Opinion ID: 3066157
Heading Depth: 3
Heading Rank: 1

Heading: The FWS’s choice of a more conservative model to

Text: calculate flow limits in Figures B-13 and B-14 was supported by substantial evidence Figure B-13 in the BiOp19 is a graph showing the relationship between salvaged adult delta smelt and the OMR flow, measured in cfs. The graph shows a positive correlation between salvaged smelt and the reverse flow of the river. That is, the greater the water pumped through the Jones and Banks pumping stations, the greater the count of smelt 19 Figures B-13 and B-14 are reproduced in the district court’s published opinion. Kempthorne, 506 F. Supp. 2d at 886–87. SAN LUIS V. JEWELL 57 salvaged at those stations. The FWS noted that the graph is upward sloping and linear in the lower half of the curve. At about !5,000 cfs there is a “break” in the data,20 and for flows more negative than !5,000 cfs (meaning more water exported from the Bay-Delta), the upward slope increases at an increasing rate. The FWS sought to verify whether the break in the data was actual. It conducted additional analyses of the data to verify that there was not a natural break at any other point and that any error in the OMR flow rates or salvage could not have caused the break. BiOp at 349–51. The FWS concluded that with “flows more negative than !1683, salvage increased.” BiOp at 351. The FWS stated that “[a] major assumption of this analysis is that as the population of Delta smelt declined, the number of fish at risk of entrainment remained constant.” BiOp at 349. What B-13 did was compare actual salvage numbers with OMR flow. What the FWS did not do—and what the appellees and the district court claim the FWS should have done—was prepare an additional figure in which it compared “normalized” salvage numbers with OMR flows. Normalized salvage would be the measure of the salvaged smelt divided by the total population of smelt,21 effectively 20 The break in the data in B-13 appears to span about !3,000 cfs to just under !6,000 cfs. BiOp at 348. The FWS did not attempt to quantify the break; it simply observed that there “appears to be a ‘break’ in the dataset at approximately !5,000 OMR.” BiOp at 347. 21 Part of the district court’s frustration may be that, to date, no one has been able to produce a reliable population estimate for the delta smelt. In 2007 when the district court sent the 2005 BiOp back to the FWS, it commented that 58 SAN LUIS V. JEWELL yielding figures showing what percentage of smelt each year were salvaged at the pumps. In fact, the FWS itself had stated that it could verify its conclusion “by normalizing the salvage data by the estimated population size based on the [Fall Midwater Trawl] data.” BiOp at 349. The peer review had similarly suggested normalizing the data: The Panel suggests that the use of predicted salvage of adult smelt should be normalized for population size. . . . One way to normalize The viability of Delta smelt has been under scrutiny for over ten years. No party has shown that producing a reliable population estimate is scientifically unfeasible. . . . Without population estimates, it is arbitrary for the agency to conclude that project operations will not result in jeopardy simply because the projects will take relatively fewer smelt than they did in the past, in the fact of the undisputed fact that the smelt population has been declining steadily in recent years. Failing to incorporate any information about smelt population abundance into the setting of the take limits is a fundamental failure rendering the BiOp arbitrary and capricious. Kempthorne, 506 F. Supp. 2d at 373. Despite the court’s warning, the FWS did not conduct a population study, nor did it explain why one could not be conducted. Yet, the FWS, its peer reviewers, and the district court’s experts suggested that there were proxies for population (such as the FMWT count) available, even if a strict population count was not. Sometimes we have to read the shadows to discern the reality behind it: Nearly twenty years after the smelt were declared endangered, we know the smelt population is continuing to decline and is imperiled, but still no one knows how many there are. It must tell us something about the difficulties that inhere in trying to count migrating, two-inch fish. SAN LUIS V. JEWELL 59 salvage for population size is to divide by the previous fall Midwater Trawl (MWT) index. A similar regression model to the one fitted to salvage would relate the normalized salvage to Old and Middle River (OMR) flows. . . . Expressing salvage as a normalized index may help remove some of the confounding of the temporal trends during the baseline period .... As the district court’s experts acknowledged, the FWS faces significant practical challenges in setting OMR flow rates to minimize delta smelt entrainment. For example, day-to-day variations in OMR flows and “noise” in smelt sampling22 used to establish abundance and distribution of the delta smelt are significant confounding factors in determining appropriate OMR flow rates, as is the distribution of the delta 22 “Noise” is a statistical term that refers to the unexplained randomness or variation that is found in a sample. It is of particular concern when statistical samples are small. As Dr. Quinn explained: [W]hat are the uncertainties in the population estimates themselves, and might there be shifting levels of accuracy as population levels change? . . . [It] is certainly true [that population growth rate is an appropriate and reliable measure of the population increases and decreases from year to year], if it is known without error but what are the assumptions about sampling? That is, as smelt become increasingly scarce, does their overall distribution become ‘thinner all around’ or is it ‘patchy’, and how might such changes influence the reliability of data from different surveys of abundance? In general, ‘noisy’ data make it more difficult to detect underlying patterns, even if the patterns are genuine. 60 SAN LUIS V. JEWELL smelt population in relation to the pumps. BiOp at 165, 331, 353–55. A lack of real-time information and variations inherent to environmental systems make precision virtually impossible. BiOp at 165, 331, 353–55. Yet, as even the district court recognized, population numbers of the delta smelt are perilously low, San Luis & Delta-Mendota, 760 F. Supp. 2d at 866, and entrainment by the pumping plants has a “sporadically significant influence on population dynamics,” id. at 877 (emphasis added). In such circumstances, the FWS’s decision to use raw salvage data rather than population-adjusted salvage data reasonably protects the delta smelt population without regard to year-by-year fluctuation in population size. The BiOp notes that this decision was motivated by a concern for the absolute number of smelt entrained in the pumps, not the relative number of smelt: “The current population cannot tolerate direct mortality through adult entrainment at levels approaching even ‘moderate’ take as observed through the historic record of recent decades.” BiOp at 287. Thus, the RPA is designed to “reduce entrainment of pre-spawning adult delta smelt during December to March” and to “[m]inimize the number of larval delta smelt entrained at the facilities” by controlling OMR flow from March to June. BiOp at 280, 357. The analytical approach preferred by appellees and the district court is best gauged to measure the number of smelt entrained at the pumps relative to the population size. This may be a more accurate reflection of the relative impact of OMR flows on the smelt population, but it is not tailored to protect the maximum absolute number of individual smelt, as the BiOp’s approach is; the process of adjusting raw salvage for the smelt population size results in SAN LUIS V. JEWELL 61 normalized numbers, but it does so at the potential cost of minimizing the impact of each individual smelt lost.23 Our deference to agency determinations is at its greatest when that agency is choosing between various scientific models, as the FWS did in the present instance. See Nw. Coal. for Alts. to Pesticides, 544 F.3d at 1050. Facing great measurement uncertainty and a smelt population whose existence is threatened, the FWS chose to be conservative in setting the flow limits in Actions 1, 2, and 3. This choice was well within its discretion; the Supreme Court has held that an agency may choose to “counteract the uncertainties” inherent in its scientific analyses by “overestimat[ing]” known parameters without being unreasonable, Baltimore Gas & Elec. Co., 462 U.S. at 103, and we have upheld an agency’s reliance on models that “yield conservative data because the 23 Appellee-Metropolitan Water District uses “one of the data points located at about !5,000 cfs on Figure B-13” for the year 2000 as an example. An unusually high smelt salvage was observed in 2000, but, as Appellee indicates, the smelt population was also higher than usual in that year. Appellee argues that because “[i]t is to be expected that more fish would be salvaged in a year in which the population was extremely large,” the raw salvage number should be normalized for total smelt population. Accepting appellee’s argument that salvage rates should be normalized, the year 2000 would have actually represented a below average (normalized) salvage. Yet, it is undisputed that an extraordinary number of smelt were salvaged in that year. A normalized analysis of smelt salvage counts the year 2000 as a below-average year, while an analysis of raw smelt salvage counts the year 2000 as an above-average year. The FWS’s choice of analysis influences whether it is the OMR flow’s relative or absolute impact on smelt population that is prioritized. Thus, the quality of the statistical method is not the only relevant factor at play, as the district court erroneously concluded: the BiOp’s choice of one model over the other implicates significantly differing management policies. 62 SAN LUIS V. JEWELL models incorporate the higher of [known potential values] in assessing the overall risk,” Nw. Coal. for Alts to Pesticides, 544 F.3d at 1050. Likewise, we give the FWS great deference in its choice of scientific tools, and, in these circumstances, hold that the FWS did not act arbitrarily or capriciously in choosing an analytical tool that resulted in greater protections for the imperiled smelt population.24 24 The district court relied substantially on the testimony of its experts, Dr. Andre Punt and Dr. Thomas Quinn, in concluding that the BiOp’s reliance on Figures B-13 and B-14 was “scientifically unacceptable.” San Luis & Delta-Mendota, 760 F. Supp. 2d at 891. But these experts present a more nuanced view of the FWS’s use of Figures B-13 and B-14. The results confirm what the FWS had already said: that additional analyses using normalized data from B-13 could have informed the FWS’s conclusions. The experts noted that B-13 was a proper measure, although not the only, and perhaps not the preferable, measure. The experts also testified as to the need for the FWS to set some parameters on OMR flows, and the difficulty in figuring out precisely where the parameters should be. In response to the district court’s question whether it was “unreasonable for FWS to rely in part on the information represented in figure B-13,” Dr. Quinn answered that he did “not regard it as unreasonable for FWS to have relied in part on this figure and the data behind it.” But he cautioned that “[t]o rely entirely on it would, however, have neglected the complexities of the issue . . . . Both the number of fish salvaged and the proportion salvaged . . . are relevant, in my view, as are other kinds of information.” Dr. Punt had a similar reaction: “it was unreasonable . . . to have only relied on the information in Figures B-13 and B-14 rather than on an analysis in which salvage is expressed relative to population size.” (emphasis added). Moreover, although both experts had been critical of the FWS’s failure to run the additional numbers, both were cautious about what the normalized data might have shown, whether any hard conclusions could be drawn from any data set, and even whether normalized data would be preferable to the non-normalized data produced. Dr. Quinn acknowledged that even if the FWS had normalized the data in B-13, “plotting flow SAN LUIS V. JEWELL 63 against a salvage index might not fully capture the risk to the population.” With respect to what B-13 showed, Dr. Quinn cautioned that it was “unwise to overestimate the precision” of the data. He was not convinced that there was a “break” in the data, “though [his] basis for saying so [was] more intuitive than statistical.” He “emphasize[d] that any point value has a measure of arbitrariness. If !5000, then why not !4900 cfs? Given the many sources of variation in the data, it strikes me as necessary to set limits even though there may not be strong statistical basis for a particular figure rather than a slightly different one.” He concluded that although “the validity of [FWS’s] specific flow regimes [was] undermined by the incomplete analyses that were done on the available data,” it was “appropriate for the FWS to have some leeway in making decision and setting limits in their efforts to protect and recover listed species.” Dr. Punt went one step further, recognizing the advantage of non-normalized data: B-13, as it is produced in the BiOp, would be justified if “any entrainment, no matter how small relative to the total population size, has long-term consequences for the population size of delta smelt.” These responses from the experts question the FWS’s failure to expand its analysis and to normalize the data underlying B-13. Had it done so, the experts concluded, the FWS would have had a more complete sense of the relationship between OMR flow and salvage, although it is far from clear that that study would have affected the FWS’s conclusions. What the experts’ testimonies do not support is the district court’s overstated conclusion that the FWS’s “use of raw salvage in the analyses depicted in Figures B-13 and B-14 is scientifically unacceptable” or that “such metrics are meaningless as management tools.” San Luis & DeltaMendota, 760 F. Supp. 2d at 891. Were we only evaluating the experts’ opinion on the BiOp, we would face a difficult question as to the continuing validity of this aspect of the BiOp: it is clear that these two experts believed the BiOp to have fallen short in this analysis, although as Dr. Punt indicates, persuasive justifications exist for the BiOp’s reliance on non-normalized data. It is less clear, however, that the BiOp—even as seen through the eyes of Drs. Punt and Quinn—would be rendered arbitrary and capricious by a sole reliance on Figures B-13 and B-14. We need not reach this question, as we accept the opinions of the district court’s experts only insofar as they are persuasive and informative, and—as will be subsequently described—we independently conclude that 64 SAN LUIS V. JEWELL