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

Heading: The OMR flow limits exist as one part in a dynamic

Text: monitoring system that accounts for the smelt population as a whole29 As we have described, the FWS’s task of monitoring OMR flow and smelt population is a daunting one. The BiOp accounts for these challenges in a number of ways, including choosing conservative models so as to best meet its ESA obligations. One other way in which the BiOp addresses these practical difficulties is by integrating its various protections; the OMR flow limits exist as but one part of a complicated dynamic system. Another significant part of this system is a limit on the total allowable take of delta smelt: the incidental take limit (ITS). BiOp at 387. 29 We do not believe the BiOp’s OMR flow limits to be arbitrary and capricious for several alternative reasons previously described. But, even had the FWS relied entirely on Figures B-13 and B-14 in setting the OMR flow limits—it did not—and even if such total reliance would otherwise be arbitrary and capricious—it would not—we hold that the BiOp’s use of whole population numbers in the ITS fully supports its OMR flow limits. 72 SAN LUIS V. JEWELL The ITS influences OMR flow levels in two primary ways. First, the ITS is used to establish a “Concern Level” estimate to “help guide implementation of the RPA.” Id. By “indicat[ing when] salvage levels approach[] the take threshold,” the Concern Level acts “as an indicator that operations need to be more constrained to avoid exceeding the incidental take.” Id. If the Concern Level is actually reached, a meeting of the Smelt Working Group—a group comprised of interagency biologists who monitor delta smelt conditions and recommend OMR flow levels—is triggered. Id. Second, the ITS “functions as an action that influences operations under the RPA.” San Luis & Delta-Mendota, 760 F. Supp. 2d at 929. Pertinent to the present discussion, the ITS is used to set actual flow levels under the RPA in real time. BiOp at 352, 354, 357. The real-time actual flow levels are set and adjusted based on the input of the Smelt Working Group and Project operators—a group informed by the ITS. BiOp at 352, 354, 357. Thus, the actual OMR flow is highly influenced by the ITS, as these two provisions work together as part of the complex dynamic system established by the BiOp. This is relevant to the present discussion: even while the OMR flow limits, viewed in isolation, may not account for total smelt population in a manner acceptable to the district court, the ITS—and therefore the actual OMR flows—takes the total smelt population into account. The ITS establishes take limits that vary each year based on the preceding Fall Midwater Trawl index (FMWT), an abundance proxy for the delta smelt’s population size—and the proxy for population suggested both by the FWS and the court-appointed experts as they considered normalizing the data in B-13. BiOp at 287, 383–86. The ITS is calculated by SAN LUIS V. JEWELL 73 projecting future salvage from historic salvage in years with comparable flows to the RPA, BiOp at 384, and then scaling that number to overall abundance using the prior year’s FMWT, BiOp at 385. This procedure “yields a discrete value for take as salvage so that the adaptive process can operate relative to an estimate of the absolute number of fish extant in the system.” San Luis & Delta-Mendota, 760 F. Supp. 2d at 926–27. As such, the take limits are adjusted to reflect the best estimate of smelt’s existing population. BiOp at 354 (noting both salvage and population size as “important variables” in setting flow). Thus, in making real-time operational recommendations to implement the RPA, the BiOp relies on both raw salvage numbers and the whole smelt population. BiOp at 352. In conclusion, we agree that the FWS should have at least prepared a graph similar to B-13 based on normalized data or explained why it could not. Nevertheless, overall, its use of OMR flows is supported by substantial evidence in the record. As convoluted as the BiOp is, we can discern the path the agency took to arrive at the !5,000 cfs figure used in RPA Component 1 (Actions 1 and 2) and RPA Component 2 (Action 3). See Bowman Transp., Inc. v. Arkansas-Best Freight Sys., Inc., 419 U.S. 281, 286 (1974) (“[W]e will uphold a decision of less than ideal clarity if the agency’s path may reasonably be discerned.”). In the sense explained by Dr. Quinn, the BiOp’s choice of !5,000 cfs was arbitrary; that is, the FWS had to choose some number from a broad range—perhaps in the !4,000 cfs to !6,000 cfs range—and no graphs or charts were likely to give the FWS a precise number. In this sense, !5,000 cfs is arbitrary because no more precise number can be identified, and a number from the range must be selected; !5,000 is thus an arbitrary number because the FWS could also have chosen !4,999 or 74 SAN LUIS V. JEWELL !5,001 or some other number within the range. That !5,000 is arbitrary in this sense does not make the choice of !5,000 arbitrary in the sense captured by the APA; its decision was not the result of arbitrariness or caprice. The APA does not demand strict scrutiny. The FWS is charged with protecting the delta smelt, and it chose a reasonable figure. B. The 2008 BiOp’s Determination of X2 Was Not Arbitrary and Capricious The FWS found that Reclamation and DWR’s proposed operations “are likely to negatively affect the abundance of delta smelt” by “substantially decreas[ing] the amount of suitable abiotic habitat for delta smelt.” BiOp at 236–37. To address the loss of habitat, the FWS proposed in RPA Component 3 (Action 4) that in September and October, in years when the preceding precipitation and runoff period was defined as “wet or above normal,” Reclamation and the DWR must provide sufficient Delta outflow to maintain monthly average X2 no more eastward than 74 km from the Golden Gate in wet years and 81 km in “above normal” immediate water years. BiOp at 282, 369. The FWS had previously found that the amount and quality of spawning habitat available to delta smelt is linked to the location of X2. BiOp at 239–40. As we previously discussed, X2 represents the point in the Bay-Delta estuary where the salinity is two parts per thousand, and is the center point of the LSZ, which is considered suitable spawning habitat for the smelt. X2, in turn, depends on delta outflow, which is largely determined by the difference between the total inflow from the Sacramento and San Joaquin Rivers and the total amount of water exported through the Banks and Jones pumping SAN LUIS V. JEWELL 75 stations, which changes both annually and seasonally.30 BiOp at 236. As the BiOp found, “CVP/SWP operations control the position of X2 and therefore are a primary driver of delta smelt habitat suitability.” BiOp at 234. Because the location of X2 directly affects how much water can be exported to southern California for agricultural and domestic purposes, the determination of where X2 is located was critical to the parties. The district court found the BiOp was arbitrary and capricious with respect to the location of X2 on two grounds. First, the district court objected to the data the FWS used to locate X2. San Luis & Delta-Mendota, 760 F. Supp. 2d at 903–09. Second, it found that the actual location of X2 lacked support in the record. Id. at 910–13, 922–23. We will address each point in turn. 1. The FWS was not arbitrary and capricious in comparing DAYFLOW to CALSIM II The FWS used two sophisticated models to determine the impacts of past, present, and future operations of the Project on X2. The FWS chose a computer model called DAYFLOW, developed by DWR, to measure the historical environmental baseline, and a computer simulation model known as CALSIM II, developed jointly by DWR and Reclamation, to measure future operations. Id. at 896–98, 907. These models were used in a number of ways in the BiOp, and were important to the BiOp’s determination of the 30 It is more correct to think of X2 as a range of points rather than a single, fixed point in the estuary. As the BiOp points out, “X2 is strongly influenced by tidal cycles, moving twice daily up and downstream 6–10 km for its average daily location.” BiOp at 372. 76 SAN LUIS V. JEWELL impacts of Project operation on the location of X2. BiOp at 145.31 The DAYFLOW computer model uses past river flow, export pumping, precipitation, and estimated agricultural diversions from 1967–2007 to estimate the outflow from the Bay-Delta to the San Francisco Bay. This data was used by the BiOp as a “historic” baseline for X2. BiOp at 207. CALSIM II is a computer simulation model that uses Central Valley hydrology from 1922–2003 to simulate Project operations. Despite the fact that environmental regulation and non-Project water demands have historically changed, the CALSIM II model assumes that these factors are fixed in its modeling scenarios. BiOp at 207. This is in contrast with the DAYFLOW model, which, because it relies largely on actual reported data, does account for changes in regulations that impact water demand. DAYFLOW and CALSIM II also differ in other ways: for example, DAYFLOW uses historical data to provide daily simulations of operation whereas CALSIM II models Project operations on a monthly basis, and DAYFLOW calculates X2 location using a mathematical method known as the “KM” method whereas CALSIM II uses the “ANN” mathematical method. The BiOp, in analyzing the predicted location of X2, estimated that median X2 would move 10 to 15 percent farther upstream under the proposed action relative to the historic median X2 baseline. BiOp at 265; see also BiOp at 235. Appellees assert, however, that it is impossible to discern whether “this change was due to continued project operations into the future or whether the change was due to 31 Action 4, which involves the management of X2, was also significantly influenced by these models. SAN LUIS V. JEWELL 77 the modeling differences between the ‘historic’ Dayflowderived baseline and the Calsim II studies.” Appellees argue that a CALSIM II to CALSIM II comparison would have been preferable. The district court agreed, concluding that although the FWS had discretion to use a historical baseline model such as DAYFLOW, the FWS abused its discretion when it compared the two different models without discussing or accounting for the resulting bias. See San Luis & Delta-Mendota, 760 F. Supp. 2d at 902–05. Although the district court acknowledged that “no superior set of models have been identified,” it held that a calibration problem created by using DAYFLOW with CALSIM II made the FWS’s choice of methodology arbitrary and capricious and required correction or explanation. Id. at 877, 899, 909. We recognize that the CALSIM II to DAYFLOW comparison is not without its limitations, but hold that the FWS’s decision to use these two models together, even without further calibration, was not arbitrary and capricious.32 Because the FWS’s decision to use the DAYFLOW and CALSIM II models together is a “scientific determination,” Baltimore Gas & Elec. Co., 462 U.S. at 103, that “requires a 32 It is not clear from the record that the district court was correct in concluding that the FWS’s reliance on a comparison of CALSIM II and DAYFLOW models taints the BiOp’s conclusions regarding the impacts of Project operations on the location of X2, or regarding Action 4. See San Luis & Delta-Mendota, 760 F. Supp. 2d at 922–23. The FWS has indicated other possible bases for its conclusions. For example, the FWS refers to field sampling data, and not modeling results, as providing the basis for its conclusions about X2 conditions, at least in the fall. The BiOp also relies on historical data to demonstrate the upstream shift of fall X2 over time, BiOp at 237, 264, as well as the extent to which the Project operations influenced the upstream shift in fall X2, BiOp at 179–82, 236, 270. See also Note 33 infra. 78 SAN LUIS V. JEWELL high level of technical expertise,” Marsh, 490 U.S. at 377, we must be at our most deferential in reviewing this provision of the BiOp, Baltimore Gas & Elec. Co., 462 U.S. at 103. Therefore, the question, under the ESA is not whether the FWS should have conducted independent studies in lieu of DAYFLOW or CALSIM II, Sw. Ctr. for Biological Diversity, 215 F.3d at 60 (“[T]he Secretary has no obligation to conduct independent studies.”), but whether these models represent the “best scientific and commercial data [currently] available,” 16 U.S.C. § 1536(a)(2); Inland Empire Public Lands Council v. U.S. Forest Serv., 88 F.3d 754, 762 (9th Cir. 1996). Because we agree with the district court’s conclusion that “no superior set of models have been identified,” San Luis & Delta-Mendota, 760 F. Supp. 2d at 909, the only question is whether the FWS’s failure to calibrate the two models renders conclusions drawn from their evidence not merely “weak,” but “arbitrary and capricious.” Greenpeace Action v. Franklin, 14 F.3d 1324, 1336 (9th Cir. 1992) (noting that “the fact that the evidence [that an agency relies on] is ‘weak’” is not dispositive); see also Bldg. Indus. Ass’n of Superior Cal. v. Norton, 247 F.3d 1241, 1246–47 (D.C. Cir. 2001) (holding that the fact that the “studies the Service relied on were imperfect . . . alone is insufficient to undermine those authorities’ status as the ‘best scientific . . . data available’”). The FWS explained why it chose to use “a combination of available tools and data.”33 San Luis & Delta-Mendota, 33 The BiOp makes clear that the FWS did not rely exclusively on the CALSIM II/DAYFLOW comparison, but looked to previous government studies, and several peer-reviewed scientific studies: SAN LUIS V. JEWELL 79 760 F. Supp. 2d at 912; BiOp at 204–05. The BiOp explained that it used the DAYFLOW model as a baseline, rather than a different CALSIM II simulation, because when it compared a CALSIM II simulation of current Project operations to a CALSIM II simulation of past Project operations, it found that the two were “nearly identical,” despite the fact that past and current Project operations are significantly different. BiOp at 204–05. According to the BiOp, “changes were expected” between the two CALSIM II studies. BiOp at 204. Because that comparison did not yield significant differences, as the FWS anticipated, the BiOp concluded that “the CALSIM monthly simulation model does not capture a precise Delta operation.” BiOp at 204. These “inaccuracies in CALSIM [lead the FWS] to use actual data to develop an empirical baseline.” BiOp at 206. The FWS chose “the DAYFLOW database . . . and OMR data obtained from USGS.” BiOp at 206. The BiOp also noted that the CALSIM II simulation provided “an imperfect representation of the pre-POD [pelagic organism decline]” environmental situation and that supplemental analysis was needed “to compensate for this modeling limitation.” BiOp at 205. In This analysis of the effects of proposed CVP and SWP operations on the delta smelt and its critical habitat uses a combination of available tools and data, including the CALSIM II model outputs provided in the appendices of Reclamations’ 2008 biological assessment, historical hydrologic data provided in the DAYFLOW database, statistical summaries derived from 936 unique 90-day particle tracking simulations published by Kimmerer and Nobriga (2008), and statistical summaries and derivative analyses of hydrodynamic and fishers data published by Feyrer et al. (2007), Kimmerer (2008), and Grimaldo et al. (accepted manuscript). BiOp at 204. 80 SAN LUIS V. JEWELL other words, when the FWS used CALSIM II as both a baseline and as a predictor, it appeared to yield inaccurate results, so the FWS used the next best available baseline: the DAYFLOW model. Thus, the FWS explained: the “[CALSIM II] Study 7.0 was the model run that Reclamation and DWR thought best represented current operations, and was thus intended as a ‘current baseline.’ However, due to limitations of CALSIM II to accurately model actual operations, [the FWS] also used the 1967–2007 DAYFLOW summaries . . . to compare against CALSIM II outputs.” BiOp at 207. The district court acknowledged that “[t]he theoretical problems with using a Calsim II to Calsim II comparison were manifest,” yet it found that the “FWS’s decision to use a Calsim II to Dayflow comparison . . . without attempting to calibrate the two models . . . was arbitrary and capricious and ignored the best available science showing that a bias was present.” San Luis & Delta-Mendota, 760 F. Supp. 2d at 906–07. The evidence for the modeling bias in the CALSIM II/DAYFLOW comparison was not clearly identified in the comments sent to the FWS before it issued the BiOp, and the comments largely recommended correcting the bias by comparing one CALSIM II model to another CALSIM II model—precisely the comparison the FWS found flawed and inaccurate. For example, San Luis & Delta-Mendota Water Authority, one of the plaintiffs-appellees here, submitted extensive and thoughtful comments on a portion of the draft BiOp and peer review analysis. The water authority expressed its concern that it was “methodologically inappropriate to compare historical data to simulated data. Simulated data must be compared to simulated data.” The DWR advised the FWS of some of the same problems. In its comments on a portion of the draft BiOp, the DWR pointed SAN LUIS V. JEWELL 81 out that the model made assumptions that might not be borne out in the historical data and that “[g]reat caution should be taken when comparing actual data to modeled data.” Like the water authority, it too recommended that CALSIM II modeling “be used to compare one set of model runs to another.” In later comments, the DWR repeated its concern that the BiOp “compared model runs of future operation with historical conditions” and suggested that “[i]mpact analyses often compare only model scenarios to avoid these . . . problems.” The independent peer review panel also expressed some concern with comparing the historical baseline with the CALSIM II simulated results. It pointed out that the “large difference between [CALSIM II] results and the historical baseline conditions defined with data can confuse the comparisons of metrics . . . between a simulated study and historical baseline.” The panel suggested that “[i]deally, a model-simulated baseline should be available that is consistent with the historical data . . . . It is unfortunate that model-generated baselines with a high degree of reliability were not made available for this analysis.” The post-hoc views of the court’s experts reflect some similar concerns. Dr. Quinn agreed that a comparison between models with identical databases and assumptions was preferable, but advised that “[a]s long as we bear in mind the fact that these are two very different models, I do not see why we cannot compare them.” After discussing some of the data provided to him, he concluded that the outputs from the two models cannot be used interchangeably for estimating either X2 (in km) or flow (in cfs). This does not reflect any criticism of either model. Their inner workings are apparently quite different, as are 82 SAN LUIS V. JEWELL their fundamental purposes, as explained to us. However any comparisons between them must explicitly account for the differences. Similarly, Dr. Punt stated that [i]n principle, there is nothing wrong with fitting a model using a set of OMR/X2 values from one model and making predictions using OMR/X2 values which are based on the output from a different model, as long as the two sets of values are calibrated . . . . Dr. Punt noted that the FWS had articulated its assumptions and explained why he thought the FWS should have performed additional calibration: It is recognized in the record that the modeled X2 does not reflect the “historical” X2 (BiOp Figure E-28), and the BiOp does compare historical and CALSIM-predicted X2 values by month (Figure E-26). However, the BiOp does not make this comparison for comparable years. Failure to attempt examination of whether it is necessary to calibrate the historical data and the CALSIM output would not normally be considered appropriate scientific practice in the field. (internal citations omitted). We recognize that the FWS’s decision to compare its chosen baseline, produced by DAYFLOW, to its future projection, produced by CALSIM II, was not perfect—as SAN LUIS V. JEWELL 83 everyone has acknowledged. We nevertheless hold that this comparison was not arbitrary and capricious. The BiOp explained its assumptions and explained why it rejected the CALSIM-to-CALSIM comparison suggested by the DWR and others who reviewed the draft BiOp. The fact that the FWS chose one flawed model over another flawed model is the kind of judgment to which we must defer. As we said in Environmental Defense Center, Inc. v. EPA: “We defer to an agency decision not to invest the resources necessary to conduct the perfect study, and we defer to a decision to use available data unless there is no rational relationship between the means [the FWS] use[d] to account for any imperfections in its data and the situation to which those means are applied.” 344 F.3d 832, 872 (9th Cir. 2003) (citations omitted). “The existence of a flaw . . . does not require us to hold that the agency’s use of the model was arbitrary.” Am. Iron & Steel Inst. v. EPA, 115 F.3d 979, 1005 (D.C. Cir. 1997) (per curiam). Rather, we will “reject an agency’s choice of a scientific model ‘only when the model bears no rational relationship to the characteristics of the data to which it is applied.’” Nat’l Wildlife Fed’n v. EPA, 286 F.3d 554, 565 (D.C. Cir. 2002) (quoting Appalachian Power Co. v. EPA, 135 F.3d 791, 802 (D.C. Cir. 1998)); accord Envtl. Def. Ctr., 344 F.3d at 872. That is not the case here. The district court’s determination to the contrary was heavily influenced by experts supplied by the parties which, for the reasons that we have explained, was inappropriate. The record is less certain than the district court was willing to admit.34 That 34 The district court refers to testimony from the parties’ experts in terms that overstate what the record will bear. See, e.g., San Luis & DeltaMendota, 760 F. Supp. 2d at 909 (“undisputed expert testimony”), id. (“[A]ll experts in this case agree”), id. at 912 (“[u]ndisputed expert 84 SAN LUIS V. JEWELL appellees were able to produce post-hoc theories alluding to the possibility of bias from such a comparison does not invalidate the FWS’s choices where there is no indication that a failure to calibrate would do more than add an uncertainty factor to the results, as well as no indication that a de-biasing calibration is technically feasible. Under our deferential standard of review, we therefore hold that the FWS’s choice and use of models was based on the best available science. Ideally, the FWS would have thoroughly discussed its reasoning with regard to possible issues arising from the use of DAYFLOW with CALSIM II. But, the fact that the FWS’s explanation for its choices does not fully address every possible issue that flows from that choice does not render the FWS’s determination unreasonable or unsupported. We do not require agencies to analyze every potential consequence of every choice they make; to do so would put an impossible burden on agencies. Rather, “we review all agency choices with respect to models, methodologies, and weighing scientific evidence” to ensure that the agency’s “choices [are] supported by reasoned analysis.” Ecology Ctr. v. Castaneda, 574 F.3d 652, 665 (9th Cir. 2009). Particularly in an area as “unwieldy and sciencedriven” as this, the FWS’s statistical modeling “does not easily lend itself to judicial review.” Appalachian Power, 135 F.3d at 802; see id. (“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.”). “[T]hat some or many [experts] would disapprove [of the FWS’s] approach does not answer the question presented to us. In reviewing [the FWS’s BiOp], we testimony”), id. at 922 (“the Calsim II to Dayflow comparison has the potential to introduce significant, if not overwhelming, bias”). SAN LUIS V. JEWELL 85 do not sit as a panel of referees on a professional [scientific] journal, but as a panel of generalist judges obliged to defer to a reasonable judgment by an agency acting pursuant to congressionally delegated authority.” City of L.A. v. Dep’t of Transp., 165 F.3d 972, 977 (D.C. Cir. 1999). In this instance, the FWS has provided a reasoned analysis explaining why the DAYFLOW model was used as the baseline. Consequently, we hold that the FWS did not act arbitrarily and capriciously in relying on the CALSIM II and DAYFLOW models in evaluating the impacts of Project operations on the location of X2, or in justifying Action 4. 2. The BiOp sufficiently explained the fall X2 locations The district court held that the BiOp “fails to explain why it is essential to maintain X2 at 74 km and 81 km, respectively, as opposed to any other specific location.” San Luis & Delta-Mendota, 760 F. Supp. 2d at 923. Specifically, the court found the “Federal Defendants have not identified any record evidence that provides such an explanation. This total lack of explanation violates the APA[].” Id. at 922. With respect to the latter finding, the record is contrary to the district court’s finding. There is record support for the BiOp’s proposal. Whether the record will “explain why it is essential to maintain X2 at 74 km and 81 km . . . as opposed to any other specific location” is a different question. In fact, it is the wrong question. As we have previously explained, as the combined pumping operations of the SWP/CVP remove hundreds of thousands of gallons of fresh water from the Bay-Delta, X2—the salinity-defined location of the smelt’s primary spawning habitat—shifts eastward towards the delta. BiOp at 86 SAN LUIS V. JEWELL 373. As the ocean’s salty influence encroaches further upstream, it mimics drought conditions in the Bay-Delta, regardless of the previous season’s precipitation. BiOp at 271, 273–74 (plotting spring and fall X2 locations). Among other things, this has resulted in an increasing divergence between spring and fall X2 locations. The BiOp determined that the “long-term upstream shift in X2 during fall has caused a long-term decrease in habitat area availability for delta smelt,” and it set forth an adaptive management program to minimize the effects of Project pumping on X2: RPA Action 4. BiOp at 374. Action 4 targets the fall location of X2 during “wet” and “above normal” years: “the years in which project operations have most significantly adversely affected fall [X2 location].” BiOp at 373. Specifically, Action 4 requires that fall X2 be maintained at a location no greater than 74 km upstream from the Golden Gate Bridge following “wet” water years, and no greater than 81 km upstream following “above normal” water years. BiOp at 282–83. The BiOp includes a number of different explanations, both specific and general, for RPA Component 3 (Action 4)’s regulation of X2 location. First, as discussed in the previous section, the FWS used CALSIM II and DAYFLOW to give it a picture of where X2 was located. Those models predicted different values for the location of X2 based on differing assumptions. DAYFLOW relied on historical data, while CALSIM II predicted where X2 might be located based on future Project operations. The FWS found that the two models offered different estimates of X2 location, and that, in general, “CALSIM II modeled scenarios were 10–15 percent further upstream than actual historic X2.” BiOp at 235. Thus, “[m]edian historic fall X2 was 79 km, while median values for the CALSIM II modeled scenarios ranged from 87 SAN LUIS V. JEWELL 87 to 91 km. The CALSIM II modeled scenarios all had an upper range of X2 at about 90 km.” BiOp at 235. The FWS generated numerous figures and charts with information taken from these models, many of which graphed X2 location as a function of another variable. See, e.g., BiOp at 260–61, 265, 270, 281, 282, 283, 284, 285. The FWS’s graphing range for X2 location was 60–95 km, with most data points between 65–85 km, and a significant cluster between 70–85 km. BiOp at 270. Second, the data from the models was consistent with the FWS’s written finding that “[d]uring the past 40 years, monthly average X2 has varied from as far downstream as San Pablo Bay (45 km) to as far upstream as Rio Vista on the Sacramento River (95 km). . . . In general, delta smelt habitat quality and surface area are greater when X2 is located in Suisun Bay.” BiOp at 191. Elsewhere in the BiOp, the FWS found based on an outside scientific study that “prior to spawning entrainment vulnerability of adult delta smelt increased at the SWP and CVP when X2 was upstream of 80km.” BiOp at 219. Third, the BiOp pointed out that X2 varies in response to a number of factors, both natural and man-made. The natural factors include the tides and the spring inflow. The BiOp found that “X2 is strongly influenced by tidal cycles, moving twice daily up and downstream 6–10 km from its average daily location.” BiOp at 372. The spring runoff affects X2 as well. The BiOp found that “very high spring outflows have always pushed X2 far downstream resulting in delta smelt distributions distant from the influence of Banks and Jones.” BiOp at 221. Aside from CVP/SWP’s operations, there are other man-made factors to consider. For example, the Suisun Marsh Salinity Control Gates have historically been 88 SAN LUIS V. JEWELL operational for anywhere from 10 to 120 days a year. BiOp at 218. Operation of the salinity control gates may shift X2 as far as 3 km upstream. BiOp at 218; see also BiOp at 241, 243–44. The BiOp noted that the 3 km upstream shift was preferable to the “10–20 km shifts that have occurred for up to 120 or more days per year during late summer through early winter due to South Delta diversions.” BiOp at 219. Fourth, the BiOp also points out that not all habitats in the Bay-Delta are equally suited to the smelt, so that as X2 location shifts, the smelt may be affected by other factors as well. For example, as X2 location shifts, the delta smelt encounter changes in agricultural runoff; changes in turbidity, which affects smelt feeding and predation; and exposure to predators. E.g., BiOp at 372 (“the daily fluctuation in X2 around an upstream point such as Brown’s Island confines the [smelt] population to narrow channels, where delta smelt may be exposed to more stressors (e.g., agricultural diversions, predation) relative to a downstream X2”); BiOp at 238 (“[T]he eastward movement of X2 will shift the distribution of delta smelt upstream, and provide environmental conditions for nonnative fishes that thrive in stable conditions.” (internal citation omitted)). Thus, the BiOp points out that although CVP/SWP operations remain the most important factor affecting smelt habitat, BiOp at 177–79, “there is no single driver of delta smelt population dynamics,” BiOp at 238; see also BiOp at 202 (referring to “the multitude of factors that affect delta smelt population dynamics”). The smelt habitat is a complex and dynamic system. Fifth, because X2 varies not only with CVP/SWP’s operations, but with natural phenomena beyond the control of the agencies—such as the tides, the seasons, and the annual SAN LUIS V. JEWELL 89 rainfall—the FWS had a range of choices for X2. Its goal was to “move the habitat away from Delta impacts and into broader open waters west of Sherman Island.”35 BiOp at 373. Rather than trying to define a single point for X2, the FWS chose a range, and refined the range by whether the year was “wet” or “above normal.” We think there was ample evidence in the record to support the choice of X2 between 74 and 81 km, depending on the season. The district court’s finding that there was a “total lack of explanation” is belied by the record.36 It appears the district court focused on whether there was support in the record for the FWS’s choice of 74 km, as opposed to 73 km or 75 km, hence its decision to question whether the FWS had adequately explained “why it is essential to maintain X2 at 74km and 81km . . . as opposed to any other specific location.” San Luis & Delta-Mendota, 760 F. Supp. 2d at 923. This was not the district court’s responsibility. The ESA provides that Reclamation had to seek the FWS’s opinion to ensure that its operations were “not likely to jeopardize the continued existence of any endangered species or threatened species or result in the 35 Sherman Island lies at the confluence of the Sacramento and San Joaquin Rivers. The 74–81 km range selected by the FWS lies west of Sherman Island. 36 The district court’s conclusion is especially puzzling because it accepted a similar FWS finding in its prior decision. See Kempthorne, 506 F. Supp. 2d at 335, 380 (noting that a survey of delta smelt abundance “increases dramatically whenever X2 is located between Chipps and Roe islands,” and that “[w]hen X2 is located upstream of Chipps Island, smelt are vulnerable to entrainment and are located in an area that is not ideal for feeding or protection”) (citing the administrative record). See also BiOp at 114, 132. 90 SAN LUIS V. JEWELL destruction or adverse modification of habitat of such species.” 16 U.S.C. § 1536(a)(2). It is the FWS’s responsibility to set forth its opinion and “those reasonable and prudent alternatives which [the Secretary of the Interior] believes would not violate [§ 1536(a)(2)] and can be taken by [Reclamation].” Id. § 1536(b)(3)(A). A “reasonable and prudent alternative” is a flexible standard for the consulting agency; it is not the equivalent of the “least restrictive alternative,” which is the way the district court treated the inquiry. Sw. Ctr. for Biological Diversity, 143 F.3d at 523. Under the ESA, the consulting agency is “not required to explain why he chose one RPA over another,” nor is it “required to pick the best alternative or the one that would most effectively protect the [species] from jeopardy.” Id. Rather, the FWS “need only have adopted a final RPA which complied with the jeopardy standard and which could be implemented by the agency.” Id. Accordingly, it was error for the district court to hold that the FWS must “explain why it is essential to maintain X2 at 74 km and 81 km . . . as opposed to any other specific location.” San Luis & DeltaMendota, 760 F. Supp. 2d at 923. Even if we thought the ESA demanded the kind of precision insisted on by the district court, we believe there is an explanation in the record for the FWS’s choice of 74 km and 81 km as its seasonal parameters. And the explanation is both logical and simple: At 74 km there is a monitoring station for the Bay-Delta at Chipps Island; at 81 km there is a monitoring station at Collinsville. BiOp at 114, 132. In its comments to the FWS, the DWR questioned the feasibility of locating fall X2, “especially if the spring X2 location is SAN LUIS V. JEWELL 91 significantly west of Port Chicago.”37 The DWR was concerned with how the agencies would measure compliance with any standard selected by the FWS and pointed out that “it would be difficult to measure an X2 at 85 km, whereas it would be much easier to measure at Collinsville (81 km) or Emmaton (92 km).” Where X2 represents a range of choices, choosing an X2 that can be measured and enforced is a perfectly rational response. See Sw. Ctr. for Biological Diversity, 143 F.3d at 523. We recognize that the stakes are exceedingly high in this case, but we conclude that the FWS’s choice, given the record, represented a reasonable and prudent alternative. C. The BiOp’s Incidental Take Statement Is Not Flawed When the implementation of an RPA will cause “incidental take” of a species, defined as “takings that result from, but are not the purpose of, carrying out an otherwise lawful activity conducted by the Federal agency or applicant,” 50 C.F.R. § 402.02, the agency is required to provide an incidental take statement (ITS) that “[s]pecifies the impact, i.e., the amount or extent, of such incidental taking on the species,” 50 C.F.R. § 402.14(i)(1)(i); see 16 U.S.C. § 1536(b)(4)(C)(i). The FWS determined that “take of the delta smelt is likely to occur in the form of kill, capture (via salvage), wound, harm, and harass as a result of CVP/SWP operations within the action area,” BiOp at 286, and prepared an ITS, BiOp at 285–310. In the ITS, the FWS provided separate take limits for juvenile and adult smelt, noting that “individuals of the larval/juvenile lifestage are 37 The FWS did not set its fall X2 target at Port Chicago, which is west of the 74 km marker proposed by the FWS. 92 SAN LUIS V. JEWELL less demographically significant than adults.” BiOp at 289. The FWS used different data sets in determining these separate limits. As the ITS notes, “[t]he mean values from 2005–2008 were used as an estimate of [juvenile] take under the RPA,” BiOp at 289, while “[t]he average[] value for [water years] 2006 to 2008 was used to calculate prespawning adult delta smelt, BiOp at 287. In other words, the year 2005 was used in calculating the juvenile, but not the adult, take limit. BiOp at 287, 289. The ITS also acknowledges its limitations: there are numerous uncertainties inherent in the measurement of smelt take, and “salvage data (our most definitive measurement endpoint) reflects only a portion of the total mortality associated with entrainment.” BiOp at 383. The district court concluded that the BiOp’s ITS was arbitrary or capricious for two reasons: First, the district court found that the FWS failed to explain adequately its decision to use 2005–2008 salvage data when setting the incidental take limit for juvenile smelt, but to only use 2006–2008 salvage data when setting the incidental take limit for adult smelt. San Luis & Delta-Mendota, 760 F. Supp. 2d at 925–28. Second, the district court found that the FWS failed to explain its decision to rely on an average cumulative salvage index when it set a “Concern Level,” which, when triggered, requires the Smelt Working Group to make “an immediate specific recommendation to the [FWS].” BiOp at 387; see San Luis & Delta-Mendota, 760 F. Supp. 2d at 928–29. We hold that the ITS is not arbitrary and capricious because it includes adequate explanation and support for its determinations. SAN LUIS V. JEWELL 93 1. The ITS reasonably uses different data sets for adult and juvenile take limits First, the district court objected to the FWS’s choice of data. The ITS’s use of separate data sets to calculate the separate incidental take limits for juvenile and adult smelt is adequately explained in the ITS. In discussing the use of “[t]he mean values from 2005–2008” to calculate juvenile take limits, the ITS explains that “[t]he reason for selecting this span of years is that the apparent abundance of delta smelt since 2005 as indexed by the 20-mm Survey and the [Summer Townet Survey] is the lowest on record.” BiOp at 289. Accordingly, “[i]t was necessary to separate out this abundance variable, but also to account for other poorly understood factors relating salvage to OMR, distribution, and the extant conditions.” BiOp at 289. As noted elsewhere in the BiOp, “[i]n contrast to adult delta smelt, there is no well established index of larval and juvenile abundance to reliably scale the take of this lifestage to abundance. . . . This should be kept in mind . . . .” BiOp at 389. Therefore, faced with a greater degree of uncertainty in calculating juvenile incidental take, the FWS chose, conservatively, to incorporate an additional year of data—a year in which smelt abundance was “the lowest on record.”38 BiOp at 389–90. The BiOp is clear that it used 2006–2008 data for adults because “these years within the historic dataset best approximate expected salvage,” BiOp at 287, and 2005–2008 data for juveniles because juvenile smelt “are less demographically significant than adults,” BiOp at 289, and therefore a larger data set 38 This determination came on the heels of the district court’s invalidation of the 2005 BiOp’s ITS based on its failure to consider record-low population abundance in setting take limits. See San Luis & Delta-Mendota, 760 F. Supp. 2d at 918. 94 SAN LUIS V. JEWELL would be preferable.39 Such a decision to use a more conservative data set, when necessary, is exactly the sort that we afford agencies discretion to make. See, e.g., Fishermen’s Finest, Inc. v. Locke, 593 F.3d 886, 893, 896–97 (9th Cir. 2010) (upholding agency’s decision to rely on some data while disregarding other data). 2. The FWS reasonably uses an average cumulative salvage index Second, the district court objected to the FWS’s decision to use an average cumulative salvage index to create its “Concern Level.” BiOp at 387, 389–90. The Concern Level “indicate[s] salvage levels approaching the take threshhold.” BiOp at 387; see also BiOp at 289 (noting that the estimated number represents a concern level where “entrainment has reached high enough numbers to indicate the need for more protective OMR restrictions.”). When the Concern Level is reached, two actions follow: The Smelt Working Group must convene and make “an immediate specific recommendation to the [FWS],” and OMR flows may have to be adjusted “to a more restrictive level.” BiOp at 387. The Concern Level does not trigger automatic restrictions in OMR flows. It “may require” a reduction “unless available data indicate some greater level of exports is possible without increasing entrainment.” BiOp at 387 (emphasis added). The FWS’s decision to use an average in setting the incidental take limits is, like its choice of data sets, a choice 39 For similar reasons we disagree with the district court that the FWS must explain why it decided to include 2006 when it calculated larval/juvenile abundance. See San Luis & Delta-Mendota, 760 F. Supp. 2d at 917–18. SAN LUIS V. JEWELL 95 entitled to substantial difference. See The Lands Council v. McNair, 537 F.3d 981, 991 (9th Cir. 2008) (noting that it is “well-established law” that courts owe deference “to agencies and their methodological choices”). As appellees note, the ITS’s “use of averaging . . . provides an ‘estimate’ of expected take that, based on the historical record of salvage, when applied[,] would likely be exceeded in many years.” In other words, appellees object to the fact that the ITS’s choice of methodology results in too restrictive of a management regime. The district court agreed, finding that “[t]he record does not explain why an ‘averaging’ approach was used.” San Luis & Delta-Mendota, 760 F. Supp. 2d at 929 (“Based on known adverse water supply consequences of operating the Projects in a ‘constrained’ manner, it is inexplicable that the FWS did not provide a clear and rational explanation of how the ITS is set.”). We hold that the record offers an adequate explanation. As with its decision to use an additional year of data when calculating the juvenile take limit, the ITS’s use of an averaging methodology “counteract[s] the uncertainties” inherent in its analyses by “overestimat[ing]” known parameters. See Baltimore Gas & Elec. Co., 462 U.S. at 103. In the context of the ITS’s repeated recognition of the “difficult[y] [in] definitively project[ing]” the “specific level of take of adult delta smelt at the CVP/SWP pumping facilities . . . due to inherent uncertainties,” BiOp at 383, the FWS’s use of an averaging methodology—that, by its nature, yields conservative limits that otherwise would have been exceeded in eleven of the past sixteen years, San Luis & Delta-Mendota, 760 F. Supp. 2d at 929—is a discernable, and justified path. See Bowman Transp., 419 U.S. at 285–86; see also Nw. Coal. for Alternatives to Pesticides, 544 F.3d at 1050 (upholding an agency’s discernable reliance on models 96 SAN LUIS V. JEWELL that “yield conservative data [where] the models incorporate[d] the higher of [the potential values] in assessing the overall risk”). Moreover, the establishment of a Concern Level is an enforcement norm, and thus a policy decision. “[S]election of an action level is primarily a legislative policy decision that we will uphold so long as it was reasonably drawn from the record.” Public Citizen Health Res. Group v. Dep’t of Labor, 557 F.3d 165, 184 (3d Cir. 2009). Ultimately, the appellees’ objection is not really to the record support for the Concern Level, but to the Concern Level itself. The choice of the Concern Level is quintessentially one within the discretion of the agency, and we have no basis for disturbing it here. D. The Record Supports the BiOp’s Conclusions Regarding the Indirect Effects of Project Operations The FWS is required to take into account both the “direct and indirect effects of an action on the species or critical habitat” when determining whether an action is likely to cause jeopardy. 50 C.F.R. § 402.02; see also 16 U.S.C. § 1536(a)(2). “Indirect effects” are “those that are caused by the proposed action and are later in time, but still are reasonably certain to occur.” 50 C.F.R. § 402.02. Here, the BiOp identified a number of indirect effects on the delta smelt from Project operations. Among other things, it concluded that Project operations were reasonably certain to (1) limit delta smelt food supply, and (2) increase harmful pollution and contaminants. It also noted (3) the harmful indirect effects that would likely spring from three “other stressors”: predation, aquatic macrophytes, and microcystis. See BiOp at 182–88, 202. SAN LUIS V. JEWELL 97 The BiOp found that a “multitude of factors . . . affect delta smelt population dynamics including predation, contaminants, introduced species, entrainment, habitat suitability, food supply, aquatic macrophytes, and microcystis.” BiOp at 202. It concluded that “[t]he extent to which these factors adversely affect delta smelt is related to hydrodynamic conditions in the Delta, which in turn are controlled to a large extent by CVP and SWP operations.” BiOp at 202. It noted that there were other sources of water diversion that affect smelt through entrainment, but that, even when “taken together,” they did not “approach[] the influence of the Banks and Jones export facilities.” BiOp at 202. Although the BiOp candidly assessed that there was “no single primary driver of delta smelt population dynamics” and that there were “non-CVP/SWP factors,” it ultimately concluded that “the CVP and SWP are a primary driver of delta smelt abiotic and biotic habitat suitability, health, and mortality” and that CVP/SWP operations “have also played an indirect role in the delta smelt’s decline by creating an altered environment in the Delta that has fostered the establishment of non-indigenous species and exacerbates these and other stressors that are adversely impacting delta smelt.” BiOp at 202–03. The district court was not persuaded, finding that “[t]he record does not support the BiOp’s conclusion that food web and pollutants/contaminant impacts are indirect effects of Project operations.” San Luis & Delta-Mendota, 760 F. Supp. 2d at 969. The district court also separately noted that “the BiOp’s conclusions about the causal connections between Project operations and ‘other stressors’ are ambiguous,” and thought the effects were “unsupported by record evidence and/or explanation” Id. We address each of these indirect effects in turn, and conclude that the BiOp analysis was 98 SAN LUIS V. JEWELL sufficiently clear and thorough so as not to be arbitrary and capricious, and that it was based on the best available science. See Kern, 450 F.3d at 1080–81. 1. Project operations indirectly affect smelt food supply First, the BiOp explores the likely impact of Project operations on smelt food supply. The BiOp describes “entrainment of Pseudodiaptomus forbesi (P. forbesi), the primary prey of delta smelt,” as a primary effect that “will adversely affect delta smelt.”40 BiOp at 203–04. Plainly stated, delta smelt appear severely food limited much of the time. P. forbesi is the smelt’s principal food source from summer to early fall, and so any Project impact on the availability of P. forbesi represents a threat to the smelt. See BiOp 228, 380. The BiOp concludes that such a threat is present: high water exports reduce flows that would otherwise transport P. forbesi into the delta smelt’s habitat, thereby contributing to smelt mortality and population declines. BiOp at 184–85, 228. Moreover, as water is pumped from the south Bay-Delta during June through September, P. forbesi are entrained in pumping stations, thereby reducing the overall availability of P. forbesi in the delta. BiOp at 228. Because “statistical evidence suggest[s] that the cooccurrence of delta smelt and [prey such as P. forbesi] has a strong . . . influence on the survival of young delta smelt from summer to fall,” BiOp at 228, the BiOp concluded that the Project’s effects on the P. forbesi population indirectly threaten the viability of delta smelt. 40 The FWS proposed to address this through Action 6, which requires the creation or restoration of 8,000 acres of habitat in the Delta and in Suisun Marsh. BiOp at 381. SAN LUIS V. JEWELL 99 We consider whether this analysis is supported by the best available science, and whether the FWS acted arbitrarily and capriciously in concluding, to a “reasonable certainty,” that Project operations indirectly affect delta smelt through its food supply. See 50 C.F.R. § 402.02. As both the district court and the peer review panel indicated, the FWS’s analysis suffers from some methodological limitations; some of the analyses underlying the agency’s conclusions involved extrapolating from a few sampling sites, and therefore may have overstated the scarcity of P. forbesi. The district court seized on the peer review panel’s comments, which pointed out: “Rather than correct this problem, FWS’s response was to abandon the quantitative analysis, choosing to advance the same, potentially flawed conclusion in a more subjective, qualitative analysis. This conduct suggests another unlawful, results-driven choice, ignoring best available science.” San Luis & Delta-Mendota, 760 F. Supp. 2d at 940. We think the district court’s criticism is incorrect. The independent peer review panel commented directly on the FWS’s analysis of the impact of CVP/SWP on P. forbesi and the BiOp’s conclusion that the abundance of P. forbesi “may vary inversely with export flow . . . and directly with outflow.” It stated: “The [p]anel agrees with this conceptual model and with the justification of its elements, which are well-supported.” The panel offered technical suggestions and then commented, “the figures meant to support this analysis are not convincing.” The panel then “suggest[ed] that this analysis be redone with the above considerations in mind. If [the] revised analysis does not show a substantial (not necessarily statistically significant) pattern, the analysis should be mentioned but the results dropped as quantitative metric from the EA.” (emphasis added). The FWS did exactly as the panel recommended. It 100 SAN LUIS V. JEWELL omitted the statistical analysis as justification for its conclusion. We cannot see the error in the FWS following the recommendation of the peer review panel. Moreover, the FWS had other reasons, explained in the record, for concluding that CVP/SWP operations had an effect on P. forbesi and that the abundance of P. forbesi indirectly affects the delta smelt. See BiOp at 184–85, 228. That it omitted a statistical study because it did not have sufficient data to justify it does not strike us as a “results-driven choice,” but as responsible science. Nothing in the ESA compelled the FWS to conduct the particular study the peer review panel thought inadequately supported by the data, and nothing in the peer review panel’s comments even hints that the statistics suggested a contrary conclusion—there is no evidence here to suggest that the FWS, in conspiracy with the peer review panel, was trying to hide evidence. Even if we thought that a “rigorous, large-scale study . . . would be preferable,” we have no authority to compel one: “in the absence of such a study,” even “credible anecdotal evidence” can “represent[] the best scientific . . . data available.” Nw. Ecosystem Alliance v. FWS, 475 F.3d 1136, 1147 (9th Cir. 2007) (internal quotation marks omitted). Like the peer review panel in question, we conclude that although the FWS’s analysis here is not without its limitations, it is “based upon the best available science.” See Nw. Ecosystem Alliance, 475 F.3d at 1147. Similarly, we are persuaded that the BiOp’s conclusion that Project operations indirectly affect the delta smelt by impacting the smelt food supply was “well supported.” We need not independently conclude that this conclusion is well supported to a “reasonable certainty.” It is sufficient that we conclude that SAN LUIS V. JEWELL 101 the BiOp’s conclusion was sufficiently supported such that the FWS did not arbitrarily and capriciously find this to be an indirect effect to a reasonable certainty. 2. Project operations indirectly affect the smelt through water contamination Second, the BiOp explores the Project’s impact on water contamination and therefore, indirectly, on smelt population viability. The BiOp first concludes that water contamination poses a threat to the delta smelt. Smelt throughout the Delta are exposed to various pesticides and contaminants, which “may affect embryo survival or inhibit prey production.” The BiOp singles out ammonia released from a waste processing facility in Sacramento and pesticides from agricultural operations. BiOp at 153, 187, 237. The BiOp observes that “concern over contaminants in the Delta is not new” and refers to mercury, selenium, pesticides, herbicides, ammonium concentrations, and undiluted drainwater. BiOp at 187. Reclamation observes that the “delta smelt are highly sensitive to high levels of ammonia” and that such contaminants are detrimental to the health of the smelt population because they render smelt susceptible to disease. BiOp at 187–88. The BiOp concludes that Project operations will dangerously increase the impact of contaminants on the smelt. One reason is topographical: as Project operations constrain the smelt habitat to smaller rivers and estuaries, the smelt’s overall exposure to these contaminants, which result primarily from land runoff, increases. See BiOp at 153. Relatedly, when Project operations reduce overall suitable habitat, the impact of contaminants on the smelt in the remaining habitat become intensified. The BiOp analyzes 102 SAN LUIS V. JEWELL this latter effect in the context of recognizing the importance of fall X2 to delta smelt viability: The FWS described two “[p]otential mechanisms for the observed effect,” one of which was that “a more confined distribution may increase the impact of stochastic events that increase mortality rates of delta smelt . . . includ[ing] . . . anthropogenic effects such as contaminants.” BiOp at 234 (citing Sommer et al. 2007). One other harmful effect of Project operations, the FWS notes, comes from the flow created by Project pumping: Projectrelated flow “increase[s] exposure to many pesticides [during spawning].” BiOp at 153. This is because flows can “mobilize contaminants.” BiOp at 240. The district court concluded that “[i]t is not clear how the BiOp or any other document in the record links the impacts of contaminants to Project Operations.” San Luis & DeltaMendota, 760 F. Supp. 2d at 942. This criticism is not wellfounded. Although the FWS recognized that “contaminant loading and its ecosystem effects within the Delta are not well understood,” BiOp at 186, the fact that science must advance further before the complicated ecosystem interactions in the Bay-Delta are fully understood does not necessarily mean that the FWS failed to rely on the best available science, or that it arbitrarily and capriciously concluded that there was a reasonable certainty that Project operations will indirectly affect smelt through water contamination. Appellees would presumably have us hold that it is impossible for an agency to simultaneously recognize that some characteristics of an indirect effect “are not well understood” or are “highly uncertain,” and that it is reasonably certain that those indirect effects are harmful and will result from the actions at issue. We decline to do so. We are confident that if we returned the BiOp to the agency, we could help the agency improve it by “point[ing] out errors and missing information” and SAN LUIS V. JEWELL 103 “insist[ing] on additional detail.” Churchill Cnty. v. Norton, 276 F.3d 1060, 1081 (9th Cir. 2001). But “[t]hat is not our role, of course.” Id. Instead, we hold that the BiOp has sufficiently explained the harmful relation between Project operations, contaminants, and delta smelt such that the FWS did not arbitrarily and capriciously conclude to a reasonable certainty that Project operations contribute to harmful contaminant-related indirect effects. 3. Project operations indirectly affect the smelt through the “other stressors” of predation, macrophytes, and microcystis As part of its analysis of the impacts of Project operations on the smelt, the BiOp discusses the effect of “other stressors”: “the multitude of factors that affect delta smelt population dynamics including predation, . . . aquatic macrophytes, and microcystis.” BiOp at 202. Because “[t]he extent to which these factors adversely affect delta smelt is related to hydrodynamic conditions in the Delta, which in turn are controlled to a large extent by CVP and SWP operations,” BiOp at 202, the BiOp’s analysis considers these “other stressors” when determining “the effects of proposed CVP/SWP operations on delta smelt,” BiOp at 203. We hold first that the BiOp’s conclusion that “hydrodynamic conditions driven or influenced by CVP/SWP operations . . . influence the dynamics of delta smelt interaction with these other stressors” was sufficiently supported in the record. BiOp at 202. The BiOp explicitly relied on outside scientific studies in concluding that Project operations “affect[] or control[]” some of these other stressors impacting delta smelt abundance. BiOp at 203. Second, having determined that Project operations likely affect the impact of “other stressors” 104 SAN LUIS V. JEWELL on the smelt, the BiOp considers the harmful effects of these other stressors on the smelt population. The district court faulted the FWS for failing to consider “available information,” San Luis & Delta-Mendota, 760 F. Supp. 2d at 934–35, or “make a rational connection between the facts in the record and its conclusions,” id. at 936. We disagree, and find the BiOp sufficiently thorough and hold that the FWS did not arbitrarily and capriciously reach this conclusion.
One stressor to the smelt is predation. As the BiOp acknowledged, there is much here that is unknown. It is known that in the 1960s, when the delta smelt were more plentiful, they were prey for striped bass, black crappie, and white catfish. BiOp at 183. The BiOp observed that “[i]t is unknown whether incidental predation by striped bass (and other lesser predators) represents a substantial source of mortality for delta smelt,” in part because the scarcity of smelt means that smelt have recently gone undetected in recent studies of predator stomach contents. BiOp at 183. The BiOp speculated that “[d]elta smelt may experience high predation mortality around water diversion where smelt are entrained and predators aggregate,” citing to an outside study showing that smelt eggs and larvae were prey for inland silversides. BiOp at 183. The BiOp also recognized the risks presented from other potential predators of smelt eggs and SAN LUIS V. JEWELL 105 larvae in such areas, including yellowfin goby, centrarchids, and Chinook salmon.41 BiOp at 183. After concluding that predation poses a harmful indirect effect to delta smelt population viability, the BiOp discusses the relation between Project operations and smelt predation. By shifting X2 further upstream, Project operations move smelt habitat to include more of these littoral areas (areas of the Bay-Delta close to shore), thereby increasing smelt exposure to predators. BiOp at 153. As the location of X2 shifts towards new Bay-Delta regions that are rife with predators the smelt follow. Moreover, the BiOp notes that “[t]he Delta-wide increase in water transparency may have intensified predation pressures on delta smelt,” citing the “[w]ide documenta[tion],” including several specific studies, indicating that water clarity significantly influences predation of pelagic fishes, including many smelt species. BiOp at 183. The district court found this analysis lacking, specifically citing the FWS’s failure to explain whether striped bass predation on the smelt “should be considered significant.” San Luis & Delta-Mendota, 760 F. Supp. 2d at 934. Here, the district court was very specific: It faulted the BiOp for failing to “include any estimates of the effect of predation on the delta smelt population” when “[s]uch information was available” and was “decidedly contrary to BiOp findings.” Id. In support, the district court referenced a 1999 California 41 The BiOp considered whether delta smelt are affected by competition from other fish, and cited one study suggesting that they were. The BiOp did not rely on competition as a stressor, however, because “there is no empirical evidence to support the conclusion that competition between these species is a factor that influences the abundance of delta smelt in the wild.” BiOp at 183. 106 SAN LUIS V. JEWELL Department of Fish & Game report submitted to the FWS as part of an incidental take permit. Id. (citing California Dep’t of Fish and Game, Conservation Plan for The California Department of Fish and Game Striped Bass Management Program (November 12, 1999)). We are not sure what the Fish & Game report adds, and we cannot see that the report is “decidedly contrary” to the FWS’s conclusions. The Fish & Game report stated that “the best available information yields imprecise, loosely constrained estimates of striped bass predation on delta smelt.” It said that there was considerable overlap between the delta smelt and striped bass, but that “striped bass rarely ate delta smelt,” likely because “delta smelt are surface oriented while striped bass tend to forage near the bottom.” Fish & Game estimated that striped bass were responsible for “an estimated annual consumption of about 5.3% of the delta smelt population.” We do not see the conflict between the Fish & Game report and the BiOp. The BiOp concluded that “[i]t is unknown whether incidental predation by striped bass . . . represents a substantial source of mortality for delta smelt.” BiOp at 183. The Fish & Game report is consistent with the FWS’s conclusion. If anything, the Fish & Game report might suggest that further study is required to see if the striped bass is a substantial source of mortality for the smelt. Although the BiOp cited post-1999 studies showing that the striped bass was not a significant predator of the delta smelt, if Fish & Game is correct (and current) in its estimates, a predator responsible for a 5.3 percent mortality rate of an endangered species might be significant. In any event, we fail to see its significance with respect to the conclusions of the BiOp. The BiOp concluded that predators—primarily fish other than the striped bass—were a potential threat to the delta smelt. More SAN LUIS V. JEWELL 107 broadly, we decline to review with a fine-toothed comb the studies on which the FWS relied in reaching its conclusions.
Another stressor noted in the BiOp is aquatic macrophytes. Macrophytes—aquatic plants that grow in or near water—have extensively colonized the interior Delta over the past two decades. BiOp at 182. As the BiOp notes, research suggests that these macrophytes have “altered fish community dynamics in the Delta, including increasing habitat for centrarchid fishes including largemouth bass, reducing habitat for native fishes, and supporting a food web pathway for centrarchids and other littoral fishes.” BiOp at 182 (citations to scientific studies omitted). These effects impact smelt both directly and indirectly. Submerged aquatic vegetation can overwhelm littoral habitats, such as inter-tidal shoals and beaches, that serve as delta smelt spawning locations, thereby rendering them unsuitable for spawning. BiOp at 182. Moreover, macrophytes trap suspended sediment and therefore reduce water turbidity, which has contributed to a decrease in both juvenile and adult smelt habitat while increasing the available habitat for fish that prey on smelt. BiOp at 182–83 (citing Feyrer et al. 2007 and Nobriga et al. 2008 in support). This decreased turbidity also may facilitate the predation of delta smelt while hampering the smelt’s own feeding, thereby further harming smelt population viability. BiOp at 183. As the BiOp notes, hydrologic conditions and water temperature play a significant role in macrophyte colonization of the Delta. BiOp at 182. The FWS concludes that it is “likely” that Project operations’ impact on Bay-Delta hydrologic conditions and reduction of seasonal flushing 108 SAN LUIS V. JEWELL flows exacerbate the spread of macrophytes in the Bay-Delta. BiOp at 277. Flushing flows are known to lead to “abrupt changes in flow and turbidity.” BiOp at 146. Indeed, the FWS found that “[a]vailable information is inconclusive regarding the extent, magnitude and pathways by which delta smelt may be affected by these stressors independent of CVP/SWP operations.” BiOp at 277. The district court was also not persuaded by this analysis, finding that “[a]lthough a connection [between Project operations and macrophytes] may exist, the record does not reflect any discussion, nor have the parties pointed to any study, connecting ‘seasonal flushing flows . . . the natural frequency of upstream and downstream movement of the LSZ, and lengthen[ed] upstream shifts of the LSZ’ to the presence of any aquatic macrophyte.” San Luis & DeltaMendota, 760 F. Supp. 2d at 935–36. Again, we disagree. The BiOp set forth several plausible explanations for how Project operations will increase the detrimental impact of macrophytes on delta smelt viability, and cited studies in support. See BiOp at 146, 182–83, 277. That the BiOp did not, as the district court requests, point to a study directly addressing the Project’s effect on Bay-Delta macrophytes does not render the FWS’s conclusions unreasonable or unsupported: The FWS has drawn rational conclusions from the best available science, and, consequently, we hold that the BiOp’s determination that it is reasonably certain that macrophytes will indirectly affect delta smelt is not arbitrary and capricious. It is not our job to task the FWS with filling the gaps in the scientific evidence. We must respect the agency’s judgment even “in the face of uncertainty.” Ariz. Cattle Growers Ass’n v. Salazar, 606 F.3d 1160, 1164 (9th Cir. 2010). SAN LUIS V. JEWELL 109
Microcystis aeruginosa is a cyanobacterium that produces toxins throughout its life cycle, with toxin concentrations sharply increasing when the bacteria population dies, usually in September or October. BiOp at 372. These high toxin levels present a threat to the delta smelt and, as the BiOp recognizes, high microcystis toxin levels have been associated with low delta smelt abundances. BiOp at 372. Microcystis can directly “pose animal and human health risks if contacted or ingested directly,” although it does not appear that current concentrations are sufficiently severe to threaten smelt. BiOp at 186. Rather, microcystis’s primary threat to the smelt is indirect, as “it appears that M. aeruginosa is toxic to copepods that delta smelt eat.” BiOp at 186 (citing an outside scientific study). There is also concern that microcystis “could out-compete diatoms[, a rich food source for zooplankton,] for light and nutrients.” BiOp at 186. As the BiOp notes, however, more studies are needed, and, in fact, “are underway to determine if zooplankton production is compromised during M. aeruginosa blooms to an extent that is likely to adversely affect delta smelt.” BiOp at 186. As the BiOp also discusses, CVP/SWP operations are likely to increase the harmful impact of microcystis on delta smelt because “[l]ow flow conditions are among the factors associated with Microcystis blooms.” BiOp at 372. By reducing flows, Project operations would cause “larval and juvenile delta smelt . . . [to] remain in the Central and South Delta, where they could . . . succumb to predation or microcystis blooms.” BiOp at 224. Overall, Microcystis “reduce[s] habitat suitability.” BiOp at 373. 110 SAN LUIS V. JEWELL The district court found that the BiOp “makes no connection whatsoever between microcystis . . . and continued CVP and SWP operation” and that “[g]iven that the impacts of regulating Project Operations are so consequential, such unsupported attributions (a result in search of a rationale) are unconscionable.” San Luis & Delta-Mendota, 760 F. Supp. 2d at 936. Again, we disagree. The FWS has proposed several plausible evidence-based hypotheses explaining the harmful Project-related impact of microcystis on delta smelt. The BiOp candidly acknowledges that additional studies in this area are underway. That CVP/SWP operations are not the only dynamic force acting on the Bay-Delta does not render the BiOp’s recognition of the inherent uncertainty associated with the highly interdependent ecosystem unreasonable. We should not deter agencies from recognizing the limitations of either science or their own knowledge. In this instance, the evidence linking Project operations, Bay-Delta hydrologic conditions, and microcystis harms is sufficient that we hold that the FWS’s microcystis conclusions were not arbitrary and capricious. E. The FWS Is Not Required to Support the “Non-Jeopardy” Elements of its RPA When the Secretary determines that an agency action will cause jeopardy to, or an adverse habitat modification of, an endangered or threatened species, the Secretary “shall suggest those reasonable and prudent alternatives which he believes would not [jeopardize the species or adversely modify its habitat] and can be taken by the Federal agency or applicant in implementing the agency action.” 16 U.S.C. § 1536(b)(3)(A); see also 50 C.F.R. §§ 402.14(h)(3), 402.14(g)(5). The FWS’s regulations further explain its duty SAN LUIS V. JEWELL 111 under the ESA. The regulations define “reasonable and prudent alternatives”—RPAs—as alternative actions identified during formal consultation [1] that can be implemented in a manner consistent with the intended purpose of the action, [2] that can be implemented consistent with the scope of the Federal agency’s legal authority and jurisdiction, [3] that is economically and technologically feasible, and [4] that the Director believes would avoid the likelihood of jeopardizing the continued existence of listed species or resulting in the destruction or adverse modification of critical habitat. 50 C.F.R. § 402.02. Element [4] in § 402.02 is commonly referred to as the “jeopardy” factor; elements[1] through [3] are referred to as the “non-jeopardy” factors. The FWS’s Consultation Handbook explains further: “If the services conclude that certain alternatives are available that would avoid jeopardy and adverse modification, but such alternatives fail to meet one of the other three elements in the definition of ‘reasonable and prudent alternative,’ the Services should document the alternative in the biological opinion to show it was considered during the formal consultation process.” U.S. Fish & Wildlife Serv. & Nat’l Marine Fisheries Serv., ESA at 4–41 (March 1998), Section 7 Consultation Handbook, available at http://www.fws.gov/ endangered/esa-library/pdf/CH4.pdf (last visited July 27, 2013) (second emphasis added). Thus, according to the Consultation Handbook, if a draft alternative fails to meet one of the non-jeopardy “elements” of a valid RPA, the Service should provide documentation to show that it considered 112 SAN LUIS V. JEWELL alternatives during consultation. Id. We have previously afforded Skidmore deference to the FWS’s Consultation Handbook. See Ariz. Cattle Growers’ Ass’n, 606 F.3d at 1165 (concluding that “[t]he definition in the handbook appears to be the result of the agency's considered judgment and . . . we are persuaded [that it is a reasonable one entitled to deference]”); see also Skidmore v. Swift & Co., 323 U.S. 134 (1944). Referring to the non-jeopardy factors, the district court found that the FWS “has articulated absolutely no connection between the facts in the record and the required conclusion that the RPA is (1) consistent with the purpose of the underlying action; (2) consistent with the action agency’s authority; and (3) economically and technologically feasible.” San Luis & Delta-Mendota, 760 F. Supp. 2d at 956–57. The court continued: the APA requires, and the public is entitled under the law to receive, some exposition in the record of why the agency concluded (if it did so at all) that all four regulatory requirements for a valid RPA were satisfied. The RPA Actions manifestly interdict the water supply for domestic human consumption and agricultural use for over twenty million people who depend on the Projects for their water supply. “Trust us” is not acceptable. FWS has shown no inclination to fully and honestly address water supply needs beyond the species despite the fact that its own regulation requires such consideration. SAN LUIS V. JEWELL 113 San Luis & Delta-Mendota, 760 F. Supp. 2d at 957. Because the FWS had failed to explain why it chose its RPAs, “to the exclusion of implementing less harmful alternatives,” the district court remanded to the FWS. Id. Put more simply, the district court found that both the FWS’s regulation and the APA required the FWS to engage in a record exposition of the non-jeopardy factors, and that the FWS did not do so. We disagree both with the district court’s legal analysis and with its reading of the record. First, contrary to the district court’s conclusion, the FWS’s “own regulation” does not require the FWS to address the non-jeopardy factors. San Luis & Delta-Mendota, 760 F. Supp. 2d at 957. Nothing in § 402.02 obligates the FWS to address the non-jeopardy factors when it proposes RPAs. Section 402.02 is a definitional section; it is defining what constitutes an RPA, not setting out hoops that the FWS must jump through. See 50 C.F.R. § 402.02; see also id. at § 402.14(g)(5) (the FWS shall “discuss [with an agency] . . . the availability of reasonable and prudent alternatives”); 302.02(h)(3) (“A ‘jeopardy’ biological opinion shall include reasonable and prudent alternatives if any.”). Moreover, the Consultation Handbook implies that no such discussion is necessary. As the Handbook notes: [Although] it is imperative that the opinion contain a thorough explanation of how each component of the [reasonable and prudent] alternative is essential to avoid jeopardy and/or adverse modification[,] . . . [i]f the Services conclude that certain alternatives are available that would avoid jeopardy and adverse modification, but such alternatives 114 SAN LUIS V. JEWELL fail to meet one of the other three elements in the definition of ‘reasonable and prudent alternative,’ the Services should document the alternative in the biological opinion to show it was considered during the formal consultation process. Section 7 Consultation Handbook, available at http://www.fws.gov/endangered/esa-library/pdf/CH4.pdf (last visited July 1, 2013); see also 50 C.F.R. § 402.14(h)(3) (“If the Service is unable to develop such [reasonable and prudent] alternatives, it [must] indicate that to the best of its knowledge there are no reasonable and prudent alternatives.”). In other words, a “thorough” documentation of jeopardy/adverse modification in the BiOp is always required, whereas documentation of the non-jeopardy factors is only required when the RPA fails to meet a non-jeopardy factor. We fail to see anywhere that the FWS has required itself to provide an explanation of the non-jeopardy factors when it lays out an RPA. We may not “impose on the agency [our] own notion of which procedures are ‘best’ or most likely to further some vague, undefined public good. Nor may we impose procedural requirements [not] explicitly enumerated in the pertinent statutes.” McNair, 537 F.3d at 993 (internal quotation marks and citations omitted).42 42 We note that the Fourth Circuit recently remanded a BiOp to the FWS for failure to evaluate an RPA for its economic and technological feasibility. Dow AgroSciences, 707 F.3d at 474–75. We do not read Dow to require the FWS to address economic and technological feasibility as a procedural matter. As we read Dow, the court was concerned that the FWS had imposed an especially onerous requirement without any thought for whether it was feasible. Id. at 475 (RPA would prohibit pesticide SAN LUIS V. JEWELL 115 Second, the APA does not, as the district court held, require the FWS to address the non-jeopardy factors in this case. See San Luis & Delta-Mendota, 760 F. Supp. 2d at 957. Under the APA, the Supreme Court has held that agency decisions that “entirely fail[] to consider an important aspect of the problem” are arbitrary and capricious. Motor Vehicle Mfrs. Ass’n of U.S., Inc. v. State Farm Mut. Auto Ins. Co., 463 U.S. 29, 43 (1983). We have held that whether an RPA will prevent jeopardy or adverse modification of critical habitat is “an important aspect of the problem.” See, e.g., Wild Fish Conservancy v. Salazar, 628 F.3d 513, 522–23 (9th Cir. 2010) (finding a BiOp that failed to explain how the RPA avoided jeopardy arbitrary and capricious); Pacific Coast Fed’n of Fishermen’s Ass’ns v. U.S. Bureau of Reclamation, 426 F.3d 1082, 1091 (9th Cir. 2005) (same). But the jeopardy factor in the RPA is independently demanded by the ESA itself. Section 1536(a)(2) requires that each federal agency shall “insure that any action . . . is not likely to jeopardize” the species or its habitat. 16 U.S.C. § 1536(a)(2). This includes the FWS, which must warrant that its RPA “would not violate [§ 1536(a)(2)].” 16 U.S.C. § 1536(b)(3)(a). That is, the FWS, in the course of proposing an RPA, must insure that the RPA does not jeopardize the species or its habitat. We can find no similar requirement in the ESA that the FWS address the remaining three nonjeopardy factors. If the ESA does not require it, we are extremely reluctant to read such a requirement into the APA. applications “within 500 feet (for ground applications) and 1,000 feet (for aerial applications) of any waterway that is connected, directly or indirectly, at any time of the year, to any water body in which salmonids might be found at some point.” (emphases in original)). 116 SAN LUIS V. JEWELL Moreover, we are persuaded that the district court misread what the economic feasibility factor addresses. The court faulted the FWS for not accounting for the cost of “interdict[ing] the water supply for domestic human consumption and agricultural use for over twenty million people who depend on the Projects for their water supply.” San Luis & Delta-Mendota, 760 F. Supp. 2d at 957. This misreads the ESA and its implementing regulations. Section 402.02 is only concerned with the economic and technological feasibility of the RPA. That is, the FWS must consider whether its proposed alternative is financially and technologically possible. Those two considerations— economics and technology—are constraints on what measures the FWS can recommend to the agency as an alternative to ceasing the activity entirely. To put it into perspective in this case: Reclamation has consulted with the FWS because it has legitimate concerns whether its continued CVP activities may jeopardize the smelt or its habitat. When the FWS concludes that Reclamation’s continued activities will jeopardize the smelt then, presumptively, Reclamation may not take or continue such activities. See Nat’l Assn of Home Builders v. Defenders of Wildlife, 551 U.S. 644, 652 (2007) (“Following the issuance of a ‘jeopardy’ opinion, the agency must either terminate the action, implement the proposed alternative, or seek an exemption from the CabinetLevel Endangered Species Committee . . . .”). In this case, of course, terminating Reclamations’ CVP-related activities is unthinkable. The whole point of the “reasonable and prudent alternative” is for the FWS to suggest what Reclamation can do to avoid such a result. The regulation identifies “economic and technological feasibility” as factors because these go to whether the RPA “can be taken by the Federal agency . . in implementing the agency action,” 16 U.S.C. § 1536(b)(3)(A) (emphasis added), not to whether restricting SAN LUIS V. JEWELL 117 CVP activities will affect its consumers.43 The “economic and technological feasibility” factor does not address the downstream economic impacts of Reclamation being unable to continue its CVP operations as it has done in the past. As important and consequential as the question is, the FWS is not responsible for balancing the life of the delta smelt against the impact of restrictions on CVP/SWP operations. That balance has already been struck by Congress in the ESA and the Central Valley Project Improvement Act. See CVPIA § 3406(b), Pub. L. No. 102-575, 106 Stat. 4600, 4714 (stating that the Secretary of the Interior is to “operate the Central Valley Project to meet all obligations under State and Federal law, including but not limited to the Federal Endangered Species Act, 16 U.S.C. § 1531 et seq”); Tenn. Valley Auth., 437 U.S. at 185 (holding that the ESA reflects “a conscious decision by Congress to give endangered species priority over the ‘primary missions’ of federal agencies”). Accordingly, the FWS’s duty is to opine on the viability of the smelt and “to halt and reverse the trend toward species extinction, whatever the cost.” Id. at 184 (emphasis added). Even if the APA did require the FWS to consider the nonjeopardy factors, the record shows that the FWS has sufficiently considered them. See Motor Vehicle Mfrs. Ass’n of U.S., Inc, 463 U.S. at 43 (holding that insufficient consideration for purposes of APA arbitrary and capricious review is an “entire[] fail[ure] to consider”). Although the FWS’s consideration of the non-jeopardy factors could certainly have been even more exhaustive, or stated more expressly, its determination that the RPA satisfied the non- 43 Neither the parties nor the district court argue that the RPAs themselves (and their proposed Actions) are not economically and technologically feasible. 118 SAN LUIS V. JEWELL jeopardy factors “may be reasonably discerned” from the record, and therefore should be upheld. Id. (holding that even “a decision of less than ideal clarity” should be upheld in such circumstances). Application of the non-jeopardy factors in this case is really quite straightforward. See 50 C.F.R. § 402.02. First, the record shows that the RPA is consistent with the purpose of the underlying action. The document that was prepared as a basis for consultation, Reclamation’s biological assessment (BA), identified the purpose of this action to be “operat[ing] the [Projects] to divert, store, redivert, and convey CVP and SWP . . . water consistent with applicable law.” The RPAs—which largely deal with regulating the water that CVP/SWP export from the DeltaBay—do not require any major changes in the way Reclamation runs its operations. Second, and similarly, the record indicates that the RPA can be implemented “consistent with the scope of the Federal agency’s legal authority.” Both the BA and the BiOp discuss the extent of Reclamation’s authority. See, e.g., BiOp at 21–25 (Reclamation’s obligations under its Coordinated Operations Agreement with DWR). Finally, there is support in the record for the FWS’s conclusion that the RPA is both technologically and economically feasible. We think this is nearly self-evident. The RPA closely resembles measures in the interim remedial order, the feasibility of which was proven in its mid-December 2007 through December 2008 implementation. BiOp at 327–28. Additionally, RPA incorporates feasibility-related comments that were made on a draft RPA from Reclamation and DWR. Again, the RPAs propose regulatory changes in what Reclamation does on a day-to-day basis, but the RPAs do not require major changes affecting Reclamation’s ability—financially or technologically—to comply with the RPAs. SAN LUIS V. JEWELL 119 In sum, we disagree with the district court’s determination that the FWS’s own regulation and the APA require the FWS to explain that the RPA satisfies § 402.02 non-jeopardy factors. Alternatively, we hold that the FWS’s consideration of these factors may be reasonably discerned from the record to satisfy any explanation requirements.44