Desktop classification of inland wetlands for systematic conservation planning in data-scarce countries: Mapping wetland ecosystem types, disturbance indices and threatened species associations at country-wide scale
van Deventer H.,South African Council for Scientific and Industrial Research |
Nel J.,South African Council for Scientific and Industrial Research |
Nel J.,Nelson Mandela Metropolitan University |
Mbona N.,South African National Biodiversity Institute |
And 4 more authors.
Aquatic Conservation: Marine and Freshwater Ecosystems | Year: 2016
Data sets on wetlands required for the representation of aquatic ecosystem biodiversity and systematic wetland conservation planning are typically not available or are inadequate, particularly at country-wide scale, which hinders conservation planning. The improvement in hierarchical classification systems and increased availability of broad-scale data sets offers new opportunities to overcome these limitations. This study demonstrates replicable methods for classifying wetland ecosystem types and condition country-wide using broad-scale data sets in data-scarce countries. A country-wide data set, compiled primarily using remote sensing techniques, was combined with regional and landscape-setting data sets to reflect the ecological and geomorphic biodiversity of wetlands. Geographical Information Systems (GIS) were employed to model wetland types, disturbance indices and identify priority wetlands through threatened faunal species associations using existing data. Accuracy of the national data was assessed through a congruency with two local data sets. Most of the 1 680 306ha of inland wetlands were classified as Natural (80%), of which the majority were located on Valley Floors (68%). However, the national data were found only to represent 54% of wetlands mapped at a local scale, and comparison with local data showed inaccuracies in the types and condition classifications. Problems regarding spatial data quality and scale are discussed and suggestions for improvement are provided. The desktop classification steps can be reproduced easily for other data-scarce countries. Data sets on freshwater ecosystems can assist in raising awareness and influence policy at a national scale. © 2015 John Wiley & Sons, Ltd.