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Collin B. Lawrence

Publications and source records attributed to Collin B. Lawrence.

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Sustaining Environmental Capital Initiative summary report

Federal agencies need credible scientific information to determine the production and value of ecosystem services in an efficient and timely manner. The U.S. Geological Survey addresses this scientific information need through the Sustaining Environmental Capital Initiative project. The project has relied on U.S. Geological Survey expertise related to water, fisheries, advanced modeling, and economics and other social sciences to conduct eight case studies across a range of environment types, including water-based environments, deserts, sagebrush ecosystems, floodplains, and forests. The Sustaining Environmental Capital Initiative also supported the development and expansion of four tools with the intent of adding content and usability for partners’ decision-making needs. The tools are the Natural Value Resource Center, Benefit Transfer Toolkit, Riverine Environmental Flow Decision Support System, and Artificial Intelligence for Ecosystem Services modeling platform.

Open-File Report

Demonstrating the value of Earth observations—methods, practical applications, and solutions—group on Earth observations side event proceedings

Executive Summary The U.S. Geological Survey, the National Oceanic and Atmospheric Administration, the European Association for Remote Sensing Companies, and the European Space Agency in coordination with the GEOValue Community hosted a side event to the Group on Earth Observations Plenary on October 23–24, 2017, in Washington, D.C. The workshop, entitled “Demonstrating the Value of Earth Observations: Methods, Practical Applications and Solutions,” brought together more than 60 international experts including economists, scientists, and engineers to consider the state of the science and applications of valuing Earth observations (EO). This 2-day workshop built upon previous activities developed under the GEOValue initiative. This workshop brought together expert analysts from multiple disciplines and backgrounds who are developing methods to identify and measure the value of information generated from the use of satellite and in-situ data. The mix of government agencies, international financial institutions, and independent consultants who participated in the workshop blended to develop a rich mix of views, approaches, and outcomes. During the first part of the workshop, the focus was on the latest science in valuing EO. A number of methodologies were described. Approaches generally assess the societal benefits of specific actions (for example, investments in EO). Some methods focus on broad measures of economic activity (for example, gross domestic product) or methods to assess total economic value such as contingent valuation surveys. Alternatively, use-case approaches (a use case is defined as an evaluation in which one or more decisions, applications, or other uses of data, information, and information products are specifically considered) start with the specific actions and how information is used to support decision making and affect outcomes. The second part of the meeting was focused on the use and development of value chains and decision trees. A value chain can be defined as the set of value-adding activities that one or more organizations perform in creating and distributing goods and services. In terms of EO, the value chain approach can be applied to consider societal benefits of the data and assess the value of data and data features. The EO value chain considers the geospatial data sources and the processing of the data into value added information to be incorporated into decision-support systems, leading to decision makers’ actions. To understand the value of EO, one would also need to recognize the demand side of the equation or how EO benefits users. Extending the value chain concept and incorporating tenets of Bayesian decision making, a decision tree would include one or more use cases. The value provided by the marginal increase in information could flow from one or several parts of the supply side of the value chain. The decision tree is based on the premise that information has no value if it is not used in at least one decision. By connecting the value chain and the decision tree, a framework is created that allows for conceptualizing the value of EO in its many uses. One can then apply economic techniques to monetize the marginal benefit of an outcome with information versus one without. A third part of the meeting applied the value chain and decision-tree frameworks to five specific thematic areas, each with the focus of using information for a decision point: Effect of increasing temperatures on human health; Flooding—Mitigating, managing, and avoiding impacts to safety and property damage; Harmful algal blooms—Effects on human health, recreation, and tourism; Energy and mineral supply—Mitigating, managing, and avoiding impacts of shortfalls on the economy; and Effects of natural hazards on transportation systems—Effects on mobility, safety, and the economy. During the working session, five separate groups worked to define and delineate the value chains and decision trees associated with each topic, discussing the related challenges and data needs. The outcomes were reported back to the full group. Because of the complexity of the topics, most groups first identified a network of value chains and then narrowed the scope to develop a single value chain to address their group’s topic. Although they worked separately and on different topics, the groups came to similar conclusions, concurring that the value chain and decision-tree frameworks are very effective for informing quantitative impact assessments and developing a relatable narrative to assist the public in understanding the link between EO and citizens.

Open-File Report

The Mississippi Alluvial Plain aquifers—An engine for economic activity

U.S. Geological Survey science supports groundwater resource management in the Mississippi Alluvial Plain region. The USGS Science and Decisions Center is working with the Water Availability and Use Science Program to integrate economics into a sophisticated model of groundwater in the region. The model will quantify the status of the groundwater system and help researchers, stakeholders, and decision-makers understand and manage groundwater resources. Including economics in the model will let users consider the influence of groundwater levels on regional economics and the effects of economic factors on the demand for groundwater.

Mississippi Alluvial Plain

Valuation of the flood attenuation ecosystem service in Difficult Run, VA, USA

Floodplains and riparian wetlands provide several ecosystem services that directly benefit people. We present a methodology for valuing the flood attenuation ecosystem service in Difficult Run, a suburban watershed with extensive natural floodplains in northern Virginia. High-resolution lidar-derived data were combined with GIS modeling techniques to produce estimates of flood inundation. We combined the modeled estimates with parcel-level property and primary economic data using a baseline and a counterfactual scenario to estimate the magnitude of flood attenuation and the associated value of the ecosystem service. Our framework brings new models and data to look at floodplains and an alternative land surface scenario in a way that has not previously been done. Annualized avoided property losses totaled $42,184 in the baseline scenario and $115,596 in the counterfactual scenario for the combined 200-, 100-, 50-, 20-, 10-, and 5-year flood events. We estimate the total annualized value of the flood attenuation ecosystem service in Difficult Run is $73,412, which is $77 per hectare of floodplain area and is consistent with similar valuation studies of floodplains. The framework presented here is not specific to the study area and could be deployed at larger spatial areas in other locations. Our methods may better inform land use decision making on the impacts of development in and surrounding floodplain areas.

Virginia