Thus, integration methods considering the maximum and complementa

Thus, integration methods considering the maximum and complementarity of different criteria Pirfenidone may be concordant with this principle. However, the adequacy of the weighting of variables for integration can be subjective

depending on the opinions of stakeholders in the case of the selection of MPAs from among prioritized EBSAs. Consensus building among researchers regarding the prioritization of EBSAs based on scientific knowledge, such as the relative importance of a given endemic species, also should be discussed for the advanced prioritization of EBSAs. From this aspect, the use of complementary analysis taking into account spatial structures and subjective weights is promising for consensus building. Another important problem that must be solved is the treatment of zero data, i.e., no data availability. It should be strictly clarified whether zero values in original data mean low scores

with supporting information or sites with no information; in the case of the latter, there are some methods for interpolating missing values. The simplest method is to assign the average value of the whole dataset. However, this procedure can cause some biases if data unavailability is associated with the nature of some criteria. For example, data deficiency due to less research this website effort likely occurs in areas with poor accessibility, which may be pristine and less-impacted sites. In such cases, the actual ranking for biological diversity and naturalness Quisqualic acid would be above the average of the available data. Various techniques for inter- and extrapolating missing data using information from other sites on the basis of spatial information such as GIS were recently developed [51] and [52]. Species

distribution models and other spatial predictions can be used to fill data gaps to more comprehensively evaluate EBSAs [53]. Finally, the adequacy of EBSAs extraction and prioritization results should be validated using other independently obtained data sources. In the case of this paper, because all available data were examined and incorporated to extract and prioritize EBSAs around the Japanese coast, it was difficult to obtain independent quantitative data for validation beforehand. Thus, cross-validation using some of the collected data is an alternative method for testing the robustness of the results. Furthermore, hearing the comments and opinions of experts regarding biodiversity and the ecosystem status of each site through interviews and questionnaires on obtained results would be worthwhile for validating the entire EBSAs extraction and prioritization process. This paper reviewed the previously used and ongoing processes for EBSA extraction and evaluation of EBSA criteria worldwide, with particular emphasis on Japan. This paper also presented a new approach for extracting and prioritizing EBSAs according to quantitative scientific information for the 7 criteria.

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