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The Use of a Predictive Habitat Model and a Fuzzy Logic Approach for Marine Management and Planning

TitreThe Use of a Predictive Habitat Model and a Fuzzy Logic Approach for Marine Management and Planning
Type de publicationJournal Article
Nouvelles publications2013
AuteursHattab, Tarek, Frida Ben Rais Lasram, Camille Albouy, Chérif Sammari, Mohamed Salah Romdhane, Philippe Cury, Fabien Leprieur, and François Le Loc’h
JournalPLoS ONE
Année de publication2013

Bottom trawl survey data are commonly used as a sampling technique to assess the spatial distribution of commercial species. However, this sampling technique does not always correctly detect a species even when it is present, and this can create significant limitations when fitting species distribution models. In this study, we aim to test the relevance of a mixed methodological approach that combines presence-only and presence-absence distribution models. We illustrate this approach using bottom trawl survey data to model the spatial distributions of 27 commercially targeted marine species. We use an environmentally- and geographically-weighted method to simulate pseudo-absence data. The species distributions are modelled using regression kriging, a technique that explicitly incorporates spatial dependence into predictions. Model outputs are then used to identify areas that met the conservation targets for the deployment of artificial anti-trawling reefs. To achieve this, we propose the use of a fuzzy logic framework that accounts for the uncertainty associated with different model predictions. For each species, the predictive accuracy of the model is classified as ‘high’. A better result is observed when a large number of occurrences are used to develop the model. The map resulting from the fuzzy overlay shows that three main areas have a high level of agreement with the conservation criteria. These results align with expert opinion, confirming the relevance of the proposed methodology in this study.