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Application of habitat suitability modelling to tracking data of marine animals as a means of analyzing their feeding habitats

Author

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  • Skov, Henrik
  • Humphreys, Elizabeth
  • Garthe, Stefan
  • Geitner, Kerstin
  • Grémillet, David
  • Hamer, Keith C.
  • Hennicke, Janos
  • Parner, Hjalte
  • Wanless, Sarah

Abstract

This paper investigates the potential for using quantitative applications of statistical models of habitat suitability based on marine animal tracking data to identify key feeding areas. Presence-only models like Ecological Niche Factor Analysis (ENFA) may be applicable to resolve habitat gradients and potentially project habitat characteristics of tracked animals over large areas of ocean. We tested ENFA on tracking data of the northern gannet (Morus bassanus) obtained from the colony at Bass Rock, western North Sea in 2003. A total of 217 diving events were selected for model development. The ecological variables of the model were calibrated by using oceanographic structures with documented influences on seabird distribution, derived from satellite and bathymetric data. The model parameters were estimates of habitat marginality and specialisation computed by comparing the distribution of the gannet in the multivariate oceanographic space encompassed by the recorded logger data with the whole set of cells in the study area. Marginality was identified by differences to the global mean and specialization was identified by the ratio of species variance to global variance. A habitat suitability index was computed on the basis of the marginality factors and the first four specialisation factors by allocating values to all grid cells in the study area, which were proportional to the distance between their position and the position of the species optimum in the factorial space. Although gannets were using a large sector of the North Sea for feeding, ENFA estimated high habitat suitability scores within a relatively small coherent zone corresponding to a hydrographic frontal area, located east of the colony. The model was evaluated by using Jack-knife cross-validation and by comparison of the predicted core feeding area with results from historic field surveys. We discuss the limitations and potentials for applying habitat suitability models to tracking data in the marine environment, and conclude that the inclusion of hydrodynamic variables seems to be the biggest constraint. Overcoming this constraint, ENFA provides a promising method for achieving improved models of the distribution of marine species with high research and conservation priority. Due to the better coverage of entire feeding ranges, the limited influence of historic factors and the lack of bias from sampling design, marine animal tracking may provide better data than at-sea surveys for habitat suitability modelling.

Suggested Citation

  • Skov, Henrik & Humphreys, Elizabeth & Garthe, Stefan & Geitner, Kerstin & Grémillet, David & Hamer, Keith C. & Hennicke, Janos & Parner, Hjalte & Wanless, Sarah, 2008. "Application of habitat suitability modelling to tracking data of marine animals as a means of analyzing their feeding habitats," Ecological Modelling, Elsevier, vol. 212(3), pages 504-512.
    • Handle: RePEc:eee:ecomod:v:212:y:2008:i:3:p:504-512
    DOI: 10.1016/j.ecolmodel.2007.11.006
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    1. Melo-Merino, Sara M. & Reyes-Bonilla, Héctor & Lira-Noriega, Andrés, 2020. "Ecological niche models and species distribution models in marine environments: A literature review and spatial analysis of evidence," Ecological Modelling, Elsevier, vol. 415(C).
    2. Galparsoro, Ibon & Borja, Ángel & Bald, Juan & Liria, Pedro & Chust, Guillem, 2009. "Predicting suitable habitat for the European lobster (Homarus gammarus), on the Basque continental shelf (Bay of Biscay), using Ecological-Niche Factor Analysis," Ecological Modelling, Elsevier, vol. 220(4), pages 556-567.
    3. Martín-García, Laura & González-Lorenzo, Gustavo & Brito-Izquierdo, Isabel T. & Barquín-Diez, Jacinto, 2013. "Use of topographic predictors for macrobenthic community mapping in the Marine Reserve of La Palma (Canary Islands, Spain)," Ecological Modelling, Elsevier, vol. 263(C), pages 19-31.
    4. Mei, Zhigang & Chen, Mao & Li, Yongtao & Huang, Shiang-Lin & Haung, Jie & Han, Yi & Zhu, Binting & Li, Chunsheng & Wang, Kexiong & Wang, Ding, 2017. "Habitat preference of the Yangtze finless porpoise in a minimally disturbed environment," Ecological Modelling, Elsevier, vol. 353(C), pages 47-53.
    5. Dai, Dongchen & Fang, Hongwei & Li, Songheng & He, Guojian & Huang, Lei & Peng, Wenqi, 2016. "Numerical simulation of fish movement behavior for habitat assessment by Eulerian-Eulerian-Habitat-Selection (EEHS) method," Ecological Modelling, Elsevier, vol. 337(C), pages 156-167.

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