encapsulates a wide range of geological and geomorphological features as well as vegetation types within an area of some 1950 km2, providing an ideal area for such research. The distribution and abundance of wetlands were defined, and a logistic regression (LR) model was used to establish whether this modelling technique is viable in semi-arid areas with highly variable rainfall patterns. Wetlands were delineated manually using geographical information systems, high-resolution aerial photographs and environmental data. More than 1700 wetland polygons were identified, with 80% of the systems being categorised as depressions, seeps and wetland flats. Unchannelled (8%) and channelled (7%) valley bottom wetlands and floodplain wetlands (5%) were also identified. The wetland database was then used to create a wetland occurrence probability model. There were 19 environmental variables used to develop the LR model, with eight variables used in the final model output. The predictive capacity of the model was good, with an area under curve value of 0.68 and an overall accuracy of 66%. This indicates that probabilistic wetland models are useful in highly variable environments with high numbers of small (<1 ha) wetlands. Such predictive models provide a tool to assist in improving the accuracy of land cover datasets in semi-arid areas, and can be used to inform management decisions on flood risk areas and key conservation zones. In addition, abiotic variables that are significant in the model output provide an indication of the factors influencing wetland functioning in the region.

Keywords

Conservation Distribution Management Probability model Semi-arid Ephemeral wetland 

Notes

Acknowledgements

Funding for this study was provided by the Water Research Commission (WRC K5/2182), DAAD-NRF Joint Scholarship Programme for Doctoral Studies, Nelson Mandela Metropolitan University (NMMU) Postgraduate Research Scholarship and Dormehl-Cunningham Scholarship. Two anonymous reviewers are sincerely thanked for their comments to the earlier versions of this manuscript.

Supplementary material

11273_2016_9518_MOESM1_ESM.docx (19 kb)
Supplementary material 1 (DOCX 18 kb)

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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Brigitte L. Melly
    • 1
  • Denise M. Schael
    • 1
  • Nick Rivers-Moore
    • 2
  • Phumelele T. Gama
    • 1
  1. 1.Department of BotanyNelson Mandela Metropolitan UniversityPort ElizabethSouth Africa
  2. 2.Centre for Water Resources ResearchUniversity of KwaZulu-NatalDurbanSouth Africa

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