Abstract
Peripheral populations located at their range edge, may be at risk due to geographical isolation, environmental changes, human disturbances or catastrophic events such as wildfires. Fine-scale spatial genetic structure (SGS) investigations provide a way to examine the spatial arrangement of genetic variation within populations. SGS can result from restricted seed and pollen dispersal and might be affected by geographic isolation and environmental changes and disturbances even in outcrossing wind-pollinated species like oaks. Studying the SGS of peripheral populations provides information that can be used to develop improved conservation and management plans at the species’ range edge. We assessed the level of genetic variation and SGS in twelve range edge populations in northern Wisconsin and the Upper Peninsula of Michigan (USA): eight Quercus rubra and four Quercus ellipsoidalis populations that were subject to different management regimes and natural disturbances. In contrast to Q. rubra populations, the drought tolerant Q. ellipsoidalis populations are isolated from the species’ main distribution range. These populations are not actively managed but are especially prone to recurring fire events. The four managed and four old growth (“unmanaged”) Q. rubra populations displayed similar levels of genetic variation. Likewise the Sp statistic showed similar SGS levels in managed and unmanaged Q. rubra populations (Sp = 0.005) comparable to other Quercus species (European Q. robur: Sp = 0.003). Q. ellipsoidalis populations showed similar or more pronounced SGS than neighboring Q. rubra populations extending up to 83 m in one population. A significant excess of homozygotes across markers in two of the Q. ellipsoidalis populations suggests potential inbreeding. In summary, diverse management activities combined with various natural disturbances are likely both influencing SGS patterns. Outcrossing forest trees like oaks hold large amounts of genetic diversity allowing adaptation to environmental changes over their long life spans. Reductions of these genetic stores, through inbreeding for example, can inhibit a species’ ability to adapt to changing environmental conditions.
This is a preview of subscription content, access via your institution.



References
Abrams MD (1990) Adaptations and responses to drought in Quercus species of North America. Tree Physiol 7:227–238
Abrams MD (1992) Fire and the development of oak forests. Bioscience 42:346–353
Aitken SN, Yeaman S, Holliday JA, Wang T, Curtis-MacLane S (2008) Adaptation, migration or extirpation: climate change outcomes for tree populations. Evol Appl 1:95–111
Aldrich PR, Cavender-Bares J (2011) Wild crop relatives: genomic and breeding resources. In: Kole C (ed) Quercus. Springer, Berlin Heidelberg, Berlin, pp 89–129
Aldrich PR, Glaubitz JC, Parker GR, Rhodes OE, Michler CH (2005) Genetic structure inside a declining red oak community in old-growth forest. J Heredity 96:627–634
Berg EE, Hamrick JL (1994) Spatial and genetic structure of two sandhills oaks: Quercus laevis and Quercus margaretta (Fagaceae). Amer J Bot 81:7–14
Berg EE, Hamrick JL (1995) Fine-scale genetic structure of a turkey oak forest. Evolution 49:110–120
Buiteveld J, Vendramin GG, Leonardi S, Kamer K, Geburek T (2007) Genetic diversity and differentiation in European beech (Fagus sylvatica L.) stands varying in management history. Forest Ecol Managem 247:98–106
Cavers S, Degen B, Caron H, Lemes MR, Margis R, Salgueiro F, Lowe AJ (2005) Optimal sampling strategy for estimation of spatial genetic structure in tree populations. Heredity 95:218–289
Chybicki IJ, Oleksa A, Burczyk J (2011) Increased inbreeding and strong kinship structure in Taxus baccata estimated from both AFLP and SSR data. Heredity 107:589–600
Cottrell JE, Munro RC, Tabbener HE, Milner AD, Forrest GI, Lowe AJ (2003) Comparison of fine-scale genetic structure using nuclear microsatellites within two British oakwoods differing in population history. Forest Ecol Managem 176:287–303
Craft KJ, Ashley MV (2007) Landscape genetic structure of bur oak (Quercus macrocarpa) savannas in Illinois. Forest Ecol Managem 239:13–20
Davis MB (1996) Eastern old-growth forests: prospects for rediscovery and recovery. Island Press, Washington
Dickmann DI, Leefers LA (2003) The forests of Michigan. University of Michigan Press, Ann Arbor
Ennos RA (1994) Estimating the relative rates of pollen and seed migration among plant populations. Heredity 72:250–259
Epperson BK (1992) Spatial structure of genetic variation within populations of forest trees. In: Adams WT, Strauss S, Copes D, Griffin AR (eds) Population Genetics of Forest Trees. Forestry Sciences, vol 42. Springer, Netherlands, pp 257–278
Epperson BK (2000) Spatial genetic structure and non-equilibrium demographics within plant populations. Pl Spec Biol 15:269–279
ESRI (2011) ArcGIS Desktop, 10th edn. Environmental Systems Research Institute, Redlands
Finkeldey R, Ziehe M (2004) Genetic implications of silvicultural regimes. Forest Ecol Managem 197:231–244
Flaspohler DJ, Meine C (2006) Planning for wildness: Aldo Leopold’s report on Huron Mountain Club. J Forest 104:32–42
Gibson SY, Van Der Marel RC, Starzomski BM (2009) Climate change and conservation of leading-edge peripheral populations. Conservation Biol 23:1369–1373
Goudet J (1995) FSTAT (Version 1.2): a computer program to calculate F-statistics. Heredity 86:485–486
Hamrick JL, Linhart YB, Mitton JB (1979) Relationships between life history characteristics and electrophoretically detectable genetic variation in plants. Annual Rev Ecol Syst 10:173–200
Hardy OJ, Vekemans X (2002) SPAGeDI: a versatile computer program to analyse spatial genetic structure at the individual or population levels. Molec Ecol Notes 2:618–620
Huebner CD (2003) Vulnerability of oak-dominated forests in West Virginia to invasive exotic plants: temporal and spatial patterns of nine exotic species using herbarium records and land classification data. Castanea 68:1–14
Jimenez P, Agundez D, Alia R, Gil L (1999) Genetic variation in central and marginal populations of Quercus suber L. Silvae Genet 48:278–284
Johnson WC, Webb T (1989) The role of blue jays (Cyanocitta cristata L.) in the postglacial dispersal of fagaceous trees in eastern North America. J Biogeogr 16:561–571
Jones FA, Hamrick JL, Peterson CJ, Squiers ER (2006) Inferring colonization history from analyses of spatial genetic structure within populations of Pinus strobus and Quercus rubra. Molec Ecol 15:851–861
Jump AS, Peñuelas J (2006) Genetic effects of chronic habitat fragmentation in a wind-pollinated tree. Proc Natl Acad Sci USA 103:8096–8100
Lind JF, Gailing O (2013) Genetic structure of Quercus rubra L and Quercus ellipsoidalis E. J. Hill populations at gene-based EST-SSR and nuclear SSR markers. Tree Genet Genomes 9:707–722
Lind-Riehl JF, Sullivan AR, Gailing O (2014) Evidence for selection on a CONSTANS-like gene between two red oak species. Ann Bot (Oxford) 113:967–975
Loiselle BA, Sork VL, Nason J, Graham C (1995) Spatial genetic structure of a tropical understory shrub, Psychotria officinalis (Rubiaceae). Amer J Bot 82:1420–1425
Lorenzo Z, Burgarella C, Lopez de Heredia U, Lumaret R, Petit RJ, Soto A, Gil L (2009) Relevance of genetics for conservation policies: the case of Minorcan cork oaks. Ann Bot (Oxford) 104:1069–1076
Lorimer CG (1993) Causes of oak regeneration problem. United States Department of Agriculture, Washington
McCauley DE (1997) The relative contributions of seed and pollen movement to the local genetic structure of Silene alba. Heredity 88:257–263
McPherson EG, Rowntree RA (1989) Using structure measures to compare twenty-two U.S. street tree populations. Landscape 8:13–23
McShea WJ, Healy WM, Devers P, Fearer T, Koch FH, Stauffer D, Waldon J (2007) Forestry matters: decline of oaks will impact wildlife in hardwood forests. J Wildlife Managem 71:1717–1728
Moran EV, Clark JS (2012) Between-site differences in the scale of dispersal and gene flow in red oak. PLoS One 7:e36492
Muir G, Lowe AJ, Fleming CC, Vogl C (2004) High nuclear genetic diversity, high levels of outcrossing and low differentiation among remnant populations of Quercus petraea at the margin of its range in Ireland. Ann Bot (Oxford) 93:691–697
Paffetti D, Travaglini D, Buonamici A, Nocentini S, Vendramin GG, Giannini R, Vettori C (2012) The influence of forest management on beech (Fagus sylvatica L.) stand structure and genetic diversity. Forest Ecol Managem 284:34–44
Pandey M, Rajora OP (2012) Higher fine-scale genetic structure in peripheral than in core populations of a long-lived and mixed-mating conifer- eastern white cedar (Thuja occidentalis L.). BMC Evol Biol 12:48
Peakall ROD, Smouse PE (2006) GenAlEx 6: genetic analysis in Excel. Population genetic software for teaching and research. Molec Ecol Notes 6:288–295
Petit RJ, Hampe A (2006) Some evolutionary consequences of being a tree. Annual Rev Ecol Evol Syst 37:187–214
Petit RJ, el Mousadik A, Pons O (1998) Identifying populations for conservation on the basis of genetic markers. Conservation Biol 12:844–855
Rajendra KC, Seifert S, Prinz K, Gailing O, Finkeldey R (2014) Subtle human impacts on patterns of neutral genetic variation in European beech (Fagus sylvatica). Forest Ecol Managem 319:138–149
Raymond M, Rousset F (1995) GenePop (Version-1.2)—population genetics software for exact tests and ecumenicism. Heredity 86:248–249
Saetre S (1983) Chequamegon: The making of a forest. Manuscript on file at the Supervisor Office. Chequamegon-Nicolet National Forest, Rhinelander
Sagnard F, Oddou-Muratorio S, Pichot C, Vendramin GG, Fady B (2011) Effects of seed dispersal, adult tree and seedling density on the spatial genetic structure of regeneration at fine temporal and spatial scales. Tree Genet Genomes 7:37–48
Sokal RR, Oden NL (1978) Spatial autocorrelation in biology: 1. Methodology. Biol J Linn Soc 10:199–228
Stefenon VM, Gailing O, Finkeldey R (2008) The role of gene flow in shaping genetic structures of the subtropical conifer species Araucaria angustifolia. Pl Biol 10:356–364
Streiff R, Labbe T, Bacilieri R, Steinkellner H, Glössl J, Kremer A (1998) Within-population genetic structure in Quercus robur L. and Quercus petraea (Matt.) Liebl. assessed with isozymes and microsatellites. Molec Ecol 7:317–328
Sullivan AR, Lind JF, McCleary TS, Romero-Severson J, Gailing O (2013) Development and characterization of genomic and gene-based microsatellite markers in North American red oak species. Plant Mol Biol Rep 31:231–239
Trapnell DW, Hamrick JL (2004) Partitioning nuclear and chloroplast variation at multiple spatial scales in the neotropical epiphytic orchid, Laelia rubescens. Molec Ecol 13:2655–2666
Troupin D, Nathan R, Vendramin GG (2006) Analysis of spatial genetic structure in an expanding Pinus halepensis population reveals development of fine-scale genetic clustering over time. Molec Ecol 15:3617–3630
Van Oosterhout C, Hutchinson WF, Wills DPM, Shipley P (2004) MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data. Molec Ecol Notes 4:535–538
Vekemans X, Hardy OJ (2004) New insights from fine-scale spatial genetic structure analyses in plant populations. Molec Ecol 13:921–935
Acknowledgments
We would like to thank the Huron Mountain Wildlife Foundation, both the Ecosystem Science Center and Biotechnology Research Center in the School of Forest Resources and Environmental Sciences at Michigan Technological University, Michigan Technological University’s Finishing Fellowship program, the NSF Plant Genome research program (NSF1025974), the USDA McIntire Stennis fund, the Hanes Trust and the Northern Institute of Applied Climate Science for providing the funding for this work. We would also like to thank Alexis Sullivan for sharing some population data and site information, James Schmierer and Deborah Veen for their willingness to share their knowledge of the management history of the CNF, NNF, and FRF-BP sites, and Jonathan Riehl for his invaluable assistance with the construction of the maps.
Author information
Authors and Affiliations
Corresponding author
Additional information
Handling editor: Christoph Oberprieler.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Lind-Riehl, J., Gailing, O. Fine-scale spatial genetic structure of two red oak species, Quercus rubra and Quercus ellipsoidalis . Plant Syst Evol 301, 1601–1612 (2015). https://doi.org/10.1007/s00606-014-1173-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00606-014-1173-y
Keywords
- Spatial genetic structure
- Quercus
- Management
- Silviculture
- Sp statistic
- Autocorrelation analysis