In:
Water SA, Academy of Science of South Africa, Vol. 44, No. 2 April ( 2018-04-25)
Abstract:
The National Biodiversity Assessment of 2011 found freshwater ecosystems to be highly threatened and poorly protected. However, a number of studies have shown that the National Wetland Map (NWM) Version 4 represents less than 54% of wetlands mapped at a fine scale. A more comprehensive South African Inventory of Inland Aquatic Ecosystems (SAIIAE) would greatly improve the assessment of wetland ecosystem types and their condition and conservation status, and is crucial for monitoring trends to inform decision making and planning. In preparation for the third National Biodiversity Assessment of 2018, a review was undertaken to identify possible data sources that could contribute to the SAIIAE. The objectives of the study were to (i) assess which type of information is available for developing a SAIIAE; and (ii) list and understand the availability of fine-scale wetland data for updating the NWM. A variety of data related to species occurrence and distribution, extent and type of inland wetlands and rivers, as well as datasets which describe regional settings of inland aquatic ecosystems, were found across a number of institutions. Fine-scale spatial data amounted to more than double the extent of inland wetlands mapped by remote sensing at a country-wide scale. Nearly 5 million ha of fine-scale data were collected from a diverse number of institutions, with the majority (73%) of these data mapped by Government (3 681 503 ha or 3% of South Africa). It is estimated that 〈 8% of the sub-quaternary catchments of South Africa had complete wetland data sets, primarily in the Gauteng, Mpumalanga and Western Cape Provinces. Accuracy assessment reports and confidence ratings were however not consistently available for the wetland datasets. Inland wetlands in the majority of South Africa (84%) therefore remain poorly represented. We recommend future steps to improve the SAIIAE, including improving the representation of inland wetland ecosystem types and focusing on accuracy assessment.
Type of Medium:
Online Resource
ISSN:
1816-7950
DOI:
10.4314/wsa.v44i2.05
Language:
Unknown
Publisher:
Academy of Science of South Africa
Publication Date:
2018
detail.hit.zdb_id:
2075781-5
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