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A system dynamics approach to modelling multiple drivers of the African penguin population on Robben Island, South Africa

Author

Listed:
  • Weller, Florian
  • Cecchini, Lee-Anne
  • Shannon, Lynne
  • Sherley, Richard B.
  • Crawford, Robert J.M.
  • Altwegg, Res
  • Scott, Leanne
  • Stewart, Theodor
  • Jarre, Astrid

Abstract

The African penguin (Spheniscus demersus) population in southern Africa has experienced rapid decline in the 20th century and as of 2010 is listed as “endangered” on the IUCN Red List. There is an urgent need for decision support tools to enable effective management of colonies. We present a system dynamics model of the penguin population on Robben Island, South Africa, that combines a demographic simulation with the modelling of multiple pressures including food availability and food competition by commercial fisheries, oil spills, predation by terrestrial and marine predators, and extreme climate events. The model is stochastic, stage-specific and resource-driven, and incorporates both well-defined, quantitative field data and qualitative expert opinion. Survival rates for eggs, chicks, immatures and adults were adapted from field data and an earlier model of this population to create a simulation of a stable population used in a variety of scenarios and sensitivity tests. The modelled population was found to be strongly driven by food availability and to a lesser degree by oiling and marine predation, while climate events and terrestrial predation had low impacts. Food biomass levels (small pelagic fish) in the penguins’ foraging area around the island (used during nesting) and further afield (used during the rest of the year) had an equal influence in driving population development in the short and long run. The impact of short-term (three years) fishing restrictions currently being trialled around the island was found to be generally beneficial to the modelled population, but easily masked by food-driven variability in population growth. The model produced population dynamics similar to those observed in 1988–2009 when immigration and a plausible change in predation pressure during this period were simulated. The model is being extended to other colonies to provide tools for specific management decisions and to enable the study of meta-populations by modelling migration between colonies. Our results suggest that improving food availability and mitigating the impact of oiling would have the highest beneficial impact on this penguin population.

Suggested Citation

  • Weller, Florian & Cecchini, Lee-Anne & Shannon, Lynne & Sherley, Richard B. & Crawford, Robert J.M. & Altwegg, Res & Scott, Leanne & Stewart, Theodor & Jarre, Astrid, 2014. "A system dynamics approach to modelling multiple drivers of the African penguin population on Robben Island, South Africa," Ecological Modelling, Elsevier, vol. 277(C), pages 38-56.
    • Handle: RePEc:eee:ecomod:v:277:y:2014:i:c:p:38-56
    DOI: 10.1016/j.ecolmodel.2014.01.013
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    References listed on IDEAS

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    1. Semeniuk, Christina A.D. & Haider, Wolfgang & Cooper, Andrew & Rothley, Kristina D., 2010. "A linked model of animal ecology and human behavior for the management of wildlife tourism," Ecological Modelling, Elsevier, vol. 221(22), pages 2699-2713.
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    Cited by:

    1. Xiaopeng Guo & Xiaodan Guo & Jiahai Yuan, 2014. "Impact Analysis of Air Pollutant Emission Policies on Thermal Coal Supply Chain Enterprises in China," Sustainability, MDPI, vol. 7(1), pages 1-21, December.
    2. Yun Eui Choi & Kihwan Song & Min Kim & Junga Lee, 2017. "Transformation Planning for Resilient Wildlife Habitats in Ecotourism Systems," Sustainability, MDPI, vol. 9(4), pages 1-28, March.
    3. Matinzadeh, Mohammad Mehdi & Abedi Koupai, Jahangir & Sadeghi-Lari, Adnan & Nozari, Hamed & Shayannejad, Mohammad, 2017. "Development of an innovative integrated model for the simulation of nitrogen dynamics in farmlands with drainage systems using the system dynamics approach," Ecological Modelling, Elsevier, vol. 347(C), pages 11-28.
    4. Douglas J. Crookes & James N. Blignaut, 2015. "Debunking the myth that a legal trade will solve the rhino horn crisis: A system dynamics model for market demand," Working Papers 520, Economic Research Southern Africa.
    5. Alistair M McInnes & Arjun Khoosal & Ben Murrell & Dagmar Merkle & Miguel Lacerda & Reason Nyengera & Janet C Coetzee & Loyd C Edwards & Peter G Ryan & Johan Rademan & Jan J van der Westhuizen & Lorie, 2015. "Recreational Fish-Finders—An Inexpensive Alternative to Scientific Echo-Sounders for Unravelling the Links between Marine Top Predators and Their Prey," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-18, November.
    6. Zhao, Rui & Xi, Beidou & Liu, Yiyun & Su, Jing & Liu, Silin, 2017. "Economic potential of leachate evaporation by using landfill gas: A system dynamics approach," Resources, Conservation & Recycling, Elsevier, vol. 124(C), pages 74-84.
    7. Weller, Florian & Sherley, Richard B. & Waller, Lauren J. & Ludynia, Katrin & Geldenhuys, Deon & Shannon, Lynne J. & Jarre, Astrid, 2016. "System dynamics modelling of the Endangered African penguin populations on Dyer and Robben islands, South Africa," Ecological Modelling, Elsevier, vol. 327(C), pages 44-56.
    8. Watermeyer, K.E. & Jarre, A. & Shannon, L.J. & Mulumba, P. & Botha, J., 2018. "A frame-based modelling approach to understanding changes in the distribution and abundance of sardine and anchovy in the southern Benguela," Ecological Modelling, Elsevier, vol. 371(C), pages 1-17.

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