Tree Genetics & Genomes

, 12:23 | Cite as

Climate change risk management in tree improvement programs: selection and movement of genotypes

  • Laura K. Gray
  • Andreas Hamann
  • Sally John
  • Deogratias Rweyongeza
  • Leonard Barnhardt
  • Barb R. Thomas
Original Article
Part of the following topical collections:
  1. Breeding


Tree improvement programs usually consist of multiple breeding populations that target different climatic or ecological regions. Parent breeding material normally originates from and is deployed within the same breeding region, assuming optimal local adaptation of populations. Given the climate trends observed over the last several decades in western Canada, this assumption is unlikely to still be valid. This problem needs to be addressed either by delineating new deployment areas for improved planting stock or by selecting genotypes suitable for changed climatic environments. In a case study for white spruce, we analyzed height data from 135,000 trees grown in 44 genetic tests established and evaluated over a period of 35 years by industry and government agencies in Alberta. We show how the risk of planting maladapted trees can be minimized by moving planting stock to new areas, or by eliminating genotypes from breeding programs that are sensitive to anticipated future climate environments. Transfers that outperformed local sources consistently originated from locations with higher temperatures, suggesting north or northwest transfers. However, adaptation to cold appears to be a prevalent driver for genetic population differentiation in spruce, thus limiting how far material may be moved in current reforestation efforts to address future climate change.


Reforestation Climate change White spruce Seed transfer Breeding programs 



This analysis includes data from every white spruce tree improvement region in Alberta and would not have been possible without participation and data sharing by Alberta Newsprint Company, Canadian Forest Products Ltd., Manning Diversified Forest Products, Millar Western Forest Products Ltd., Northlands Forest Products, Timber Ltd., Tolko Industries Ltd., West Fraser Mills Ltd. (including its divisions: Hinton Wood Products and Blue Ridge Lumber), Weyerhaeuser Company Ltd. (Grande Prairie and Pembina Timberlands), and the provincial ministry of Agriculture and Forestry (AAF). Funding was provided by the Tree Species Adaptation Risk Management project, managed by Tree Improvement Alberta (TIA) and funded by Climate Change and Emissions Management (CCEMC) Corporation and AAF (formerly Alberta Environment and Sustainable Resource Development). We would like thank Daniel Chicoine from Incremental Forest Technology Ltd. for his contribution as the CCEMC project Manager. Finally, we would like to acknowledge the commitment and tireless effort and support of Bruce Macmillan, who was instrumental in helping to secure the CCEMC project funding and ensuring the success of this work.

Data accessibility

Data from genetic field trials were provided by private companies and government agencies (see Acknowledgements), and so are not owned by the authors and thus not available in the archive.

Supplementary material

11295_2016_983_MOESM1_ESM.csv (104 kb)
Table S1 Best linear unbiased estimates (BLUEs) with their standard errors (SE) of performance of families and provenances (AccessionID) when tested in their region and when transferred to other breeding regions in Alberta (TestREGION). BLUEs and their standard errors are normalized by the mean of all accessions planted in their home breeding region set to zero and a standard deviation of one, so that the performance of each accession is expressed in percentage above or below the performance of local sources. (CSV 103 kb)


  1. Andalo C, Beaulieu J, Bousquet J (2005) The impact of climate change on growth of local white spruce populations in Quebec, Canada. For Ecol Manag 205:169–182CrossRefGoogle Scholar
  2. Barber VA, Juday GP, Finney BP (2000) Reduced growth of Alaskan white spruce in the twentieth century from temperature-induced drought stress. Nature 405:668–673CrossRefPubMedGoogle Scholar
  3. Beaulieu J (1996) Breeding program and strategy for white spruce in Quebec. Natural Resource Canada, Canadian Forest Service, Sainte-Foy, Quebec. Inf. Rep. LAU-X-117E, 25 pGoogle Scholar
  4. Beaulieu J, Perron M, Bousquet J (2004) Multivariate patterns of adaptive genetic variation and seed source transfer in Picea mariana. Canadian J For Res 34:531–545Google Scholar
  5. Bigras FJ (2005) Photosynthetic response of white spruce families to drought stress. New For 29:135–148CrossRefGoogle Scholar
  6. 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 28:2031–2064CrossRefGoogle Scholar
  7. De'Ath G (2002) Multivariate regression trees: a new technique for modeling species-environment relationships. Ecology 83:1105–1117Google Scholar
  8. De'ath G (2014) mvpart: Multivariate partitioning. R Package Version 1.6.2. Available at:
  9. Fettig CJ, Reid ML, Bentz BJ, Sevanto S, Spittlehouse DL, Wang T (2013) Changing climates, changing forests: a Western North American perspective. J For 111:214–228Google Scholar
  10. Field CB, Mortsch LD, Brklacich M, Forbes DL, Kovacs P, Patz JA, Running SW, Scott MJ (2007) Climate change 2007: impacts, adaptation and vulnerability. In: Parry ML, Canziani OF, Palutikof JP, van der Linden PJ, Hanson CE (eds) Contribution of working group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, pp 617–652Google Scholar
  11. Gilmour AR, Thompson R, Cullis BR (1995) Average information REML: an efficient algorithm for variance parameter estimation in linear mixed models. Biometrics 1440–1450Google Scholar
  12. Gilmour AR, Gogel BJ, Cullis BR, Thompson R (2009) ASReml User Guide Release 3.0. VSN International Ltd, Hemel Hempstead, HP1 1ES, UKGoogle Scholar
  13. Gray LK, Hamann A (2012) Strategies for reforestation under uncertain future climates: guidelines for Alberta, Canada. PLoS One 6:e22977CrossRefGoogle Scholar
  14. Gray LK, Hamann A (2013) Tracking suitable habitat for tree populations under climate change in western North America. Clim Chang 117:289–303CrossRefGoogle Scholar
  15. Gray LK, Gylander T, Mbogga MS, Chen PY, Hamann A (2011) Assisted migration to address climate change: recommendations for aspen reforestation in western Canada. Ecol Appl 21:1591–1603CrossRefPubMedGoogle Scholar
  16. Hamann A, Wang TL (2005) Models of climatic normals for genecology and climate change studies in British Columbia. Agric For Meteorol 128:211–221CrossRefGoogle Scholar
  17. Hamann A, Gylander T, Chen P (2011) Developing seed zones and transfer guidelines with multivariate regression trees. Tree Genetics Genomes 7:399–408CrossRefGoogle Scholar
  18. Hamann A, Wang T, Spittlehouse DL, Murdock TQ (2013) A comprehensive, high-resolution database of historical and projected climate surfaces for western North America. Bull Am Meteorol Soc 94:1307–1309CrossRefGoogle Scholar
  19. Hogg EH, Brandt JP, Kochtubajda B (2002) Growth and dieback of aspen forests in northwestern Alberta, Canada, in relation to climate and insects. Can J For Res 32:823–832CrossRefGoogle Scholar
  20. Hogg EH, Brandt JP, Michaelian M (2008) Impacts of a regional drought on the productivity, dieback, and biomass of western Canadian aspen forests. Can J For Res 38:1373–1384CrossRefGoogle Scholar
  21. Kawecki TJ, Ebert D (2004) Conceptual issues in local adaptation. Ecol Lett 7:1225–1241CrossRefGoogle Scholar
  22. Li P, Beaulieu J, Bousquet J (1997) Genetic structure and patterns of genetic variation among populations in eastern white spruce (Picea glauca). Can J For Res 27:189–198CrossRefGoogle Scholar
  23. Lloyd A, Fastie C (2002) Spatial and temporal variability in the growth and climate response of treeline trees in Alaska. Clim Chang 52:481–509CrossRefGoogle Scholar
  24. Mbogga MS, Hamann A, Wang T (2009) Historical and projected climate data for natural resource management in western Canada. Agric For Meteorol 149:881–890CrossRefGoogle Scholar
  25. Michaelian M, Hogg EH, Hall RJ, Arsenault E (2011) Massive mortality of aspen following severe drought along the southern edge of the Canadian boreal forest. Glob Chang Biol 17:2084–2094CrossRefPubMedCentralGoogle Scholar
  26. O’Neill GA, Ukrainetz NK, Carlson MR, Cartwright CV, Jaquish BC, King JN, Krakowski J, Russell JH, Stoehr MU, Xie C, Yanchuk AD (2008) Assisted migration to address climate change in British Columbia: recommendations for interim seed transfer standards. BC Ministry Forest Range, Research Branch, Victoria, BC. Technical Rep, 48Google Scholar
  27. Oksanen J, Kindt R, Legendre P, O’Hara B, Stevens MHH, Oksanen MJ, Suggests M (2013) vegan: R functions for community ecology. R Package Version 2.0.7. Available at:
  28. Peng CH, Ma ZH, Lei XD, Zhu Q, Chen H, Wang WF, Liu SR, Li WZ, Fang XQ, Zhou XL (2011) A drought-induced pervasive increase in tree mortality across Canada’s boreal forests. Nat Clim Change 1:467–471CrossRefGoogle Scholar
  29. R Development Core Team (2015) R: a language and environment for statistical computing. R Foundation for Statistical Computing Version 3.1.3, Vienna, AustriaGoogle Scholar
  30. Rweyongeza D (2011) Pattern of genotype–environment interaction in Picea glauca (Moench) Voss in Alberta, Canada. Ann For Sci 68:245–253CrossRefGoogle Scholar
  31. Rweyongeza D, Yang R, Dhir N, Barnhardt L, Hansen C (2007a) Genetic variation and climatic impacts on survival and growth of white spruce in Alberta, Canada. Silvae Genetica 56:117–126Google Scholar
  32. Rweyongeza DM, Dhir NK, Barnhardt LK, Hansen C, Yang R-C (2007b) Population differentiation of the lodgepole pine (Pinus contorta) and jack pine (Pinus banksiana) complex in Alberta: growth, survival, and responses to climate. Can J Bot 85:545–556CrossRefGoogle Scholar
  33. Rweyongeza D, Barnhardt L, Dhir N, Hansen C (2010) Population Differentiation and Climatic Adaptation for Growth Potential of White Spruce (Picea glauca) in Alberta, Canada. Silvae Genetica 59:158Google Scholar
  34. Savolainen O, Pyhäjärvi T, Knürr T (2007) Gene flow and local adaptation in trees. Annu Rev Ecol Evol Syst 38:595–619CrossRefGoogle Scholar
  35. SRD (2009) Alberta Forest Genetic Resource Management and Conservation Standards (FGRMS). Alberta Sustainable Resource Development, EdmontonGoogle Scholar
  36. Szekely GJ, Rizzo ML (2005) Hierarchical clustering via joint between-within distances: extending Ward’s minimum variance method. J Classif 22:151–183CrossRefGoogle Scholar
  37. Wang T, O’Neill G, Aitken SN (2010) Integrating environmental and genetic effects to predict responses of tree populations to climate. Ecol Appl 20:153–163CrossRefPubMedGoogle Scholar
  38. Wang Y, Hogg EH, Price DT, Edwards J, Williamson T (2014) Past and projected future changes in moisture conditions in the Canadian boreal forest. For Chron 90:678–691CrossRefGoogle Scholar
  39. Williams ER, Matheson AC, Harwood CE (2002) Experimental design and analysis for tree improvement Second Ed. CSIRO publishing, CollingwoodGoogle Scholar
  40. Worrall JJ, Rehfeldt GE, Hamann A, Hogg EH, Marchetti SB, Michaelian M, Gray LK (2013) Recent declines of Populus tremuloides in North America linked to climate. For Ecol Manag 299:35–51CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Department of Renewable ResourcesUniversity of AlbertaEdmontonCanada
  2. 2.Isabella Point Forestry Ltd.Salt Spring IslandCanada
  3. 3.Alberta Agriculture and Forestry, Forest Management BranchEdmontonCanada
  4. 4.Department of Renewable ResourcesUniversity of AlbertaEdmontonCanada

Personalised recommendations