R ecent understanding about system dynamics and predictability that has emerged from the study of complex systems is creating new tools for modeling interactions between anthropogenic and natural systems. A range of techniques has become available through advances in computer speed and accessibility and by implementing a broad, interdisciplinary systems view. Systems are groups of interacting, interdependent parts linked together by exchanges of energy, matter, and information. Complex systems are characterized by strong (usually nonlinear) interactions between the parts, complex feedback loops that make it difficult to distinguish cause from effect, and significant time and space Robert Costanza is director of the Maryland International Institute for Ecological Economics (MIIEE), Center for Environmental and Estuarine Studies (CEES),
Recent understanding about system dynamics and predictability that has emerged from the study of complex systems is creating new tools for modeling interactions between anthropogenic and natural systems. A range of techniques has become available through advances in computer speed and accessibility and by implementing a broad, interdisciplinary systems view.Systems are groups of interacting, interdependent parts linked together by exchanges of energy, matter, and information. Complex systems are characterized by strong (usually nonlinear) interactions between the parts, complex feedback loops that make it difficult to distinguish cause from effect, and significant time and space lags, discontinuities, thresholds, and limits. These characteristics all result in scien-
a b s t r a c tThere is growing demand for information regarding the impacts of decisions on ecosystem services and human benefits. Despite the large and growing quantity of published ecosystem services research, there remains a substantial gap between this research and the information required to support decisions.Research often provides models and tools that do not fully link social and ecological systems; are too complex, specialized, and costly to use; and are targeted to outcomes that differ from those needed by decision makers. Decision makers require cost-effective, straightforward, transferable, scalable, meaningful, and defensible methods that can be readily understood. We provide illustrative examples of these gaps between research and practice and describe how researchers can make their work relevant to decision makers by using Benefit Relevant Indicators (BRIs) and choosing models appropriate for particular decision contexts. We use examples primarily from the United States, including cases that illustrate varying degrees of success in closing these gaps. We include a discussion of the challenges and opportunities researchers face in adapting their work to meet the needs of practitioners.
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