3
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      May the matrix be with you! Guidelines for the application of expert-based matrix approach for ecosystem services assessment and mapping

      ,

      One Ecosystem

      Pensoft Publishers

      Read this article at

      ScienceOpenPublisher
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Matrices or look-up tables are increasingly popular flexible tools for ecosystem services mapping and assessment. The matrix approach links ecosystem types or land cover types to ecosystem services by providing a score for ecosystem service (ES) capacity, supply, use, demand or other concepts. Using expert elicitation enables quick and integrative ES scoring that can meet general demand for validated ES mapping and assessment at different scales. Nevertheless, guidance is needed on how to collect and integrate expert knowledge to address some of the biases and limits of the expert elicitation method. This paper aims to propose a set of guidelines to produce ES matrices based on expert knowledge. It builds on existing literature and experience acquired through the production of several ES matrices in several ES assessments carried out in France. We propose a 7-steps methodology for the expert-based matrix approach that aims to promote cogency in the method and coherency in the matrices produced. The aim here is to use collective knowledge to produce semi-quantitative estimates of ES quantities and not to analyse individual or societal preferences or importance of ES. The definition of the objectives and the preparation phase is particularly important in order to define the components of capacity to demand ES chain to be addressed. The objectives and the ES components addressed will influence the composition of the expert panel. We recommend an individual filling of an empty matrix in order to strengthen the statistical analysis of the scores' variability and the analysis of congruency between experts. Expert scoring should follow a process of discussion, information-sharing and collective appropriation of a list of ecosystem types and ES to be assessed. We suggest that the ES matrix should not only focus on ES central scores but also address the variabilities and uncertainties as part of the ES assessment. The analysis of these sources of variability allows the documentation of variations in the ES quantity but also an exploration into the lack of consensus or knowledge gaps that needs to be addressed.

          Related collections

          Most cited references 47

          • Record: found
          • Abstract: found
          • Article: not found

          Who's in and why? A typology of stakeholder analysis methods for natural resource management.

          Stakeholder analysis means many things to different people. Various methods and approaches have been developed in different fields for different purposes, leading to confusion over the concept and practice of stakeholder analysis. This paper asks how and why stakeholder analysis should be conducted for participatory natural resource management research. This is achieved by reviewing the development of stakeholder analysis in business management, development and natural resource management. The normative and instrumental theoretical basis for stakeholder analysis is discussed, and a stakeholder analysis typology is proposed. This consists of methods for: i) identifying stakeholders; ii) differentiating between and categorising stakeholders; and iii) investigating relationships between stakeholders. The range of methods that can be used to carry out each type of analysis is reviewed. These methods and approaches are then illustrated through a series of case studies funded through the Rural Economy and Land Use (RELU) programme. These case studies show the wide range of participatory and non-participatory methods that can be used, and discuss some of the challenges and limitations of existing methods for stakeholder analysis. The case studies also propose new tools and combinations of methods that can more effectively identify and categorise stakeholders and help understand their inter-relationships.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Eliciting expert knowledge in conservation science.

            Expert knowledge is used widely in the science and practice of conservation because of the complexity of problems, relative lack of data, and the imminent nature of many conservation decisions. Expert knowledge is substantive information on a particular topic that is not widely known by others. An expert is someone who holds this knowledge and who is often deferred to in its interpretation. We refer to predictions by experts of what may happen in a particular context as expert judgments. In general, an expert-elicitation approach consists of five steps: deciding how information will be used, determining what to elicit, designing the elicitation process, performing the elicitation, and translating the elicited information into quantitative statements that can be used in a model or directly to make decisions. This last step is known as encoding. Some of the considerations in eliciting expert knowledge include determining how to work with multiple experts and how to combine multiple judgments, minimizing bias in the elicited information, and verifying the accuracy of expert information. We highlight structured elicitation techniques that, if adopted, will improve the accuracy and information content of expert judgment and ensure uncertainty is captured accurately. We suggest four aspects of an expert elicitation exercise be examined to determine its comprehensiveness and effectiveness: study design and context, elicitation design, elicitation method, and elicitation output. Just as the reliability of empirical data depends on the rigor with which it was acquired so too does that of expert knowledge. ©2011 Australian Governmemt Conservation Biology©2011 Society for Conservation Biology.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Why do dominant personalities attain influence in face-to-face groups? The competence-signaling effects of trait dominance.

              Individuals high in the personality trait dominance consistently attain high levels of influence in groups. Why they do is unclear, however, because most group theories assert that people cannot attain influence simply by behaving assertively and forcefully; rather, they need to possess superior task abilities and leadership skills. In the present research, the authors proposed that individuals high in trait dominance attain influence because they behave in ways that make them appear competent--even when they actually lack competence. Two studies examined task groups using a social relations analysis of peer perceptions (D. A. Kenny & L. LaVoie, 1984). The authors found that individuals higher in trait dominance were rated as more competent by fellow group members, outside peer observers, and research staff members, even after controlling for individuals' actual abilities. Furthermore, frequency counts of discrete behaviors showed that dominance predicts the enactment of competence-signaling behaviors, which in turn predicts peer ratings of competence. These findings extend researchers' understanding of trait dominance, hierarchies in groups, and perceptions of competence and abilities.
                Bookmark

                Author and article information

                Journal
                One Ecosystem
                OE
                Pensoft Publishers
                2367-8194
                May 03 2018
                May 03 2018
                : 3
                : e24134
                Article
                10.3897/oneeco.3.e24134
                © 2018

                Comments

                Comment on this article