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Genetic diversity and fine-scale spatial genetic structure of unmanaged old-growth versus managed second-growth populations of Scots pine (Pinus sylvestris L.) in Lithuania

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A Correction to this article was published on 05 June 2023

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Abstract

We tested the hypothesis that old-growth unmanaged (OGU) forests have higher genetic diversity than second-growth managed (SGM) forests and systematic forest tending markedly reduces genetic diversity and alters the fine-scale spatial genetic structure (SGS) of contemporary generation in natural populations, employing Scots pine (Pinus sylvestris L.). We examined genetic diversity, differentiation and SGS of three OGU and three post-tending natural SGM populations of Scots pine on similar ecosites in different parts of Lithuania by genotyping 890 mature trees at 11 nuclear microsatellite loci. The genetic differentiation between OGU and SGM population groups was not significant. Although OGU populations had higher allelic diversity, effective population size (Ne) and higher inbreeding coefficient than SGM populations, the differences between OGU and SGM populations were not significant for these parameters. However, we found a significant loss of OGU-specific private rare alleles, copies of rare alleles and genotypic diversity in the SGM populations. OGU populations had significantly stronger SGS and larger neighborhood size than SGM populations. We infer that systematic tending in natural Scots pine forests  does not cause a significant reduction in common genetic diversity parameters and reduces SGS by disrupting clusters of relatives. However, it does cause significant loss of rare alleles and genotypic diversity and some genetic differentiation from OGU. We suggest genetic monitoring for genetic diversity conservation and Ne maintenance, and developing forest management and gene conservation guidelines for better conservation of rare alleles and genotypic diversity.

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References

  • Allen CD et al (2010) A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. For Ecol Manag 259(4):660–684

    Google Scholar 

  • Anonymous (2010) The European Forest Sector Outlook Study II 2010–2030. United Nations publication Sales No E.11.II.E.14 ISSN 1020-2269, 111 p. http://www.fao.org/3/a-ap406e.pdf

  • Anonymous (2019) Lithuanian forest statistics. Electronic publication of Lithuanian Forest Servicer http://www.amvmt.lt/index.php/leidiniai/misku-ukio-statistika/2019. Accessed March 1, 2021

  • Anonymous (2020) Forest sector outlook study 2020–2040. Copyright © 2021 United Nations and the Food and Agriculture Organization of the United Nations. ECE/TIM/SP/51, UNITED NATIONS PUBLICATION, Sales No. E.22.II.E.11, ISBN 978-92-1-117289-8, eISBN 978-92-1-001297-3, ISSN 1020-2269, eISSN 2518-6450 (electronic publication accessed Jan 13, 2023)

  • Aravanopoulos F (2018) Do silviculture and forest management affect the genetic diversity and structure of long-impacted forest tree populations? Forests 9:355. https://doi.org/10.3390/f9060355

    Article  Google Scholar 

  • Bacilieri R, Labbe T, Kremer A (1994) Intraspecific genetic structure in a mixed population of Quercus petraea (Matt) Leibl and Quercus robur L. Heredity 73:130–141

    Google Scholar 

  • Belletti P, Ferrazzini D, Piotti A, Monteleone I, Ducci F (2012) Genetic variation and divergence in Scots pine (Pinus sylvestris L.) within its natural range in Italy. Eur J for Res 131:1127–1138

    Google Scholar 

  • Bonnet-Masimbert M (1987) Floral induction in conifers: a review of available techniques. For Ecol Manag 19(1–4):135–146. https://doi.org/10.1016/0378-1127(87)90019-3

    Article  CAS  Google Scholar 

  • Boshier D, Amaral W (2005) Threats to forest ecosystems and challenges for the conservation and sustainable use of forest genetic resources. In: Challenges in managing forest genetic resources for livelihoods: examples from Argentina and Brazil; Biodiversity international Rome, Italy, pp 8–27

  • Buchert GP, Rajora OP, Hood JV, Dancik BP (1997) Effects of harvesting on genetic diversity in old-growth eastern white pine in Ontario, Canada. Conserv Biol 11:747–758

    Google Scholar 

  • Burczyk J (1991) The mating system in Scots pine clonal seed orchard in Poland. Ann for Sci 48:443–451

    Google Scholar 

  • Burczyk J, Difazio SP, Adams WT (2004) Gene flow in forest trees: how far do genes really travel? For Genet 11(3):179–192

    CAS  Google Scholar 

  • Cavers S, Degen B, Caron H et al (2005) Optimal sampling strategy for estimation of spatial genetic structure in tree populations. Heredity 95:281–289

    CAS  PubMed  Google Scholar 

  • Chapuis M, Lecoq M, Michalakis Y, Loiseau A, Sword GA, Piry S, Estoup A (2008) Do outbreaks affect genetic population structure? A worldwide survey in Locusta migratoria a pestplagued by microsatellite null alleles. Mol Ecol 17:640–3653

    Google Scholar 

  • Charlesworth D, Charlesworth B (1987) Inbreeding depression and its evolutionary consequences. Annu Rev Ecol Syst 118:237–268

    Google Scholar 

  • Chhatre VE, Rajora OP (2014) Genetic divergence and signatures of natural selection in marginal populations of a keystone, long-lived conifer, eastern white pine (Pinus strobus) from northern Ontario. PLoS ONE 9(5):e97291. https://doi.org/10.1371/journal.pone.0097291

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Chybicki IJ, Burczyk J (2009) Simultaneous estimation of null alleles and inbreeding coefficients. J Hered 100:106–113

    CAS  PubMed  Google Scholar 

  • Chybicki IJ, Dzialuk A, Trojankiewicz M, Slawski M, Burczyk J (2008) Spatial genetic structure within two contrasting stands of Scots pine (Pinus sylvestris L.). Silvae Genetica 57(4):193–202

    Google Scholar 

  • Cornuet JM, Luikart G (1996) Description and power analysis of two tests for detecting recent population bottlenecks from allele frequency data. Genetics 144(4):2001–2014. https://doi.org/10.1093/genetics/144.4.2001

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Danusevičius D, Buchovska J, Stanys V, Šikšnianiene JB, Marozas V, Bendokas V (2013) DNA marker-based identification of spontaneous hybrids between Pinus mugo and P. sylvestris at the Lithuanian sea-side. Nord J Bot 31:1–9. https://doi.org/10.1111/j.1756-1051.2012.01575.x

    Article  Google Scholar 

  • Danusevičius D, Kavaliauskas D, Fussi B (2016a) Optimum sample size for SSR-based estimation of representative allele frequencies and genetic diversity in scots pine populations. Balt for 22(2):194–202

    Google Scholar 

  • Danusevičius D, Kerpauskaite V, Kavaliauskas D, Fussi B, Konnert M, Baliuckas V (2016b) The effect of tending and commercial thinning on the genetic diversity of Scots pine stands. Eur J for Res 135:1159–1174. https://doi.org/10.1007/s10342-016-1002-7

    Article  CAS  Google Scholar 

  • Danusevicius D, Marozas V, Brazaitis G, Petrokas R (2012) Spontaneous hybridization between Pinus mugo (Turra) and Pinus sylvestris (L.) at the Lithuanian sea-side: a morphological survey. Sci World J 2012:11. https://doi.org/10.1100/2012/172407

    Article  Google Scholar 

  • De-Lucas AI, Gonzales-Martnez SC, Vendramin GG, Hidalgo E, Heuertz M (2009) Spatial genetic structure in continuous and fragmented populations of Pinus pinaster Aiton. Mol Ecol 18:4564–4576. https://doi.org/10.1111/j.1365-294X.2009.04372.x

    Article  CAS  PubMed  Google Scholar 

  • Do C, Waples RS, Peel D, Macbeth GM, Tillett BJ, Ovenden JR (2014) NeEstimator v2: re-implementation of software for the estimation of contemporary effective population size (Ne) from genetic data. Mol Ecol Resour 14:209–214

    CAS  PubMed  Google Scholar 

  • Dumolin S, Demesure B, Petit RJ (1995) Inheritance of chloroplast and mitochondrial genomes in pedunculate oak investigated with an efficient PCR method. Theor Appl Genet 91:1253–1256

    CAS  PubMed  Google Scholar 

  • Durrant TH, De Rigo D, Caudullo G (2016) Pinus sylvestris in Europe: distribution, habitat, usage and threats. European atlas of forest tree species, pp 132–133

  • Earl DA, von Holdt BM (2012) STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv Genet Resour 4:359–361. https://doi.org/10.1007/s12686-011-9548-7

    Article  Google Scholar 

  • Elsik CG, Minihan VT, Hall SE, Scarpa AM, Williams CG (2000) Low-copy microsatellite markers for Pinus taeda L. Genome 43:550–555

    CAS  PubMed  Google Scholar 

  • El-Kassaby YA, Benowicz A (2000) Effects of commercial thinning on genetic, plant species and structural diversity in second-growth Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) stands. For Genet 7:193–203

    Google Scholar 

  • Engelmark O (1993) Early post-fire tree regeneration in a Picea-Vaccinium forest in northern Sweden. J Veg Sci 4:791–794

    Google Scholar 

  • Epperson BK (1992) Spatial structure of genetic variation within populations of forest trees. New for 6:257–278

    Google Scholar 

  • Epperson BK (2004) Multilocus estimation of genetic structure within populations. Theor Popul Biol 65:227–237

    PubMed  Google Scholar 

  • Epperson BK, Allard RW (1989) Spatial autocorrelation analysis of the distribution of genotypes within populations of lodgepole pine. Genetics 121:369–377

    CAS  PubMed  PubMed Central  Google Scholar 

  • Epperson BK, Chung MG (2001) Spatial genetic structure of allozyme polymorphisms within populations of Pinus strobus (Pinaceae). Am J Bot 88:1006–1010

    CAS  PubMed  Google Scholar 

  • Eriksson G (1998) Evolutionary forces influencing variation among populations of Pinus sylvestris. Silva Fennica 32(2):173–184. https://doi.org/10.14214/sf.694

    Article  Google Scholar 

  • Escudero A, Iriondo JM, Torres ME (2003) Spatial analysis of genetic diversity as a tool for plant conservation. Biol Conserv 113:351–365

    Google Scholar 

  • Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software structure: a simulation study. Mol Ecol 14:2611–2620. https://doi.org/10.1111/j.1365-294X.2005.02553.x

    Article  CAS  PubMed  Google Scholar 

  • Fady F, Aravanopoulos F, Benavides R, González-Martínez S, Grivet D et al (2020) Genetics to the rescue: managing forests sustainably in a changing world. Tree Genet Genomes. https://doi.org/10.1007/s11295-020-01474-8

    Article  Google Scholar 

  • Fageria MS, Rajora OP (2013) Effects of harvesting of increasing intensities on genetic diversity and population structure of white spruce. Evol Appl 6:778–794. https://doi.org/10.1111/eva.12064

    Article  PubMed  PubMed Central  Google Scholar 

  • Fageria MS, Rajora OP (2014) Effects of silvicultural practices on genetic diversity and population structure of white spruce in Saskatchewan. Tree Genet Genomes 10:287–296. https://doi.org/10.1007/s11295-013-0682-0

    Article  Google Scholar 

  • Finkeldey R, Ziehe M (2004) Genetic implications of silvicultural regimes. For Ecol Manag 197:231–244

    Google Scholar 

  • Fussi B, Westergren M, Aravanopoulos F et al (2016) Forest genetic monitoring: an overview of concepts and definitions. Environ Monit Assess 188:493. https://doi.org/10.1007/s10661-016-5489-7

    Article  PubMed  PubMed Central  Google Scholar 

  • García Gil MR, Olivier F, Kamruzzahan S, Waldmann P (2009) Joint analysis of spatial genetic structure and inbreeding in a managed population of Scots pine. Heredity 103:90–96

    PubMed  Google Scholar 

  • García Gil MR, Floran V, Östlund L, Mullin TJ, Andersson Gull B (2015) Genetic diversity and inbreeding in natural and managed populations of Scots pine. Tree Genet Genomes 11(2):1–12

    Google Scholar 

  • Geewein JB, Kesseli RV (2006) Genetic diversity and population structure of Quercus rubra (Fagaceae) in old-growth and secondary forests in southern New England. Rhodora 108:1–18

    Google Scholar 

  • Götz J, Rajora OP, Gailing O (2022) Genetic structure of natural northern range-margin mainland, peninsular, and island populations of northern red oak (Quercus rubra L.). Front Ecol Evol 10:907414. https://doi.org/10.3389/fevo.2022.907414

    Article  Google Scholar 

  • Goudet J (1995) FSTAT (version 1.2): a computer program to calculate F-statistics. J Hered 86:485–486. https://doi.org/10.1093/oxfordjournals.jhered.a111627

    Article  Google Scholar 

  • González-Díaz P, Jump AS, Perry A, Wachowiak W, Lapshina E, Cavers S (2017) Ecology and management history drive spatial genetic structure in Scots pine. For Ecol Manag 400:68–76. https://doi.org/10.1016/j.foreco.2017.05.035

    Article  Google Scholar 

  • Hampe A, Petit RJ (2005) Conserving biodiversity under climate change: the rear edge matters. Ecol Lett 8:461–467

    PubMed  Google Scholar 

  • Hardy OJ, Vekemans X (2002) SPAGeDi: a versatile computer program to analyse spatial genetic structure at the individual or population levels. Mol Ecol Notes 2:618–620

    Google Scholar 

  • Hayden K, Nettle K, Dodd RS, Garbelolotto M (2011) Will the trees fall? Variable resistance to an introduced forest disease in a highly susceptible forest. For Ecol Manag 261:1781–1791

    Google Scholar 

  • Heuertz M, Vekemans X, Hausman JF, Palada M, Hardy OJ (2003) Estimating seed vs. pollen dispersal from spatial genetic structure in the common ash. Mol Ecol 12:2483–2495

    CAS  PubMed  Google Scholar 

  • Hoban S, Bruford M, Jackson JD’U, Lopez-Fernandez M, Heuertz M, Hohenlohe P (2020) Genetic diversity targets and indicators in the CBD post-2020 Global Biodiversity Framework must be improved. Biol Conserv 248:1–11. https://doi.org/10.1016/j.biocon.2020.108654

  • Hosius B, Leinemann L, Konnert M, Bergmann F (2006) Genetic aspects of forestry in Central Europe. Eur J for Res 125:907–913. https://doi.org/10.1007/s10342-006-0136-4

    Article  Google Scholar 

  • Jimenez-Ramirez A, Grivet D, Robledo-Arnuncio JJ (2021) Measuring effective recent gene flow among large populations in Pinus sylvestris: local pollen shedding does not preclude substantial long-distance pollen immigration. PLoS ONE 16(8):e0255776. https://doi.org/10.1371/journal.pone.0255776

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Jump AS, Penuelas J (2007) Extensive spatial genetic structure revealed by AFLP but not SSR molecular markers in the wind-pollinated tree Fagus sylvatica. Mol Ecol 16:925–936. https://doi.org/10.1111/j.1365-294X.2006.03203.x

    Article  CAS  PubMed  Google Scholar 

  • Juodvalkis A, Kairiūkštis L (2009) Medynų formavimas ir kirtimai (Forest tending manual). Lututė, Kaunas, ISBN 9789955370901, 224 p. (In Lithuanian)

  • Kärkkäinen K, Savolainen O (1993) The degree of early inbreeding depression determines the selfing rate at the seed stage: model and results from Pinus sylvestris (Scots pine). Heredity 71:160–166

    Google Scholar 

  • Kärkkäinen K, Koski V, Saivolainen O (1996) Geographic variation in the inbreeding depression of Scots pine. Evolution 50:111–119

    PubMed  Google Scholar 

  • Kavaliauskas D, Fussi B, Westergren M, Aravanopoulos F, Finzgar D, Baier R, Kraigher H (2018) The interplay between forest management practices, genetic monitoring, and other long-term monitoring systems. Forests 9(3):133

    Google Scholar 

  • Kavaliauskas D, Danusevičius D, Baliuckas V (2022) New insight into genetic structure and diversity of scots pine (Pinus sylvestris L.) populations in lithuania based on nuclear, chloroplast and mitochondrial DNA markers Forests 13(8):1179. https://doi.org/10.3390/f13081179

  • Kembrytė R, Danusevičius D, Baliuckas V, Buchovska J (2022) Phenology is associated with genetic and stem morphotype variation in European beech (Fagus sylvatica L.) stands. Forests 13(5):664. https://doi.org/10.3390/f13050664

    Article  Google Scholar 

  • Knowles P, Perry DJ, Foster A (1992) Spatial genetic structure in two tamatack (Larix laricina (DuRoi) K. Koch.) populations with differing establishment histories. Evolution 46:572–576

    PubMed  Google Scholar 

  • Kopelman N, Mayzel J, Jacobsson M, Rosenberg N, Mayrose I (2015) CLUMPAK: a program for identifying clustering modes and packaging population structure inferences across K. Mol Ecol Resour 15:1179–1191

    CAS  PubMed  PubMed Central  Google Scholar 

  • Krakau U-K, Liesebach M, Aronen T, Leu-Walter M-A, Schneck V (2013) Scots pine (Pinus sylvestris L.). 2013. In: Pâques LE (ed) Forest tree breeding in Europe. Series: managing forest ecosystems, vol 25. Springer, pp 267–325. VI, ISBN 978-94-007-6146-9

  • Kuhner MK (2006) LAMARC 2.0: maximum likelihood and Bayesian estimation of population parameters. Bioinformatics 22(6):768–770. https://doi.org/10.1093/bioinformatics/btk051

    Article  CAS  PubMed  Google Scholar 

  • Ledig FT (1992) Human impacts on genetic diversity in forest ecosystems. Oikos 63:87–108

    Google Scholar 

  • Lefèvre F (2004) Human impacts on forest genetic resources in the temperate zone: an updated review. For Ecol Manag 197:257–271

    Google Scholar 

  • Leonardi S, Menozzi P (1996) Spatial structure of genetic variability in natural stands of Fagus sylvatica L. (beech) in Italy. Heredity 77:359–368

    Google Scholar 

  • Lind BM, North MP, Maloney PE, Eckert AJ (2019) Effect of fire and thinning on fine-scale genetic structure and gene flow in fire-suppressed populations of sugar pine (Pinus lambertiana Dougl). For Ecol Manag 447:115–129

    Google Scholar 

  • Lindgren D, Paule L, Shen X, Yazdani R, Segerstrom U, Vallin J-E, Lejdebro ML (1995) Can viable pollen carry Scots pine genes over long distances? Grana 34:64–69

    Google Scholar 

  • Loiselle BA, Sork VL, Nason J, Graham C (1995) Spatial genetic structure of a tropical understory shrub, Psychotria officinalis (Rubiaceae). Am J Bot 82:1420–1425

    Google Scholar 

  • Marquardt PE, Epperson BK (2004) Spatial and population genetic structure of microsatellites in white pine. Mol Ecol 13:3305–3315

    CAS  PubMed  Google Scholar 

  • Marquardt PE, Echt CS, Epperson BK, Pubanz DM (2007) Genetic structure, diversity, and inbreeding of eastern white pine under different management conditions. Can J for Res 37(12):2652–2662

    CAS  Google Scholar 

  • Mátyás C, Ackzell L, Samuel CJA (2004) EUFORGEN technical guidelines for genetic conservation and use for Scots pine (Pinus sylvestris). Bioversity International, Rome, 6 p. ISBN: 92-9043-661-1

    Google Scholar 

  • Muona O, Yazdani R, Rudin D (1987) Genetic change between life stages of Pinus sylvestris: allozyme variation in seedlings and planted seedlings. Silvae Genetica 36(1):39–42

    Google Scholar 

  • Namkoong G, Boyle T, El-Kassaby YA, Palmberg-Lerche C, Eriksson G, Gregorius H-R, Joly H, Kremer A, Savolainen O, Wickneswari R, Young A, Zeh-Nlo M, Prabhu R (2002) Criteria and indicators for sustainable forest management: assessment and monitoring of genetic variation. Forest genetic resources working Paper FGR/37E, forest resources development service, Forest, pp 281–289

  • Neale DB (1985) Genetic implications of shelterwood regeneration of Douglas-fir in southwest Oregon. For Sci 31:995–1005

    Google Scholar 

  • O’Connell LM, Mosseler A, Rajora OP (2006) Impacts of forest fragmentation on the mating system and genetic diversity of white spruce (Picea glauca) at the landscape level. Heredity 97:418–426

    PubMed  Google Scholar 

  • O’Connell LM, Mosseler A, Rajora OP (2007) Extensive long-distance pollen dispersal in a fragmented landscape maintains genetic diversity in white spruce. J Hered 97:640–645

    Google Scholar 

  • 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). BMC Evol Biol 12:48. https://doi.org/10.1186/1471-2148-12-48

    Article  PubMed  Google Scholar 

  • 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. For Ecol Manag 284:34–44

    Google Scholar 

  • Peakall R, Smouse PE (2006) GenAlEx 6: genetic analysis in Excel. Population genetic software for teaching and research. Mol Ecol Notes 6:288–295. https://doi.org/10.1111/j.1471-8286.2005.01155.x

    Article  Google Scholar 

  • Piry S, Luikart G, Cornuet JM (1999) Computer note. BOTTLENECK: a computer program for detecting recent reductions in the effective size using allele frequency data. J Hered 90:502–503

    Google Scholar 

  • Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155(2):945–959

    CAS  PubMed  PubMed Central  Google Scholar 

  • Pyhäjärvi T, Kujala ST, Savolainen O (2020) 275 years of forestry meets genomics in Pinus sylvestris. Evol App 13:11–30 (Pmid: 31988655)

    Google Scholar 

  • Rajora OP (1999) Genetic biodiversity impacts of silvicultural practices and phenotypic selection in white spruce. Theor Appl Genet 99:954–961

    CAS  Google Scholar 

  • Rajora OP, Mosseler A (2001a) Challenges and opportunities for conservation of forest genetic resources. Euphytica 118:197–212

    Google Scholar 

  • Rajora OP, Mosseler A (2001b) Molecular markers in sustainable management, conservation, and restoration of forest genetic resources. In: Starck G, Schubert R (eds) Genetic response of forest systems to changing environmental conditions, vol 70. Kluwer Academic Publishers, Dordrecht, pp 187–201

    Google Scholar 

  • Rajora OP, Pluhar SA (2003) Genetic diversity impacts of forest fires, forest harvesting and alternative reforestation practices in black spruce (Picea mariana). Theor Appl Genet 106:1203–1212

    CAS  PubMed  Google Scholar 

  • Rajora OP, Zinck JWR (2021) Genetic diversity, structure and effective population size of old-growth vs. second-growth populations of keystone and long-lived conifer, eastern white pine (Pinus strobus): conservation value and climate adaptation potential. Front Genet 12(12):650299. https://doi.org/10.3389/fgene.2021.650299

    Article  PubMed  PubMed Central  Google Scholar 

  • Rajora OP, Rahman MH, Buchert GP, Dancik BP (2000) Microsatellite DNA analysis of genetic effects of harvesting in old-growth eastern white pine (Pinus strobus) in Ontario, Canada. Mol Ecol 9:339–348

    CAS  PubMed  Google Scholar 

  • Ratnam W, Rajora OP, Finkeldey R, Aravanopoulos F, Bouvet J-M, Vaillancourt RE et al (2014) Genetic effects of forest management practices: global synthesis and perspectives. For Ecol Manag 333:52–65. https://doi.org/10.1016/j.foreco.2014.06.008

    Article  Google Scholar 

  • Reiman BE, Allendorf FW (2001) Effective population size and genetic conservation criteria for bull trout. N Am J Fish Manag 21:756–764

    Google Scholar 

  • Reusch TBH, Ehlers A, Hammerli A, Worm B (2005) Ecosystem recovery after climate extremes enhanced by genotypic diversity. Proc Natl Acad Sci USA 102:2826–2831

    CAS  PubMed  PubMed Central  Google Scholar 

  • Rocha LF, Rebeiro de Paula N, Carvalho DD (2021) Fine-scale analysis reveals a potential influence of forest management on the spatial genetic structure of Eremanthus erythropappus. J for Res 32:1567–1578

    CAS  Google Scholar 

  • Roger F, Godhe A, Gamfeldt L (2012) Genetic diversity and ecosystem functioning in the face of multiple stressors. PLoS ONE 7(9):e45007. https://doi.org/10.1371/journal.pone.0045007

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Rousset F (2008) Genepop: a complete re-implementation of the Genepop software for Windows and Linux. Mol Ecol Resour 8:103–106

    PubMed  Google Scholar 

  • Salo T, Gustafsson C (2016) The effect of genetic diversity on ecosystem functioning in vegetated coastal ecosystem. Ecosystems 19:1429–1444

    Google Scholar 

  • Savolainen O, Pyhäjärvi T, Knürr T (2007) Gene flow and local adaptation in trees. Ann Rev Ecol Evol Syst 38:595–619

    Google Scholar 

  • Sebastiani F, Pinzauti F, Kujala ST, González-Martínez SC, Vendramin GG (2012) Novel polymorphic nuclear microsatellite markers for Pinus sylvestris L. Conserv Genet Resour 4(2):231–234

    Google Scholar 

  • Sjölund MJ, Jump AS (2015) Coppice management of forests impacts spatial genetic structure but not genetic diversity in European beach (Fagus sylvatica L.). For Ecol Manag 336:65–71

    Google Scholar 

  • Smouse PE, Peakall R, Gonzales E (2008) A heterogeneity test for fine-scale genetic structure. Mol Ecol 17:3389–3400

    PubMed  Google Scholar 

  • Smouse PE, Peakall R (1999) Spatial autocorrelation analysis of individual multiallele and multilocus genetic structure. Heredity 82:561–573

    PubMed  Google Scholar 

  • Soranzo N, Provan J, Powell W (1998) Characterization of microsatellite loci in Pinus sylvestris L. Mol Ecol 7:1260–1261

    CAS  PubMed  Google Scholar 

  • Spies TA (2004) Ecological concepts and diversity of old-growth forests. J Forest 102:14–20

    Google Scholar 

  • Strakauskaite N (2004) Klaipeda and the Curonian spit guide. R. Paknio publishing, Klaipeda, p 80. ISBN 9986-830-87-7

  • van Oosterhout C, Hutchinson WF, Wills DPM, Shipley PF (2005) Micro-checker user guide. The University of Hull, 27 p

  • Vekemans X, Hardy OJ (2004) New insights from fine-scale spatial genetic structure analyses in plant populations. Mol Ecol 13(4):921–935. https://doi.org/10.1046/j.1365-294x.2004.02076.x

    Article  CAS  PubMed  Google Scholar 

  • Vornam B, Decarli N, Gailing O (2004) Spatial distribution of genetic variation in a natural beech stand (Fagus sylvatica L.) based on microsatellite markers. Conserv Genet 5:561–570. https://doi.org/10.1023/B:COGE.0000041025.82917.ac

    Article  CAS  Google Scholar 

  • Wachowiak W, Wόjkiewicz B, Cavers S, Lewandowski A (2014) High genetic similarity between Polish and North European Scots pine (Pinus sylvestris L.) populations at nuclear gene loci. Tree Genet Genomes 10(4):1015–1025

    Google Scholar 

  • Wang Z-S, Liu H, Xu W-X, Wei N, An S-Q (2010) Genetic diversity in young and mature cohorts of cultivated and wild populations of Picea asperata Mast (Pinaceae), a spruce endemic in western China. Eur J for Res 129:719–728

    Google Scholar 

  • Waples R, Do C (2010) Linkage disequilibrium estimates of contemporary Ne using highly variable genetic markers: a largely untapped resource for applied conservation and evolution. Evol Appl 3:244–262

    PubMed  Google Scholar 

  • Weir BS, Cockerham CC (1984) Estimating F-statistics for the analysis of population structure. Evolution 38(6):1358–1370. https://doi.org/10.1111/j.1558-5646.1984.tb05657.x

    Article  CAS  PubMed  Google Scholar 

  • Wright S (1946) Isolation by distance under diverse systems of mating. Genetics 3:39–59

    Google Scholar 

  • Zhu L, Lou A (2012) Old-growth Platycladus orientalis as a resource for reproductive capacity and genetic diversity. PLoS ONE 8(2):e56489. https://doi.org/10.1371/journal.pone.0056489

    Article  CAS  Google Scholar 

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Acknowledgements

We acknowledge the grant from project No VP1-3.1-ŠMM-08-K-01-025 entitled "Specific, genetic diversity and sustainable development of Scots pine forest to mitigate the negative effects of increased human pressure and climate change" supported by the EU Social Fund. Om P. Rajora acknowledges the funding from the Natural Sciences and Engineering Research Council of Canada Discovery Grant (RGPIN 2017-04589) to him.

Funding

The study was funded by the grant from project No VP1-3.1-ŠMM-08-K-01–025 entitled “Specific, genetic diversity and sustainable development of Scots pine forest to mitigate the negative effects of increased human pressure and climate change” supported by the EU Social Fund.

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Author notes

  1. Darius Danusevicius and Om P. Rajora contributed equally to the work.

Authors and Affiliations

  1. Vytautas Magnus University, K. Donelaičio Str. 58, 44248, Kaunas, Lithuania

    Darius Danusevicius, Darius Kavaliauskas, Virgilijus Baliuckas & Algirdas Augustaitis

  2. Faculty of Forestry and Environmental Management, University of New Brunswick, 28 Dineen Drive, PO Box 44000, Fredericton, NB, E3B 5A3, Canada

    Om P. Rajora

  3. Forestry Institute, Lithuanian Research Centre for Agriculture and Forestry, Liepu Str. 1, 53101, Kaunas, Lithuania

    Virgilijus Baliuckas

Authors
  1. Darius Danusevicius
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  2. Om P. Rajora
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  3. Darius Kavaliauskas
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  4. Virgilijus Baliuckas
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  5. Algirdas Augustaitis
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Contributions

DD proposed the study idea, wrote the manuscript and carried out statistical analyses; OPR conceived the study, contributed to design and overall directions, analyzed and interpreted the data, and wrote and revised the manuscript; DK carried out the laboratory analysis and statistical analysis, and collected the field data; VB was involved in material selection and field sampling; and AA took part in funding and material selection.

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Correspondence to Darius Danusevicius or Om P. Rajora.

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Danusevicius, D., Rajora, O.P., Kavaliauskas, D. et al. Genetic diversity and fine-scale spatial genetic structure of unmanaged old-growth versus managed second-growth populations of Scots pine (Pinus sylvestris L.) in Lithuania. Eur J Forest Res 142, 773–793 (2023). https://doi.org/10.1007/s10342-023-01556-x

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