Award Abstract #0814628
CNH: Collaborative Research: Integrated Dynamic Modeling of Ecosystem Services, Incentive-Based Policies, Land-Use Decisions, and Ecological Outcomes

NSF Org:	BCS Division of Behavioral and Cognitive Sciences
Initial Amendment Date:	September 22, 2008
Latest Amendment Date:	September 22, 2008
Award Number:	0814628
Award Instrument:	Standard Grant
Program Manager:	Thomas J. Baerwald BCS Division of Behavioral and Cognitive Sciences SBE Directorate for Social, Behavioral & Economic Sciences
Start Date:	October 1, 2008
Expires:	March 31, 2012 (Estimated)
Awarded Amount to Date:	$234003
Investigator(s):	Stephen Polasky polasky@umn.edu (Principal Investigator)
Sponsor:	University of Minnesota-Twin Cities 200 OAK ST SE MINNEAPOLIS, MN 55455 612/624-5599
NSF Program(s):	BE: DYN COUPLED NATURAL-HUMAN
Field Application(s):
Program Reference Code(s):	EGCH, 9278, 9186, 9169, 1691
Program Element Code(s):	1691

ABSTRACT

Over the past century, rapid growth of human population and the human economy has transformed landscapes around the world. These transformations have reduced and fragmented natural habitat, resulting in loss of biodiversity and many ecosystem services. Maintaining biodiversity and ecosystem services while meeting the needs of human society for food, fiber, fuel, and other essentials requires integrated assessment of the biological and economic consequences of land use and land management. This interdisciplinary research project will develop and apply an integrated dynamic landscape-modeling approach to predict and compare how alternative policy incentives and market forces affect land-use decisions; how resulting land-use changes affect species conservation, carbon storage, and the value of commodity production; and how this will affect future land-use decisions. The investigators will approach these questions by developing statistical models based on observed landowner behavior in order to predict likely land-use changes as a function of current land-use conditions, public policy, and market opportunities. Land-use changes have consequences for species conservation, ecosystem services, and economic returns. Land-use patterns shaped by these decisions will serve as input into models that predict the status of species, the flow of ecosystem services, and the value of commodity production from the landscape. Current land-use decisions and the resulting set of consequences will set the stage for future conditions that shape future policies and market opportunities, which, in turn, will affect future land-use changes. This integrated approach will be used to analyze the likely effect of alternative policies on land-use change dynamics, the consequent trajectory for species conservation, ecosystem services, and economic activities on the landscape. The integrated dynamic landscape modeling approach will be applied to landscapes at several geographic scales, from the 48 contiguous states to regional analysis applied to the Willamette Basin in Oregon and the Northern Lakes Region in Wisconsin. Two questions will be addressed by using different scales of analysis within the same modeling approach: (1) How much difference does inclusion of increased detail and spatial resolution make to the analysis and results?, and (2) Can analyses be nested in the sense that one can use the broad-scale analysis to highlight areas and species of concern, at which point more detailed analysis can be undertaken using finer scale analysis?

Conserving biodiversity and maintaining ecosystem services necessary for human welfare in the long-run in the midst of a growing human economy with pressing current needs requires careful planning based on an understanding of the full set of consequences of human choices and actions. This project will integrate economic and ecological research into a coherent framework to predict landscape dynamics and the effects of these dynamics on biodiversity conservation, ecosystem services, and economic production. The integrated landscape model developed in this project will provide tools and insights that can be used to improve decision making by a broad range of stakeholders. By facilitating careful thinking about the pattern, extent, and intensity of human activities across the landscape through time, this project may help landowners and policy makers to achieve important species conservation and ecosystem service objectives while also generating high economic returns over the long term. This project is supported by the NSF Dynamics of Coupled Natural and Human Systems (CNH) Program.

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