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An indicator-based approach for cross-realm coastal biodiversity assessments

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dc.contributor.author Harris, LR
dc.contributor.author Skowno, AL
dc.contributor.author Sink, KJ
dc.contributor.author Van Niekerk, Lara
dc.contributor.author Holness, SD
dc.contributor.author Monyeki, M
dc.contributor.author Majiedt, P
dc.date.accessioned 2023-01-24T06:44:48Z
dc.date.available 2023-01-24T06:44:48Z
dc.date.issued 2022-10
dc.identifier.citation Harris, L., Skowno, A., Sink, K., Van Niekerk, L., Holness, S., Monyeki, M. & Majiedt, P. 2022. An indicator-based approach for cross-realm coastal biodiversity assessments. <i>African Journal of Marine Science, 44(3).</i> http://hdl.handle.net/10204/12586 en_ZA
dc.identifier.issn 1814-232X
dc.identifier.issn 1814-2338
dc.identifier.uri https://doi.org/10.2989/1814232X.2022.2104373
dc.identifier.uri http://hdl.handle.net/10204/12586
dc.description.abstract Ecosystem status assessments are generally separated into realm-specific analyses (terrestrial, freshwater, estuarine or marine), but without integrating these into a coherent assessment of coastal biodiversity across the land-sea interface. Trends in assessment indicators in coastal versus non-coastal areas have also rarely been considered. In this study we aimed to compile the first cross-realm national biodiversity assessment for the South African coast using three key indicators. The ecological condition, ecosystem threat status, and ecosystem protection level of coastal ecosystem types (n = 186) were determined and compared with those of non-coastal ecosystem types (n = 444). Nearly half (46.9%) of the South African coastal habitat has been degraded compared with 20% of non-coastal areas. Proportionately, there are three-times (60%) as many threatened coastal ecosystem types (or 55% by area) as there are threatened non-coastal ecosystem types (19%, 6% by area). Despite the impacted state of coastal biodiversity, protection levels are generally higher in the coastal zone (87% of ecosystem types have some protection) compared with non-coastal areas (75%), although fewer coastal ecosystem types have met their biodiversity targets (24%, vs 28% for non-coastal ecosystem types). These results illustrate the importance of using a cross-realm approach for status assessments, management and conservation of coastal biodiversity. The assessment methods described are flexible and widely applicable to other regions. en_US
dc.format Abstract en_US
dc.language.iso en en_US
dc.relation.uri https://www.tandfonline.com/doi/abs/10.2989/1814232X.2022.2104373 en_US
dc.source African Journal of Marine Science, 44(3) en_US
dc.subject Coastal management en_US
dc.subject Ecological conditions en_US
dc.subject Ecological indicators en_US
dc.subject Ecosystem protection level en_US
dc.subject Ecosystem threat status en_US
dc.subject IUCN Red List of Ecosystems en_US
dc.title An indicator-based approach for cross-realm coastal biodiversity assessments en_US
dc.type Article en_US
dc.description.pages 239-253 en_US
dc.description.note Copyright © NISC (Pty) Ltd en_US
dc.description.cluster Smart Places en_US
dc.description.impactarea Coastal Systems en_US
dc.identifier.apacitation Harris, L., Skowno, A., Sink, K., Van Niekerk, L., Holness, S., Monyeki, M., & Majiedt, P. (2022). An indicator-based approach for cross-realm coastal biodiversity assessments. <i>African Journal of Marine Science, 44(3)</i>, http://hdl.handle.net/10204/12586 en_ZA
dc.identifier.chicagocitation Harris, LR, AL Skowno, KJ Sink, Lara Van Niekerk, SD Holness, M Monyeki, and P Majiedt "An indicator-based approach for cross-realm coastal biodiversity assessments." <i>African Journal of Marine Science, 44(3)</i> (2022) http://hdl.handle.net/10204/12586 en_ZA
dc.identifier.vancouvercitation Harris L, Skowno A, Sink K, Van Niekerk L, Holness S, Monyeki M, et al. An indicator-based approach for cross-realm coastal biodiversity assessments. African Journal of Marine Science, 44(3). 2022; http://hdl.handle.net/10204/12586. en_ZA
dc.identifier.ris TY - Article AU - Harris, LR AU - Skowno, AL AU - Sink, KJ AU - Van Niekerk, Lara AU - Holness, SD AU - Monyeki, M AU - Majiedt, P AB - Ecosystem status assessments are generally separated into realm-specific analyses (terrestrial, freshwater, estuarine or marine), but without integrating these into a coherent assessment of coastal biodiversity across the land-sea interface. Trends in assessment indicators in coastal versus non-coastal areas have also rarely been considered. In this study we aimed to compile the first cross-realm national biodiversity assessment for the South African coast using three key indicators. The ecological condition, ecosystem threat status, and ecosystem protection level of coastal ecosystem types (n = 186) were determined and compared with those of non-coastal ecosystem types (n = 444). Nearly half (46.9%) of the South African coastal habitat has been degraded compared with 20% of non-coastal areas. Proportionately, there are three-times (60%) as many threatened coastal ecosystem types (or 55% by area) as there are threatened non-coastal ecosystem types (19%, 6% by area). Despite the impacted state of coastal biodiversity, protection levels are generally higher in the coastal zone (87% of ecosystem types have some protection) compared with non-coastal areas (75%), although fewer coastal ecosystem types have met their biodiversity targets (24%, vs 28% for non-coastal ecosystem types). These results illustrate the importance of using a cross-realm approach for status assessments, management and conservation of coastal biodiversity. The assessment methods described are flexible and widely applicable to other regions. DA - 2022-10 DB - ResearchSpace DP - CSIR J1 - African Journal of Marine Science, 44(3) KW - Coastal management KW - Ecological conditions KW - Ecological indicators KW - Ecosystem protection level KW - Ecosystem threat status KW - IUCN Red List of Ecosystems LK - https://researchspace.csir.co.za PY - 2022 SM - 1814-232X SM - 1814-2338 T1 - An indicator-based approach for cross-realm coastal biodiversity assessments TI - An indicator-based approach for cross-realm coastal biodiversity assessments UR - http://hdl.handle.net/10204/12586 ER - en_ZA
dc.identifier.worklist 26190 en_US


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