The mandate to increase endangered salmon populations in the Columbia River Basin of North America has created a complex, controversial resource-management issue. We constructed an integrated assessment model as a tool for analyzing biological-economic trade-offs in recovery of Snake River spring- and summer-run chinook salmon (Oncorhynchus tshawytscha). We merged 3 frameworks: a salmon-passage model to predict migration and survival of smolts; an age-structured matrix model to predict long-term population growth rates of salmon stocks; and a cost-effectiveness analysis to determine a set of least-cost management alternatives for achieving particular population growth rates. We assessed 6 individual salmon-management measures and 76 management alternatives composed of one or more measures. To reflect uncertainty, results were derived for different assumptions of effectiveness of smolt transport around dams. Removal of an estuarine predator, the Caspian Tern (Sterna caspia), was cost-effective and generally increased long-term population growth rates regardless of transport effectiveness. Elimination of adult salmon harvest had a similar effect over a range of its cost estimates. The specific management alternatives in the cost-effective set depended on assumptions about transport effectiveness. On the basis of recent estimates of smolt transport effectiveness, alternatives that discontinued transportation or breached dams were prevalent in the cost-effective set, whereas alternatives that maximized transportation dominated if transport effectiveness was relatively high. More generally, the analysis eliminated 80-90% of management alternatives from the cost-effective set. Application of our results to salmon management is limited by data availability and model assumptions, but these limitations can help guide research that addresses critical uncertainties and information. Our results thus demonstrate that linking biology and economics through integrated models can provide valuable tools for science-based policy and management.

Several people made critical contributions to this project. Dr. Anne Wein, a volunteer operations research analyst, provided critical insights into formulating the mathematics of the theoretical framework. Amy Mathie contributed considerable time and energy to the early phases of defi ning and scoping this analysis. Members of the Program Management Section-including Dale Russell, Bill Coronel, John Fisher, and Janet Goodman-assisted us in arranging and conducting the interviews of GIS managers and contractors, from which we were able to derive much of our data. Dr. Stephen Gillespie generously reworked survey numbers for inclusion into our modeling. He also gave signifi cant feedback and helpful criticism to both the theoretical and computational model development. We are deeply indebted to two technical peer reviewers, Carl Shapiro and Donald Bieniewicz, whose extremely detailed comments and insights greatly improved the fi nal analysis and report. Finally, we appreciate the assistance given by Linda Hicklin and Joan Sziede in scoping the project. vi vii Contents Executive Summary …………………………………………………………………………… iii Acknowledgments …………………………………………………………………………… v Introduction …………………………………………………………………………………… 1 1. Literature Review …………………………………………………………………………… 1 2. Framework for Cost-Benefit Analysis of The National Map ………………………………… 3 3. Data and Modeling Methods, Results, and Sensitivity Analysis …………………………… 8 4. Results and Sensitivity Analysis …………………………………………………………… 10 5. Discussion ………………………………………………………………………………… 14 References Cited ……………………………………………………………………………… 14 Appendices A. Formal Economic Theory …………………………………………………………… 17 B. Details of Data Gathering and Synthesis …………………………………………… 18 C. STELLA Software and NB-Sim Model Details ………………………………………… 26 D. Sensitivity Analysis …………………………………………………………………… 37 Tables ES-1. Yearly results for mean net present value of baseline scenario ……………………… iii 1. Mean net present values (NPV) of baseline scenario, by year ……………………… 11 B1. Calculating the value of an application ……………………………………………… 19 B2. Applications and their estimated values (where available) ………………………… 21 B3. Alphabetical list of county-level GIS applications …………………………………… 25 C1. Variables in the theoretical and simulation models and their baseline values ……… 27 C2. Default NB-Sim model inputs and their sources ……………………………………… 28 D1. Sensitivity analysis scenarios and results …………………………………………… 39 ES-1. Total cost and total benefit curves of The National Map …………………………… iv ES-2. Sensitivity analysis results; mean net present value by scenario …………………… iv 1. Values of spatial data over time ……………………………………………………… 4 2. Possible future values of spatial data over time ……………………………………… 4 3. Variation in net present value resulting from 50 runs of the baseline scenario ……… 12 4. The total cost and total benefit curves for a single run of the baseline scenario …… 12 C1. The user interface in the computational model, NB-Sim …………………………… 29 C2-C8. Diagrams of underlying dynamics of the NB-Sim model …………………………… 30-...

No abstract

Protected areas comprise one major type of global conservation effort that has been in the form of parks, easements, or conservation concessions. Though protected areas are increasing in number and size throughout tropical ecosystems, there is no systematic method for optimally targeting specific local areas for protection, designing the protected area, and monitoring it, or for guiding follow-up actions to manage it or its surroundings over the long run. Without such a system, conservation projects often cost more than necessary and/or risk protecting ecosystems and biodiversity less efficiently than desired. Correcting these failures requires tools and strategies for improving the placement, design, and long-term management of protected areas. The objective of this project is to develop a set of spatially based analytical tools to improve the selection, design, and management of protected areas. In this project, several conservation concessions will be compared using an economic optimization technique. The forest land use portfolio model is an integrated assessment that measures investment in different land uses in a forest. The case studies of individual tropical ecosystems are developed as forest (land) use and preservation portfolios in a geographic information system (GIS). Conservation concessions involve a private organization purchasing development and resource access rights in a certain area and retiring them. Forests are put into conservation, and those people who would otherwise have benefited from extracting resources or selling the right to do so are compensated. Concessions are legal agreements wherein the exact amount and nature of the compensation result from a negotiated agreement between an agent of the conservation community and the local community. Funds are placed in a trust fund, and annual payments are made to local communities and regional/national governments. The payments are made pending third-party verification that the forest expanse and quality have been maintained. RESEARCH PARTNERS Recently Conservation International (CI) has established conservation concessions as a means to conserve biodiversity. CI accepts private donations and "invests" them in conservation concessions. The Field Museum of Natural History (Field Museum) has a research branch that conducts ecological classifications and rapid biological assessments. The Field Museum has been working with CI to prioritize areas for protection on the basis of ecological significance of habitat areas that contain large quantities of biodiversity. CI combines economics, finance, and negotiation with the Field Museum's biological and ecological inventories to target areas for protection. Hardner and Gullison Associates, LLC (HGA) is an environmental consulting firm that assists CI with economic and ecological analyses and with negotiations for each concession. Finally, the Ecosystem Science and Technology (EST) Branch of the National Aeronautics and Space Administration (NASA) provides expertise in remotely sensed instruments and in...

To assess the opportunities and needs for mobile-computing technology at the U.S. Geological Survey (USGS), we conducted an internal, Internet-based survey of bureau scientists whose research includes fieldwork. In summer 2005, 144 survey participants answered 65 questions about fieldwork activities and conditions, technology to support field research, and postfieldwork data processing and analysis. Results suggest that some types of mobile-computing technology are already commonplace, such as digital cameras and Global Positioning System (GPS) receivers, whereas others are not, such as personal digital assistants (PDAs) and tablet-based personal computers (tablet PCs). The potential for PDA use in the USGS is high: 97 percent of respondents record field observations (primarily environmental conditions and waterquality data), and 87 percent take field samples (primarily water-quality data, water samples, and sediment/soil samples). The potential for tablet PC use in the USGS is also high: 59 percent of respondents map environmental features in the field, primarily by sketching in field notebooks, on aerial photographs, or on topographic-map sheets. Results also suggest that efficient mobile-computing-technology solutions could benefit many USGS scientists because most respondents spend at least 1 week per year in the field, conduct field sessions that are least 1 week in duration, have field crews of one to three people, and typically travel on foot about 1 mi from their field vehicles. By allowing researchers to enter data directly into digital databases while in the field, mobile-computing technology could also minimize postfieldwork data processing: 93 percent of respondents enter collected field data into their office computers, and more than 50 percent spend at least 1 week per year on postfieldwork data processing. Reducing postfieldwork data processing could free up additional time for researchers and result in cost savings for the bureau. Generally, respondents support greater use of mobile-computing technology at the USGS and are interested in training opportunities and further discussions related to data archiving, access to additional digital data types, and technology development.