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

10Citations
Citations of this article
24Readers
Mendeley users who have this article in their library.
Get full text

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.

Cite

CITATION STYLE

APA

Harris, L. R., Skowno, A. L., Sink, K. J., van Niekerk, L., Holness, S. D., Monyeki, M., & Majiedt, P. (2022). An indicator-based approach for cross-realm coastal biodiversity assessments. African Journal of Marine Science, 44(3), 239–253. https://doi.org/10.2989/1814232X.2022.2104373

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free