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Simulating cryptic movements of a mangrove crab: Recovery phenomena after small scale fishery

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  • Piou, Cyril
  • Berger, Uta
  • Hildenbrandt, Hanno
  • Grimm, Volker
  • Diele, Karen
  • D’Lima, Coralie

Abstract

The semi-terrestrial burrowing crab Ucides cordatus is an important ecological component and economic resource of Brazilian mangrove forests. The crab population of the Caeté peninsula (the location of our study site) has been exploited for the last 40 years. Recovery of fished areas by crabs from non-fished areas under the roots of the mangrove tree Rhizophora mangle was hypothesized to be an important buffer mechanism against rapid overfishing. However, catch per unit effort decreased in recent years, suggesting that the sustainability of the crab fishery might become endangered. It is therefore important to better understand the movement behaviour of these crabs, even though it is hard to observe directly. Following the approach of pattern-oriented modelling, we developed an individual-based model to infer movement behaviour from patterns in density recovery that were observed in field experiments. Two alternative submodels simulating factors causing movement were contrasted: with and without local competition among crabs. To describe local competition, the field-of-neighbourhood (FON) approach was used, which was originally designed for sessile organisms. Without competition, unrealistically high movement frequencies were required to fit the observed linear recovery patterns. With competition included, better fits to the recovery patterns were obtained, and lower and thus more realistic movement frequencies were sufficient. This indicates that local competition between crabs is the main reason for them to move and change their burrows. Our work shows that the FON approach is suitable to describe local interactions not only among sessile organisms, but also among mobile organisms in conditions of competition for resources. The simulation results illustrate the importance of the non-fished rooted areas as buffers against rapid over-fishing. The IBU model presents a potential for future analysis of these buffer mechanisms and thus for a better understanding of the crab fishery and its management.

Suggested Citation

  • Piou, Cyril & Berger, Uta & Hildenbrandt, Hanno & Grimm, Volker & Diele, Karen & D’Lima, Coralie, 2007. "Simulating cryptic movements of a mangrove crab: Recovery phenomena after small scale fishery," Ecological Modelling, Elsevier, vol. 205(1), pages 110-122.
    • Handle: RePEc:eee:ecomod:v:205:y:2007:i:1:p:110-122
    DOI: 10.1016/j.ecolmodel.2007.02.008
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    References listed on IDEAS

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    1. Glaser, Marion & Diele, Karen, 2004. "Asymmetric outcomes: assessing central aspects of the biological, economic and social sustainability of a mangrove crab fishery, Ucides cordatus (Ocypodidae), in North Brazil," Ecological Economics, Elsevier, vol. 49(3), pages 361-373, July.
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    Cited by:

    1. Fulford, Richard S. & Tolan, Jessica L. & Hagy, James D., 2024. "Simulating implications of fish behavioral response for managing hypoxia in estuaries with spatial dissolved oxygen variability," Ecological Modelling, Elsevier, vol. 490(C).
    2. Semeniuk, C.A.D. & Musiani, M. & Hebblewhite, M. & Grindal, S. & Marceau, D.J., 2012. "Incorporating behavioral–ecological strategies in pattern-oriented modeling of caribou habitat use in a highly industrialized landscape," Ecological Modelling, Elsevier, vol. 243(C), pages 18-32.
    3. Tyre, Andrew & Kerr, Gregory D. & Tenhumberg, Brigitte & Bull, C. Michael, 2007. "Identifying mechanistic models of spatial behaviour using pattern-based modelling: An example from lizard home ranges," Ecological Modelling, Elsevier, vol. 208(2), pages 307-316.
    4. Grimm, Volker & Berger, Uta, 2016. "Structural realism, emergence, and predictions in next-generation ecological modelling: Synthesis from a special issue," Ecological Modelling, Elsevier, vol. 326(C), pages 177-187.
    5. J. Gareth Polhill & Dawn C. Parker & Daniel Brown & Volker Grimm, 2008. "Using the ODD Protocol for Describing Three Agent-Based Social Simulation Models of Land-Use Change," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(2), pages 1-3.
    6. Casey C Day & Nicholas P McCann & Patrick A Zollner & Jonathan H Gilbert & David M MacFarland, 2019. "Temporal plasticity in habitat selection criteria explains patterns of animal dispersal," Behavioral Ecology, International Society for Behavioral Ecology, vol. 30(2), pages 528-540.
    7. Piou, Cyril & Berger, Uta & Grimm, Volker, 2009. "Proposing an information criterion for individual-based models developed in a pattern-oriented modelling framework," Ecological Modelling, Elsevier, vol. 220(17), pages 1957-1967.

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