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Lessons Learned from Large-Scale Restoration Efforts in the USA 1
Technical Report 2004-01
Application of the “Best Available Science” in Ecosystem Restoration:Lessons Learned from Large-Scale Restoration Project Efforts in the USA
Prepared in support of the Puget Sound Nearshore Partnership (PSNP)
May 2004
F. Brie Van Cleve, University of WashingtonF. Brie Van Cleve, University of WashingtonCharles Simenstad, University of WashingtonFred Goetz, US Army Corps of EngineersTom Mumford, Washington Department of Natural Resources
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AcknowledgementsWe are grateful for the time and eff ort contributed to this exercise in “lessons learned” by the restoration and science program rep-resentatives who either traveled to Seattle – Kim Taylor and Sam Luoma (CALFED), Steve Gloss, Brad Ack, and Duncan Patten (GCDAMP), Stuart Appelbaum and John Ogden (CERP) – or who hosted the NST’s visit – Don Boesch, Carl Hershner, Rich Batiuk, and Kevin Sellner (CBP); and Denise Reed and Suzanne Hawes (LCA).
We also thank participants from the Puget Sound Nearshore Partnership Nearshore Science Team and Steering Committee, especially Jacques White, and Project Managers Bernie Hargrave and Tim Smith for their enthusiasm and contributions to this document. Kim Taylor from CALFED, Denise Reed from LCA, Carl Hershner from CPB, Stuart Appelbaum from CERP, and Steve Gloss from GCDAMP also provided vital review and feedback on the Program Description section as well as the Program Compari-son Matrix.
We appreciate the excellent work by Washington Sea Grant Pro-gram staff , who provided editing, design, and publication services for the document. Funding for the publication of this document was provided by a grant from the King Conservation District through the WRIA 9 Watershed Forum. Puget Sound Nearshore Partnership appreciates the ongoing support from WRIA 9.
Finally, we are grateful to the multiple agencies that funded the visits, meetings and the compilation process – the U.S. Geological Survey; the Washington State departments of Natural Resources, Ecology, and Fish and Wildlife; the Puget Sound Action Team; and the U.S. Army Corps of Engineers, Seattle District.
Citation:
Van Cleve, F. B., C. Simenstad, F. Goetz, and T. Mumford, 2004. Application of “best available science” in ecosystem restoration: lessons learned from large-scale restoration eff orts in the USA. Puget Sound Nearshore Partnership Report No. 2004-01. Pub-lished by Washington Sea Grant Program, University of Washing-ton, Seattle, Washington. Available at http://pugetsoundnearshore.org.
Cover: Cama Beach on Camano Island, Washington is an example of a bluff backed beach. Courtesy of Hugh Shipman, Washington, Department of Ecology.
Technical subject matter of this document was produced by the Puget Sound Nearshore Partnership which is entirely responsible for its contents. Publication services were pro-vided by Washington Sea Grant, with fi nancial support from King Conservation District. Copyright 2005, University of Washington. Th is document may be freely copied and dis-tributed without charge.
Lessons Learned from Large-Scale Restoration Efforts in the USA I
Contents
Executive Summary ................................................................................................................................. ii
Introduction ............................................................................................................................................ 1Opportunity Addressed .................................................................................................................................1Hypothesis and Purpose ................................................................................................................................1Selection Criteria and Clarifi cation of Terms ...............................................................................................1
Methods ................................................................................................................................................... 3Program Backgrounds ...................................................................................................................................3Chesapeake Bay Program ..............................................................................................................................3Comprehensive Everglades Restoration Plan ...............................................................................................4California Bay–Delta Program .......................................................................................................................5Glen Canyon Dam Adaptive Management Program ..................................................................................6Louisiana Coastal Area Ecosystem Restoration Program ............................................................................6
Results ...................................................................................................................................................... 7Chesapeake Bay Program ..............................................................................................................................8Comprehensive Everglades Restoration Plan ...............................................................................................8California Bay–Delta Program .......................................................................................................................8Glen Canyon Dam Adaptive Management Program ..................................................................................9Louisiana Coastal Area Ecosystem Restoration Program ............................................................................9
Discussion ................................................................................................................................................ 9Best Available Science and Restoration Policy ...........................................................................................10Problem Statements and Program Goals ...................................................................................................10Fix the Problem, Not the Symptoms ...........................................................................................................11Program Organizational Structure .............................................................................................................11Maximizing Use of Science ..........................................................................................................................11Vertical and Horizontal Coordination and Integration ............................................................................12Conceptual and Numerical Models ............................................................................................................12Adaptive Management ...............................................................................................................................12Performance Measures ................................................................................................................................12Monitoring and Assessment ........................................................................................................................12Public Involvement and Support .................................................................................................................12
Conclusions ............................................................................................................................................14General Conclusions ....................................................................................................................................14Observations .................................................................................................................................................15
References .............................................................................................................................................17
Appendix A: Interview Questions .......................................................................................................19
Appendix B. Program Background Matrix ..........................................................................................21
Appendix C. Program Comparison Matrix ..........................................................................................23
Glossary of Terms ..................................................................................................................................29
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Executive SummaryPurposeTh e Puget Sound Nearshore Partnership (PSNP) proposes to re-store degraded shoreline ecosystems of Puget Sound. To provide scientifi c direction for PSNP in its planning phase, the program’s Nearshore Science Team (NST) sought to more clearly defi ne the role and position of scientifi c input into large restoration programs such as PSNP. More specifi cally, the NST set out to clarify how sci-ence is incorporated into program management and organizational structure such that the “best available science” (BAS) is realized. Th e NST suggests that effi ciently and eff ectively using science as a foundation for making decisions will greatly improve a restoration program’s ability to successfully conceptualize, design, and imple-ment large-scale restoration eff orts in the long term.
To accomplish their objective, the NST conducted a “lessons learned” exercise to characterize the role of science in fi ve large-scale restoration programs for more mature ecosystems beyond the Pacifi c Northwest: the Chesapeake Bay Program, the Compre-hensive Everglades Restoration Plan, the California Bay–Delta Au-thority, the Glen Canyon Adaptive Management Program, and the Louisiana Coastal Areas Ecosystem Restoration Program. In spite of diffi culties encountered by these programs, the NST was encour-aged by the numerous innovative approaches employed to meet the challenges inherent in large-scale restoration.
MethodsTh e NST sought a comprehensive understanding of the role of sci-ence in large-scale restoration eff orts from four major sources: (1) site visits and personal interviews with scientists, policy or decision makers, and non-governmental organizations; (2) peer-reviewed literature; (3) websites; and (4) unpublished documents.
Semi-structured interviews were conducted using a list of ques-tions organized by topic (Appendix A), which were designed to provide information about the role of science and elicit the strengths and weaknesses of the approaches taken by each pro-gram. Data collected from the interviews, publications, and web-sites were organized and evaluated using two matrices to compare elements of the programs (Appendix B, basic program informa-tion, and Appendix C, interview answers).
Th e lessons discussed in this paper were developed by comparing and contrasting program features summarized in the matrices and relating these to lessons explicitly stated by program representa-tives or those lessons gained by the NST over the course of this study. Th us, the lessons presented arise from (1) the experience of program representatives, (2) characteristics and strategies for incorporating BAS that the NST deemed noteworthy, and (3) the best professional judgment of the NST.
ResultsHighlights from the many lessons learned are as follows:
• Clearly articulated problems are essential for program success. For scientists to translate program goals into technical objectives and assess the feasibility and associated uncertainties of potential actions, science must be involved from the earliest (planning) phase of the program.
• Maintaining the independence of science from policy pressures ensures legitimacy and quality. However, science activities must be coordinated with other aspects of the program. Vertical integration teams help ensure communication between policy and scientifi c aspects of programs.
• Th e method used to solicit science should ideally be a combination of “bottom-up” and “top-down” approaches, thus, ensuring the high level of quality and creativity associated with the former and the strategic, coordinated results associated with the latter.
• Th e strongest assurance for scientifi c credibility is rigorous peer review, both internal and external to the organizational structural. Th is will help ensure that information disseminated to stakeholders via publications, websites, and other media is credible, legitimate, and salient.
• Scientifi c information must be summarized in a way that is understandable to the general public and disseminated to stakeholders in a timely manner. Outreach and education eff orts are critical for gaining long-term support of restoration eff orts.
• Horizontal integration enables programs to tap into outside sources of information and expertise (e.g., academia, contractors). Th is can ensure that fresh perspective and innovative ideas continue to be introduced to the program. Th is also can be accomplished by ensuring turnover of committee members and program managers, especially in long-term programs.
• Developing conceptual and numerical models with a diverse community of scientists/technicians is an eff ective means to resolve confl ict and build scientifi c consensus. Models also help communicate scientifi c understanding to the public.
• While rigorous adaptive management is necessary, this powerful tool can only be eff ectively used if all program participants understand it. Th erefore, education about what adaptive management is and is not is an important aspect of management eff orts.
• Performance measures may be more useful politically than scientifi cally. Selecting appropriate indicators is diffi cult, and some scientists are reluctant to use such narrow, static measures to judge ecosystem health. Indicators like water fl ow requirements and intact salt marsh habitats are important, but they are not the endpoint. All programs
Lessons Learned from Large-Scale Restoration Efforts in the USA III
should be mindful of looking deeper than the surface of the problem if a long-term solution is to be achieved.
• Overwhelmingly, scientists agree that in absence of monitoring, a project may be rendered invalid. While funding for monitoring is almost universally short of what is required to address scientifi c and technical uncertainties, monitoring is the only way to understand short- and long-term eff ects of restoration actions.
• While program goals and individual intentions are important, program accomplishments can largely be driven by the personalities involved. Th is underscores the importance of a capable lead scientist to negotiate compromises between science, politics, and stakeholders.
• Programs tend to plan poorly for numerous expensive and time-consuming unknowns that are characteristic of ecosystem management. Political factors may distract program participants from achieving their goals. A pro-active assessment of the political climate and public receptiveness may help avoid such distractions.
• No programs surveyed made data management a prominent organizational or funding priority. A strategic approach to data management—fundamental to applying scientifi c results—should be formulated at program onset.
• Social sciences have been excluded from restoration eff orts, despite increasing evidence that the success of restoration requires detailed understanding of its social context. A broader, more inclusive meaning of “best available science”—including social sciences—may be diffi cult yet worthwhile in undertaking restoration of large-scale ecosystems in which humans continue to play and increasingly greater role.
By summarizing the lessons learned about how to secure and sup-port the best available science, the NST hopes this document will stimulate interest in improving the role of science in ecosystem restoration and provide present and future restoration practitioners with practical advice gained from predecessor programs.
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Lessons Learned from Large-Scale Restoration Efforts in the USA 1
IntroductionTh e use of the best available scientifi c information is required un-der U.S. law in many environmental decisions. In most instances, statutes requiring the use of best available science (BAS)1 have left the term undefi ned. Th erefore, interpretations of BAS have been developed in state, regional, and federal courtrooms to guide sci-entists, policy makers, and natural resource managers in deciding what is good science. Best available science “include[s] biological, good science. Best available science “include[s] biological, goodecological, economic, and social data”,2 and the generation of BAS normally involves peer review, scientifi c methodologies, logi-cal conclusions and reasonable inferences, quantitative analysis, appropriate context, and thorough references.3 Even less well defi ned, and the topic of this paper, is the most appropriate way to use BAS in diffi cult policy and management decisions, such as those involved in ecosystem restoration.
Th e Puget Sound Nearshore Partnership (PSNP; formerly known as the Puget Sound Nearshore Ecosystem Restoration Program) is a cost-sharing agreement between federal partners and Washing-ton State to identify urgent ecosystem problems in the Puget Sound basin, evaluate potential solutions, and restore and preserve critical ecosystem features of degraded shorelines of Puget Sound.4 Th is process-based, ecosystem restoration project was launched in 2001 and is in its planning phase.5 Scientists within PSNP were aware of the many approaches to using science in large-scale restoration programs across the country. At its inception, PSNP formed a Nearshore Science Team (NST) to provide technical products and scientifi c guidance for the project. To better understand the role of scientists and science in formulating a comprehensive restoration strategy, we sought the opportunity to critically examine science in several, more mature ecosystem restoration programs beyond the Pacifi c Northwest region. Th e purpose of this document is to convey some of the essential lessons learned by the NST to other members of PSNP and to the broader community of restoration practitioners.
Opportunity Addressed Numerous publications address the science of restoration ecology (i.e., Jordan et al. 1987, Zedler 2001) and the incorporation of sci-ence into environmental policy (i.e., Healey and Hennessey 1994; Huxham and Sumner 2000; Lee 1993; Leschine et al. 2003; Nation-al Academy of Sciences 1995, 2000). However, published literature concerning the use of science in restoration policy is lacking. One exception, although outdated, is the National Research Council report, Restoration of Aquatic Ecosystems (NRC 1992). Although updating and fi lling this information gap is beyond the scope of this paper, we intend to focus attention on the need for improving the incorporation of BAS into restoration programs such as PSNP.
Hypothesis and Purpose Th e NST’s fundamental hypothesis is that a restoration program that effi ciently and eff ectively uses science as a foundation for mak-ing decisions will be, in the long run, more successful in meetingrestoration goals. Here, “effi ciently” refers those cases where sci-ence is free to examine all technical approaches to restoration in the absence of non-scientifi c constraints; “eff ectively” refers to situ-ations where science, operating within the confi nes and structure of the discipline, contributes to a decision-making process leading to the accomplishment of restoration goals. We hypothesize that the organizational structure of the program that develops to ad-dress large-scale restoration will dictate the effi cacy of science in the near term. Th erefore, we aim to examine the organizational structure, and specifi cally the placement of science within that structure, in fi ve cases of large-scale, process-based restoration.
Judging the “success” of these restoration programs is not ap-propriate at this time because all are ongoing and each has its own methods for determining success. Instead, by dissecting the organizational structure, we compare elements of programs that infl uence the effi ciency and effi cacy of science. Th e purpose of this document is both to inform and guide the restoration strategy in the Puget Sound and to inform ongoing and future restoration ef-forts elsewhere, ultimately improving the practical application of restoration science.
Selection Criteria and Clarifi cation of TermsWe considered programs that were large-scale and to some extent process-based and ecosystem-focused. “Large-scale” refers to the target area impacted by restoration actions. Generally, and in the case of all programs examined here, large-scale programs have a very large and complicated organizational structure that has devel-oped out of the need to address large spatial areas, long time scales, multiple jurisdictions, and robust fi nancial resources. More im-portantly, we focused on large-scale programs because we believe that many of the environmental degradation challenges cannot be resolved with small-scale actions alone, but will instead require large-scale, landscape approaches. Th is expanded scope requires coordination of interdisciplinary science and a strategic approach to management.
1. Best Available Science is required by the National Environmental Policy Act, Section 102, Subsection B; Marine Mammal Protection Act, Section 108; Endangered Species Act, Section 7(a)(2); and Magnuson–Stevens Fisheries Management and Conservation Act, Section 301(1)(2).
2. Code of Federal Regulations § 602.12(b)(1).
3. Washington State Legislature, Growth Management Act—Procedural Criteria for Adopting Comprehensive Plans and Development Regulations, Part Nine: Best Available Science (365-195-900 thru 365-195-925). See also Bisbal (2002).
4. PSNP website: http://pugetsoundnearshore.org/whatwedo.htm.
5. PSNP website: http://pugetsoundnearshore.org. For more information contact Bernie Hargrave (Bernard.L.Hargrave.Jr@nws02.usace.army.mil) or Tim Smith (smithtrs@dfw.wa.gov).
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Many early restoration eff orts resembled what we would now consider to be site-specifi c mitigation, with emphasis on restoring ecosystem structure rather than ecosystem process. On the basis of ecological understanding that structure and function follow process, restoration eff orts are increasingly expected to restore pro-cesses (i.e., sediment transport, erosion) rather than structure (i.e., a beach or wetland). Th erefore, we selected programs that, to some degree, specifi cally approached their goal from the perspective of restoring ecosystem processes. Our fi ve case studies are by no means an exhaustive list of all process-based restoration programs in the USA.
Our fi nal criterion in selecting case studies was that programs have the general intent to restore the whole ecosystem as opposed specifi c elements of the ecosystem, such as target species or bird nesting habitat. While fully restoring ecosystem processes, struc-ture, and function may be yet beyond our scientifi c capabilities, we selected programs based on their intent rather than their suc-cess at restoring the ecosystem. Th e fi ve programs studied are the Chesapeake Bay Program (CBP), the Comprehensive Everglades Restoration Program (CERP), the California Bay–Delta Author-ity (CALFED), the Glen Canyon Dam Adaptive Management Program (GCDAMP), and the Louisiana Coastal Areas Ecosystem Restoration Program (LCA).
Lessons Learned from Large-Scale Restoration Efforts in the USA 3
MethodsInsights into the role of science in large-scale restoration eff orts were acquired by the NST over 2 years and were generated from four major sources: (1) site visits and personal interviews, (2) peer-reviewed literature, (3) websites, and (4) unpublished documents. Th e data gathered were used to populate two matrices, described in the following text. NST members traveled to Louisiana and the Chesapeake Bay to meet with LCA and CPB program staff and tour project sites, and invited representatives from CERP, CALFED, and GCDMRP to Seattle. Th e NST sought a comprehensive un-derstanding of each program by interviewing scientists, policy or decision makers, and applicable non-governmental organizations (NGOs).
Semi-structured interviews were conducted using a list of ques-tions organized by topic similar to the method described by Kvale (1996). Th e topics and the respective sub-questions (Appendix A) were designed to provide information about the role of science and elicit the strengths and weaknesses of the approaches taken by each program. Th e topics that were addressed included the following:
• Project organizational structure and activities
• Restoration planning and guidance
• Assessment of the causal mechanisms
• Data management
• External factors (such as socioeconomics and policy)
• Integrating science into restoration planning and assessment
• Monitoring and adaptive management
• Peer review
To organize and evaluate the data collected from the interviews, publications, and websites, we designed two matrices to compare elements of the programs. Th e Program Background Matrix con-tains basic program information (Appendix B) while the Program Comparison Matrix summarizes the answers to relevant ques-tions organized by topic (Appendix C). Th e Program Comparison Matrix is based on the interview questions presented in Appendix A. Where answers were not provided or where clarifi cation was needed, individuals within programs were contacted to obtain or verify information.
Th e lessons discussed in this paper were developed by comparing and contrasting program features summarized in the matrices and relating these to lessons explicitly stated by program representa-tives or those lessons gained by the NST over the course of this study. Th us, the lessons presented arise from (1) the experience of program representatives, (2) characteristics and strategies for incorporating BAS that the NST deemed noteworthy, and (3) the best professional judgment of the NST.
Program BackgroundsIn the following sections, descriptions of each program highlight organization and structure specifi cally relating to the role of sci-ence. Th e fi ve programs represent a diverse collection of manage-ment approaches, organizational structures, and environmental,
historical, and social issues; each program has approached its respective challenges diff erently and has integrated science into the organizational structure in unique ways. Th e programs are ordered from oldest to youngest based on the observation that the role of science may evolve as these programs mature and as new programs learn from the mistakes made by predecessors.
Th e following descriptions are not intended to be a complete over-view of each program. We have presented the minimum amount of background necessary to frame our discussion of lessons learned regarding the role of science.6
Chesapeake Bay Program
Project Formation and PurposeFormed in 1983, the CBP is based on an agreement between Mary-land, Pennsylvania, Virginia, and the District of Columbia to re-store and protect the Chesapeake Bay and its tidal tributaries. Th e initial focus of this restoration was water quality, driven by increas-ing eutrophication (Batiuk et al. 2003). Th e watershed for the bay encompasses an area of over 166,000 km2 extending into six states.
In its early years, the program focused on reducing nutrients in the bay. A notable goal of the program was to reduce nutrients in the bay by 40% by the year 2000. While substantial progress toward this goal has been made, subsequent analysis has identifi ed a need for even greater reductions to aff ect meaningful restoration of the system. In subsequent years, this focus expanded to include reduc-ing excess sediments and toxics, as well as restoring important habitat areas and populations of target organisms, such as oysters and fi nfi sh. Th e program monitors the health of the bay through numerous ecosystem indicators.
Organizational Structure and ScienceTh e program is funded and staff ed by the U.S. Environmental Pro-tection Agency (EPA) and the partner states. Direction is provided by an Executive Council composed of the governors of the three states, the mayor of the District, the EPA administrator, and the chair of the Chesapeake Bay Commission (a body of state legisla-tors). Th e Executive Council is served by a Principal Staff commit-tee comprising secretaries of natural resources for the three states and senior staff for other Executive Council members. Routine operations of the Program are overseen by an Implementation Committee, comprising primarily senior state and federal agency personnel and the chairs of the many committees. Numerous pro-gram committees address issues ranging from living resources to local government interests. Stakeholder involvement and public outreach is emphasized on all committees.
A year aft er the Chesapeake Bay program was established, a Sci-ence and Technical Advisory Committee (STAC) was formed to
6. A lesson learned by the authors is that these programs are constantly evolving, making it diffi cult to write an accurate description that is not immediately outdated.
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Comprehensive Everglades Restoration Plan
Project Formation and PurposeTh e Comprehensive Everglades Restoration Plan (CERP) is led by the U.S. Army Corps of Engineers (USACE) and the South Florida Water Management District as equal federal and state partners. CERP evolved in response to the realization that water fl ow from central Florida through the Everglades had decreased dramatically due to extensive engineering and diversion projects and that nutri-ent concentrations of water reaching the Everglades had increased. As a result, the health of the Everglades ecosystem was found to be in broad decline. Th e program covers an area of 47,000 km2 and aims to restore, preserve, and protect an Everglades ecosystem in southern Florida that is self-sustaining and ecologically rich while mitigating risk of fl ood and meeting water supply needs to the area through the year 2050.
Th e Water Resources Development Acts of 1992 and 1996 gave the USACE authority to reevaluate the Central and Southern Florida Project (called the “Restudy”). Th e reconnaissance phase of this eff ort was initiated in June 1993 and the feasibility phase of the Restudy was completed in 1999 with the submission of the Com-prehensive Everglades Restoration Plan to Congress. Supported by the passage of the Water Resources Development Act of 2000, the CERP has the goal to “deliver the right amount of water, of the right quality, to the right places, and at the right time.” Th is four part goal is addressed in the plan with numerous discrete projects, rather than one overarching project, many of which are pilot or experimental projects. Th ese projects are not solicited by requests for proposals, but directed by the program and assigned to appro-priate experts (an example of a “top-down” approach). Funding for the project comes primarily from the USACE budget, ad valorumtaxes from the South Florida Water Management District, and the Florida State budget. Addition funding is provided by other agen-cies such as the U.S. Department of the Interior.
Organizational Structure and ScienceWhile CERP is at the center of the restoration eff orts in Florida, it coordinates extensively with other ongoing restoration eff orts in the state. Th e RECOVER Team (REstoration, COordination, and VERifi cation) was established in 1999 at the completion of the USACE’s Restudy to coordinate science in the program and throughout the implementation of individual projects. RECOVER is a scientifi c and technical group specifi cally charged with estab-lishing scientifi c indicators, assessing progress of the plan, and en-suring an overarching perspective of program actions.7 RECOVER is led by two program managers, one from the USACE and one from the South Florida Water Management District. RECOVER leadership comprises 12 agency representatives. Six Project Deliv-ery Teams serve as the working groups for science and are coordi-nated by RECOVER. Th ese multidiciplinary teams are populated by RECOVER leaders and other interested parties.
enhance scientifi c communication and outreach throughout the Chesapeake Bay watershed and beyond. Th e STAC provides scien-tifi c and technical advice to the program in various ways, including (1) technical reports and position papers, (2) discussion groups, (3) assistance in organizing merit reviews of CBP programs and projects, (4) technical conferences and workshops, and (5) service on CBP subcommittees and workgroups. Th e STAC also serves as a liaison between the scientifi c/engineering community and the CBP. Th rough professional and academic contacts and organizational networks of its members, the STAC ensures close cooperation among the various research institutions and management agencies represented in the bay watershed. Th e Chesapeake Research Con-sortium, Inc., provides staff and logistic support.
Th e STAC reports to the Implementation Committee quarterly and to the Executive Council annually. Th e 38-member committee comprises 11 scientists (appointed by governors and the mayor), 6 federal agency scientists, and 21 scientists selected by their peers to represent a mix of disciplinary expertise. Term limits ensure mem-bership turnover and the input of fresh perspective. STAC mem-bers are not compensated for their service although travel expenses are reimbursed. STAC operates with a limited budget that supports the staff , meetings, workshops, and reviews. STAC does not fund or undertake research. Th e committee makes assessments and recommendations of research needs, but these are passed to other committees within the CBP for further action. Program com-mittees, subcommittees, and workgroups each solicit funding to accomplish tasks. Although these groups report to the Implemen-tation Committee, inter-committee communication/coordination is not always optimal and, in the face of limited program funding, committees compete with each other for resources (Batiuk et al. 2003).
7. Comprehensive Everglades Restoration Program website: http://www.evergladesplan.org/pm/recover/recover.cfm.
Lessons Learned from Large-Scale Restoration Efforts in the USA 5
Th e South Florida Ecosystem Task Force (the Task Force) was es-tablished by the South Florida Water Management District in 1993. Th e Task Force comprises 13 members—7 federal, and 6 non-federal agency representatives—and meets several times per year. Th e Task Force coordinates policies and strategies and, although not actually part of CERP, provides advice and guidance to CERP. Th e Working Group is subordinate to the Task Force and com-prises 33 members from state agencies. Th e Working Group meets monthly to carry out tasks and provide reports to the Task Force. Under the Working Group, the Science coordination team was established to develop a science coordination plan. Th e Science Coordination Team was disbanded aft er the completion of the Re-study but may be reinitiated directly under the Task Force (Apple-baum 2003). Th e Committee for the Restoration of the Greater Everglades Ecosystem (CROGEE), which was established by the National Academy of Sciences, provides independent scientifi c re-view to CERP. Th e Task Force approves CROGEE’s work plan and CROGEE provides completed reports to the Task Force.
California Bay–Delta Program
Project Formation and PurposeTh e California Bay–Delta Program, also called the California Bay–Delta Authority,8 was established to coordinate eff orts to address numerous interrelated water management, ecosystem restoration, drinking water quality, and levy reliability issues in California’s Sac-ramento–San Joaquin Delta. Th e Program was formally launched in 1994 with the signing of a “Framework Agreement” by federal and state environmental and natural resource agencies. Th is agree-ment evolved into a long-term program, CALFED, which is be-ing cooperatively implemented by more than 23 state and federal agencies to manage the quality and quantity of water allocation to urban, agricultural, and ecosystem needs in the bay–delta region, an area of 3,000 km2. Th e program addresses four interrelated objectives—water supply reliability, water quality, ecosystem resto-
ration, and levy system integrity—which are further divided into 11 components. Th e program addresses these objectives by for-mulating water quality standards and coordinating the State Water Project and Central Valley Project operations with regulatory re-quirements the Authority hopes will ensure long-term solutions to problems in the Bay–Delta estuary.9
Governance of this program is carried out by state and federal agencies with legislative authority to conduct activities. Overall coordination is the responsibility of the California Bay–Delta Au-thority, a state agency specifi cally created in 2002 to fi ll the over-sight role in the program.10 Th e program shares the staff of partner agencies and has its own staff dedicated to helping accomplish program mandates (Luoma and Taylor 2002).
Th e main program funding source is state and federal appro-priations, while auxiliary or new program requirements can be met with bonds or special state and federal appropriations. Th e program has completed Phase I (assessment) and II (selection of alternatives) and is now entering Phase III, the implementation of preferred alternatives and construction. Th us far, several early-action ecosystem restoration projects have been completed. Th ese projects are generally selected on a competitive basis in response to a request for proposals (Luoma and Taylor 2002).
Organizational Structure and ScienceScience and technical expertise is integrated throughout all ar-eas of the CALFED program; however, the Science Program housed within the California Bay–Delta Program is the nexus of authoritative scientifi c and technical information.11 Th e Science Program focuses on disseminating information, developing com-
9. CALFED (2000); CALFED website: http://calwater.ca.gov.
10. CALFED website: http://calwater.ca.gov.
11. CALFED website: http://science.calwater.ca.gov/index.shtml.
8. As of August 2002, the California Bay–Delta Program, commonly called CALFED, was renamed the California Bay–Delta Authority. As a convention we will use CALFED when referring to this program.
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mon language, acting as publication support within CALFED, and providing advice and support for integrating science throughout the program (Taylor 2003). Th e Science Program staff comprises experts employed by their agency and compensated for CALFED time (Luoma and Taylor 2002).
Within the Science Program, the Executive Science Board is a standing committee of recognized experts that directly advises the Authority. A core element of the Science Program is a system of advisory boards and peer-review panels overseen by the Indepen-dent Science Board. Standing boards comprise experts appointed by the Lead Scientist that combine interdisciplinary expertise to provide advice and review. Technical panels and ad hoc working groups are assembled to address specifi c technical and scientifi c issues (CALFED 2003a). In general these science groups do not address policy questions but strictly provide technical advice to the Authority pertaining to policy decisions (Luoma and Taylor 2002).
Within the science program, the Executive Science Board is a stand-ing committee of recognized experts that directly advises CALFED. A core element of the science program is a system of advisory boards and peer-review panels overseen by the Independent Science Board. Standing boards comprise experts appointed by the lead sci-entist that combine interdisciplinary expertise to provide advice and review. Technical panels and ad hoc working groups are assembled to address specifi c technical and scientifi c issues (CALFED 2003b). In general these science groups do not address policy questions but strictly provide technical advice to CALFED pertaining to policy decisions (Luoma and Taylor 2002).
Glen Canyon Dam Adaptive Management Program
Project Formation and PurposeTh e Glen Canyon Dam Adaptive Management Program (GCDAMP) is coordinated by the U.S. Department of the Interior’s Grand Canyon Monitoring and Research Center (GCMRC). GCMRC’s mission is “to provide credible, objective scientifi c infor-mation to the Glen Canyon Dam Adaptive Management Program on the eff ects of operating Glen Canyon Dam on the downstream resources of the Colorado River ecosystem.”12 Dam operations have
had several negative downstream aff ects including alteration of the structure and integrity of downstream beaches, resulting in loss of spawning and rearing habitat for endangered fi sh species. In re-sponse, the GCDAMP aims to evaluate the impacts of dam opera-tions on the Colorado River ecosystem by conducting a long-term monitoring and research program using an ecosystem-based ap-proach.13 Th e GCMRC has conducted the scientifi c investigations called for in the GCDAMP since the establishment of the research institution in 1996.
We selected this program because of its employment of adaptive management—that is, the incorporation of scientifi c experiments into natural resource management.
Organizational Structure and ScienceTh e Adaptive Management Work Group (AMWG) of the GCDAMP directs the monitoring program for the lower Colorado River from Lake Powell to the westernmost boundary of the Grand Canyon National Park. Th e scientifi c results generated by the activi-ties of the AMWG are used by the GCMRC to improve ecosystem management in Lake Powell, the lower Glen Canyon, and in the Grand Canyon.
Th e AMWG is a federal advisory committee comprising federal, state, tribal, and other stakeholder representatives. Th e AMWG meets semiannually to review Glen Canyon Dam management and operations; it makes recommendations to the Secretary of the Interior on dam management and advises and directs the GCMRC (GCMRC 1999). Several Independent Review Panels operate within the GCDAMP to increase scientifi c credibility of GCMRC science.
Louisiana Coastal Area Ecosystem Restoration Program
Project Formation and PurposeLouisiana loses coastal wetlands at a rate of approximately 60 km2
per year—a combined result of the natural subsidence of the delta and the interruption of natural deltaic sedimentation processes due to diking and channelization of the Mississippi River.14 In 1990, as a response to national wetland degradation and to the alarming rate of land loss in Louisiana, Congress enacted the Coastal Wet-lands, Planning, Protection and Restoration Act (CWPPRA, also known as the Breaux Act). CWPPRA funds wetlands enhancement projects and has contributed substantially to planning for large-scale restoration of Louisiana’s disappearing coast, making this program the largest, in area, of the programs studied.
In recognition that the CWPPRA eff ort alone could not address the scale of the Louisiana’s coastal degradation problem, a new
12. Glen Canyon Monitoring and Research Center website: http://www.gcmrc.gov.
13. Ibid.
14. Louisiana Coastal Area Ecosystem Restoration Program website: http://www.coast2050.gov/lca.htm.
Lessons Learned from Large-Scale Restoration Efforts in the USA 7
state and federal plan was adopted in 1998. Th e report, titled “Coast 2050: Toward a Sustainable Coastal Louisiana” (or “Coast 2050”),15 divides Louisiana’s coastal area into four (sub-province) regions and aims to restore or reconstruct the natural coast-build-ing processes in Louisiana at a more regional scale. Eighty-eight restoration strategies for the four regions are presented in this document, which was developed by state, federal, and local partici-pants, including stakeholder and public interest groups.
In May 1999, the USACE headquarters commissioned a feasibil-ity study under the Louisiana Coastal Area Authority of 1967. Th e cost of the study is shared by the New Orleans District of the USACE and the Louisiana State Department of Natural Resources (DNR). Th is feasibility study, projected to last 2 years, is based on the strategies identifi ed in the Coast 2050 plan and is called the Louisiana Coastal Areas Comprehensive Coastwide Ecosystem Restoration Study (LCA). Th e aim is to determine a comprehen-sive action plan for the four sub-provinces based on the ideas
15. Ibid.
presented in the 88 restoration strategies identifi ed in Coast 2050. Th e study area includes all of coastal Louisiana stretching from Mississippi to Texas.16
Organizational Structure and ScienceTh e LCA Feasibility Study is directed by an Executive Committee lead by a secretary from DNR and a commander from the USACE. A Project Delivery Team oversees production of reports and the dissemination of information within the project. Th e Project De-livery Team also facilitates involvement from the broader scientifi c community. Th is outside, non-agency contribution of scientifi c information has been of considerable importance for the project and has addressed tasks such as synthesizing the state of the sci-ence and developing complex ecological modeling techniques.
Several teams advise the Executive Committee and the Project De-livery Team. Th e National Technical Review Committee (NTRC) provides independent peer review and valuable outside perspective to the Executive Committee. Th e NTRC comprises 10 scientists from around the country representing expertise in the natural sci-ences, economics, engineering, and planning (Porthouse 2003). Th e Vertical Integration Team, comprising local and federal repre-sentatives, is charged with expediting scientifi c reviews and issue resolution (Porthouse 2003). Th e Vertical Integration Team’s vital function is to provide a mechanism by which science and policy issues are communicated to all program levels.
Several other groups provide advice and help to identify and resolve confl ict. A Principals Group coordinates agency input into the program and the Regional Working Group facilitates the transfer of information between local participants and the Prin-cipals Group. A Framework Development Team comprises local representatives of federal and state agencies, academia, and NGOs (Porthouse 2003).
16. LCA (2002) and http://www.lacoast.gov/cwppra/org/techcom.htm#description.
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17. Joy Zedler (2001) argues against the use of “success” in discussions of meeting restoration endpoints because of the implied possibility for failure if success is not attained within the program confi nes. She suggests “progress” replace “success” in most cases because this term allows success to take on multiple forms. We agree and also favor the term “performance” to describe elements of restoration programs.
ResultsWe found that the fi ve programs represented a range of approaches to address the fundamental challenges of integrating science into policy and decision making. Each program has evolved in very diff erent natural and political environments. We make no attempt to judge overall program performance, or “success”,17 only to learn from the various scientifi c strategies undertaken in each program. In this section, we address specifi c lessons learned program by program. (Refer to the Program Comparison Matrix in Appendix C for details.)
Chesapeake Bay ProgramTh e CBP demonstrated the importance of a lead scientist to negoti-ate compromises between science, politics, and stakeholders. In this program, the intentions of individuals and program goals were important, but the fi nal accomplishments of the program have been largely a result of the personalities of the individuals at the table.
Th e Chesapeake Bay Program demonstrated the benefi t of cultivat-ing involvement with outside academic scientists. Th is horizontal integration requires dedicated eff ort to maintain, but it is facilitated by collaboration with research consortia, such as the Chesapeake Research Consortium, Inc. In the Chesapeake Bay Program, science fellows, oft en PhD students on a 2-year contract to work with the science program, helped bring fresh perspective into the program and keep high-level and innovative science going. Science fellows also provided staff support to work with committees so that com-mittee members do not become overwhelmed with managerial and administrative details. We also found it important to ensure turn-over among program managers and science committee members.
Th is program also provided several lessons regarding public buy-in and participation. In the late 1990s, when the CBP found itself working on very important issues in the bay that the public did not relate to, program leaders shift ed the focus from eutrophication to include more charismatic problems, such as decreasing oyster and fi nfi sh populations. Th is program also demonstrated that problems should be phrased to engage the public and decision makers. For example, “recover oyster populations” is likely to draw more and broader support than “improved sediment dynamics.” Th is shift in the CBP has engaged the public in scientifi c issues, therefore increasing saliency of the scientifi c program (see Discussion), and has helped focus the program on the entire ecosystem.
An additional lesson highlighted by the CBP is that these large, ambitious programs oft en fail to plan appropriately for the expense and time required to manage resources at an ecosystem scale. Th e CBP substantially underestimated the eff ort required for the
transition from a regulatory water quality program to ecosystem management.
Th e public is extensively involved in the CBP and we noted two successful strategies for gaining this participation. Chesapeake Bay Foundation, a non-profi t organization, provides tremendous help with public outreach. Forming alliances with local NGOs helps to spread resources and off er more people and groups the opportu-nity to become involved and contribute to the program’s progress. Also, the CBP puts substantial eff ort into regularly communicating scientifi c results to the public via weekly and quarterly publica-tions (Th e Bay Journal and the Chesapeake Futures Report). Th is has helped obtain public support and educate stakeholders.
Comprehensive Everglades Restoration PlanTh e CERP was established to address the water distribution crisis in South and Central Florida. Because the “crisis” was widely ac-cepted politically and publicly, CERP was able to generate politi-cal and fi nancial support. CERP has been well served by such a clearly defi ned and urgent problem. In the late 1980s, program members conducted a unique brainstorming session to develop program goals and objectives, which served to inform and defi ne the USACE reconnaissance and feasibility study and ultimately the CERP.
In this program, the organizational structure was fi xed and the range of restoration options already predetermined before science began to play a role. Th is situation constrained innovative science and limited the power of science to infl uence decisions. Also, this program has oft en been frustrated by tensions between state and federal agency partners, which may be a result of the USACE’s tendency to rely on engineering solutions to solve environmental problems or the highly political nature of the problem. At times, this confl ict has hindered progress and consumed resources. CERP also demonstrated the importance of a charismatic leader in gaining broad support for the program and negotiating compro-mises between individuals and groups involved in the program.
CERP has successfully established a spectrum of performance measures/indicators. Th ey did this by winnowing a list of 1,000 potential indicators to approximately 50 that will be tracked; less than 10 were used for planning purposes in reporting to high-level decision makers. Although the exercise resulted in a list of indicators, the brainstorm approach taken may not have been the most effi cient or eff ective. CERP also has an adaptive monitoring assessment team that assesses early actions, or “demonstration” projects. Th e system-wide monitoring and assessment plan that was scheduled to be released at the end of 2003 (Applebaum 2003) may resolve the lack of attention and resource paid to monitoring in this program.
California Bay–Delta ProgramTh e simplifi ed objective of any program should be to determine that the appropriate restoration and management actions are pro-posed and that they will work. CALFED has done well to ensure that proposed and accepted projects answer pertinent questions
Lessons Learned from Large-Scale Restoration Efforts in the USA 9
about estuarine function and structure, are of high scientifi c qual-ity, and have high probability to achieve the desired performance.
CALFED is a strongly “bottom-up” restoration program. It posts requests for proposals widely and selects projects on a competitive basis. Th is strategy guarantees high-quality science through a com-petitive process, whereas the “top-down,” or directed, approach employed by most other programs in this study may diminish scientifi c creativity and quality. Because “bottom-up” restoration actions tend to be more opportunistic and potentially disjointed, CALFED has instituted a separate, directed science program to strategically address specifi c science and monitoring needs. Al-though CALFED has a monitoring plan, they are still struggling to determine what to monitor and have instituted a program to scien-tifi cally resolve monitoring metrics that comprehensively assess the contribution of CALFED restoration.
CALFED has demonstrated that peer review is the most eff ective way to ensure the use of best available science. Th eir extensive internal and independent peer-review system has shown that the best combination of experts for a peer-review panel includes indi-viduals who are local and involved in the program, local and unin-volved, and non-local and uninvolved. Th ese individuals should be recognized as much for their objectivity as for their expertise.
Additionally, CALFED has managed to infuse science throughout the program, partly aided by several “integration teams.” Vertical integration (see LCA program description in Methods) is best ac-complished with purposeful help from planners or facilitators, as scientists themselves oft en do not excel at integrating their work with policy.
Conceptual models have played an important role in commu-nicating basic ecosystem understanding to CALFED program participants and as a scientifi c aid in making program decisions. Also, funding packages or portfolios, used by CALFED, are an in-novative and creative approach to ensuring long-term funding and to integrating science throughout the process. It remains to be seen how CALFED’s funding portfolios will play out in the long term.
Glen Canyon Dam Adaptive Management ProgramTh e most valuable lesson that this program provided was regarding the use of adaptive management in a restoration and experimental ecosystem management context. Adaptive management in this program requires a high level of participation and commitment from resource managers and scientists. It also requires constant feedback between resource users and scientists, and appropriate mechanisms must be in place to support this. Scientifi c experi-ments, the foundation of adaptive management, are oft en diffi cult to support, as demonstrated by the fact that there has only been one experimental fl ooding event at the Glen Canyon Dam. In comparison, it is generally easier to generate fi nancial support for monitoring programs than for adaptive management.
Adaptive management is oft en misunderstood. Th e term is sometimes used to describe informal learning from management mistakes and other times to describe management decisions based on controlled, scientifi c experiments. For this tool to be properly used, it must be explained to all involved. Th e Glen Canyon Pro-gram demonstrated the importance of educating users and stake-holders about adaptive management.
Louisiana Coastal Areas Ecosystem Restoration ProgramTh e integration of science into the LCA program has been slow— possibly because science was not explicitly involved in the forma-tion of the program. Th us, the program development process has not facilitated optimal use of science and, as a result, the program is still struggling to bring science into the decision-making process. Also, political pressures and powerful stakeholders, such as oyster growers, confi ne the range of possible solutions, thus limiting sci-ence’s infl uence and legitimacy within the program. While several long- and short-term problems have resulted from not infusing science throughout the program, LCA’s Vertical Integration Team does represent a good example for a strategy to coordinate restora-tion eff orts and link science and policy.
Although the LCA program has successfully addressed the symp-toms of the problems facing the Louisiana coast (land loss and eutrophication of the Mississippi River), it has struggled to address the underlying problems (dam construction and operation in the Missouri/Arkansas river basins, agricultural chemical use in the Mississippi River watershed, and coastal land-use practices). Be-cause the root problem includes resource-use practices in the entire Mississippi–Ohio–Missouri River Basin, this program has had to balance the tendency to focus on smaller, localized problem symp-toms with a long-term approach aimed at the underlying problems. Th is development was demonstrated by the transition from the res-toration activities accomplished under the Breaux Act, the majority of which were small in scale and uncoordinated, to the watershed-scale LCA program, which aims for a strategic approach to restora-tion planning activities.
Similarly to CERP, this program has been frustrated from tensions and misunderstandings between state and federal agency partners. Also, like most programs, the LCA has struggled to incorporate monitoring into the program. However, the LCA recently estab-lished a long-overdue monitoring scheme for some Breaux Act actions.
Th e National Technical Review Committee (NTRC) provides essential outside program review. Th is panel of external but in-formed experts meets at least twice a year and serves as an excellent template for a strategy to ensure appropriate program actions and focus.
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DiscussionIn this section, we organize lessons learned by general topic and explicit subject headings. Lessons presented in the Results section are discussed in the context of current knowledge and available literature. Th ree similarly structured documents provided espe-cially helpful comparisons of restoration programs: Putting it Back Together: Making Ecosystem Restoration Work, published by Save the Bay (Koehler and Blair 2001); Investigative Review: Institu-tional Arrangements, published by USACE’s Engineering Research and Design Center (Soileau 2002); and Lessons from Large Wa-tershed Programs, published by the National Academy of Public Administration (Adler et al. 2000). Although these documents do not focus specifi cally on the role of science, they contributed to our comparative understanding of these programs.
Best Available Science and Restoration PolicyTh e published literature is rich with insights into the oft en troubled relationship between science and policy.18 Th roughout our inter-actions with the fi ve projects, we were reminded of several basic principles of an eff ective working relationship between science and policy that further suggest fundamental strategies for optimizing science’s role in the decision making processes.
To avoid the misuse, and ensure the best use, of science, we must understand the fundamental limitations of the scientifi c discipline. Science is a process of inquiry grounded in hypothesis testing and observation. Scientists aim to produce objective, value-free19information from data gathered from the natural world. Th us, scientists are comfortable collecting information that can be used to understand the potential consequences of actions; however, sci-entists generally begin to feel uncomfortable when asked to advise decision makers regarding what should be done given the scientifi c should be done given the scientifi c shouldinformation presented. Scientists who abandon objectivity for ad-vocacy run the risk of loosing credibility in the eyes of other scien-tists and the public (Boesch and Macke 2000). Th erefore, scientists should not be asked what should be done, but rather to defi ne the should be done, but rather to defi ne the shouldpossible range of actions and evaluate the consequences of those actions. Decision makers should then consider other factors, such as social, economic, and legal issues in addition to scientifi c input (Boesch 1999, Huxham and Sumner 2000).20
In order for science, and problems addressed by scientists, to eff ec-tively infl uence decision-making, the science must be judged to be relevant. Clark et al. (2002) defi ned three attributes that infl uence the eff ectiveness of science:
Saliency—whether science is perceived as addressing policy-relevant questions
Credibility—whether science meets standards of scientifi c rigor, technical adequacy, and truthfulness
Legitimacy—whether science is perceived as fair and politically unbiased
Generally, attaining these three attributes requires making diffi cult compromises. Although defi ciencies in one attribute may be off set by strengths in another, some threshold level of all three attributes is required for science to contribute to policy decisions (Clark et al. 2002).
In this study, all programs demonstrated that peer review is the best way to ensure credibility and the development and use of BAS. Th ese programs used the term “peer review” to describe activities that ranged from rigorous and anonymous review of products by out-side technical experts to review of the overall restoration program by respected scientists from outside the program region. Th e op-timal combination for reviewing products and proposals includes objective experts who are local and involved, local and uninvolved, and uninvolved and not local. Saliency and legitimacy were en-hanced in these programs when high-level external review was employed.21 Th ese programmatic reviews provided critical outside advice to guide the focus and structure of the program.
Although peer review is clearly the best way to ensure credible science, opinions vary about what is encompassed in “best avail-able science.” Th e dissenting view proposed that “science” is not a monolith—not a thing, but just one way to frame issues in a very narrow context. One interviewee suggested that the term “schol-arship” is perhaps better because it includes dimensions that are important to humans, such as the humanities, history, and the social sciences. Many people we talked with agreed that the divide between natural and social sciences should be narrowed, but few had demonstrated practical techniques to accomplish this.
Problem Statements and Program GoalsAll programs demonstrated that clearly articulated problems and goals are essential to ensure federal and state agency coordination. Also, the problem statement almost always emerges from a widely accepted “crisis,” which means that the public has to be involved in
18. For early articles see Dunn (1980) and Webber (1983).
19. For discussions of whether science is truly value-free, see Huxham and Sumner (2000), p. 52-55.
20. Sabatier rejects the notion of neutral scientists in his promotion of the concept of an “advocacy coalition framework” (Sabatier 1988, 2000). See also Hass (1990) for a related discussion on “epistemic communities.”
21. External programmatic review can lend credibility to national programs subjected to intense external scrutiny. LCA has benefi ted from a National Academy of Engineering review (scheduled to be released in April 2004) and also has established its own institutionalized panel, the NTRC. In 1999, the GCMRC’s adaptive management plan was reviewed by the NRC (1999). CERP was recently reviewed by the General Accounting Offi ce (2003) and is in the process of establishing a NRC review panel (Applebaum 2003). CALFED’s Independent Science Board provides review and advice and works with the NRC when outside review is necessary (CALFED 2003b).
Lessons Learned from Large-Scale Restoration Efforts in the USA 11
defi ning the problem. Public buy-in at the problem-defi nition stage of the project is tied to many aspects of the potential for progress towards meeting restoration goals. Articulated problems should be phrased for the public—that is, “recover populations of key spe-cies” rather than “improved sediment dynamics.”
Th e overall goal of large-scale restoration programs should be to determine that the right actions are proposed and that they will work. Th is should include a well-developed approach to addressing problems.
Fix the Problem, Not the SymptomsAll programs should be mindful of looking deeper than the sur-face of the problem if a long-term solution is to be achieved. We were warned to be aware of surrogates; water fl ow requirements and intact salt-marsh habitats are all indicators that show overall ecosystem change and degradation. Th ese surrogates are both indi-vidually valuable targets and important stepping stones to the para-mount goal of recovering the integrity of ecosystems, but it should be remembered that surrogates are not the endpoint.
Cultural Diff erences Between Science and PolicyClear communication between scientists and among users of scien-tifi c information, or horizontal and vertical integration (see follow-ing section), is a challenge for those at the policy/science interface (Douglas 2000). Th is arises from the cultural diff erences between scientists and policy makers. Th e need for translation between science and policy is oft en quite real as the disciplines have diff er-ing world views, peer pressures, reward systems, and specialized speech and jargon. A well-documented source of misunderstand-ing is the diff erent interpretations of uncertainty. Scientists are trained to work with uncertainty and confi dence intervals or prob-ability statements to describe levels of uncertainty. To policy mak-ers uncertainty oft en translates to risk, which in the political arena, is to be avoided at all costs (Bierbaum 2002, Boesch and Macke 2000, Lee 1993). Th e divide separating interpretations of uncer-tainty is large; “where science thrives on the unknown, politics is oft en paralyzed by it” (Gore 1992).
Policy makers frequently complain that scientists oft en fail to gen-erate information in the short timeframe of most policy decisions (Bierbaum 2002, Boesch and Macke 2000, Douglas 2000). Science should not be asked to generate quick results from long-term studies; however, scientists could package preliminary results for delivery to policy makers. Conversely, future policy decisions can be based on a long-term strategy where planning decisions are co-ordinated with the expected delivery of key scientifi c results.
Science should phrase results in a way that is useful to decision makers. For example, it is helpful for decision makers to know “x% of a particular ecological feature must be unencumbered for it to be functional (± error bars).” Th is way information is packaged functional (± error bars).” Th is way information is packaged functionalsuch that decision makers can weigh scientifi c input against other factors that contribute to decisions, such as social values and economics.
We found that oft en too much is expected of science and that
sometimes scientists oversell what science can accomplish. Science can help reduce uncertainty by disproving experimental hypothe-ses. Science does not naturally provide clear policy solutions. Even among the volumes of published literature explaining the distinct cultures of science and policy, there is still a need to translate be-tween scientists and policy makers.
Program Organizational Structure For several programs, a strong lead scientist has been vital for negotiating compromises between science, politics, and stakehold-ers. Th ese charismatic leaders should convey the consequences of actions over space and time and stay focused. Leadership should be established early in the program rather than later if possible. Intentions and goals are important, but the fi nal accomplishments of the program will likely be a result of the personalities in leader-ship roles.
Another lesson was about the importance of building into the pro-gram a mechanism to incorporate new people and fresh perspec-tive. If the program will operate for more than 5 years, turnover in leadership and membership is essential. Hiring research fellows or short-term apprentices is a unique way to incorporate fresh perspective.
Several programs mentioned the importance of a common geo-graphic center for science and planning activities. Having a co-located team engenders better interactions if program participants share space and resources. Also, teams and work committees should be provided with staff support for optimal operation so that experts are not swamped with administrative details.
Maximizing Use of ScienceTo address the high uncertainty in large-scale restoration, science should clearly have a role in any large-scale eff orts. However, there is not one correct model for that role. Th e programs examined all involved science, but the best strategies incorporated science into the process early, oft en from the beginning or before the formal creation of the program. If the program structure is fi xed before science begins to play a role, the alternatives that science can evalu-ate are oft en predetermined and already limited, and all the stake-holders do not necessarily see a thorough scientifi c assessment of all technically viable alternatives. In this situation, science is not operating optimally and may be frustrated by the organizational constraints of the program.
In general, we observed that a bottom-up approach to soliciting restoration projects and proposals guaranteed high-quality science through a competitive process, whereas top-down approaches can diminish the creativity and quality of the science. However, a bot-tom-up approach that allowed science to “bubble up” from the broader scientifi c community tended to result in an ad hoc, dis-jointed approach to opportunistic, small-scale restoration while a top-down approach resulted in strategic, coordinated science. Th us, we found the best approach for incorporating science into the program was by using a directed approach with a built-in mechanism to incorporate unsolicited proposals. CALFED dem-
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onstrated this combination of bottom-up and top-down approach-es by soliciting Requests for Proposals from the scientifi c commu-nity while still maintaining the vision of strategic, long-term science.
In these programs, science tended to be most eff ective when there was a formal pathway for transporting or translating scientifi c information to decision makers while science itself was insulated from the planning process. Th us, scientists were not put in a posi-tion to advocate for decisions and risk losing credibility or be infl u-enced by political pressures and risk compromising legitimacy, but were still able to provide unbiased scientifi c information for deci-sion makers. Most programs, however, lack an effi cient and estab-lished method for getting scientifi c information to policy makers. We found that most programs are still driven by policy makers without adequate feedback from scientists.
Vertical and Horizontal Coordination and Integration Most programs stressed that science is most eff ective when it is involved in the program formation process and infused through-out every level of the program. If science is not well integrated into the program it can be detrimental to long-term progress because fundamental science issues may be overlooked. Th is infusion re-quires a concerted integration eff ort. We found that integration is oft en limited by not having dedicated staff because it is placed on the shoulders of part time staff as extra work. Full-time research fellows have helped the Chesapeake Bay Program staff with the integration eff ort. In two programs, vertical integration teams have been essential in coordinating restoration players within the program and linking policy and science. Also, CALFED’s portfolio funding approach helped to integrate science throughout the pro-cess.
Horizontal integration includes coordinating with appropriate academic groups and consulting fi rms. Th is eff ort also deserves assigned responsibility because it can be extremely valuable to tap into outside sources of information and expertise. Programs were most successful at horizontal integration when there was an exist-ing research consortium in the area with which to collaborate.
Lack of coordination between state and federal partners sometimes resulted in tensions that frustrated progress. We also noted that confl icting science issues, if not resolved, can disrupt the coordina-tion of the program. Sometimes this resolution requires trained facilitators and outside planners.
Conceptual and Numerical ModelsConceptual models help communicate scientifi c understanding to program participants, stakeholders, and the public. Th ese models also allow us to clearly explain the working hypotheses behind on-going restoration projects and determine appropriate performance measures. Oft en there is confl icting scientifi c evidence for envi-ronmental degradation. When the resulting competition between so-called objective experts is seen as politically motivated, it com-promises scientifi c credibility and hampers acceptance of science
and technology’s necessary contribution to ecosystem restoration. We found that drawing on a diverse community of scientists/tech-nicians to develop conceptual and numerical working models to test all restoration strategies was a means to resolve confl icts and for passing a scientifi c “consensus” on to restoration managers and decision makers. In addition, the requirement in bottom-up programs such as CALFED, whereby proponents for funding were required to provide a conceptual model of the project and expected outcomes, greatly improved the quality of proposals and resulting projects.
Adaptive ManagementMonitoring, adaptive management, and continual assessment of actions must be integrated for successful implementation and con-tinued scientifi c learning in long-term restoration programs. Adap-tive management is a very powerful, yet poorly understood, natural resource management tool that purposefully includes learning from scientifi c experiments. It must be understood by those who use, support, fund, and challenge it. Th erefore, education is a very important part of adaptive management.
Performance MeasuresWe found that performance measures may be more politically than scientifi cally useful. Gauging progress in response to restoration actions is important, but forgetting to look past the selected indica-tors is dangerous. Selecting appropriate indicators of system health or program performance is extremely diffi cult; we found that sev-eral scientists were reluctant to judge ecosystem health with such narrow, static measures. Few programs have actually established performance measures.
Monitoring and AssessmentOverwhelmingly, we heard from scientists that if it is impossible to monitor the results of project actions, the worth of the project should be seriously questioned. Several NST members suggested that no less than 20% of the money spent on restoration actions be devoted to monitoring and assessment. Scientists and policy makers have spent far too much money already on actions with unknown eff ects. Monitoring is the only way to understand short- and long-term eff ects of restoration action and more oft en than not it is the fi rst thing to be cut from the budget.
Public Involvement and Support Regular and extensive communication of scientifi c results is one of the most important ways to obtain stakeholder/public invest-ment in the program. To get the most out of best available science in restoration decision making, stakeholders and the public must perceive it as credible, legitimate, and salient. In these large-scale restoration programs, public support is vital because it is ultimately linked to the long-term sustainability of the program in terms of public buy-in and cooperation and funding appropriated to resto-ration action. All programs agreed that the responsibility to ensure an established method of pubic outreach needs to be assigned to
Lessons Learned from Large-Scale Restoration Efforts in the USA 13
some person or group. Public involvement can, however, be aided by the outreach capabilities of involved, local NGOs.
Some disagreement existed over the quantity and form of public involvement. Most people indicated that there can never be too much, while others cautioned that too oft en the public’s prejudices or uninformed gut feelings are allowed to defi ne project direc-tion and restoration actions. Th e latter view held that it is the responsibility of governmental agencies or resource managers to create an educated populace and to help the public understand the consequences of actions on spatial/temporal scales. Th is role is, of
22. For a discussion on “shared statements” of truth relative to PSNP, see the introduction of the Guiding Ecological Principles document (Goetz 2004).
course, dependent on managers and agency representatives who are themselves scientifi cally informed.
All programs agreed that it is essential to build credibility and trust in the program and, ultimately, its science. Th e best techniques for cultivating credibility and trust are with tools including peer re-view and outreach, user-driven milestones, and articulated shared “statements of truth.”22 It is also essential to acknowledge the dif-fi culty of explaining uncertainty and to demonstrate a convincing and accurate problem statement.
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ConclusionsScience has an essential role in large-scale ecosystem restora-tion. Th e high degree of uncertainty inherent in the scientifi c and technical requirements of ecosystem-scale restoration demands that actions are based on the best scientifi c understanding avail-able. Th rough ongoing ecosystem restoration eff orts such as we described in this document, the role of science is becoming more defi ned and the strategies for incorporating science are gradually improving.
We were encouraged by the number of large-scale restoration programs available for our analysis. In general, these programs are making impressive progress towards the diffi cult task of ecosystem restoration on a landscape scale. Th e diverse natural and political environments that shaped these programs and their resulting or-ganizational structures provided a variety of strategies for optimal use of science. In essence, they provided us with experimental treatments to test the diverse approaches for incorporating science into their programs. Th ey also documented, albeit in hindsight, an array of pitfalls to be avoided. As more large-scale restoration ef-forts emerge in the future, we trust that the lessons learned in these earlier programs will be refl ected as a heightened incorporation of the best available science and a proportional decrease in restora-tion uncertainty.
General Conclusions1. Clear and well-defi ned program goals must be translated
into scientifi c and technical objectives.
a. Th e process of placing broad program goals into a scientifi c and technical context frames the initial scope, feasibility, and uncertainty associated with available approaches to restoration.
b. It is essential to ensure science is a participant in goal setting and problem defi nition and can contribute to the technical success of the program from the beginning.
c. Goals must be phrased to engage the public and decision makers.
2. Maintain the independence of science while balancing maximum communication and coordination across all program sectors.
a. Science should inform policy, and vice versa, but neither should regulate the role of the other; scientists and policy makers could each become a student of the other’s culture.
b. Incorporate and populate the scientifi c sector early, preferably at the same time that policy, management, outreach and the other sectors are developed.
c. Science should be allowed to focus on the technical and scientifi c goals, and those eff orts should not be diluted by infusion of other demands from the program for scientifi c analysis and advice not directly related to their mission.
d. Inter-program communication or “vertical integration” is essential where science is explicitly represented in other management, policy, outreach, and other program sectors.
3. Both bottom-up and top-down scientifi c direction needs to be integrated into a large-scale ecosystem restoration program.
a. Large-scale ecosystem restoration cannot be strategic if left to bottom- (“bubble”) up science alone; distributing restoration alternatives across the landscape must be scaled to restore ecosystem processes, which is diffi cult if not impossible with ad hoc deployment of opportunistic, small-scale restoration.
b. Similarly, scientifi c creativity must not be stifl ed by an overly authoritative science structure; programs should incorporate mechanisms and support for unsolicited proposals that allow the program to grow and evolve “outside the box” as well as draw in qualifi ed outside expertise.
c. In exemplary programs, illustrated to some degree by CALFED, some level of top-down scientifi c guidance provides a template within which bottom-up science can fl ourish and contribute.
4. Establish several layers of independent scientifi c review.
a. Establish a peer-review system of local-involved, local-uninvolved, and external-uninvolved objective experts to critique solicited and unsolicited program initiatives and products.
b. Form an outside panel for broad programmatic review/advice, potentially modeled aft er the LCA’s NTRC, that can provide critical guidance and credibility at the national/international level of expertise; this should serve as the program’s reality check.
5. Allow science to systematically analyze the initial range of all possible restoration strategies and promote scientifi c assessment of emerging alternatives.
a. Aft er science has outlined the possibilities, these alternatives can be examined in detail by all stakeholders, through politics, economics, and social and legal factors for an equitable and sustainable solution.
6. Because large-scale restoration projects must ultimately develop spatially explicit models of fundamental ecosystem processes and structure, managers should require the use of conceptual models and promote more advanced modeling.
a. Conceptual models are essential to broad understanding at all levels of science, policy, and stakeholder involvement.
Lessons Learned from Large-Scale Restoration Efforts in the USA 15
b. All restoration strategies should be developed using a basic conceptual model, whether narrative or diagrammatic.
c. Predicting ecosystem responses and quantifying the level of uncertainty associated with restoration alternatives is best served by multiple levels of numerical modeling to capture underlying ecosystem processes and “forcing factors.”
7. Invest in a rigorous, science-based defi nition and application of adaptive management.
a. Science is implicit in adaptive management, not an aft erthought of a token policy concept; adaptive management is explicit experimentation and large, ecosystem-scale restoration is by defi nition experimental.
b. Commit to intensive monitoring and evaluation of initial, “demonstration” restoration projects; increased scientifi c understanding should be the goal, rather then simply to “move dirt.”
8. Seek strong scientifi c leadership and avoid suppressing it.
a. Th e strongest programs, such as CALFED, have robust scientifi c leadership, wherein a lead scientist who is broadly respected provides guidance for the program’s science role.
b. Such a lead scientist should not be a spokesperson for management, but a communicator to management and the other sectors; this person can provide much of the important vertical integration (see #2).
9. Synthesize and disseminate scientifi c information in a manner that is timely and comprehensible to stakeholders.
a. Synthesize available information and organize it into transmittable knowledge.
b. Begin disseminating regular publications for the communication of scientifi c results to the general public.
c. Involve program scientists in outreach activities.
10. Encourage independent scientifi c collaboration and input.
a. Fund a research fellows program that supports (“post-doc”) scientists early in their careers to work within the overall program, particularly to incorporate a fresh perspective and to link academic institutions to agencies and other technically involved stakeholders such as NGOs.
b. Solicit input and presentations by scientifi c experts,
professionals, and restoration practitioners from outside the program.
c. Encourage collaboration with non-expert, local working groups.
d. Promote incorporation of social science into science teams or workgroups.
ObservationsSeveral observations that were made during the ‘lessons learned’ exercise deserve specifi c mention, but not always because they were highlighted by these restoration programs; several were most no-table for their absence in all programs. Th e four observations briefl y discussed below either frustrate present restoration eff orts—in the case of the fi rst two—or limit the full potential of optimal use of best available science in large-scale restoration eff orts—the second two. Among the programs, we did not fi nd resolution to these is-sues; however, we discuss them here because they constitute, none-theless, lessons learned by the NST.
Realistic Estimate of Required Resources and Time FrameWe found that programs are, not surprisingly, planning poorly for the numerous expensive and time-consuming unknown variables that are characteristic of ecosystem management. Politics and spe-cial interest groups still dictate the focus of most programs, which results in a distraction from program goals. With hindsight, many political distractions could have been avoided with pro-active as-sessment of the political climate and receptiveness of the public. Generally speaking, natural scientists are not good at judging the receptiveness of the public to their restoration suggestions, so per-haps this important initial task should be assigned to trained pro-fessionals. Th e method of presentation could mean the diff erence between a successful, publicly supported program and a program that the public, or select stakeholders, sabotage.
FundingScientists in several programs were frustrated by the constraints of the fi scal year budget cycle. In programs that were particularly linked to the U.S. federal budget, such as those under the USACE authority, scientists typically described their eff orts as scrimping during most of the year’s limited funding only to spend feverishly at the end of the year. In addition to being an obviously ineffi cient use of resources, this spending pattern is especially contrary to the long-term and steady funding needs of most restoration ecology studies. Alternatively, funding packages or portfolios, such as those used by CALFED, are an innovative, creative, and more effi cient approach to ensuring the long-term funding that allows scientifi c and restoration eff orts to proceed optimally.
Data ManagementDespite the NST’s lengthy consideration of a comprehensive data management system and standard policy for coordination of PSNP scientifi c and planning information, we found that none of the pro-
16 PUGET SOUND NEARSHORE PARTNERSHIP Technical Report 1
grams we surveyed highlighted data management as a prominent organizational or funding priority. Th ere was no good example of an eff ective approach to data management although all programs were generally aware of its importance. While considerable invest-ment in data management will not guarantee good science per se, a strategic approach to data management is fundamental to the ap-plication of scientifi c results and should be formulated at program onset. Good data management also provides the means to translate and widely disseminate data within and outside the program.
Social SciencesAlthough several programs mentioned the importance of incorpo-rating all scientifi c disciplines—social as well as natural sciences—into restoration eff orts, none of the programs actually involved so-cial scientists as a part of their institutional framework. Th e incor-poration of a broader, more inclusive meaning of science into our defi nition of BAS is a challenging yet worthy objective of future large-scale, ecosystem restoration eff orts where humans make up an increasing and inexorable part of the landscape.
Lessons Learned from Large-Scale Restoration Efforts in the USA 17
Adler R., S. Michele, and H. Green. 2000. Lessons from large watershed programs: A comparison of the Colorado River Basin Salinity Control Program with the San Francisco Bay-Delta Program, Central and South Florida, and the Chesapeake Bay Program. Th e National Academy of Public Administration, Center for the Economy and the Environment, Washington, D.C.
Bierbaum, R. 2002. Th e role of science in federal policy development on a regional to global scale: personal commentary. Estuaries 25:878-885.
Bisbal, G. A. 2002. Th e best available science for the management of the anadromous salmonids in the Columbia River basin. Canadian Journal of Fisheries and Aquatic Sciences 59:1952-1959.
Boesch D. F. 1999. Th e role of science in ocean governance. Ecological Economics 31:189-198.
Boesch, D. F., and S. A. Macke. 2000. Bridging the gap: what natural scientists and policymakers and implementers need to know about each other. Pages 33-48 in Improving Interactions Between Coastal Science and Policy: Proceedings of the California Symposium. National Academy Press.
CALFED (California Bay–Delta Authority). 2000. CALFED Final Programmatic EIS/EIR. California Bay–Delta Program, Sacramento, California.
CALFED (California Bay–Delta Authority). 2003a. Science program multi-year program plan. California Bay–Delta Authority.
CALFED (California Bay–Delta Authority). 2003b. CALFED independent science board summary. California Bay–Delta Authority. Available at http://science.calwater.ca.gov/sci_tools/ex_comm.shtml.
Clark W., R. Mitchell, D. Cash, F. Alcock. 2002. Information as infl uence: How institutions mediate the impact of scientifi c assessments on global environmental aff airs. John F. Kennedy School of Government, Harvard University, Cambridge, Massachusetts. 7 p.
Collin, P. 1988. Dictionary of Ecology and the Environment. Peter Collin Publishing, Great Britain. 197 p.
Douglas, P. 2000. What do policymakers and policy-implementers need from scientists? In Improving Interactions Between Coastal Science and Policy: Proceedings of the California Symposium. National Academy Press.
Dunn W. 1980. Th e two-communities metaphor and models of knowledge use. Knowledge 1:515-536.
General Accounting Offi ce. 2003. South Florida ecosystem restoration: improved science coordination needed to increase the likelihood of success. United States General Accounting Offi ce.
ReferencesGCMRC (Grand Canyon Monitoring and Research Center).
1999. Draft report: the state of the natural and cultural resources in the Colorado River ecosystem. Glen Canyon Monitoring and Research Center, Flagstaff , Arizona.
Goetz, F., C. Tanner, C. S. Simenstad, K. Fresh, T. Mumford and M. Logsdon, 2004. Guiding restoration principles. Puget Sound Nearshore Partnership Report No. 2004-03. Published by Washington Sea Grant Program, University of Washington, Seattle,Washington. Available at http://pugetsoundnearshore.org.pugetsoundnearshore.org.pugetsoundnearshore.org
Gore, A. 1992. Earth in Balance: Ecology and the Human Spirit. Hughton Miffl in, Boston. 408 p.
Hass, P. M. 1990. Saving the Mediterranean: Th e Politics of International Environmental Cooperation. Columbia University Press, New York.
Healey, M. C., and T. M. Hennessey. 1994. Th e utilization of scientifi c information in the management of estuarine ecosystems. Ocean and Coastal Management 23:167-191.
Huxham, M., and D. Sumner. 2000. Chapter 2. Science and the search for truth. Pages 33-61 in Science and Environmental Decision Making. Pearson Education Limited, Harlow, United Kingdom.
Jordan, W. R. I., M. E. Gilpin, and J. D. Aber (eds.). 1987. Restoration Ecology: A Synthetic Approach to Ecological Research. Cambridge University Press, Cambridge. 342 p.
Koehler, C., and E. Blair. 2001. Putting it back together: making ecosystem restoration work. San Francisco Bay Association.
Kvale, S. 1996. InterViews: An Introduction to Qualitative Research Interviewing. Sage Publications, London.
LCA (Louisiana Coastal Area). 2002. Louisiana coastal area ecosystem restoration: comprehensive coastwide ecosystem restoration feasibility study. U.S. Army Corps of Engineers New Orleans District, Louisiana Coastal Area Ecosystem Restoration Program.
Lee, K. N. 1993. Compass and Gyroscope: Integrating Science and Politics for the Environment. Island Press, Washington, D.C. 243 p.
Leschine, T. M., B. E. Ferriss, K. P. Bell, K. K. Bartz, S. MacWilliams, M. Pico, and A. K. Bennett. 2003. Challenges and strategies for better use of scientifi c information in the management of coastal estuaries. Estuaries 26:1189-1204.
National Academy of Sciences. 1995. Science, Policy, and the Coast: Improving Decisionmaking. National Academy Press, Washington, D.C.
National Academy of Sciences. 2000. Improving interactions between coastal science and policy. In Proceedings from the California Symposium. National Academy Press.
NRC (National Research Council). 1992. Restoration of Aquatic Ecosystems. National Academy Press, Washington, D.C.
18 PUGET SOUND NEARSHORE PARTNERSHIP Technical Report 1
NRC (National Research Council). 1999. Downstream: Adaptive Management of Glen Canyon Dam and the Colorado River Ecosystem. National Academy Press, Washington, D.C. 230 p.
Sabatier, P. A. 1988. An advocacy coalition framework of policy change and the role of policy-oriented learning therein. Policy Sciences 21:129-168.
Sabatier, P. A. 2000. Alternative models of the role of science in public policy: applications to coastal zone management. Pages 83-96 in Improving Interactions Between Coastal Science and Policy: Proceedings of the California Symposium. National Academy Press.
Soileau, R. 2002. Investigative review: institutional arrangements. United States Army Corps of Engineers, Engineering Research and Design Center.
Webber, D. 1983. Obstacles to the utilization of systematic policy analysis. Knowledge 4:534-560.
Zedler J. B. (ed.). 2001. Handbook for Restoring Tidal Wetlands. CRC Press LLC, Boca Raton, Florida.
Interview References
Applebaum S. 2003. Comprehensive Everglades Restoration Program. Phone Interview, Review of CERP program background. Seattle, Washington, November 13.
Batiuk R., D. F. Boesch C. Hershner, and K. Sellner. 2003. Chesapeake Bay Program. Personal Interview, Lessons learned meeting with Chesapeake Bay Program. Annapolis, Maryland, April 17.
Luoma, S., and Taylor K. 2002. California Bay–Delta Authority. Personal Interview, Lessons learned meeting with the California Bay-Delta Program. Seattle, Washington, December 6.
Porthouse, J. 2003. Louisiana Coastal Areas Ecosystem Restoration Program. Email Interview, Review of LCA Program Background. Seattle, Washington, September 12.
Taylor, K. 2003. California Bay–Delta Authority. Email Interview, Review of CALFED program background. Seattle, Washington, September 15.
Lessons Learned from Large-Scale Restoration Efforts in the USA 19
A. Project organizational structure and activities
1. What is the purpose of your program? What are the problems (actual or perceived) that are the focus of the program? What are the goals? Are there project milestones? How are decisions made?
2. What is the organizational structure of your program? Is there a steering committee or an NST analog? How were members at all levels selected?
3. What SPECIFIC actions have been taken as part of this program? How was it decided to take these actions? Who proposed them? Are they part of a large plan? How were they funded? Are the projects being monitored? Who is doing this monitoring?
4. Does your program review or comment on specifi c permit types of actions?
5. How does your program connect to the public? How much local “control” or input is there? What are the other players in the game in the area and how do they have input?
6. How has the program evolved/changed over time? How would you characterize today vs. the program’s start-up?
7. Did they have suites of early action projects that have been “no regrets”?
B. Restoration planning and guidance
1. Are you doing process-based restoration (vs. structure-based)? How do you defi ne “project” site in a process-based restoration scheme? Examples?
2. Is there a set of guiding ecological or science principles? How do you decide between opportunistic projects vs. strategic ecosystem restoration?
3. Is there a plan available that provides guidance? How was the plan developed? Is the plan intended to just guide your specifi c program or is there a larger-scale plan?
4. Did you develop a conceptual model or models to guide the program?
5. Did you have strategy at fi rst? Were there bad assumptions?
6. How does your program distinguish among the disparate components of science to determine what may provide useful guidance and what may not.
C. How is the system “broken?” Assessment of the causal mechanisms?
1. What are the major scientifi c uncertainties (i.e., major information needs) in the program? How were those identifi ed? What is being done about them?
2. How do you balance between theoretical long-range strategic science and short-term needs?
3. How do you narrow down lists of problems to the primary issue(s) your program will address?
D. Data management
1. How does your program handle and manage data? Do they collect and maintain their own? Is there a central database/location that all have access to?
E. External factors
1. What inputs does socio-economics have in the decision-making process?
2. What are major impediments (of all types) to attaining goals and objectives (science-based, policy-based, fi nancial impediments)?
F. Integrating science into restoration planning and assessment
1. What inputs does “science” have in the decision-making process? Is there policy or political control of science? If science was not used in selected parts of the program, which parts and why not?
2. How much of your project’s scientifi c studies could be considered “basic” science, as opposed to direct application to the project (e.g., for a better, broader understanding of ecosystem processes)?
3. What were the specifi c recommendations from the science team that helped in guiding restoration? How were recommendations used? If recommendations weren’t used, why not?
4. How was science used in the development of the restoration plan?
5. How do you “translate” science to managers/decision makers?
6. How would you recommend integrating science into large projects such as the Puget Sound Nearshore Ecosystem Study?
Appendix A: Interview Questions Lessons Learned in Large-Scale Restoration Project Efforts in the USA
General Questions for Restoration Project Planners and Scientists
20 PUGET SOUND NEARSHORE PARTNERSHIP Technical Report 1
7. How do you “update” 20-year-old (thinking) scientists?
8. How do you balance high-level science oversight (program review) vs. on-the-ground needs for design/review?
9. Is there modeling? In particular, are there scenario (e.g., eff ects of future actions) types of models that are used to help decision making?
10. How do you involve the larger local scientifi c community? Has this increased or decreased the incentive of the academic scientists involved to participate in similar investigations in the future?
11. How do you turn science into political support (i.e., “tell a story”)?
12. How were science:policy/politics confl icts resolved, if they were?
13. How did you handle multi-disciplinary work?
G. Monitoring and adaptive management
1. Is adaptive management, in the true sense of using restoration as an experiment that can be modifi ed
adaptively in response to scientifi c/technical assessment, applied in your program? If so, how? Is there an adaptive management plan? How was it developed?
2. How are you learning from early projects? Do you have the ability, mechanism, and inclination to change the program from early actions?
3. How essential is a comprehensive managing program (upfront studies vs. actions vs. monitoring, monitoring each site)?
4. How are performance measures developed and evaluated? Do you use objective metrics such as IBI, etc.?
H. Peer review
1. What has been the role of “outside” peer reviews? What types and how many of these types of reviews are there?
2. How does high-level (e.g., NAS/NRC) peer-review happen?
Lessons Learned from Large-Scale Restoration Efforts in the USA 21
Ap
pen
dix
B. P
rog
ram
Bac
kgro
un
d M
atri
x
Che
sape
ake
Bay
Prog
ram
(CBP
)C
ompr
ehen
sive
Ever
glad
es
Rest
orat
ion
Proj
ect (
CER
P)C
alifo
rnia
Bay
-Del
ta P
roje
ct
(CA
LFED
)
Gle
n C
anyo
n D
am A
dapt
ive
Man
agem
ent P
rogr
am
(GC
DA
MP)
Loui
siana
Coa
stal
A
reas
Pro
gram
(LC
A)
Puge
t Sou
nd N
ears
hore
Pa
rtne
rshi
p (P
SNER
P)
Purp
ose
To m
anag
e th
e C
hesa
peak
e Ba
y as
an
inte
grat
ed e
cosy
stem
and
to re
stor
e an
d pr
otec
t it.
To re
stor
e, p
rote
ct, a
nd
pres
erve
the
wat
er re
sour
ces
of C
entr
al a
nd S
outh
ern
Flor
ida
To im
prov
e by
, col
labo
ra-
tion
and
coop
erat
ion,
wat
er
supp
lies i
n C
alifo
rnia
and
the
heal
th o
f the
San
Fra
ncis
co
Bay–
Sacr
amen
to/S
an Jo
aqui
n Ri
ver D
elta
Wat
ersh
ed.
To m
easu
re th
e eff
ect
s of t
he
Gle
n C
anyo
n D
am (G
CD
) op
erat
ions
on
the
Col
orad
o Ri
ver (
CR)
from
GC
D to
La
ke M
ead.
To re
stor
e an
d/or
m
imic
the
natu
ral
proc
esse
s tha
t bui
lt an
d m
aint
aine
d co
asta
l Lo
uisia
na.
To id
entif
y sig
nifi c
ant e
cosy
s-To
iden
tify
signi
fi can
t eco
sys-
To id
entif
y sig
nifi c
ant e
cosy
s-To
iden
tify
signi
fi can
t eco
sys-
tem
pro
blem
s in
Was
hing
ton
tem
pro
blem
s in
Was
hing
ton
Stat
e’s P
uget
Sou
nd B
asin
, ev
alua
te p
oten
tial s
olut
ions
, an
d re
stor
e an
d pr
eser
ve c
riti-
and
rest
ore
and
pres
erve
crit
i-an
d re
stor
e an
d pr
eser
ve c
riti-
and
rest
ore
and
pres
erve
crit
i-ca
l nea
rsho
re h
abita
t.
Miss
ion
To e
valu
ate
prog
ress
in th
e C
hesa
-pe
ake
Bay
rest
orat
ion
eff o
rt; t
o m
onito
r env
ironm
enta
l con
ditio
n an
d en
viro
nmen
tal r
espo
nse
to re
stor
a-tio
n eff
ort
s; to
pro
vide
info
rmat
ion
need
ed to
est
ablis
h re
stor
atio
n go
als;
to in
form
and
invo
lve
the
publ
ic in
ac
hiev
ing
rest
orat
ion
goal
s; to
mak
e de
taile
d in
form
atio
n an
d re
fere
nce
data
for t
hese
indi
cato
rs a
vaila
ble
on
requ
est.
To p
rom
ote
a su
stai
nabl
e So
uth
Flor
ida
by re
stor
ing
the
ecos
yste
m, e
nhan
cing
w
ater
supp
lies,
and
mai
n-ta
inin
g fl o
od p
rote
ctio
n.
Dev
elop
and
impl
emen
t lo
ng-t
erm
com
preh
ensiv
e pl
an
to re
stor
e ec
olog
ical
hea
lth
and
impr
ove
wat
er m
anag
e-m
ent f
or b
enefi
cia
l use
s of t
he
Bay–
Del
ta.
To p
rovi
de c
redi
ble,
obj
ec-
tive
scie
ntifi
c in
form
atio
n to
th
e G
CD
Ada
ptiv
e M
anag
e-m
ent P
rogr
am o
n th
e eff
ect
s G
CD
ope
ratio
ns o
n th
e do
wns
trea
m re
sour
ces o
f the
C
R ec
osys
tem
, util
izin
g an
ec
osys
tem
scie
nce
appr
oach
.
Rest
ore
and
prot
ect
disa
ppea
ring
coa
stal
w
etla
nds.
Still
bei
ng d
evel
oped
.
Prob
lem
Sta
te-
men
t (c
lear
ly st
ated
, w
idel
y-ac
cept
ed
“cri
sis”?
)
Nut
rien
ts, h
abita
t los
s, to
xic
chem
i-ca
ls, o
verfi
shin
g, a
nd se
dim
ents
. Ve
ry
clea
r and
com
pelli
ng a
nd re
cogn
ized
as
a “c
risis
.”
Wat
er sh
orta
ges f
or u
rban
an
d ag
ricu
lture
and
a
dest
roye
d Ev
ergl
ades
. Pr
oble
m is
cle
ar a
nd a
wid
ely
acce
pted
“cri
sis.”
Dec
reas
ed h
ealth
of t
he B
ay.
Prob
lem
stat
emen
t som
ewha
t cl
ear.
Wid
ely
acce
pted
as a
pr
oble
m b
y a
wel
l-inf
orm
ed
publ
ic. Th
e G
CD
has
impa
cted
th
e bi
olog
ical
, cul
tura
l, an
d ph
ysic
al re
sour
ces o
f the
CR.
Pr
oble
m is
cle
ar a
nd c
ompe
l-lin
g, b
ut n
ot c
onsid
ered
a
“cri
sis.”
Coa
stal
land
loss
due
to se
d-im
ent d
iver
sions
and
coa
stal
la
nd-u
se p
ract
ices
. C
lear
an
d co
mpe
lling
“cri
sis.”
Th e
prob
lem
is a
co
mbi
natio
n of
man
y pr
oble
ms e
mer
ging
fr
om se
vera
l pla
ces.
Th e
prob
lem
stat
emen
t is s
till
Th e
prob
lem
stat
emen
t is s
till
Th e
prob
lem
stat
emen
t is s
till
Th e
prob
lem
stat
emen
t is s
till
bein
g re
fi ned
.
Goa
ls an
d O
bjec
tives
1. R
esto
re, e
nhan
ce a
nd p
rote
ct li
ving
re
sour
ces,
thei
r hab
itats
, and
eco
logi
-ca
l rel
atio
nshi
ps to
sust
ain
all fi
sher
ies
and
prov
ide
for a
bal
ance
d ec
osys
tem
. 2.
Pre
serv
e, p
rote
ct, a
nd re
stor
e th
ose
habi
tats
and
nat
ural
are
as th
at a
re
vita
l to
the
surv
ival
and
div
ersit
y of
th
e liv
ing
reso
urce
s of t
he B
ay/t
ribu
-ta
ries
. 3.
Ach
ieve
and
mai
ntai
n th
e w
ater
qua
lity
nece
ssar
y to
supp
ort t
he
aqua
tic li
ving
reso
urce
s and
to p
rote
ct
hum
an h
ealth
. 4.
Dev
elop
, pro
mot
e,
and
achi
eve
soun
d la
nd-u
se p
ract
ices
th
at p
rote
ct a
nd re
stor
e re
sour
ces a
nd
wat
er q
ualit
y an
d m
aint
ain
redu
ced
pollu
tant
load
ings
. 5. P
rom
ote
indi
vidu
al st
ewar
dshi
p an
d as
sist
indi
vidu
als,
orga
niza
tions
, bus
ines
ses,
loca
l gov
ernm
ents
, and
scho
ols t
o un
-de
rtak
e in
itiat
ives
to a
chie
ve th
e go
als
and
com
mitm
ents
of t
his a
gree
men
t.
Th e
over
arch
ing
obje
ctiv
e of
th
e Pl
an is
the
rest
orat
ion,
pr
eser
vatio
n, a
nd p
rote
ctio
n of
the
Sout
h Fl
orid
a ec
o-sy
stem
whi
le p
rovi
ding
for
othe
r wat
er-r
elat
ed n
eeds
of
the
regi
on, i
nclu
ding
wat
er
supp
ly a
nd fl
ood
prot
ectio
n.
Th e
goal
s are
to e
nhan
ce
ecol
ogic
al v
alue
s and
en
hanc
e ec
onom
ic v
alue
s an
d so
cial
wel
l-bei
ng.
Th es
e go
als w
ill b
e ac
com
plish
ed
by d
eliv
erin
g th
e ri
ght
amou
nt o
f wat
er, o
f the
righ
t qu
ality
, to
the
righ
t pla
ces,
and
at th
e ri
ght t
ime.
Impr
ove
and
incr
ease
aqu
atic
an
d te
rres
tria
l hab
itats
and
im
prov
e ec
olog
ical
func
tions
in
the
Bay–
Del
ta to
supp
ort
sust
aina
ble
popu
latio
ns o
f di
vers
e an
d va
luab
le p
lant
and
an
imal
spec
ies;
redu
ce th
e m
ismat
ch b
etw
een
Bay–
Del
ta
wat
er su
pplie
s and
cur
rent
an
d pr
ojec
ted
bene
fi cia
l use
s de
pend
ent o
n th
e Ba
y–D
elta
sy
stem
; red
uce
the
risk
to la
nd
use
and
asso
ciat
ed e
cono
mic
ac
tiviti
es, w
ater
supp
ly, in
fra-
stru
ctur
e, a
nd th
e ec
osys
tem
fr
om c
atas
trop
hic
brea
chin
g of
D
elta
leve
es.
Obj
ectiv
es a
re to
im
prov
e w
ater
qua
lity,
ecos
ys-
tem
qua
lity,
and
wat
er su
pply,
an
d to
dec
reas
e vu
lner
abili
ty o
f D
elta
func
tions
.
Th e
goal
s of t
he G
CM
RC a
re
to d
evel
op m
onito
ring
and
re
sear
ch p
rogr
ams a
nd re
-la
ted
scie
ntifi
c ac
tiviti
es th
at
eval
uate
shor
t- a
nd lo
ng-
term
impa
cts o
f the
GC
D o
n th
e bi
olog
ical
, cul
tura
l, an
d ph
ysic
al re
sour
ces o
f the
CR
ecos
yste
m.
Th e
goal
is a
lso
to p
rovi
de le
ader
ship
to a
c-co
mpl
ish a
free
-fl ow
ing
CR.
Obj
ectiv
es a
re to
id
entif
y an
d ex
plor
e lo
ng-r
ange
, lar
ge-s
cale
ec
osys
tem
rest
orat
ion
stra
tegi
es to
rest
ore
and
prot
ect c
oast
al
Loui
siana
and
to su
s-ta
in c
oast
al e
cosy
stem
s th
at su
ppor
t and
pro
-te
ct th
e en
viro
nmen
t, ec
onom
y, an
d cu
lture
of
sout
hern
Lou
isian
a,
and
that
con
trib
ute
grea
tly to
the
econ
omy
and
wel
l-bei
ng o
f the
na
tion.
Prel
imin
ary
goal
s are
to 1
. re
habi
litat
e ec
osys
tem
nat
ural
re
habi
litat
e ec
osys
tem
nat
ural
re
habi
litat
e ec
osys
tem
nat
ural
re
habi
litat
e ec
osys
tem
nat
ural
pr
oces
ses,
2. p
rote
ct a
nd/o
r re
stor
e fu
nctio
nal h
abita
t ty
pes i
n Pu
get S
ound
, 3.
prev
ent f
utur
e lis
tings
and
ac
hiev
e re
cove
ry o
f at-
risk
na
tive
spec
ies,
4. p
reve
nt
the
esta
blish
men
t of a
d-di
tiona
l non
-nat
ive
spec
ies,
5. im
prov
e an
d/or
mai
ntai
n w
ater
and
sedi
men
t qua
lity
cond
ition
s, an
d 6.
incr
ease
the
cond
ition
s, an
d 6.
incr
ease
the
cond
ition
s, an
d 6.
incr
ease
the
cond
ition
s, an
d 6.
incr
ease
the
unde
rsta
ndin
g of
the
natu
ral
proc
esse
s and
func
tions
of t
he
proc
esse
s and
func
tions
of t
he
proc
esse
s and
func
tions
of t
he
proc
esse
s and
func
tions
of t
he
Puge
t Sou
nd.
22 PUGET SOUND NEARSHORE PARTNERSHIP Technical Report 1
App
endi
x B.
Pro
gram
Bac
kgro
und
Mat
rix
(con
t.)
Che
sape
ake
Bay
Prog
ram
(CBP
)C
ompr
ehen
sive
Ever
glad
es
Rest
orat
ion
Proj
ect (
CER
P)C
alifo
rnia
Bay
-Del
ta P
roje
ct
(CA
LFED
)
Gle
n C
anyo
n D
am A
dapt
ive
Man
agem
ent P
rogr
am
(GC
DA
MP)
Loui
siana
Coa
stal
A
reas
Pro
gram
(LC
A)
Puge
t Sou
nd N
ears
hore
Pa
rtne
rshi
p (P
SNER
P)
Year
of P
rogr
am
Form
atio
n19
8319
9219
9419
9619
9920
01
Form
atio
n Pr
oces
sC
itize
n-m
otiv
ated
Fede
ral/s
tate
-mot
ivat
edFe
dera
l/sta
te- a
nd c
itize
n-m
o-tiv
ated
Gra
ssro
ots-
mot
ivat
edFe
dera
l/sta
te-m
oti-
vate
dFe
dera
l/sta
te-m
otiv
ated
Evol
utio
n sin
ce
Form
atio
nEv
olve
d fr
om w
ater
qua
lity/
eutr
ophi
-ca
tion
focu
s to
fi she
ries
and
hab
itat.
Unk
now
n A
utho
rity
adde
d in
200
2Ve
ry li
ttle
Brea
ux A
ct a
ctiv
ities
le
ad to
pro
cess
-bas
ed
rest
orat
ion.
Unk
now
n
Geo
grap
hic
Scop
eTh
e C
B w
ater
shed
is o
ver 1
66,0
00
km2 .
Th e
targ
et a
rea
in S
outh
ern
FL is
47,
000
km2 .
Th e
Bay-
Del
ta a
rea
is 3,
000
km2 .
From
the
fore
bay
of L
ake
Pow
ell t
o th
e w
este
rn
boun
dary
of G
rand
Can
yon
Nat
iona
l Par
k (2
93 ri
ver
mile
s or 4
73 k
m).
Th e
entir
e Lo
uisia
na
coas
t fro
m M
S to
TX
.4,
000
km o
f sho
relin
e m
ultip
lied
by th
e w
idth
of n
ears
hore
.
URL
http
://w
ww.
ches
apea
keba
y.net
http
://w
ww.
ever
glad
espl
an.
org/
http
://ca
lwat
er.c
a.go
v/ht
tp://
ww
w.gc
mrc
.gov
/ht
tp://
ww
w.co
ast2
050.
gov/
lca.
htm
http
://pu
gets
ound
near
shor
e.or
g
Lessons Learned from Large-Scale Restoration Efforts in the USA 23
Ap
pen
dix
C. P
rog
ram
Co
mp
aris
on
Mat
rix
Che
sape
ake
Bay
Prog
ram
(C
BP)
Com
preh
ensiv
e Ev
ergl
ades
Re
stor
atio
n Pr
ojec
t (C
ERP)
Cal
iforn
ia B
ay-D
elta
Pro
ject
(C
ALF
ED)
Gle
n C
anyo
n D
am A
dapt
ive
Man
agem
ent P
rogr
am (G
CA
MP)
Loui
siana
Coa
stal
Are
as P
rogr
am (L
CA
)
Is th
ere
a sc
ienc
e te
am?
Con
cent
rate
d on
STA
C,
but a
lso o
ccur
s on
sub-
com
mitt
ees.
Th e
REC
OV
ER te
am is
the
or-
gani
zatio
nal c
ente
r of s
cien
ce,
but s
cien
ce a
lso o
ccur
s and
is
repr
esen
ted
on a
ll pr
ojec
t de
liver
y te
ams.
Scie
nce
is in
tegr
ated
thro
ugho
ut th
e pr
ogra
m b
ut th
e ER
P’s S
cien
ce B
oard
pr
ovid
es th
e m
ost d
irect
scie
ntifi
c gu
id-
ance
to re
stor
atio
n.
Ada
ptiv
e M
anag
emen
t Wor
k G
roup
Disp
erse
d th
roug
hout
the
proj
ect,
but
Disp
erse
d th
roug
hout
the
proj
ect,
but
Disp
erse
d th
roug
hout
the
proj
ect,
but
Disp
erse
d th
roug
hout
the
proj
ect,
but
the
only
gro
up o
f sci
entis
ts is
org
aniz
ed
the
only
gro
up o
f sci
entis
ts is
org
aniz
ed
the
only
gro
up o
f sci
entis
ts is
org
aniz
ed
the
only
gro
up o
f sci
entis
ts is
org
aniz
ed
sole
ly u
nder
the
mod
elin
g ro
le a
nd o
ther
so
lely
und
er th
e m
odel
ing
role
and
oth
er
sole
ly u
nder
the
mod
elin
g ro
le a
nd o
ther
so
lely
und
er th
e m
odel
ing
role
and
oth
er
sole
ly u
nder
the
mod
elin
g ro
le a
nd o
ther
so
lely
und
er th
e m
odel
ing
role
and
oth
er
sole
ly u
nder
the
mod
elin
g ro
le a
nd o
ther
sp
ecifi
c ta
sks.
Th e
NTR
C re
view
s and
sp
ecifi
c ta
sks.
Th e
NTR
C re
view
s and
sp
ecifi
c ta
sks.
Th e
NTR
C re
view
s and
sp
ecifi
c ta
sks.
Th e
NTR
C re
view
s and
ad
vise
s.
If sc
ienc
e is
dis
pers
ed
thro
ugho
ut th
e pr
ojec
t, is
ther
e a
‘scie
ntifi
c he
ad-
quar
ters
’?
Form
ed in
199
4, ra
ther
la
te in
the
proc
ess.
STA
C
is th
e sc
ient
ifi c
“hea
d-qu
arte
rs.”
REC
OV
ER is
the
“hea
dqua
r-te
rs.”
It w
as fo
rmed
in 1
999.
Sc
ienc
e is
also
disp
erse
d on
all
proj
ect d
eliv
ery
team
s.
Th e
ERP
Scie
nce
Boar
d em
erge
d ve
ry
early
. Th e
Sci
ence
Pro
gram
is le
d by
th
e Ex
ecut
ive
Scie
nce
Boar
d, a
pan
el o
f ex
pert
s nom
inat
ed b
y th
e Sc
ienc
e Pr
o-gr
am le
ad a
nd a
ppro
ved
by th
e A
utho
r-ity
, but
this
deve
lopm
ent c
ame
late
r.
Scie
nce
mak
es u
p th
e m
ajor
ity
of th
e pr
ogra
m.
Th e
AM
WG
is a
fo
cus o
f sci
entifi
c a
ctiv
ity.
Scie
nce
was
not
em
brac
ed u
ntil
late
r in
Scie
nce
was
not
em
brac
ed u
ntil
late
r in
Scie
nce
was
not
em
brac
ed u
ntil
late
r in
Scie
nce
was
not
em
brac
ed u
ntil
late
r in
the
prog
ram
and
is p
layi
ng c
atch
-up.
th
e pr
ogra
m a
nd is
pla
ying
cat
ch-u
p.
the
prog
ram
and
is p
layi
ng c
atch
-up.
th
e pr
ogra
m a
nd is
pla
ying
cat
ch-u
p.
Th e
NTR
C a
lso c
ame
into
the
proc
ess
Th e
NTR
C a
lso c
ame
into
the
proc
ess
Th e
NTR
C a
lso c
ame
into
the
proc
ess
Th e
NTR
C a
lso c
ame
into
the
proc
ess
late
, aft e
r man
y of
the
scie
nce
deci
sions
la
te, a
ft er m
any
of th
e sc
ienc
e de
cisio
ns
late
, aft e
r man
y of
the
scie
nce
deci
sions
la
te, a
ft er m
any
of th
e sc
ienc
e de
cisio
ns
wer
e al
read
y fo
rmul
ated
.
Scie
nce
team
/com
mitt
ee
mem
ber s
elec
tion
proc
ess
App
oint
ed a
nd re
com
-m
ende
dTh
e le
ader
ship
team
of
REC
OV
ER is
app
oint
ed b
y re
pres
ente
d ag
enci
es.
Th e
mem
bers
hip
of th
e ot
her 6
te
ams i
s ad
hoc
(who
ever
is
inte
rest
ed).
Reco
mm
ende
dG
over
nmen
tal a
genc
y re
pres
enta
-tio
nSc
ienc
e te
am m
ake
up c
ame
out o
f Ro
bert
Tw
iley’s
wor
k.
Is sc
ienc
e so
licite
d us
ing
mor
e of
a “
top-
dow
n” o
r a
“bot
tom
-up”
app
roac
h?
Botto
m-u
pTo
p-do
wn
Botto
m-u
p RF
P ap
proa
ch (s
till l
acki
ng
feed
back
and
gui
danc
e fr
om sc
ienc
e).
Top-
dow
nTo
p-do
wn
prog
ram
mat
ic a
ppro
ach
(205
0 pr
opos
es a
top-
dow
n ap
proa
ch,
(205
0 pr
opos
es a
top-
dow
n ap
proa
ch,
(205
0 pr
opos
es a
top-
dow
n ap
proa
ch,
(205
0 pr
opos
es a
top-
dow
n ap
proa
ch,
but p
revi
ous p
roje
cts u
nder
CW
PPRA
bu
t pre
viou
s pro
ject
s und
er C
WPP
RA
but p
revi
ous p
roje
cts u
nder
CW
PPRA
bu
t pre
viou
s pro
ject
s und
er C
WPP
RA
wer
e m
ore
botto
m-u
p).
Who
mak
es p
rogr
am d
eci-
sion
s? S
ee o
rgan
izat
iona
l ch
arts
in A
ppen
dix
1.
Exec
utiv
eTh
e Pr
ojec
t Man
ager
s who
re
pres
ent t
he C
orps
of
Engi
neer
s and
S. F
L W
ater
M
anag
emen
t Dist
rict
.
Th e
Aut
horit
y, w
hich
is a
dvis
ed d
irect
ly
by th
e Ex
ecut
ive
Scie
nce
Boar
d.U
nkno
wn
Mad
e at
the
Vert
ical
Inte
grat
ion
Team
or
Mad
e at
the
Vert
ical
Inte
grat
ion
Team
or
Mad
e at
the
Vert
ical
Inte
grat
ion
Team
or
Mad
e at
the
Vert
ical
Inte
grat
ion
Team
or
Mad
e at
the
Vert
ical
Inte
grat
ion
Team
or
Mad
e at
the
Vert
ical
Inte
grat
ion
Team
or
Mad
e at
the
Vert
ical
Inte
grat
ion
Team
or
Exec
utiv
e C
omm
ittee
leve
l
Org
aniz
atio
nal e
volu
tion/
chan
ge o
ver t
ime
rega
rd-
ing
scie
nce
Incr
easin
g ro
le o
f ac
adem
ic a
nd o
ther
no
n-ag
ency
scie
ntist
s in
prog
ram
.
Th e
Scie
nce
Coo
rdin
atio
n Te
am w
as in
volv
ed d
urin
g th
e Re
stud
y, bu
t has
sinc
e be
en
disb
ande
d.
Alth
ough
Sci
ence
Pro
gram
cam
e la
te, i
t ha
s refi
ned
the
mec
hani
sms f
or sc
ienc
e in
the
prog
ram
.
Th e
prog
ram
has
gro
wn
to in
clud
e m
ore
disc
iplin
es th
an ju
st sc
ienc
e.Si
nce
the
feas
ibili
ty re
port
, an
expl
icit
Sinc
e th
e fe
asib
ility
repo
rt, a
n ex
plic
it Si
nce
the
feas
ibili
ty re
port
, an
expl
icit
Sinc
e th
e fe
asib
ility
repo
rt, a
n ex
plic
it Sc
ienc
e Pl
an d
irect
s the
evo
lutio
n of
the
Scie
nce
Plan
dire
cts t
he e
volu
tion
of th
e Sc
ienc
e Pl
an d
irect
s the
evo
lutio
n of
the
Scie
nce
Plan
dire
cts t
he e
volu
tion
of th
e sc
ienc
e as
app
lied
to re
stor
atio
n.
Issu
es/p
robl
ems e
ncou
n-te
red
Cha
ngin
g pr
ogra
m
stru
ctur
e an
d pu
rpos
e w
as m
ore
diffi
cult
than
an
ticip
ated
.
Th is
prog
ram
was
fi xe
d be
fore
sc
ienc
e w
as b
roug
ht in
, thu
s sc
ienc
e w
as c
onfi n
ed to
wor
k w
ithin
the
alre
ady
fi xed
rang
e of
alte
rnat
ives
. Cre
ativ
ity w
as
limite
d an
d op
tions
oth
er
than
“rep
lum
bing
” wer
e no
t co
nsid
ered
.
Con
trac
ting
(bet
wee
n st
ate
and
fede
ral
agen
cies
ove
r ter
ms,
data
righ
ts, a
nd
confl
icts
of i
nter
est)
and
fi sc
al is
sues
(1
). So
me
of th
e sc
ienc
e iss
ues a
re
extr
emel
y ch
alle
ngin
g.
It’s b
een
very
(pol
itica
lly) d
iffi c
ult
to ru
n a
seco
nd e
xper
imen
tal fl
ood
.St
rong
pol
itica
l pre
ssur
e fo
r inc
lusio
n of
St
rong
pol
itica
l pre
ssur
e fo
r inc
lusio
n of
St
rong
pol
itica
l pre
ssur
e fo
r inc
lusio
n of
St
rong
pol
itica
l pre
ssur
e fo
r inc
lusio
n of
St
rong
pol
itica
l pre
ssur
e fo
r inc
lusio
n of
so
me
rest
orat
ion
actio
ns a
nd m
etho
ds
som
e re
stor
atio
n ac
tions
and
met
hods
so
me
rest
orat
ion
actio
ns a
nd m
etho
ds
som
e re
stor
atio
n ac
tions
and
met
hods
th
at a
re n
ot st
rong
ly su
ppor
ted
by sc
i-th
at a
re n
ot st
rong
ly su
ppor
ted
by sc
i-th
at a
re n
ot st
rong
ly su
ppor
ted
by sc
i-th
at a
re n
ot st
rong
ly su
ppor
ted
by sc
i-en
ce.
For e
xam
ple,
a la
wsu
it by
oys
ter
ence
. Fo
r exa
mpl
e, a
law
suit
by o
yste
r en
ce.
For e
xam
ple,
a la
wsu
it by
oys
ter
ence
. Fo
r exa
mpl
e, a
law
suit
by o
yste
r gr
ower
s aga
inst
the
Stat
e, fo
r dam
ages
gr
ower
s aga
inst
the
Stat
e, fo
r dam
ages
gr
ower
s aga
inst
the
Stat
e, fo
r dam
ages
gr
ower
s aga
inst
the
Stat
e, fo
r dam
ages
du
e to
rest
orat
ion
actio
n, in
one
regi
on
due
to re
stor
atio
n ac
tion,
in o
ne re
gion
du
e to
rest
orat
ion
actio
n, in
one
regi
on
due
to re
stor
atio
n ac
tion,
in o
ne re
gion
se
vere
ly re
duce
d te
chni
cal o
ptio
ns c
on-
seve
rely
redu
ced
tech
nica
l opt
ions
con
-se
vere
ly re
duce
d te
chni
cal o
ptio
ns c
on-
seve
rely
redu
ced
tech
nica
l opt
ions
con
-sid
ered
in th
at re
gion
, des
pite
scie
ntifi
c sid
ered
in th
at re
gion
, des
pite
scie
ntifi
c sid
ered
in th
at re
gion
, des
pite
scie
ntifi
c sid
ered
in th
at re
gion
, des
pite
scie
ntifi
c ev
iden
ce su
ppor
ting
thos
e re
stor
atio
n ev
iden
ce su
ppor
ting
thos
e re
stor
atio
n ev
iden
ce su
ppor
ting
thos
e re
stor
atio
n ev
iden
ce su
ppor
ting
thos
e re
stor
atio
n op
tions
.
How
is sc
ienc
e in
tegr
ated
in
to th
e re
st o
f the
pro
-gr
am, i
f it i
s?
No
dire
cted
inte
grat
ion;
ve
ry b
otto
m-u
p in
this
resp
ect?
Scie
nce
is no
t alw
ays w
ell i
n-te
grat
ed a
lthou
gh th
e at
tem
pt
is m
ade
by h
avin
g sc
ienc
e re
pres
ente
d on
all
proj
ect
deliv
ery
team
s.
Scie
nce
prov
ides
inpu
t to
all l
evel
s of
the
orga
niza
tiona
l str
uctu
re.
Pred
omin
antly
a sc
ienc
e-ba
sed
prog
ram
, so
stro
ng v
ertic
al a
nd
hori
zont
al in
tegr
atio
n.
LCA’
s ver
tical
inte
grat
ion
team
was
an
LCA’
s ver
tical
inte
grat
ion
team
was
an
LCA’
s ver
tical
inte
grat
ion
team
was
an
LCA’
s ver
tical
inte
grat
ion
team
was
an
inno
vativ
e ap
proa
ch to
coo
rdin
atin
g in
nova
tive
appr
oach
to c
oord
inat
ing
inno
vativ
e ap
proa
ch to
coo
rdin
atin
g in
nova
tive
appr
oach
to c
oord
inat
ing
rest
orat
ion
play
ers.
How
ever
, in
gene
ral
rest
orat
ion
play
ers.
How
ever
, in
gene
ral
rest
orat
ion
play
ers.
How
ever
, in
gene
ral
rest
orat
ion
play
ers.
How
ever
, in
gene
ral
rest
orat
ion
play
ers.
How
ever
, in
gene
ral
scie
nce
has n
ot b
een
wel
l int
egra
ted.
scie
nce
has n
ot b
een
wel
l int
egra
ted.
scie
nce
has n
ot b
een
wel
l int
egra
ted.
scie
nce
has n
ot b
een
wel
l int
egra
ted.
Science within the Organizational Structure
24 PUGET SOUND NEARSHORE PARTNERSHIP Technical Report 1
App
endi
x C
. Pro
gram
Com
pari
son
Mat
rix
(con
t.)
Che
sape
ake
Bay
Prog
ram
(C
BP)
Com
preh
ensiv
e Ev
ergl
ades
Re
stor
atio
n Pr
ojec
t (C
ERP)
Cal
iforn
ia B
ay-D
elta
Pro
ject
(C
ALF
ED)
Gle
n C
anyo
n D
am A
dapt
ive
Man
agem
ent P
rogr
am (G
CA
MP)
Loui
siana
Coa
stal
Are
as P
rogr
am
(LC
A)
Is sc
ienc
e fr
om o
utsid
e th
e pr
ogra
m in
tegr
ated
with
sc
ienc
e w
ithin
the
prog
ram
(i.
e., i
s the
re c
olla
bora
tion
with
a re
sear
ch c
onso
rtiu
m)?
Yes,
this
is ai
ded
by
inte
ract
ions
with
the
Che
sape
ake
Rese
arch
C
onso
rtiu
m, I
nc.
No,
CER
P is
isol
ated
from
ac
adem
ic a
nd o
utsid
e sc
ienc
e.
Out
side
scie
nce
is on
ly in
cor-
pora
ted
thro
ugh
agen
cy c
on-
tact
and
thro
ugh
som
e re
latio
n be
twee
n lo
cal u
nive
rsiti
es a
nd
the
S. F
L W
ater
Mgm
t. D
ist.
Yes,
they
hav
e es
tabl
ished
a re
sear
ch
cons
ortiu
m.
In a
dditi
on, t
he C
AL-
FED
Sci
ence
Con
fere
nce
is a
very
eff
ect
ive
mec
hani
sm to
invo
lve
the
broa
der s
cien
tifi c
com
mun
ity.
To so
me
degr
ee; U
SGS
prom
otes
co
llabo
ratio
n.N
o ou
tsid
e sc
ient
ifi c
invo
lvem
ent a
t thi
s N
o ou
tsid
e sc
ient
ifi c
invo
lvem
ent a
t thi
s N
o ou
tsid
e sc
ient
ifi c
invo
lvem
ent a
t thi
s N
o ou
tsid
e sc
ient
ifi c
invo
lvem
ent a
t thi
s st
age.
A c
onso
rtiu
m is
han
dlin
g m
uch
of
stag
e. A
con
sort
ium
is h
andl
ing
muc
h of
st
age.
A c
onso
rtiu
m is
han
dlin
g m
uch
of
stag
e. A
con
sort
ium
is h
andl
ing
muc
h of
th
e te
chni
cal s
cien
ce (e
.g.,
hydr
odyn
am-
the
tech
nica
l sci
ence
(e.g
., hy
drod
ynam
-th
e te
chni
cal s
cien
ce (e
.g.,
hydr
odyn
am-
the
tech
nica
l sci
ence
(e.g
., hy
drod
ynam
-ic
mod
elin
g) b
ut t
his
is a
fund
amen
tal
ic m
odel
ing)
but
thi
s is
a fu
ndam
enta
l ic
mod
elin
g) b
ut t
his
is a
fund
amen
tal
ic m
odel
ing)
but
thi
s is
a fu
ndam
enta
l pr
ogra
m c
ompo
nent
. Th u
s fa
r, th
ere
are
prog
ram
com
pone
nt. Th
us
far,
ther
e ar
e pr
ogra
m c
ompo
nent
. Th u
s fa
r, th
ere
are
prog
ram
com
pone
nt. Th
us
far,
ther
e ar
e fe
w f
orm
al m
echa
nism
s fo
r in
put
from
fe
w f
orm
al m
echa
nism
s fo
r in
put
from
fe
w f
orm
al m
echa
nism
s fo
r in
put
from
fe
w f
orm
al m
echa
nism
s fo
r in
put
from
ou
tsid
e th
e pr
ogra
m.
Is sc
ienc
e in
depe
nden
t fro
m
polic
y?Ye
sM
ostly
. Th
ere
is a
conc
erte
d eff
ort
to se
para
te th
e tw
o.Ye
s; sc
ienc
e is
aski
ng a
nd ra
ising
dif-
fi cul
t que
stio
ns.
Yes,
if yo
u co
nsid
er re
mov
al o
f the
da
m n
ot a
n op
tion.
No
Doe
s the
scie
nce
have
sup-
port
ive
staff
?So
mew
hat.
Sci
ence
fel-
low
s also
pla
y th
is ro
le.
Th e
only
staff
is t
hat p
rovi
ded
by th
e sc
ient
ist’s
agen
cy.
Yes;
they
pro
vide
it th
roug
h co
ntra
c-to
rs.
Unk
now
nO
nly
as p
art o
f sci
entifi
c ta
sks.
Th e
NTR
C is
pro
vide
d no
staff
.
Is th
ere
a w
ay to
invo
lve
fres
h sc
ient
ifi c
pers
pect
ives
?Ye
s: sc
ienc
e, o
r res
earc
h fe
llow
sN
o fo
rmal
way
. Th
ere
is pl
enty
of t
urno
ver a
nd fr
esh
pers
pect
ive
does
not
nee
d to
be
solic
ited.
Th is
is an
art
icul
ated
futu
re g
oal f
or
the
next
few
yea
rs (1
, p4)
.N
oN
o, b
ut p
ropo
sed
Scie
nce
Plan
pro
vide
s N
o, b
ut p
ropo
sed
Scie
nce
Plan
pro
vide
s N
o, b
ut p
ropo
sed
Scie
nce
Plan
pro
vide
s N
o, b
ut p
ropo
sed
Scie
nce
Plan
pro
vide
s fo
r tha
t.
Was
ther
e an
obv
ious
and
ag
reed
-upo
n pr
oble
m?
Yes,
the
heal
th o
f the
Bay
w
as th
e pr
oble
m, b
ut th
e ca
use
was
mor
e di
ffi cu
lt to
und
erst
and.
Yes,
the
loss
of t
he E
verg
lade
s an
d w
ater
shor
tage
s/pr
oble
ms.
Yes,
wat
er q
uant
ity a
nd q
ualit
y iss
ues
as w
ell a
s eco
syst
em d
egra
datio
n/ha
bita
t los
s.
Th e
dam
was
obv
ious
, but
it w
asn’
t an
agr
eed-
upon
pro
blem
save
for
the
ecos
yste
m.
Yes,
it w
as u
nive
rsal
ly a
gree
d th
at la
nd
loss
was
the
prob
lem
with
seve
ral c
ausa
l lo
ss w
as th
e pr
oble
m w
ith se
vera
l cau
sal
loss
was
the
prob
lem
with
seve
ral c
ausa
l lo
ss w
as th
e pr
oble
m w
ith se
vera
l cau
sal
fact
ors b
ehin
d it.
How
wer
e in
form
atio
n ga
ps/n
eeds
in th
e pr
ogra
m
iden
tifi e
d?
Publ
ic o
pini
on is
infl u
-en
tial.
By a
larg
e “b
rain
dum
p” in
the
‘80s
. Th
is be
cam
e th
e C
orps
pr
ojec
t.
Th ro
ugh
issue
-foc
used
wor
ksho
ps
supp
orte
d by
bot
h th
e ER
P an
d Sc
i-en
ce P
rogr
am; e
xplic
it pr
oduc
ts h
ave
been
pro
duce
d by
thes
e w
orks
hops
.
Unk
now
nId
entifi
ed
by sc
ient
ists.
How
do
you
iden
tify
issue
(s)
to a
ddre
ss fr
om li
st o
f pr
oble
ms?
Scie
nce
and
tech
nica
l ex
pert
s mos
tly id
entif
y iss
ues.
From
CER
P’s s
cien
ce p
lan
and
from
risk
s and
unc
erta
inty
id
entifi
ed
from
pro
ject
s. S
ome
scie
nce
need
s also
com
e fr
om
outs
ide
of C
ERP.
CA
LFED
did
an
espe
cial
ly g
ood
job
iden
tifyi
ng n
umer
ous a
ctio
ns to
ad-
dres
s pro
blem
s tha
t cou
ld w
ork,
but
is
only
now
in th
e pr
oces
s of s
ettin
g pr
iorit
ies.
A c
once
ptua
l mod
el in
ea
ch E
RP p
ropo
sal a
lso fa
cilit
ates
th
at p
roce
ss.
Scie
nce
iden
tifi e
s iss
ues.
Man
agem
ent i
nteg
ratio
n of
com
bina
-tio
n of
scie
ntifi
c ad
vice
and
stak
ehol
der
tion
of sc
ient
ifi c
advi
ce a
nd st
akeh
olde
r tio
n of
scie
ntifi
c ad
vice
and
stak
ehol
der
inpu
t, bu
t tha
t has
evo
lved
from
thin
k-in
g ab
out t
he p
robl
ems a
t the
loca
l sca
le
ing
abou
t the
pro
blem
s at t
he lo
cal s
cale
in
g ab
out t
he p
robl
ems a
t the
loca
l sca
le
ing
abou
t the
pro
blem
s at t
he lo
cal s
cale
to
the
syst
em sc
ale.
Was
ther
e a
larg
e ba
se o
f ex-
istin
g sc
ient
ifi c
know
ledg
e?Ye
sYe
sYe
sN
ot a
s muc
h.Ye
s
Wha
t inp
uts d
oes “
scie
nce”
ha
ve in
the
deci
sion
mak
ing
proc
ess?
Inpu
t is t
rans
mitt
ed
thro
ugh
repo
rts.
Scie
nce
cont
ribu
tes p
rim
ar-
ily v
ia p
rodu
cts d
eliv
ered
to
prog
ram
man
agem
ent.
Exec
utiv
e Sc
ienc
e Bo
ard
advi
ses t
he
Aut
horit
y.Fo
rmul
atio
n of
exp
erim
ents
for
adap
tive
man
agem
ent (
wat
er re
-le
ases
) and
inte
rpre
tatio
n fo
r wat
er
regu
latio
n.
Th e
advi
ce o
f the
scie
nce
and
tech
nica
l ex
pert
s is s
eldo
m h
eard
by
the
publ
ic o
r ex
pert
s is s
eldo
m h
eard
by
the
publ
ic o
r ex
pert
s is s
eldo
m h
eard
by
the
publ
ic o
r ex
pert
s is s
eldo
m h
eard
by
the
publ
ic o
r ev
en th
e PM
s.
Whe
n di
d sc
ienc
e be
gin
play
ing
a ro
le in
dec
ision
-m
akin
g?
Late
From
the
begi
nnin
gTh
e Ex
ecut
ive
Scie
nce
Boar
d fo
rmed
la
te (i
n 20
00),
but t
here
was
alw
ays
scie
nce
infu
sed
in th
e pr
ogra
m.
From
the
begi
nnin
gSt
ill fi
ghtin
g to
bri
ng sc
ienc
e in
to th
e pr
ogra
m.
Wha
t is t
he so
urce
of s
cien
ce
used
?M
ostly
aca
dem
ic a
nd
agen
cy.
Som
e in
de-
pend
ent (
i.e. c
onsu
lting
fi r
ms)
.
Mos
t sci
ence
is a
genc
y sc
ienc
e,
eith
er e
xist
ing
or g
ener
-at
ed fr
om w
ithin
CER
P.
Peer
-rev
iew
ed a
genc
y sc
ienc
e an
d pu
blish
ed p
eer-
revi
ewed
lit
erat
ure.
Th e
scie
nce
agen
da is
det
erm
ined
pa
rtly
by
man
agem
ent a
nd st
ake-
hold
er q
uest
ions
and
par
tly b
y sc
ient
ifi c
char
ge o
f the
pro
gram
’s go
als a
nd o
bjec
tives
(1).
Pred
omin
antly
scie
nce
agen
cy
(USG
S) a
nd a
cade
mic
Th e
Cor
ps b
roug
ht sp
ecifi
cally
sele
cted
sc
ient
ists t
o re
view
the
prod
uct,
raisi
ng
cred
ibili
ty is
sues
. La
te in
the
deve
lop-
men
t of r
esto
ratio
n op
tions
, the
Sta
te
brou
ght i
n ac
adem
ic sc
ient
ists t
o pr
ovid
e cr
itica
l inp
ut.
Science within the Organizational Structure (cont.) Diagnosis of Problem and Causal Mechanisms Role of Science in Restoration Planning and Action Role of Science in Restoration Planning and Action Role of Science in Restoration Planning and Action
Lessons Learned from Large-Scale Restoration Efforts in the USA 25
App
endi
x C
. Pro
gram
Com
pari
son
Mat
rix
(con
t.)
Che
sape
ake
Bay
Prog
ram
(C
BP)
Com
preh
ensiv
e Ev
ergl
ades
Re
stor
atio
n Pr
ojec
t (C
ERP)
Cal
iforn
ia B
ay-D
elta
Pro
ject
(C
ALF
ED)
Gle
n C
anyo
n D
am A
dapt
ive
Man
agem
ent P
rogr
am (G
CA
MP)
Loui
siana
Coa
stal
Are
as P
rogr
am (L
CA
)
Is th
ere
polit
ical
con
trol
ov
er h
ow sc
ienc
e is
used
?N
ot to
o m
uch.
Som
e, b
ecau
se p
oliti
cal d
eci-
sions
are
mad
e ab
out f
undi
ng.
No
Yes,
the
pow
er c
ompa
nies
are
po
wer
ful.
Polit
ics d
oes i
nfl u
ence
how
scie
nce
is us
ed.
Polit
ics d
oes i
nfl u
ence
how
scie
nce
is us
ed.
Polit
ics d
oes i
nfl u
ence
how
scie
nce
is us
ed.
Polit
ics d
oes i
nfl u
ence
how
scie
nce
is us
ed.
Is th
e sc
ienc
e m
ostly
di
rect
ed o
r is t
here
som
e di
scov
ery?
Dire
cted
with
som
e ro
om fo
r dis
cove
ry.
Also
the
man
y ac
adem
ic
inst
itutio
ns a
nd re
sear
ch
cons
ortiu
ms c
ontr
ibut
e to
dis
cove
ry-d
eriv
ed
know
ledg
e.
Dire
cted
Dis
cove
ry-b
ased
. M
ost i
s bas
ic e
co-
syst
em sc
ienc
e an
d is
dire
ctly
app
li-ca
ble
to th
e pr
ojec
t but
not
dire
cted
or
requ
este
d by
the
proj
ect.
Dire
cted
with
som
e ro
om fo
r di
scov
ery
beca
use
the
mai
n or
gani
-za
tion
is th
e G
CM
RC u
nder
DO
I.
So e
ven
thei
r “di
rect
ed” r
esea
rch
is fa
irly
“dis
cove
ry”.
Dire
cted
. PM
s ide
ntifi
ed sc
ient
ifi c
need
s D
irect
ed.
PMs i
dent
ifi ed
scie
ntifi
c ne
eds
Dire
cted
. PM
s ide
ntifi
ed sc
ient
ifi c
need
s D
irect
ed.
PMs i
dent
ifi ed
scie
ntifi
c ne
eds
and
capa
ble
rese
arch
ers t
o an
swer
spec
ifi c
and
capa
ble
rese
arch
ers t
o an
swer
spec
ifi c
and
capa
ble
rese
arch
ers t
o an
swer
spec
ifi c
and
capa
ble
rese
arch
ers t
o an
swer
spec
ifi c
ques
tions
bec
ause
of s
peed
and
effi
cien
cy.
ques
tions
bec
ause
of s
peed
and
effi
cien
cy.
ques
tions
bec
ause
of s
peed
and
effi
cien
cy.
ques
tions
bec
ause
of s
peed
and
effi
cien
cy.
Are
mod
els o
r sce
nari
os
used
to m
ake
deci
sions
?Ye
s, ex
tens
ive
use
of
mod
els.
Yes,
at le
ast s
omew
hat (
nam
ely
the
Nat
ural
Sys
tem
Mod
el).
Yes,
exte
nsiv
ely
Yes
To in
form
dec
ision
s onl
y
Is th
ere
invo
lvem
ent f
rom
th
e la
rger
scie
ntifi
c co
m-
mun
ity?
Yes,
subs
tant
ial
Som
ewha
tSo
me,
but
ther
e sh
ould
be
mor
e.U
nkno
wn
No;
lim
ited
How
did
you
han
dle
mul
ti-di
scip
linar
y w
ork?
Unk
now
n if
ther
e is
a sp
ecifi
c st
rate
gy.
Th e
proj
ect d
eliv
ery
team
s are
al
l mul
tidis
cipl
inar
y. Th
e c
hal-
leng
e is
mor
e in
wor
king
with
m
ultip
le a
genc
ies.
Som
etim
es
faci
litat
ors a
re b
roug
ht in
to
solv
e re
latio
nshi
p iss
ues.
Stan
ding
Boa
rds a
re a
ppoi
nted
for
inte
grat
ed w
ork.
Tec
hnic
al P
anel
s ad
dres
s ind
ivid
ual i
ssue
s (1,
13)
. Ex
plic
it en
cour
agem
ent,
thou
gh
prop
osal
fund
ing
and
dire
cted
act
ion
revi
ew.
Part
icip
atin
g sc
ienc
e co
mpo
sitio
nA
s nee
ded
thro
ugh
dire
cted
pro
gram
task
sA
s nee
ded
thro
ugh
dire
cted
pro
gram
task
sA
s nee
ded
thro
ugh
dire
cted
pro
gram
task
sA
s nee
ded
thro
ugh
dire
cted
pro
gram
task
s
How
wer
e sc
ienc
e:po
licy/
polit
ics c
onfl i
cts r
esol
ved,
if
they
wer
e?
Publ
ic a
nd st
akeh
olde
r in
volv
emen
t.Pr
ogra
m m
ay h
ave
adap
ted
to
the
prob
lem
s.Pu
rpos
eful
ly w
ith w
orks
hops
, fac
ili-
tato
rs a
nd in
tegr
atio
n te
ams.
Also
w
ith lo
ts o
f upd
ates
, mile
ston
es, a
nd
prod
ucts
(all
prog
ram
s).
Unk
now
nN
ot re
solv
ed
Are
ther
e “G
uidi
ng
Ecol
ogic
al P
rinc
iple
s” o
r “S
cien
ce P
rinc
iple
s”?
Unk
now
nU
nkno
wn
Yes,
not w
idel
y kn
own
Unk
now
nTh
ere
are
rest
orat
ion
prin
cipl
es, b
ut S
ci-
ence
Pla
ns p
rovi
des e
xplic
it pr
inci
ples
for
ence
Pla
ns p
rovi
des e
xplic
it pr
inci
ples
for
ence
Pla
ns p
rovi
des e
xplic
it pr
inci
ples
for
ence
Pla
ns p
rovi
des e
xplic
it pr
inci
ples
for
cond
uctin
g sc
ienc
e.
Is th
ere
a re
stor
atio
n pl
an
to p
rovi
de g
uida
nce?
Did
sc
ienc
e co
ntri
bute
to it
s fo
rmat
ion?
Yes,
and
scie
ntist
s wer
e ac
tive
in it
s for
mat
ion.
Yes,
but i
t was
larg
ely
form
ed
by th
e tim
e sc
ienc
e w
as
brou
ght t
o th
e ta
ble.
Yes,
with
in th
e “E
cosy
stem
Res
tora
-tio
n Pr
ogra
m”
Unk
now
nYe
s, th
roug
h th
e 20
50 p
lan
Is th
ere
a co
mpr
ehen
sive
proj
ect o
r mer
ely
one
spec
ifi c
actio
n?
Com
preh
ensiv
e pl
anne
d ac
tions
A st
rate
gic
port
folio
of d
iscr
ete
actio
nsLo
ts o
f sep
arat
e ac
tions
that
are
in-
fl uen
ced
by p
olic
y as
wel
l as s
cien
ceSm
alle
r act
ions
supp
ort o
ne la
rge
actio
n (e
xper
imen
tal fl
ood
ing)
.A
set o
f act
ions
org
aniz
ed a
roun
d th
e pr
ogra
m p
urpo
se
Is th
ere
a C
once
ptua
l M
odel
(CM
)?Ye
sYe
s, as
wel
l as o
ther
mod
els
that
use
hyd
rolo
gy a
s a p
erfo
r-m
ance
mea
sure
.
Th er
e ar
e lo
ts o
f con
cept
ual m
odel
s; al
l pro
posa
ls m
ust i
nclu
de a
CM
and
ea
ch e
lem
ent o
f the
pro
gram
has
its
own
CM
. C
ALF
ED d
emon
stra
ted
wel
l the
impo
rtan
ce o
f a C
M.
Unk
now
nYe
s, as
wel
l as o
ther
mod
els -
the
CM
was
Ye
s, as
wel
l as o
ther
mod
els -
the
CM
was
Ye
s, as
wel
l as o
ther
mod
els -
the
CM
was
Ye
s, as
wel
l as o
ther
mod
els -
the
CM
was
oft
en
in n
arra
tive
form
and
som
etim
es n
ot
oft e
n in
nar
rativ
e fo
rm a
nd so
met
imes
not
oft
en
in n
arra
tive
form
and
som
etim
es n
ot
oft e
n in
nar
rativ
e fo
rm a
nd so
met
imes
not
cl
early
stat
ed.
If so
, is i
t use
d as
a d
eci-
sion-
mak
ing
tool
?Ye
sU
nkno
wn
Yes,
cont
ribu
ting
to re
stor
atio
n de
sign
and
asse
ssm
ent
Unk
now
nYe
s, in
term
s of i
dent
ifyin
g co
nseq
uenc
es o
f Ye
s, in
term
s of i
dent
ifyin
g co
nseq
uenc
es o
f Ye
s, in
term
s of i
dent
ifyin
g co
nseq
uenc
es o
f Ye
s, in
term
s of i
dent
ifyin
g co
nseq
uenc
es o
f id
entif
ying
rest
orat
ion
actio
ns
Role of Science in Restoration Planning and Action (cont.) Restoration Planning and Guidance
26 PUGET SOUND NEARSHORE PARTNERSHIP Technical Report 1
App
endi
x C
. Pro
gram
Com
pari
son
Mat
rix
(con
t.)
Che
sape
ake
Bay
Prog
ram
(C
BP)
Com
preh
ensiv
e Ev
ergl
ades
Re
stor
atio
n Pr
ojec
t (C
ERP)
Cal
iforn
ia B
ay-D
elta
Pro
ject
(C
ALF
ED)
Gle
n C
anyo
n D
am A
dapt
ive
Man
agem
ent P
rogr
am (G
CA
MP)
Loui
siana
Coa
stal
Are
as P
rogr
am (L
CA
)
Was
ther
e a
stra
tegi
c pl
an a
t th
e on
set?
Is t
here
a st
rate
-gi
c ap
proa
ch to
add
ress
ing
scie
nce
issue
s?
Unk
now
nYe
s, be
caus
e to
p-do
wn
Yes,
ther
e is
a 19
97 d
ocum
ent t
hat
lays
out
a st
rate
gic
plan
for E
RP.
Unk
now
nYe
s, be
caus
e to
p-do
wn.
205
0 co
nstit
utes
Ye
s, be
caus
e to
p-do
wn.
205
0 co
nstit
utes
Ye
s, be
caus
e to
p-do
wn.
205
0 co
nstit
utes
Ye
s, be
caus
e to
p-do
wn.
205
0 co
nstit
utes
a
stra
tegi
c re
stor
atio
n pl
an, b
ut th
ere
was
a
stra
tegi
c re
stor
atio
n pl
an, b
ut th
ere
was
a
stra
tegi
c re
stor
atio
n pl
an, b
ut th
ere
was
a
stra
tegi
c re
stor
atio
n pl
an, b
ut th
ere
was
no
t a st
rate
gic
scie
nce
plan
and
scie
nce
has
not a
stra
tegi
c sc
ienc
e pl
an a
nd sc
ienc
e ha
s no
t a st
rate
gic
scie
nce
plan
and
scie
nce
has
not a
stra
tegi
c sc
ienc
e pl
an a
nd sc
ienc
e ha
s no
t bee
n w
ell i
nteg
rate
d un
til th
e pr
opos
ed
not b
een
wel
l int
egra
ted
until
the
prop
osed
no
t bee
n w
ell i
nteg
rate
d un
til th
e pr
opos
ed
not b
een
wel
l int
egra
ted
until
the
prop
osed
Sc
ienc
e Pl
an.
How
doe
s you
r pro
gram
di
stin
guish
am
ong
the
disp
arat
e co
mpo
nent
s of
scie
nce
to d
eter
min
e w
hat
may
pro
vide
use
ful g
uid-
ance
and
wha
t may
not
?
Unk
now
nU
nkno
wn
Th e
CM
s hel
p fi t
the
scie
nce
into
the
over
all p
rogr
am, a
nd d
eman
d ri
gor-
ous s
cien
tifi c
revi
ew.
Unk
now
nSc
ienc
e is
very
inte
rnal
ized
.
How
do
you
bala
nce
betw
een
theo
retic
al lo
ng-
rang
e st
rate
gic
scie
nce
and
shor
t-te
rm n
eeds
?
Th er
e is
supp
ort f
or lo
ng-
rang
e pl
anni
ng.
Littl
e ro
om to
mee
t mor
e th
an
imm
edia
te n
eeds
All
stud
ies h
ave
to b
e re
new
ed fo
r fu
ndin
g ev
ery
3 ye
ars;
how
ever
, C
ALF
ED e
mbr
aces
theo
retic
al st
ud-
ies a
s muc
h as
pos
sible
by
empl
oyin
g a
botto
m-u
p ap
proa
ch to
solic
it-in
g pr
opos
als.
Th e
y us
e ad
aptiv
e m
anag
emen
t to
bala
nce
long
- and
sh
ort-
term
scie
nce.
Shor
t-te
rm n
eeds
are
not
so
pres
sing
as to
elim
inat
e lo
ng-t
erm
pl
anni
ng.
Shor
t-te
rm n
eeds
are
ext
rem
ely
pres
sing
Shor
t-te
rm n
eeds
are
ext
rem
ely
pres
sing
Shor
t-te
rm n
eeds
are
ext
rem
ely
pres
sing
Shor
t-te
rm n
eeds
are
ext
rem
ely
pres
sing
but r
equi
re so
me
long
-ter
m p
lann
ing,
w
hich
they
hav
e ye
t to
real
ly a
ddre
ss
(alth
ough
Sci
ence
Pla
n do
es a
ttem
pt to
do
(alth
ough
Sci
ence
Pla
n do
es a
ttem
pt to
do
(alth
ough
Sci
ence
Pla
n do
es a
ttem
pt to
do
(alth
ough
Sci
ence
Pla
n do
es a
ttem
pt to
do
that
).
Was
ther
e an
ana
lysis
of
hist
oric
al c
ondi
tion?
Yes,
this
has b
een
a m
ajor
fo
cus o
f eff o
rt.
Th e
hist
oric
al a
naly
sis w
as
mad
e up
of a
necd
otal
info
rma-
tion
whi
ch w
as c
ombi
ned
with
pr
esen
t sci
ence
kno
wle
dge
to
prod
uce
simul
atio
ns o
f hist
ori-
cal c
ondi
tions
.
Yes,
lots
of i
nfor
mat
ion
to m
ake
up
the
hist
oric
al a
naly
sisLi
mite
dYe
s
Do
you
addr
ess t
he d
iff er
-en
ce b
etw
een
fi xin
g th
e pr
oble
m a
nd th
e sy
mp-
tom
s?
Yes,
mor
e so
Som
ewha
t, al
thou
gh u
rban
an
d ag
ricu
ltura
l wat
er u
se is
no
t bei
ng d
ecre
ased
.
Som
ewha
t, al
thou
gh m
ost a
ctio
ns
seem
to b
e co
ncen
trat
ed o
n ph
ysi-
cal/s
truc
tura
l rat
her t
han
popu
latio
n gr
owth
and
con
trol
.
No,
bec
ause
the
dam
will
not
be
rem
oved
in th
e ne
ar fu
ture
. N
ot re
ally,
but
fi xi
ng th
e pr
oble
m in
volv
es
Not
real
ly, b
ut fi
the
prob
lem
invo
lves
N
ot re
ally,
but
fi xi
ng th
e pr
oble
m in
volv
es
Not
real
ly, b
ut fi
the
prob
lem
invo
lves
th
e en
tire
mid
-wes
t. H
owev
er, t
here
are
th
e en
tire
mid
-wes
t. H
owev
er, t
here
are
th
e en
tire
mid
-wes
t. H
owev
er, t
here
are
th
e en
tire
mid
-wes
t. H
owev
er, t
here
are
ex
plic
it pr
oces
s-ba
sed
solu
tions
at t
he
coas
tal s
cale
.
How
doe
s the
pro
gram
dea
l w
ith d
ata
man
agem
ent?
No
stra
tegi
c pl
anN
o st
rate
gic
plan
Dis
cuss
ing
appl
ying
a w
eb-b
ased
sy
stem
to C
ALF
ED; m
anag
ed b
y su
ppor
ting
the
Del
ta S
cien
ce C
on-
sort
ium
and
by
enco
urag
ing
data
co
ordi
natio
n an
d an
alys
is (1
).
Dev
elop
ing
a pl
anN
o st
rate
gic
plan
, exc
ept t
hat t
he p
ropo
sed
No
stra
tegi
c pl
an, e
xcep
t tha
t the
pro
pose
d N
o st
rate
gic
plan
, exc
ept t
hat t
he p
ropo
sed
No
stra
tegi
c pl
an, e
xcep
t tha
t the
pro
pose
d Sc
ienc
e Pl
an h
as a
n ex
plic
it in
form
atic
s Sc
ienc
e Pl
an h
as a
n ex
plic
it in
form
atic
s Sc
ienc
e Pl
an h
as a
n ex
plic
it in
form
atic
s Sc
ienc
e Pl
an h
as a
n ex
plic
it in
form
atic
s st
rate
gy.
Wer
e th
ere
early
act
ion
(“lo
w-h
angi
ng fr
uit”
) pro
j-ec
ts?
Succ
essf
ul o
r not
?
Yes;
help
ful
Yes,
four
pilo
t pro
ject
s tha
t ha
ve y
et to
be
cons
truc
ted.
Th
ese
are
mos
tly to
test
tech
-no
logi
es.
Hig
h-pr
ofi le
pro
ject
s, w
ith e
xten
sive
stak
ehol
der i
nvol
vem
ent a
nd o
rgan
i-za
tion,
are
“sig
natu
re p
roje
cts”
that
ha
ve b
een
usef
ul in
test
ing
rest
ora-
tion
succ
ess,
but t
hey’r
e st
ill tr
ying
to
fi gur
e ou
t nex
t ste
ps fo
r tho
se a
reas
.
Not
real
lyC
WPP
RA c
onst
itute
d th
ese
proj
ects
.
In w
hat s
tage
is th
e pr
o-gr
am?
Wel
l alo
ng w
ith a
ctio
ns
and
proj
ect a
nd lo
ng-t
erm
di
rect
ion.
In th
e fi n
al p
lann
ing
stag
es
befo
re im
plem
enta
tion
ERP
in im
plem
enta
tion
Hav
e co
nduc
ted
one
AM
exp
eri-
men
t and
still
lear
ning
and
pla
n-ni
ng fo
r the
nex
t.
Fini
shed
reco
nnai
ssan
ce st
udy
and
prep
ar-
Fini
shed
reco
nnai
ssan
ce st
udy
and
prep
ar-
Fini
shed
reco
nnai
ssan
ce st
udy
and
prep
ar-
Fini
shed
reco
nnai
ssan
ce st
udy
and
prep
ar-
ing
to su
bmit
feas
ibili
ty re
port
to c
ongr
ess.
ing
to su
bmit
feas
ibili
ty re
port
to c
ongr
ess.
ing
to su
bmit
feas
ibili
ty re
port
to c
ongr
ess.
ing
to su
bmit
feas
ibili
ty re
port
to c
ongr
ess.
Restoration Planning and Guidance (continued) Actions and Activities
Lessons Learned from Large-Scale Restoration Efforts in the USA 27
App
endi
x C
. Pro
gram
Com
pari
son
Mat
rix
(con
t.)
Che
sape
ake
Bay
Prog
ram
(C
BP)
Com
preh
ensiv
e Ev
ergl
ades
Re
stor
atio
n Pr
ojec
t (C
ERP)
Cal
iforn
ia B
ay-D
elta
Pro
ject
(C
ALF
ED)
Gle
n C
anyo
n D
am A
dapt
ive
Man
agem
ent P
rogr
am (G
CA
MP)
Loui
siana
Coa
stal
Are
as P
rogr
am (L
CA
)
Are
ther
e ex
plic
it se
lect
ion
crite
ria
for r
esto
ratio
n ac
tions
? A
re th
ey st
rate
gic,
lo
ng-t
erm
?
Unk
now
nTh
e se
lect
ion
crite
ria
are
larg
ely
polit
ical
.Pr
opos
als
are
awar
ded
fund
ing
on
com
petit
ive
basis
and
mus
t fi t
int
o th
e foc
us o
f CA
LFED
. Pro
ject
s are
re-
view
ed b
y th
e te
chni
cal r
evie
w b
oard
an
d th
e ge
ogra
phic
revi
ew b
oard
.
Unk
now
nA
s yet
no
proc
ess b
eyon
d co
st-e
ff ect
iven
ess
As y
et n
o pr
oces
s bey
ond
cost
-eff e
ctiv
enes
sA
s yet
no
proc
ess b
eyon
d co
st-e
ff ect
iven
ess
As y
et n
o pr
oces
s bey
ond
cost
-eff e
ctiv
enes
s
Are
act
ions
mon
itore
d (a
nd
by w
hom
)?Ye
s. M
onito
ring
is
orga
nize
d by
subc
omm
it-te
es a
nd c
arri
ed o
ut b
y ag
enci
es, a
cade
mic
s, or
by
citiz
en g
roup
s.
Very
littl
ePe
rfor
man
ce m
easu
res a
re th
e m
ain
way
to n
ot o
nly
mon
itor b
ut a
sses
s pr
ogre
ss; j
ust n
ow re
quir
ing
proj
ect
to d
o m
onito
ring
. New
IRW
M p
ro-
gram
has
yet
to d
evel
op p
roto
cols.
Yes.
Mon
itori
ng is
org
aniz
ed b
y th
e G
CM
RC a
nd c
ontr
acte
d ou
t or
assig
ned
to o
ther
gro
ups.
CW
PPRA
has
a w
ell d
evel
oped
mon
itori
ng
CW
PPRA
has
a w
ell d
evel
oped
mon
itori
ng
CW
PPRA
has
a w
ell d
evel
oped
mon
itori
ng
CW
PPRA
has
a w
ell d
evel
oped
mon
itori
ng
prog
ram
, whi
ch L
CA
will
like
ly b
uild
on.
prog
ram
, whi
ch L
CA
will
like
ly b
uild
on.
prog
ram
, whi
ch L
CA
will
like
ly b
uild
on.
prog
ram
, whi
ch L
CA
will
like
ly b
uild
on.
How
doe
s you
r pro
gram
en
sure
the
best
act
ions
are
be
ing
take
n?
Unk
now
nU
nkno
wn
Ensu
re “g
ood”
pro
posa
ls by
not
be-
ing
afra
id to
say
“no”
and
by
hold
ing
wor
ksho
ps to
teac
h pe
ople
how
to
writ
e a
good
pro
posa
l.
Unk
now
nN
o pr
oces
s at p
rese
nt
How
are
act
ions
fund
ed?
Man
y fu
ndin
g so
urce
s, fe
dera
l bud
gets
Dire
ct fe
dera
l/sta
teM
any
prop
osal
s are
sele
cted
by
a hi
ghly
com
petit
ive
RFP;
how
ever
, so
me
prog
ram
are
as, s
uch
as c
onve
y-an
ce p
roje
cts,
have
not
yet
bee
n su
bjec
t to
rigo
rous
com
petit
ion.
Fede
ral p
rogr
am b
udge
tA
s par
t of p
rogr
am im
plem
enta
tion
stra
t-A
s par
t of p
rogr
am im
plem
enta
tion
stra
t-A
s par
t of p
rogr
am im
plem
enta
tion
stra
t-A
s par
t of p
rogr
am im
plem
enta
tion
stra
t-eg
y, ba
sed
on fe
asib
ility
repo
rt
Do
you
prac
tice
adap
tive
man
agem
ent?
How
?W
orki
ng to
war
ds A
M,
but p
ract
icin
g ad
aptiv
e le
arni
ng
Yes,
ther
e is
an a
dapt
ive
mon
i-to
ring
ass
essm
ent t
eam
that
as-
sess
es p
rogr
ess a
nd m
onito
rs.
Ada
ptiv
e m
anag
emen
t is a
fund
a-m
enta
l ten
ant o
f the
ERP
.Ye
s. Th
is i
s the
foun
datio
n of
the
prog
ram
.N
o. Th
ey’r
e w
orki
ng o
n ad
aptiv
e le
arn-
No.
Th e
y’re
wor
king
on
adap
tive
lear
n-N
o. Th
ey’r
e w
orki
ng o
n ad
aptiv
e le
arn-
No.
Th e
y’re
wor
king
on
adap
tive
lear
n-in
g an
d th
e Sc
ienc
e Pl
an la
ys o
ut so
me
prin
cipl
es.
Is th
ere
an a
dapt
ive
man
-ag
emen
t pla
n an
d ho
w w
as
it de
velo
ped?
Unk
now
nTh
e ad
aptiv
e m
anag
emen
t pl
an is
still
bei
ng d
evel
oped
. Th
e pr
oces
s is c
oord
inat
ed b
y th
e RE
CO
VER
team
.
Th e
plan
will
be
deve
lope
d us
ing
wor
ksho
ps, C
Ms,
inte
grat
ing
peer
-re
view
ed A
M p
roje
ct p
ropo
sals,
and
pa
nels
of e
xper
ts.
Yes,
deve
lope
d by
scie
ntist
sIn
pro
pose
d Sc
ienc
e Pl
an
Is th
ere
a m
echa
nism
to
inco
rpor
ate
less
ons l
earn
ed
from
ear
ly a
ctio
n pr
ojec
ts?
Do
you
use
it?
Yes
Yes,
the
pilo
t pro
ject
s add
ress
ar
eas o
f unc
erta
inty
and
eac
h ha
s mec
hani
sms t
o le
arn
from
th
e ex
peri
ence
.
ERP
has m
ade
som
e at
tem
pt a
t a
“loo
k ba
ck” e
xerc
ise.
Yes,
thro
ugh
AM
Con
duct
ed u
nder
CW
PPRA
; LC
A w
ould
C
ondu
cted
und
er C
WPP
RA; L
CA
wou
ld
Con
duct
ed u
nder
CW
PPRA
; LC
A w
ould
C
ondu
cted
und
er C
WPP
RA; L
CA
wou
ld
cond
uct i
t thr
ough
Sci
ence
Pla
n.
Is th
ere
mon
itori
ng?
Has
it
been
diffi
cul
t to
just
ify?
Doe
s it p
lay
a la
rge
role
?
Yes,
wat
er q
ualit
y m
oni-
tori
ng st
arte
d ve
ry e
arly,
bu
t it h
as o
nly
rece
ntly
ex-
pand
ed to
be
wid
ely
use-
ful.
It re
mai
ns so
mew
hat
chal
leng
ing
to ju
stify
.
Th er
e ha
s bee
n he
avy
fi nan
cial
in
vest
men
t in
mon
itori
ng
from
ear
ly o
n. E
arly
act
ion
mon
itori
ng p
roje
cts a
re c
alle
d “d
emon
stra
tion
proj
ects
.”
Th er
e is
limite
d m
onito
ring
of
spec
ifi c
proj
ects
. Th e
y’re
still
stru
g-gl
ing
with
a to
ken
com
mitm
ent t
o m
onito
ring
and
poo
r fol
low
-thr
ough
(f
rom
visi
t not
es).
Yes,
mon
itori
ng is
a su
bsta
ntia
l pa
rt o
f the
pro
gram
and
it h
as b
een
chal
leng
ing
to ju
stify
, but
it st
arte
d w
hen
the
dam
was
bui
lt, w
hich
he
lped
.
Mon
itori
ng o
f Bre
aux
Act
eff o
rts i
s wel
l M
onito
ring
of B
reau
x A
ct e
ff ort
s is w
ell
Mon
itori
ng o
f Bre
aux
Act
eff o
rts i
s wel
l M
onito
ring
of B
reau
x A
ct e
ff ort
s is w
ell
esta
blish
ed, a
lbei
t at m
inim
al le
vels.
Do
you
have
per
form
ance
m
easu
res?
Yes,
mos
tly in
form
of
ecos
yste
m in
dica
tors
. “40
%
redu
ctio
n of
nut
rient
s” w
as
a not
ewor
thy m
easu
re.
Yes,
from
ear
ly o
n. 1
,000
in
dica
tors
wer
e de
velo
ped
and
narr
owed
dow
n to
und
er 5
0.
Yes,
prot
otyp
es h
ave
been
dev
elop
ed
and
PMs w
ill fo
llow.
Unk
now
nN
ot e
xplic
itly,
and
may
hav
e ac
tual
ly
been
de-
emph
asiz
ed; L
CA
wou
ld d
evel
op
been
de-
emph
asiz
ed; L
CA
wou
ld d
evel
op
been
de-
emph
asiz
ed; L
CA
wou
ld d
evel
op
been
de-
emph
asiz
ed; L
CA
wou
ld d
evel
op
perf
orm
ance
mea
sure
s thr
ough
the
Scie
nce
perf
orm
ance
mea
sure
s thr
ough
the
Scie
nce
perf
orm
ance
mea
sure
s thr
ough
the
Scie
nce
perf
orm
ance
mea
sure
s thr
ough
the
Scie
nce
Plan
.
How
wer
e pe
rfor
man
ce
mea
sure
s dev
elop
ed a
nd
used
in e
valu
atio
n?
Unk
now
nD
evel
oped
by
mak
ing
a lo
ng
list a
nd w
inno
win
g it
dow
n.
Th is
met
hod
may
not
hav
e be
en th
e m
ost e
ffi ci
ent o
r cor
-re
ct a
ppro
ach.
Prot
otyp
e PM
s dev
elop
ed b
y Sc
ienc
e Pr
ogra
m co
nsul
tant
usin
g Sc
ienc
e Pr
ogra
m’s
tem
plat
e for
gui
danc
e of P
M
sele
ctio
n. A
s mor
e is l
earn
ed, r
eal P
Ms
will
be s
ubst
itute
d fo
r pro
toty
pes (
1).
Unk
now
nN
one
at th
is tim
e
Actions and Activities (cont.) Monitoring and Adaptive Management
28 PUGET SOUND NEARSHORE PARTNERSHIP Technical Report 1
App
endi
x C
. Pro
gram
Com
pari
son
Mat
rix
(con
t.)
Che
sape
ake
Bay
Prog
ram
(C
BP)
Com
preh
ensiv
e Ev
ergl
ades
Re
stor
atio
n Pr
ojec
t (C
ERP)
Cal
iforn
ia B
ay-D
elta
Pro
ject
(C
ALF
ED)
Gle
n C
anyo
n D
am A
dapt
ive
Man
agem
ent P
rogr
am (G
CA
MP)
Loui
siana
Coa
stal
Are
as P
rogr
am (L
CA
)
Do
you
empl
oy “o
utsid
e”
peer
revi
ews?
Ye
sC
ROG
EE
prov
ides
in
depe
n-de
nt sc
ient
ifi c r
evie
w. C
urre
ntly
w
orki
ng to
est
ablis
h an
out
side
Nat
iona
l A
cade
my
of S
cien
ces
revi
ew p
anel
that
will
like
ly r
e-pl
ace C
ROG
EE (w
ebsit
e).
All
prop
osal
s and
pro
duct
s are
pee
r re
view
ed.
Th e
Inde
pend
ent S
ci-
ence
Boa
rd is
the
mai
n pe
er-r
evie
w
pane
l, bu
t oth
er te
chni
cal p
anel
s and
st
andi
ng b
oard
s also
pro
vide
revi
ew
(8/1
4/03
mee
ting,
item
#8)
.
Unk
now
nTh
e N
at’l
Tech
Rev
iew
Com
mitt
ee is
the
Th e
Nat
’l Te
ch R
evie
w C
omm
ittee
is th
e Th
e N
at’l
Tech
Rev
iew
Com
mitt
ee is
the
Th e
Nat
’l Te
ch R
evie
w C
omm
ittee
is th
e ou
tsid
e re
view
boa
rd, a
nd th
ere
is an
on
goin
g N
RC re
view
.
Is th
ere
som
e ot
her e
stab
-lis
hed
way
to a
cces
s exp
ert
advi
ce?
Yes,
colla
bora
tion
with
re
sear
ch c
onso
rtiu
ms.
Cur
rent
ly p
uttin
g a
peer
-re
view
pro
gram
toge
ther
to
revi
ew R
ECO
VER
pro
duct
s.
Th er
e ha
s bee
n so
me
prob
lem
s se
curi
ng e
xter
nal p
eer r
evie
w
and
acce
ss to
adv
ice
from
out
side
expe
rts.
But,
they
inve
st c
onsid
erab
le
reso
urce
s in
peer
revi
ew.
Th is
is du
e to
a la
ck o
f an
esta
blish
ed sy
stem
(1).
Unk
now
nW
orki
ng p
anel
s hav
e in
depe
nden
t sci
en-
Wor
king
pan
els h
ave
inde
pend
ent s
cien
-W
orki
ng p
anel
s hav
e in
depe
nden
t sci
en-
Wor
king
pan
els h
ave
inde
pend
ent s
cien
-tis
ts; a
lso, t
he N
TRC
.
How
doe
s hig
h-le
vel (
e.g.
, N
AS/
NRC
) pee
r-re
view
ha
ppen
?
Unk
now
nIn
freq
uent
revi
ew (e
.g. O
MB
stud
y)It
does
n’t h
appe
n w
ithin
the p
rogr
am;
too
fi ne o
f sca
le. In
the n
ext c
oupl
e yea
rs
they
’re p
lanni
ng a
Nat
iona
l Aca
dem
y C
ompa
rativ
e Rev
iew
(1, p
18).
Unk
now
nLi
ttle
revi
ew o
f Bre
aux
Act
pro
posa
ls.
Th er
e is
an o
ngoi
ng N
RC re
view
whi
ch
Th er
e is
an o
ngoi
ng N
RC re
view
whi
ch
Th er
e is
an o
ngoi
ng N
RC re
view
whi
ch
Th er
e is
an o
ngoi
ng N
RC re
view
whi
ch
will
revi
ew th
e N
at’l.
Tec
h. re
view
repo
rt.
will
revi
ew th
e N
at’l.
Tec
h. re
view
repo
rt.
will
revi
ew th
e N
at’l.
Tec
h. re
view
repo
rt.
will
revi
ew th
e N
at’l.
Tec
h. re
view
repo
rt.
In w
hat w
ays i
s the
pub
lic
invo
lved
?Lo
ts of
pub
lic in
volv
emen
tLi
ttle
publ
ic in
volv
emen
tLo
ts o
f pub
lic in
volv
emen
t with
pu
blic
bon
ds, o
utre
ach,
and
a h
igh
leve
l of e
xist
ing
publ
ic in
tere
st
Unk
now
nTh
ere
have
bee
n m
any
publ
ic m
eetin
gs
Th er
e ha
ve b
een
man
y pu
blic
mee
tings
Th
ere
have
bee
n m
any
publ
ic m
eetin
gs
Th er
e ha
ve b
een
man
y pu
blic
mee
tings
un
der 2
050,
and
sim
ilar s
take
hold
er m
eet-
unde
r 205
0, a
nd si
mila
r sta
keho
lder
mee
t-un
der 2
050,
and
sim
ilar s
take
hold
er m
eet-
unde
r 205
0, a
nd si
mila
r sta
keho
lder
mee
t-in
gs u
nder
LC
A.
Is th
ere
scie
nce
outr
each
to
the
publ
ic?
Yes w
ith re
gula
r rep
orts
an
d pu
blic
atio
nsN
ot sp
ecifi
cally
from
scie
nce,
bu
t CER
P ha
s an
outr
each
pr
ogra
m a
nd p
ublic
mee
tings
ar
e he
ld to
del
iver
scie
ntifi
c in
form
atio
n to
the
publ
ic.
Yes,t
here
is in
volv
emen
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wor
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LFED
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ntly
intr
o-du
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an o
nlin
e sc
ienc
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urna
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al
l doc
umen
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nclu
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pro
posa
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are
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Is th
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info
rmed
? Su
p-po
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form
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nd la
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alth
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ther
e is
stak
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Info
rmed
fairl
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thou
gh th
ere
is st
akeh
olde
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nfl ic
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y ha
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Info
rmed
fairl
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ell,
and
sup-
port
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he p
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co
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In
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In
form
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pro
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of t
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Th e
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is tr
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stak
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Th e
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confl
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as sh
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al p
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is su
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by st
ate-
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con
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stat
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of c
onst
itutio
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amen
dmen
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Th ro
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act
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.So
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s are
a fa
ctor
in d
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sion
mak
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Scie
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Boar
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are
also
repr
esen
ted
othe
r tha
n ju
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chni
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cien
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Expl
icitl
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Env
ironm
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ater
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ium
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iven
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the p
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agni
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Pote
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ourc
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nfl ic
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Pote
ntia
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Pote
ntia
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ourc
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nfl ic
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of th
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oble
m a
nd li
kely
solu
tions
.
Peer Review Public involvement External factors
1. C
alifo
rnia
Bay
–Del
ta P
rogr
am: S
cien
ce P
rogr
am M
ulti-
Year
Pro
gram
Pla
n (Y
ears
4-7
). A
ugus
t 200
3.
Lessons Learned from Large-Scale Restoration Efforts in the USA 29
Adaptive management—sci-entifi c experiments applied to natural resource management. It prescribes adapting manage-ment based on the results of rigorous scientifi c experimenta-tion that is built into the man-agement plan.
Conceptual model—in the cases examined here, a model, either numerical or diagram-matic, that summarizes and describes a simplifi ed version of the natural environment.
Directed vs. discovery sci-ence—directed science is what we’ve referred to as “top-down,” or science that is called for as part of a science plan. Discov-ery science, or “bottom-up” sci-ence is not orchestrated by an overarching plan, but “bubbles” up from the broader scientifi c community.
Ecosystem—system which includes all the organisms of an area and the environment in which they live (Collin 1988). A biological community together with the physical and chemi-cal environment with which it interacts (National Research Council [NRC] 1992).
Ecosystem function—any per-formance attribute or rate func-tion at some level of biological organization (e.g., energy fl ow, detritus processing, nutrient spiraling) (NRC 1992).
Indicator—a substance which shows that another substance is present; species which has par-ticular requirements and whose presence in an area shows that these requirements are pres-ent also. An indicator species is sensitive to changes in the environment and can warn that environmental changes are tak-ing place (Collin 1988).
Landscape scale/large-scale—this is a gauge to measure the magnitude of the project relative to its surroundings. Large-scale projects usually overlap governmental juris-dictions, thus requiring col-laboration from a broad range of participants. Large-scale is also a measurement relative to other restoration projects in the region. For example, CERP is large-scale and the Kissimmee River project, dwarfed by CERP, is smaller scale.
Mitigation—actions taken to avoid, reduce, or compensate for the eff ects of environmen-tal damage. Among the broad spectrum of possible actions are those that restore, enhance, create, or replace damaged eco-system (NRC 1992).
Performance measures—met-rics or indicators (see previous) that are related to an ecosystem process or function and are measurable in a natural ecosys-tem, which can be used to judge the performance of restoration actions. Programmatic perfor-mance measures could measure public support, access to fund-ing, etc.
Processes-based restoration—restoration (see following) or processes that shape an ecosys-tem, such as sediment transport or erosion, rather than the res-toration of ecosystem features, such as tidal marshes or species populations.
Restoration—returning an eco-system to a close approximation of its pre-disturbance state in terms of structure and function (NRC 1992).
Glossary of Terms
PSNERP and the Nearshore Partnership
Th e Puget Sound Nearshore Ecosystem Restoration Project(PSNERP) was formally initiated as a General Investigation (GI) Feasibility Study in September 2001 through a cost-share agree-ment between the U.S. Army Corps of Engineers and the State of Washington, represented by the Washington Department of Fish and Wildlife. Th is agreement describes our joint interests and re-sponsibilities to complete a feasibility study to
“…evaluate signifi cant ecosystem degradation in the Puget Sound Basin; to formulate, evaluate, and screen potential solutions to these problems; and to recommend a series of actions and projects that have a federal inter-est and are supported by a local entity willing to provide the necessary items of local cooperation.”
Th e current Work Plan describing our approach to completing this study can be found at:
http://pugetsoundnearshore.org/documents/StrategicWorkPlanfi nal.pdf
Since that time, PSNERP has attracted considerable attention and support from a diverse group of individuals and organizations interested and involved in improving the health of Puget Sound nearshore ecosystems and the biological, cultural, and economic resources they support. Th e Puget Sound Nearshore Partnershipis the name we have chosen to describe this growing and diverse group, and the work we will collectively undertake that ultimately supports the goals of PSNERP, but is beyond the scope of the GI Study. Collaborating with the Puget Sound Action Team, the Near-shore Partnership seeks to implement portions of their Work Plan pertaining to nearshore habitat restoration issues. We understand that the mission of PSNERP remains at the core of our partner-ship. However restoration projects, information transfer, scientifi c studies, and other activities can and should occur to advance our understanding, and ultimately, the health of the Puget Sound near-shore beyond the original focus and scope of the ongoing GI Study. As of the date of publication for this Technical Report, our partner-ship includes participation by the following entities:
Interagency Committee for Outdoor Recreation
King Conservation District
King County
National Wildlife Federation
NOAA Fisheries
Northwest Indian Fisheries Commission
People for Puget Sound
Pierce County
Puget Sound Action Team
Salmon Recovery Funding Board
Taylor Shellfi sh Company
Th e Nature Conservancy
U.S. Army Corps of Engineers
U.S. Environmental Protection Agency
U.S. Geological Survey
U.S. Fish and Wildlife Service
University of Washington
Washington Department of Ecology
Washington Department of Fish and Wildlife
Washington Department of Natural Resources
Washington Public Ports Association
Washington Sea Grant
WRIA 9
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