23 research outputs found

    Cycle-based Cluster Variational Method for Direct and Inverse Inference

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    We elaborate on the idea that loop corrections to belief propagation could be dealt with in a systematic way on pairwise Markov random fields, by using the elements of a cycle basis to define region in a generalized belief propagation setting. The region graph is specified in such a way as to avoid dual loops as much as possible, by discarding redundant Lagrange multipliers, in order to facilitate the convergence, while avoiding instabilities associated to minimal factor graph construction. We end up with a two-level algorithm, where a belief propagation algorithm is run alternatively at the level of each cycle and at the inter-region level. The inverse problem of finding the couplings of a Markov random field from empirical covariances can be addressed region wise. It turns out that this can be done efficiently in particular in the Ising context, where fixed point equations can be derived along with a one-parameter log likelihood function to minimize. Numerical experiments confirm the effectiveness of these considerations both for the direct and inverse MRF inference.Comment: 47 pages, 16 figure

    Analyse écorégionale marine de Nouvelle-Calédonie : atelier d'identification des aires de conservation prioritaires

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    Dans le cadre de l'initiative pour les récifs coralliens du Pacifique sud (CRISP), le WWF-France a souhaité développer un projet pour la protection des récifs et des lagons néo-calédoniens. L'atelier, qui s'est déroulé les 10 et 11 août à Nouméa, avait pour objectif de rassembler les scientifiques et les experts du lagon néocalédonien pour identifier, sur la base de leur connaissance experte, les zones les plus remarquables du lagon (richesse, endémisme, originalité des faunes et flores, espèces emblématiques, zones d'intérêt fonctionnel) sur lesquelles doivent porter en priorité les efforts de conservation. Il a permis d'identifier 20 aires prioritaires pour la conservation, parmi lesquelles 6 ont un intérêt mondial, 4 ont un intérêt sur le plan régional, les autres ayant un intérêt local

    Comparison of Marine Spatial Planning Methods in Madagascar Demonstrates Value of Alternative Approaches

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    The Government of Madagascar plans to increase marine protected area coverage by over one million hectares. To assist this process, we compare four methods for marine spatial planning of Madagascar's west coast. Input data for each method was drawn from the same variables: fishing pressure, exposure to climate change, and biodiversity (habitats, species distributions, biological richness, and biodiversity value). The first method compares visual color classifications of primary variables, the second uses binary combinations of these variables to produce a categorical classification of management actions, the third is a target-based optimization using Marxan, and the fourth is conservation ranking with Zonation. We present results from each method, and compare the latter three approaches for spatial coverage, biodiversity representation, fishing cost and persistence probability. All results included large areas in the north, central, and southern parts of western Madagascar. Achieving 30% representation targets with Marxan required twice the fish catch loss than the categorical method. The categorical classification and Zonation do not consider targets for conservation features. However, when we reduced Marxan targets to 16.3%, matching the representation level of the “strict protection” class of the categorical result, the methods show similar catch losses. The management category portfolio has complete coverage, and presents several management recommendations including strict protection. Zonation produces rapid conservation rankings across large, diverse datasets. Marxan is useful for identifying strict protected areas that meet representation targets, and minimize exposure probabilities for conservation features at low economic cost. We show that methods based on Zonation and a simple combination of variables can produce results comparable to Marxan for species representation and catch losses, demonstrating the value of comparing alternative approaches during initial stages of the planning process. Choosing an appropriate approach ultimately depends on scientific and political factors including representation targets, likelihood of adoption, and persistence goals
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