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The main objective of this study was to examine the climatic sensitivity of the radial growth response of 13 eastern white pine (Pinus strobus L.) provenances planted at seven test sites throughout the northern part of the species' native distribution in eastern North America.
The test sites (i.e., Wabeno, Wisconsin, USA; Manistique, Michigan, USA; Pine River, Michigan, USA; Newaygo, Michigan, USA; Turkey Point, Ontario, Canada; Ganaraska, Ontario, Canada; and Orono, Maine, USA) examined in this study were part of a range-wide white pine provenance trial established in the early 1960s in the eastern United States and Canada. Principal components analysis (PCA) was used to examine the main modes of variation [first (PC1) and second (PC2) principal component axes] in the standardized radial growth indices of the provenances at each test site. The year scores for PC1 and PC2 were examined in relation to an array of test site climate variables using multiple regression analysis to examine the commonality of growth response across all provenances to the climate of each test site. Provenance loadings on PC1 and PC2 were correlated with geographic parameters (i.e., latitude, longitude, elevation) and a suite of biophysical parameters associated with provenance origin location.
The amount of variation in radial growth explained by PC1 and PC2 ranged from 43.4% to 89.6%. Dendroclimatic models revealed that white pine radial growth responses to climate were complex and differed among sites. The key dendroclimatic relationships observed included sensitivity to high temperature in winter and summer, cold temperature in the spring and fall (i.e., beginning and end of the growing season), summer moisture stress, potential sensitivity to storm-induced damage in spring and fall, and both positive and negative effects of higher winter snowfall. Separation of the loadings of provenances on principal component axes was mainly associated with temperature-related bioclimatic parameters of provenance origin at 5 of the 7 test sites close to the climate influence of the Great Lakes (i.e., Wabeno, Manistique, Pine River, Newaygo, and Turkey Point). In contrast, differences in radial growth response to climate at the Ganaraska test site, were driven more by precipitation-related bioclimatic parameters of the provenance origin location while radial growth at the easternmost Orono test site was independent of bioclimate at the provenance origin location.
Study results suggest that genetic adaptation to temperature and precipitation regime may significantly influence radial growth performance of white pine populations selected for use in assisted migration programs to better adapt white pine to a future climate.
The main objective of this study was to examine the climatic sensitivity of the radial growth response of 13 eastern white pine (Pinus strobus L.) provenances planted at seven test sites throughout the northern part of the species' native distribution in eastern North America.
The test sites (i.e., Wabeno, Wisconsin, USA; Manistique, Michigan, USA; Pine River, Michigan, USA; Newaygo, Michigan, USA; Turkey Point, Ontario, Canada; Ganaraska, Ontario, Canada; and Orono, Maine, USA) examined in this study were part of a range-wide white pine provenance trial established in the early 1960s in the eastern United States and Canada. Principal components analysis (PCA) was used to examine the main modes of variation [first (PC1) and second (PC2) principal component axes] in the standardized radial growth indices of the provenances at each test site. The year scores for PC1 and PC2 were examined in relation to an array of test site climate variables using multiple regression analysis to examine the commonality of growth response across all provenances to the climate of each test site. Provenance loadings on PC1 and PC2 were correlated with geographic parameters (i.e., latitude, longitude, elevation) and a suite of biophysical parameters associated with provenance origin location.
The amount of variation in radial growth explained by PC1 and PC2 ranged from 43.4% to 89.6%. Dendroclimatic models revealed that white pine radial growth responses to climate were complex and differed among sites. The key dendroclimatic relationships observed included sensitivity to high temperature in winter and summer, cold temperature in the spring and fall (i.e., beginning and end of the growing season), summer moisture stress, potential sensitivity to storm-induced damage in spring and fall, and both positive and negative effects of higher winter snowfall. Separation of the loadings of provenances on principal component axes was mainly associated with temperature-related bioclimatic parameters of provenance origin at 5 of the 7 test sites close to the climate influence of the Great Lakes (i.e., Wabeno, Manistique, Pine River, Newaygo, and Turkey Point). In contrast, differences in radial growth response to climate at the Ganaraska test site, were driven more by precipitation-related bioclimatic parameters of the provenance origin location while radial growth at the easternmost Orono test site was independent of bioclimate at the provenance origin location.
Study results suggest that genetic adaptation to temperature and precipitation regime may significantly influence radial growth performance of white pine populations selected for use in assisted migration programs to better adapt white pine to a future climate.
Abrams MD, van de Gevel S, Dodson RC, Copenheaver CA (2000) The dendroecology and climatic impacts for old-growth white pine and hemlock on the extreme slopes of the Berkshire Hills, Massachusetts, U.S.A. Can J Bot 78:851–861
Alexander RM, Perschel R (2009) A review of forestry mitigation and adaptation strategies in the northeast US. Clim Chang 96:167–183
Black BA, Abrams MD (2005) Disturbance history and climate response in an old-growth hemlock-white pine forest, central Pennsylvania. J Torrey Bot Soc 132:103–114
Chen P-Y, Welsh C, Hamann A (2010) Geographic variation in growth response of Douglas-fir to interannual climate variability and projected climate change. Glob Chang Biol 16:3374–3385
Chhin S (2010) Influence of climate on growth of hybrid poplar in Michigan. Forests 1:209–229
Chhin S (2015) Impact of future climate change on a genetic plantation of hybrid pine. Botany 93:397–404
Chhin S, Chumack K, Dahl TA, David ET, Kurzeja P, Magruder M, Telewski FW (2013) Growth-climate relationships of Pinus strobus in a floodway versus terrace forest along the banks of the red Cedar River, Michigan. Tree-ring Res 69:37–47
Chhin S, Hogg EH, Lieffers VJ, Huang S (2008) Potential effects of climate change on the growth of lodgepole pine across diameter size classes and ecological regions. Forest Ecol Manag 256:1692–1703
Daly C, Halbleib M, Smith JI, Gibson WP, Doggett MK, Taylor GH, Curtis J, Pasteris PP (2008) Physiologically sensitive mapping of climatological temperature and precipitation across the conterminous United States. Intl. J Climatol 28:2031–2064
Eilmann B, Sterck F, Wegner L, de Vries SMG, von Arx G, Mohren GMJ, den Ouden J, Sass-Klaassen U (2014) Wood structural differences between northern and southern beech provenances growing at a moderate site. Tree Physiol 34:882–893
Everham EM, Brokaw NVL (1996) Forest damage and recovery from catastrophic wind. Bot Rev 62:113–185
Genys JB (1987) Provenance variation among different provenances of Pinus strobus from Canada and the United States. Can J For Res 17:228–235
Graumlich LJ (1993) Response of tree growth to climatic variation in the mixed conifer and deciduous forest of the upper Great Lakes region. Can J For Res 23:133–143
Gray LK, Rweyongeza D, Hamann A, John S, Thomas BR (2016) Developing management strategies for tree improvement programs under climate change: insights gained from long-term field trials with lodgepole pine. Forest Ecol Manag 377:128–138
Grissino-Mayer HD (2001) Evaluating crossdating accuracy: a manual and tutorial for the computer program COFECHA. Tree-Ring Res 57:205–221
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 94:1307–1309
Hogg EH (1997) Temporal scaling of moisture and the forest-grassland boundary in western Canada. Agric For Meteorol 84:115–122
Holmes RL (1983) Computer-assisted quality control in tree-ring dating and measurement. Tree-Ring Bull 43:69–75
Iverson LR, Prasad AM, Matthews SN, Peters M (2008) Estimating potential habitat for 134 eastern U.S. tree species under six climate scenarios. Forest Ecol Manag 254:390–406
Iverson LR, Thompson FR Ⅲ, Matthews S, Peters M, Prasad A, Dijak WD, Fraser J, Wang WJ, Hanberry B, He H, Janowiak M, Butler P, Brandt L, Swanston C (2017) Multi-model comparison on the effects of climate change on tree species in the eastern U.S.: results from an enhanced niche model and process-based ecosystem and landscape models. Landsc Ecol 32:1327–1346
Joyce DG, Lu P, Sinclair RW (2002) Genetic variation in height growth among populations of eastern white pine (Pinus strobus L.) in Ontario. Silv Genet 51:136–142
Joyce DG, Rehfeldt GE (2013) Climatic niche, ecological genetics, and impact of climate change on eastern white pine (Pinus strobus L.): guidelines for land managers. Forest Ecol Manag 295:173–192
Kilgore JS, Telewski FW (2004) Climate-growth relationships for native and nonnative Pinaceae in northern Michigan's pine barrens. Tree-ring Res 60:3–13
King GM, Gugerli F, Fonti P, Frank DC (2013) Tree growth response along an elevational gradient: climate or genetics? Oecologia 173:1587–1600
King JP, Nienstaedt H (1969) Variation in eastern white pine seed sources planted in the Lake states. Silv Genet 18:83–86
Kipfmueller KF, Elliott GP, Larson ER, Salzer MW (2010) An assessment of the dendroclimatic potential of three conifer species in northern Minnesota. Tree-ring Res 66:113–126
Kozlowski TT, Kramer PJ, Pallardy SG (1991) The physiological ecology of Woody plants. Academic Press, San Diego, CA
Legendre P, Legendre L (1998) Numerical ecology. 2nd Ed. developments in environmental modeling 20. Elsevier science BV, Amsterdam, Netherlands
Lu P, Joyce DG, Sinclair RW (2003a) Geographic variation in cold hardiness among eastern white pine (Pinus strobus L.) provenances in Ontario. Forest Ecol Manag 178:329–340
Lu P, Joyce DG, Sinclair RW (2003b) Effect of selection on shoot elongation rhythm of eastern white pine (Pinus strobus L.) and its implications to seed transfer in Ontario. Forest Ecol Manag 182:161–173
McKenney DW, Pedlar JH, Lawrence K, Campbell K, Hutchinson MF (2007) Potential impacts of climate change on the distribution of north American trees. Bioscience 57:939–948
McLane SC, Daniels LD, Aitken SN (2011) Climate impacts on lodgepole pine (Pinus contorta) radial growth in a provenance experiment. Forest Ecol Manag 262:115–123
Mickler RA, Birdsey RA, Hom J (2000) Responses of northern U.S. forests to environmental change. Springer, NY, p 578
Millar CI, Stephenson NL, Stephens SL (2007) Climate change and forests of the future: managing in the face of uncertainty. Ecol Appl 17:2145–2151
Parmesan C, Yohe G (2003) A globally coherent fingerprint of climate change impacts across natural systems. Nature 421:37–42
Peters EB, Wythers HK, Zhang S, Bradford JB, Reich PB (2013) Potential climate change impacts on temperate forest ecosystem processes. Can J For Res 43:939–950
Peterson CJ (2000) Catastrophic wind damage to north American forests and the potential impact of climate change. Sci Total Environ 262:287–311
Pluess AR, Weber P (2012) Drought-adaptation potential in Fagus sylvatica: linking moisture availability with genetic diversity and dendrochronology. PLoS ONE 7:Article e33636
Rehfeldt GE, Yin CC, Spittlehouse DL, Hamilton Jr D (1999) Genetic responses to climate change in Pinus contorta: niche breadth, climate change and reforestation. Ecol Monogr 69:373–407
Scott RW, Huff FA (1996) Impacts of the Great Lakes on regional climate conditions. J Great Lakes Res 22:845–863
Stokes MA, Smiley TL (1996) An introduction to tree-ring dating. The University of Arizona Press. Tucson, Arizona
Vose JM, Swank WT (1994) Effects of long-term drought on the hydrology and growth of a white pine plantation in the southern Appalachians. Forest Ecol Manag 64:25–39
Wang T, Hamann A, Yanchuk A, O'Neill GA, Aitken SN (2006) Use of response functions in selecting lodgepole pine populations for future climates. Glob Chang Biol 12:2404–2416
Wang T, O'Neill GA, Aitken SN (2010) Integrating environmental and genetic effects to predict responses of tree populations to climate. Ecol Appl 20:153–163
Yang J, Pedlar JH, McKenney DW, Weersink A (2015) The development of universal response functions to facilitate climate-smart regeneration of black spruce and white pine in Ontario, Canada. Forest Ecol Manag 339:34–43
Zalesny RS Jr, Headlee WL (2015) Developing woody crops for the enhancement of ecosystem services under changing climates in the north Central United States. J Forest Exp Sci 31: 78–90
Zar JH (1999) Biostatistical analysis, 4th edn. Prentice Hall, Upper Saddle River, NJ
Thanks go to N. Eskelin, B. Brown, J. Winters, P. Lu, S. Colombo, K. Finley, K. Minnix, I. Allen, B. Birr, and A. Wiese for assistance with field and laboratory data collection. We are grateful to E. Bauer, Dr. W. Headlee, and two anonymous reviewers for their many helpful comments on earlier versions of this manuscript. The conclusions and opinions in this paper are those of the authors and not the Northeastern States Research Cooperative (NSRC), the US Forest Service, or the USDA.
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