Uncertainties in landscape analysis and ecosystem service assessment

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Original languageEnglish
Pages (from-to)S117-31
JournalJournal of Environmental Management
Volume127 Suppl
Publication statusPublished - Sept 2013

Abstract

Landscape analysis and ecosystem service assessment have drawn increasing concern from research and application at the landscape scale. Thanks to the continuously emerging assessments as well as studies aiming at evaluation method improvement, policy makers and landscape managers have an increasing interest in integrating ecosystem services into their decisions. However, the plausible assessments carry numerous sources of uncertainties, which regrettably tend to be ignored or disregarded by the actors or researchers. In order to cope with uncertainties and make them more transparent for landscape managers, we demonstrate them by reviewing literature, describing an example and proposing approaches for uncertainty analysis. Additionally, we conclude with potential actions to reduce the insecurities accompanying landscape analysis and ecosystem service assessments. As for landscape analysis, the fundamental uncertainty origins are landscape complexity and methodological uncertainties. Concerning the uncertainty sources of ecosystem service assessments, the complexity of the natural system, respondents' preferences and technical problems play essential roles. By analyzing the assessment process, we find that initial data uncertainty pervades the whole assessment and argue that the limited knowledge about the complexity of ecosystems is the focal origin of uncertainties. For analyzing uncertainties in assessments, we propose systems analysis, scenario simulation and the comparison method as promising strategies. To reduce uncertainties, we assume that actions should integrate continuous learning, expanding respondent numbers and sources, considering representativeness, improving and standardizing assessment methods and optimizing spatial and geobiophysical data.

Keywords

    Conservation of Natural Resources/methods, Ecosystem, Environmental Monitoring/methods, Uncertainty

Cite this

Uncertainties in landscape analysis and ecosystem service assessment. / Hou, Y; Burkhard, B; Müller, F.
In: Journal of Environmental Management, Vol. 127 Suppl, 09.2013, p. S117-31.

Research output: Contribution to journalArticleResearchpeer review

Hou Y, Burkhard B, Müller F. Uncertainties in landscape analysis and ecosystem service assessment. Journal of Environmental Management. 2013 Sept;127 Suppl:S117-31. doi: 10.1016/j.jenvman.2012.12.002
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abstract = "Landscape analysis and ecosystem service assessment have drawn increasing concern from research and application at the landscape scale. Thanks to the continuously emerging assessments as well as studies aiming at evaluation method improvement, policy makers and landscape managers have an increasing interest in integrating ecosystem services into their decisions. However, the plausible assessments carry numerous sources of uncertainties, which regrettably tend to be ignored or disregarded by the actors or researchers. In order to cope with uncertainties and make them more transparent for landscape managers, we demonstrate them by reviewing literature, describing an example and proposing approaches for uncertainty analysis. Additionally, we conclude with potential actions to reduce the insecurities accompanying landscape analysis and ecosystem service assessments. As for landscape analysis, the fundamental uncertainty origins are landscape complexity and methodological uncertainties. Concerning the uncertainty sources of ecosystem service assessments, the complexity of the natural system, respondents' preferences and technical problems play essential roles. By analyzing the assessment process, we find that initial data uncertainty pervades the whole assessment and argue that the limited knowledge about the complexity of ecosystems is the focal origin of uncertainties. For analyzing uncertainties in assessments, we propose systems analysis, scenario simulation and the comparison method as promising strategies. To reduce uncertainties, we assume that actions should integrate continuous learning, expanding respondent numbers and sources, considering representativeness, improving and standardizing assessment methods and optimizing spatial and geobiophysical data. ",
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