# In Re Consolidated Salmonid Cases

> District Court, E.D. California · September 20, 2011 · 791 F. Supp. 2d 802

URL: https://www.frixlaw.com/law-library/cases/2176473

## Case

- **Court:** District Court, E.D. California
- **Decided:** September 20, 2011
- **Citations:** 791 F. Supp. 2d 802; 2011 WL 4552293
- **Precedential status:** Published
- **Opinion:** Opinion
- **Cited by:** 7 later opinions in the Frix Law Library

## Citator (automated)

- No negative treatment found by the automated citator. That is not the same as a confirmation that the case is good law; read the citing cases.
- Full citator and citing cases: https://www.frixlaw.com/law-library/cases/2176473

## How later opinions describe it (automated extraction)

- describing how the parties’ cross motions for summary judgment “included ... thousands of pages of supporting declarations and exhibits”

## Opinion text

791 F.Supp.2d 802 (2011)
The CONSOLIDATED SALMONID CASES
San Luis & Delta-Mendota Water Authority; Westlands Water District
v.
Gary F. Locke, as Secretary of the United States Department of Commerce; et al. (1:09-cv-01053-OWW-DLB)
Stockton East Water District, et al.
v.
National Oceanic and Atmospheric Administration, et al. (1:09-cv-01090-OWW-DLB)
State Water Contractors
v.
Gary F. Locke, et al. (1:09-cv-01378-OWW-SMS)
Kern County Water Agency, et al.
v.
United States Department of Commerce, et al. (1:09-cv-01520-OWW-SMS)
Oakdale Irrigation District, et al.
v.
United States Department of Commerce, et al. (1:09-cv-01580-OWW-DLB)
The Metropolitan Water District of Southern California
v.
National Marine Fisheries Service, et al. (1:09-cv-01625-OWW-SMS).
Nos. 1:09-CV-01053, 1:09-CV-01090, 1:09-CV-01373, 1:09-CV-01520, 1:09-CV-01580, 1:09-CV-01625.
United States District Court, E.D. California.
September 20, 2011.
*810 Daniel Joseph O'Hanlon, Hanspeter Walter, K. Eric Adair, Rebecca Rose Akroyd, Kronick, Moskovitz, Tiedemann & Girard, David A. Diepenbrock, Jon David Rubin, Jonathan R. Marz, Diepenbrock Harrison, Eileen M. Diepenbrock, Diepenbrock *811 Elkin LLP, Linus Serafeim Masouredis, Metropolitan Water District of Southern California, Sacramento, CA, Charles Wesley Strickland, Brownstein Hyatt Farber and Schreck LLP, Santa Barbara, CA, Geoffrey M. Williamson, Mark J. Mathews, PHV, Martha F. Bauer, PHV, Michelle C. Kales, PHV, Brownstein Hyatt Farber Schreck LLP, Denver, CO, Steve O. Sims, PHV, Brownstein Hyatt Farber Schreck LLP, Albuquerque, NM, Harold Craig Manson, Westlands Water District, Fresno, CA, Alexis Keane Galbraith, Jeanne M. Zolezzi, Karna E. Harrigfeld, Jennifer L. Spaletta, Herum Crabtree, Stockton, CA, Tim P. O'Laughlin, William C. Paris, III, O'Laughlin & Paris, LLP, Chico, CA, Audrey M. Huang, Paul S. Weiland, Nossaman LLP, Irvine, CA, Stopher J. Carr, William M. Sloan, Edgar B. Washburn, Morrison and Foerster LLP (San Francisco), San Francisco, CA, Amelia Minaberrigarai, Bakersfield, CA, Gregory K. Wilkinson, Steven M. Anderson, Best, Best & Krieger, LLP, Riverside, CA, for Plaintiffs.
Bridget Kennedy McNeil, United States Department of Justice Environment & Natural Res. Div., Wildlife & Marine Resources, Denver, CO, Bradley H. Oliphant, Washington, DC, Charles Ray Shockey, William James Shapiro, United States Department of Justice, Sacramento, CA, for Defendants.
MEMORANDUM DECISION RE CROSS MOTIONS FOR SUMMARY JUDGMENT (DOCS. 430, 435, 446, 474, 477)
OLIVER W. WANGER, District Judge.
TABLE OF CONTENTS
I. INTRODUCTION.......................................................................812
II. BACKGROUND .......................................................................813
A. The Listed Species.............................................................813
1. Sacramento River Winter-Run Chinook Salmon..................................813
2. Spring Run Chinook..........................................................814
3. Central Valley Steelhead....................................................815
4. Green Sturgeon..............................................................816
5. Southern Resident Killer Whale..............................................816
B. The 2009 Salmonid BiOp and RPA.................................................816
III. STANDARD OF DECISION..... .......................................................818
IV. BASIC LEGAL FRAMEWORK.............................................................819
A. Review under the APA...........................................................819
1. Record Review...............................................................819
2. Deference to Agency Expertise...............................................819
B. General Obligations Under the ESA..............................................820
1. Best Available Science......................................................821
2. Best Available Science Standards and the Application of Analytical/
Statistical Methodologies.................................................824
V. EXPORT PLAINTIFFS' & DWR'S CLAIMS..................................................824
A. Alleged Clear Scientific Errors Pertaining to Delta Operations................824
1. Challenged Statistical Methodologies ......................................825
2. Failure to Perform a Population-Level Quantitative Analysis ...............834
B. Baseline Analysis Challenges...................................................845
1. Failure to Distinguish Between Discretionary and Nondiscretionary
Actions..................................................................845
2. Treatment of Available Data on Ocean Harvest and Ocean Conditions..........852
C. Effects Analysis Challenges....................................................858
*812
1. Use of a 100-Year Timeframe................................................858
2. Winter-Run Viability Analysis..............................................861
3. Orca Analysis..............................................................864
4. Interior Delta Mortality as an Indirect Effect.............................866
D. Critical, Habitat Analysis.....................................................871
1. There Is No Requirement that NMFS Identify a Numerical Threshold
for Adverse Modification..................................................871
2. Significance of Impacts to Critical Habitat................................872
E. Use of Surrogates..............................................................880
F. Challenges to the Reasonable and Prudent Alternative...........................882
1. RPA Action IV.2.1...........................................................882
2. RPA Action IV.2.3...........................................................898
3. Action IV.3.................................................................909
G. Compliance with 50 C.F.R. § 402.02 .......................................911
1. Consistency with Purposes of the Action ....................................914
2. Consistency with the Action Agency's Legal Authority and Jurisdiction.......917
3. Economic and Technical Feasibility..........................................919
4. Avoidance Jeopardy and/or Adverse Modification..............................922
5. DWR's Feasibility Challenges to Action IV.4.2...............................922
VI. STANISLAUS RIVER PLAINTIFFS' CLAIMS ..............................................928
A. Relevant Factual Background ...................................................928
1. The New Melones Project.....................................................928
2. The Stanislaus River Plaintiffs.............................................928
3. The Status of Steelhead in the Stanislaus River.............................928
B. Inclusion of the New Melones Unit in the Proposed Action Subject to
Consultation ................................................................930
C. Effects Analysis Challenges....................................................931
1. New Melones Operations v. Baseline Effects..................................931
2. Challenge to Critical Habitat Adverse Modification Finding..................934
D. Stanislaus River RPA Challenges................................................937
1. Challenge to the Assumptions Used to Model New Melones Project
Operations................................................................937
2. Do Actions III.1.2, III.1.3, and IV.1.2 Improperly Require Reclamation
to Infringe Upon OID and SSJID's Prior Right to Stanislaus River
Water in violation of 50 C.F.R. § 402.02 ?............................938
3. Use of the San Joaquin River Temperature Model..............................941
4. Exceptions Built into Action III.1.2........................................947
5. Does the Record Support the Finding that Action III.1.3 Will Avoid
Jeopardy to or Adverse Modification of CV Steelhead or Critical
Habitat? .................................................................948
6. DFG Salmon Population Model ................................................950
7. SR Plaintiffs' "Impermissible Major Changes" Argument.......................951
8. Challenges to the BiOp's Feasibility Analyses?..............................951
9. Are Actions III.1.3, III.2.2 Consistent with the Purposes of the Project?...952
10. Waste and Unreasonable Use of Water (California Constitution Article
X, Section 2).............................................................953
VII. RECLAMATION'S LIABILITY UNDER THE ESA.................................................954
VIII. CONCLUSION...........................................................................955
I. INTRODUCTION
These consolidated cases arise out of continuing efforts to protect several species listed under the Endangered Species Act ("ESA"), namely the endangered Sacramento River winter-run Chinook salmon (Oncorhynchus tshawytscha) ("winter-run"), threatened Central Valley spring-run Chinook salmon (O. tshawytscha) ("spring-run"), threatened Central Valley *813 steelhead (O. mykiss) ("CV steelhead"), threatened Southern Distinct Population Segment ("DPS") of North American green sturgeon (Acipenser medirostris), and endangered Southern Resident killer whales (Orcinus orca) (collectively, "Listed Species"); and associated impacts to the water supply for more than half the State of California.
Plaintiffs, San Luis & Delta Mendota Water Authority and Westlands Water District; State Water Contractors ("SWC"); Kern County Water Agency and Coalition for a Sustainable Delta; and Metropolitan Water District of Southern California ("MWD" or "Metropolitan") (collectively "Export Plaintiffs") move for summary judgment on their claims that the United States National Marine Fisheries Service's ("NMFS") June 4, 2009 Biological Opinion, addressing the impacts of the coordinated operations of the federal Central Valley Project ("CVP") and State Water Project ("SWP") (collectively the "Project") on the Listed Species ("2009 Salmonid BiOp" or "BiOp") and its Reasonable and Prudent Alternative ("RPA"), violates the ESA and the Administrative Procedure Act ("APA"). Doc. 430. [1] Plaintiffs Stockton East Water District, Oakdale Irrigation District, and South San Joaquin Irrigation District ("Stanislaus River Plaintiffs" or "SR Plaintiffs") filed a separate motion for summary judgment, raising unique challenges to the BiOp. Doc. 435. Plaintiff-in-Intervention, the California Department of Water Resources ("DWR") filed a separate motion for summary judgment on narrower grounds. Doc. 446.
Federal Defendants, the United States Department of Commerce ("DOC"), the National Oceanic and Atmospheric Administration ("NOAA"), the agency within DOC of which NMFS is a part, NMFS, the United States Department of the Interior ("DOI"), and its sub-agency the United States Bureau of Reclamation ("Reclamation"), oppose and cross move for summary judgment on all remaining claims, Doc. 477, as do Defendant-Intervenors California Trout, Friends Of The River, Natural Resources Defense Council, Northern California Council of the Federation of Fly Fishers, Pacific Coast Federation of Fishermen's Associations/Institute for Fisheries Resources, Sacramento River Preservation Trust, San Francisco Baykeeper, The Bay Institute, and the Winnemem Wintu Tribe, Doc. 474. All parties filed replies. Docs. 487, 492, 513, 515. These cross motions, which included over 700 pages of briefing and thousands of pages of supporting declarations and exhibits, came on for hearing on December 16 and 17, 2010.
II. BACKGROUND
A. The Listed Species.
1. Sacramento River Winter-Run Chinook Salmon.
Sacramento River winter-run Chinook salmon (Oncorhynchus tshawytscha) ("winter-run") is listed as "endangered" under the ESA. 70 Fed.Reg. 37,160 (June 28, 2005). Historical winter-run population estimates were as high as approximately 230,000 fish in the 1960s, BiOp at 82, but declined to under 200 fish in the 1990s. Id. at 81 . In recent years, population surveys of winter-run estimated a high of 17,344 fish in 2006, followed by a decline in 2007 (2,542 fish) that persisted into 2008 (2,830 fish). Id. [2]
*814 Adult winter-run Chinook salmon migrate upstream from the Pacific Ocean through the Bay-Delta estuary during November through July, moving upstream past Red Bluff Diversion Dam ("RBDD") from mid-December through early August, with peak passage occurring in mid-March. BiOp at 80. Spawning typically occurs in the mainstream Sacramento River downstream of Keswick Dam during April through August, with the greatest spawning activity typically taking place during May and June. Id.
Winter-run fry begin to emerge from the gravel beds where eggs are laid in late June and early July, continuing through October. Id. Juvenile rearing and emigration typically occurs between July and February in the upper Sacramento River, with juvenile migration downstream past RBDD beginning as early as mid-July, peaking in September, and continuing through March in some years. Id. at 80-81 .
Juvenile winter-run occur in the Delta from November through May. Id.; Pac. Coast Fed'n of Fisherman's Ass'ns. v. Gutierrez ("Gutierrez II "), 606 F.Supp.2d 1195, 1216-17 (E.D.Cal.2008). Winter-run juveniles typically remain in the Delta until they reach a fork length of approximately 118 millimeters and are from 5 to 10 months of age. BiOp. at 81. Juveniles begin exiting to the ocean as early as November and continue to do so through May. Id.
Designated critical habitat for winter-run includes the Sacramento River, the Delta, and downstream bays to the Golden Gate Bridge. 58 Fed.Reg. 33,212 (June 16, 1993). Gutierrez II, 606 F.Supp.2d at 1217 . The following physical and biological features are identified as essential for the conservation of winter-run:
(1) access from the Pacific Ocean to appropriate spawning areas in the upper Sacramento River, (2) the availability of clean gravel for spawning substrate, (3) adequate river flows for successful spawning, incubation of eggs, fry development and emergence, and downstream transport of juveniles, (4) water temperatures between 42.5 and 57.5°F for successful spawning, egg incubation, and fry development, (5) habitat areas and adequate prey that are not contaminated, (6) riparian habitat that provides for successful juvenile development and survival, and (7) access downstream so that juveniles can migrate from spawning grounds to San Francisco Bay and the Pacific Ocean.
BiOp at 90. Currently, the value of winter-run critical habitat is "degraded," by, among other things, the presence of dams, temperature control issues on the upper Sacramento River, unscreened diversions, and degraded spawning and riparian habitat. Id. at 93.
2. Spring Run Chinook.
Central Valley spring-run Chinook salmon (O. tshawytscha) ("spring-run") is listed as "threatened" under the ESA. 71 Fed. Reg. 834 (June 5, 2005); 70 Fed.Reg. 37160 (June 28, 2005) (critical habitat designated). There are three "independent" populations of spring-run, located on Butte, Deer and Mill Creeks, several "dependent" populations (which rely on the three independent populations for continued existence), and a population of hatchery fish from the Feather River Hatchery (FRH). BiOp at 93-94.
Spring-run Chinook have been declining over recent years. The Central Valley as a whole is estimated to have supported spring runs as large as 600,000 fish between the late 1880s and 1940s. Id. at 94 . *815 The 2007 escapement was 7,819 for all tributary populations (all independent and dependent populations, excluding those fish returning to FRH). Id. at 97 .
Adult spring-run enter freshwater in the spring, beginning in late January, entering the Sacramento River between March and September, primarily in May and June, and entering spawning grounds between mid-April and mid-June. Id. at 93 . Adults hold over the summer in cool, high elevation streams while they sexually mature, and then spawn in the fall, between September and October, depending on water temperatures. Id. at 93 .
Juveniles typically spend a year or more in freshwater before emigrating to the ocean. Id. at 93 . The emigration period for spring-run extends from November to June and is highly variable. Id. at 94 .
Designated critical habitat for spring-run includes the Sacramento River, tributaries supporting spring-run, the Delta, and downstream bays to the Golden Gate Bridge. Gutierrez II, 606 F.Supp.2d at 1217 . The value of spring-run critical habitat currently is "degraded." BiOp at 101, 104.
3. Central Valley Steelhead.
Central Valley steelhead (O. mykiss) ("CV steelhead") is listed as "threatened" under the ESA. 71 Fed.Reg. 834 (Jan. 5, 2006). Wild CV steelhead are confined mostly to the upper Sacramento River and its tributaries. BiOp at 107. Recent surveys also have detected small, self-sustaining populations on the Stanislaus, Mokelumne, and Calaveras Rivers, as well as observations of juvenile steelhead on the Tuolumne and Merced Rivers. Id. These small populations make up the remaining representatives of the Southern Sierra Nevada Diversity Group ("SSNDG") of CV Steelhead. Id. at 198.
While there is limited information on population size, NMFS estimates that the current population for the entire distinct population segment ("DPS") [3] (including the SSNDG as well as all other populations) in the Central Valley is less than 3,628 spawning females, compared with 40,000 spawners in the 1960s. BiOp at 106. The CV Steelhead population has shown a pattern of negative growth since the late 1960s, and there is no indication that the trend has changed. BiOp at 108-09 & Figures 4-4 & 4-5.
CV steelhead generally leave the ocean from August through April and spawn from December through April in small streams and tributaries where cool, well-oxygenated water is available year-round. Id. at 104. Unlike Pacific salmon, steelhead are capable of spawning more than once before death. Although one-time spawners are the great majority, approximately 17.2 percent in California streams are repeat spawners. Id. at 103-104.
Steelhead eggs hatch approximately 30 days after spawning, and fry emerge from the gravel four to six weeks later into shallow areas where they feed. Id. at 105. Steelhead rear during the summer and emigrate "episodically" from their natal streams during fall, winter, and spring high flows. Id. at 106. Emigrating CV Steelhead use the lower reaches of the Sacramento River and Delta for rearing and as a migration corridor to the ocean. Id. Juvenile CV steelhead typically emigrate *816 through the Delta from late September through June. Id. at 105 (Table 4-6).
Approximately 80% of historical CV Steelhead range is blocked by dams. Id. at 109. CV steelhead critical habitat is degraded. Id. at 113.
4. Green Sturgeon.
The southern distinct population segment of the North American green sturgeon ("green sturgeon") (Acipenser medirostris) is listed as "threatened" under the ESA. 71 Fed.Reg. 17757 (Apr. 7, 2006); 73 Fed.Reg. 52,084 (critical habitat designated).
Green sturgeon are anadromous fish that spawn and rear in freshwater rivers and estuaries but spend most of their lives in the ocean. See BiOp at 114-15. They are a long-lived, slow-growing species. 68 Fed.Reg. 4,433, 4,436 (Jan. 29, 2003). Juvenile green sturgeon are present in the Delta year round. BiOp at 119.
There are no definitive population counts or figures for the Southern DPS green sturgeon. Evidence available at the time the BiOp was written suggests that the population in the Delta watershed is "relatively small," ranging from several hundred to a few thousand adults. Id. at 124.
Critical habitat for the Southern DPS of green sturgeon was proposed on September 8, 2008, 73 Fed.Reg. 52,084, but had not been adopted as of the issuance of the BiOp. Proposed critical habitat included "approximately 325 miles of riverine habitat and 1,058 square miles of estuarine habitat in California, Oregon, and Washington, and 11,927 square miles of coastal marine habitat off California, Oregon, and Washington within the geographical area presently occupied by the Southern DPS of green sturgeon." BiOp at 126. In addition, approximately 136 square miles of habitat within the Yolo and Sutter bypasses, adjacent to the Sacramento River, are proposed for designation. Id. The BiOp concluded that the current condition of proposed critical habitat for the Southern DPS of green sturgeon is "degraded over historical conditions." Id. at 134.
5. Southern Resident Killer Whale.
The Southern Resident DPS of killer whale (Orcinus orca) ("Southern Residents") was listed as "endangered" under the ESA on November 18, 2005, 70 Fed. Reg. 69,903 (Nov. 18, 2005), and the DPS is designated as "depleted" under the Marine Mammal Protection Act. BiOp at 158-59. Southern Residents are found throughout the coastal waters off Washington, Oregon, and Vancouver Islands and are known to travel as far south as central California. Id. at 159 .
The BiOp addresses the impact of Project operations on Southern Residents and concludes that extinction of winter-run and spring-run Chinook salmon, as well as reductions in fall-run [4] Chinook salmon populations, "would reduce prey availability and increase the likelihood for local depletions of prey in particular locations and times," which would, in turn, increase the risk of extinction of the Southern Residents. BiOp at 573-74.
B. The 2009 Salmonid BiOp and RPA.
The 2009 Salmonid BiOp, prepared pursuant ESA § 7, 16 U.S.C. § 1536 (a)(2), concluded that "the long-term operations of the CVP and SWP are likely to jeopardize the continued existence" of the Listed Species and "destroy or adversely modify" critical habitat for winter-run, spring-run, and CV steelhead. BiOp at 575. As required by law, the BiOp includes an RPA designed to allow the projects to continue *817 operating without causing jeopardy to the species or adverse modification to its critical habitat. Id. at 575-671 . The RPA "is composed of numerous elements for each of the various project divisions and associated stressors," which, according to the BiOp, "must be implemented in its entirety to avoid jeopardy and adverse modification." Id. at 578 . The BiOp provides a succinct overview of the RPA:
There are several ways in which water operations adversely affect listed species that are addressed in this RPA. We summarize the most significant here:
1) Water operations result in elevated water temperatures that have lethal and sub-lethal effects on egg incubation and juvenile rearing in the upper Sacramento River. The immediate operational cause is lack of sufficient cold water in storage to allow for cold water releases to reduce downstream temperatures at critical times and meet other project demands. This elevated temperature effect is particularly pronounced in the Upper Sacramento for winter-run and mainstem spring-run, and in the American River for steelhead. The RPA includes a new year-round storage and temperature management program for Shasta Reservoir and the Upper Sacramento River, as well as long-term passage prescriptions at Shasta Dam and re-introduction of winter-run into its native habitat in the McCloud and/or Upper Sacramento rivers.
2) In Clear Creek, recent project operations have led to increased abundance of Clear Creek spring-run, which is an essential population for the short-term and long-term survival of the species. Nonetheless, in the proposed action, continuation of these operations is uncertain. The RPA ensures that essential flows and temperatures for holding, egg incubation and juvenile survival will be maintained.
3) Red Bluff Diversion Dam (RBDD) on the Sacramento River impedes both upstream migration of adult fish to spawning habitat and downstream migration of juveniles. Effects are significant for winter-run and spring-run, but are particularly pronounced for green sturgeon and its proposed critical habitat in that a significant portion of the population is blocked from its spawning and holding habitat. The RPA mandates gate openings at critical times in the short term while an alternative pumping plant is built, and, by 2012, opening of the gates all year.
4) Both project and non-project effects have led to a significant reduction in necessary juvenile rearing habitat in the Sacramento River Basin and Delta. The project's flood control operations result in adverse effects through reduced frequency and magnitude of inundation of rearing habitat. To minimize these effects, the RPA contains both short-term and long-term actions for improving juvenile rearing habitat in the Lower Sacramento River and northern Delta.
5) Another major effect of water operations is diversion of out-migrating juveniles from the north Delta tributaries into the interior Delta through the open DCC gates. Instead of migrating directly to the outer estuary and then to sea, these juveniles are caught in the interior Delta and subjected to pollution, predators, and altered food webs that cause either direct mortality or impaired growth. The RPA mandates additional gate closures to minimize these adverse effects to winter-run, spring-run, and steelhead.
6) Similarly, water pumping causes reverse flows, leading to loss of juveniles migrating out from the Sacramento River system in the interior Delta and more juveniles being exposed to the State and *818 Federal pumps, where they are salvaged at the facilities. The RPA prescribes Old and Middle River flow levels to reduce the number of juveniles exposed to the export facilities and prescribes additional measures at the facilities themselves to increase survival of fish.
7) The effects analysis shows that juvenile steelhead migrating out from the San Joaquin River Basin have a particularly high rate of loss due to both project and non-project related stressors. The RPA mandates additional measures to improve survival of San Joaquin steelhead smolts, including both increased San Joaquin River flows and export curtailments. Given the uncertainty of the relationship between flow and exports, the RPA also prescribes a significant new study of acoustic tagged fish in the San Joaquin Basin to evaluate the effectiveness of the RPA and refine it over the lifetime of the project.
8) On the American River, project-related effects on steelhead are pronounced due to the inability to consistently provide suitable temperatures for various life stages and flow-related effects caused by operations. The RPA prescribes a flow management standard, a temperature management plan, additional technological fixes to temperature control structures, and, in the long term, a passage at Nimbus and Folsom Dams to restore steelhead to native habitat.
9) On the Stanislaus River, project operations have led to significant degradation of floodplain and rearing habitat for steelhead. Low flows also distort cues associated with out-migration. The RPA proposes a year-round flow regime necessary to minimize project effects to each life-stage of steelhead, including new spring flows that will support rearing habitat formation and inundation, and will create pulses that cue out-migration.
10) Nimbus Fish Hatchery steelhead program contribute to both loss of genetic diversity and mixing of wild and hatchery stocks of steelhead, which reduces the viability of wild stocks. The Nimbus and Trinity River Hatchery programs for non-listed fall-run also contribute to a loss of genetic diversity, and therefore, viability, for fall-run. The RPA requires development of Hatchery Genetics Management Plans to improve genetic diversity of both steelhead and fall-run, an essential prey base of Southern Resident.
Id. at 576-78 .
III. STANDARD OF DECISION
Summary judgment is appropriate when the pleadings and the record demonstrate that "there is no genuine dispute as to any material fact and the movant is entitled to judgment as a matter of law." Fed.R.Civ.P. 56(c). The claims in this case involve NMFS's issuance of a biological opinion, final agency action subject to judicial review under the APA, 5 U.S.C. § 702 . Nat'l Wildlife Fed'n v. Nat'l Marine Fisheries Serv., 524 F.3d 917, 925 (9th Cir.2008) (" NWF v. NMFS II "). A court conducting APA judicial review may not resolve factual questions, but instead determines "whether or not as a matter of law the evidence in the administrative record permitted the agency to make the decision it did." Sierra Club v. Mainella, 459 F.Supp.2d 76, 90 (D.D.C. 2006) (quoting Occidental Eng'g Co. v. INS, 753 F.2d 766 , 769 (9th Cir.1985)). "[I]n a case involving review of a final agency action under the [APA] ... the standard set forth in Rule 56(c) does not apply because of the limited role of a court in reviewing the administrative record." Id. at 89. In this context, summary judgment becomes the "mechanism for deciding, as a matter of law, whether the agency action is supported by the administrative *819 record and otherwise consistent with the APA standard of review." Id. at 90.
IV. BASIC LEGAL FRAMEWORK
A. Review under the APA.
APA invalidation of a biological opinion requires Plaintiffs to prove that NMFS's action was "arbitrary, capricious, an abuse of discretion, or otherwise not in accordance with law." 5 U.S.C. § 706 (2)(A).
1. Record Review.
APA review of a biological opinion is "based upon the evidence contained in the administrative record." Arizona Cattle Growers' Ass'n v. U.S. Fish and Wildlife, 273 F.3d 1229, 1245 (9th Cir. 2001). Judicial review under the APA must focus on the administrative record already in existence, not some new record made initially in a reviewing court. Parties may not use "post-decision information as a new rationalization either for sustaining or attacking the agency's decision." Ass'n of Pac. Fisheries v. EPA, 615 F.2d 794 , 811-12 (9th Cir.1980). Exceptions to administrative record review for technical information or expert explanation make such evidence admissible only for limited purposes, and those exceptions are narrowly construed and applied. Lands Council v. Powell, 395 F.3d 1019 , 1030 (9th Cir.2005).
Here, as evidentiary rulings explained, see, e.g., Docs. 387, 392 (10/19/09 Hearing Transcript ("Tr.")), 406, 407, 462, 740 (7/8/10 Tr.), 750, expert testimony has been considered solely for explanation of technical terms and complex scientific subject matter beyond the Court's knowledge; and to understand the agency's explanations, or lack thereof, and the parties' arguments.
2. Deference to Agency Expertise.
A court must defer to the agency on matters within the agency's expertise, unless the agency completely failed to address some factor, consideration of which was essential to making an informed decision. Nat'l Wildlife Fed'n v. Nat'l Marine Fisheries Serv., 422 F.3d 782, 798 (9th Cir.2005) (" NWF v. NMFS I "). A court "may not substitute its judgment for that of the agency concerning the wisdom or prudence of the agency's action." River Runners for Wilderness v. Martin, 593 F.3d 1064, 1070 (9th Cir.2010):
In conducting an APA review, the court must determine whether the agency's decision is "founded on a rational connection between the facts found and the choices made ... and whether [the agency] has committed a clear error of judgment." Ariz. Cattle Growers' Ass'n v. U.S. Fish & Wildlife, 273 F.3d 1229 , 1243 (9th Cir.2001). "The [agency's] action... need be only a reasonable, not the best or most reasonable, decision." Nat'l Wildlife Fed. v. Burford, 871 F.2d 849 , 855 (9th Cir.1989).
Id.
Although deferential, judicial review under the APA is designed to "ensure that the agency considered all of the relevant factors and that its decision contained no clear error of judgment." Arizona v. Thomas, 824 F.2d 745, 748 (9th Cir.1987) (internal citation and quotation omitted). "The deference accorded an agency's scientific or technical expertise is not unlimited." Brower v. Evans, 257 F.3d 1058, 1067 (9th Cir.2001).
[An agency's decision is] arbitrary and capricious if [it] has relied on factors which Congress has not intended it to consider, entirely failed to consider an important aspect of the problem, offered an explanation for its decision that runs counter to the evidence before the agency, *820 or is so implausible that it could not be ascribed to a difference in view or the product of agency expertise.
Motor Vehicle Mfrs. Ass'n of U.S. v. State Farm Mut. Auto. Ins. Co., 463 U.S. 29, 43 , 103 S.Ct. 2856 , 77 L.Ed.2d 443 (1983); see also Citizens to Preserve Overton Park, Inc. v. Volpe, 401 U.S. 402, 416 , 91 S.Ct. 814 , 28 L.Ed.2d 136 (1971) (reviewing court may overturn an agency's action as arbitrary and capricious if the agency failed to consider relevant factors, failed to base its decision on those factors, and/or made a "clear error of judgment"), overruled on other grounds by Califano v. Sanders, 430 U.S. 99, 105 , 97 S.Ct. 980 , 51 L.Ed.2d 192 (1977)).
More generally, "[u]nder the APA `the agency must examine the relevant data and articulate a satisfactory explanation for its action including a rational connection between the facts found and the choice made.'" Humane Soc. of U.S. v. Locke, 626 F.3d 1040, 1048 (9th Cir.2010) (quoting Motor Vehicle Mfrs. Ass'n, 463 U.S. at 43 , 103 S.Ct. 2856 ). "The reviewing court should not attempt itself to make up for an agency's deficiencies: We may not supply a reasoned basis for the agency's action that the agency itself has not given." Id.
B. General Obligations Under the ESA.
ESA Section 7(a)(2) prohibits agency action that is "likely to jeopardize the continued existence" of any endangered or threatened species or "result in the destruction or adverse modification" of its critical habitat. 16 U.S.C. § 1536 (a)(2).
To "jeopardize the continued existence of" means "to engage in an action that reasonably would be expected, directly or indirectly, to reduce appreciably the likelihood of both the survival and recovery of a listed species in the wild by reducing the reproduction, numbers, or distribution of that species." 50 C.F.R. § 402.02 ; see also NWF v. NMFS II, 524 F.3d 917 (rejecting agency interpretation of 50 C.F.R. § 402.02 that in effect limited jeopardy analysis to survival and did not realistically evaluate recovery, thereby avoiding an interpretation that reads the provision "and recovery" entirely out of the text). An action is "jeopardizing" if it keeps recovery "far out of reach," even if the species is able to cling to survival. NWF v. NMFS II, 524 F.3d at 931 . "[A]n agency may not take action that will tip a species from a state of precarious survival into a state of likely extinction. Likewise, even where baseline conditions already jeopardize a species, an agency may not take action that deepens the jeopardy by causing additional harm." Id. at 930 .
To satisfy this obligation, the federal agency undertaking the action (the "action agency") must prepare a "biological assessment" that evaluates the action's potential impacts on species and species' habitat. 16 U.S.C. § 1536 (c); 50 C.F.R. § 402.12 (a). If the proposed action "is likely to adversely affect" a threatened or endangered species or adversely modify its designated critical habitat, the action agency must engage in "formal consultation" with NMFS [5] to obtain its biological opinion as to the impacts of the proposed action on the listed species. See 16 U.S.C. § 1536 (a)(2), (b)(3); see also 50 C.F.R. § 402.14 (a), (g). Once the consultation process has been completed, NMFS must give the action agency a written biological opinion "setting forth [NMFS's] opinion, and a summary of the information on which the opinion is based, detailing how the agency action affects the species or its critical habitat." 16 U.S.C. *821 § 1536(b)(3)(A); see also 50 C.F.R. § 402.14 (h).
If NMFS determines that jeopardy or destruction or adverse modification of critical habitat is likely, NMFS "shall suggest those reasonable and prudent alternatives which [it] believes would not violate subsection (a)(2) of this section and can be taken by the Federal agency or applicant in implementing the agency action." 16 U.S.C. § 1536 (b)(3)(A). "Following the issuance of a `jeopardy' opinion, the agency must either terminate the action, implement the proposed alternative, or seek an exemption from the Cabinet-level Endangered Species Committee pursuant to 16 U.S.C. § 1536 (e)." Nat'l Ass'n of Home Builders v. Defenders of Wildlife, 551 U.S. 644, 652 , 127 S.Ct. 2518 , 168 L.Ed.2d 467 (2007).
1. Best Available Science.
Under the ESA, an agency's actions must be based on "the best scientific and commercial data available." 16 U.S.C. § 1536 (a)(2); 50 C.F.R. § 402.14 (g)(8) ("In formulating its Biological Opinion, any reasonable and prudent alternatives, and any reasonable and prudent measures, the Service will use the best scientific and commercial data available...."). A failure by the agency to utilize the best available science is arbitrary and capricious. See Gutierrez II, 606 F.Supp.2d at 1244 .
"The obvious purpose of the [best available science requirement] is to ensure that the ESA not be implemented haphazardly, on the basis of speculation or surmise." Bennett v. Spear, 520 U.S. 154, 176 , 117 S.Ct. 1154 , 137 L.Ed.2d 281 (1997).
While this no doubt serves to advance the ESA's overall goal of species preservation, we think it readily apparent that another objective [of the best available science requirement] (if not indeed the primary one) is to avoid needless economic dislocation produced by agency officials zealously but unintelligently pursuing their environmental objectives. That economic consequences are an explicit concern of the ESA is evidenced by § 1536(h), which provides exemption from § 1536(a)(2)'s no-jeopardy mandate where there are no reasonable and prudent alternatives to the agency action and the benefits of the agency action clearly outweigh the benefits of any alternatives. We believe the "best scientific and commercial data" provision is similarly intended, at least in part, to prevent uneconomic (because erroneous) jeopardy determinations.
Id. at 176-77, 117 S.Ct. 1154 .
A decision about jeopardy must be made based on the best science available at the time of the decision; the agency cannot wait for or promise future studies. See Ctr. for Biological Diversity v. Rumsfeld, 198 F.Supp.2d 1139, 1156 (D.Ariz.2002) (the best scientific and commercial data available standard "recognizes that better scientific evidence will most likely always be available in the future"). The "best available science" mandate of the ESA sets a basic standard that "prohibits the [agency] from disregarding available scientific evidence that is in some way better than the evidence [it] relies on." Am. Wildlands v. Kempthorne, 530 F.3d 991, 998 (D.C.Cir.2008) (internal quotation omitted).
What constitutes the "best" available science implicates core agency judgment and expertise to which Congress requires the courts to defer; a court should be especially wary of overturning such a determination on review. Baltimore Gas & Elec. Co. v. Natural Res. Defense Council, 462 U.S. 87, 103 , 103 S.Ct. 2246 , 76 L.Ed.2d 437 (1983) (a court must be "at its most deferential" when an agency is "making predictions within its area of special expertise, at the frontiers of science"). As explained in the en banc decision in Lands *822 Council v. McNair, 537 F.3d 981, 993 (9th Cir.2008), courts may not "impose on the agency their own notion of which procedures are best or most likely to further some vague, undefined public good." In particular, an agency's "scientific methodology is owed substantial deference." Gifford Pinchot Task Force v. U.S. Fish & Wildlife Serv., 378 F.3d 1059 , 1066 (9th Cir.2004).
"When specialists express conflicting views, an agency must have discretion to rely on the reasonable opinions of its own qualified experts even if, as an original matter, a court might find contrary views more persuasive." Lands Council, 537 F.3d at 1000 (quoting Marsh v. Oregon Natural Res. Council, 490 U.S. 360, 378 , 109 S.Ct. 1851 , 104 L.Ed.2d 377 (1989)). Mere uncertainty, or the fact that evidence may be "weak," is not fatal to an agency decision. Greenpeace Action v. Franklin, 14 F.3d 1324, 1337 (9th Cir. 1992) (upholding biological opinion, despite uncertainty about the effectiveness of management measures, because decision was based on a reasonable evaluation of all available data); Nat'l Wildlife Fed'n v. Babbitt, 128 F.Supp.2d 1274, 1300 (E.D.Cal.2000) (holding that the "most reasonable" reading of the best scientific data available standard is that it "permits [NMFS] to take action based on imperfect data, so long as the data is the best available"). NMFS "must utilize the best scientific... data available, not the best scientific data possible." Building Indus. Ass'n v. Norton, 247 F.3d 1241, 1246 (D.C.Cir.2001), cited with approval in Kern County Farm Bureau v. Allen, 450 F.3d 1072, 1080-81 (9th Cir.2006) ("Absent superior data occasional imperfections do not violate" the ESA best available data standard); see also Defenders of Wildlife v. Babbitt, 958 F.Supp. 670, 680 (D.D.C.1997) (best available science standard does not require "conclusive evidence," only that agency use best science available and not ignore contrary evidence).
The deference afforded under the best available science standard is not unlimited. For example, Tucson Herpetological Society v. Salazar, 566 F.3d 870, 879 (9th Cir.2009), held that an agency may not rely on "ambiguous studies as evidence" to support findings made under the ESA. There, in the context of an ESA § 4 listing determination, NMFS "affirmatively relie[d] on ambiguous studies as evidence of persistence (i.e., stable and viable populations), and in turn argue[d] that this `evidence' of persistence ... proves that the lizard's lost range is insignificant for purposes of the ESA." Id. The Ninth Circuit found this conclusion to be unreasonable because "[t]he studies do not lead to the conclusion that the [species] persists in a substantial portion of its range, and therefore cannot support [NMFS's] conclusion." Id. [6] ; see also Rock Creek Alliance v. U.S. *823 Fish & Wildlife Service, 390 F.Supp.2d 993, 1008 (D.Mont.2005) (rejecting section 7 biological opinion's reliance on a disputed scientific report, which explicitly stated its analysis was not applicable to the small populations addressed in the challenged opinion).
Alternatively, the presumption of agency expertise may be rebutted if the agency's decisions, although based on scientific expertise, are not reasoned, Greenpeace v. NMFS, 80 F.Supp.2d 1137, 1147 (W.D.Wash.2000), or if the agency disregards available scientific evidence better than the evidence on which it relies, Kern County Farm Bureau, 450 F.3d at 1080 .
Courts routinely perform substantive reviews of record evidence to evaluate the agency's treatment of best available science. The judicial review process is not one of blind acceptance. See, e.g., Kern County, 450 F.3d at 1078-79 (thoroughly reviewing three post-comment studies and FWS's treatment of those studies to determine whether they "provide[d] the sole, essential support for" or "merely supplemented" the data used to support a listing decision); Home Builders Ass'n of N. Cal. v. U.S. Fish and Wildlife Serv., 529 F.Supp.2d 1110, 1120 (N.D.Cal.2007) (examining substance of challenge to FWS's determination that certain data should be disregarded); Trout Unlimited v. Lohn, 645 F.Supp.2d 929 (D.Or.2007) (finding best available science standard had been violated after thorough examination of rationale for NMFS's decision to withdraw its proposal to list Oregon Coast Coho salmon); Oceana, Inc. v. Evans, 384 F.Supp.2d 203, 217-18 (D.D.C.2005) (carefully considering scientific underpinnings of challenge to FWS's use of a particular model, including post decision evidence presented by an expert to help the court understand the complex model, applying one of several record review exceptions articulated in Esch v. Yeutter, 876 F.2d 976, 991 (D.C.Cir.1989), which are similar to those articulated by the Ninth Circuit).
Courts are not required to defer to an agency conclusion that runs counter to that of other agencies or individuals with specialized expertise in a particular technical area. See, e.g., Am. Tunaboat Ass'n v. Baldrige, 738 F.2d 1013, 1016-17 (9th Cir.1984) (NMFS's decision under the Marine Mammal Protection Act was not supported by substantial evidence because agency ignored data that was product of "many years' effort by trained research personnel"); Sierra Club v. U.S. Army Corps of Eng'rs, 701 F.2d 1011 , 1030 (2d Cir.1983) ("court may properly be skeptical as to whether [the conclusions of an environmental impact statement prepared under the National Environmental Policy Act] have a substantial basis in fact if the responsible agency has apparently ignored the conflicting views of other agencies having pertinent experience[ ]"). A court should "reject conclusory assertions of agency `expertise' where the agency spurns unrebutted expert opinions without itself offering a credible alternative explanation." N. Spotted Owl v. Hodel, 716 F.Supp. 479, 483 (W.D.Wash.1988) (citing Am. Tunaboat Ass'n, 738 F.2d at 1016 ).
In Conner v. Burford, 848 F.2d 1441, 1453-54 (9th Cir.1988), the agency attempted to defend its biological opinions by arguing that there was a lack of sufficient information to perform additional analysis. In rejecting this defense, the Ninth Circuit held that "incomplete information... does not excuse the failure to comply with the statutory requirement of a comprehensive biological opinion using the best information available," and noted that FWS could have completed more analysis with the information that was available. Id. at 1454 .
In light of the ESA requirement that the agencies use the best scientific and commercial data available ... the FWS *824 cannot ignore available biological info or fail to develop projections of ... activities which may indicate potential conflicts between development and the preservation of protected species. We hold that the FWS violated the ESA by failing to use the best information available to prepare comprehensive biological opinions.
Id.
2. Best Available Science Standards and the Application of Analytical/Statistical Methodologies.
These above-described standards apply with equal force to the use and interpretation of statistical methodologies. As the D.C. Circuit in Appalachian Power Co. v. EPA, 135 F.3d 791 (D.C.Cir.1998), explained in reviewing a challenge to a decision of the Environmental Protection Agency ("EPA") under the "arbitrary and capricious" standard of review:
Statistical analysis is perhaps the prime example of those areas of technical wilderness into which judicial expeditions are best limited to ascertaining the lay of the land. Although computer models are "a useful and often essential tool for performing the Herculean labors Congress imposed on EPA in the Clean Air Act," [citation] their scientific nature does not easily lend itself to judicial review. Our consideration of EPA's use of a regression analysis in this case must therefore comport with the deference traditionally given to an agency when reviewing a scientific analysis within its area of expertise without abdicating our duty to ensure that the application of this model was not arbitrary.
Id. at 802 .
The model must fit the available data. See Nat'l Wildlife Fed'n v. EPA, 286 F.3d 554 , 565 (D.C.Cir.2002) (" NWF v. EPA ") (a court will only reject the choice of a model "when the model bears no rational relationship to the characteristics of the data to which it was applied"). For example, Oceana, 384 F.Supp.2d at 220 , rejected a challenge to NMFS's use of a particular analytical model that used data drawn from existing literature, even though experts "suggested that reliable take limits cannot be established without quantitative data gathered from `in-water' surveys." Although NMFS conceded "a thorough quantitative analysis based on empirical estimates of population size would be a superior way to analyze the impact [ ] on [the species]," it was undisputed that "given the paucity of information on sea turtles and the difficulties of using the data that does exist, [a] different or more complex model [than that used by NMFS] was not available and could not even be constructed." Id. (internal quotations omitted). Likewise, "the fact that a given model has some imperfections does not prevent it from constituting the `best scientific information available.'" Oceana v. Evans, 2005 WL 555416 , *16-*17 (D.D.C. Mar. 9, 2005) (citing 16 U.S.C. § 1851 (a)(2)) (approving NMFS's use of a model despite known limitations, where it was the only model available and the agency supplemented its analysis with other sources to address areas where the model was unable to make accurate predictions).
V. EXPORT PLAINTIFFS' & DWR'S CLAIMS.
A. Alleged Clear Scientific Errors Pertaining to Delta Operations.
A major premise of the BiOp is that pumping "causes reverse flows, leading to loss of juveniles migrating out from the Sacramento River system in the interior Delta and more juveniles being exposed to the State and Federal pumps, where they are salvaged [7] at the facilities." BiOp at *825 577. The effects analysis also concluded "that juvenile steelhead migrating out from the San Joaquin River Basin have a particularly high rate of loss due to both project and non-project related stressors." Id. at 577-78 . To mitigate for these impacts, the RPA "prescribes Old and Middle River flow levels to reduce the number of juveniles exposed to the export facilities and prescribes additional measures at the facilities themselves to increase survival of fish." Id. at 577 . In addition, "to improve survival of San Joaquin steelhead smolts," the RPA prescribes "both increased San Joaquin River flows and export curtailments." Id. at 578 .
Plaintiffs strenuously argue that NMFS made certain "clear" scientific errors in reaching the conclusion that exports adversely affect juvenile salmonid survival.
1. Challenged Statistical Methodologies.
a. Use of Raw Salvage in Figures 6-65 and 6-66.
NMFS relied on salvage data provided by Plaintiff-Intervenor, DWR, presented in Figures 6-65 and 6-66 of the BiOp:
*826
Id. at 361-62 . These figures were cited to demonstrate that "[l]oss of older juveniles at the CVP and SWP fish collection facilities increase sharply at [OMR] flows of approximately -5,000 cfs and depart from the initial slope at flows below this." Id. at 361 . Federal Defendants' cross motion explains that NMFS used this data to "help evaluate where along the spectrum of OMR flows any significant change in salvage could be observed." Doc. 477-1 at 53.
These figures, which are based upon average salvage figures over many years, use "raw" salvage numbers that are not scaled to reflect the size of the population from which the fish were salvaged at the time the particular sample was taken. Previous rulings in this and the related Consolidated Delta Smelt Cases have discussed at length why the use of such data is not consistent with standard practice in the fields of fish biology and population dynamics. See San Luis & Delta-Mendota Water Authority v. Salazar, 760 F.Supp.2d 855, 885-90 (E.D.Cal.2010). The May 18, 2010 Findings of Fact and Conclusions of Law Re Plaintiffs' Request for Preliminary Injunction ("PI Decision") in this case found:
125. ... The comparisons of salvage to negative OMR flows relied upon in the BiOp utilize raw salvage numbers, rather than scaling salvage to population size. See Doc. 179, Declaration of Richard B. Deriso at ¶¶ 3-5. Scaling salvage to population size is standard fisheries science practice and could have been accomplished for several of the Listed Species based on existing population data. See id. at ¶¶ 5-6. This failure is a fundamental and inexplicable error. Salvage may have been higher in some years simply because the population was higher, not because of any differences in negative OMR flows. Salvage may have been lower in other years because the population was lower. Dr. Deriso demonstrated the potential significance of this failure by plotting the population adjusted Juvenile Chinook Incidental take rate against OMR flow. Based upon this revised analysis for spring-run and winter-run, Dr. Deriso concluded that there is no statistically significant relationship between the take index and OMR flows. Id. at ¶ 6.
126. The BiOp's conclusions reached about the spring-run and winter-run Chinook failed to utilize the best available *827 scientific methodology, because population data was available at the time the BiOp was issued that would have permitted NMFS to perform the straightforward population adjustment required to conform to standard, generally accepted practices for fisheries population measurements utilized in their field of expertise. If, in those years when salvage was greatest, population sizes overall were 10 or 100 times larger than other years, the effects might not be jeopardizing. Without adjustment for population size, NMFS's reliance on that figure was arbitrary and capricious.
127. As to the CV steelhead, for which no population numbers are available, it is less clear whether the use of raw salvage numbers is always inappropriate. Figures 6-65 and 6-66 ambiguously reference monthly CVP and SWP "Older Juvenile Loss" on the y axis. Were most of the salvaged fish represented on these charts Chinook salmon? No reason is offered why NMFS did not segregate the steelhead figures from those of Chinook salmon. If the species had been evaluated separately, would it have been reasonable for NMFS to fail to adjust the steelhead figures for population size? Separate analysis was not done.
Consol. Salmonid Cases, 713 F.Supp.2d 1116, 1142-43 (E.D.Cal.2010) (emphasis added).
Federal Defendants attempt to explain their use of these figures in two ways. First, Jeffrey Stuart, NMFS Fisheries Biologist and the primary author of the Delta section of the BiOp, opines that "the general trend in fish loss should still be apparent regardless of scaling." Fourth Stuart Decl., Doc. 485 at ¶ 72. He insists that this data "indicates that additional loss of fish occurs with increasing export levels as measured by the OMR flow values." Id. This explanation simply defies common sense. When trying to discern trends from data points that range across many years, an obvious "confounding variable" is population size. A trend observed in data that is unsealed for population size may change or completely disappear when scaled for population size. See Deriso Decl., Doc. 440 at ¶¶ 13-31. Federal Defendants had the information needed to perform such a simple analysis of the available data, but did not do so, and unjustifiably relied on the unsecaled data to form a quantitative conclusion that salvage rates increased sharply above—5,000 cfs OMR. This was a clear scientific error.
Defendant-Intervenors argue that the agency cannot violate the ESA by failing to take an additional step to scale the salvage data to salmonid population abundance. They maintain that all the ESA requires is that NMFS consider the "available" evidence not that it create new data or "follow scientific practices defined by Export Plaintiffs experts." Doc. 484 at 51. It is true that the best available science standard does not require NMFS to create new data or apply new models to existing data, Building Indus. Ass'n, 247 F.3d at 1246 . However, here, NMFS put data to a use for which it is not appropriate, as it produces unreliable results. Cf. NWF v. EPA, 286 F.3d at 565 (a court may reject agency's choice of model when it "bears no rational relationship to the characteristics of the data to which it was applied"). Every biostatistics expert who presented evidence in this and related fish cases has agreed that it is wholly inappropriate and scientifically unreasonable to draw management conclusions from a plot comparing unscaled salvage data to OMR flows collected over a period of years when population varied. The agency is required to apply generally recognized and accepted biostatistical principles, which constitute best available science, in reaching its decisions.
*828 b. Was the BiOp's Reliance on Figures 6-65 and 6-66 Harmless?
Alternatively, Federal Defendants argue that any such error was harmless given the other record evidence that supports the BiOp's conclusions. No party has provided authority that a harmless error rule applies when the agency commits a substantive error under the ESA. [8] Arguendo, Defendants' alternative evidence is considered.
(1) Record Citations Provided by Mr. Stuart.
Mr. Stuart states: "[a]dditional assessment of the effects of the OMR flow levels on salmon loss was derived from data provided by NMFS staff for the BDCP. NMFS XXXXX-XXX; XXXXX-XXXXX; 90852-98." Fourth Stuart Decl., Doc. 485 at ¶ 73. These are several thousand pages of documents. Mr. Stuart does not explain how the voluminous referenced information was used or analyzed. It is impossible to determine whether these referenced pages provide a sufficient alternative basis for the BiOp's conclusions. NMFS has provided no explanation for an alternative to its scientifically unreliable conclusions. Humane Soc. v. Locke, 626 F.3d at 1048 (holding NMFS did not offer a satisfactory explanation for its findings); Am. Tunaboat Ass'n, 738 F.2d at 1016 (finding that despite broad discretion afforded NOAA, where record evidence detracts from that relied upon by the agency, a court may find the agency's decision arbitrary and capricious). Citing this information and then failing to explain it is arbitrary and capricious.
(2) Particle Tracking Model Results.
The BiOp also relied on outputs from computer model runs utilizing the so-called Particle Tracking Model ("PTM"). Export Plaintiffs' and DWR's 2010 PI Motion challenged the use of PTM, arguing that while PTM is useful to track the fate of neutrally buoyant particles, it does not accurately reflect the behavior of salmonids, which are strong, volitional swimmers. These challenges were rejected in the May 18, 2010 PI Decision on the grounds that the BiOp acknowledged the limitations of PTM and reasonably relied on PTM studies to support certain conclusions:
120. This is a dispute among scientists. While DWR criticizes PTM modeling, Stuart and NMFS recognized its limitations and found PTM studies helpful to support its conclusions that: (a) as exports increase, negative OMR flows also increase; and (b) that at Station 815 (the confluence of the Mokelumne River and the San Joaquin River), particle entrainment increases from 10% at -2,500 cfs, to 20% at -3,500 cfs, to 40% at -5,000 cfs, and 90% at -7,000 cfs. NMFS, through Mr. Stuart, took into account inherent differences in the movement of neutrally buoyant particles and their speed and direction of travel. Administrative law requires deference to the Agency. Additional record analysis is necessary to determine the extent of support for NMFS's additional opinion that exports affect salmonid survival.
Consol, Salmonid Cases, 713 F.Supp.2d at 1141 . These challenges are discussed in other sections of this decision. Here, it is sufficient to note that the PTM results are not a complete replacement for Figures 6-65 and 6-66, as they only explain how particles, not actual fish, would respond to increased OMR flow. Nor do Federal Defendants point to any other information in the record that delineates "where along the spectrum of OMR flows any significant change in salvage could be observed," the *829 purposes for which Federal Defendants use 6-65 and 6-66.
The same reasoning applies to acoustic tag studies and other data the BiOp relies upon. This other data was treated in the May 18, 2010 decision and below in greater detail. It is undisputed that none of these studies or additional data pinpoint for management purposes at what point negative OMR flows must be controlled. Doc. 347 ¶¶ 128-138.
It is not appropriate to speculate how NMFS's analysis and/or conclusions would have changed had the data used in figures 6-65 and 6-66 been scaled to population size. This must be done on remand.
Whether there is sufficient data to scale CV steelhead salvage information to population size is unclear. Compare BiOp at 107 (discussing existing population data and difficulties posed by "lack of monitoring program") with Doc. 431 at 11 (citing Burnham Decl., Doc. 439 at ¶ 42 ("NMFS has access to the number of hatchery-produced salmon each year"), for the proposition that NMFS had "readily available" data regarding how many CV Steelhead were released from hatcheries each year)). That scaling for population size may not be possible for all species may limit NMFS's efforts. If population data is unavailable for certain species, the agency must nevertheless explain how it can make management conclusions without such information. The extent to which any such limitations mitigate NMFS's failure to scale raw salvage data cannot be discerned from the present record.
(3) Figures 6-71, 6-72, and 6-73.
The BiOp also relies on a series of plots, taken directly from Reclamation's Biological Assessment ("BA" or "OCAP BA"), of monthly juvenile salmonid "loss" against average exports. The first set of plots, Figure 6-71, depicts loss of juvenile Chinook salmon versus average monthly CVP and SWP exports for a period from 1995 through 2007.
*830 BiOp at 370. This plot was specifically cited as quantitative evidence of a relationship between exports and loss at the pumps:
The CVP/SWP operations BA presented data that regressed the loss of older juvenile Chinook salmon against exports (figure 6-71) and found that a significant relationship existed. The relationship was stronger for exports at the SWP (p = 0.000918) than for exports at the CVP (p = 0.0187). The months of December through April resulted in the most informative relationship based on the historical number of older juvenile Chinook salmon salvaged each month and the relationship of each month to salvage and exports. Conversely, regressions performed for monthly salvage of YOY Chinook salmon against exports did not result in a significant relationship at either the SWP or CVP facilities....
Id. at 368-69. In this way, the BiOp used Figure 6-71 as quantitative evidence of a statistically significant connection between loss of older juvenile Chinook salmon and export levels. These plots suffer from the same flaw of misusing raw salvage data. They must be re-analyzed and explained on remand if they are to be used as scientific justification for the BiOp's conclusions.
Figures 6-72 and 6-73 present a more difficult issue, as they concern CV steelhead salvage, for which much less data is available. Figure 6-72 plots monthly CV Steelhead salvage (both clipped/hatchery and unclipped/wild [9] ) against exports:
Id. at 371. The BiOp indicates that these "regressions resulted in significant relationships *831 between exports and salvage of steelhead at the facilities, more so for the SWP than the CVP." Id. at 369. Figure 6-73 plots monthly CV Steelhead salvage against the monthly average export to inflow ratio, finding significant relationships:
Id. at 370-71. The 2010 PI Decision found that "[a]s to the CV steelhead, for which no population numbers are available, it is less clear whether the use of raw salvage numbers is always inappropriate." Consol. Salmonid Cases, 713 F.Supp.2d at 1143 . Export Plaintiffs do not explain how it would be possible to scale to overall population size the wild CV steelhead salvage data, referenced in Figure 6-73 as "unclipped" CV steelhead. However, plaintiffs point out that the exact number of hatchery CV steelhead released each year is known, and therefore argue that NMFS could have scaled the hatchery or "clipped" CV Steelhead data to population size. Doc. 431 at 11. Federal Defendants do not respond to this assertion. There appears to be no reason to distinguish between the clipped CV steelhead analyses and Chinook salmon analyses, for which population scaling is the best available scientific methodology.
More importantly, Federal Defendants do not explain how these figures, even if valid, serve the same purpose as Figures 6-65 and 6-66, 66, which were cited to demonstrate that "[l]oss of older juveniles at the CVP and SWP fish collection facilities increase sharply at [OMR] flows of approximately -5,000 cfs and depart from the initial slope at flows below this." Id. at 361.
None of the alternative bases offered by Federal Defendants are sufficient to render NMFS's reliance on Figures 6-65 and 6-66 "harmless error." The significance of *832 Mr. Stuart's voluminous record citations is unexplained. Neither the PTM Modeling Results, nor Figures 6-71, 6-72, or 6-73 provide alternative bases for NMFS's conclusions regarding the negative OMR flows below which loss of juvenile salmonids "increases sharply." Export Plaintiffs' motion for summary judgment that Federal Defendants acted unlawfully by relying on raw salvage analyses is GRANTED; Federal Defendants' and Defendant-Intervenors' cross motions are DENIED.
c. Separate Challenges to Statistical Analyses in Figures 6-71, 6-72, and 6-73.
Export Plaintiffs also maintain that all three sets of graphs misrepresent the statistical significance of the data because "the decision to divide the data by month created an arbitrarily large sample size." Doc. 431 at 10. According to Export Plaintiffs, this "produce[d] facially incredible P-values (the standard statistical measure of significance) that misrepresented the validity of the models that were fit to the data." Id. A P-value "represents the probability that the result obtained in a statistical test is due to chance rather than a genuine relationship between the variables." Burnham Decl., Doc. 439 at ¶ 43. Regression analysis is generally considered statistically significant when the P-value is smaller than 0.05. Id.
The upper right graph from Figure 6-72, which plots monthly SWP exports for January through May of 1998 through 2006 against the raw salvage of hatchery steelhead, presents a P-value of 0.XXXXXXXXXXXX. This is several million times smaller than 0.05. Dr. Burnham opines that while "[s]uch a P-value is not impossible ... it would be surprising and especially so with this graph" because "[t]he scatter of the data points indicates that the regression is not a very good fit." Id. at ¶ 44.
Dr. Burnham describes the R2 value of 0.62 as not very strong. The R2 value is a statistical measure of how well the regression explains the data. "Roughly speaking an R2 of 0.5 means that the regression accounts for 50% of the variation observed in the data, while the other 50% is explained by other, unknown factors. Generally speaking an R2 of 0.5 is considered weak, while an R2 of 0.8 or above is considered strong." Id. at ¶ 36.
Dr. Burnham opined that this high level of apparent "significance" is the result of treating each of the monthly export points as an independent data point, which increases the sample size and influences the P-value. Id. at ¶ 45. Because the monthly data is "highly correlated with each individual year, due to the unique natural conditions that characterize each year, such as the abundance of the salmon cohort, patterns of flow, changes in temperature, etc." Id. at 47. Dr. Burnham offers a helpful explanation of why this is a problem:
For example, a medical researcher could misrepresent the significance of a drug study by performing [a] test on 10 people, and then treating the results for each individual person as if that person was 100 people. If the initial result of the test on 10 people was that 80% had been cured by the drug, nothing would change by acting as if the test had been performed on 1000 people: 80% would still be cured. However, the study would appear more significant because of the claim the results were true for a 1000 people rather than 10 people.
Id. at ¶ 46. In the present case, Dr. Burnham opines that NMFS's approach caused the relationship between exports and salvage to "appear more significant than it really is," when in fact "the high salvage levels in [certain] years may have actually been primarily caused by one independent factor, such as a large hatchery release *833 that year." Id. at ¶ 49. The results of the "January Only" data depicted in red on Figure 6-73, are different, showing much higher P-values, with only one of the four graphs showing statistical significance. Id. at 51.
Mr. Stuart responds to these critiques in his Fourth Declaration:
... Dr. Burnham critiques the statistical analysis of the data that was presented to NMFS in the biological assessment by DWR. NMFS reported the data presented by DWR in the BA as it was written without altering its content. While the probability of the regressions lines is unusual, having an unusually low "p" value, this is not a reason to completely disregard the data because the general trend of the lines is consistent with trends previously seen in consultations and reports provided to NMFS. This data is also consistent with the results of the radio tagged salmon studies conducted by Vogel in the South Delta in 2000 and 2001 in which tagged fish were drawn to the export facilities in higher numbers when exports were high as compared to lower levels of exports (Vogel 2002 cited in Vogel 2004). NMFS regarded the trends as more explanatory biologically than the accuracy of the statistical analysis being reported.
Doc. 485 at ¶ 75. Mr. Stuart now argues that the trend lines have biological significance even if the statistical analyses were incorrectly performed. Yet, the BiOp specifically emphasizes how these graphs demonstrated "significant relationship[s]" between the variables. See, e.g., BiOp at 369.
Mr. Stuart also provides a substantive rebuttal to Dr. Burnham's critique of the statistical analyses, premised on Dr. Burnham's argument that it was clear error to use monthly data points in the correlation analysis because they are highly correlated within years. Mr. Stuart opines that this premise is flawed because "[m]onthly exports do not necessarily correlate with each other between months or between years." Fourth Stuart Decl., Doc. 485 at ¶ 76.
For example, exports in March do not correlate with exports in April and May from 2000 to 2006, as Dr. Burnham has alleged, since exports are curtailed in April and May for the VAMP experiment during this time period. So regardless of what the March pumping rate is, the exports in April and May will be lower. Likewise, exports in January are allowed to reach a maximum of 65 percent of the inflow to the Delta, while exports from February through June are only allowed to reach a maximum of 35 percent of inflow.
Id. This provides a partial explanation for the statistical analyses.
This is an area of disagreement among experts. The agency is due deference in such circumstances, unless its experts' opinions are unsupported or wrong. Cactus Corner, LLC v. U.S. Dept. of Agric., 346 F.Supp.2d 1075, 1113 (E.D.Cal. 2004).
When specialists express conflicting views, an agency must have discretion to rely on the reasonable opinions of its own qualified experts even if, as an original matter, a court might find contrary views more persuasive.
Marsh v. Oregon Natural Resources Council, 490 U.S. 360, 378 , 109 S.Ct. 1851 , 104 L.Ed.2d 377 (1989) (explaining in the context of an agency's decision not to supplement a NEPA environmental impact statement that "courts should not automatically defer to the agency's express reliance on an interest in finality without carefully reviewing the record and satisfying themselves that the agency has made a reasoned decision based on its evaluation *834 of the significance-or lack of significance-of the new information" and noting that "[a] contrary approach would not simply render judicial review generally meaningless, but would be contrary to the demand that courts ensure that agency decisions are founded on a reasoned evaluation "of the relevant factors"").
This is a close call. Dr. Burnham's opinion suggests that it was unreasonable for NMFS to rely on the statistical analyses it performed. Mr. Stuart offers some explanation to counter certain aspects Dr. Burnham's critique, but does not satisfactorily explain the anomalous statistical results. Because the BiOp's reliance on these graphs must be remanded for other reasons, the agency must explain the flaws in its approach to the statistical analyses on remand.
2. Failure to Perform a Population-Level Quantitative Analysis.
Plaintiffs maintain that the BiOp violated the best available science requirement because it failed to employ a "population-level quantitative analysis." Doc. 431 at 15. It is undisputed that quantitative population dynamics models, or life cycle models, are the most reliable method to evaluate the impacts of various stressors on a fish population. This has been indisputably established in these related cases. Plaintiffs' expert Dr. Hilborn opined:
Life cycle modeling for salmonids is widely recognized as an available and necessary scientific tool, and is generally accepted in the scientific community as the best method for identifying the factors affecting fish population abundance and determining the significance or relative importance of distinct factors causing salmonid fish population increases or decreases.
Hilborn Decl., Doc. 443 at ¶ 5. The BiOp concedes that "[i]deally, a life cycle approach, in which the effects on individual life stages on the life cycle could be estimated independent of the effects on other stages, would be implemented to assess the relative impacts on abundance...." BiOp at 66.
However, such models only qualify as "best available science" where an appropriate model is available. [10] In the Consolidated Delta Smelt Cases, an appropriate smelt population dynamics was not available at the time the biological opinion in dispute in that case was issued:
The ESA does not require FWS[ ] to generate new studies. In Southwest Center for Biological Diversity v. Babbitt, 215 F.3d 58 (D.C.Cir.2000), the district court found "inconclusive" the available evidence regarding FWS's decision not to list the Queen Charlotte goshawk, and held that the agency was obligated to find better data on the species' abundance. The D.C. Circuit reversed, emphasizing that, although "the district court's view has a superficial appeal ... this superficial appeal cannot circumvent the statute's clear wording: The secretary must make his decision as to whether to list a species as threatened or endangered `solely on the basis of the best scientific and commercial data available to him....' 16 U.S.C. § 1533 (b)(1)(A)." Id. at 61 (emphasis added); see also American Wildlands v. Kempthorne, 530 F.3d 991, 998 (D.C.Cir. *835 2008) (the "best available data" standard "requires not only that the data be attainable, but that researchers in fact have conducted the tests").
Plaintiffs advocate a narrow reading of both Southwest Center and American Wildlands, arguing these cases only mean that the agency is not required to gather new data in the field regarding a species if such information is not already available. Doc. 697 at 22. Plaintiffs object that "[n]either of these cases supports Defendants' position that FWS could disregard the smelt abundance data that were already in its possession and fail to undertake the necessary statistical analyses to satisfy its statutory mandate to determine `whether the action... is likely to jeopardize the continued existence of the species.' 50 C.F.R. § 402.14 (g)(4)." Id.
Plaintiffs cite no authority suggesting that the non-existence of an analytical model should be treated any differently from the non-existence of raw field data. FWS did not have an off-the-shelf form of "statistical analysis" it could apply to determine the effects of Project Operations on the delta smelt population. Although life-cycle modeling is standard practice in the field of fisheries biology, and a life-cycle model is being (and should have been) developed for delta smelt, it is undisputed that an appropriate life cycle model had not been developed at the time the BiOp issued. FWS must apply the best "available" science; not the best science possible. FWS's failure to apply a life cycle model did not per se violate the ESA or the APA.
San Luis v. Salazar, 760 F.Supp.2d at 884-85 .
The 2010 PI Decision in this case found that Plaintiffs' were not likely to succeed on the merits of their life cycle modeling claim because they had not "present[ed] evidence that they, or anyone else[,] developed or made available to NMFS an appropriate life cycle model or the results of an appropriate life cycle analysis prior to the issuance of the BiOp." Consol. Salmonid Cases, 713 F.Supp.2d at 1132 . However, the PI Decision is not law of the case. S. Or. Barter Fair v. Jackson County, Or., 372 F.3d 1128 , 1136 (9th Cir.2004) ("[D]ecisions on preliminary injunctions are just that—preliminary—and must often be made hastily and on less than a full record.") (citing Univ. of Tex. v. Camenisch, 451 U.S. 390, 395 , 101 S.Ct. 1830 , 68 L.Ed.2d 175 (1981)).
Plaintiffs insist that NMFS did have access to "several fully featured quantitative life-cycle models[,] which had been specifically designed for use in the Delta...." Doc. 431 at 15. Plaintiffs focus on the Interactive Object-Oriented Salmon simulation ("IOS") model, developed by Bradley Cavallo, and the Oncorhynchus Bayesian Analysis ("OBAN") model, which was developed in coordination with NMFS. Id. at 19
a. IOS.
The BiOp discussed its decision not to use IOS, which was designed to evaluate the influence of different Central Valley water operations on the life cycle of winter-run using simulated historical flow and water temperature inputs." BiOp at 65.
NMFS did not use the results of the IOS model for our analysis in this Opinion because the intended application of the model in the CVP/SWP operations BA was not useful for estimating, in an overall sense, how winter-run might respond to the proposed action. For example, the CVP/SWP operations BA cautions the use of the IOS model results in making inferences related to how winter-run abundance is affected by the proposed action: "In evaluating effects of the proposed actions, differences *836 between the three studies rather than absolute trends should be examined" (Appendix O in CVP/SWP operations BA). Thus, it seems that the IOS model results presented in the CVP/SWP operations BA are not intended to reflect either abundance estimates observed in the past or future abundance with implementation of the proposed Project. Estimates based on observations are much different than estimates based on modeling without observation input. Results of the IOS model presented in the CVP/SWP operations BA show an increasing trend in winter-run escapement throughout the entire simulation period (i.e., from 1923 through 2002), such that by 2002, escapement is above 40,000 fish for all CALSIM II studies examined (figure 11-5 in CVP/SWP operations BA). Those results contrast with observed winter-run escapement estimates, which show a dramatic population crash during this period (see Grandtab at http://www.delta.dfg.ca.gov/afrp/), eventually leading to their endangered status under the ESA.
In the Opinion, NMFS must consider how winter-run is expected to respond to implementation of the proposed action. Model results, such as the IOS model results presented in the CVP/SWP operations BA, that are not intended to at least generally approximate past or future conditions, do not inform us in this consideration. If the IOS model results in the CVP/SWP operations BA are intended to be used strictly as an alternatives comparison tool, as the CVP/SWP operations BA indicates, instead of one that produces somewhat meaningful trend information for individual model runs, then the utility of those results for the Opinion is limited, particularly considering that a model alternative representing just baseline conditions does not exist. The CALFED Peer Review Panel stated that, "The default should be comparing the CALSIM studies of future scenarios (with different scenarios for climate change) to baseline" (Anderson et al. 2009). The context of this statement was that comparisons among alternatives such as those used in the IOS model (e.g., CALSIM studies 6, 7, and 8) are inconsistent with the Opinion's analytical approach. As such, NMFS did not use the IOS model results presented in the CVP/SWP operations BA as evidence for analyzing how winter-run will be affected by the proposed action.
Another consideration for not using the IOS model in the Opinion is that the model has not yet been published in peer reviewed scientific literature, and NMFS does not understand either the model's limitations or its extent. As described in Paine et al. (2000), mathematical models intended to help guide management of natural populations must be used wisely and with understanding of limitations. One potential limitation associated with applying large scale models over the entire life cycle of a species, as is done in the IOS model, is whether enough data are available to reliably estimate model parameters. Paine et al. (2000) state: "When the data are not available for the needed estimates of parameter values, there is a tendency to insert values based on opinion or expert testimony. This practice is dangerous. The idea that opinion and "expert testimony" might substitute for rigorous scientific methodology is anathema to a serious modeler and clearly represents a dangerous trend." With these considerations in mind, NMFS did not utilize the IOS model in this Opinion.
Id. at 65-65 (italics in original). It is ironic that NMFS's reverence for "rigorous scientific methodology" is honored in the breach by the agency's failure to utilize *837 the most rigorous method possible in the disputed BiOp.
Garwin Yip, supervisor for the Water Operations and Delta Consultations branch of NMFS's Sacramento Area Office, elaborated on the first explanation provided in the BiOp—that IOS estimates did not match actual historic winter run population levels—by pointing out that even Plaintiffs' expert Dr. Burnham stated that: "If the data does generally not match the model, then we know that our assumption is somehow incorrect and needs refinement." Yip Decl., Doc. 481 at ¶ 9 (citing Burnham Decl., Doc. 439, at ¶ 24). Mr. Yip points out that "[h]ad NMFS based our conclusion for winter-run on the quantitative approach of the IOS life cycle model results contained in the BA, we would have erroneously concluded that the proposed CVP/SWP operations would help a great deal in recovering the species, rather than jeopardizing it." Id. at ¶ 10.
Second, Mr. Yip points out that the CalFed Science Panel, in its review of the December 11, 2008, draft BiOp, discussed NMFS's decision not to use IOS in the BiOp and acknowledged that "the IOS model is relatively new and has not been extensively vetted and published, but all of these types of models are flexible and the Panel wonders if, with sufficient time and with some adjustments and modifications, whether a new version of the IOS could be used." Id. at ¶ 11 (citing AR [11] 00108178 (Anderson, et al. 2009)). The CalFed Science Panel did not recommend or encourage the use of IOS in its current state at the time the BiOp was being developed.
Mr. Yip points out that the NMFS Central Valley Office requested that NMFS's Southwest Fisheries Science Center ("NMFS-SWFSC") review various models, including IOS, for overall assumptions and limitations. According to Yip, NMFS-SWFSC "did not have the considerable staff resources and time it would take to adequately review and comment on the IOS model, it did have previous experience with similar models developed by Cramer Fish Sciences, and therefore, offered some comments." Id. at ¶ 12.
To adequately review such a model [IOS model] one must thoroughly examine the model's foundation, functional relationships, error structure, and parameter values in order to assess the quality of the model's resulting inferences. The range of elements incorporated in similar models developed by this contractor [Cramer Fish Sciences] is extensive, many of which are hypothetical in nature and remain the focus of active research. For those model elements that are well-founded, many of the parameter values will, given the data poor situation we find ourselves in, have been set using data from other populations, locations, species, or simply by assumption. Adequate review of the appropriateness of the assumed functional relationship and parameter values would require a significant amount of time.... Parenthetically, we note that the use of large and complex models in data-poor situations runs directly counter to the advice given to NMFS by expert scientific review panels concerned with salmon recovery.
AR XXXXXXXX-X (emphasis added).
NMFS contends that the IOS model was not available in a reliable, appropriate, and usable form at the time the BiOp was developed, and denies that IOS could have been adapted in a reasonable amount of time for use in the BiOp. NMFS knows all experts agree a life cycle model is the best methodology for measuring population effects. The agency continues to dodge serious *838 questions the parties are entitled to have answered by refusing employ existing models. At the same time, NMFS continues to plead poverty by describing this case as a "data-poor situation." If the data is so sparse that a workable model cannot be formulated, when does NMFS's failure to ensure appropriate data collection is taking place constitute bad faith? After more than five years of dispute, future pleas of data poverty will no longer be accepted.
As to the IOS model, although it is a close call, Federal Defendants' contention that IOS was not available in a reliable form at the time the BiOp issued has not been rebutted. Plaintiffs' motion for summary judgment that NMFS violated the ESA by failing to apply IOS in the BiOp is DENIED; Federal Defendants' and Defendant-Intervenors' cross motions are GRANTED.
b. OBAN.
Plaintiffs further argue that NMFS acted unlawfully by failing to apply the OBAN model in the BiOp. The BiOp mentions OBAN, but does not specifically address it, opting instead to generally explain that because existing life-cycle models only address population abundance, leaving out other aspects of the Viable Salmonid Population ("VSP") framework (e.g., spatial structure and genetic and life history diversity), the BiOp's analysis is superior because it encompasses these other factors:
An alternative approach recommended by the CALFED Science Review Panel for estimating an ASR for the Central Valley includes the use of computer models. In particular, the IOS model (Cavallo et al. 2008) and the Oncorhynchus Bayesian Analysis (OBAN) model (Hendrix 2008) were referenced as potentially useful tools. IOS is a detailed mechanistic model that describes the entire life cycle of both winter-run and spring-run in the Sacramento River, while the OBAN model is a Bayesian statistical model for winter-run in the Sacramento River. Although the CALFED Science Review Panel identified these models as potentially viable options either in combination or independently, it acknowledged the necessary refinement and implementation of this type of model by NMFS for the Opinion may not have been practical because of time constraints and the need for additional modeling expertise. Further development of mortality rates at different life stages specific to the Central Valley could be incorporated into the model to reduce the amount of assumptions currently required, and lead to more realistic and informative results. However, as previously mentioned, this type of information will not be available in the near term. Moreover, in order to sufficiently address the issue of fish routing through the Delta, identified as a critical component by the CALFED Science Review Panel, additional data collection and modeling over the long term (i.e., beyond the timeline allowed for the development of this Opinion) would be required.
As discussed above, this Opinion equates a listed species' probability or risk of extinction with the likelihood of both the survival and recovery of the species, and uses "likelihood of viability" as a standard to bridge between the VSP framework (McElhany et al. 2000) and the jeopardy standard. Assessing the viability of salmonid populations requires the consideration of other parameters in addition to population abundance, including productivity (i.e., population growth rate), spatial structure, and genetic and life-history diversity (McElhany et al. 2000). All four VSP parameters are deemed important in evaluating a population's ability to persist, especially when faced with catastrophic *839 disturbances (Lindley et al. 2007). Although the life cycle modeling approaches discussed above have the potential to provide information on all VSP parameters at some point in the future, it would require substantial data collection and model refinement. Any present attempt to complete such an exercise would only address one of those parameters (i.e., abundance), and any results would include making many assumptions. Therefore, although a method for evaluating impacts during a specific life stage in terms of the overall loss in numbers of fish would be useful, there are other potential consequences resulting from project operations that need to be considered. For example, are mortalities at different life stages, or the loss of historical habitats, likely to have effects on the other VSP parameters? The analyses within this Opinion, in an attempt to encompass this broader range of effects, focused on determining whether or not appreciable reductions were expected from the proposed action, rather than trying to quantify the absolute magnitude of those reductions.
Id. at 67-68.
NMFS staff from the Seattle office collaborated with Dr. Nobel Hendrix, the author of the OBAN model, during the model's development. AR 00050578. Throughout 2008, NMFS communicated with Dr. Hendrix about the model, AR XXXXXXXX-XX, and NMFS staff scheduled and attended meetings about the model, see, e.g., AR 00050874. NMFS requested that its own Science Center review the OBAN model. AR XXXXXXXX-XX.
Plaintiffs argue that Dr. Brian Wells, an NMFS fisheries biologist, described the OBAN model as "a great approach," AR 00050825, "a superior model design" and "well thought out," a model that "is the best approach laid out yet and deserves full attention," AR 00103798. Plaintiffs selectively quote Dr. Wells. For example, in a November 13, 2008 letter to Bruce Oppenheim, a NMFS biologist working on the BiOp, Dr. Wells did compliment the OBAN model:
Statistically, this is a superior model design because it integrates each life-history phase transition appropriately through a string of Beverton-Holt recruitment models [citations]. The approach is well thought out and, with appropriate data, could result in an intriguing model that will allow the user to determine the potential impact of management decisions at any given life-history stage on the ultimate production of the stock...
AR XXXXXXXXX. However, his next paragraph raises a concern about the available data set:
The only criticism I have for this approach is in the capacity of the dat[a] to address these questions. At each stage the data is compromised. For instance, Chipp's Island data does not allow for stock-specific allocation of production and ocean data is reliant on notoriously poor effort data which is not stock specific. Such data will undoubtedly reduce the precision of these models to predict the effects of variability at each life-history phase on the cohort and it is possible that the process error could become cumulatively greater as additional life stages are strung together. Having said that, this is the best approach laid out yet and deserves full attention. The author is clearly aware of the data limitations and through his approach has done the best to accommodate.
Id.
The model's own developer agreed with the Science Center's concern that OBAN contains "a lot of factors that are hypothesized to affect winter run relative to the *840 amount of data," and suggested that a "goal of the modeling effort is to identify some of the most important places to collect additional data. " AR 00054082 (emphasis added). As of February 2009, NMFS still had not received a clear response about whether appropriate and sufficient data were available to reliably model population dynamics using OBAN. AR 00070672 (indicating it "is uncertain as to whether appropriate and sufficient data are available to reliably model the population dynamics of winter-run Chinook salmon and spring-run Chinook salmon. If appropriate data are not available, application of the OBAN and IOS models to inform risk analysis may lead to erroneous management decisions. Before utilizing the OBAN or IOS models, it is necessary for PRD to gain further confidence in the various results each model can produce.").
Plaintiffs also do not address the 2010 PI Decision's finding that the application of population or life cycle models is not feasible for any analyses applicable to the CV steelhead, for which no population indices are available. Consol. Salmonid Cases, 713 F.Supp.2d at 1164 .
Federal Defendants also remonstrate that even if sufficient data had been available, email communications in late 2008 and early 2009, while the BiOp was being prepared, describe the model as still under development. See AR 00060571 (January 21, 2009 email discussing need to develop temperature metrics). The software needed to run the model was not available until late April 2009. AR 00086362 (April 20, 2009 workshop demonstrating new software for OBAN model).
Plaintiffs rejoin that "Defendants' principal criticism of the OBAN model ... that the data were incomplete ... suggests a fundamental misunderstanding of life-cycle modeling generally." Doc. 48 at 15. Plaintiffs characterize Defendants' position as based on an erroneous premise that a life cycle model can never be used unless and until it is fully and finally perfected, peer reviewed, and populated with perfect data." Id. Plaintiffs complain that this is an impossible standard that ignores the reality that perfect data does not exist and that modeling is an iterative process. For example, Dr. Hilborn opines that life cycle models are "always evolving and many times being challenged by models that make alternative assumptions." Hilborn Reply Decl., Doc. 496 at ¶ 26.
The standard scientific approach is a process of confronting competing models with data, not having a perfect and unchanging model. To suggest that a model is unavailable for use because it will require some adjustment or refinement ignores this reality.
Id. Dr. Hilborn pointed out that preliminary results from OBAN indicated that water temperature and harvest were the dominant factors affecting salmonid populations and that water exports was "not one of the most powerful explanatory factors." Id. at ¶ 25.
The record reflects that NMFS was working in late 2008 to integrate OBAN into the consultation process, see AR XXXXXXXX-XX; AR XXXXXXXX-XX, but that the agency elected not to make use of the model in the final BiOp approximately three months before the BiOp was issued, AR XXXXXXX-XX. Plaintiffs assert that this was unreasonable because OBAN was "fully functional and ready to be integrated into the BiOp." Doc. 487 at 16. Agency experts concluded that there was not enough data to reliably apply OBAN. [12]
*841 This is more disassembling by NMFS. Having not devoted necessary attention to OBAN, it rationalizes its doubts about the reliability of application of OBAN in the BiOp as not clearly erroneous. NMFS remains in the position where it can raise doubt about all conflicting science and hide behind the rubric it cannot be compelled to collect data or develop a model. Plaintiffs' motion for summary judgment that NMFS violated the ESA by failing to apply the OBAN model in the BiOp is DENIED and Federal Defendants' and Defendant-Intervenors' cross motions are GRANTED, but this is the last time NMFS will be permitted to avoid studying, analyzing, and applying a life cycle model. NMFS's chronic failure to do so now approaches bad faith in view of the undeniable importance of the information to resolve the perennial dispute over population dynamics. At some point, this diminishes the agency's credibility.
c. Ricker and/or Beverton-Holt Models.
Plaintiffs argue that, even if use of the IOS and/or OBAN models was not legally required, NMFS violated the ESA because it did not make use of certain "basic tools of fisheries management," such as the Ricker or Beverton-Holt models, two mathematical models developed in the mid-1900s. See Doc. 431 at 26. According to Plaintiffs' expert Dr. Burnham, these models make use of "simple mathematical expressions, based solely on past observations [that] combine all life history and environmental information into the period between parent spawners and the resultant returning spawners in the next generation." Burnham Decl., Doc. 439 at ¶ 18. According to another of Plaintiffs' experts, Dr. Ray Hilborn, these models are part of a "standard set of population dynamics models . . . that form the core of the body of knowledge" among fisheries biologists. Hilborn Reply Decl., Doc. 493 at ¶ 6. Dr. Hilborn concludes:
NMFS should have at the very minimum used simple multiple regression with Ricker or Beverton-Holt models (as discussed in the declaration submitted by Dr. Richard B. Deriso (Doc. 440-0)) to see if exports or OMR flows and other factors such as ocean harvest rates, ocean upwelling, and (for winter Chinook) water temperatures on the spawning grounds were related to the cohort replacement rates. Such an analysis can be done in a matter of hours, and NMFS has dozens of scientists at the Science Centers who could have done this analysis. I find no explanation in the BiOp or the administrative record why such an analysis was not performed. It is 1940s science, is available, and could have and should have been performed at the very outset of the BiOp.
Id. at ¶ 30.
NMFS's biologist Garwin Yip submitted a detailed response:
*842 23. Dr. Hilborn suggests that NMFS should have performed a statistical regression analysis to identify whether or not various environmental factors were related to, for example, the cohort replacement rate. Hilborn Reply Decl. ¶ 7, ¶ 30. While it's true that building a multiple regression model can be relatively simple and straightforward using available programs such as Excel, it is also true that many data are not suited for analysis with a straightforward multiple regression model. For example, Newman and Rice (2002, NMFS XXXXXX-XX) note that:
"The work of Kjelson et al. (1989) was closely scrutinized by numerous interested parties, and their methodology was criticized on a number of grounds. The assumptions and methods for estimating the indices, the application of standard linear regression to dependent variables ranging between 0 and 1, and the selection of covariates were major criticisms. In light of these criticisms, the interested parties chose to bring in statisticians previously unaffiliated with this work (namely, the authors) in an attempt to develop an alternative approach for modeling the release-recovery data. This article describes the resulting model. Although the approach here was quite different from that of Kjelson et al., some of our conclusions were quite similar-for example, the sizeable effect of water temperature."
NMFS 127364 . Indicative of the sophistication of the Newman and Rice (2002) analysis is the fact that it was published not in a fisheries or ecological journal, but rather in the Journal of the American Statistical Association.
24. Further warning of the potential pitfalls of using a "basic procedure" comes from p. 285 of Hilborn and Walters (1992), on the page immediately following the excerpt quoted by Dr. Hilborn, Hilborn Reply Decl. ¶ 7. After providing general equations for including multiple environmental terms in the Ricker and Beverton-Holt models, Hilborn and Walters (1992) ask "Why is this dangerous?" and proceed to say that "as tempting as it is to add environmental variables to stock-recruitment data, this is a potentially dangerous practice." On the same page, an explicit "warning" message reads "Be very, very cautious in fitting environmental variables, as it is almost impossible to make sure the apparent correlation is not spurious." (see Exhibit 1).
25. The devil is in the details, of course. I do not disagree with Dr. Hilborn's view that a basic regression analysis, possibly including an assessment of environmental terms in a standard stock-recruitment relationship, can be useful in many situations. However, in the specific case of evaluating the effects of CVP/SWP operations on cohort replacement rates of ESA-listed fish in California's Central Valley, I note that the "basic procedure" he suggests grows rather quickly either into a more complicated procedure, or into a "basic procedure" that relies on a set of assumptions that make interpretation and application of the analysis result more complicated. Consider, for example, a simple regression of cohort replacement rate (CRR) for winter-run Chinook salmon, against a single environmental factor. Below, I discuss several issues that would either complicate the analysis, or require simplifying assumptions: the interaction of age structure with the environmental variable of interest, and the selection of specific environmental measures.
26. First, how would the age structure of the spawning population in a given year be handled? One could, as did NMFS in the CRR summary provided in the status section for winter-run Chinook *843 salmon (BiOp at 83), assume that the spawning population was composed entirely of three year olds. Using this assumption, the CRR is calculated as the spawning population at time t divided by the spawning population at t-3. While this assumption keeps the life-history model simple, it introduces an inaccuracy into the estimate of cohort replacement rate (unless one makes yet additional assumptions), since the 2- and 4-year olds in the spawning population at time t have actually been produced by spawners at time t-2 and t-4, respectively. The assessment of potential environmental influences on CRR can also be affected by this assumption of no age structure in the spawning population, depending on the environmental factor being considered. For example, an assessment of attraction flows in year t (the year of return) as a factor affecting CRR would still be very appropriate, since all returning fish, regardless of age, would have experienced the flows observed in year t. In contrast, an assessment of OMR flows (or Sacramento River flow, or exports) during the juvenile outmigration period in year t-3 (the brood year) as a factor affecting CRR would be less appropriate, since the 2-and 4-year olds would not have experienced those OMR flows (or Sacramento River flow, or exports). Even if 3-year olds do make up the majority of spawners in a given year, 2- and 4-year old fish may well introduce sufficient mismatch into the model as to mask any environmental effect. Adjusting the model to allow appropriate matching of environmental factor with each age class of spawner leads down a yet more complicated analysis path.
27. Second, what measure would one use to assess "simple" effects like exports or OMR? Looking at row 16e of the stressor table for winter-run Chinook salmon (Table 9-1, BiOp at 452-460), one might choose to assess the impacts of OMR flows during the juvenile emigration period on CRR. Row 16e notes that OMR flows are a potential stressor in the Delta for juvenile winter-run Chinook salmon from November through May, so that's one possible averaging period, though clearly winter-run are more prevalent in the Delta in some months within that period than in others. Dr. Deriso, in his basic analysis of winter-run population growth rate against OMR flows, used the average OMR flow from December through March. Mechanistically, the impacts of OMR are likely to occur on the scale of days to weeks—it is not clear how to capture the effects of OMR variability at this temporal resolution in a model that (unless it is made more complex) calls for an environmental time series with a single value per year.
28. As described in the previous paragraph, a single, "simple" effect could be modeled in many ways. If one wants to consider additional effects (e.g., temperature during the spawning period, exports), each of which also can be modeled in various ways (and for factors such as temperatures, may have watershed-specific values), the possible list of environmental time series grows large very quickly. With this abundance of possible environmental effects, one needs to be very cautious about the risks of overfitting the model (which is an increasing risk as one includes more and more environmental factors into a single regression analysis) or the risks of increasing the Type 1 error rate by performing a large number of simple, single-factor comparisons. While there are various stepwise model-fitting procedures and multiple comparison procedures available to address these two issues, respectively, I note yet again that even the seemingly simple analysis proposed *844 by Dr. Hilborn requires a not insignificant set of assumptions.
29. NMFS did perform some basic analyses in evaluating effects of the projects, (e.g. for estimating reasonable OMR targets to manage entrainment), and has been roundly criticized by other plaintiffs' experts (e.g., Dr. Burnham, Dr. Deriso) for the statistical imperfections of those analyses. On the whole, NMFS used a mix of quantitative and qualitative analyses, including analyses provided in the BA and selected scientific literature, in order to come up with its assessment of project effects and the suite of actions necessary to avoid jeopardy.
Third Yip Decl., Doc. 518. The application of these "simple" models is not as straightforward as Plaintiffs claim. The law relegates their use and application to the discretion of the agency unless clearly erroneous. Plaintiffs have not demonstrated that NMFS's use or non-use of these models is more than scientific dispute, which is resolved in favor of the agency. A court cannot lawfully second-guess the agency, unless clear scientific error or bad faith is so manifest that the agency's judgments can no longer be trusted. Plaintiffs' motion for summary judgment that NMFS acted unlawfully by failing to use the Ricker and Beverton-Holt models is DENIED; Federal Defendants' and Defendant-Intervenors' cross motions are GRANTED. [13]
d. Does the Absence of a Quantitative Analysis Render the BiOp's Quantitative Limits Per Se Unjustified?
Plaintiffs argue that even if the BiOp's failure to apply quantitative life cycle modeling was not per se unlawful, the absence of such analyses "necessarily cripple[s] the specific quantitative limits imposed by the RPAs." Doc. 431 at 31. The Peer Review Panel addressed this issue:
The preparation of the RPAs shifts the questions from jeopardy/no-jeopardy to questions like: Will proposed export and other modifications in the Delta provide the expected benefit for targeted species? Will water withdrawals through a new pumping facility at Red Bluff impose new mortality on downstream migrants that largely offsets the reduced mortality from lifting the dam gates at RBDD? Will remedial actions be effective or will they become expensive projects that show little improvement in species status? How will specific RPAs affect other listed species (e.g., delta smelt) and unlisted species (e.g., fall-run Chinook salmon)?
Tier 1 comments, especially related to defining baseline and lack of quantitative integrative tools, become even more important in addressing these and similar RPA related questions. The long-term solution to this challenge is targeted research on the critical issues; careful monitoring of responses to implemented *845 actions; and further development of models for generating baseline conditions, downscaling temporally and spatially coarse outputs, and simulating life cycle dynamics. The modeling and monitoring before and after implementation of actions is needed to highlight or test key uncertainties and to increase our understanding of the system in order to facilitate improved management in the future. We believe that lack of quantitative integrative tools will hinder the development of RPAs because NMFS cannot presently quantify the relative contributions of the different project effects to population status nor can NMFS quantitatively determine the potential benefits of specific remedial actions to population recovery. Without this information, it is difficult to rank the many possible remedial actions by their biological effectiveness relative to their fiscal and social costs in order to logically develop an optimal mix of actions.
AR XXXXXXXX-XX (emphasis added). Although the Peer Review certainly warned of the pitfalls of attempting to formulate RPA's without "quantitative integrative tools," it acknowledged that the "long-term solution" was further development of modeling tools. The Peer Review did not outright advise the abandonment of quantitative RPAs in the short term. It did caution that the benefits cannot be quantified, nor can the fiscal and social costs.
For the purposes of this challenge to the BiOp and its RPAs, it is not appropriate or justified to find all the RPA Actions unlawful simply because Plaintiffs were not satisfied with the quantitative analyses performed in the BiOp. Each challenged RPA must be analyzed in light of the record evidence.
B. Baseline Analysis Challenges.
1. Failure to Distinguish Between Discretionary and Nondiscretionary Actions.
Plaintiffs opening brief advances an elaborate argument based on National Association of Home Builders v. Defenders of Wildlife, 551 U.S. 644 , 127 S.Ct. 2518 , 168 L.Ed.2d 467 (2007), which held that the ESA's consultation requirement was not triggered when an agency undertook nondiscretionary actions, because the agency has no choice. Plaintiffs argue that NMFS erred by failing to distinguish between the discretionary and nondiscretionary aspects of CVP and SWP project operations. Doc. 431 at 48-55. Although it is undisputed that Reclamation operates the project to fulfill certain mandatory water delivery obligations, Plaintiffs' argument that Home Builders should be extended to require NMFS to segregate discretionary from non-discretionary operations, placing non-discretionary ones in the "baseline" for purposes of evaluating the action's effect on the Listed Species, was rejected in a December 14, 2010 Memorandum Decision issued in the related Consolidated Delta Smelt Cases:
Plaintiffs complain that the BiOp's Project Effects analysis was "tainted" because it does not distinguish between discretionary and non-discretionary actions. [] National Association of Home Builders v. Defenders of Wildlife, 551 U.S. 644 , 127 S.Ct. 2518 , 168 L.Ed.2d 467 (2007), held that ESA § 7's consultation requirements do not apply to non-discretionary actions. Where an agency is required by law to perform an action, it lacks the power to insure that the action will not jeopardize the species. Id. at 667, 127 S.Ct. 2518 . Plaintiffs' cite the Coordinated Operations Agreement, the Central Valley Project Improvement Act's ("CVPIA") requirements *846 to deliver water for Central Valley wildlife refuge areas, and D-1641 as examples of mandatory aspects of Project operations that, they claim, should have been segregated from other Project Operations in the Project Effects Analysis.
However, Home Builders does not address whether, once section 7 consultation is triggered, the jeopardy analysis must separately identify and segregate discretionary from non-discretionary actions, relegating the non-discretionary actions to the environmental baseline. Home Builders addressed whether the section 7 consultation obligation attaches to a particular agency action at all. See Home Builders, 551 U.S. at 669-70 , 127 S.Ct. 2518 (holding that consultation "duty does not attach to actions. . . that an agency is required by statute to undertake. . . .") (emphasis added). Plaintiffs do not suggest that section 7 does not apply to the coordinated operations of the Projects. Rather, Plaintiffs contend that the section 7 consultation process requires distinguishing between discretionary and non-discretionary Project operations to identify the actions not subject to Section 7. Neither Home Builders nor the regulation interpreted in Home Builders , 50 C.F.R. § 402.03 , includes any such requirement. Plaintiffs' motion for summary judgment that the BiOp unlawfully failed to distinguish between discretionary and non-discretionary actions is DENIED. This does not mean non-discretionary actions required by law must not be considered in the consultation process. Federal Defendants and Defendant-Intervenors' cross-motion on identification of non-discretionary actions is GRANTED.
San Luis v. Salazar, 760 F.Supp.2d at 947-48 . Any voluntary efforts by NMFS to segregate discretionary from non-discretionary actions in the BiOp does not alter the fact that Home Builders imposes no legal obligation to do so.
Plaintiffs advance a related argument that even if Home Builders does not require segregation of discretionary from non-discretionary project operations in the BiOp, the ESA otherwise requires NMFS to consider only discretionary operations when evaluating the "effects of the action" vis-à-vis the environmental baseline. Doc. 431 at 55-58. This is based in part on the Science Panel's recommendation that NMFS model a baseline that represents a "hypothetical situation in which physical project infrastructure exists, but no project operations are performed except those mandated by prior agreements or those that are not part of the proposed actions." AR 00108175. The Panel offered:
For example, the decline of stream habitat because the dams block gravel recruitment from upstream would be part of baseline, as would providing water to fulfill senior water rights agreements. Modeling in the Delta seemed to use recent conditions rather than an estimate of baseline conditions (i.e., recent conditions minus effects of project-related actions). This definition of baseline was described in words (although too succinctly, in the opinion of the Panel) in the draft BO but never quantified with model results. This can be a serious omission because without a proper baseline, one struggles to make straightforward comparisons of scenarios that differ only by whether proposed project operations are included or not. Much of the draft BO involves comparing results of various simulations, but we had difficulty interpreting results without direct comparisons of the correct baseline to the correct baseline with project operations.. . . NMFS must clearly define the baseline used in analyses and explain why this baseline was used rather than *847 the baseline quoted above and seemingly required by the ESA.
Id. (emphasis added).
NMFS addressed this recommendation in the BiOp:
ESA regulations define the environmental baseline as "the past and present impacts of all Federal, State, or private actions and other human activities in the action area, the anticipated impacts of all proposed Federal projects in the action area that have already undergone formal or early section 7 consultation, and the impact of State or private actions which are contemporaneous with the consultation in process" (50 CFR 402.02). The "effects of the action" include the direct and indirect effects of the proposed action and of interrelated or interdependent activities, "that will be added to the environmental baseline" (50 CFR 402.02). Implicit in both these definitions is a need to anticipate future effects, including the future component of the environmental baseline. Future effects of Federal projects that have undergone consultation and of contemporaneous State and private actions, as well as future changes due to natural processes, are part of the future baseline, to which effects of the proposed project are added.
In consultations on continuing actions such as CVP/SWP operations, it is quite difficult to separate future baseline effects from the anticipated effects of the proposed action. Operations of existing structures, such as dams and gates, for water supply, flood control, and other purposes—the proposed action—are integrally related to the existence of the structures themselves, but effects of the mere existence of the structures are not effects of the proposed action. See National Wildlife Federation v. National Marine Fisheries Service, 524 F.3d 917, 930-31 (9th Cir.2008). Similarly, some activities that are part of the proposed project are non-discretionary, and their effects are also not effects of the proposed action. See id. at 928-29 (citing National Ass'n of Home Builders v. Defenders of Wildlife, 551 U.S. 644 [ 127 S.Ct. 2518 , 168 L.Ed.2d 467 ] (2007)[)]. Consequently, it is not surprising that in its review of NMFS' December 11, 2008, draft OCAP Opinion, the CALFED Science Review Panel (Anderson et al.2009) commented that a clearly defined baseline was lacking. Reclamation (2009) provided similar comments. NMFS acknowledges that it was not easy to discern a uniform approach to characterizing the environmental baseline in the draft Opinion. NMFS believes, however, that this is due to the nature of the action under consultation and available information, rather than a flawed approach to the analysis. NMFS clarifies its approach here and in relevant sections of the Opinion.
In National Wildlife Federation, a case regarding consultation on the effects of operating hydropower dams on the Columbia River, the 9th Circuit Court of Appeals rejected NMFS' attempt to narrow the "effects of the action" by defining the baseline to include operations that NMFS deemed to be "nondiscretionary." The Court observed that many of the actions NMFS deemed "nondiscretionary" actually were subject to the action agencies' discretion, and it held that it was impermissible to create an imaginary "reference operation" excluding these actions, to which the effects of the action could be compared. Rather, the Court said that the regulatory requirement to consider the effects of the action added to the environmental baseline "simply requires NMFS to consider the effects of [the] actions `within the context of other existing human activities that impact the *848 listed species.' [citations omitted]" Id. at 930. In other words, the effects of a particular Federal action are intended to be evaluated not simply on their own, but as they affect the species in combination with other processes and activities.
The question addressed in a consultation is whether the project jeopardizes the species' continued existence. As the court stated in National Wildlife Federation, even if the baseline itself causes jeopardy to the species, only if the project causes additional harm can the project be found to jeopardize the species' continued existence. Id. This determination requires an evaluation of the project's effects, separate from the conditions that would exist if the project were

[Text truncated at 120,000 characters. The full text is on the page linked above.]

---

Source: Frix Law Library, https://www.frixlaw.com/law-library/cases/2176473. Public record. Not legal advice.