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Comparing species distribution models: a case study of four deep sea urchin species

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Abstract

There is an increasing demand for biodiversity mapping to address new challenges in the management of marine ecosystems. Species distribution models are a key tool in supplying part of this information. However, the use of these models in the marine environment is still developing and the reasons for the underlying use of different methodological approaches are not always clear. In this work, we compared four different statistical techniques: the ecological niche factor analysis (ENFA), the MAXimun ENTropy algorithm (MAXENT), general additive Models (GAMs), and Random Forest. ENFA and MAXENT were applied using presence-only data whereas GAM and Random Forest used presence–absence data. As a case study, we used four deep sea urchin species: Centrostephanus longispinus, Coelopleurus floridanus, Stylocidaris affinis, and Cidaris cidaris. The distribution of the studied sea urchins showed strong bathymetric segregation. Depth was the most important variable, followed by reflectivity and slope. The correlations between the predictive outputs of the models were similar between GAM, Random Forest and MAXENT, and lower for ENFA. Models using presence/absence data showed the highest scores in the four species, significantly outperforming ENFA in most of the cases, although differences with MAXENT were significant in only one species.

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Acknowledgments

This study was made possible thanks to the invaluable work of all the participants in the INCOECO surveys and the crew of the RVs; “Miguel Oliver”, “Professor Lozano,” and “Emma Bardan”. We are grateful to doctors Alberto Serrano and Phil Boulcott for their critical revision and useful suggestions which greatly improved this manuscript and to John Clarke for his help with the English and his support during the last phase of this work. This work was developed in the context of the European research project INDEMARES, funded by Fundación Biodiversidad (LIFE funds).

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Authors and Affiliations

  1. Marine Scotland, Marine Laboratory, 375 Victoria Road, PO Box 101, Aberdeen, AB11 9DB, Scotland, UK

    José M. González-Irusta

  2. Centro Oceanográfico de Canarias, Instituto Español de Oceanografía, Vía Espaldón, dársena pesquera, Parcela 8, Santa Cruz de Tenerife, 38011, Canary Islands, Spain

    Marcos González-Porto, Roberto Sarralde, Bruno Almón & Pablo Martín-Sosa

  3. Instituto Español de Oceanografía, Sede Central. Corazón de María nº8, Madrid, 28002, Spain

    Beatriz Arrese

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  1. José M. González-Irusta
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  2. Marcos González-Porto
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  4. Beatriz Arrese
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Correspondence to José M. González-Irusta.

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Handling editor: Begoña Santos

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Distribution maps of the four analyzed species for the four tested models. The figures show the probability of presence of each combination of species and model on the Banco de la Concepción seamount (TIFF 6288 kb)

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González-Irusta, J.M., González-Porto, M., Sarralde, R. et al. Comparing species distribution models: a case study of four deep sea urchin species. Hydrobiologia 745, 43–57 (2015). https://doi.org/10.1007/s10750-014-2090-3

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