System dynamics modelling of the Endangered African penguin populations on Dyer and Robben islands, South Africa
African penguins (Spheniscus demersus) in South Africa have been subject to rapid decline in the 20th century and are currently listed as “endangered” on the IUCN Red List. A stochastic, stage-specific system dynamics model with spatial components was developed to investigate the interaction of mult...
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Veröffentlicht in: | Ecological modelling 2016-05, Vol.327, p.44-56 |
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Sprache: | eng |
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Zusammenfassung: | African penguins (Spheniscus demersus) in South Africa have been subject to rapid decline in the 20th century and are currently listed as “endangered” on the IUCN Red List. A stochastic, stage-specific system dynamics model with spatial components was developed to investigate the interaction of multiple pressures on penguin population development, and originally applied to study conservation management options for the penguin colony at Robben Island, Table Bay, South Africa. We here present an extension of the model to the nearby colony at Dyer Island. The modelled population was found to be strongly dominated by the effects of Cape fur seal (Arctocephalus pusillus pusillus) predation and immature emigration, which appear to be key drivers behind current declines in population numbers at this colony. Chronic low-level oiling also had a consistent impact despite ongoing mitigation measures, while kelp gull predation had a lower effect than expected. At current low population size, the pressure from either seal predation or immature emigration seems sufficient to mask any beneficial effects to penguins from possible improvements in available food biomass (e.g., from fishery restrictions). Results suggest that conservation management at this colony should focus on regular culling of predating seals combined with improving availability of prey (thus discouraging emigration) both in the foraging range of breeding penguins and in their general foraging area. Our findings demonstrate the use of site-specific scenario tools to explore conservation strategies in data-poor management situations. |
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ISSN: | 0304-3800 1872-7026 |
DOI: | 10.1016/j.ecolmodel.2016.01.011 |