Skip to main content

Advertisement

Log in

Improving conservation policy with genomics: a guide to integrating adaptive potential into U.S. Endangered Species Act decisions for conservation practitioners and geneticists

  • Review Article
  • Published:
Conservation Genetics Aims and scope Submit manuscript

Abstract

Rapid environmental change makes adaptive potential—the capacity of populations to evolve genetically based changes in response to selection—more important than ever for long-term persistence of at-risk species. At the same time, advances in genomics provide unprecedented power to test for and quantify adaptive potential, enabling consideration of adaptive potential in estimates of extinction risk and laws protecting endangered species. The U.S. Endangered Species Act (ESA) is one of the most powerful environmental laws in the world, but so far, the full potential of genomics in ESA listing and recovery decisions has not been realized by the federal agencies responsible for implementing the ESA or by conservation geneticists. The goal of our paper is to chart a path forward for integrating genomics into ESA decision making to facilitate full consideration of adaptive potential in evaluating long-term risk of extinction. For policy makers, managers, and other conservation practitioners, we outline why adaptive potential is important for population persistence and what genomic tools are available for quantifying it. For conservation geneticists, we discuss how federal agencies can integrate information on the effect of adaptive potential on extinction risk—and the related uncertainty—into decisions, and suggest next steps for advancing understanding of the effect of adaptive potential on extinction risk. The mechanisms and consequences of adaptation are incredibly complex, and we may never have a complete understanding of adaptive potential for any organism. Nevertheless, we argue that the best available evidence regarding adaptive potential can now be incorporated by federal agencies into modeling and decision making processes, while at the same time conserving genome-wide variation and striving for a deeper understanding of adaptive potential and its effects on population persistence to improve decision making into the future.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Agashe D, Falk JJ, Bolnick DI (2011) Effects of founding genetic variation on adaptation to a novel resource. Evolution 65:2481–2491

    Article  PubMed  Google Scholar 

  • Aitken SN, Whitlock MC (2013) Assisted gene flow to facilitate local adaptation to climate change. Annu Rev Ecol Evol Syst 44:367–388. https://doi.org/10.1146/annurev-ecolsys-110512-135747

    Article  Google Scholar 

  • Allendorf FW, Hohenlohe PA, Luikart G (2010) Genomics and the future of conservation genetics. Nat Rev Genet 11:697–709

    Article  PubMed  CAS  Google Scholar 

  • Allendorf FW, Luikart G, Aitken SN (2013) Conservation and the genetics of populations, 2nd edn. Wiley, Oxford

    Google Scholar 

  • Alvarez M, Schrey AW, Richards CL (2015) Ten years of transcriptomics in wild populations: what have we learned about their ecology and evolution? Mol Ecol 24:710–725

    Article  PubMed  CAS  Google Scholar 

  • Andrews KR, Good JM, Miller MR et al (2016) Harnessing the power of RADseq for ecological and evolutionary genomics. Nat Rev Genet 17:81–92. https://doi.org/10.1038/nrg.2015.28

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Bataille A, Cashins SD, Grogan L, Skerratt LF, Hunter D, McFadden M, Scheele B, Brannelly LA, Macris A, Harlow PS, Bell S, Berger L, Waldman B (2015) Susceptibility of amphibians to chytridiomycosis is associated with MHC class II conformation. Proc R Soc B 282:20143127

    Article  PubMed  Google Scholar 

  • Beaumont MA, Balding DJ (2004) Identifying adaptive genetic divergence among populations from genome scans. Mol Ecol 13:969–980

    Article  PubMed  CAS  Google Scholar 

  • Bell G, Collins S (2008) Adaptation, extinction and global change. Evol Appl 1:3–16

    Article  PubMed  PubMed Central  Google Scholar 

  • Bell G, Gonzalez A (2009) Evolutionary rescue can prevent extinction following environmental change. Ecol Lett 12:942–948. https://doi.org/10.1111/j.1461-0248.2009.01350.x

    Article  PubMed  Google Scholar 

  • Bell G, Gonzalez A (2011) Adaptation and evolutionary rescue in metapopulations experiencing environmental deterioration. Science 332:1327–1330. https://doi.org/10.1126/science.1203105

    Article  PubMed  CAS  Google Scholar 

  • Berg JJ, Coop G (2014) A population genetic signal of polygenic adaptation. PLOS Genet 10:e1004412. https://doi.org/10.1371/journal.pgen.1004412

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Bernatchez L (2016) On the maintenance of genetic variation and adaptation to environmental change: considerations from population genomics in fishes. J Fish Biol 89:2519–2556

    Article  PubMed  CAS  Google Scholar 

  • Berven KA (1982) The genetic basis of altitudinal variation in the wood frog Rana sylvatica. I. An experimental analysis of life history traits. Evolution 36:962–983

    PubMed  Google Scholar 

  • Bierne N, Roze D, Welch JJ (2013) Pervasive selection or is it… why are FST outliers sometimes so frequent? Mol Ecol 22:2061–2064. https://doi.org/10.1111/mec.12241

    Article  PubMed  Google Scholar 

  • Black WCIV, Baer CF, Antolin MF, DuTeau NM (2001) Population genomics: genome-wide sampling of insect populations. Annu Rev Entomol 46:441–469

    Article  PubMed  CAS  Google Scholar 

  • Blows MW, Hoffmann AA (2005) A reassessment of genetic limits to evolutionary change. Ecology 86:1371–1384. https://doi.org/10.1890/04-1209

    Article  Google Scholar 

  • Bonin A, Nicole F, Pompanon F et al (2007) Population adaptive index: a new method to help measure intraspecific genetic diversity and prioritize populations for conservation. Conserv Biol 21:697–708. https://doi.org/10.1111/j.1523-1739.2007.00685.x

    Article  PubMed  Google Scholar 

  • Boyd C, DeMaster DP, Waples RS, Ward EJ, Taylor BL (2017) Consistent extinction risk assessment under the U.S. Endangered Species Act. Conserv Lett 10:328–336. https://doi.org/10.1111/conl.12269

    Article  Google Scholar 

  • Brosi BJ, Biber EG (2009) Statistical inference, Type II error, and decision making under the US Endangered Species Act. Front Ecol Environ 7:487–494

    Article  Google Scholar 

  • Burger R, Lynch M (1995) Evolution and extinction in a changing environment—a quantitative-genetic analysis. Evolution 49:151–163

    Article  PubMed  Google Scholar 

  • Canessa S, Guillera-Arroita G, Lahoz-Monfort JJ, Southwell DM, Armstrong DP, Chadès I, Lacy RC, Converse SJ (2015) When do we need more data? A primer on calculating the value of information for applied ecologists. Methods Ecol Evol 6:1219–1228

    Article  Google Scholar 

  • Carroll R, Augspurger C, Dobson A, Franklin J, Orians G, Reid W, Tracy R, Wilcove D, Wilson J (1996) Strengthening the use of science in achieving the goals of the endangered species act: an assessment by the Ecological Society of America. Ecol Appl 6:1–11

    Article  Google Scholar 

  • Catchen J, Hohenlohe PA, Bassham S, Amores A, Cresko WA (2013) Stacks: an analysis tool set for population genomics. Mol Ecol 22:3124–3140

    Article  PubMed  PubMed Central  Google Scholar 

  • Catchen JM, Hohenlohe PA, Bernatchez L et al (2017) Unbroken: RADseq remains a powerful tool for understanding the genetics of adaptation in natural populations. Mol Ecol Resour 17:362–365. https://doi.org/10.1111/1755-0998.12669

    Article  PubMed  CAS  Google Scholar 

  • Cattau CE, Fletcher RJ Jr, Kimball RT, Miller CW, Kitchens WM (2017) Rapid morphological change of a top predator with the invasion of a novel prey. Nature Ecol Evol 2(1):108

    Article  Google Scholar 

  • Claussen J, Keck DD, Hiesey WM (1948) Experimental studies on the nature of species. III. Environmental responses of climatic races of Achillea. Carnegie Institution of Washington Publication, Washington

    Google Scholar 

  • Converse SJ, Moore CT, Armstrong DP (2013) Demographics of reintroduced populations: estimation, modeling, and decision analysis. J Wildl Manag 77:1081–1093

    Article  Google Scholar 

  • Converse SJ, Bailey LL, Mosher BA, Funk WC, Gerber BD, Muths E (2017) A model to inform management actions as a response to chytridiomycosis-associated decline. Ecohealth 14:S144–S155

    Article  Google Scholar 

  • Coop G, Witonsky D, Di Rienzo A, Pritchard JK (2010) Using environmental correlations to identify loci underlying local adaptation. Genetics 185:1411–1423

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Crandall KA, Bininda-Emonds ORP, Mace GM, Wayne RK (2000) Considering evolutionary processes in conservation biology. Trends Ecol Evol 15:290–295

    Article  PubMed  CAS  Google Scholar 

  • Creech TG, Epps CW, Landguth EL et al (2017) Simulating the spread of selection-driven genotypes using landscape resistance models for desert bighorn sheep. PLoS ONE 12:e0176960. https://doi.org/10.1371/journal.pone.0176960

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Davey JW, Hohenlohe PA, Etter PD, Boone JQ, Catchen JM, Blaxter ML (2011) Genome-wide genetic marker discovery and genotyping using next-generation sequencing. Nat Rev Genet 12:499–510

    Article  PubMed  CAS  Google Scholar 

  • Dawson TP, Jackson ST, House JI et al (2011) Beyond predictions: biodiversity conservation in a changing climate. Science 332:53–58. https://doi.org/10.1126/science.1200303

    Article  PubMed  CAS  Google Scholar 

  • de Villemereuil P, Frichot É, Bazin É et al (2014) Genome scan methods against more complex models: when and how much should we trust them? Mol Ecol 23:2006–2019. https://doi.org/10.1111/mec.12705

    Article  PubMed  Google Scholar 

  • Doak DF, Himes Boor GK, Bakker VJ, Morris WF, Louthan A, Morrison SA, Stanley S, Crowder LB (2015) Recommendations for improving recovery criteria under the US Endangered Species Act. Bioscience 65:189–199

    Article  Google Scholar 

  • Dobzhansky T, Wright S (1941) Genetics of natural populations. V. Relations between mutation rate and accumulation of lethals in populations of Drosophila pseudoobscura. Genetics 26:23–51

    PubMed  PubMed Central  CAS  Google Scholar 

  • Doremus H (1997) Listing decisions under the Endangered Species Act: why better science isn’t always better policy. Wash Univ Law Q 75:1029–1153

    Google Scholar 

  • [ESA] US Endangered Species Act of 1973, as amended, Pub. L. No. 93-205, 87 Stat. 884 (28 Dec 1973). http://www.fws.gov/endangered/esa-library/pdf/ESAall.pdf

  • Falconer DS, Mackay TFC (1996) Introduction to quantitative genetics. Longman, Harlow

    Google Scholar 

  • Ficetola GF, De Bernardi F (2005) Supplementation or in situ conservation? Evidence of local adaptation in the Italian agile frog Rana latastei and consequences for the management of populations. Anim Conserv 8:33–40. https://doi.org/10.1017/S1367943004001805

    Article  Google Scholar 

  • Fisher RA (1930) The genetical theory of natural selection. Clarendon Press, Oxford

    Book  Google Scholar 

  • Forester BR, Lasky JR, Wagner HH, Urban DL (2018) Comparing methods for detecting multilocus adaptation with multivariate genotype-environment associations. Mol Ecol 27:2215–2233

    Article  PubMed  CAS  Google Scholar 

  • François O, Martins H, Caye K, Schoville SD (2016) Controlling false discoveries in genome scans for selection. Mol Ecol 25:454–469

    Article  PubMed  CAS  Google Scholar 

  • Frankham R, Lees K, Montgomery ME, England PR, Lowe EH, Briscoe DA (1999) Do population size bottlenecks reduce evolutionary potential? Anim Conserv 2:255–260

    Article  Google Scholar 

  • Frankham R, Ballou JD, Briscoe AD (2002) Introduction to conservation genetics. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Frankham R, Brook BW, Bradshaw CJA, Traill LW, Spielman D (2013) 50/500 rule and minimum viable populations: response to Jamieson and Allendorf. Trends Ecol Evol 28:187–188

    Article  PubMed  Google Scholar 

  • Franklin IR (1980) Evolutionary change in small populations. In: Soulé ME, Wilcox BA (eds) Conservation biology: an evolutionary-ecological perspective. Sinauer Associates, Sunderland

    Google Scholar 

  • Franks SJ, Kane NC, O’Hara NB, Tittes S, Rest JS (2016) Rapid genome-wide evolution in Brassica rapa populations following drought revealed by sequencing of ancestral and descendant gene pools. Mol Ecol 25:3622–3631

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Fraser DJ, Bernatchez L (2001) Adaptive evolutionary conservation: towards a unified concept for defining conservation units. Mol Ecol 10:2741–2752

    Article  PubMed  CAS  Google Scholar 

  • Frichot E, Schoville SD, Bouchard G, Francois O (2013) Testing for associations between loci and environmental gradients using latent factor mixed models. Mol Biol Evol 30:1687–1699

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Fritts TH (1984) Evolutionary divergence of giant tortoises in Galapagos. Biol J Linn Soc 21:165–176. https://doi.org/10.1111/j.1095-8312.1984.tb02059.x

    Article  Google Scholar 

  • Funk WC, McKay JK, Hohenlohe PA, Allendorf FW (2012) Harnessing genomics for delineating conservation units. Trends Ecol Evol 27:489–496. https://doi.org/10.1016/j.tree.2012.05.012

    Article  PubMed  PubMed Central  Google Scholar 

  • Garant D, Forde SE, Hendry AP (2007) The multifarious effects of dispersal and gene flow on contemporary adaptation. Funct Ecol 21:434–443

    Article  Google Scholar 

  • Garner BA, Hand BK, Amish SJ, Bernatchez L, Foster JT, Miller KM, Morin PA, Narum SR, O’Brien SJ, Roffler G, Templin WD, Sunnucks P, Strait J, Warheit KI, Seamons TR, Wenburg J, Olsen J, Luikart G (2016) Genomics in conservation: case studies and bridging the gap between data and application. Trends Ecol Evol 31:81–83

    Article  PubMed  Google Scholar 

  • Garrard GE, Rumpff L, Runge MC, Converse SJ (2017) Rapid prototyping for decision structuring: an efficient approach to conservation decision analysis. In: Bunnefeld N, Nicholson E, Milner-Gulland E (eds) Decision-making in conservation and natural resource management: models for interdisciplinary approaches. Cambridge University Press, Cambridge

    Google Scholar 

  • Gienapp P, Fior S, Guillaume F, Lasky JR, Sork VL, Csillery K (2017) Genomic quantitative genetics to study evolution in the wild. Trends Ecol Evol 32:897–908

    Article  PubMed  Google Scholar 

  • Glenn TC (2011) Field guide to next-generation DNA sequencers. Mol Ecol Resour 11:759–769

    Article  PubMed  CAS  Google Scholar 

  • Gregory R, Failing L, Harstone M, Long G, McDaniels T, Ohlson D (2012) Structured decision making: a practical guide to environmental management choices. Wiley, Oxford

    Book  Google Scholar 

  • Haig SM, D’Elia J (2010) Avian subspecies and the U.S. Endangered Species Act. Ornithol Monogr 67:24–34

    Article  Google Scholar 

  • Haldane JBS (1930) A mathematical theory of natural and artificial selection (VI Isolation). Proc Cambridge Philos Soc 26:220–230

    Article  Google Scholar 

  • Hansen MM, Olivieri I, Waller DM, Nielsen EE, Grp GW (2012) Monitoring adaptive genetic responses to environmental change. Mol Ecol 21:1311–1329

    Article  PubMed  Google Scholar 

  • Hanson JO, Rhodes JR, Riginos C, Fuller RA (2017) Environmental and geographic variables are effective surrogates for genetic variation in conservation planning. PNAS 114:12755–12760

    Article  PubMed  CAS  Google Scholar 

  • Harrisson KA, Pavlova A, Telonis-Scott M, Sunnucks P (2014) Using genomics to characterize evolutionary potential for conservation of wild populations. Evol Appl 7:1008–1025. https://doi.org/10.1111/eva.12149

    Article  PubMed  PubMed Central  Google Scholar 

  • Hendry AP, Kinnison MT, Heino M et al (2011) Evolutionary principles and their practical application. Evol Appl 4:159–183. https://doi.org/10.1111/j.1752-4571.2010.00165.x

    Article  PubMed  PubMed Central  Google Scholar 

  • Hess JE, Zendt JS, Matala AR, Narum SR (2016) Genetic basis of adult migration timing in anadromous steelhead discovered through multivariate association testing. Proc R Soc B 283. https://doi.org/10.1098/rspb.2015.3064

  • Hoffmann AA, Sgro CM (2011) Climate change and evolutionary adaptation. Nature 470:479–485

    Article  PubMed  CAS  Google Scholar 

  • Hoffmann AA, Hallas RJ, Dean JA, Schiffer M (2003) Low potential for climatic stress adaptation in a rainforest Drosophila species. Science 301:100–102. https://doi.org/10.1126/science.1084296

    Article  PubMed  CAS  Google Scholar 

  • Hoffmann AA, Sgro CM, Kristensen TN (2017) Revisting adaptive potential, population size, and conservation. Trends Ecol Evol 32:506–517. https://doi.org/10.1016/j.tree.2017.03.012

    Article  PubMed  Google Scholar 

  • Hohenlohe PA, Day MD, Amish SJ, Miller MR, Kamps-Hughes N, Boyer MC, Muhlfeld CC, Allendorf FW, Johnson EA, Luikart G (2013) Genomic patterns of introgression in rainbow and westslope cutthroat trout illuminated by overlapping paired-end RAD sequencing. Mol Ecol 22:3002–3013

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Hong EP, Park JW (2012) Sample size and statistical power calculation in genetic association studies. Genomics Inform 10:117–122. https://doi.org/10.5808/GI.2012.10.2.117

    Article  PubMed  PubMed Central  Google Scholar 

  • Jamieson IG, Allendorf FW (2012) How does the 50/500 rule apply to MVPs? Trends Ecol Evol 27:578–584

    Article  PubMed  Google Scholar 

  • Jamieson IG, Allendorf FW (2013) A school of red herring: reply to Frankham et al. Trends Ecol Evol 28:188–189

    Article  PubMed  Google Scholar 

  • Johnson FA, Hagan G, Palmer WE, Kemmerer M (2014) Uncertainty, robustness, and the value of information in managing a population of northern bobwhites. J Wildl Manag 78:531–539

    Article  Google Scholar 

  • Joost S, Bonin A, Bruford MW, Despres L, Conord C, Erhardt G, Taberlet P (2007) A spatial analysis method (SAM) to detect candidate loci for selection: towards a landscape genomics approach to adaptation. Mol Ecol 16:3955–3969

    Article  PubMed  CAS  Google Scholar 

  • Keeney RL (1992) Value-focused thinking: a path to creative decision making. Harvard University Press, Cambridge

    Google Scholar 

  • Keith D, Akçakaya HR, Butchart SHM, Collen B, Dulvy NK, Homes EE, Hutchings JA, Keinath D, Schwartz MK, Shelton AO, Wapes RS (2015) Temporal correlations in population trends: conservation implications from time-series analysis of diverse animal taxa. Biol Conserv 192:247–257

    Article  Google Scholar 

  • Kellermann VM, Heerwaarden B van, Hoffmann AA, Sgrò CM (2006) Very low additive genetic variance and evolutionary potential in multiple populations of two rainforest Drosophila species. Evolution 60:1104–1108. https://doi.org/10.2307/4095411

    Article  PubMed  Google Scholar 

  • Kelly MW, Sanford E, Grosberg RK (2012) Limited potential for adaptation to climate change in a broadly distributed marine crustacean. Proc R Soc B 279:349–356

    Article  PubMed  Google Scholar 

  • Kimura M, Crow JF (1963) The measurement of the effective population number. Evolution 17:279–288

    Article  Google Scholar 

  • Korte A, Farlow A (2013) The advantages and limitations of trait analysis with GWAS: a review. Plant Methods 9:29

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Kovach RP, Gharrett AJ, Tallmon DA (2012) Genetic change for earlier migration timing in a pink salmon population. Proc R Soc B 279:3870–3878

    Article  PubMed  Google Scholar 

  • Lasky JR, Upadhyaya HD, Ramu P et al (2015) Genome-environment associations in sorghum landraces predict adaptive traits. Sci Adv 1:e1400218. https://doi.org/10.1126/sciadv.1400218

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Lemmon AR, Emme SA, Lemmon EM (2012) Anchored hybrid enrichment for massively high-throughput phylogenomics. Syst Biol 61:727–744

    Article  PubMed  CAS  Google Scholar 

  • Li S, Li B, Cheng C et al (2014) Genomic signatures of near-extinction and rebirth of the crested ibis and other endangered bird species. Genome Biol 15:557. https://doi.org/10.1186/s13059-014-0557-1

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Lowry DB, Hoban S, Kelley JL et al (2016) Breaking RAD: an evaluation of the utility of restriction site-associated DNA sequencing for genome scans of adaptation. Mol Ecol Resour 17:142–152. https://doi.org/10.1111/1755-0998.12635

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Luikart G, England PR, Tallmon D, Jordan S, Taberlet P (2003) The power and promise of population genomics: from genotyping to genome typing. Nat Rev Genet 4:981–994

    Article  PubMed  CAS  Google Scholar 

  • Manel S, Perrier C, Pratlong M, Abi-Rached L, Paganini J, Pontarotti P, Aurelle D (2016) Genomic resources and their influence on the detection of the signal of positive selection in genome scans. Mol Ecol 25:170–184

    Article  PubMed  CAS  Google Scholar 

  • McKay JK, Bishop JG, Lin JZ, Richards JH, Sala A, Mitchell-Olds T (2001) Local adaptation across a climatic gradient despite small effective population size in the rare sapphire rockcress. Proc R Soc B 268:1715–1721

    Article  PubMed  CAS  Google Scholar 

  • McKinney GJ, Larson WA, Seeb LW, Seeb JE (2017) RADseq provides unprecedented insights into molecular ecology and evolutionary genetics: comment on Breaking RAD by Lowry et al. (2016). Mol Ecol Resour 17:356–361. https://doi.org/10.1111/1755-0998.12649

    Article  PubMed  CAS  Google Scholar 

  • Merilä J, Hendry AP (2014) Climate change, adaptation, and phenotypic plasticity: the problem and the evidence. Evol Appl 7:1–14. https://doi.org/10.1111/eva.12137

    Article  PubMed  PubMed Central  Google Scholar 

  • Muñoz NJ, Farrell AP, Heath JW, Neff BD (2015) Adaptive potential of a Pacific salmon challenged by climate change. Nat Clim Change 5:163–166

    Article  Google Scholar 

  • Nagy ES, Rice KJ (1997) Local adaptation in two subspecies of an annual plant: implications for migration and gene flow. Evolution 51:1079–1089

    Article  Google Scholar 

  • [NMFS and USFWS] National Marine Fisheries Serivice and U.S. Fish and Wildlife Service (2010) Interim endangered and threatened species recover planning guidance, version 1.3. http://www.nmfs.noaa.gov/pr/recovery/

  • Neel MC, Leidner AK, Haines A, Goble DD, Scott JM (2012) By the numbers: how is recovery defined by the US Endangered. Species Act? BioScience 62:646–657

    Article  Google Scholar 

  • Nicotra AB, Beever EA, Robertson AL et al (2015) Assessing the components of adaptive capacity to improve conservation and management efforts under global change. Conserv Biol 29:1268–1278. https://doi.org/10.1111/cobi.12522

    Article  PubMed  Google Scholar 

  • O’Connor MI, Selig ER, Pinsky ML, Altermatt F (2012) Toward a conceptual synthesis for climate change responses. Glob Ecol Biogeogr 21:693–703

    Article  Google Scholar 

  • Payseur BA, Rieseberg LH (2016) A genomic perspective on hybridization and speciation. Mol Ecol 25:2337–2360

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Penuelas J, Sardans J, Estiarte M, Ogaya R, Carnicer J, Coll M, Barbeta A, Rivas-Ubach A, Llusia J, Garbulsky M, Filella I, Jump AS (2013) Evidence of current impact of climate change on life: a walk from genes to the biosphere. Glob Chang Biol 19:2303–2338

    Article  PubMed  Google Scholar 

  • Perrier C, Delahaie B, Charmantier A (2018) Heritability estimates from genomewide relatedness matrices in wild populations: application to a passerine, using a small sample size. Mol Ecol Resour (in press)

  • Prince DJ, O’Rourke SM, Thompson TQ, Ali OA, Lyman HS, Saglam IK, Hotaling TJ, Spidle AP, Miller MR (2017) The evolutionary basis of premature migration in Pacific salmon highlights the utility of genomics for informing conservation. Sci Adv 3:e1603198

    Article  PubMed  PubMed Central  Google Scholar 

  • Reed TE, Schindler DE, Hague MJ, Patterson DA, Meir E, Waples RS, Hinch SG (2011) Time to evolve? Potential evolutionary responses of Fraser River sockeye salmon to climate change and effects on persistence. PLoS ONE 6:e20380

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Regan TJ, Taylor BL, Thompson GG, Cochrane JF, Ralls K, Runge MC, Merrick R (2013) Testing decision rules for categorizing species’ extinction risk to help develop quantitative listing criteria for the U.S. Endangered Species Act. Conserv Biol 27:821–831

    Article  PubMed  Google Scholar 

  • Rellstab C, Gugerli F, Eckert AJ et al (2015) A practical guide to environmental association analysis in landscape genomics. Mol Ecol 24:4348–4370. https://doi.org/10.1111/mec.13322

    Article  PubMed  Google Scholar 

  • Rohlf DJ (1991) Six biological reasons the Endangered Species Act doesn’t work—and what to do about it. Conserv Biol 5:273–282

    Article  Google Scholar 

  • Ruegg K, Bay RA, Anderson EC, Saracco JF, Harrigan RJ, Whitfield M, Paxton EH, Smith TB (2018) Ecological genomics predicts climate vulnerability in an endangered southwestern songbird. Ecol Lett (in press)

  • Ruhl JB (2004) The battle over the Endangered Species Act methodology. FSU College of Law, Public Law Research Paper No. 99

  • Runge MC (2011) An introduction to adaptive management for threatened and endangered species. J Fish Wildl Manag 2:220–233

    Article  Google Scholar 

  • Runge MC, Converse SJ, Lyons JE (2011) Which uncertainty? Using expert elicitation and expected value of information to design an adaptive program. Biol Conserv 144:1214–1223

    Article  Google Scholar 

  • Ryder OA (1986) Species conservation and systematics: the dilemma of subspecies. Trends Ecol Evol 1:9–10

    Article  Google Scholar 

  • Savage AE, Zamudio KR (2011) MHC genotypes associate with resistance to a frog-killing fungus. Proc Natl Acad Sci USA 108:16705–16710

    Article  PubMed  Google Scholar 

  • Scheffers BR, De Meester L, Bridge TCL, Hoffmann AA, Pandolfi JM, Corlett RT, Butchart SHM, Pearce-Kelly P, Kovacs KM, Dudgeon D, Pacifici M, Rondinini C, Foden WB, Martin TG, Mora C, Bickford D, Watson JEM (2016) The broad footprint of climate change from genes to biomes to people. Science 354:aaf7671

    Article  PubMed  CAS  Google Scholar 

  • Sgro C, Lowe A, Hoffmann A (2011) Building evolutionary resilience for conserving biodiversity under climate change. Evol Appl 4:326–337. https://doi.org/10.1111/j.1752-4571.2010.00157.x

    Article  PubMed  Google Scholar 

  • Shafer ABA, Wolf JBW, Alves PC, Bergstrom L, Bruford MW, Brannstrom I, Colling G, Dalen L, De Meester L, Ekblom R, Fawcett KD, Fior S, Hajibabaei M, Hill JA, Hoezel AR, Hoglund J, Jensen EL, Krause J, Kristensen TN, Krutzen M, McKay JK, Norman AJ, Ogden R, Ouml;sterling EM, Ouborg NJ, Piccolo J, Popovic D, Primmer CR, Reed FA, Roumet M, Salmona J, Schenekar T, Schwartz MK, Segelbacher G, Senn H, Thaulow J, Valtonen M, Veale A, Vergeer P, Vijay N, Vila C, Weissensteiner M, Wennerstrom L, Wheat CW, Zielinski P (2015) Genomics and the challenging translation into conservation practice. Trends Ecol Evol 30:78–87

    Article  PubMed  Google Scholar 

  • Shaffer ML, Stein MA (2000) Safeguarding our precious heritage. In: Stein BA, Kutner LS, Adams JS (eds) Precious heritage: the status of biodiversity in the United States. Oxford University Press, New York, pp 301–321

    Google Scholar 

  • Sillanpää MJ (2011) On statistical methods for estimating heritability in wild populations. Mol Ecol 20:1324–1332

    Article  PubMed  Google Scholar 

  • Slatkin M (1987) Gene flow and the geographic structure of natural populations. Science 236:787–792

    Article  PubMed  CAS  Google Scholar 

  • Smith DR, Allan NL, McGowan CP, Szymanski JA, Oetker SR, Bell HM (2018) Development of a Species Status Assessment process for decisions under the U.S. Endangered Species Act. J Fish Wildl Manag 9:302–320

    Article  Google Scholar 

  • Sork VL (2018) Genomic studies of local adaptation in natural plant populations. J Hered 109:3–15

    Article  Google Scholar 

  • Stanton-Geddes J, Yoder JB, Briskine R, Young ND, Tiffin P (2013) Estimating heritability using genomic data. Methods Ecol Evol 4:1151–1158

    Article  Google Scholar 

  • Steane DA, Potts BM, McLean E et al (2014) Genome-wide scans detect adaptation to aridity in a widespread forest tree species. Mol Ecol 23:2500–2513. https://doi.org/10.1111/mec.12751

    Article  PubMed  Google Scholar 

  • Steffen W, Broadgate W, Deutsch L, Gaffney O, Ludwig C (2015) The trajectory of the Anthropocene: the Great Acceleration. Anthropocene Rev 2:81–98

    Article  Google Scholar 

  • Szymanski J, Smith T, Horton A, Parkin M, Ragan L, Masson G, Olson E, Gifford K, Hill L (2016a) Rusty patched bumble bee (Bombus affinis) species status assessment. U.S. Fish and Wildlife Service, Final Report, Version 1

  • Szymanski J, Pollack C, Ragan L, Redmer M, Clemency L, Voorhies K, JaKa J (2016b) Species status assessment for the eastern massasauga rattlesnake (Sistrurus catenatus). U.S. Fish and Wildlife Service, SSA Report Version 2

  • Taylor MFJ, Suckling KF, Rachlinski JJ (2005) The effectiveness of the Endangered Species Act: a quantitative analysis. Bioscience 55:360–367

    Article  Google Scholar 

  • Theimer TC, Smith AD, Mahoney SM, Ironside KE (2016) Available data support protection of the Southwestern willow flycatcher under the Endangered Species Act. Condor 118:289–299

    Article  Google Scholar 

  • Thomas L, Palumbi SR (2017) The genomics of recovery from coral bleaching. Proc R Soc B https://doi.org/10.1098/rspb.2017.1790

    Article  PubMed  Google Scholar 

  • Thorpe RS, Reardon JT, Malhotra A (2005) Common garden and natural selection experiments support ecotypic differentiation in the Dominican anole (Anolis oculatus). Am Nat 165:495–504

    Article  PubMed  Google Scholar 

  • Todd EV, Black MA, Gemmell NJ (2016) The power and promise of RNA-seq in ecology and evolution. Mol Ecol 25:1224–1241. https://doi.org/10.1111/mec.13526

    Article  PubMed  CAS  Google Scholar 

  • U.S. Fish and Wildlife Service (1995) Endangered and threatened wildlife and plants; final rule determining endangered status for the Southwestern Willow Flycatcher. Fed Reg 60:10694–10715

    Google Scholar 

  • [USFWS and NMFS] U.S. Fish and Wildlife Service and National Marine Fisheries Service (1996) Policy regarding the recognition of distinct vertebrate population segments under the Endangered Species Act. Fed Reg 61:4722–4725

    Google Scholar 

  • U.S. Fish and Wildlife Service (2016) Endangered and threatened wildlife and plants; threatened species status for rusty patched bumble bee. Fed Reg 82:3186–3208

    Google Scholar 

  • U.S. Fish and Wildlife Service (2017) Endangered and threatened wildlife and plants; endangered species status for the eastern massasauga rattlesnake. Fed Reg 81:667214–671936

    Google Scholar 

  • Verhoeven KJF, Vonholdt BM, Sork VL (2016) Epigenetics in ecology and evolution: what we know and what we need to know. Mol Ecol 25:1631–1638

    Article  PubMed  Google Scholar 

  • Visscher PM, Goddard ME (2015) A general unified framework to assess the sampling variance of heritability estimates using pedigree or marker-based relationships. Genetics 199:223–232

    Article  PubMed  Google Scholar 

  • Visscher PM, Hill WG, Wray NR (2008) Heritability in the genomics era—concepts and misconceptions. Nat Rev Genet 9:255–266

    Article  PubMed  CAS  Google Scholar 

  • Vucetich JA, Nelson MP, Phillips MK (2006) The normative dimension and legal meaning of endangered and recovery in the US Endangered Species Act. Conserv Biol 20:1383–1390

    Article  PubMed  Google Scholar 

  • Walters C (1986) Adaptive management of renewable resources. MacMillan, New York

    Google Scholar 

  • Waples RS (1991) Pacific salmon, Oncorhynchus spp., and the definition of ‘species’ under the Endangered Species Act. Act Mar Fish Rev 53:11–22

    Google Scholar 

  • Waples RS, Nammack M, Cochrane JF, Hutchings JA (2013) A tale of two acts: endangered species listing practices in Canada and the United States. Bioscience 63:723–734

    Article  Google Scholar 

  • Waples RK, Larson WA, Waples RS (2016) Estimating contemporary effective population size in non-model species using linkage disequilibrium across thousands of loci. Heredity 117:233–240

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Weeks AR, Sgro CM, Young AG et al (2011) Assessing the benefits and risks of translocations in changing environments: a genetic perspective. Evol Appl 4:709–725. https://doi.org/10.1111/j.1752-4571.2011.00192.x

    Article  PubMed  PubMed Central  Google Scholar 

  • White GC, Burnham KP (1999) Program MARK: survival estimation from populations of marked animals. Bird Study Suppl 46:120–138

    Article  Google Scholar 

  • Williams BK, Szaro RC, Shapiro CD (2007) Adaptive management: the U.S. Department of the Interior Technical Guide. Adaptive Management Working Group, U.S. Department of the Interior, Washington DC

    Google Scholar 

  • Williams BK, Eaton MJ, Breininger DR (2011) Adaptive resource management and the value of information. Ecol Modell 222:3429–3436

    Article  Google Scholar 

  • Wright S (1931) Evolution in Mendelian populations. Genetics 16:97–159

    PubMed  PubMed Central  CAS  Google Scholar 

  • Wright S (1938) Size of population and breeding structure in relation to evolution. Science 87:430–431

    Google Scholar 

  • Wright S (1943) Isolation by distance. Genetics 28:114–138

    PubMed  PubMed Central  CAS  Google Scholar 

  • Zink RM (2015) Genetics, morphology, and ecological niche modeling do not support the subspecies status of the endangered willow flycatcher (Empidonax traillii extimus). Condor 117:78–86

    Article  Google Scholar 

Download references

Acknowledgements

We first thank A. Rus Hoelzel for inviting WCF to the Discussion Meeting at Durham University in September 2017 on “Conserving Adaptive Potential and Functional Diversity.” Without Rus’ initiative and perseverance in organizing this meeting, we would not have been spurred to assemble the diverse team of coauthors needed to bring together the ideas outlined here. We also thank Robin Waples and Gordon Luikart for excellent suggestions for improving the manuscript. We acknowledge funding from Colorado State University and National Science Foundation Ecology of Infectious Diseases Grant (DEB 1413925). The findings and conclusions in this article are those of the authors and do not necessarily represent the views of the US Fish and Wildlife Service.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to W. C. Funk.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Funk, W.C., Forester, B.R., Converse, S.J. et al. Improving conservation policy with genomics: a guide to integrating adaptive potential into U.S. Endangered Species Act decisions for conservation practitioners and geneticists. Conserv Genet 20, 115–134 (2019). https://doi.org/10.1007/s10592-018-1096-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10592-018-1096-1

Keywords

Navigation