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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

2 PUGET SOUND NEARSHORE PARTNERSHIP Technical Report 1

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

II PUGET SOUND NEARSHORE PARTNERSHIP Technical Report 1

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.

IV PUGET SOUND NEARSHORE PARTNERSHIP Technical Report 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 ([email protected]) or Tim Smith ([email protected]).


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).


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.


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.


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.


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.


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.


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


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.


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).


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-


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


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.


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.


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-


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.


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.


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.


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


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?


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s, to

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chem

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ls, o

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shin

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dim

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. Ve

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clea

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as

a “c

risis

.”

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ges f

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ricu

lture

and

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dest

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ades

. Pr

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m is

cle

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nd a

wid

ely

acce

pted

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sis.”

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reas

ed h

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of t

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ay.

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ered

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stal

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ract

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natio

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oble

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mer

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vera

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prob

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till

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prob

lem

stat

emen

t is s

till

bein

g re

fi ned

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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.


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


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


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


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


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

xing

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

xing

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


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


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

t on

wor

king

gr

oups

. CA

LFED

has

rece

ntly

intr

o-du

ced

an o

nlin

e sc

ienc

e jo

urna

l and

al

l doc

umen

ts, i

nclu

ding

pro

posa

ls,

are

on th

e w

eb.

Unk

now

nN

o sc

ienc

e ou

trea

ch

Is th

e pu

blic

info

rmed

? Su

p-po

rtiv

e?In

form

ed a

nd su

ppor

tive,

ye

sIn

form

ed y

es, a

nd la

rgel

y su

ppor

tive

alth

ough

ther

e is

stak

ehol

der c

onfl i

ct.

Info

rmed

fairl

y w

ell,

and

fairl

y su

p-po

rtiv

e al

thou

gh th

ere

is st

akeh

olde

r co

nfl ic

t; bu

t the

y ha

ve su

ppor

ted

fund

ing

prop

ositi

ons.

Info

rmed

fairl

y w

ell,

and

sup-

port

ive

from

all

but t

he p

ower

co

mpa

nies

who

are

no

long

er v

ery

criti

cal.

Info

rmed

of t

he p

robl

em, b

ut n

ot o

f the

In

form

ed o

f the

pro

blem

, but

not

of t

he

Info

rmed

of t

he p

robl

em, b

ut n

ot o

f the

In

form

ed o

f the

pro

blem

, but

not

of t

he

solu

tion.

Th e

re is

trem

endo

us st

akeh

olde

r so

lutio

n. Th

ere

is tr

emen

dous

stak

ehol

der

solu

tion.

Th e

re is

trem

endo

us st

akeh

olde

r so

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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

application of the “best available science” in ecosystem ... learned from large-scale...

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