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Land-use decision support

Improving predictive ability for environmental management is a major theme the lab's resarch. Two main modeling gaps we aim to bridge are 1) the connection between biophysical parameters and the ‘ecosystem services’ of interest to society to make predictions more relevant; and 2) probabilistic characterizations in environmental impact assessment to allow for decisions more consistent with risk preferences.

We are therefore interested in developing mechanistic biophysical/statistical models for ecosystem services nested within probabilistic, decision-analytic frameworks. This can characterize the wide uncertainties inherent in environmental systems and the relationship with risk tolerance and decision preferences among policymakers.

Wetland restoration affects many endpoints as a function of multiple physical processes
Coastal wetland restoration decisions trigger interacting biophysical processes which can be mapped to ecosystem services. These forecasts are reconciled in a probabilistic, economic framework. Adapted from Calder et al. (2019)

Nature-based adaptations to climate-change

Nature-based adaptations to climate change (such as restoration of coastal wetlands) are increasingly popular because they provide a variety of ecosystem services not offered by dikes and levees (e.g., recreation, water filtration). However, these ‘ecosystem services’ are the product of interacting biophysical processes, are highly uncertain and accrue over different timescales. This complicates decision-making.

We have worked to create modular tools to describe how interventions impact monetizable (and other) ecosystem services via interacting biophysical pathways and to describe how uncertainties and nonstationarities (e.g., increasing flood risk with sea level rise) combine to affect decision optima under different risk preferences.

This work has shown that mechanistic models can narrow the large uncertainties associated with landcover-based benefits-transfer valuations and that, in the setting of coastal wetlands, non-flood-related ecosystem services can dominate benefits over shorter payback periods.

Military land-use decisions

MoTIVES implementation for Eglin Air Force Base, FL

With funding from the Strategic Environmental Research Development Program (SERDP), we have expanded this framework into a decision platform we call MoTIVES (Model-based Tracking and Integrated Valuation of Ecosystem Services). This platform links management decisions at military bases to probabilistic descriptions of impacts on vegetation, flooding and other biophysical properties. The outputs from these simulations are valued using available economic characterizations, which in turn provides decision guidance.

So far, MoTIVES has been developed around the case study of Eglin Air Force Base in the Florida Panhandle. We are working to expand this platform into decision-support tools for bases across the United States.


2019     RSD Calder, C Shi, SA Mason, LP Olander & ME Borsuk. ‘Forecasting ecosystem services to guide coastal wetland rehabilitation decisions’ in Ecosyst Serv, vol. 39: 101007. 

2019     RSD Calder, ME Borsuk, SA Mason, LP Olander, A Plantinga & CS Robinson. ‘Assessing ecosystem service benefits from military installations’. Report to the Strategic Environmental Research and Development Program, Dept. of Defense, Washington, D.C. 

2019     J Kagan, ME Borsuk (co-presenter), RSD Calder, M Creutzburg, SA Mason, LP Olander & A Plantinga. ‘Assessing ecosystem service benefits from military installations’, Strategic Environmental Research and Development Program Symposium, Washington, D.C.

2018     C Shi, RSD Calder, SA Mason, LP Olander & ME Borsuk. ‘Forecasting ecosystem services to guide coastal wetland rehabilitation decisions’, International Congress on Environmental Modelling and Software’, Fort Collins CO.

2017     ME Borsuk, RSD Calder, C Shi, SA Mason & LP Olander (co-presenter). ‘Ecosystem services conceptual models’, San Francisco Bay National Estuarine Research Reserve, Tiburon, CA.




This work was carried out in the Modeling of Environmental Risks and Decisions Lab, directed by Prof. Mark Borsuk. The collaborators listed above and funding provided by SERDP and USGS have been essential.