Several contributions have shown that the process and results of Ecosystem Services (ES) indicator development for decision making is not only a scientific process. The way how ES indicators are framed and defined pre-determines what is being assessed and how this assessment can be used in policy, planning and decision making. It is unavoidable and even necessary to include the various value, knowledge and belief systems of decision makers or participants in decision processes. Consequently it is also important to reflect associated normative biases. An institutionalized, long-term, science-policy dialogue to arrive at a co-design of indicators to inform a multi-level ES governance approach could help here. Furthermore, social and environmental monitoring approaches need to be adapted towards delivering the requested indicator information. To account for the complexity of decision contexts one approach could be to bundle and aggregate indicator systems to social-ecological indices. Such indices could contribute also to services that are not visible and difficult to assess but are relevant for the well-being of future generations. An additional aspect is that such indices account better for aspect such as landscape composition and configuration, which are currently often ignored. Increasing ES literacy of decision makers is necessary and iterative, learning-by-doing approaches in transdisciplinary processes proved to be useful
Developing and applying ecosystem service indicators in decision-support at various scales
LA ROSA, SANTI DANIELE;
2016-01-01
Abstract
Several contributions have shown that the process and results of Ecosystem Services (ES) indicator development for decision making is not only a scientific process. The way how ES indicators are framed and defined pre-determines what is being assessed and how this assessment can be used in policy, planning and decision making. It is unavoidable and even necessary to include the various value, knowledge and belief systems of decision makers or participants in decision processes. Consequently it is also important to reflect associated normative biases. An institutionalized, long-term, science-policy dialogue to arrive at a co-design of indicators to inform a multi-level ES governance approach could help here. Furthermore, social and environmental monitoring approaches need to be adapted towards delivering the requested indicator information. To account for the complexity of decision contexts one approach could be to bundle and aggregate indicator systems to social-ecological indices. Such indices could contribute also to services that are not visible and difficult to assess but are relevant for the well-being of future generations. An additional aspect is that such indices account better for aspect such as landscape composition and configuration, which are currently often ignored. Increasing ES literacy of decision makers is necessary and iterative, learning-by-doing approaches in transdisciplinary processes proved to be usefulFile | Dimensione | Formato | |
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