The use of population genetics in Endangered Species Act listing decisions

Ecology Law Quarterly

Volumn 37, Issue 4, 2010, Pages 1107-1158

  Kelly, Ryan P ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

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EID: 79954592397     PISSN: 00461121     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Review

References (289)

1. Endangered Species Act of 1973, 16 U.S.C. §§1531-1539 (2006).
2. 2=0.49),
3. id. at 1190, underscoring the common-sense suggestion that the trend will continue to accelerate in the future as the costs of generating genetic data continue to plummet.
4. See §1533(b)(1)(A) (2006).
5. See §1533(b). The Administrative Procedure Act, Pub. L. No. 79-404, 60 Stat. 237 (codified as amended in scattered sections of 5 U.S.C.), also provides protections in the form of public participation (through rulemaking requirements), and judicial review.
6. See, e.g., Holly Doremus, Science and ESA Listing Decisions, 75 WASH. U. L. REV. 1029, 1079 (1997) (discussing the internal data-gathering and handling processes of the Fish and Wildhfe Service).
7. See 5 U.S.C. § 706 (2006).
8. But see Ctr. for Biological Diversity v. Norton, 336 F. Supp. 2d 1155, 1161-62 (D.N.M. 2004) (holding that scientific recommendations to the Fish and Wildhfe Service regarding an ESA listing claim fell under the deliberative or mental process privilege, and thus could be protected from discovery during litigation).
9. See, e.g., Sara A. Clark, Taking a Hard Look at Agency Science: Can the Courts Ever Succeed?, 36 ECOLOGY L.Q. 317, 352 (2009) ("Increased transparency also opens up agency science to the scientific community, which, with a clearer picture of agency science, can better review and critique this information to the benefit of both the agency and the scientific community.").
10. Professor Holly Doremus has written extensively on the need for transparency in agency science, and has suggested mechanisms for improving agency policies.
11. See, e.g., Holly Doremus, Scientific and Political Integrity in Environmental Policy, 86 TEX. L. REV. 1601, 1646 (2008);
12. Holly Doremus & A. Dan Tarlock, Science, Judgment and Controversy in Natural Resource Regulation, 26 PUB. LAND & RESOURCES L. REV. 1, 31 (2005) ("We suggest that both the scientific and policy advice of agency scientists should be available to the public. This could be achieved by requiring the various judgments of agency scientists to be included in the public record, but also structuring those evaluations to separate scientific from other judgments. Even if agency scientists are just as inclined as agency politicians to hide their political judgments, and just as skilled at doing so, mandating public release of their advice should help expose those judgments. Agency decision makers who must disclose internal scientific advice counter to their ultimate decision will face political and judicial pressures to explain the discrepancy. That will give them incentives to reveal the policy judgments both in their ultimate decision and in the recommendations of their scientists.").
13. See Portland Cement Ass'n v. Ruckelshaus, 486 F.2d 375, 393 (1973) ("It is not consonant with the purpose of a rule-making proceeding to promulgate rules on the basis of inadequate data, or on data that, [in] critical degree, is known only to the agency."),
14. superseded by statute on other grounds, 15 U.S.C. §793(c)(1), Am. Trucking Ass'ns, Inc. v. EPA, 175 F.3d 1027, 48 (D.C Cir. 1999);
15. see also United States v. Nova Scotia Food Prods. Corp., 568 F.2d 240, 251 (2d Cir. 1977) (reversing dismissal of challenge to agency ruling because "interested parties were not informed of the scientific data, or at least of a selection of such data deemed important by the agency, so that comments could be addressed to the data");
16. Ober v. Envtl. Prot. Agency, 84 F.3d 304, 314 (9th Cir. 1996) (holding agency improperly rehed on information submitted after public comment period in making decision).
17. But see Ctr. for Biological Diversity v. Norton, 336 F. Supp. 2d 1155, 1161-62 (D.N.M. 2004) ("[T]he Magistrate Judge thoughtfully analyzed the [relevant] factors ... and concluded that the withheld materials . .. need not be disclosed because the extensive administrative record already supplied contained sufficient documentation of the listing decision.").
18. Endangered Species Act of 1973, 16 U.S.C. §§1531-1544 (2006).
19. See id. §§1531, 1532(3).
20. See id. §1531(b).
21. The FWS and NMFS differ in that by default, FWS treats endangered and threatened species as equivalent for section 9 "take" purposes, while NMFS regulates section 9 take of threatened species on a species-by-species basis.
22. See 16 U.S.C. §1538 (2006); 50 C.F.R. §§ 17.2(b) (for NMFS), 17.31(a) (2010) (for FWS). Because much of the literature and case law on marine and anadromous species refers to the listing agency as "NMFS," I will use that terminology rather than "NOAA" for consistency. For most purposes, FWS and NMFS apply the ESA identically, and I will treat the two as interchangeable here unless specifically noted.
23. See 16 U.S.C. §1533(b)(4) (2006).
24. See id. §1533(b)(3)(A).
25. See id. §1533(b)(1)(A).
26. See id. §1533(b)(3)(B)(iii).
27. See id. §1533(b)(3)(C)(i) (treating warranted-but-precluded finding as equivalent to a new petition for listing, which must be acted upon within 12 months).
28. See id. §1531(a).
29. See 16 U.S.C. §1533(d) (allowing Secretary's discretion in making regulations to protect threatened species);
30. see also supra note 13.
31. See 16 U.S.C. §1533(a)(1)(A)-(E) (2006).
32. See Chevron v. Natural Res. Def. Council, 467 U.S. 837, 844 (1984).
33. See, e.g., Home Builders Ass'n of N. Cal. v. U.S. Fish & Wildlife Serv., 529 F. Supp. 2d 1110, 1117 (N.D. Cal. 2007) (granting deference to agency in listing California tiger salamander as threatened).
34. See 16 U.S.C. §1533(b)(1)(A);
35. see, e.g., Ctr. for Biological Diversity v. Lohn, 296 F. Supp. 2d. 1223, 1238 (W.D. Wash. 2003) ("When the best available science indicates that the 'standard taxonomie distinctions' are wrong ... NMFS must apply that best available science."), vacated on other grounds, 511 F. 3d 960 (9th Cir. 2007).
36. See 16 U.S.C. §1532(16).
37. See id. ("The term 'species' includes any subspecies of fish or wildhfe or plants, and any distinct population segment of any species of vertebrate fish or wildlife which interbreeds when mature."). This definition corresponds with the "biological species concept," one commonlyused idea in the scientific community for delineating species.
38. The scientific literature surrounding species concepts is voluminous, and features overlapping and conflicting ideas of what a species is. For reviews of the debate,
39. see, e.g., Joel Cracraft, Species as Entities of Biological Theory, in WHAT THE PHILOSOPHY OF BIOLOGY Is 31 (Michael Ruse ed., 1989);
40. Jody Hey, The Mind of the Species Problem, 16 TRENDS IN ECOLOGY & EVOLUTION 326 (2001);
41. Kevin de Queiroz, Ernst Mayr and the Modern Concept of Species, 102 PROC. NAT'L ACAD. Sa. 6600 (2005).
42. Here "taxonomic" refers to the system of scientific names used to classify species. The example I use in the main text, infra, is Puma concolor, commonly known as the cougar.
43. The ESA, after all, is the Endangered Species Act, presumably written under the assumption that species are discrete and real entities. For a discussion of how species definitions impact ESA implementation,
44. see generally Anna L. George & Richard L. Mayden, Species Concepts and the Endangered Species Act: How a Valid Biological Definition of Species Enhances the Legal Protection of Biodiversity, 45 NAT. RESOURCES J. 369 2005).
45. See H.R. REP. No. 95-1804, at 2 (1978) (Conf. Rep.);
46. Endangered Species Act Amendments of 1978, Pub. L. No. 95-632, §2,92 Stat. 3751,3752 (1978).
47. See 16 U.S.C. §1533(c)(2) (2006).
48. See Oliver A. Ryder, Species Conservation and Systematics: The Dilemma of Subspecies, 1 TRENDS IN ECOLOGY & EVOLUTION 9 (1986).
49. Robin S. Waples, Pacific Salmon, Oncorhynchus spp., and the Definition of "Species" under the Endangered Species Act, 53 MARINE HSHERIES REV. 3, 12 (1991).
50. See Dylan J. Fraser & Louis Bernatchez, 10 MOLECULAR ECOLOGY 2741, 2742 (2001);
51. Robin S. Waples, Distinct Population Segments, in 2 SCOTT ET AL., THE ENDANGERED SPECIES ACT AT THIRTY 127 (2006).
52. See Waples, supra note 33, at 15 (citing phenotypic and life history traits as relevant to the distinctness inquiry).
53. See Policy on Applying the Definition of Species under the Endangered Species Act to Pacific Salmon, 56 Fed. Reg. 58,612 (Nov. 20,1991).
54. Id. at 58,612.
55. Id.
56. See Policy Regarding the Recognition of Distinct Vertebrate Population Segments under the Endangered Species Act, 61 Fed. Reg. 4722 (Feb. 7,1996) [hereinafter DPS Policy].
57. See id. at 4725.
58. Id. at 4725.
59. See id. Populations may also be discrete by virtue of existing on either side of an international boundary.
60. See id.
61. Id. at 4725.
62. Here, "taxon" refers to the entire named, taxonomic species. Note that in the scientific literature, "taxon" refers more generally to a named unit of biological organization, whether a species, genus, family, etc. The INTERNATIONAL CODE OF ZOOLOGICAL NOMENCLATURE, the formal rules for naming animals, provides a yet more general definition: "A taxonomic unit, whether named or not: i.e. a population, or group of populations of organisms which are usually inferred to be phylogenetically related and which have characters in common which differentiate (q.v.) the unit (e.g. a geographic population, a genus, a family, an order) from other such units. A taxon encompasses all included taxa of lower rank (q.v.) and individual organisms."
63. Glossary, INTERNATIONAL CODE OF ZOOLOGICAL NOMENCLATURE, http://www.nhm.ac.uk/hosted-sites/iczn/code/index.jsp?booksection= glossary&nfv=true (last visited Oct. 3, 2010).
64. See DPS Policy, supra note 39, at 4725.
65. See supra Part I.A.
66. See DPS Policy, supra note 39, at 4725. Note that a population may be discrete but not significant, even in the face of genetic data.
67. See, e.g., Twelve-Month Finding on a Petition to List the Coaster Brook Trout as Endangered, 74 Fed. Reg. 23,376, 23,386 (May 19, 2009) (to be codified at 50 C.F.R. pt. 17) (noting that while the "coaster brook trout are a discrete population segment," this population segment is not significant to the larger brook trout taxon because the coaster brook trout "co-occur with and are a subset of the same population as other brook trout types (stream residents) in the upper Great Lakes"); infra Part IV.B (discussing the cactus pygmy owl).
68. See NAT'L RESEARCH COUNCIL, SQENCE AND THE ENDANGERED SPECIES ACT 8 (1995).
69. Id. at 184 (emphasis added).
70. See generally Gary W. Luck, Gretchen C. Daily & Paul R. Ehrlich, Population Diversity and Ecosystem Services, 18 TRENDS IN ECOLOGY AND EVOLUTION 331 (2003);
71. Thorsten B.H. Reusch & A. Randall Hughes, The Emerging Role of Genetic Diversity for Ecosystem Functioning: Estuarine Macrophytes as Models, 29 ESTUARIES & COASTS 159 (2006);
72. Thomas Elmqvist et al., Response Diversity, Ecosystem Change, and Resilience, 1 FRONTIERS IN ECOLOGY & ENV'T 488 (2003).
73. See 16 U.S.C. § 1531(b) (2006) ("The purposes of this Act are to provide a means whereby the ecosystems upon which endangered species and threatened species depend may be conserved....").
74. Though more accessible information can make science-based policy judgments more politicized, see generally Daniel Sarewitz, How Science Makes Environmental Controversies Worse, 7 ENVTL. SCI. & POL'Y 385 (2004), greater transparency in decision making surely helps to identify the agency value judgments underlying some decisions.
75. A standard (and good) biology textbook that goes into more detail is NEIL A. CAMPBELL ET AL., BIOLOGY (9th ed. 2007).
76. A great population genetics reference is DANIEL L. HARTL & ANDREW G. CLARK, PRINOPLES OF POPULATION GENETICS (4th ed. 2007).
77. These letters stand for adenine, cytosine, guanine, and thymine.
78. Genes occur in discrete places on the DNA strand; such genes and other identifiable regions in DNA are often known by the Latin loci (singular: locus, meaning "place").
79. Substances as diverse as enzymes, hemoglobin, structural elements of cells, and the active portions of muscles are all different proteins.
80. This is possible because the genetic code is redundant: there is more than one way to make an amino acid, the building blocks of proteins. Silent mutations simply change the underlying DNA sequence to a slightly different sequence that nevertheless encodes the same amino acids, resulting in the same protein. Silent mutations are also known as synonymous mutations.
81. A search on the BIOSIS database, ISI WEB KNOWLEDGE, http://isiknowledge. com/BIOSIS (last visited Nov. 3, 2010), reveals only 336 papers in the 1970s with the terms "allozyme" or "allozymes" in the title; the 1980s yielded 1777 such papers.
82. In fact, allele frequency differences imply a more complicated variety of evolutionary phenomena. For the present purposes, migration is equivalent to gene flow among populations, and is the most important demographic parameter in evaluating a DPS. Note that allelic diversity within and among populations may also inform a species' endangered or threatened status: as populations become smaller, they very quickly lose diversity.
83. See DANIEL L. HARTL, A PRIMER ON POPULATION GENETICS 95 (3d ed. 2000).
84. Note that I have elided the difference between sequence alleles (that is, different versions of DNA sequences encoding a given protein) and protein alleles (that is, different protein versions resulting from underlying DNA sequence differences). This distinction is important generally, but not for the purposes here.
85. See, e.g., HARTL, supra note 59.
86. See Fallon, supra note 2 (analyzing the frequency with which different data types have been used in recent ESA decisions).
87. A representative larger-scale allozyme study, for example, bore on the delisting of the Douglas white-tailed deer DPS, which featured a presumptive thirty-five loci. See Final Rule to Remove the Douglas County Distinct Population Segment of Columbian White-Tailed Deer from the Federal List of Endangered and Threatened Wildilife, 68 Fed. Reg. 43, 647 (July 24, 2003) (to be codified at 50 C.F.R. pt. 17)
88. (citing Thomas Gavin & Bernie May, 52 J. WILDLIFE MGMT. 1 (1988)). Of these thirty-five, only seven were variable and informative for the focal species.
89. See Gavin & May, supra, at 1. By contrast, even the smallest modern study of DNA sequence data will include several hundred nucleotides. Because each nucleotide site might vary between individuals, DNA sequence data generally provides an opportunity for much higher-resolution data than allozymes, though in practice, even DNA sequence data can be invariant.
90. See, e.g., Alec J. Jeffreys, Genetic Fingerprinting, 11 NATURE MED. 1035, 1036 (describing a case in which allozyme evidence could establish some familial tie between individuals in an immigration and parentage dispute, but DNA evidence was required to establish a parent-child relationship specifically).
91. See Endangered Status for the Peninsular Ranges Population Segment of the Desert Bighorn Sheep in Southern Cahfornia, 63 Fed. Reg. 13, 134 (Mar. 18, 1998) (to be codified at 50 C.F.R. pt. 17) (discussing RFLP versus DNA sequence data).
92. "Base pairs" is often abbreviated "bp," such that a sequence of DNA 350 base pairs (nucleotides) long is abbreviated "350 bp."
93. We may complicate the picture by hypothesizing that different DNA sequences will result in cut sites occurring in different positions along the fragment, as often happens. This results in different alleles having not only different numbers of cut sites (and thus resulting fragments) but also different sizes of resulting fragments. Nevertheless, the point stands: a RFLP results in far fewer potential alleles than the underlying DNA sequence data themselves.
94. See generally Pieter Vos et al., AFLP: A New Technique for DNA Fingerprinting, 23 NUCLEIC ACIDS RES. 4407 (1995) (describing the technique).
95. DNA sequencing technology was developed in the late 1970s, and became widely available in the late 1980s and early 1990s.
96. See F. Sanger, S. Nicklen & A.R.. Coulson, DNA Sequencing with Chain-terminating Inhibitors, 74 PROC. NAT'L ACAD. Sa. U.S.A. 5463 (1977). Sanger won one of his two Nobel Prizes in Chemistry for his work in developing DNA sequencing technology. See Biography of Fredrick Sanger, SANGER INST., http://www.sanger.ac.uk/about/people/fsanger.html (last visited Oct. 31, 2010). BIOSIS lists over 64,000 citations to the 1977 paper. Newer, high-throughput technologies are now becoming widespread and will greatly increase the resolution of available data by sequencing orders of magnitude more DNA and even whole genomes.
97. See, e.g.. Jay Shendure & Hanlee Ji, Next-generation DNA Sequencing, 26 NATURE BIOTECHNOLOGY 1135 (2008) (reviewing sequencing techniques now becoming available).
98. ST,
99. see infra Part III.C.1 (discussing Wright's F Statistics), one would need 700 microsatellite loci. See Takezaki & Nei, supra, at 389, tbl.2. Even then, the analysis would result in the correct relationships only 90.4 percent of the time.
100. See id. For more reahstic datasets of ten microsatellite loci, the same statistic correctly inferred the evolutionary relationships in 2.9 percent of trials. See
101. id. As a guiding principle, then, microsatellites are not appropriate for inferring relationships among samples. Nevertheless, authors commonly use microsatellites in this way, despite their demonstrated failures.
102. Chromosomes are dense aggregations of nucleic acids and proteins that form coherent rod-like structures in the nucleus of eukaryotic cells (that is, cells having a nucleus), and circular structures in bacteria and eukaryotic organelles such as mitochondria.
103. The human mitochondrion, for example, contains thirteen protein-coding genes, two moderately-sized regions encoding ribosomal RNAs, and twenty-two small regions encoding transfer RNAs.
104. See Anderson et al., Sequence and Organization of the Human Mitochondrial Genome, 290 NATURE 457 (1981). Other species' mitochondria are similar in size and composition.
105. The human mitochondrion contains about 16,500 bp. See id. at 457. By comparison, the human nucleus contains over three billion base pairs.
106. See The Human Genome Project Completion: Frequently Asked Questions, NAT'L HUMAN GENOME RES. INST., http://www.genome.gov/11006943 (last visited Oct. 3, 2010).
107. This is for at least two reasons: one, a lot of existing (known) sequence information exists from which to base amplifications, and two, mtDNA is haploid, containing only one copy of the target gene. Because only one copy is present, it is simple to read clean sequence data from the mitochondrion. Where multiple, different copies of genes exist, conflicting sequence reads can result.
108. A variety of mutation rates in different gene regions makes the mitochondrion rather like a buffet: depending on the timescale of interest, a researcher may collect data from gene regions with faster or slower rates. Faster rates tend to inform shorter-timescale questions. Mutational rates vary within the mitochondrion over about an order of magnitude.
109. See JOHN C. AVISE, MOLECULAR MARKERS, NATURAL HISTORY, AND EVOLUTION 123 (2d ed. 2004) (reviewing relevant literature).
110. See infra note 88 (discussing Hardy-Weinberg equilibrium).
111. For example, see the case studies of the beluga whale and pygmy owl, infra Part IV.
112. As opposed to the circular chromosome of the mitochondrion and of free-living bacteria.
113. The largest known genome has over 670 billion nucleotides, and belongs to a lowly amoeba-like single-celled animal.
114. See Laura Wegener Parfrey, Daniel J. G. Lahr & Laura A. Katz, The Dynamic Nature of Eukaryotic Genomes, 25 MOLECULAR BIOLOGY & EVOLUTION 787 (2008). Clearly, genome size does not scale with an organism's complexity.
115. Technical reasons include multiple copies of the same gene in the nucleus and the difficulty of sequencing different alleles of the same gene simultaneously. Historical reasons include the wide availability of mitochondrial primers-critical tools in the PCR and sequencing processes that are based on known sequence data. Hence, there is a positive feedback loop with molecular data; once some sequence information is available, it is easier to focus on the known gene region than to look elsewhere in the genome for data.
116. I distinguish between sequence data (that is, the actual sequence of nucleotides in the genetic code) and other forms of data because nuclear DNA is widely used in the other data types I discuss here. Microsatellites and RFLPs, for example, are most often expressions of nuclear DNA data, but do not result in actual sequence-level information.
117. See infra Part III.A.1 (discussing individual-focused approaches).
118. Captive breeding programs monitor genetic relatedness among individuals, in order to maximize the amount of genetic diversity by making breeding decisions that minimize inbreeding. For the importance of precision in measuring genetic differences in natural populations of listed species,
119. see infra Part IV.B (discussing the pygmy owl).
120. The transfer RNA molecules encoded on the mitochondrion are used in protein synthesis.
121. For an accessible and interesting treatment of noncoding DNA and other features of the nuclear genome,
122. see Carl Zimmer, Now: The Rest of the Genome, N.Y. TIMES, NOV. 11, 2008, at D1.
123. See generally Michael M. Hansen, Expression of Interest: Transcriptomics and the Designation of Conservation Units, 19 MOLECULAR ECOLOGY 1757 (2010).
124. For an example of natural selection acting on genes that are subject to natural selection in the wild,
125. see generally Catherine R. Linnen et al., On the Origin and Spread of an Adaptive Allele in Deer Mice, 325 SCIENCE 1095 (2009) (linking selection for a hght-colored coat in deer mice to a particular genetic locus, the expression of which results in lighter coloration).
126. These are the basic assumptions of the Hardy-Weinberg equilibrium (HWE). HWE is the baseline-the null hypothesis, in experimental terms-against which observed populations are measured. A significant departure from HWE is therefore evidence that one or more evolutionary forces is acting. Researchers most often interpret violations of HWE as evidence of selection or population subdivision (requiring nonrandom mating). This is necessarily a gross simplification, and many volumes have been written about the subject.
127. See, e.g., HARTL, supra note 59.
128. See, e.g., Laurent Excoffier, Guillaume Laval & Stefan Schneider, Arlequin (Version 3.0): An Integrated Software Package for Population Genetics Data Analysis, 1 EVOLUTIONARY BIOINFORMATICS ONLINE 47 (2005) (providing a means of calculating distances for various data types and for both individual differences (within a species) and differences between groups of individuals);
129. see also L.L. Cavalli-Sforza & A.W.F. Edwards, Phylogenetic Analysis: Models and Estimation Procedures, 19 AM. J. HUMAN GENETICS 233 (1967) (discussing the often-used Cavalli-Sforza chord distance measure).
130. See HARTL, supra note 59, at 107. This pairwise distance between DNA sequences is known as π (pi). The raw number of pairwise differences may be augmented using a model of molecular evolution; if, for example, a mutation of T → C is more probable than T → G, weighting genetic distances according to a specific mutational model can account for these probabilities.
131. See DPS Policy, supra note 39, at 4725.
132. Low diversity can also result from a recent population "bottleneck," in which a small number of individuals survives for a period of time, inbreeding and losing alleles, and subsequently increases in number-in which case the population size will have recovered from the bottleneck, but the genetic diversity will not yet have rebounded. The genetic bottleneck is a critical concept in conservation biology, because imperiled species often experience this kind oí population depression, but it is not directly relevant to diagnosing a DPS for listing.
133. Note that an individual can be either homozygous or heterozygous for a given diploid locus. Thus the proportion of heterozygotes and the proportion of homozygotes sums to one, for any given diploid locus.
134. See, e.g., Andrew Young, Tim Boyle & Tony Brown, The Population Genetic Consequences of Habitat Fragmentation for Plants, 11 TRENDS IN ECOLOGY & EVOLUTION 413 (1996).
135. See DPS Policy, supra note 39, at 4725.
136. See, e.g., RICHARD FRANKHAM, JONATHAN BALLOU & DAVID BRISCOE, INTRODUCTION TO CONSERVATION GENETICS 78 (2009).
137. Here, "migration" refers to the exchange of individuals between populations, and "genetic drift" refers to chance changes in allele frequency between generations, a factor only in very small populations.
138. See HARTL, supra note 59, at 29.
139. For an example of the test for HWE in a candidate species for ESA listing, see Terry D. Beacham, Douglas E. Hay & Khai D. Le, Population Structure and Stock Identification of Eulachon (Thaleichthys Pacificus), an Anadromous Smelt, in the Pacific Northwest, 7 MARINE BIOTECHNOLOGY 363 (2005).
140. See The Administrative Procedure Act, Pub. L. No. 79-404, 60 Stat. 237 (codified as amended in scattered sections of 5 U.S.C.).
141. See §1533(b)(1)(A) (2006).
142. See 5 U.S.C. §706 (2006);
143. Earth Island Inst. v. Hogarth, 494 F.3d 757, 766 (9th Cir. 2007) ("An agency action is not supportable if it did not consider all the relevant factors and if there is no rational connection between the facts found and the determination made.")
144. (citing Pac. Coast Fed'n of Fishermen's Ass'ns v. Nat'l Marine Fisheries Serv., 265 F.3d 1028, 1034 (9th Cir. 2001));
145. see also Motor Vehicle Mfrs. Ass'n v. State Farm Mut. Auto. Ins. Co., 463 U.S. 29, 43 (1983) ("Normally, an agency rule would be arbitrary and capricious if the agency has relied on factors which Congress has not intended it to consider, entirely failed to consider an important aspect of the problem, offered an explanation for its decision that runs counter to the evidence before the agency, or is so implausible that it could not be ascribed to a difference in view or the product of agency expertise.").
146. See, e.g., Baltimore Gas and Elec. Co. v. Natural Res. Def. Council, 462 U.S. 87, 103 (1983) ("[A] reviewing court must remember that the Commission is making predictions, within its area of special expertise, at the frontiers of science. When examining this kind of scientific determination, as opposed to simple findings of fact, a reviewing court must generally be at its most deferential."). In Baltimore Gas, the Court deferred to the Nuclear Regulatory Commission's decision regarding the environmental impact of long-term storage of nuclear material. Id. at 104. The Court distinguished, interestingly, between "simple findings of fact" and "scientific determination[s]." Id. at 103.
147. Note that the researchers would not know prior to sampling that the gene region is identical in all individuals. This would become apparent only after sequencing, at which point the nucleotide sequence would be the same in each sample. As a result, a challenger could employ this argument only in a situation in which the agency improperly relied on the data after the fact; for example, using the results to demonstrate a lack of discreteness between the two populations, which is plainly not a reasonable interpretation of the data in hand.
148. Note that small sample sizes present this problem even when variable markers are used: the subtler the genetic difference, the larger the sample size needed to detect it.
149. See generally Robin S. Waples, Separating the Wheat from the Chaff: Patterns of Genetic Differentiation in High Gene Flow Species, 89 J. HEREDITY 438 (1998). As a result, if a challenger can show a statistical impossibility of finding that two populations are significantly different with the given dataset, a court could find the resulting agency finding arbitrary and capricious.
150. See also Berry J. Brosi & Eric G. Biber, Statistical Inference, Type II Error, and Decision Making under the US Endangered Species Act, 7 FRONTIERS ECOLOGY & ENV'T 487 (2009) (discussing statistical power in genetic data in the ESA context).
151. It is possible to avoid making this assumption by using models of evolutionary change that account for mutations that can result in identical alleles arising independently.
152. This tree, estimating the relationships among Central Valley Chinook salmon populations, is used with permission from THOMAS P. GOOD, ROBIN S. WAPLES & PETE ADAMS, NOAA TECHNICAL MEMORANDUM NMFS-NWFSC-66, UPDATED STATUS OF FEDERALLY LISTED ESUS OF WEST COAST SALMON AND STEELHEAD 156 (2005), available at http://www.nwr.noaa.gov/Publications/Biological-Status-Reviews/upload/SR2005- allspecies.pdf. This particular tree is based on allozyme data, with nodes indicating different fish populations. Branch length indicates a measure of genetic distance between the populations.
153. From G. M. O'Corry-Crowe et al., Phylogeography, Population Structure and Dispersal Patterns of the Beluga Whale Delphinapterus leucas in the Western Nearctic Revealed by Mitochondrial DNA, 6 MOLECULAR ECOLOGY 955, 961 (1997). This haplotype network details the mtDNA patterns of the beluga whale. Each circle, or node, represents a particular allele of mtDNA, with the connections between them representing mutation events. The size of the circle represents the abundance of the allele in the sample. The numbers, used for identifying individual alleles, are arbitrary. Note that a network can represent ambiguous relationships; a given allele can be equally closely linked to multiple others.
154. Id.
155. See, e.g., JOSEPH FELSENSTEIN, INFERRING PHYLOGENIES (2004) (exhaustively treating the subject);
156. iee generally MOLECULAR SYSTEMATICS (David M. Hillis, Craig Moritz & Barbara K. Mable eds., 2d ed. 1996) (an aging, but still widely used, reference for the details of molecular phylogenetic methods);
157. see also HARTL, supra note 59, at 136-38 (introducing the topic).
158. UPGMA sequentially combines the two least-distant individuals in the overall dataset into a higher-order cluster. Once a cluster is formed, its distance to the remaining individuals is the average of the members' distances.
159. See PETER H. A. SNEATH & ROBERT R. SOKAL, NUMERICAL TAXONOMY: PRINCIPLES AND PRACTICE OF NUMERICAL CLASSIFICATION 230-34 (1973). Neighbor joining joins the two least-distant individuals, with distances transformed by an equation that incorporates the number of individuals to be joined and the distances between each pair. The algorithm then adds each nearest neighbor in stepwise fashion.
160. See generally Naruya Saitou & Masatoshi Nei, The Neighbor-joining Method: A New Method for Reconstructing Phylogenetic Trees, 4 MOLECULAR BIOLOGY & EVOLUTION 406 (1987). Note that both methods produce a single tree from a given data matrix, which can give the misleading appearance of having produced the one "true" tree. Note also the vintage of these methods; prior to powerful desktop computers, the speed of a tree-building method was more critical than it is today.
161. This distinction highlights the different focus between the academic biologists that publish the primary data papers and conservationists or agency biologists that may have a particular legal test in mind when evaluating data.
162. Models of molecular evolution effectively weight the relationships among individuals based on a description of how mutations occur in the DNA sequence. The models vary most importantly in their rates and probabilities of character-state changes. Different character-state changes (for example a mutation that changes an "A" to a "T" in the DNA sequence) occur with different frequencies in nature, due in part to different biochemical properties of the nucleotides. While the earliest model of molecular evolution hypothesized that all changes (for example, from "A" to any one of "C," "G," or "T") were equally probable, subsequent models have improved by specifying different rates and probabilities.
163. See Pietro Lió & Nick Goldman, Models of Molecular Evolution and Phytogeny, 8 GENOME RES. 1233 (1998), for an accessible review.
164. See generally FELSENSTEIN, supra note 111, for a detailed discussion of the differences among phylogenetic methods.
165. See FELSENSTEIN, supra note 111, at 335-62.
166. See Takezaki & Nei, supra note 70.
167. An algorithm is still required to infer a set of connections among individuals in a network, but because nodes (individuals) in a network can have multiple connections to other such nodes, the philosophy underlying network-building is probably less important than in tree building. Parsimony criteria are the most often used in building biological minimum spanning networks, such as those discussed here.
168. See Alan R. Templeton, Nested Clade Analyses of Phylogeographic Data: Testing Hypotheses About Gene Flow and Population History, 7 MOLECULAR ECOLOGY 381, 381 (1998). For an example of NCA in the context of an endangered species,
169. see K. Shanker et al., Phylogeography of Olive Ridley Turtles (Lepidochelys olivacea,) on the East Coast of India: Implications for Conservation Theory, 13 MOLECULAR ECOLOGY 1899 (2004).
170. See supra Part III.B.2.
171. "Clade" is a general term in evolutionary biology, referring to any group of individuals more closely related to each other than any other such group.
172. See Templeton, supra note 119, at 384 (describing the technique).
173. See generally Rémy J. Petit, The Coup de Grâce for the Nested Clade Phylogeographic Analysis?, 17 MOLECULAR ECOLOGY 516 (2007) (discussing results that indicate NCA has extremely high false-positive rates of detecting restricted gene flow);
174. see also, L.L. Knowles, The Burgeoning Field of Statistical Phylogeography, 17 J. EVOL. BIOL. 1, 4 (2004) (criticizing NCA as not accounting for stochastic genetic processes).
175. BIOSIS reports more than 300 articles with NCA in the topic heading.
176. See Takezaki & Nei, supra note 70.
177. See Petit, supra note 123.
178. See supra Part LB (discussing the DPS concept).
179. See supra Part III.A.1.
180. See Sewall Wright, Genetical Structure of Populations, 166 NATURE 247, 247 (1950).
181. n, the heterozygosity of the individual relative to the subpopulation, and the individual relative to the total, respectively.
182. See AVISE, supra note 75, at 24;
183. Montgomery Slatkin, A Measure of Population Subdivision Based on Microsatellite Allele Frequencies, 139 GENETICS 457 (1995).
184. Here, "subpopulation" is Wright's term and is equivalent to the concept of a population as I've used it.
185. ST) based on an underlying distribution. This "null" distribution is created by permuting the data matrix many times, to approximate a random distribution. Hence, the significance of the observed value is the probability of it occurring by chance alone.
186. ST one might use; for our purposes, a value of one is both illustrative and indicative of the calculation under several formulations of the statistic. Some versions normalize by the overall level of diversity in the sample.
187. See 16 U.S.C. §1531(b) (2006).
188. See generally L. Excoffier, P.E. Smouse & J.M. Quattro, Analysis of Molecular Variance Inferred from Metric Distances among DNA Haplotypes: Application to Human Mitochondrial DNA Restriction Data, 131 GENETICS 479 (1992).
189. sea turtle, see B.W. Bowen, A.L. Bass, L. Soares & RJ. Toonen, Conservation Implications of Complex Population Structure: Lessons from the Loggerhead Turtle (Caretta caretta), 14 MOLECULAR ECOLOGY 2389 (2005).
190. See, e.g., Excoffier, Laval & Schneider, supra note 89.
191. Peter E. Smouse, Jeffrey C. Long & Robert R. Sokal, Multiple Regression and Correlation Extensions of the 7antel Test of Matrix Correspondence, 35 SYSTEMATIC ZOOLOLOGY 627 (1986).
192. For an example of the use of the Mantel test in the ESA context, see V.L. Friesen et al., Population Genetic Structure and Conservation of Marbled Murrelets (Brachyramphus Marmoratus;, 6 CONSERVATION GENETICS 607 (2005).
193. See, e.g., Peter E. Smouse & Rod Peakall, Spatial Autocorrelation Analysis of Individual Multiallele and Multilocus Genetic Structure, 82 HEREDITY 561 (1999).
194. But see Ryan P. Kelly et al., A Method for Detecting Population Genetic Structure in Diverse, High Gene-Flow Species, 101 J. HEREDITY 423 (2010) (suggesting that spatial autocorrelation has high false positive and false negative rates of detection for population subdivision). For the use of the method in an endangered species, though with demographic rather than genetic data,
195. see Peter C. Trenham, Walter D. Koenig & H. Bradley Shaffer, Spatially Autocorrelated Demography and Interpond Dispersal in the Salamander Ambystoma Californiense, 82 ECOLOGY 3519 (2001).
196. See, e.g., M.P. Miller, Alleles In Space (AIS): Computer Software for the Joint Analysis of Interindividual Spatial and Genetic Information, 96 J. HEREDITY 722 (2005);
197. Ryan P. Kelly et al., supra note 141.
198. Identifying the individual alleles of diploid organisms is not necessarily trivial. Distinguishing the individual alleles of a heterozygote (an organism having two different alleles at the same genetic locus) is known as determining the "phase" of the alleles.
199. For a useful review of these techniques, see Adam G. Jones & William R. Ardren, Methods of Parentage Analysis in Natural Populations, 12 MOLECULAR ECOLOGY 2511 (2003). For an analysis of different data types' performances in parentage analysis,
200. see S. Gerber et al., Comparison of Microsatellites and Amplified Fragment Length Polymorphism Markers for Parentage Analysis, 9 MOLECULAR ECOLOGY 1037 (2000).
201. For a helpful review, see Stephanie Manel, Oscar E. Gaggiotti & Robin S. Waples, Assignment Methods: Matching Biological Questions with Appropriate Techniques, 20 TRENDS ECOLOGY & EVOLUTION 136 (2005). For a review of Bayesian statistical inference in assignment tests,
202. see Mark A. Beaumont & Bruce Rannala, The Bayesian Revolution in Genetics, 5 NATURE REVS. GENETICS 251, 254 (2004).
203. Particularly relevant to this analysis is a software package called STRUCTURE. See Jonathan K. Pritchard, Matthew Stephens & Peter Donnelly, Inference of Population Structure Using Multilocus Genotype Data, 155 GENETICS 945, 956 (2000).
204. See also the related software, Software, PRITCHARD LAB, UNIV. CHICAGO, http://pritch.bsd.uchicago.edu/software.html (last visited Oct. 30, 2010).
205. For an example of parentage analysis in the ESA context, see Jason Baumsteiger et al., Use of Parentage Analysis to Determine Reproductive Success of Hatchery-Origin Spring Chinook Salmon Outplanted into Shitike Creek, Oregon, 28 N. AM. J. FISHERIES MGMT. 1472 (2008). For an example of an assignment test,
206. see Jesse W. Breinholt et al., Population Genetic Structure of an Endangered Utah Endemic, Astragalus Ampullarioides (Fabaceae), 96 AM. J. BOTANY 661 (2009).
207. This rate is an accepted standard for most researchers and journals. Note, however, that this provides no information about the test's false-negative rate, the probability of finding no significant difference when in fact one exists.
208. Usually denoted p = 0.05.
209. Note that this hypothetical works equally well for any agency nonaction on the basis of a failure to find statistically significant results; it is a point about false negative rates, not about erring on the side of listing rather than non-listing.
210. See, e.g., ROBIN S. WAPLES, NOAA TECHNICAL MEMORANDUM NMFS F/NWC-194, DEHNITION OF "SPECIES" UNDER THE ENDANGERED SPECIES ACT: APPLICATION TO PACIFIC SALMON, (1991), available at http://www.nwfsc.noaa.gov/publications/ techmemos/tm194/waples.htm ("It is important to realize that 'statistical significance' is a different concept than 'evolutionary significance' as it relates to the Act. . . . [F]ailure to find a statistically significant difference does not disprove the existence of population differences. Power to detect true differences in population means is a function of sample size, so this factor should also be considered in evaluating results of statistical tests.");
211. see also Brosi & Biber, supra note 106, at 489 ("[W]hen the FWS analyzed whether low water flows were correlated with endangered fish mortality in the Klamath River of Oregon and California, the agency required a statistically significant connection between the two before it would commit to action to increase water flows, even though ... the lack of a statistically significant correlation would provide little or no information about whether such a correlation existed.")
212. (citing DJ. McGarvey, Merging Precaution with Sound Science under the Endangered Species Act, 57 BIOSCIENCE 65 (2007)).
213. See, e.g., Listing the San Miguel Island Fox, Santa Rosa Island Fox, Santa Cruz Island Fox, and Santa Catalina Island Fox as Endangered, 69 Fed. Reg. 10,335 (Mar. 5, 2004) (to be codified at 50 C.F.R. pt. 17).
214. See Notice of Interagency Cooperative Policy on Information Standards under the Endangered Species Act, 59 Fed. Reg. 34,271 (July 1, 1994) (noting use of academic articles);
215. Notice of Interagency Cooperative Policy for Peer Review in Endangered Species Act Activities, 59 Fed. Reg. 34,270 (July 1,1994) (noting use of data from wide range of sources).
216. See Endangered Status for the Cook Inlet Beluga Whale, 73 Fed. Reg. 62,919 (Oct. 22, 2008) (to be codified at 50 C.F.R. pt. 224).
217. Id. at 62,926 (citations omitted) (citing O'Corry-Crowe et al., supra note 109).
218. Id.
219. Status reviews are required for each listed species every five years. See 16 U.S.C. § 1533(c)(2)(A) (2006).
220. R.C. HOBBS & K.E.W. SHELDEN, NAT'L OCEANIC & ATMOSPHERIC ADMIN., AFSC PROCESSED REPORT NO. 2008-08, SUPPLEMENTAL STATUS REVIEW AND EXTINCTION ASSESSMENT OF COOK INLET BELUGAS (DELPHINAPTERUS LEUCAS) (2008).
221. R.C. HOBBS, K.E.W. SHELDEN, D.J. VOS, K.T. GOETZ & DJ. RUGH, NAT'L OCEANIC & ATMOSPHERIC ADMIN, AFSC PROCESSED REP. NO. 2006-16, STATUS REVIEW AND EXTINCTION ASSESSMENT OF COOK INLET BELUGAS (DELPHINAPTERUS LEUCAS) (2006). The beluga was a candidate species prior to being listed, and thus the subject of a status review.
222. See id. at 37 (internal citation omitted).
223. See id. at 10 (internal citations omitted).
224. See G.M. O'Corry-Crowe et al., Phylogeography, Population Structure and Dispersal Patterns of the Beluga Whale Delphinapterus Leucas in the Western Nearctic Revealed by Mitochondrial DNA, 6 MOLECULAR ECOLOGY 955 (1997).
225. See id. at 957, 960.
226. See id. at 960.
227. See id. at 962.
228. Again, this is given the data in hand. Further data could muddy the waters, as it were, but the agency must make decisions based on the available data. Also note that O'Corry-Crowe et al., supra note 162, does not discuss the possibility that the observed low genetic diversity is a result of a decline in population size, which is a general concern for imperiled species.
229. See Endangered Status for the Cook Inlet Beluga Whale, 73 Fed. Reg. 62, 919, 62, 926 (Oct. 22,2008) (to be codified at 50 C.F.R. pt. 224).
230. See Proposed Endangered Status for the Cook Inlet Beluga Whale, 72 Fed. Reg. 19, 854, 19, 855 (Apr. 20,2007) (to be codified at 50 C.F.R. pt. 224).
231. See Determination of Endangered Status for the Cactus Ferruginous Pygmy-owl in Arizona, 62 Fed. Reg. 10,730 (Mar. 10,1997) (to be codified at 50 C.F.R. pt. 17).
232. See id. at 10, 731.
233. See Final Rule to Remove the Arizona Distinct Population Segment of the Cactus Ferruginous Pygmy-owl from the Federal List of Endangered and Threatened Wildlife, 71 Fed. Reg. 19,452 (Apr. 14, 2006) (to be codified at 50 C.F.R. pt. 17) [hereinafter Final Arizona DPS Removal Rule].
234. See DPS Policy, supra note 39, at 4725.
235. Determination of Endangered Status for the Cactus Ferruginous Pygmy-owl in Arizona, 62 Fed. Reg. 10, 730, 10, 737 (Mar. 10, 1997) (to be codified at 50 C.F.R. pt. 17).
236. Nat'l Ass'n of Home Builders v. Norton, 340 F.3d 835, 852 (9th Cir. 2003).
237. See id.
238. See id. at 847.
239. See id. at 852.
240. See ARIZ. ECOLOGICAL SERVS. OFFICE, U.S. FISH & WILDLIFE SERV., WHITE PAPER: SIGNIFICANCE OF THE WESTERN POPULATION(S) OF THE CACTUS FERRUGINOUS PYGMY-OWL 318 (2003).
241. See id. at 321-28.
242. See Proposed Rule to Remove the Arizona Distinct Population Segment of the Cactus Ferruginous Pygmy-owl from the Federal List of Endangered and Threatened Wildlife, 70 Fed. Reg. 44,547 (Aug. 3, 2005) (to be codified at 50 C.F.R. pt. 17) [hereinafter Proposed Arizona DPS Removal Rule]. The delisting became final a year later. See Final Arizona DPS Removal Rule, supra note 171.
243. See Memorandum from C.H. Huckelberry, County Administrator, to Pima County Board of Supervisors 1 (Jan. 22,2001) (on file with author).
244. Id. The present versions of the Plan are available at SONORAN DESERT CONSERVATION PLAN, http://www.pima.gov/cmo/sdcp (last visited Oct. 31, 2010).
245. See GLENN A. PROUDFOOT & R. DOUGLAS SLACK, COMPARISONS OF FERRUGINOUS PYGMY-OWL MTDNA AT LOCAL AND INTERNATIONAL SCALES 5 (2001).
246. See id. at 4-5.
247. See id. at 5-6.
248. Id. at 6.
249. ST.
250. See Proudfoot et al., infra note 188. These calculated values for population subdivision suggest an extremely attenuated level of connectivity between Arizonan and Mexican owl populations.
251. ST and related statistics, I should note that Proudfoot does not consider these values to represent "markedly different" populations in Arizona and Mexico.
252. See E-mail from Glenn A. Proudfoot, Research Associate, Vassar College, to author (Nov. 24, 2009, 06:05 PST) (on file with author).
253. See Proposed Arizona DPS Removal Rule, supra note 180, at 44, 547.
254. Id. at 44,550 (emphasis added) (citation omitted).
255. Id. (emphasis added) (citations omitted).
256. See reference to this population in PROUDFOOT & SLACK, supra note 183.
257. See PROUDFOOT & SLACK, supra note 183.
258. See Proudfoot et al., supra note 188.
259. See supra note 189 and accompanying text.
260. See Final Arizona DPS Removal Rule, supra note 171, at 19, 454 ("No new information related to the Arizona DPS is presented that is not already found in [PROUDFOOT & SLACK, supra note 183], which is available to the public and cited in our proposed rule. We did not rely on any of the work within Dr. Proudfoot's unpublished papers in making our determination."). Proudfoot et al. had submitted the microsatellite data paper to CONSERVATION GENETICS on July 25, 2005, before FWS issued its Proposed Rule. The dataset eventually contained in their 2006 CONSERVATION GENETICS article, supra note 188, was thus available to FWS during the comment period, though the above quote from the Final Rule makes it clear that the agency did not consider the new data to be of any value. Proudfoot has refused to speculate on why the FWS did not take the microsatellite data into account. See E-mail from Glenn A. Proudfoot, Research Associate, Vassar College, to author (Nov. 24,2009) (on file with author).
261. See Final Arizona DPS Removal Rule, supra note 171, at 19, 454
262. 16 U.S.C. §1533(b)(1)(A) (2006)
263. See PROUDFOOT & SLACK, supra note 183, at 12
264. Proudfoot et al., supra note 188, at 951
265. See supra note 188
266. See Nat'l Ass'n of Home Builders v. Norton, 340 F.3d 835, 847 (9th Cir. 2003) (indicating the loss-of-genetic-variability criterion for making the creation of a "gap" in the range of a species significant was speculative absent actual genetic data)
267. Defenders of Wildlife and allied groups subsequently challenged FWS's decision to delist the owl, in part arguing that the available genetic data favored a finding of significance for the Arizona population under the DPS Policy. In an unpublished memorandum opinion, the Ninth Circuit upheld the FWS delisting decision without discussing the treatment of genetic data
268. See Nat'l Ass'n of Home Builders v. Norton, 2009 WL 226048, at *1 (9th Cir. Jan. 30, 2009).
269. See Ninety-Day Finding on a Petition to List the Cactus Ferruginous Pygmy-Owl as Threatened or Endangered with Critical Habitat, 73 Fed. Reg. 31, 418, 31, 420. (June 2, 2008)
270. See supra note 188
271. See Final Arizona DPS Removal Rule, supra note 171. For a discussion of the significance prong of the DPS test
272. see DPS Policy, supra note 39, at 4725
273. See DPS Policy, supra note 39, at 4725 (indicating that the significance of a DPS is not limited to the listed factors, and that "it is not possible to describe prospectively all the classes of information that might bear on the biological and ecological importance of a discrete population segment")
274. But see Ctr. for Biological Diversity v. Lohn, 296 F. Supp. 2d. 1223 (2003) (remanding agency decision for a failure to use the best available science in considering petition to list the "Southern Resident" population of orca as a DPS), vacated as moot, 511 F.3d 960 79th Cir. 2007)
275. See Endangered Status for the Cook Inlet Beluga Whale, 73 Fed. Reg. 62, 919 (Oct. 22, 2008) (to be codified at 50 C.F.R. pt. 224)
276. Id. at 62,930. This is typical of ESA rules and proposed rules in the Federal Register
277. See Final Arizona DPS Removal Rule, supra note 59, at 19, 458. Making references available by mail is nearly ubiquitous in FWS listing decisions; NOAA/NMFS routinely references the agency's website
278. PROUDFOOT & SLACK, supra note 183
279. I am grateful to FWS's Nick Carillo for his help in finding, scanning, and emailing the 2001 report. In this case, the process took several weeks, but given less enthusiastic help from an agency office, one imagines that obtaining documents might take longer than the comment period on a proposed rule
280. See, e.g., Doremus & Tarlock, supra note 8, at 36
281. See, e.g., 16 U.S.C. §1533(a)(1)(E) ("other natural or manmade factors")
282. DPS Policy, supra note 39, at 4725
283. See ALASKA REG'L OFFICE, NOAA FISHERIES, http://www.fakr.noaa.gov (last visited Oct. 20, 2010)
284. See Endangered Status for the Cook Inlet Beluga Whale, 73 Fed. Reg. 62, 919 (Oct. 22, 2008) (to be codified at 50 C.F.R. pt. 224)
285. The whole administrative record in an agency rulemaking is subject to judicial review
286. See 5 U.S.C. §706 ("[T]he court shall review the whole record or those parts of it cited by a party.")
287. The Freedom of Information Act has a broad presumption of availability of records
288. See 5 U.S.C. §552(a)(3) (2006) (requiring agency disclosure of records upon any request reasonably describing such records)
289. See GenBank Overview, NAT'L CTR. FOR BIOTECHNOLOGY INFO., http://www.ncbi.nlm.nih.gov/genbank (last visited Oct. 3, 2010)