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Ecology and Evolution logoLink to Ecology and Evolution
. 2018 Feb 19;8(6):3208–3218. doi: 10.1002/ece3.3852

Effect of climatic variation on the morphological characteristics of 37‐year‐old balsam fir provenances planted in a common garden in New Brunswick, Canada

Matthew E Akalusi 1, Charles P‐A Bourque 1,
PMCID: PMC5869355  PMID: 29607018

Abstract

The extent of the effect of projected changes in climate on trees remains unclear. This study investigated the effect of climatic variation on morphological traits of balsam fir [Abies balsamea (L.) Mill.] provenances sourced from locations spanning latitudes from 44° to 51°N and longitudes from 53° to 102°W across North America, growing in a common garden in eastern Canada. Lower latitude provenances performed significantly better than higher latitude provenances (p < .05) with regard to diameter at breast height (DBH), height (H), and crown width (CW), a distinction indicative of genotypic control of these traits. There was, however, no significant difference among provenances in terms of survival (> .05), an indication of a resource allocation strategy directed at survival relative to productivity in higher latitude provenances as seen in their lower DBH, H, and CW compared to the lower latitude provenances. Temperature had a stronger relationship with DBH, H, and CW than precipitation, a reflection of adaptation to local conditions in populations of the species along latitudinal gradients. Both climatic variables had some effect on tree survival. These results suggest that the response of balsam fir to climatic variation will likely not be uniform in the species, but differ based on genetic characteristics between populations located in the northern and southern parts of the species’ range. Population differences in response to climatic variation may be evident earlier in growth traits, compared to survival in balsam fir. The findings of this study will facilitate modeling in the species that is reflective of genetic variation in response to climatic conditions, and guide provenance selection for utilization in terms of productivity or resilience as well as breeding programs directed at obtaining species that possibly combine both traits.

Keywords: climate model, climate normals, intraspecific variation, latitude, plant–climate interactions, population, species range

1. INTRODUCTION

Climate is a major environmental factor that controls the distribution and growth of plant species (Woodward, 1987). Species occupying large ranges which also span more than one climate zone usually show large intraspecific variation in physiology, morphology, and growth rate (Abrams, 1994; Palmroth, Berninger & Nikinmaa, 1999; Aspelmeier & Leuschner, 2004; Donselman & Flint, 1982; Geber & Dawson, 1993; Schuler 1994; Marchin, Sage, & Ward, 2008).Climate models predict a rise in the mean annual temperature of the Northern Hemisphere and modified patterns of precipitation (Andalo, Beaulieua, & Bousquet, 2005). North America is projected to warm by between 1 and 3°C this century, with the greatest warming expected to occur at high latitudes in winter and the southwest of the United States (US) in summer. Annual precipitation is projected to increase across the North American continent, except in the southwest of the United States where a decrease is anticipated, and parts of southern Canada where precipitation declines are expected to occur in summer and fall (Intergovernmental Panel on Climate Change, 2007; Lemmen, Warren, Lacroix, & Bush, 2008; Warren & Lemmen, 2014). It is projected that climate change will have a tremendous effect on forest ecosystems and tree growth. Iverson and Prasad (1998) based on scenario analysis, involving several conifer and broad‐leaved species in the United States, show potential shifts arising from climate change, which may result in species range transformations. Briffa Schweingruber, Jones, Osborn, Harris, et al. (1998); Briffa, Schweingruber, Jones, Osborn, Shiyatov, et al. (1998) in Northern Hemisphere tree ring studies showed increasing divergence between ring width and maximum latewood density and temperature variation over decadal scales. The extent of these anticipated changes, however, remains unclear (Saxe, Cannell, Johnsen, Ryan, & Vourlitis, 2001; Solberg, Hofgaard, & Hytteborn, 2002;  Wilson & Elling, 2004;  Büntgen et al., 2006; Savva, Bergeron, Denneler, Koubaa, & Tremblay, 2008).

Provenance trials, originally established in many countries in the last century for the selection of superior commercial genotypes, have emerged serendipitously as in situ laboratories for the study of tree response to climate change (Matyas, 1994; O'Neill & Nigh, 2011). Provenance trials involve the transfer of seeds from different parts of a species range to a similar environment, and as a result, simulate spatially the complex atmospheric variations likely to occur over the next few decades (Anderson, Panetta, & Mitchell‐Olds, 2012; Montesinos‐Navarro, Wig, Xavier Pico, & Tonsor, 2011), making them well‐suited for studying tree response to climate change (Schmidtling, 1994; Carter, 1996; Matyas, 1996, 1999; Persson, 1998;  Rehfeldt, Tchebakova, & Barnhardt, 1999; Andalo et al., 2005; Savva et al., 2008). Plant species comprising populations genetically attuned to different climates will experience short‐ and long‐term impacts on their growth and survival when such populations are moved from their climate of origin to a different climate (Rehfeldt, 2004). Short‐term impacts are controlled by the ability of species to make phenotypic adjustments to environmental change, while the long‐term response of forest trees to climate is achieved through processes such as selection, migration, and random genetic drift, which result in modification of gene pools (Rweyongeza, Yang, Dhir, Barnhardt, & Hansen, 2007). Using provenance trials, species or population responses across an environmental gradient can be characterized by relating the provenance's performance to climatic conditions at its source area. Effects of climatic change on future performance of species or populations can be predicted by modeling these response patterns, facilitating forest management strategies that can be based on knowledge of the adaptive capabilities of these species (Cherry & Parker, 2003; Thomson & Parker, 2008).

Balsam fir is a shade‐tolerant tree with a range that spans Canada (from Newfoundland to Alberta) and the United States (a substantial part of the northeast, extending to Minnesota and Virginia). It is used in pulp production, light frame construction, paneling, and the manufacture of medicines, and is popular as a Christmas tree (Frank, 1990). Several studies have modeled the response of conifers to climatic change using provenance trials based on jack pine (Pinus banksiana, Rweyongeza, Dhir, Barnhardt, Hansen, & Yang, 2007; Savva, Denneler, Koubaa, Tremblay, & Tjoelker, 2007; 2008; Tjoelker, Oleksyn, Reich, & Zytkowiak, 2008), white spruce (Picea glauca, Andalo et al., 2005; Rweyongeza, Yang, et al., 2007), black spruce, Picea mariana, Wei, Han, Dhir, & Yeh, 2004; Thomson, Riddell, & Parker, 2009), and Scots pine (Pinus sylvestris, Reich, Oleksyn, & Tjoelker, 1996; Persson, 1998; Rehfeldt et al., 2002). Such studies based on balsam fir are uncommon (Carter, 1996). The objectives of this study were to (i) determine the effect of climatic variation on morphological traits of balsam fir and (ii) develop climate response models for this species.

2. MATERIALS AND METHOD

2.1. Test site and Provenances

This study is based on data from a provenance trial established in 1961, made up of twelve balsam fir [Abies balsamia (L.) Mill.] seed sources planted at Salmon River Balsam Fir Provenance Research Plantation in northern New Brunswick, Canada (47° 7′N and 67° 32′W; MacGillivray, 1963). The test site is located in the Atlantic Maritime Ecozone (Ecological Stratification Working Group 1996), with the following climatic conditions for the period 1971‐2000 (i) mean annual temperature of 3.5°C; (ii) mean summer temperature of 16.8°C; (iii) mean winter temperature of −11.1°C; and (iv) total precipitation of 1134.4 mm (Environment Canada 2016). The provenances were sourced from locations spanning latitudes from 44° to 51°N and longitudes from 53° to 102°W across North America (Table 1).

Table 1.

Provenance sources and provenance test site, with their coordinate position, key climatic variables for the period 1971‐2000 (mean annual temperature (MAT), mean winter temperature (MWT), mean summer temperature (MST), all in °C; total annual precipitation (TPPT), in mm), and Ecozone/Ecoregion location (refer to MacGillivray, 1963; Bailey, 1995; Ecological Stratification Working Group 1996; and Environment Canada 2016)

Provenance Source Latitude Longitude MAT (°C) MWT (°C) MST (°C) TPPT (mm) Ecozone/Ecoregion
MS‐130 Duck Mountain,
Saskatchewan (SK)
51° 50ʹN 102°W 1.6 −15.5 11.1 450.9 Prairies
MS‐133 Roddickton,
Newfoundland (NF)
50° 55ʹN 56°W 2.1 −9.2 13.2 975.3 Boreal Shield
MS‐131 Airplane Bay,
Manitoba (MB)
50° 40ʹN 100°W 1.1 −16.1 16.4 457.1 Prairies
MS‐126 Hawke's Bay,
Newfoundland (NF)
50° 37ʹN 57° 15ʹW 2.4 −8.4 12.7 1145.2 Boreal Shield
MS‐127 Bonne Bay,
Newfoundland (NF)
49° 25ʹN 57° 44ʹW 4.1 −6.5 14.7 1620.7 Boreal Shield
MS‐123 Sandy Brook,
Newfoundland (NF)
48° 44ʹN 56° 04ʹW 3.2 −7.8 14.1 1082.8 Boreal Shield
MS‐2 Green River Watershed,
New Brunswick (NB)
47° 46ʹN 68° 15ʹW 3.2 −11.2 16.5 1091.5 Atlantic Maritime
MS‐125 Salmonier,
Newfoundland (NF)
47° 17ʹN 53° 20ʹW 4.9 −3.7 13.3 1392.1 Boreal Shield
Test Site Salmon River Plantation,
New Brunswick (NB)
47° 07ʹN 67° 32ʹW 3.5 −11.1 16.8 1134.4 Atlantic Maritime
MS‐124 Valcartier Forest Station, Quebec (QC) 46° 55ʹN 71° 32ʹW 4.5 −10.5 18.2 1139.8 Atlantic Maritime
MS‐118 Acadia Research Forest,
New Brunswick (NB)
45° 59ʹN 66° 21ʹW 5.0 −8.4 17.4 1202.7 Atlantic Maritime
MS‐117 Oromocto,
New Brunswick (NB)
45° 52ʹN 66° 24ʹW 5.4 −7.9 17.9 1152.1 Atlantic Maritime
MS‐303 Adirondack Mountains,
New York (NY)
44° 42ʹN 74°W 6.2 −6.8 18.4 1102.0 Warm Continental

2.2. Experimental design and data collection

The layout is a block design with three replications. Each block is made up of twelve 0.04 ha plots in which 100 trees were planted at a spacing of 1.8 m × 1.8 m in 10 rows of 10 trees. A total number of 3,600 trees were planted covering 0.48 ha.

In 1998, survival (%) per provenance plot was calculated, as well as 37‐year diameter at breast height (DBH, cm), height (H, m), and crown width (CW, cm) of all sampled trees. Mean values for each variable were calculated per provenance plot per block, and averaged across blocks for provenance means.

2.3. Analysis of Variance (ANOVA)

Analysis of variance (ANOVA) was used for DBH, H, CW, and survival using the General Linear Model option in SPSS Statistical software (ver. 24, IBM Corp., New York, USA), with provenance and block as fixed effects. Levene's test for homogeneity of sample variances was conducted. Analysis of variance was performed to determine the level of significance of the effect of provenance and blocking on the four tree variables. If the analysis of variance detected significant differences, the least significant difference (LSD) post hoc test was subsequently used to separate effect means.

2.4. Regression models

Statistical models were developed for 37‐year DBH, H, CW, and survival of balsam fir. Development of each model was based on the methods of Matyas and Yeatman (1992), Rehfeldt et al. (2002), Rweyongeza, Yang, et al. (2007), and Thomson and Parker (2008). Climatic variables for the period 1971‐2000 (described as climate normals) were obtained from weather station data (Environment Canada 2016; United States National Oceanic and Atmospheric Administration 2016) and used to relate provenance growth to climate at provenance origin. A total of 53 climatic variables were examined, including annual and seasonal (winter, spring, and summer) temperature‐based (18 variables, in total) and precipitation‐based variables (10); heat accumulation indices; growing degree days above 5 and 10°C (2); annual and seasonal moisture indices (8); durations above temperature (5) and precipitation thresholds (9); and a continentality index based on the difference between the warmest and coldest months in a year. The annual and seasonal moisture indices were calculated from the ratio of growing degree days >5 and 10°C to precipitation over the course of a year or in respective seasons. Values obtained were indicative of temperature levels and their effect on moisture availability, with higher values representative of areas with warm or hot summers with a potential for moisture deficits, and lower values representative of areas with cooler conditions (Rweyongeza, Dhir, et al., 2007). Based on prior visual review of scatter plots, linear regression (equation (1)) was used in assessing the relationship between CW and the climatic variables, whereas linear and quadratic regressions (equation (2)) were used in assessing the relationship between DBH, H, and survival, and the same suite of variables.

Provenance response to climate was assessed using regressions of each trait on a climatic variable at the provenance source area:

Y=β0+β1X+ε (1)
Y=β0+β1X+β2X2+ε (2)

Dependent variable Y in equations (1) and (2) is the provenance trait; independent variable X is the explanatory climatic variable for the provenance, β0, β1, and β2 are regression coefficients to be estimated, and ε is the error term for the provenance source. Based on the results of linear and quadratic regressions, climatic variables suitable for model development for balsam fir were retained, based on r 2‐values ≥.40 and p‐values <.05.

3. RESULTS

3.1. Provenance

The results show that provenance of 37‐year‐old balsam fir had a significant effect on DBH, H, and CW (< .05), but no significant effect on survival (> .05) on survival. Provenances sourced from Oromocto and NY were the best performing compared to other provenances (< .05) in terms of DBH and H. Provenances sourced from Oromoctoand QC were the best performing, compared to other provenances in terms of CW (p < .05). The best performing provenances were all sourced from locations south of the study site Table 2. Generally, provenances sourced from locations south of the study site (hereafter, lower latitude provenances), and as a result moved to a cooler location, performed better than provenances sourced from locations north of the study site (hereafter, higher latitude provenances), moved to a warmer location.

Table 2.

Mean DBH (cm), H (m), CW (cm) and survival (%) of 37‐year‐old balsam fir provenances growing in a common garden in northern New Brunswick; ±standard deviations are in parenthesis

Provenance Mean DBH (cm) Mean H (m) Mean CW (cm) Mean survival (%)
MS‐2 13.19 (±0.86) 12.09 (±0.43) 258.40 (±25.90) 76.33 (±5.86)
MS‐117 14.78 (±0.54) 12.93 (±0.05) 288.51 (±29.46) 80.33 (±5.69)
MS‐118 13.01 (±0.57) 10.91 (±0.51) 247.74 (±11.87) 76.00 (±3.46)
MS‐123 12.73 (±1.42) 10.60 (±0.78) 236.67 (±18.08) 77.33 (±3.06)
MS‐124 13.29 (±0.69) 12.29 (±0.68) 283.37 (±17.80) 78.67 (±7.02)
MS 125 11.39 (±0.64) 9.77 (±0.53) 278.47 (±5.58) 72.67 (±4.04)
MS‐126 11.13 (±0.43) 10.01 (±0.35) 246.69 (±4.07) 77.67 (±3.79)
MS‐127 12.09 (±0.75) 10.58 (±0.39) 260.37 (±26.45) 69.33 (±2.31)
MS‐130 13.15 (±0.82) 11.83 (±0.43) 216.12 (±25.73) 77.00 (±2.65)
MS‐131 11.72 (±0.48) 10.73 (±0.51) 234.34 (±7.81) 69.00 (±8.54)
MS‐133 12.90 (±0.40) 11.02 (±0.53) 269.67 (±20.74) 75.00 (±17.09)
MS‐303 14.49 (±0.44) 13.08 (±0.70) 262.56 (±31.06) 80.00 (±1.73)

3.2. Climatic variables

Annual moisture index based on GDD10 had the strongest influence on DBH (r 2 = .67) in a nonlinear relationship (for variable definition, refer to Table 4; consult Figure 1a for relationship). Spring moisture index based on GDD10 had the strongest influence on H (r 2 = .78), also in a nonlinear relationship (Figure 2a). Maximum DBH and H occurred at moderate annual and spring moisture indices based on GDD10, respectively, with lower latitude provenances sourced from Oromocto, NB, and Valcartier, QC, in the Atlantic Maritime Ecozone of Canada, and Adirondack, NY, in the Warm Continental Ecoregion of the United States, while the lowest values were obtained with higher latitude provenances sourced from Salmonier and Hawke's Bay, NF, in the Boreal Shield Ecozone of Canada. Mean minimum annual temperature had the strongest influence on CW (r 2 = .56), with values increasing linearly (Figure 3a). Crown width values increased with decreasing mean minimum annual temperature. Maximum CW was obtained with the lower latitude provenances sourced from Oromocto, NB, and Valcartier, QC, whereas the lowest CW values were obtained in the higher latitude provenances sourced from Airplane Bay, MB, and Duck Mountain, SK. The ecozone of the NB and QC provenances is as indicated earlier, and the MB and SK provenances were sourced from the Prairie Ecozone of Canada. Total precipitation had the strongest influence on survival (r 2 = .58) in a nonlinear relationship (Figure 4a). Maximum survival occurred at moderate TPPT with lower latitude provenances sourced from Oromocto, NB, and Valcartier, QC, in the Atlantic Maritime Ecozone of Canada, and Adirondack, NY, in the Warm Continental Ecoregion of the United States, whereas the lowest values were obtained with higher latitude provenances sourced from Bonne Bay, NF, and Airplane Bay, MB, in the Boreal Shield Ecozone of Canada (Table 3).

Table 4.

Climatic variables and abbreviations

Parameter Abbreviation
Mean maximum annual temperature MMAX
Mean minimum annual temperature MMIN
Mean maximum spring temperature SpMAX
Highest temperature of the warmest month HTWM
Lowest temperature of the warmest month LTWM
Mean temperature of the warmest month MTWM
Days with minimum temperature <−20°C DMIN ‐20
Days with minimum temperature <−2°C DMIN ‐2
Total precipitation TPPT
Winter precipitation WPPT
Total rainfall TR
Days with precipitation above 10 mm DPPT10
Growing degree days >10°C GDD10
Annual moisture index based on GDD10 AMI10
Spring moisture index based on GDD10 SpMI10
Summer moisture index based on GDD10 SMI10

Figure 1.

Figure 1

Diameter at breast height (cm) of 37‐year‐old balsam fir provenances in northern New Brunswick in relation to (a) annual moisture index based on GDD10, (b) mean temperature of the warmest month, and (c) GDD10 (refer to Table 4 for variable definition) at the point of origin. Lower latitude provenances are denoted by open circles, whereas higher latitude provenances are denoted by closed circles

Figure 2.

Figure 2

Tree height (m) of 37‐year‐old balsam fir provenances in northern New Brunswick in relation to (a) spring moisture index based on GDD10, (b) GDD10, and (c) the highest temperature of the warmest month at the point of origin. Lower latitude provenances are denoted by open circles, whereas higher latitude provenances are denoted by closed circles

Figure 3.

Figure 3

Crown width (cm) of 37‐year‐old balsam fir provenances in northern New Brunswick in relation to (a) the mean minimum annual temperature, (b) total rainfall, and (c) the days with minimum temperature <−2°C at the point of origin. Lower latitude provenances are denoted by open circles, whereas higher latitude provenances are denoted by closed circles

Figure 4.

Figure 4

Mean survival (%) of 37‐year‐old balsam fir provenances in northern New Brunswick in relation to (a) total precipitation, (b) the number of days with precipitation >10 mm, and (c) the number of days with temperature <−20°C at the point of origin. Lower latitude provenances are denoted by open circles, whereas higher latitude provenances are denoted by closed circles

Table 3.

Coefficients (β0, β1, β2, r 2) and p‐value from regressions of mean DBH (cm), H (m), CW (cm), and survival (%) of 37‐year‐old balsam fir in northern New Brunswick, in relation to climatic variables at the point of origin. Climatic variable abbreviations appear in Table 4

Trait Climatic variable β0 β1 β2 r 2 p
Mean DBH (cm) AMI10 9.351 9.418 −4.410 .67 .007
MTWM 4.752 0.470 .62 .002
GDD10 10.582 0.003 .60 .003
SpMAX 10.294 0.331 .56 .005
MMAX 9.042 0.432 .53 .007
Mean H (m) SpMI10 7.063 2.160 −0.197 .78 .001
GDD10 8.905 0.003 .73 .0004
HTWM 3.800 0.329 .66 .001
LTWM 4.596 0.587 .51 .009
SpMAX 8.766 0.335 .59 .003
SMI10 9.366 0.797 .50 .010
Mean CW (cm) MMIN 270.473 8.993 .56 .005
TR 209.047 0.060 .51 .009
DMIN ‐2 365.847 −0.733 .48 .013
Mean survival (%) TPPT 59.335 0.039 −0.00002 .58 .020
DPPT10 65.697 0.770 −0.012 .56 .024
DMIN ‐20 70.010 0.521 −0.008 .51 .039
WPPT 71.094 0.048 −0.0001 .50 .046

Also, the mean temperature of the warmest month, maximum spring temperature, maximum annual temperature, and GDD10 correlated fairly well with DBH. Diameter at breast height increased linearly with the mean temperature of the warmest month and GDD10 (Figure 1b,c). The spring and summer moisture indices based on GDD10, GDD10, the highest and lowest temperatures of the warmest month, and mean maximum spring temperature had good relationships with H. Tree height increased linearly with GDD10 and the highest temperature of the warmest month (Figure 2b,c). The mean minimum annual temperature, total rainfall, and days with minimum temperature <−2°C had good relationships with CW. Crown width increased with total rainfall, but decreased linearly in relation to days with minimum temperature < −2°C (Figure 3b,c). The number of days with precipitation above 10 mm, days with minimum temperature < −20°C, and winter precipitation had good relationships with survival, which were all nonlinear. Maximum survival was obtained in relation to moderate number of days with precipitation >10 mm and temperature below −20°C (Figure 4b,c).

4. DISCUSSION

The latitudinal distinction between lower and higher latitude provenances with regard to DBH, H, and CW is indicative of genotypic control of these traits arising from adaptations developed at their respective seed sources. Growing season length between spring bud‐burst and autumn leaf‐fall is well associated with latitudinal gradients (Elmore, Guinn, Minsley, & Richardson, 2012; Lechowicz, 1984; Thiel et al., 2012). Lower latitude provenances originate from warm more southerly environments with a longer growing season, characterized by earlier spring bud‐burst and later bud‐setting in fall (Davis & Shaw, 2001; Giertych & Oleksyn, 1981, 1992; Johnsen, Seiler, & Major, 1996; O'Neill & Yanchuk, 2005; Oleksyn, Zytkowiak, Karolewski, Reich, & Tjoelker, 2000; Repo, Zhang, Ryyppo, Rikala, & Vuorinen, 2000; Savva et al., 2007; Shutyaev & Giertych, 1997), whereas higher latitude provenances originate from cold northern environments with a short growing season, where metabolic activities and growth rates are limited by low temperatures and unfavorable soil conditions (Friend & Woodward, 1990; Larcher, 1980; Oleksyn, Reich, Chalupka, & Tjoelker, 1999; Oleksyn, Tjoelker, & Reich, 1992; Reich, Walters, & Ellsworth, 1992; Reich et al., 1996).

The finding of this study that provenances did not differ (> .05) significantly in terms of survival is similar to that of Rweyongeza, Yang, et al. (2007), from a study of P. contorta and P. banksiana provenances. In conifers, survival often shows genetic variation patterns that differ from those seen in growth characteristics (Andalo et al., 2005; Eriksson, Anderson, Eiche, Ifver, & Persson, 1980; Persson, 1994; Schmidtling, 1994; Wei et al., 2004). Once trees grow past a height of two meters, they develop a high capacity to buffer against climate deterioration and low mortality, and are able to cope with diverse climatic stresses during their lifetime (Kullman, 1987; Persson, 1998). However, the conservative growth pattern developed by higher latitude provenances in response to the harsh climatic conditions at their source stands may have resulted in the absence of provenance effect on survival. The adaptation of lower latitude provenances to the mild climatic conditions from which they originate results in their better growth performance from increased carbon assimilation, compared to higher latitude provenances when grown in a common garden but they can be affected by damage from late frosts, pest attacks, and disease that can cause them to incur higher mortality rates than higher latitude provenances (Campbell, 1979; Korner, 2003; Savva et al., 2007; Vitasse, Delzon, Bresson, Michalet, & Kremer, 2009; Zobel & Talbert, 1984). Higher latitude provenances have been adapted to lower winter temperatures and shorter growing seasons of colder climates as well as longer and deeper periods of dormancy they experience at their source sites compared to lower latitude provenances, enabling them to survive adverse conditions. As a result, conservative, slower growth of higher latitude provenances may be a resource allocation strategy directed at survival relative to productivity, developed in response to the climatic conditions at the provenance source stand (Lechowicz, 1984; Leinonen & Hanninen, 2002; Oleksyn, Reich, Zytkowiak, Karolewski, & Tjoelker, 2003; Schmidtling, 1994; Vitasse et al., 2009).

The results show that temperature has a stronger influence on DBH, H, and CW of balsam fir. Precipitation, in combination with the heat accumulation index (moisture index), shows an influence on DBH and H. Temperature and precipitation both had influences on survival. Several studies (Matyas & Yeatman, 1992); Schmidtling, 1994; Parker & Niejenhuis, 1996;  Matyas, 1997; Thomson et al., 2009) have similarly reported that temperature is a better determinant of variation in plant populations, compared to precipitation. The results suggest a strong adaptation of balsam fir provenances to the temperature at their seed sources. The balance between selection and gene flow is influential in local adaptation. Balsam fir, like most conifers, is monecious. However, conifers commonly cross‐pollinate because of the location of female and male reproductive structures in the upper and lower branches of the tree crown, respectively, and the flowering of such structures not coinciding precisely. This is, in addition to wind pollination, characteristic of conifer life history (Barnes, Zak, Denton, & Spurr, 1998; Frank, 1990; Pallardy, 2008). Such circumstances would facilitate gene flow among species populations and could minimize selective pressure that would engender adaptation to local conditions at the provenance sites. Adaptation to local temperature conditions, as the results show, could therefore be an indication of relatively strong directional selection in the species, which may have been facilitated by the spatial predictability of temperature with latitude (Andalo et al., 2005; Arend, Kuster, Günthardt‐Goerg, & Dobbertin, 2011; Oleksyn, Tjoelker, & Reich, 1998).

The annual moisture index based on GDD10 encompasses the growing season, during which tree diameter growth from cambial activity occurs in spring and early summer (Barnes et al., 1998). Although the lower and higher latitude provenances had comparable annual precipitation levels at their seed sources, the higher GDD10 levels at the lower latitude provenance seed sources may have contributed to adaptations in them, which resulted in earlier reactivation of cambial activity than in the higher latitude provenances. Key to cambial reactivation and growth is spring temperature and soil water availability during the growing season (Barnes et al., 1998; Deslauriers, Rossi, Anfodillo, & Saracino, 2008; Gricar, Zupancic, Cufar, & Oven, 2007; Gricar et al., 2006; Kirdyanov, Hughes, Vaganov, Schweingruber, & Silkin, 2003; Oribe, Funada, & Kubo, 2003; Oribe, Funada, Shibagaki, & Kubo, 2001). The response of H to spring moisture index based on GDD10 is indicative of the importance of spring events to height growth. Height growth commences early, often prior to the last frost, and concludes in the early part of the growing season (Baldwin, 1931; Barnes et al., 1998; Cook, 1941; Husch, 1959; Kozlowski, 1955, 1962; Kozlowski & Ward, 1957a,b; Kramer, 1943; Salminen & Jalkanen, 2005; Zimmerman & Brown, 1974). As with annual precipitation, the lower and higher latitude provenances had comparable spring precipitation levels at seed source, but the higher GDD10 values at the lower latitude provenance seed sources may also have engendered adaptations, which resulted in earlier spring budding activity, for which spring warming is an important factor (Barnes et al., 1998). Crown width is an important factor in tree growth, as the crowns of trees are the means by which they intercept and absorb solar radiation, and the location of physiological processes, such as photosynthesis, respiration, and transpiration (Honer, 1971; Grace, 1990; Wang & Jarvis, 1990; Stenberg et al., 1994; Vose et al., 1994; McCrady & Jokela, 1996, 1998; Xiao, Jokela, & White, 2003; Crecente‐Campo et al. 2009). The variation of CW among provenance sources in response to mean minimum annual temperature may be indicative of the restrictive effect of very low winter temperatures on CW (Bechtold, 2003) of the higher latitude provenances of the Prairie Ecozone, compared to the lower latitude provenances of the Atlantic Maritime Ecozone. The relationships of survival with total precipitation, the number of days with precipitation above 10 mm, and temperature below −20°C are in agreement with the findings of Rweyongeza, Dhir, et al. (2007), who reported that survival in white spruce (Picea spp.) provenances responded best to precipitation over the course of the year, and cool seasonal temperatures.

These results suggest that the response of balsam fir to climatic variation will likely not be uniform in the species, but differ based on genetic characteristics between populations located in the northern and southern parts of the species’ range. Population differences in response to climatic variation may be evident earlier in growth traits, compared to survival in balsam fir. The findings of this study will facilitate modeling in the species that is reflective of genetic variation in response to climatic conditions, and guide provenance selection for utilization in terms of productivity or resilience as well as breeding programs directed at obtaining species that possibly combine both traits.

5. CONCLUSION

This study investigated the effect of climatic variation on morphological traits of balsam fir provenances growing in a common garden in northern New Brunswick. The results showed that lower latitude provenances performed significantly better than higher latitude provenances (p < .05), with regard to DBH, H, and CW, indicative of genotypic control of these traits. The lack of a significant difference among provenances (p > .05) with regard to survival is reflective of a resource allocation strategy directed at survival relative to productivity arising from genetic adaptations in higher latitude provenances, which, although resulting in slower growth compared to the lower latitude provenances, facilitates a lowering of mortality rates under adverse conditions. Temperature had a stronger relationship with DBH, H, and CW than precipitation. Both climatic variables had some effect on survival. The relationship of temperature with DBH, H, and CW suggests strong directional selection in balsam fir that has engendered adaptation to local conditions in populations of the species along latitudinal gradients. The results suggest that the response of balsam fir to climatic variation will likely differ between populations located in the northern and southern parts of the species range. Population differences in response to climatic variation may be evident earlier in growth traits compared to survival in the species. These findings will facilitate modeling for balsam fir that is reflective of genetic variation in response to climatic conditions, and guide provenance selection for utilization and breeding programs.

CONFLICT OF INTEREST

None declared.

AUTHOR CONTRIBUTION

MEA and CPAB conceived the ideas; MEA collected the data from Natural Resources Canada, designed the methods used, analyzed the data, and led the writing of the manuscript; CPAB reviewed the drafts, made amendments to the manuscript, and gave final approval for its publication.

ACKNOWLEDGMENTS

This study was supported by funding from the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Faculty of Forestry and Environmental Management (University of New Brunswick) in the form of research assistantships. The authors thank researchers of Natural Resources Canada who set up the trial and collected the data used in this article and Ben MacLellan for help with retrieval and preparation of the climate data.

Akalusi ME, Bourque CP‐A. Effect of climatic variation on the morphological characteristics of 37‐year‐old balsam fir provenances planted in a common garden in New Brunswick, Canada. Ecol Evol. 2018;8:3208–3218. https://doi.org/10.1002/ece3.3852

REFERENCES

  1. Abrams, M. D. (1994). Genotypic and phenotypic variation as stress adaptations in temperate tree species: A review of several case studies. Tree Physiology, 14, 833–842. https://doi.org/10.1093/treephys/14.7-8-9.833 [DOI] [PubMed] [Google Scholar]
  2. Andalo, C. , Beaulieua, J. , & Bousquet, J. (2005). The impact of climate change on growth of local white spruce populations in Quebec, Canada. Forest Ecology and Management, 205, 169–182. https://doi.org/10.1016/j.foreco.2004.10.045 [Google Scholar]
  3. Anderson, J. T. , Panetta, A. M. , & Mitchell‐Olds, T. (2012). Evolutionary and ecological responses to anthropogenic climate change: Update on anthropogenic climate change. Plant Physiology, 160, 1728–1740. https://doi.org/10.1104/pp.112.206219 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Arend, M. , Kuster, T. , Günthardt‐Goerg, M. S. , & Dobbertin, M. (2011). Provenance‐specific growth responses to drought and air warming in three European oak species (Quercus robur, Q. petraea and Q. pubescens). Tree Physiology, 31, 287–297. https://doi.org/10.1093/treephys/tpr004 [DOI] [PubMed] [Google Scholar]
  5. Aspelmeier, S. , & Leuschner, C. (2004). Genotypic variation in drought response of silver birch (Betula pendula): Leaf water status and carbon gain. Tree Physiology, 24, 517–528. https://doi.org/10.1093/treephys/24.5.517 [DOI] [PubMed] [Google Scholar]
  6. Bailey, R. G. (1995). Descriptions of the ecoregions of the United States. Washington DC.: US Department of Agriculture Forest Service. [Google Scholar]
  7. Baldwin, H. I. (1931). The period of height growth in some northeastern conifers. Ecology, 12, 665–689. https://doi.org/10.2307/1929471 [Google Scholar]
  8. Barnes, B. V. , Zak, D. R. , Denton, S. R. , & Spurr, S. H. (1998). Forest ecology, 4th ed. New York: John Wiley and Sons Inc.. [Google Scholar]
  9. Bechtold, W. A. (2003). Crown‐diameter prediction models for 87 species of stand‐grown trees in the eastern United States. Southern Journal of Applied Forestry, 27, 269–278. [Google Scholar]
  10. Briffa, K. R. , Schweingruber, F. H. , Jones, P. D. , Osborn, T. J. , Harris, I. C. , Shiyatov, S. G. , … Grudd, H. (1998). Trees tell of past climates: But are they speaking less clearly today? Philosophical Transactions of The Royal Society B, Biological Sciences, 353, 65–73. https://doi.org/10.1098/rstb.1998.0191 [Google Scholar]
  11. Briffa, K. R. , Schweingruber, F. H. , Jones, P. D. , Osborn, T. J. , Shiyatov, S. G. , & Vaganov, E. A. (1998). Reduced sensitivity of recent tree‐growth to temperature at high northern latitudes. Nature, 391, 678–682. https://doi.org/10.1038/35596 [Google Scholar]
  12. Büntgen, U. , Frank, D. C. , Schmidhalter, M. , Neuwirth, B. , Seifert, M. , & Esper, J. (2006). Growth/climate response shift in a long subalpine spruce chronology. Trees, 20, 99–110. https://doi.org/10.1007/s00468-005-0017-3 [Google Scholar]
  13. Campbell, R. K. (1979). Genecology of Douglas‐fir in a watershed in the Oregon Cascades. Ecology, 60, 1036–1050. https://doi.org/10.2307/1936871 [Google Scholar]
  14. Carter, K. K. (1996). Provenance tests as indicators of growth response to climate change in 10 north temperate tree species. Canadian Journal of Forest Research, 26, 1089–1095. https://doi.org/10.1139/x26-120 [Google Scholar]
  15. Cherry, M. , & Parker, W. H. (2003). Utilization of genetically improved stock to increase carbon sequestration. Ont. For. Res. Inst. For. Res. Rep. No. 160. Sault Ste. Marie, Ontario: Ont. Min. Nat. Res. Queen's Printer for Ontario. [Google Scholar]
  16. Cook, B. B. (1941). The period of growth of some north eastern trees. Journal of Forestry, 39, 957–959. [Google Scholar]
  17. Crecente‐Campo, F. , Marshall, P. , LeMay, V. , & Dieguez‐Aranda, U. (2009). A crown profile model for Pinus radiata D. Don in northwestern Spain. Forest Ecology and Management, 257, 2370–2379. [Google Scholar]
  18. Davis, M. B. , & Shaw, R. G. (2001). Range shifts and adaptive responses to quaternary climate change. Science, 292, 673–679. https://doi.org/10.1126/science.292.5517.673 [DOI] [PubMed] [Google Scholar]
  19. Deslauriers, A. , Rossi, S. , Anfodillo, T. , & Saracino, A. (2008). Cambial phenology, wood formation and temperature thresholds in two contrasting years at high altitude in southern Italy. Tree Physiology, 28, 863–871. https://doi.org/10.1093/treephys/28.6.863 [DOI] [PubMed] [Google Scholar]
  20. Donselman, H. M. , & Flint, H. L. (1982). Genecology of eastern redbud (Cercis canadensis). Ecology, 63, 962–971. https://doi.org/10.2307/1937236 [Google Scholar]
  21. Ecological Stratification Working Group . (1996). A national ecological framework for Canada. Ottawa: Agriculture and Agri‐Food Canada & Environment Canada. [Google Scholar]
  22. Elmore, A. J. , Guinn, S. M. , Minsley, B. J. , & Richardson, A. D. (2012). Landscape controls on the timing of spring, autumn, and growing season length in mid‐Atlantic forests. Global Change Biology, 18, 656–674. https://doi.org/10.1111/j.1365-2486.2011.02521.x [Google Scholar]
  23. Environment Canada . (2016). http://climate.weather.gc.ca/climate_normals/index_e.html.
  24. Eriksson, G. , Anderson, S. , Eiche, V. , Ifver, J. , & Persson, A. (1980). Severity index and transfer effects on survival and volume production of Pinus sylvestris in northern Sweden. Studia Forestalia Suecica, 156, 1–32. [Google Scholar]
  25. Frank, R. M. (1990). Abies balsamea. Silvics of North America: 1. Conifers; 2. Hardwoods. Agriculture Hand book 654, Vol. 1 (Tech. Cords. R. M. Burns & B.H. Honkala). Washington, DC.: U.S. Department of Agriculture, Forest Service; 877 p. [Google Scholar]
  26. Friend, A. D. , & Woodward, F. I. (1990). Evolutionary and ecophysiological responses of mountain plants to the growing season environment. Advances in Ecological Research, 20, 59–120. https://doi.org/10.1016/S0065-2504(08)60053-7 [Google Scholar]
  27. Geber, M. A. , & Dawson, T. E. (1993). Evolutionary responses of plants to global change In Kareiva P. M., Kingsolver J. G., & Huey R. B. (Eds.), Biotic interactions and global change (pp. 179–197). Sunderland, MA: Sinauer Associates Inc. [Google Scholar]
  28. Giertych, M. , & Oleksyn, J. (1981). Summary of results in Scots pine (Pinus sylvestris L.) volume production in Ogievskij's pre‐revolutionary Russian provenance experiments. Silvae Genetica, 30, 56–74. [Google Scholar]
  29. Giertych, M. , & Oleksyn, J. (1992). Studies on genetic variation in Scots pine (Pinus sylvestris L.) coordinated by IUFRO. Silvae Genetica, 41, 133–143. [Google Scholar]
  30. Grace, J. C. (1990). Modeling the interception of solar radiation energy and net photosynthesis In Dixon R. K., & Last F. T. (Eds.), Process modeling of forest growth response to environmental stress (pp. 142–158). Portland: Timber Press. [Google Scholar]
  31. Gricar, J. , Zupancic, M. , Cufar, K. , Koch, G. , Schmitt, U. , & Oven, P. (2006). Effect of local heating and Cooling on cambial activity and cell differentiation in the stem of Norway spruce (Picea abies). Annals of Botany, 97, 943–951. https://doi.org/10.1093/aob/mcl050 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Gricar, J. , Zupancic, M. , Cufar, K. , & Oven, P. (2007). Regular cambial activity and xylem and phloem formation in locally heated and cooled stem portions of Norway spruce. Wood Science and Technology, 41, 463–475. https://doi.org/10.1007/s00226-006-0109-2 [Google Scholar]
  33. Honer, T. G. (1971). Crown shape in open‐ and forest‐grown balsam fir and black spruce. Canadian Journal Forest Research, 1, 203–207. https://doi.org/10.1139/x71-027 [Google Scholar]
  34. Husch, B. (1959). Height growth of white pine in relation to selected environmental factors on four sites in southwestern New Hampshire. New Hampshire Agricultural Experimental Station, University of New Hampshire. Technical Bulletin 100. [Google Scholar]
  35. Intergovernmental Panel on Climate Change (2007). Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change In Parry M., Canziani O., Palutikof J., Van der Linden P., & Hanson C. (Eds.), Climate change: 2007: impacts, adaptation and vulnerability (976 p). New York: Cambridge University Press. [Google Scholar]
  36. Iverson, L. R. , & Prasad, A. M. (1998). Predicting abundance of 80 tree species following climate change in the eastern United States. Ecological Monographs, 68, 465–485. https://doi.org/10.1890/0012-9615(1998)068[0465:PAOTSF]2.0.CO;2 [Google Scholar]
  37. Johnsen, K. H. , Seiler, J. R. , & Major, J. E. (1996). Growth, shoot phenology and physiology of diverse seed sources of black spruce: II. 23‐year‐old field trees. Tree Physiology, 16, 375–380. https://doi.org/10.1093/treephys/16.3.375 [DOI] [PubMed] [Google Scholar]
  38. Kirdyanov, A. , Hughes, M. , Vaganov, E. , Schweingruber, F. , & Silkin, P. (2003). The importance of early summer temperature and date of snow melt for tree growth in the Siberian Subarctic. Trees, 17, 61–69. https://doi.org/10.1007/s00468-002-0209-z [Google Scholar]
  39. Korner, C. (2003). Alpine plant life: Functional plant ecology of high mountain ecosystems. Berlin: Springer‐Verlag; https://doi.org/10.1007/978-3-642-18970-8 [Google Scholar]
  40. Kozlowski, T. T. (1955). Tree growth, action and interaction of soil and other factors. Journal of Forestry, 53, 508–512. [Google Scholar]
  41. Kozlowski, T. T. (1962). Tree growth. New York: The Ronald Press Company. [Google Scholar]
  42. Kozlowski, T. T. , & Ward, R. C. (1957a). Seasonal height growth of conifers. Forest Science, 3, 61–66. [Google Scholar]
  43. Kozlowski, T. T. , & Ward, R. C. (1957b). Seasonal height growth of deciduous trees. Forest Science, 3, 168–174. [Google Scholar]
  44. Kramer, P. J. (1943). Amount and duration of growth of various species of tree seedlings. Plant Physiology, 18, 239–251. https://doi.org/10.1104/pp.18.2.239 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Kullman, L. (1987). Long‐term dynamics of high altitude population of Pinus sylvestris L. in the Swedish Scandes. Journal of Biogeography, 14, 1–8. https://doi.org/10.2307/2844782 [Google Scholar]
  46. Larcher, W. (1980). Physiological plant ecology. New York: Springer‐ Verlag; https://doi.org/10.1007/978-3-642-96545-6 [Google Scholar]
  47. Lechowicz, M. J. (1984). Why do temperate deciduous trees leaf out at different times? Adaptation and ecology of forest communities. The American Naturalist, 124(6), 821–842. https://doi.org/10.1086/284319 [Google Scholar]
  48. Leinonen, I. , & Hanninen, H. (2002). Adaptation of the timing of bud burst of Norway spruce to temperate and boreal climates. Silva Fennica, 36, 695–701. [Google Scholar]
  49. Lemmen D. S., Warren F. J., Lacroix J., & Bush E. (Eds.) (2008). Impacts to adaptation: Canada in a changing climate 2007 (448 p). Ottawa, ON: Government of Canada. [Google Scholar]
  50. MacGillivray, H. G. (1963). Progress Report, Balsam fir provenance planting, 1956 sowing. Project M 95; Related studies; Petawawa experiments number 63, number 175 and number 176. Department of Forestry, Forest Research Branch, Canada.
  51. Marchin, R. M. , Sage, E. L. , & Ward, J. K. (2008). Population‐level variation of Fraxinus americana (white ash) is influenced by precipitation differences across the native range. Tree Physiology, 28, 151–159. https://doi.org/10.1093/treephys/28.1.151 [DOI] [PubMed] [Google Scholar]
  52. Matyas, C. (1994). Modeling climate change effects with provenance test data. Tree Physiology, 14, 797–804. https://doi.org/10.1093/treephys/14.7-8-9.797 [DOI] [PubMed] [Google Scholar]
  53. Matyas, C. (1996). Climatic adaptation of trees: Rediscovering provenance tests. Euphytica, 92, 45–54. https://doi.org/10.1007/BF00022827 [Google Scholar]
  54. Matyas, C. (1997). Effects of environmental change on the productivity of tree populations In Matyas C. (Ed.), Perspectives of forest genetics and tree breeding in a changing world (pp. 109–121). Vienna: International Union of Forestry Research Organizations. [Google Scholar]
  55. Matyas, C. (1999). Forest genetics and sustainability. Dordrecht, Boston: Kluwer Academic Publishers; https://doi.org/10.1007/978-94-017-1576-8 [Google Scholar]
  56. Matyas, C. , & Yeatman, W. (1992). Effect of geographical transfer on growth and survival of jack pine (Pinus banksiana Lamb.) populations. Silvae Genetica, 41, 370–375. [Google Scholar]
  57. McCrady, R. L. , & Jokela, E. J. (1996). Growth phenology and crown structure of selected loblolly pine families planted at two spacings. Forest Science, 42, 46–57. [Google Scholar]
  58. McCrady, R. L. , & Jokela, E. J. (1998). Canopy dynamics, light interception, and radiation use efficiency of selected loblolly pine families. Forest Science, 44, 64–72. [Google Scholar]
  59. Montesinos‐Navarro, A. , Wig, J. , Xavier Pico, F. , & Tonsor, S. J. (2011). Arabidopsis thaliana populations show clinal variation in a climatic gradient associated with altitude. New Phytologist, 189, 282–294. https://doi.org/10.1111/j.1469-8137.2010.03479.x [DOI] [PubMed] [Google Scholar]
  60. Oleksyn, J. , Reich, P. B. , Chalupka, W. , & Tjoelker, M. G. (1999). Differential above‐ and below‐ground biomass accumulation of European Pinus sylvestris populations in a 12‐year‐old Provenance experiment. Scandinavian Journal of Forest Research, 14, 7–17. https://doi.org/10.1080/02827589908540804 [Google Scholar]
  61. Oleksyn, J. , Reich, P. B. , Zytkowiak, R. , Karolewski, P. , & Tjoelker, M. G. (2003). Nutrient conservation increases with latitude of origin in European Pinus sylvestris populations. Oecologia, 136, 220–235. https://doi.org/10.1007/s00442-003-1265-9 [DOI] [PubMed] [Google Scholar]
  62. Oleksyn, J. , Tjoelker, M. G. , & Reich, P. B. (1992). Whole plant CO, exchange of seedlings of two Pinus sylvestris L. provenances grown under simulated photoperiodic conditions of 50” and 60” N. Trees, 6, 225–231. [Google Scholar]
  63. Oleksyn, J. , Tjoelker, M. G. , & Reich, P. B. (1998). Adaptation to changing environment in Scots pine populations across a latitudinal gradient. Silva Fennica, 32, 129–140. [Google Scholar]
  64. Oleksyn, J. , Zytkowiak, R. , Karolewski, P. , Reich, P. B. , & Tjoelker, M. G. (2000). Genetic and environmental control of seasonal carbohydrate dynamics in trees of diverse Pinus sylvestris populations. Tree Physiology, 20, 837–847. https://doi.org/10.1093/treephys/20.12.837 [DOI] [PubMed] [Google Scholar]
  65. O'Neill, G. A. , & Nigh, G. (2011). Linking population genetics and tree height growth models to predict impacts of climate change on forest production. Global Change Biology, 17, 3208–3217. https://doi.org/10.1111/j.1365-2486.2011.02467.x [Google Scholar]
  66. O'Neill, G. , & Yanchuk, A. (2005). Climate change and forest genetics. Summary of the 29th Biennial Meeting of the Canadian Tree Improvement Association and the Western Forest Genetics Association, Kelowna, BC, July 27–29, 2004. Forestry Chronicle, 81, 18–19. [Google Scholar]
  67. Oribe, Y. , Funada, R. , & Kubo, T. (2003). Relationship between cambial activity, cell differentiation and the localization of starch in storage tissues around the cambium in locally heated stem of Abies sachalinensis (Schmidt) Masters. Trees, 17, 185–192. [Google Scholar]
  68. Oribe, Y. , Funada, R. , Shibagaki, M. , & Kubo, T. (2001). Cambial reactivation in locally heated stems of Evergreen conifer Abies sachalinensis (Schmidt) Masters. Planta, 212, 684–691. https://doi.org/10.1007/s004250000430 [DOI] [PubMed] [Google Scholar]
  69. Pallardy, S. G. (2008). Physiology of woody plants, 3rd ed. Massachusetts: Elsevier Inc.. [Google Scholar]
  70. Palmroth, S. , Berninger, F. , & Nikinmaa, E. (1999). Structural adaptation rather than water conservation was observed in Scots pine over a range of wet to dry climates. Oecologia, 121, 302–309. https://doi.org/10.1007/s004420050932 [DOI] [PubMed] [Google Scholar]
  71. Parker, W. H. , & vanNiejenhuis, A. (1996). Seed zone delineation for jack pine in the former Northwest Region of Ontario using short‐term testing and geographic information systems. Tech. Rep. NODA/NFP TR‐35. Natural Resources Canada, Canadian Forest Service, Great Lakes Forestry Centre, Sault Ste. Marie, Ont.
  72. Persson, B. (1994). Effects of provenance transfer on survival in nine experimental series with Pinus sylvestris (L). in northern Sweden. Scandinavian Journal of Forest Research, 9, 275–287. https://doi.org/10.1080/02827589409382841 [Google Scholar]
  73. Persson, B. (1998). Will climate change affect the optimal choice of Pinus sylvestris provenances? Silva Fennica, 32, 121–128. [Google Scholar]
  74. Rehfeldt, G. E. (2004). Interspecific and intraspecific variation in Picea engelmannii and its congeneric cohorts: biosystematics, genecology, and climate change. USDA For. Serv. Gen. Tech. Rep. RMRS GTR‐134.
  75. Rehfeldt, G. E. , Tchebakova, N. M. , & Barnhardt, L. K. (1999). Efficacy of climate transfer functions: Introduction of Eurasian populations of Larix into Alberta. Canadian Journal of Forest Research, 29, 1660–1668. https://doi.org/10.1139/x99-143 [Google Scholar]
  76. Rehfeldt, G. E. , Tchebakova, N. M. , Parfenova, Y. I. , Wykoff, W. R. , Kuzmina, N. A. , & Milyutin, L. I. (2002). Intraspecific responses to climate change in Pinus sylvestris . Global Change Biology, 8, 912–929. https://doi.org/10.1046/j.1365-2486.2002.00516.x [Google Scholar]
  77. Reich, P. B. , Oleksyn, J. , & Tjoelker, M. G. (1996). Needle respiration and nitrogen concentration in Scots pine populations from a broad latitudinal range: A common garden test with field‐grown trees. Functional Ecology, 10, 768–776. https://doi.org/10.2307/2390512 [Google Scholar]
  78. Reich, P. B. , Walters, M. B. , & Ellsworth, D. S. (1992). Leaf lifespan in relation to leaf, plant, and stand characteristics among diverse ecosystems. Ecological Monograph, 62, 365–392. https://doi.org/10.2307/2937116 [Google Scholar]
  79. Repo, T. , Zhang, G. , Ryyppo, R. , Rikala, R. , & Vuorinen, M. (2000). The relation between growth cessation and frost hardening in Scots pines of different origins. Trees, 14, 456–464. https://doi.org/10.1007/s004680000059 [Google Scholar]
  80. Rweyongeza, D. M. , Dhir, N. K. , Barnhardt, L. K. , Hansen, C. , & Yang, R. (2007). Population differentiation of the lodgepole pine (Pinus contorta) and jack pine (Pinus banksiana) complex in Alberta: Growth, survival, and responses to climate. Canadian Journal of Botany, 85, 545–556. https://doi.org/10.1139/B07-053 [Google Scholar]
  81. Rweyongeza, D. M. , Yang, R.‐C. , Dhir, N. K. , Barnhardt, L. K. , & Hansen, C. (2007). Genetic variation and climatic impacts on survival and growth of white spruce in Alberta, Canada. Silvae Genetica, 56, 117–127. [Google Scholar]
  82. Salminen, H. , & Jalkanen, R. (2005). Modelling the effect of temperature on height increment of Scots pine at high latitudes. Silva Fennica, 39, 497–508. [Google Scholar]
  83. Savva, Y. , Bergeron, Y. , Denneler, B. , Koubaa, A. , & Tremblay, F. (2008). Effect of interannual climate variations on radial growth of jack pine provenances in Petawawa, Ontario. Canadian Journal of Forest Research, 38, 619–630. https://doi.org/10.1139/X07-178 [Google Scholar]
  84. Savva, Y. , Denneler, B. , Koubaa, A. , Tremblay, F. , & Tjoelker, M. G. (2007). Seed transfer and climate change effects on radial growth of jack pine populations in a common garden in Petawawa, Ontario, Canada. Forest Ecology and Management, 243, 636–647. https://doi.org/10.1016/j.foreco.2007.01.073 [Google Scholar]
  85. Saxe, H. , Cannell, M. G. R. , Johnsen, B. , Ryan, M. G. , & Vourlitis, G. (2001). Tree and forest functioning in response to global warming. New Phytologist, 149, 369–399. [DOI] [PubMed] [Google Scholar]
  86. Schmidtling, R. C. (1994). Use of provenance tests to predict response to climatic change: Loblolly pine and Norway spruce. Tree Physiology, 14, 805–817. https://doi.org/10.1093/treephys/14.7-8-9.805 [DOI] [PubMed] [Google Scholar]
  87. Schuler, T. M. (1994). Survival and growth of white ash families and provenances 15 years after establishment in West Virginia. USDA Forest Service Research Paper, NE‐684.
  88. Shutyaev, A. M. , & Giertych, M. (1997). Height growth variation in a comprehensive Eurasian provenance experiment of (Pinus sylvestris L.). Silvae Genetica, 46, 332–349. [Google Scholar]
  89. Solberg, B. O. , Hofgaard, A. , & Hytteborn, H. (2002). Shifts in radial growth responses of coastal Picea abies induced by climatic change during the 20th century, central Norway. Ecoscience, 9, 79–88. https://doi.org/10.1080/11956860.2002.11682693 [Google Scholar]
  90. Stenberg, P. , Kuuluvainen, T. , Kellomaki, S. , Grace, J. , Jokela, E. J. , & Gholz, H. L. (1994). Crown structure, light interception and productivity of pine trees and stands. Environmental constraints on the structure and productivity of pine forest ecosystems: A comparative analysis. (eds H.L. Gholz, S. Linder, & R.E. McMurtrie). Ecological Bulletins, 43, 20–34. [Google Scholar]
  91. Thiel, D. , Nagy, L. , Beierkuhnlein, C. , Huber, G. , Jentsch, A. , Konnert, M. , & Kreyling, J. (2012). Uniform drought and warming responses in Pinus nigra provenances despite specific overall performances. Forest Ecology and Management, 270, 200–208. https://doi.org/10.1016/j.foreco.2012.01.034 [Google Scholar]
  92. Thomson, A. M. , & Parker, W. H. (2008). Boreal forest provenance tests used to predict optimal growth and response to climate change. 1. Jack pine. Canadian Journal of Forest Research, 38, 157–170. https://doi.org/10.1139/X07-122 [Google Scholar]
  93. Thomson, A. M. , Riddell, C. L. , & Parker, W. H. (2009). Boreal forest provenance tests used to predict optimal growth and response to climate change: 2. Black spruce. Canadian Journal of Forest Research, 39, 143–153. https://doi.org/10.1139/X08-167 [Google Scholar]
  94. Tjoelker, M. G. , Oleksyn, J. , Reich, P. B. , & Zytkowiak, R. (2008). Coupling of respiration, nitrogen, and sugars underlies convergent temperature acclimation in Pinus banksiana across wide‐ranging sites and populations. Global Change Biology, 14, 782–797. https://doi.org/10.1111/j.1365-2486.2008.01548.x [Google Scholar]
  95. United States National Oceanic and Atmospheric Administration . (2016). Climatography of the United States Number 81: Monthly station normals of temperature, precipitation, and heating and cooling degree days (1971‐2000). https://www.ncdc.noaa.gov/climatenormals/clim81/NYnorm.pdf.
  96. Vitasse, Y. , Delzon, S. , Bresson, C. C. , Michalet, R. , & Kremer, A. (2009). Altitudinal differentiation in growth and phenology among populations of temperate‐zone tree species growing in a common garden. Canadian Journal of Forest Research, 39, 1259–1269. https://doi.org/10.1139/X09-054 [Google Scholar]
  97. Vose, J. M. , Dougherty, P. M. , Long, J. N. , Smith, F. W. , Gholz, H. L. , & Curran, P. J. (1994). Factors influencing the amount and distribution of leaf area of pine stands. Ecological Bulletins, 43, 102–114. [Google Scholar]
  98. Wang, Y. P. , & Jarvis, P. G. (1990). Influence of crown structural properties on PAR absorption, photosynthesis, and transpiration in Sitka spruce: An application of a model (MAESTRO). Tree Physiology, 7, 297–316. https://doi.org/10.1093/treephys/7.1-2-3-4.297 [DOI] [PubMed] [Google Scholar]
  99. Warren, F. J. , & Lemmen, D. S. (Eds.). (2014). Canada in a changing climate: Sector perspectives on impacts and adaptation (286 p). Ottawa: Government of Canada. [Google Scholar]
  100. Wei, R. , Han, S. , Dhir, N. K. , & Yeh, F. C. (2004). Population variation in growth and 15‐year‐old shoot elongation along geographic and climatic gradients in black spruce in Alberta. Canadian Journal of Forest Research, 34, 1691–1702. https://doi.org/10.1139/x04-050 [Google Scholar]
  101. Wilson, R. , & Elling, W. (2004). Temporal instability in tree‐growth/climate response in the Lower Bavarian Forest region: Implications for dendroclimatic reconstruction. Trees, 18, 19–28. https://doi.org/10.1007/s00468-003-0273-z [Google Scholar]
  102. Woodward, F. I. (1987). Climate and plant distribution. London: Cambridge University Press. [Google Scholar]
  103. Xiao, Y. , Jokela, E. J. , & White, T. L. (2003). Species differences in crown structure and growth performance of juvenile loblolly and slash pine. Forest Ecology and Management, 174, 295–313. https://doi.org/10.1016/S0378-1127(02)00038-5 [Google Scholar]
  104. Zimmerman, M. H. , & Brown, C. L. (1974). Trees: structure and function, 2nd ed. New York: Springer‐Verlag. [Google Scholar]
  105. Zobel, B. J. , & Talbert, J. T. (1984). Applied tree improvement. New York: John Wiley and Sons. [Google Scholar]

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