cold acclimation in populations of pinus contorta from the northern rocky mountains

Cold Acclimation in Populations of Pinus contorta from the Northern Rocky MountainsAuthor(s): Gerald E. RehfeldtSource: Botanical Gazette, Vol. 141, No. 4 (Dec., 1980), pp. 458-463Published by: The University of Chicago PressStable URL: http://www.jstor.org/stable/2474610 .

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BOT. GAZ. 141(4):458-463. 1980. Copyright is not claimed for this article.

COLD ACCLIMATION IN POPULATIONS OF PINUS CONTORTA FROM

THE NORTHERN ROCKY MOUNTAINS

GERALD E. REHFELDT1

Intermountain Forest and Range Experiment Station, Forest Service, U.S. Department of Agriculture, Ogden, Utah 84401

Freezing tests were conducted to follow cold acclimation in seedlings representing 30 populations of Pinus contorta from the northern Rocky Mountains. For each of 12 dates from August to November, leaves from 2-yr-old seedlings growing in a common environment were frozen at four test temperatures. Injury from freezing was scored primarily by tissue discoloration. Hardiness of populations developed in a slow and uniform pattern. Mean differences in the hardiness of populations were readily detected throughout acclimation, and the relative ranking of populations for hardiness remained essentially constant. Elevation and geographic region of the seed origin accounted for 78% of the variance in hardiness among populations.

Introduction Geographic races of numerous woody plants ex-

hibit differential patterns of cold acclimation in common environments. Variation in cold acclimation separates geographic races of Cornus stolonifera (SMITHBERG and WEISER 1968), Liquidambar styraciflua (WILLIAMs and MCMILLAN 1971), Quercus rubra (FLINT 1972), and Abies grandis (LARSEN 1978b). In Pseudotsuga menziesii, differential patterns of cold acclimation not only separate the coastal variety (P. m. var. menziesii) from the Rocky Mountain variety (P. m. var. glauca) (REHFELDT 1977) but even dis- tinguish populations within the two varieties (LAR- SEN 1978a; REHFELDT 1979b).

In the heterogeneous environments of the northern Rocky Mountains, freezing temperatures can occur during any month; temperatures below -40 C are not rare. Variation in cold acclimation among populations reflects differential adaptations to cold environments. This paper investigates variation in cold acclimation among populations of lodgepole pine (Pinus contorta var. latifolia) from the northern Rockies. Since this study assesses ecological adaptations of populations, it is basic to successful practical programs of tree improvement and artificial re- forestation.

Within the study region (fig. 1), lodgepole pine is ubiquitous. The species is seral on a range of sites from all but the driest habitats at low elevations to the coldest habitats near upper timberline (DAUBEN- MIRE and DAUBENMIRE 1968; PFISTER et al. 1977; STEELE et al., in press). Yet, ubiquity occurs in a region of climatic and physiognomic diversity. East of the Continental Divide the climate is pronounced- ly continental, precipitation is low, and valley floors are at relatively high elevations. For Idaho and western Montana, a climate that has considerable maritime influence on the northwest gradually

1 Plant geneticist, Forestry Sciences Laboratory, Moscow, Idaho 83843.

Manuscript received March 1980; revised manuscript received June 1980.

changes toward the continental on the east and southeast; precipitation tends to decrease; and the elevation of valley floors tends to increase along the climatic gradient. Consequently, the region is readily divided into four provinces that tend to be distinct geographically, climatically, physiognomically, and ecologically. The Continental Divide borders the central Montana province; the crests of the Cabinet and Bitterroot Mountains generally separate northern Idaho and western Montana, and the Salmon River roughly separates southern and northern Idaho.

Material and methods Cold acclimation was studied in 2-yr-old seedlings

from 30 populations of lodgepole pine (fig. 1). Popu- lations were selected to represent the elevational and geographic distribution of the species within the forested lands of the northern Rocky Mountains. Each population was represented by about 50 seedlings growing in plastic containers (150 cm3) in a shadehouse at Moscow, Idaho.

Freezing tests determined levels of cold hardiness of each population on 12 dates between mid-August and early November 1979. These tests generally followed the procedures outlined by LEVITT (1972). At each sampling date, four sets of 10 leaves were plucked from the upper portion of the current shoot of seedlings from each population. Leaves in each set were moistened and packaged in plastic bags. Each set contained leaves from 10 different seedlings; the same group of seedlings was not represented in more than one set.

Sets of leaves were stored overnight at 3 C. The following morning, plastic bags were suspended in a freezing chamber equipped with two fans for circu- lation. Leaves were frozen at the rate of 5 C/h, and one set of leaves was removed at each of four test temperatures. Test temperatures for a given date were arbitrarily chosen and spanned a range of 5- 10 C. For example, test temperatures selected for August 15 ranged from -8 to -13 C; those for September 24, from -14 to -20 C; and those for

458



REHFELDT-PINUS CONTORTA 459

November 30, from -30 to -40 C. Leaves were removed from the freezer according to remote sens- ing of internal air temperatures, thawed at 2 C for 24 h, and placed on a shaded greenhouse bench for 2 days.

Injury from freezing was scored primarily by tissue discoloration, but as seedlings of lodgepole pine harden, a color change occurs in some leaves similar to the expression of freezing injuries. Conse- quently, for sampling dates in late autumn, injury to leaves was also scored according to flaccidity. For

each population, the number of leaves exhibiting injury was recorded at each test temperature for all sampling dates.

Hardiness of plant tissues is commonly expressed as the temperature associated with 50% injury (LEVITT 1972). Accordingly, cold acclimation of all seedlings was depicted by the temperature associated with injury to 50% of the leaves sampled at each date. However, hardiness of individual populations could not be similarly described because many populations suffered either more or less than 50% damage

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FIG. 1.-Location of populations at the indicated elevations (m)



460 BOTANICAL GAZETTE [DECEMBER

at all test temperatures for given dates. Consequent- ly, an absolute value reflecting hardiness of populations at each sampling date could not be derived directly from the data. Only relative differences in hardiness could be assessed from the percentage of damage to populations according to test temperatures and sampling dates.

Statistical analyses were made (1) to determine the extent of population differentiation at each sampling date, (2) to assess possible interactions of cold acclimation of populations with the weather at Moscow, (3) to compare relative hardiness among populations, and (4) to relate variation in relative hardiness of populations to geographic and physiognomic criteria of the seed source.

To determine if the observed differences in injury to populations were real, analyses of variance were made for each sampling date according to a model of random effects (STEELE and TORRIE 1960): Yij = A + pi + tj + gij, where Yij = the percentage of injury (arcsin V/X) to population i at temperature j, = overall mean; pi = effects of population i;

tj= effects of temperature j; and gij = interaction of population i in temperature j.

Correlation coefficients of population injury at successive sampling dates were calculated to determine whether populations were acclimating in con- trasting patterns. These analyses involved the mean percentage of damage to populations from the four test temperatures at each sampling date.

Tolerance of individual populations to freezing was compared in regression analyses that were made for each population according to the logistic model. This model is suitable for proportional data (JOHN- SON and KOTZ 1970): Yij = 1/(1 + be-rx), represented by the linear model: ln [(1/Yij) -1] = -rXj + ln b, where Yij = proportion of leaves injured for population i in treatment j; Xi = index of freezing severity = percentage of leaves from all populations injured in freezing treatment j; b = (l/yo) - 1, where yo is the predicted damage if no freezing treatment is applied (Xj = 0); and r = rate of increase in damage associated with an increase in severity index.

Finally, values of population injury predicted from logistic models at a freezing severity index of 50% (half of the leaves from all populations exhibited injury) were used to relate variation in freezing tolerance to geographic and ecologic conditions of the seed source according to the general model: Y50% = bo + b1Xii + b2X2i + . . . + bX where

= predicted damage at freezing severity of 50% for population i; X1i = meters elevation of population i; X2i = degrees latitude of population i; XU = degrees longitude of population i; and X4i to X7i = constant terms (values of 0 or 1) that code geographic regions: Idaho north of the Salmon River, Idaho south of the Salmon River, Montana

west of the Continental Divide, and Montana east of the Continental Divide, respectively.

To select a model best representing the data, several regression analyses were made with different combinations of independent variables. For models involving constant terms, effects of one geographic region were included within the intercept (bo). Thus, regression coefficients for the remaining constant terms reflect deviations from the mean value of that geographic region represented by bo.

Results Cold acclimation proceeded slowly but uniformly

(fig. 2). Hardiness typically develops in association with the minimum temperature (LEVITT 1972), and tolerance to extreme cold ordinarily occurs after a frost (WEISER 1970). Thus, the observed pattern of acclimation undoubtedly was accentuated by the late frost at Moscow in 1979. Moreover, it is likely that hardiness was increasing rapidly during the final sampling date on November 6 because fully hardened leaves of lodgepole pine are not injured at -80 C (SAKAI and WEISER 1973).

Results of analyses of variance for assessing differences in hardiness among populations at each sampling date are presented as intraclass correlation coefficients (table 1). These coefficients were calculated from the components expected in each mean square under the model of random effects. They reflect the proportion of the total variance attribut- able to each source of variation. Values of F for main effects of populations and test temperatures were

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-25 *

-30 * *

-35 - *

-40 -

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15 25 5 1014 24 2 9 16 22 30 6 AUG. SEPT. OCT. NOV.

MONTH AND DATE

FIG. 2.-Development of hardiness (bottom) in relation to daily minimum temperatures (top). Stars denote the temperature associated with injury to 50% of the leaves at each sampling date.



1980] REHFELDT-PINUS CONTORTA 461

statistically significant (5% level) for all sampling dates. Significant effects for test temperatures illustrate percentages of injury that ranged from near zero to almost 100 for test temperatures at all but two sampling dates. On October 2 and 22, the warm- est test temperatures induced only 35% damage; thus, relatively little variance could be attributed to test temperatures (table 1).

Analyses of variance also indicate mean differences in hardiness among populations at all sampling dates. Yet main effects of populations accounted for little variance (< 10%) in August and November btut accounted for 25%-57% of the variance in September and October (table 1). Thus, populations were relatively equal in hardiness in August, differed greatly during initial stages of acclimation in Septem- ber and October, and reached relatively constant levels in early November when cold tolerance was high.

Since the analyses of variance suggested that mean differences in the hardiness of populations did not remain constant throughout acclimation, a further assessment of this interaction was made by correlation analyses. The correlation matrix of mean per-

TABLE 1

INTRACLASS CORRELATION COEFFICIENTS DERIVED FROM ANALYSES OF VARIANCE OF PERCENTAGE OF INJURY

TO POPULATIONS AT EACH SAMPLING DATE

SOURCE OF VARIANC.E

SAMPLING DATE Populations Temperatures Interaction

August 15 ............ .03 .92 .05 August 25 ............ .11 .65 .24 September 5 .......... .25 .53 .22 September 10 ......... .42 .31 .27 September 14 ......... .43 .31 .25 September 24 ......... .37 .39 .24 October 2 ............ .56 .24 .20 October 9 ............ .34 .43 .24 October 16 ........... .25 .56 .19 October 22 ......... .57 .16 .27 October 30 ........... .33 .52 .14 November 6 .......... .03 .93 .04

centage of injury to populations at the various sampling dates contains simple correlation coefficients (table 2), all of which are statistically significant (5%70 level or less). The lowest coefficients in- volve the August and November sampling dates when mean differences among populations were the most difficult to detect (table 1). During September and October when variation among populations was the greatest, correlation coefficients were excep- tionally high. Thus, the relative ranking of populations according to percentage of injury remained essentially constant throughout acclimation. Differ- ences in pattern of acclimation among populations (interaction of population hardiness and sampling date) arise because absolute differences in population hardiness fluctuated between sampling dates while relative rankings of populations remained constant.

To assess differences in hardiness of populations statistically, data on percentage of injury were fitted to the logistic model. Separate regressions were made for each population. Regressions of freezing tolerance were statistically significant (1% level) for all populations and accounted for an average of 73% of the variance. Response curves for five populations illustrate the variety of observed responses to freezing severity (fig. 3); each curve differs significantly (5% level) for either r or b in the regression equation. If the freezing treatment (regardless of sampling date) was sufficiently severe to damage 40% of the leaves from all populations (fig. 3), damage to only 3%o of the leaves representing the south Idaho population from 2,600 m altitude would have been expected. Damage to 841% of the leaves of the north Idaho population from 900 m is predicted from the same freezing severity. Results of logistic analyses indicate tremendous population differentiation for freezing injury and, consequently, for hardiness.

The response curves (fig. 3) were calculated from the percentage of injury at all test temperatures and sampling dates. Because hardiness of populations differed little for the first two and last sampling dates, data from these three dates may have pro-

TABLE 2

CORRELATION MATRIX OF MEAN PERCENTAGE OF DAMAGE TO POPULATIONS AT VARIOUS SAMPLING DATES

Sampling date 1 2 3 4 5 6 7 8 9 10 11 12

1 August 15..... ... .48 .54 .71 .63 .68 .60 .57 .36 .51 .53 .39 2 August 25.... . ... .64 .68 .76 .63 .60 .53 .51 .41 .49 .49 3 September 5 ... ... .85 .81 .81 .90 .72 .71 .73 .74 .70 4 September 10.. .86 .84 .85 .81 .73 .71 .80 .66 5 September 14.. ... .83 .87 . 77 .78 .70 .85 .71 6 September 24 .78 .80 78 .81 .79 .69 7 October 2 ..... ... .73 .71 .66 .80 .75 8 October 9 ........ .82 .87 .85 .65 9 October 16 .... ... .81 .88 .71

10 October 22 ... ... .85 .69 11 October 30.. .. ... .75 12 November 6...



462 BOTANICAL GAZETTE [DECEMBER

100

80 H--

im 40~ ~

0 20 40 60 80 10

LU> .

c> < 20

0 20 40 60 80 100

PERCENT DAMAGE TO LEAVES OF ALL POPULATIONS

FIG. 3.-Response curves of freezing damage according to the severity of the freezing treatment for five populations that illustrate the variety of observed responses.

vided extraneous variance to the logistic models. Therefore, a separate set of regressions was calculated from the 36 observations that remained after elimination of three sampling dates. Results of both regressions for each population were the same. In fact, the simple correlation of predicted damage at a freezing severity of 50%X0 (Y50) derived from 48 observations with that derived from 36 observations was essentially perfect (r = .997).

The hardiness of populations could have been expressed by the mean injury of populations for all 48 test temperatures as well as by Y50. The simple correlation between these two values for all populations was also nearly perfect (r = .992). Moreover, mean injury for all test temperatures differed by nearly 46%7 for populations of maximum contrast. Thus, the relatively sophisticated logistic models apparently provided no greater information than the simple mean.

The value of Y50 was used as a dependent variable in multiple regression analysis to relate population differentiation to geographic and physiognomic criteria of the seed source. Multiple regression models are partially interpretable from the intercorrelations among dependent and independent variables, which were strongly related except for the latitude and longitude of population origin (table 3). Of the various combinations of the independent variables tested in multiple regression analyses, the model that accounted for both the most variance among populations (R2 = .78) and the lowest residual mean square included elevation and geographic regions as independent variables (table 4). Models that included elevation showed no significant effects of

TABLE 3

COEFFICIENTS OF DETERMINATION (R2) AMONG VARI- ABLES DESCRIBING THE SEED SOURCE AND PREDICTED

INJURY AT A FREEZING SEVERITY OF 50%

Geographic Variable Latitude Longitude Elevation region

Predicted injury.... . 26* .46* -.64* .61*

Latitude . 01 -.41* .55* Longitude. . . -.23* .83* Elevation.... 43*

* Statistically significant at the 1% level of probability.

TABLE 4

RESULTS OF MULTIPLE REGRESSION ANALYSES FOR RELATING DAMAGE OF POPULATIONS AT A FREEZING SEVERITY OF 50% TO GEO- GRAPHIC AND ECOLOGIC CRITERIA OF THE SEED SOURCE

Regression Independent variable coefficient

Xi elevation ................ . -.031 Geographic region:

X4 North Idaho ............ 31.46 X5 South Idaho ............ 13.64 X6 West Montana .......... 19.97 X7 Central Montana ........ .00

NOTE.-bo = 88.83 (contains effects of the central Mon- tana region as well as the intercept), R2 = .78, and sy. =

13.28.

latitude, and models that included geographic regions showed no significant effects of longitude.

Under the regression model (table 4), effects of the central Montana geographic region are contained within the intercept (bo); therefore, regression coefficients for the constant terms (b4-b6) represent deviations from the mean for the central Montana region. For instance, when no freezing injury occurs within populations from central Montana, the expected percentage of individuals injured in populations from south Idaho, west Montana, and north Idaho averages 14%, 20%, and 31%, respectively. All regression coefficients describing geographic regions differ significantly (5% level) from each other except those coefficients representing southern Idaho and western Montana populations. Regardless of geographic region, for each 1,000-m increase in elevation, predicted injury decreased by 31%.

Discussion Freezing tests indicated population differentiation

in cold hardiness throughout the period of cold acclimation. Differentiation was greatest before the first frost and development of tolerance to extreme cold. Still, the relative hardiness of populations remained essentially constant throughout acclimation. These patterns of variation in acclimation of



1980] REHFELDT-PINUS CONTORTA 463

populations of lodgepole pine are similar to those in populations of Rocky Mountain Douglas-fir (REH- FELDT 1979b), even though leaves of lodgepole pine are more hardy throughout acclimation than those of Douglas-fir. For lodgepole pine to be more hardy than Douglas-fir is consistent with other freezing tests (SAKAI and WEISER 1973) and phytosociologi- cal studies that relegate the pine to a colder range of environments than Douglas-fir (DAUBENMIRE and DAUBENMIRE 1968; PFISTER et al. 1977).

As a survey of adaptive differentiation, the present study did not allow estimation of the amount of cold each population could withstand at a given date, but the approach did allow an assessment of the amount of injury each population suffered from a given amount of cold. Logistic analyses illustrated genetic diversity among populations (fig. 3). In addition, at each date except those in August and November, injury to various populations ranged from 0% to 1000% at the temperature associated with injury to 50%J0 of all leaves. These results show tremendous genetic differentiation in cold tolerance of populations.

Even though logistic regression analyses depicted genetic differentiation, levels of injury predicted from logistic models essentially were perfectly corre- lated with the simple population mean of leaves injured for all freezing treatments. This result, when coupled with those showing that relative differences among populations remained essentially constant throughout acclimation, suggests that population differentiation could have been assessed without

loss of information by the average number of leaves injured on a single sampling date, provided that mean injury was accurately estimated.

Multiple regression analyses related variation in cold hardiness among populations to the elevation and geographic region of population origin. These results seem sensible. Temperatures decrease with increasing altitude, and major climatic, ecologic, and physiognomic features separate geographic regions of the northern Rockies (DAUBENMIRE and DAUBENMIRE 1968; PFISTER et al. 1977; ARNO 1979; STEELE et al., in press). Moreover, the results are strikingly similar to those involving Douglas-fir from the same geographic regions (WRIGHT et al. 1977; REHFELDT 1978, 1979a, 1979b).

This paper represents only a general survey of adaptive differentiation in cold hardiness of lodgepole pine populations, but the results have direct practical application. Tree improvement programs will be initiated soon with lodgepole pine in the northern Rocky Mountains. A successful program requires that genetically improved trees retain adaptations to the natural environment. Current data suggest that separate improvement programs are necessary for lodgepole pine in north Idaho, south Idaho, west Montana, and central Montana. Future work is needed (1) to assess adaptive differentiation of populations within geographic regions, (2) to estimate genetic gain in cold hardiness that can be made through population or family selection, and (3) to determine relationships between cold hardiness and other traits, particularly growth potential.

LITERATURE CITED

ARNO, S. F. 1979. Forest regions of Montana. U.S. Dep. Agr. Forest Service, Res. Paper INT-218. Intermountain Forest and Range Experiment Station, Ogden, Utah.

DAUBENMIRE, R., and J. B. DAUBENMIRE. 1968. Forest vegeta- tion of eastern Washington and northern Idaho. Washington Agr. Exp. Sta. Tech. Bull. 60. 104 pp.

FLINT, H. L. 1972. Cold hardiness of twigs of Quercus rubra as a function of geographic origin. Ecology 53:1163-1170.

JOHNSON, N. L., and S. KOTZ. 1970. Distributions in statistics: continuous univariate distributions. Vol. 2. Wiley, New York. 306 pp.

LARSEN, J. B. 1978a. Die Frostresistenz der Douglasie (Pseudotsuga menziesii [Mirb.] Franco) verschiedener Herkuinfte mit unterschiedlicher Hohenlage. Silvae Genet. 27:150-156. - . 1978b. Die Klimaresistenz der Abies grandis (Dougl.) Lindl. I. Die Frostresistenz von 23 Herkuinften aus dem IUFRO Provenienz-versuch von 1974. Silvae Genet. 27:156-161.

LEVITT, J. 1972. Responses of plants to environmental stresses. Academic Press, New York. 697 pp.

PFISTER, R. D., B. L. KOVALCHIK, S. F. ARNO, and R. C. PRESBY. 1977. Forest habitats of Montana. U.S. Dep. Agr. Forest Service, Gen. Tech. Rep. INT-34. Intermountain Forest and Range Experiment Station, Ogden, Utah.

REHFELDT, G. E. 1977. Growth and cold hardiness of inter- varietal hybrids of Douglas-fir. Theoret. Appl. Genet. 50:3-15. --. 1978. Genetic differentiation of Douglas-fir popula-

tions from the Northern Rocky Mountains. Ecology 59:1264-1270.

-. 1979a. Ecological adaptations in Douglas-fir (Pseu- dotsuga menziesii var. glauca) populations. I. North Idaho and northeast Washington. Heredity 43:383-397. --. 1979b. Variation in cold hardiness among populations of Pseudotsuga menziesii var. glauca. U.S. Dep. Agr. Forest Service, Res. Paper INT-233. Intermountain Forest and Range Experiment Station, Ogden, Utah.

SAKAI, A., and C. J. WEISER. 1973. Freezing resistance of trees of North America with reference to tree regions. Ecology 54:118-126.

SMITHBERG, M. H., and C. J. WEISER. 1968. Patterns of variation among climatic races of red-osier dogwood. Ecology 49:495-505.

STEELE, R., R. D. PFISTER, R. A. RYKER, and J. A. KITTAMS. In press. Forest habitat types of central Idaho. U.S. Dep. Agr. Forest Service, Gen. Tech. Rep. Intermountain Forest and Range Experiment Station, Ogden, Utah.

STEELE, R. G. D., and J. H. TORRIE. 1960. Principles and procedures of statistics. McGraw-Hill, New York. 481 pp.

WEISER, C. J. 1970. Cold resistance and injury in woody plants. Science 169:1268-1278.

WILLIAMS, G. J., III, and C. MCMILLAN. 1971. Frost tolerance of Liquidambar styraciflua native to the United States, Mexico, and Central America. Can. J. Bot. 49:1551-1558.

WRIGHT, J. W., F. H. KUNG, R. A. READ, W. A. LEMMIEN, and J. N. BRIGHT. 1977. Genetic variation in Rocky Moun- tain Douglas-fir. Silvae Genet. 20:54-60.



cold acclimation in populations of pinus contorta from the northern rocky mountains

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