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Uncertainty of Monetary Valued Ecosystem Services – Value Transfer Functions for Global Mapping

Growing demand of resources increases pressure on ecosystem services (ES) and biodiversity. Monetary valuation of ES is frequently seen as a decision-support tool by providing explicit values for unconsidered, non-market goods and services. Here we present global value transfer functions by using a...

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Detalles Bibliográficos
Autores principales: Schmidt, Stefan, Manceur, Ameur M., Seppelt, Ralf
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4777407/
https://www.ncbi.nlm.nih.gov/pubmed/26938447
http://dx.doi.org/10.1371/journal.pone.0148524
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author Schmidt, Stefan
Manceur, Ameur M.
Seppelt, Ralf
author_facet Schmidt, Stefan
Manceur, Ameur M.
Seppelt, Ralf
author_sort Schmidt, Stefan
collection PubMed
description Growing demand of resources increases pressure on ecosystem services (ES) and biodiversity. Monetary valuation of ES is frequently seen as a decision-support tool by providing explicit values for unconsidered, non-market goods and services. Here we present global value transfer functions by using a meta-analytic framework for the synthesis of 194 case studies capturing 839 monetary values of ES. For 12 ES the variance of monetary values could be explained with a subset of 93 study- and site-specific variables by utilizing boosted regression trees. This provides the first global quantification of uncertainties and transferability of monetary valuations. Models explain from 18% (water provision) to 44% (food provision) of variance and provide statistically reliable extrapolations for 70% (water provision) to 91% (food provision) of the terrestrial earth surface. Although the application of different valuation methods is a source of uncertainty, we found evidence that assuming homogeneity of ecosystems is a major error in value transfer function models. Food provision is positively correlated with better life domains and variables indicating positive conditions for human well-being. Water provision and recreation service show that weak ownerships affect valuation of other common goods negatively (e.g. non-privately owned forests). Furthermore, we found support for the shifting baseline hypothesis in valuing climate regulation. Ecological conditions and societal vulnerability determine valuation of extreme event prevention. Valuation of habitat services is negatively correlated with indicators characterizing less favorable areas. Our analysis represents a stepping stone to establish a standardized integration of and reporting on uncertainties for reliable and valid benefit transfer as an important component for decision support.
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spelling pubmed-47774072016-03-10 Uncertainty of Monetary Valued Ecosystem Services – Value Transfer Functions for Global Mapping Schmidt, Stefan Manceur, Ameur M. Seppelt, Ralf PLoS One Research Article Growing demand of resources increases pressure on ecosystem services (ES) and biodiversity. Monetary valuation of ES is frequently seen as a decision-support tool by providing explicit values for unconsidered, non-market goods and services. Here we present global value transfer functions by using a meta-analytic framework for the synthesis of 194 case studies capturing 839 monetary values of ES. For 12 ES the variance of monetary values could be explained with a subset of 93 study- and site-specific variables by utilizing boosted regression trees. This provides the first global quantification of uncertainties and transferability of monetary valuations. Models explain from 18% (water provision) to 44% (food provision) of variance and provide statistically reliable extrapolations for 70% (water provision) to 91% (food provision) of the terrestrial earth surface. Although the application of different valuation methods is a source of uncertainty, we found evidence that assuming homogeneity of ecosystems is a major error in value transfer function models. Food provision is positively correlated with better life domains and variables indicating positive conditions for human well-being. Water provision and recreation service show that weak ownerships affect valuation of other common goods negatively (e.g. non-privately owned forests). Furthermore, we found support for the shifting baseline hypothesis in valuing climate regulation. Ecological conditions and societal vulnerability determine valuation of extreme event prevention. Valuation of habitat services is negatively correlated with indicators characterizing less favorable areas. Our analysis represents a stepping stone to establish a standardized integration of and reporting on uncertainties for reliable and valid benefit transfer as an important component for decision support. Public Library of Science 2016-03-03 /pmc/articles/PMC4777407/ /pubmed/26938447 http://dx.doi.org/10.1371/journal.pone.0148524 Text en © 2016 Schmidt et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Schmidt, Stefan
Manceur, Ameur M.
Seppelt, Ralf
Uncertainty of Monetary Valued Ecosystem Services – Value Transfer Functions for Global Mapping
title Uncertainty of Monetary Valued Ecosystem Services – Value Transfer Functions for Global Mapping
title_full Uncertainty of Monetary Valued Ecosystem Services – Value Transfer Functions for Global Mapping
title_fullStr Uncertainty of Monetary Valued Ecosystem Services – Value Transfer Functions for Global Mapping
title_full_unstemmed Uncertainty of Monetary Valued Ecosystem Services – Value Transfer Functions for Global Mapping
title_short Uncertainty of Monetary Valued Ecosystem Services – Value Transfer Functions for Global Mapping
title_sort uncertainty of monetary valued ecosystem services – value transfer functions for global mapping
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4777407/
https://www.ncbi.nlm.nih.gov/pubmed/26938447
http://dx.doi.org/10.1371/journal.pone.0148524
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