@article{fdi:010055829,
  title = {{C}omparison of marine spatial planning methods in {M}adagascar demonstrates value of alternative approaches},
  author = {{A}llnutt, {T}. {F}. and {M}c{C}lanahan, {T}. {R}. and {A}ndr{\'e}fou{\¨e}t, {S}erge and {B}aker, {M}. and {L}agabrielle, {E}rwann and {M}c{C}lennen, {C}. and {R}akotomanjaka, {A}. {J}. {M}. and {T}ianarisoa, {T}. {F}. and {W}atson, {R}. and {K}remen, {C}.},
  editor = {},
  language = {{ENG}},
  abstract = {{T}he {G}overnment of {M}adagascar plans to increase marine protected area coverage by over one million hectares. {T}o assist this process, we compare four methods for marine spatial planning of {M}adagascar's west coast. {I}nput 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). {T}he 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 {M}arxan, and the fourth is conservation ranking with {Z}onation. {W}e present results from each method, and compare the latter three approaches for spatial coverage, biodiversity representation, fishing cost and persistence probability. {A}ll results included large areas in the north, central, and southern parts of western {M}adagascar. {A}chieving 30% representation targets with {M}arxan required twice the fish catch loss than the categorical method. {T}he categorical classification and {Z}onation do not consider targets for conservation features. {H}owever, when we reduced {M}arxan targets to 16.3%, matching the representation level of the "strict protection" class of the categorical result, the methods show similar catch losses. {T}he management category portfolio has complete coverage, and presents several management recommendations including strict protection. {Z}onation produces rapid conservation rankings across large, diverse datasets. {M}arxan is useful for identifying strict protected areas that meet representation targets, and minimize exposure probabilities for conservation features at low economic cost. {W}e show that methods based on {Z}onation and a simple combination of variables can produce results comparable to {M}arxan for species representation and catch losses, demonstrating the value of comparing alternative approaches during initial stages of the planning process. {C}hoosing an appropriate approach ultimately depends on scientific and political factors including representation targets, likelihood of adoption, and persistence goals.},
  keywords = {},
  booktitle = {},
  journal = {{P}los {O}ne},
  volume = {7},
  numero = {2},
  pages = {e28969},
  ISSN = {1932-6203},
  year = {2012},
  DOI = {10.1371/journal.pone.0028969},
  URL = {https://www.documentation.ird.fr/hor/fdi:010055829},
}