Skip to main content

Advertisement

SpringerLink
Log in

Macro-scale assessment of demographic and environmental variation within genetically derived evolutionary lineages of eastern hemlock (Tsuga canadensis), an imperiled conifer of the eastern United States

  • Original Paper
  • Published:
Biodiversity and Conservation Aims and scope Submit manuscript

Abstract

Eastern hemlock (Tsuga canadensis) occupies a large swath of eastern North America and has historically undergone range expansion and contraction resulting in several genetically separate lineages. This conifer is currently experiencing mortality across most of its range following infestation of a non-native insect. With the goal of better understanding the current and future conservation potential of the species, we evaluate ecological differences among populations within these genetically defined clusters, which were previously inferred using nuclear microsatellite molecular markers from 58 eastern hemlock populations. We sub-divide these clusters into four genetic zones to differentiate putative north-central, north-east and southeast (SE) and southwest evolutionary lineages in eastern hemlock. We use demographic data (relative abundance, mortality, and seedling regeneration) from the Forest Inventory Analysis program in conjunction with environmental data to model how these lineages respond to current and future climatic gradients. Ecologically meaningful relationships are explored in the intraspecific context of hemlock abundance distribution and then related to genetic variation. We also assess hemlock’s colonization likelihood via a long distance dispersal model and explore its future genetic and ecological conservation potential by combining the future suitable habitats with colonization likelihoods. Results show that future habitats under climate change will markedly decline for eastern hemlock. The remaining areas with higher habitat quality and colonization potential are confined to the SE, the genetic zone nearest the species’ putative glacial refugia, pointing to the need to focus our conservation efforts on this ecologically and genetically important region.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Alsos IG, Ehrich D, Thuiller W, Eidesen PB, Tribsch A, Schonswetter P, Lagaye C, Taberlet P, Brochmann C (2012) Genetic consequences of climate change for northern plants. Proc R Soc B 279:2042–2051

    Article  PubMed  PubMed Central  Google Scholar 

  • Andrew RL, Wallis IR, Harwood CE, Foley WJ (2010) Genetic and environmental contributions to variation and population divergence in a broad-spectrum foliar defence of Eucalyptus tricarpa. Ann Bot 105:707–717

    Article  PubMed  PubMed Central  Google Scholar 

  • Baltunis BS, Gapare WJ, Wu HX (2010) Genetic parameters and genotype by environment interaction in radiata pine for growth and wood quality traits in Australia. Silvaec Genet 59:113–124

    Google Scholar 

  • Bechtold WA, Scott CT (2005) The forest inventory and analysis plot design. In: Bechtold WA, Patterson PL (eds) The enhanced forest inventory and analysis program—national sampling design and estimation procedures., Technical Report SRS-80, GeneralUnited States Department of Agriculture, Forest Service, Southern Research Station, Asheville, pp 27–42

    Google Scholar 

  • Breiman L (2001) Random forests. Mach Learn 45:5–32

    Article  Google Scholar 

  • Bucklin DN, Basille M, Benscoter AM, Brandt LA, Mazzotti FJ, Romañach SS, Speroterra C, Watling JI (2015) Comparing species distribution models constructed with different subsets of environmental predictors. Divers Distrib 21:23–35

    Article  Google Scholar 

  • Cale JA, Teale SA, West JL, Zhang LJI, Castello DR, Devlin P, Castello JD (2014) A quantitative index of forest structural sustainability. Forests 5:1618–1634

    Article  Google Scholar 

  • Cheah C, Montgomery ME, Salom S, Parker B, Skinner M, Costa S (2004) Biological Control of Hemlock Woolly Adelgid. United States Department of Agriculture, Forest Service, Forest Health Technology Enterprise Team, Morgantown

    Google Scholar 

  • Chen T, Guestrin C (2016) XGBoost?: reliable large-scale tree boosting system. arXiv:1603.02754 [cs.LG], http://arxiv.org/pdf/1603.02754v1

  • Chen T, He T (2015) Higgs Boson discovery with boosted trees. JMLR 42:69–80

    CAS  Google Scholar 

  • Chen C, Durand E, Forbes F, Francois O (2007) Bayesian clustering algorithms ascertaining spatial population structure: a new computer program and a comparison study. Mol Ecol Notes 7:747–756

    Article  Google Scholar 

  • Comes HP, Kadereit JW (1998) The effect of quaternary climatic changes on plant distribution and evolution. Trends Plant Sci 3:432–438

    Article  Google Scholar 

  • Cutler DR, Edwards TC, Beard KH, Cutler A, Hess KT, Gibson J, Lawler JJ (2007) Random forests for classification in ecology. Ecology 88:2783–2792

    Article  PubMed  Google Scholar 

  • Daly C, Halbleib M, Smith JI, Gibson WP, Doggett MK, Taylor GH, Curtis J, Pasteris PP (2008) Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous United States. Int J Climatol 28:2031–2206

    Article  Google Scholar 

  • Dobrowski SZ (2011) A climatic basis for microrefugia: the influence of terrain on climate. Glob Change Biol 17:1022–1035

    Article  Google Scholar 

  • Eckert CG, Samis KE, Lougheed SC (2008) Genetic variation across species’ geographical ranges: the central-marginal hypothesis and beyond. Mol Ecol 17:1170–1188

    Article  CAS  PubMed  Google Scholar 

  • Eckert AJ, Wegrzyn JL, Liechty JD, Lee JM, Cumbie WP, Davis JM, Goldfarb B, Loopstra CA, Palle SR, Quesada T, Langley CH, Neale DB (2013) The evolutionary genetics of the genes underlying phenotypic associations for loblolly pine (Pinus taeda, Pinaceae). Genetics 195:1353–1372

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • ESRI (2015) ArcGIS [GIS software]. Version 10.3.1. Environmental Systems Research Institute, Redlands, CA

  • Excoffier L, Laval G, Schneider S (2005) Arlequin ver. 3.0: an integrated software package for population genetics data analysis. Evol Bioinform 1:47–50

    CAS  Google Scholar 

  • Felsenstein J (2005) PHYLIP (phylogeny inference package), version 3.6. Department of Genome Sciences, University of Washington, Washington, DC

    Google Scholar 

  • Ford CR, Vose JM (2007) Tsuga canadensis (L.) Carr. mortality will impact hydrologic processes in southern Appalachian forest ecosystems. Ecol Appl 17:1156–1167

    Article  PubMed  Google Scholar 

  • Friedman JH (2002) Stochastic gradient boosting. Comput Stat Data Anal 38:367–378

    Article  Google Scholar 

  • Gapare WJ, Aitken SN, Ritland CE (2005) Genetic diversity of core and peripheral Sitka spruce (Picea sitchensis (Bong.) Carr) populations: implications for conservation of widespread species. Biol Cons 123:113–123

    Article  Google Scholar 

  • Gent PR, Danabasoglu G, Donner LJ, Holland MM, Hunke EC, Jayne SR, Lawrence DM, Neale RB, Rasch PJ, Vertenstein M, Worley PH, Yang ZL, Zhang M (2011) The community climate system model, version 4. J Clim 24:4973–4991

    Article  Google Scholar 

  • Geurts P, Ernst D, Wehenkel L (2006) Extremely randomized trees. Mach Learn 63:3–42

    Article  Google Scholar 

  • Godman RM, Lancaster K (1990) Eastern Hemlock. In: Burns RM, Honkala BH (eds) Silvics of North America: 1 conifers. United States Department of Agriculture Forest Service, Washington, DC

    Google Scholar 

  • Godsoe W (2010) I can’t define the niche but I know it when I see it: a formal link between statistical theory and the ecological niche. Oikos 119:53–60

    Article  Google Scholar 

  • Gotelli NJ, Stanton-Geddes J (2015) Climate change, genetic markers and species distribution modelling. J Biogeogr 42:1577–1585

    Article  Google Scholar 

  • Goudet J (1995) FSTAT (Version 1.2): a computer program to calculate F-statistics. J Hered 86:485–486

    Article  Google Scholar 

  • Guth PL (2006) Geomorphometry from SRTM: comparison to NEDPhotogrammetric engineering and remote sensing 72:269–277

    Google Scholar 

  • Hastie T, Tibshirani R, Friedman J (2009) The elements of statistical learning. Springer, New York, p 745

    Book  Google Scholar 

  • Heard MJ, Valente MJ (2009) Fossil pollen records forecast response of forests to hemlock woolly adelgid invasion. Ecography 32:881–887

    Article  Google Scholar 

  • Hewitt GM (2000) The genetic legacy of the Quaternary ice ages. Nature 405:907–913

    Article  CAS  PubMed  Google Scholar 

  • Iverson LR, McKenzie D (2013) Tree-species range shifts in a changing climate, detecting, modeling, assisting. Landsc Ecol 28:879–889

    Article  Google Scholar 

  • Iverson LR, Schwartz MW, Prasad AM (2004) How fast and far might tree species migrate under climate change in the eastern United States? Glob Ecol Biogeogr 13:209–219

    Article  Google Scholar 

  • Iverson LR, Prasad AM, Matthews SN, Peters M (2008) Estimating potential habitat for 134 eastern US tree species under six climate scenarios. For Ecol Manage 254:390–406

    Article  Google Scholar 

  • Jetton RM, Whittier WA, Dvorak WS, Potter KM (2008) Status of ex situ conservation efforts for Carolina and eastern hemlock in the southeastern United States. In: Onken B, Reardon R (eds) Proceedings of the fourth symposium on Hemlock Woolly adelgid in the Eastern United States. USDA Forest Service, Hartford, pp 81–89

    Google Scholar 

  • Jetton RM, Whittier WA, Dvorak WS, Rhea JR (2013) Conserved ex situ genetic resources of eastern and Carolina hemlock: eastern North American conifers threatened by the hemlock woolly adelgid. Tree Plant Notes 56:59–71

    Google Scholar 

  • Jones MC, Cheung WWL (2015) Multi-model ensemble projections of climate change effects on global marine biodiversity. ICES J Mar Sci 72:741–752

    Article  Google Scholar 

  • Jones CD, Hughes JK, Bellouin N, Hardiman SC, Jones GS, Knight J, Liddicoat S, O’Connor FM, Andres RJ, Bell C, Boo KO, Bozzo A, Butchart N, Cadule P, Corbin KD, Doutriaux-Boucher M, Friedlingstein P, Gornall J, Gray L, Halloran PR, Hurtt G, Ingram WJ, Lamarque JF, Law RM, Meinshausen M, Osprey S, Palin EJ, Parsons-Chini L, Raddatz T, Sanderson MG, Sellar AA, Schurer A, Valdes P, Wood N, Woodward S, Yoshioka M, Zerroukat M (2011) The HadGEM2-ES implementation of CMIP5 centennial simulations. Geosci Model Dev 4:543–570

    Article  Google Scholar 

  • Josserand SA, Potter KM, Echt CS, Nelson CD (2008) Isolation and characterization of microsatellite markers for Carolina hemlock (Tsuga caroliniana). Mol Ecol Resour 8:1371–1374

    Article  CAS  PubMed  Google Scholar 

  • Kessell S (1979) Adaptation and dimorphism in Eastern Hemlock, Tsuga canadensis (L.) Carr. Am Nat 113:333–350

    Article  Google Scholar 

  • Kirk H, Freeland JR (2011) Applications and Implications of neutral versus non-neutral markers in molecular ecology. Int J Mol Sci 12:3966–3988

    Article  PubMed  PubMed Central  Google Scholar 

  • Kramer AT, Havens K (2009) Plant conservation genetics in a changing world. Trends Plant Sci 14:599–607

    Article  CAS  PubMed  Google Scholar 

  • Kuhn M (2008) Building predictive models in R using the caret package. J Stat Softw 28:1–26

    Article  Google Scholar 

  • Lawler JJ, White D, Neilson RP, Blaustein AR (2006) Predicting climate-induced range shifts: model differences and model reliability. Glob Change Biol 12:1568–1584

    Article  Google Scholar 

  • Lemieux MJ, Beaulieu J, Bousquet J (2011) Chloroplast DNA polymorphisms in eastern hemlock: range-wide genogeographic analyses and implications for gene conservation. Can J For Res 41:1047–1059

    Article  CAS  Google Scholar 

  • Lou X (2014) Gene–gene and gene–environment interactions underlying complex traits and their detection. Biomed Biostat Int J 1:1–8

    Google Scholar 

  • Manel S, Schwartz MK, Luikart G, Taberlet P (2003) Landscape genetics: combining landscape ecology and population genetics. Trends Ecol Evol 18:189–197

    Article  Google Scholar 

  • Martre P, Wallach D, Asseng S, Ewert F, Boote KJ, Ruane AC, Peter J, Cammarano D, Hatfield JL, Rosenzweig C, Aggarwal PK, Angulo C, Basso B, Bertuzzi P (2015) Multimodel ensembles of wheat growth: many models are better than one. Glob Change Biol 21:911–925

    Article  Google Scholar 

  • McClure MS, Salom SM, Shields KS (2003) Hemlock woolly adelgid. Forest Health Technology Enterprise Team, United States Department of Agriculture, Forest Service, Morgantown

    Google Scholar 

  • McLachlan JS, Clark JS (2004) Reconstructing historical ranges with fossil data at continental scales. For Ecol Manage 197:139–147

    Article  Google Scholar 

  • Meinshausen M, Smith SJ, Calvin K, Daniel JS, Kainuma MLT, Lamarque JF, Matsumoto K, Montzka SA, Raper SCB, Riahi K, Thomson A, Velders GJM, van Vuuren DPP (2011) The RCP greenhouse gas concentrations and their extensions from 1765 to 2300. Clim Change 109:213–241

    Article  CAS  Google Scholar 

  • Montgomery ME, Bentz SE, Olsen RT (2009) Evaluation of hemlock (Tsuga) species and hybrids for resistance to Adelges tsugae (Hemiptera: Adelgidae) using artificial infestation. J Econ Entomol 102:1247–1254

    Article  PubMed  Google Scholar 

  • Morin RS, Liebhold AM (2015) Invasions by two non-native insects alter regional forest species composition and successional trajectories. For Ecol Manage 341:67–74

    Article  Google Scholar 

  • Morin RS, Oswalt SN, Trotter RT, Liebhold AW (2011) Status of hemlock in the Eastern United States, Forest Inventory and Analysis factshee. US Department of Agriculture Forest Service, Southern Research Station, Asheville

    Google Scholar 

  • Murillo O (2001) Genotype by environment interaction and genetic gain on. Agron Costarric 25:21–31

    Google Scholar 

  • Nagaraju SK, Gudasalamani R, Barve N, Ghazoul J, Narayanagowda GK, Ramanan US (2013) Do ecological niche model predictions reflect the adaptive landscape of species? A test using Myristica malabarica Lam, an endemic tree in the Western Ghats, India. PLoS ONE 8:1–13

    Article  Google Scholar 

  • Nienstaedt H, Olson JS (1961) Effects of photoperiod and source on seedling growth of eastern hemlock. For Sci 7:81–96

    Google Scholar 

  • NRCS (Natural Resources Conservation Service) (2009) Soil survey geographic (SSURGO). http://soildatamart.nrcs.usda.gov/State.aspx. Accessed between August 2009 and November 2010

  • Olson JS, Nienstaedt H (1957) Photoperiod and chilling control growth of hemlock. Science 125:492–494

    Article  Google Scholar 

  • Oten KLF, Merkle SA, Jetton RM, Smith BC, Talley ME, Hain FP (2014) Understanding and developing resistance in hemlocks to the hemlock woolly adelgid. Southeast Nat 13:147–167

    Google Scholar 

  • Pais AL, Whetten RW, Xiang Q (2017) Ecological genomics of local adaptation in Cornus florida L. by genotyping and sequencing. Ecol Evol 7:441–465

    Article  PubMed  Google Scholar 

  • Pederson N, Amato AWD, Dyer JM, Foster DR, Goldblum D, Hart JL, Hessl AE, Iverson LR et al (2015) Climate remains an important driver of post-European vegetation change in the eastern United States. Glob Change Biol 21:2105–2110

    Article  Google Scholar 

  • Pedlar JH, McKenney DW, Aubin I, Beardmore T, Beaulieu J, Iverson L, O’Neill GA, Winder RS, Ste-Marie C (2012) Placing forestry in the assisted migration debate. Bioscience 62:835–842

    Article  Google Scholar 

  • Peters MP, Matthews SN, Iverson LR, Prasad AM (2013) Delineating generalized species boundaries from species distribution data and a species distribution model. Int J Geogr Inf Sci 28:1547–1560

    Article  Google Scholar 

  • Potter KM, Hargrove WW (2012) Determining suitable locations for seed transfer under climate change, a global quantitative model. New Forest 43:581–599

    Article  Google Scholar 

  • Potter KM, Dvorak WS, Crane BS, Hipkins VD, Jetton RM, Whittier WA, Rhea R (2008) Allozyme variation and recent evolutionary history of eastern hemlock (Tsuga canadensis) in the southeastern United States. New Forest 35:131–145

    Article  Google Scholar 

  • Potter KM, Jetton RM, Dvorak WS, Hipkins VD, Rhea R, Whittier WA (2012) Widespread inbreeding and unexpected geographic patterns of genetic variation in eastern hemlock (Tsuga canadensis), an imperiled North American conifer. Conserv Genet 13:475–498

    Article  Google Scholar 

  • Prasad AM (2015) Macroscale intraspecific variation and environmental heterogeneity: analysis of cold and warm zone abundance, mortality, and regeneration distributions of four eastern US tree species. Ecol Evol 5:5033–5048

    Article  PubMed  PubMed Central  Google Scholar 

  • Prasad AM, Iverson LR, Liaw A (2006) Newer classification and regression tree techniques: bagging and random forests for ecological prediction. Ecosystems 9:181–199

    Article  Google Scholar 

  • Prasad AM, Gardiner JD, Iverson LR, Matthews SN, Peters M (2013) Exploring tree species colonization potentials using a spatially explicit simulation model: implications for four oaks under climate change. Glob Change Biol 19:2196–2208

    Article  Google Scholar 

  • Prasad AM, Iverson LR, Matthews SN, Peters MP (2016) A multistage decision support framework to guide tree species management under climate change via habitat suitability and colonization models, and a knowledge-based scoring system. Landsc Ecol. doi:10.1007/s10980-016-0369-

    Google Scholar 

  • Preisser EL, Miller-Pierce MR, Vansant J, Orwig DA (2011) Eastern hemlock (Tsuga canadensis) regeneration in the presence of hemlock woolly adelgid (Adelgis tsugae) and elongate hemlock scale (Fiorinia externa). Can J For Res 41:2433–2439

    Article  Google Scholar 

  • PRISM Climate Group (2017) Oregon State University, http://prism.oregonstate.edu

  • Provan J, Bennett KD (2008) Phylogeographic insights into cryptic glacial refugia. Trends Ecol Evol 23:564–571

    Article  PubMed  Google Scholar 

  • Pulliam HR (2000) On the relationship between niche and distribution. Ecol Lett 3:349–361

    Article  Google Scholar 

  • R Core Team (2016) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. https://www.R-project.org/

  • Schaberg PG, DeHayes DH, Hawley GJ, Nijensohn SE (2008) Anthropogenic alterations of genetic diversity within tree populations: implications for forest ecosystem resilience. For Ecol Manage 256:855–862

    Article  Google Scholar 

  • Schwartz MW (1993) Modelling effects of habitat fragmentation on the ability of trees to respond to climatic warming. Biodivers Conserv 2:51–61

    Article  Google Scholar 

  • Shamblin BM, Faircloth BC, Josserand SA, Nelson D, Nairn CJ (2008) Microsatellite markers for eastern hemlock (Tsuga canadensis). Mol Ecol Resour 8:1354–1356

    Article  CAS  PubMed  Google Scholar 

  • Shinneman DJ, Means RE, Potter KM, Hipkins VD (2016) Exploring climate niches of ponderosa pine haplotypes in the western United States: insight into evolutionary history and implications for future conservation. PLoS ONE 11(3):e0151811

    Article  PubMed  PubMed Central  Google Scholar 

  • Smith WB (2002) Forest inventory and analysis: a national inventory and monitoring program. Environ Pollut 116:S233–S242

    Article  CAS  PubMed  Google Scholar 

  • Soberon J, Peterson AT (2005) Interpretation of models of fundamental ecological niches and species’ distributional areas. Biodivers Inform 2:1–10

    Article  Google Scholar 

  • Spaulding HL, Rieske LK (2010) The aftermath of an invasion: structure and composition of Central Appalachian hemlock forests following establishment of the hemlock woolly adelgid, Adelges tsugae. Biol Invasions 12:3135–3143

    Article  Google Scholar 

  • Svenning JC, Skov F (2007) Could the tree diversity pattern in Europe be generated by postglacial dispersal limitation? Ecol Lett 10:453–460

    Article  PubMed  Google Scholar 

  • Quantum GIS Development Team (2016). Quantum geographic information system. Open source geospatial foundation project. http://qgis.osgeo.org. Accessed 17 Feb 2017

  • Thomassen HA, Cheviron ZA, Freedman AH, Harrigan RJ, Wayne RK, Smith TB (2010) Spatial modelling and landscape-level approaches for visualizing intra-specific variation. Mol Ecol 19:3532–3548

    Article  PubMed  Google Scholar 

  • Thornthwaite C, Mather J (1957) Instructions and tables for computing potential evapotranspiration and the water balance. Publ Climatol 10:185–311

    Google Scholar 

  • Thrasher B, Xiong J, Wang W, Melton F, Michaelis A, Nemani R (2013) Downscaled climate projections suitable for resource management. Trans Am Geophys Union 94:321–323

    Article  Google Scholar 

  • Trotter RT, Shields KS (2009) Variation in winter survival of the invasive hemlock woolly adelgid (Hemiptera, Adelgidae) Across the Eastern United States. Environ Entomol 38:577–587

    Article  PubMed  Google Scholar 

  • Trotter RT, Morin RS, Oswalt SN, Liebhold AM (2013) Changes in the regional abundance of hemlock associated with the invasion of hemlock woolly adelgid (Adelges tsugae Annand). Biol Invasions 15:2667–2679

    Article  Google Scholar 

  • USDA Forest Service (2015) Forest health protection—Hemlock Woolly Adelgid, distribution maps. https://www.na.fs.fed.us/fhp/hwa/maps/distribution.shtm. Accessed 13 Feb 2017

  • Ward JS, Montgomery ME, Cheah C, Onken BP, Cowles RS (2004) Eastern Hemlock forests: guidelines to minimize the impacts of Hemlock Woolly Adelgid. United States Department of Agriculture, Forest Service, Morgantown

    Google Scholar 

  • Woudenberg SW, Conkling BL, O’Connell BM, LaPoint EB, Turner JA, Waddell KL (2010) The forest inventory and analysis database: database description and user’s manual version 4.0 for Phase 2. General Technical Report RMRS-GTR-245, USDA Forest Service, Rocky Mountain Research Station, Fort Collins, Colorado

  • Yansa CH (2006) The timing and nature of Late Quaternary vegetation changes in the northern Great Plains, USA and Canada: a re-assessment of the spruce phase. Q Sci Rev 25:263–281

    Article  Google Scholar 

  • Zenni RD, Lamy JB, Lamarque LJ, Porte AJ (2014) Adaptive evolution and phenotypic plasticity during naturalization and spread of invasive species: implications for tree invasion biology. Biol Invasions 16:635–644

    Article  Google Scholar 

  • Zhang L, Liu S, Sun P, Wang T, Wang G, Zhang X, Wang L (2015) Consensus forecasting of species distributions: the effects of niche model performance and niche properties. PLoS ONE 10:1–18

    Google Scholar 

Download references

Acknowledgements

The authors thank Louis Iverson and Bill Hargrove for their advice and assistance, and to the two anonymous reviewers for their valuable comments. The authors also express their gratitude to the Forest Inventory and Analysis field crew members for their efforts to collect the data used in this study. This research was supported in part through Cost Share Agreements 14-CS-11330110-042 and 15-CS-11330110-067 between the between the U.S. Department of Agriculture, Forest Service, Southern Research Station, and North Carolina State University.

Author information

Authors and Affiliations

  1. Northern Research Station, USDA Forest Service, Delaware, OH, 43065, USA

    Anantha M. Prasad

  2. Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC, USA

    Kevin M. Potter

  3. Southern Research Station, USDA Forest Service, Research Triangle Park, NC, 27709, USA

    Kevin M. Potter

Authors
  1. Anantha M. Prasad
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kevin M. Potter
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Anantha M. Prasad.

Additional information

Communicated by Danna J. Leaman.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 2067 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Prasad, A.M., Potter, K.M. Macro-scale assessment of demographic and environmental variation within genetically derived evolutionary lineages of eastern hemlock (Tsuga canadensis), an imperiled conifer of the eastern United States. Biodivers Conserv 26, 2223–2249 (2017). https://doi.org/10.1007/s10531-017-1354-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10531-017-1354-4

Keywords

Search

Navigation