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A comparison of ring-width and event-year chronologies derived from white oak (Quercus alba) and northern red oak (Quercus rubra), southwestern Quebec, Canada
ARTICLE IN PRESS
Dendrochronologia 23 (2006) 133–138 www.elsevier.de/dendro
ORIGINAL ARTICLE
A comparison of ring-width and event-year chronologies derived from white oak (Quercus alba) and northern red oak (Quercus rubra), southwestern Quebec, Canada J.C. Tardif, F. Conciatori Centre for Forest Interdisciplinary Research (C-FIR), University of Winnipeg, 515 Portage Avenue, Winnipeg, Man., Canada R3B 2E9 Received 20 June 2005; accepted 18 October 2005
Abstract In dendrochronology, ring width has been a variable of choice when assessing the radial growth–climate association of tree species. We compared ring-width and event-year chronologies from a dendroclimatic perspective using both white oak (Quercus alba L.) and northern red oak (Quercus rubra L.). The study was conducted in three regions of the Ottawa valley in southern Que´bec. Twelve mixed red and white oak stands were selected and for each oak species, 12 chronologies were developed from tree-ring measurement and 12 others were derived using visual assessment of narrow or wide rings (event years). Ring-width and event-year chronologies gave almost identical results and revealed the prevalence of drought in the early growing season as the most influential factor in both species. This study emphasizes the utility of event-year chronologies in tree-ring studies and their comparativeness with ring width. Establishing event-year chronologies has the advantage of being faster than measuring ring width, it does not necessitate complex equipment and depending on the purpose of the study may prove to be at least comparable. The choice of species, their mean sensitivity, the ability to recognize narrow or large rings as well as the number of trees and sites to analyze may, however, be factors to consider when choosing to use event-year chronologies over the more commonly used ring-width ones. r 2005 Elsevier GmbH. All rights reserved. Keywords: Ring width; Event years; Principal components analysis; Redundancy analysis; Radial growth–climate association
Introduction In dendrochronology, ring width constitutes the variable of interest in most studies (Schweingruber, 1996). Data derived from skeleton plots have received much less attention and the accuracy of data derived Corresponding author. Tel.: +1 204 786 9475; fax: +1 204 774 4134. E-mail address: [email protected] (J.C. Tardif).
1125-7865/$ - see front matter r 2005 Elsevier GmbH. All rights reserved. doi:10.1016/j.dendro.2005.10.001
from visual determination of event years (Schweingruber et al., 1990) has often been questioned (Weber, 1995). The identification of an event year is considered more subjective (it may vary with the observer’s experience) than measuring ring width and the series produced are temporally discontinuous. In a comparison study of manual and computer generated skeleton plots, Cropper (1979) reported about 85% agreement between the two. Using a simple index resulting in continuous time series, Weber (1995) observed 88.85%
ARTICLE IN PRESS 134
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concordance between chronologies derived from skeleton plot data (narrow and large rings) and unfiltered ring-width series. The objective of this study was to assess how chronologies developed from ring-width measurement and event years performed when compared for assessing the radial growth–climate association of two oaks species. More specifically, we compared the two chronology types in white oak (Quercus alba L.) and red oak (Quercus rubra L.) trees growing at the northern distribution limit of white oak.
Methods Study area The study area is located in southwestern Quebec and covers approximately 200 km (eastern to western most sites). Twelve mixed oak stands were sampled in three regions of the Ottawa valley in southern Que´bec. The oak forests sampled have developed on subxeric to xeric south to southwest facing slopes of the Precambrian Shield. Q. alba reaches the northern limit of its distribution range in southern Que´bec and is listed as rare in the province (Bouchard et al., 1983; Labrecque and Lavoie, 2002). More complete descriptions and analyses of these oak stands are found in Gagnon and Bouchard (1981), Gauthier and Gagnon (1990), Nantel (1995) and Tardif et al. (in press).
Chronology development The 12 stands were selected according to Q. alba abundance. The mean number and standard deviation of trees sampled in each stand was 46726 (min ¼ 16 and max ¼ 97) for Q. alba and 50730 (min ¼ 17 and max ¼ 124) for Q. rubra. Each tree was cored at its base and a single core was generally extracted (Nantel, 1995). The mean number and standard deviation of cores sampled in each stand was 51728 (min ¼ 16 and max ¼ 103) for Q. alba and 56733 (min ¼ 21 and max ¼ 131) for Q. rubra. All wood samples were prepared following standard methods (Stokes and Smiley, 1968). They were dated and visually crossdated to identify event years. Ring widths were measured at a precision of 0.001 mm using a Velmex measuring system and data quality was validated with the COFECHA program (Holmes, 1983). Each measured series was standardized using a spline function with a 50% frequency response of 50 years (Cook and Peters, 1981). Twelve paired Q. alba and Q. rubra residual ring-width chronologies were developed after autoregressive modelling was performed on each standardized series to remove temporal autocorrelation.
All residual series were averaged by site/species using a biweight robust mean. All procedures were conducted using program ARSTAN (Cook, 1985) and resulted in 12 residual ring-width chronologies per species that is one for each sampled stand. All event years (narrow ring, extreme narrow ring, wide ring, extreme large ring and abrupt growth suppression) were qualitatively recorded for each core by a single observer. In this study, narrow rings and very narrow rings were given a negative value of 1 and separately coded. The opposite value (+1) was used for large and very large rings. A period of suppression was determined as a period for which more than five consecutive rings were narrow to extremely narrow (Fig. 1). For the purpose of the study, we calculated for each of the 12 stands the relative frequency of negative and positive events in each species. Each event year was recorded, summed for each year (negative and positive events cancelled each other) and divided by the number of series present at that time for a specific species and site. The resulting fractions were then multiplied by 100. This simple operation provided 12 continuous eventyear chronologies per species that is one for each sampled stand.
Comparison of chronologies and relationship to climate Principal components analysis (PCA) and redundancy analysis (RDA) were used (i) to compare the two chronology types (2 species, 12 sites) and (ii) to assess the radial growth–climate association in both species. To determine the common variation among all 48 chronologies (2 types, 2 species, 12 sites), the structure of their variance was first analyzed using PCA (Peters et al., 1981; Girardin and Tardif, 2005). In dendroecology, the relationships between tree-ring indices and climate variables are usually calculated in the form of a correlation or a response function (Fritts, 1976; Cook and Kairiukstis, 1990). RDA is also effective in quantifying the relationship between tree-ring indices and climatic factors (Tardif et al., 2003; Girardin et al., 2004a). RDA, the canonical form of PCA, constitutes the direct extension of multiple regressions applied to multivariate data (Legendre and Legendre, 1998). In RDA, the ordination axes are constrained to be linear combinations of supplied environmental variables (ter Braak, 1994; ter Braak and Prentice, 1988). All ordination analyses were computed using program CANOCO (Ver 4.52). They were calculated using a correlation matrix and scaling of ordination scores was done using a correlation biplot (ter Braak, 1994). In RDA, significant climatic variables (po0:05) were selected after a forward selection using a Monte Carlo permutation test based on 999 random permutations.
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Fig. 1. Residual ring-width chronologies (black line, outer-left scale) and event-year chronologies (stacked bar, inner-left scale) for Quercus alba and Quercus rubra growing at Waltham (northern most site) for the period 1860–1989. The white, gray and black bars indicate periods of growth suppression, narrow (large) rings and very narrow (very large) rings respectively. Sample depth (number of cores) is indicated at the bottom of each graph.
To compare the RDA with methods more commonly used in tree-ring studies, Pearson’s correlations were calculated between PC-1, derived from the separate PCA of the two chronology types, and climate variables. The meteorological station with the longest and most complete record in the area is Ottawa CDA (Environment Canada, 2003). For all climate analyses, mean monthly temperature and total monthly precipitation from May of the preceding growing season (t 1) to August of the current growing season (t) were used as predictors. In addition, the Canadian Drought Code (CDC) component of the Canadian Forest Fire Behavior System (Van Wagner, 1987; Girardin et al., 2004b) was used. More details on the climate data can also be found in Tardif et al. (in press). For all climate analyses, the reference period was set to 1920–1989.
Results and discussion Chronologies and climate association A strong correspondence was observed between the residual ring-width and event-year chronologies in both species (Fig. 1). The similarity among sites and species was also emphasized by the large variance explained by the first two principal components (PC1: 57.9% and PC2: 9.1%, respectively) computed for the period 1920–1989. Only on PC1 was a slight but significant difference observed between the mean loading value of
the 24 event-year chronologies and the 24 residual ringwidth chronologies (Two-sample t-test: 0.7370.09 and 0.7970.08, respectively, p ¼ 0:018). No significant differences in species’ loadings on PC1 and PC2 were observed. The absence of a significant correlation between sample depth and site longitude in Q. alba (r ¼ 0:24, p ¼ 0:456, n ¼ 12) compared to Q. rubra (r ¼ 0:78, p ¼ 0:003, n ¼ 12) made it possible to determine if PC1 and PC2 were related to either of these variables. In Q. rubra, both variables were significantly correlated with PC2 (r ¼ 0:82, p ¼ 0:0001, n ¼ 24 and r ¼ 0:56, p ¼ 0:005, n ¼ 24, respectively). In Q. alba, only site longitude was significantly correlated with PC2 (r ¼ 0:82, p ¼ 0:0001, n ¼ 24; sample depth: r ¼ 0:25, p ¼ 0:242, n ¼ 24) suggesting that chronologies made-up of 20, 40 or more cores had similar influence in the formation of the PCs. Comparison of both chronology types indicated that the 12 residual ring-width chronologies displayed higher mean correlation and percentage of variance in the first eigenvector compared to event-year chronologies (Table 1). Eventyear chronologies showed no autocorrelation and slightly higher mean sensitivity values. The RDA further highlighted the similarities among the 24 oak chronologies within each chronology type as well as their similar association with climatic variables (Fig. 2). All chronologies shared a positive loading on axis-1 indicating common contribution to the creation of that axis (Figs. 2a and b). This reflects the fact that radial growth patterns in oak were correlated over the entire region. The climatic variables most strongly and
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Table 1. Dendrochronological features of the 12 residual ring-width chronologies and 12 event-year chronologies for each species and calculated for the reference period 1920–1989 Ring width
Quercus alba Mean sensitivity First order autocorrelation Mean correlationa EPSa % Variance in PC1a Quercus rubra Mean sensitivity First order autocorrelation Mean correlationa EPSa % Variance in PC1a a
Event year
Mean
Std
Min
Max
Mean
Std
Min
Max
0.31 0.07 0.64 0.95 66.97
0.06 0.09 — — —
0.23 0.21 — — —
0.42 0.08 — — —
0.38 0.13 0.53 0.93 57.88
0.09 0.09 — — —
0.25 0.03 — — —
0.54 0.24 — — —
0.26 0.06 0.66 0.96 69.26
0.04 0.05 — — —
0.19 0.14 — — —
0.33 0.02 — — —
0.29 0.12 0.55 0.94 59.43
0.10 0.07 — — —
0.13 0.02 — — —
0.53 0.28 — — —
Value obtained when calculating a reference chronology using each set of twelve site chronologies.
Fig. 2. Redundancy analysis (RDA) calculated from the 24 residual ring-width chronologies (A) and the 24 event-year chronologies (B) for the reference period 1920–1989. White symbols refer to Quercus alba chronologies and gray symbols refer to Quercus rubra chronologies. Significant (po0:05) climatic factors are indicated by vector with dark gray solid line. Vectors with broken dark gray lines indicate variables that were made passive. T ¼ Temperature, P ¼ Precipitation, CDC ¼ Canadian Drought Code, (t 1) ¼ year before ring formation. Note: In RDA biplots, the correlation between biotic and abiotic variables is given by the cosine of the angle between two vectors (arrows). Vectors pointing in roughly the same direction indicate a high positive correlation, vectors crossing at right angles correspond to a near-zero correlation, and vectors pointing in opposite directions show a high negative correlation (ter Braak and Prentice, 1988). Climatic variables with long vectors are the most significant in the analysis. The black vectors (arrow) related to the chronologies were not all drawn for visual clarity. (C–D) indicate how well the predicted scores (gray line) obtained from the climatic variables fit the first RDA axis (black line) whereas (D–E) apply to the second RDA axis. The correlation coefficient between the RDA loadings and their predicted values is indicated.
positively associated to radial growth in both species were June–July precipitation during the year of ring formation (Figs. 2a and b). The strong negative
association with the July CDC (Table 2), which was made passive in the RDA (Figs. 2a and b), also emphasized the importance of early growing season
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Table 2. Pearson correlations coefficients between the loading of the first principal component derived for the twelve residual ring-width (left column) and event-year (right column) chronologies separately and climate variables for the reference period 1920–1989
Mai (t 1) June (t 1) July (t 1) August (t 1) September (t 1) October (t 1) November (t 1) December (t 1) January February March April May June July August
Ring width: PC-1
Event year: PC-1
T
P
D
T
0.01 0.02 0.11 0.12 0.01 0.21 0.05 0.12 0.09 0.03 0.03 0.17 0.32 0.23 0.20 0.17
0.02 0.06 0.24 0.08 0.06 0.01 0.01 0.14 0.15 0.26 0.02 0.01 0.16 0.51 0.30 0.03
0.03 0.02 0.01 0.21 0.22 0.17 NA NA NA NA NA 0.02 0.25 0.43 0.57 0.36
0.05 0.06 0.03 0.07 0.02 0.06 0.18 0.30 0.10 0.16 0.04 0.22 0.04 0.07 0.21 0.16 0.05 0.10 0.01 0.08 NA 0.17 0.11 NA 0.11 0.13 NA 0.04 0.20 NA 0.00 0.05 NA 0.20 0.01 0.03 0.22 0.14 0.21 0.24 0.51 0.44 0.13 0.29 0.58 0.18 0.02 0.33
P
D
Coefficients in bold are significant at po0:05. T: mean temperature, P: total precipitation and D: Canadian Drought Code.
moisture availability for radial growth. These results are consistent with numerous studies showing that the response of Q. alba and Q. rubra is dominated by water balance in the early growing season (Jacobi and Tainter, 1988; Graumlich, 1993; Rubino and McCarthy, 2000; LeBlanc and Terrell, 2001; Terrell and LeBlanc, 2002; Tardif et al., in press). When looking at variations between species, both the negative correlation between radial growth and May temperature and the inverse one with July precipitation were slightly higher in Q. alba (Fig. 2a). July precipitation during the year prior to ring formation was more highly correlated with radial growth in Q. rubra (Figs. 2a and b). Both climate models performed well and correlation between the first two RDA axis scores and their estimated values were slightly higher when residual ring-width chronologies were used (Figs. 2c, d, e and f). The RDA results were also concordant with the Pearson correlations (Table 2). The residual ring-width chronologies had a higher number of significant correlations and the negative association with May temperature was better captured.
Ring width or event years? Our results support those of Weber (1995) who observed great similarity between ring-width series and those derived from skeleton plots. In our study, both ring-width and event-year chronologies adequately
137
captured the extreme values in radial growth and both reflected essentially the same climate signal (Fig. 1). Compared to the development of ring-width chronologies, establishing event-year chronology is faster, it does not necessitate complex and expensive equipment and elaborated standardization procedures. When identifying narrow and large rings, the human eye and brain behave as a high-pass filter revealing the high-frequency signal in tree-rings (Cook and Briffa, 1990; Weber, 1995). Despite the dissimilarity in the approaches – ringwidth chronologies depict the mean radial growth of a stand at a time and the event-year chronologies provide an idea of the percentage number of trees affected by a given event in time (Weber, 1995) – both were found comparable in their ability to identify the climatic response of Q. alba and Q. rubra. In conclusion, our findings demonstrated that ringwidth and event-year chronologies were comparable in the extraction of the dominant climate signal in both oak species. This approach may, however, not be as successful when applied to material with weaker climatic signal (more complacent material) and more research with such material and/or species is needed (Weber, 1995). As with ring width, the portion of the signal due to endogenous/ exogenous disturbances also needs to be considered. In our data, no major episodes of sustained growth suppression were observed making it possible to make use of all negative and positive event years. The number of trees and sites to analyse may also be factors to consider when choosing to use event-year chronologies over the more commonly used ring-width ones. Our results indicated that PCA was an effective method of analysis and that sample size had a negligible impact on the analyses. Finally, we concur with Weber (1995), that the ability to recognize narrow and large rings may vary from one observer to the other despite establishing similar procedures and this variability also needs to be better quantified.
Acknowledgments Many thanks to field assistants P. Boivin, D. De´ry, J.-F. Dubuc, S. Grignon, L. Lauzon, M.-A. Martin and H. Williams. We thank M.-P. Girardin for calculating the Canadian Drought Code and P. Nantel and D. Gagnon for providing the wood samples. We thank P. Cherubini, C. Urbinati and an anonymous reviewer for their constructive comments on a previous draft of the manuscript. This research was supported by the Natural Sciences and Engineering Research Council of Canada and the University of Winnipeg.
References Bouchard A, Barabe´ D, Dumais M, Hay S. The rare vascular plants of Quebec. National Museum of Canada. Syllogeus 1983;48:1–75.
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Cook ER. A time series analysis approach to tree-ring standardization. Dissertation, University of Arizona, 1985. Cook ER, Briffa KR. A comparison of some tree-ring standardization methods. In: Cook ER, Kairiukstis LA, editors. Methods of dendrochronology: applications in the environmental sciences. Dordrecht: Kluwer Academic Publishers; 1990. p. 104–23. Cook ER, Kairiukstis LA, editors. Methods of dendrochronology: applications in the environmental sciences. Dordrecht: Kluwer Academic Publishers; 1990. 408p Cook ER, Peters K. The smoothing spline: a new approach to standardizing forest interior tree-ring width series for dendroclimatic studies. Tree-Ring Bulletin 1981;41:45–53. Cropper JP. Tree-ring skeleton plotting by computer. TreeRing Bulletin 1979;39:47–60. Environment Canada. Canadian Climate Normals, 1971–2000 [electronic resource]. Canadian Climate Program, Atmospheric Environment Service, 2003. Fritts HC. Tree rings and climate. New York: Academic Press; 1976. 567p Gagnon D, Bouchard A. La ve´ge´tation de l’escarpement d’Eardley, parc de la Gatineau, Que´bec. Canadian Journal of Botany 1981;59:2667–91. Gauthier S, Gagnon D. La ve´ge´tation des contreforts des Laurentides: une analyse des gradients e´cologiques et du niveau successionnel des communaute´s. Canadian Journal of Botany 1990;68:391–401. Girardin M-P, Tardif J. Sensitivity of tree growth to the atmospheric vertical profile in the Boreal Plains of Manitoba. Canadian Journal of Forest Research 2005;35:48–64. Girardin M-P, Tardif J, Flannigan MD, Bergeron Y. Multicentury reconstruction of the Canadian Drought Code from eastern Canada and its relationships with paleoclimatic indexes of atmospheric circulation. Climate Dynamics 2004a;23:99–115. Girardin M-P, Tardif J, Flannigan MD, Wotton MB, Bergeron Y. Trends and periodicities in the Canadian Drought Code and their relationships with atmospheric circulation for the southern Canadian boreal forest. Canadian Journal of Forest Research 2004b;34:103–19. Graumlich LJ. Response of tree growth to climatic variation in the mixed conifer and deciduous forest of the upper Great Lakes region. Canadian Journal of Forest Research 1993;23:133–43. Holmes RL. Computer-assisted quality control in tree-ring dating and measurement. Tree-Ring Bulletin 1983;43: 68–78. Jacobi JC, Tainter FH. Dendroclimatic examination of white oak along an environmental gradient in the Piedmont of South Carolina. Castanea 1988;53:252–62. Labrecque J, Lavoie G. Les plantes vasculaires menace´es ou vulne´rables du Que´bec. Direction du patrimoine e´cologique
et du de´veloppement durable, Ministe`re de l’Environnement du Que´bec, 2002. 200p. LeBlanc D, Terrell M. Dendroclimatic analyses using the Thornthwaite-mather-type evapotranspiration models: a bridge between dendroecology and forest simulation models. Tree-Ring Research 2001;57:55–66. Legendre P, Legendre L. Numerical ecology. New York: Elsevier Scientific Publishing Company; 1988. 853p. Nantel P. De´mographie comparative et analyse de la viabilite´ de populations de plantes a` la limite nord de leur aire de distribution. Dissertation, Universite´ du Que´bec a` Montre´al, 1995. Peters K, Jacoby GC, Cook ER. Principal components analysis of tree-ring sites. Tree-Ring Bulletin 1981;41: 1–19. Rubino DL, McCarthy BC. Dendroclimatological analysis of white oak (Quercus alba L. Fagaceae) from an old-growth forest of southern Ohio, USA. Journal of the Torrey Botanical Club 2000;27:240–50. Schweingruber FH. Tree ring and environment. Dendroecology. Berne: Paul Haupt Verlag; 1996. 609p. Schweingruber FH, Eckstein D, Serre-Bachet F, Braker OU. Identification, presentation and interpretation of event years and pointer years in dendrochronology. Dendrochronologia 1990;8:9–38. Stokes MA, Smiley TL. An introduction to tree-ring dating. Chicago: University of Chicago Press; 1968. 73p. Tardif J, Camarero JJ, Ribas M, Gutie´rrez E. Spatiotemporal variability in radial growth of trees in the Central Pyrenees: climatic and site influences. Ecological Monographs 2003;73:241–57. Tardif JC, Conciatori F, Nantel P, Gagnon D. Radial growth of white oak (Quercus alba) and northern red oak (Quercus rubra) growing at the north-eastern distribution limit of white oak, southwestern Quebec, Canada. Journal of Biogeography, in press. ter Braak CJF. Canonical community ordination. Part I: Basic theory and linear methods. Ecoscience 1994;1: 127–40. ter Braak CJF, Prentice IC. A theory of gradient analysis. Advances in Ecological Research 1988;18:271–317. Terrell M, LeBlanc D. Spatial variation in response of northern red oak to climate stresses in eastern North America. In: Be´gin Y, editor. Dendrochronology, environmental change and human history, sixth international conference on dendrochronology, Laval University, 2002. p. 340–3. Van Wagner CE. Development and structure of the Canadian Forest Fire Weather Index System. Canadian Forest Service, Forestry Technical Report 35, 1987. 37pp. Weber URS M. Ring width measurements versus skeleton plots: a preliminary comparison. Dendrochronologia 1995;13:147–8.
Dendrochronologia 23 (2006) 133–138 www.elsevier.de/dendro
ORIGINAL ARTICLE
A comparison of ring-width and event-year chronologies derived from white oak (Quercus alba) and northern red oak (Quercus rubra), southwestern Quebec, Canada J.C. Tardif, F. Conciatori Centre for Forest Interdisciplinary Research (C-FIR), University of Winnipeg, 515 Portage Avenue, Winnipeg, Man., Canada R3B 2E9 Received 20 June 2005; accepted 18 October 2005
Abstract In dendrochronology, ring width has been a variable of choice when assessing the radial growth–climate association of tree species. We compared ring-width and event-year chronologies from a dendroclimatic perspective using both white oak (Quercus alba L.) and northern red oak (Quercus rubra L.). The study was conducted in three regions of the Ottawa valley in southern Que´bec. Twelve mixed red and white oak stands were selected and for each oak species, 12 chronologies were developed from tree-ring measurement and 12 others were derived using visual assessment of narrow or wide rings (event years). Ring-width and event-year chronologies gave almost identical results and revealed the prevalence of drought in the early growing season as the most influential factor in both species. This study emphasizes the utility of event-year chronologies in tree-ring studies and their comparativeness with ring width. Establishing event-year chronologies has the advantage of being faster than measuring ring width, it does not necessitate complex equipment and depending on the purpose of the study may prove to be at least comparable. The choice of species, their mean sensitivity, the ability to recognize narrow or large rings as well as the number of trees and sites to analyze may, however, be factors to consider when choosing to use event-year chronologies over the more commonly used ring-width ones. r 2005 Elsevier GmbH. All rights reserved. Keywords: Ring width; Event years; Principal components analysis; Redundancy analysis; Radial growth–climate association
Introduction In dendrochronology, ring width constitutes the variable of interest in most studies (Schweingruber, 1996). Data derived from skeleton plots have received much less attention and the accuracy of data derived Corresponding author. Tel.: +1 204 786 9475; fax: +1 204 774 4134. E-mail address: [email protected] (J.C. Tardif).
1125-7865/$ - see front matter r 2005 Elsevier GmbH. All rights reserved. doi:10.1016/j.dendro.2005.10.001
from visual determination of event years (Schweingruber et al., 1990) has often been questioned (Weber, 1995). The identification of an event year is considered more subjective (it may vary with the observer’s experience) than measuring ring width and the series produced are temporally discontinuous. In a comparison study of manual and computer generated skeleton plots, Cropper (1979) reported about 85% agreement between the two. Using a simple index resulting in continuous time series, Weber (1995) observed 88.85%
ARTICLE IN PRESS 134
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concordance between chronologies derived from skeleton plot data (narrow and large rings) and unfiltered ring-width series. The objective of this study was to assess how chronologies developed from ring-width measurement and event years performed when compared for assessing the radial growth–climate association of two oaks species. More specifically, we compared the two chronology types in white oak (Quercus alba L.) and red oak (Quercus rubra L.) trees growing at the northern distribution limit of white oak.
Methods Study area The study area is located in southwestern Quebec and covers approximately 200 km (eastern to western most sites). Twelve mixed oak stands were sampled in three regions of the Ottawa valley in southern Que´bec. The oak forests sampled have developed on subxeric to xeric south to southwest facing slopes of the Precambrian Shield. Q. alba reaches the northern limit of its distribution range in southern Que´bec and is listed as rare in the province (Bouchard et al., 1983; Labrecque and Lavoie, 2002). More complete descriptions and analyses of these oak stands are found in Gagnon and Bouchard (1981), Gauthier and Gagnon (1990), Nantel (1995) and Tardif et al. (in press).
Chronology development The 12 stands were selected according to Q. alba abundance. The mean number and standard deviation of trees sampled in each stand was 46726 (min ¼ 16 and max ¼ 97) for Q. alba and 50730 (min ¼ 17 and max ¼ 124) for Q. rubra. Each tree was cored at its base and a single core was generally extracted (Nantel, 1995). The mean number and standard deviation of cores sampled in each stand was 51728 (min ¼ 16 and max ¼ 103) for Q. alba and 56733 (min ¼ 21 and max ¼ 131) for Q. rubra. All wood samples were prepared following standard methods (Stokes and Smiley, 1968). They were dated and visually crossdated to identify event years. Ring widths were measured at a precision of 0.001 mm using a Velmex measuring system and data quality was validated with the COFECHA program (Holmes, 1983). Each measured series was standardized using a spline function with a 50% frequency response of 50 years (Cook and Peters, 1981). Twelve paired Q. alba and Q. rubra residual ring-width chronologies were developed after autoregressive modelling was performed on each standardized series to remove temporal autocorrelation.
All residual series were averaged by site/species using a biweight robust mean. All procedures were conducted using program ARSTAN (Cook, 1985) and resulted in 12 residual ring-width chronologies per species that is one for each sampled stand. All event years (narrow ring, extreme narrow ring, wide ring, extreme large ring and abrupt growth suppression) were qualitatively recorded for each core by a single observer. In this study, narrow rings and very narrow rings were given a negative value of 1 and separately coded. The opposite value (+1) was used for large and very large rings. A period of suppression was determined as a period for which more than five consecutive rings were narrow to extremely narrow (Fig. 1). For the purpose of the study, we calculated for each of the 12 stands the relative frequency of negative and positive events in each species. Each event year was recorded, summed for each year (negative and positive events cancelled each other) and divided by the number of series present at that time for a specific species and site. The resulting fractions were then multiplied by 100. This simple operation provided 12 continuous eventyear chronologies per species that is one for each sampled stand.
Comparison of chronologies and relationship to climate Principal components analysis (PCA) and redundancy analysis (RDA) were used (i) to compare the two chronology types (2 species, 12 sites) and (ii) to assess the radial growth–climate association in both species. To determine the common variation among all 48 chronologies (2 types, 2 species, 12 sites), the structure of their variance was first analyzed using PCA (Peters et al., 1981; Girardin and Tardif, 2005). In dendroecology, the relationships between tree-ring indices and climate variables are usually calculated in the form of a correlation or a response function (Fritts, 1976; Cook and Kairiukstis, 1990). RDA is also effective in quantifying the relationship between tree-ring indices and climatic factors (Tardif et al., 2003; Girardin et al., 2004a). RDA, the canonical form of PCA, constitutes the direct extension of multiple regressions applied to multivariate data (Legendre and Legendre, 1998). In RDA, the ordination axes are constrained to be linear combinations of supplied environmental variables (ter Braak, 1994; ter Braak and Prentice, 1988). All ordination analyses were computed using program CANOCO (Ver 4.52). They were calculated using a correlation matrix and scaling of ordination scores was done using a correlation biplot (ter Braak, 1994). In RDA, significant climatic variables (po0:05) were selected after a forward selection using a Monte Carlo permutation test based on 999 random permutations.
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Fig. 1. Residual ring-width chronologies (black line, outer-left scale) and event-year chronologies (stacked bar, inner-left scale) for Quercus alba and Quercus rubra growing at Waltham (northern most site) for the period 1860–1989. The white, gray and black bars indicate periods of growth suppression, narrow (large) rings and very narrow (very large) rings respectively. Sample depth (number of cores) is indicated at the bottom of each graph.
To compare the RDA with methods more commonly used in tree-ring studies, Pearson’s correlations were calculated between PC-1, derived from the separate PCA of the two chronology types, and climate variables. The meteorological station with the longest and most complete record in the area is Ottawa CDA (Environment Canada, 2003). For all climate analyses, mean monthly temperature and total monthly precipitation from May of the preceding growing season (t 1) to August of the current growing season (t) were used as predictors. In addition, the Canadian Drought Code (CDC) component of the Canadian Forest Fire Behavior System (Van Wagner, 1987; Girardin et al., 2004b) was used. More details on the climate data can also be found in Tardif et al. (in press). For all climate analyses, the reference period was set to 1920–1989.
Results and discussion Chronologies and climate association A strong correspondence was observed between the residual ring-width and event-year chronologies in both species (Fig. 1). The similarity among sites and species was also emphasized by the large variance explained by the first two principal components (PC1: 57.9% and PC2: 9.1%, respectively) computed for the period 1920–1989. Only on PC1 was a slight but significant difference observed between the mean loading value of
the 24 event-year chronologies and the 24 residual ringwidth chronologies (Two-sample t-test: 0.7370.09 and 0.7970.08, respectively, p ¼ 0:018). No significant differences in species’ loadings on PC1 and PC2 were observed. The absence of a significant correlation between sample depth and site longitude in Q. alba (r ¼ 0:24, p ¼ 0:456, n ¼ 12) compared to Q. rubra (r ¼ 0:78, p ¼ 0:003, n ¼ 12) made it possible to determine if PC1 and PC2 were related to either of these variables. In Q. rubra, both variables were significantly correlated with PC2 (r ¼ 0:82, p ¼ 0:0001, n ¼ 24 and r ¼ 0:56, p ¼ 0:005, n ¼ 24, respectively). In Q. alba, only site longitude was significantly correlated with PC2 (r ¼ 0:82, p ¼ 0:0001, n ¼ 24; sample depth: r ¼ 0:25, p ¼ 0:242, n ¼ 24) suggesting that chronologies made-up of 20, 40 or more cores had similar influence in the formation of the PCs. Comparison of both chronology types indicated that the 12 residual ring-width chronologies displayed higher mean correlation and percentage of variance in the first eigenvector compared to event-year chronologies (Table 1). Eventyear chronologies showed no autocorrelation and slightly higher mean sensitivity values. The RDA further highlighted the similarities among the 24 oak chronologies within each chronology type as well as their similar association with climatic variables (Fig. 2). All chronologies shared a positive loading on axis-1 indicating common contribution to the creation of that axis (Figs. 2a and b). This reflects the fact that radial growth patterns in oak were correlated over the entire region. The climatic variables most strongly and
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Table 1. Dendrochronological features of the 12 residual ring-width chronologies and 12 event-year chronologies for each species and calculated for the reference period 1920–1989 Ring width
Quercus alba Mean sensitivity First order autocorrelation Mean correlationa EPSa % Variance in PC1a Quercus rubra Mean sensitivity First order autocorrelation Mean correlationa EPSa % Variance in PC1a a
Event year
Mean
Std
Min
Max
Mean
Std
Min
Max
0.31 0.07 0.64 0.95 66.97
0.06 0.09 — — —
0.23 0.21 — — —
0.42 0.08 — — —
0.38 0.13 0.53 0.93 57.88
0.09 0.09 — — —
0.25 0.03 — — —
0.54 0.24 — — —
0.26 0.06 0.66 0.96 69.26
0.04 0.05 — — —
0.19 0.14 — — —
0.33 0.02 — — —
0.29 0.12 0.55 0.94 59.43
0.10 0.07 — — —
0.13 0.02 — — —
0.53 0.28 — — —
Value obtained when calculating a reference chronology using each set of twelve site chronologies.
Fig. 2. Redundancy analysis (RDA) calculated from the 24 residual ring-width chronologies (A) and the 24 event-year chronologies (B) for the reference period 1920–1989. White symbols refer to Quercus alba chronologies and gray symbols refer to Quercus rubra chronologies. Significant (po0:05) climatic factors are indicated by vector with dark gray solid line. Vectors with broken dark gray lines indicate variables that were made passive. T ¼ Temperature, P ¼ Precipitation, CDC ¼ Canadian Drought Code, (t 1) ¼ year before ring formation. Note: In RDA biplots, the correlation between biotic and abiotic variables is given by the cosine of the angle between two vectors (arrows). Vectors pointing in roughly the same direction indicate a high positive correlation, vectors crossing at right angles correspond to a near-zero correlation, and vectors pointing in opposite directions show a high negative correlation (ter Braak and Prentice, 1988). Climatic variables with long vectors are the most significant in the analysis. The black vectors (arrow) related to the chronologies were not all drawn for visual clarity. (C–D) indicate how well the predicted scores (gray line) obtained from the climatic variables fit the first RDA axis (black line) whereas (D–E) apply to the second RDA axis. The correlation coefficient between the RDA loadings and their predicted values is indicated.
positively associated to radial growth in both species were June–July precipitation during the year of ring formation (Figs. 2a and b). The strong negative
association with the July CDC (Table 2), which was made passive in the RDA (Figs. 2a and b), also emphasized the importance of early growing season
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Table 2. Pearson correlations coefficients between the loading of the first principal component derived for the twelve residual ring-width (left column) and event-year (right column) chronologies separately and climate variables for the reference period 1920–1989
Mai (t 1) June (t 1) July (t 1) August (t 1) September (t 1) October (t 1) November (t 1) December (t 1) January February March April May June July August
Ring width: PC-1
Event year: PC-1
T
P
D
T
0.01 0.02 0.11 0.12 0.01 0.21 0.05 0.12 0.09 0.03 0.03 0.17 0.32 0.23 0.20 0.17
0.02 0.06 0.24 0.08 0.06 0.01 0.01 0.14 0.15 0.26 0.02 0.01 0.16 0.51 0.30 0.03
0.03 0.02 0.01 0.21 0.22 0.17 NA NA NA NA NA 0.02 0.25 0.43 0.57 0.36
0.05 0.06 0.03 0.07 0.02 0.06 0.18 0.30 0.10 0.16 0.04 0.22 0.04 0.07 0.21 0.16 0.05 0.10 0.01 0.08 NA 0.17 0.11 NA 0.11 0.13 NA 0.04 0.20 NA 0.00 0.05 NA 0.20 0.01 0.03 0.22 0.14 0.21 0.24 0.51 0.44 0.13 0.29 0.58 0.18 0.02 0.33
P
D
Coefficients in bold are significant at po0:05. T: mean temperature, P: total precipitation and D: Canadian Drought Code.
moisture availability for radial growth. These results are consistent with numerous studies showing that the response of Q. alba and Q. rubra is dominated by water balance in the early growing season (Jacobi and Tainter, 1988; Graumlich, 1993; Rubino and McCarthy, 2000; LeBlanc and Terrell, 2001; Terrell and LeBlanc, 2002; Tardif et al., in press). When looking at variations between species, both the negative correlation between radial growth and May temperature and the inverse one with July precipitation were slightly higher in Q. alba (Fig. 2a). July precipitation during the year prior to ring formation was more highly correlated with radial growth in Q. rubra (Figs. 2a and b). Both climate models performed well and correlation between the first two RDA axis scores and their estimated values were slightly higher when residual ring-width chronologies were used (Figs. 2c, d, e and f). The RDA results were also concordant with the Pearson correlations (Table 2). The residual ring-width chronologies had a higher number of significant correlations and the negative association with May temperature was better captured.
Ring width or event years? Our results support those of Weber (1995) who observed great similarity between ring-width series and those derived from skeleton plots. In our study, both ring-width and event-year chronologies adequately
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captured the extreme values in radial growth and both reflected essentially the same climate signal (Fig. 1). Compared to the development of ring-width chronologies, establishing event-year chronology is faster, it does not necessitate complex and expensive equipment and elaborated standardization procedures. When identifying narrow and large rings, the human eye and brain behave as a high-pass filter revealing the high-frequency signal in tree-rings (Cook and Briffa, 1990; Weber, 1995). Despite the dissimilarity in the approaches – ringwidth chronologies depict the mean radial growth of a stand at a time and the event-year chronologies provide an idea of the percentage number of trees affected by a given event in time (Weber, 1995) – both were found comparable in their ability to identify the climatic response of Q. alba and Q. rubra. In conclusion, our findings demonstrated that ringwidth and event-year chronologies were comparable in the extraction of the dominant climate signal in both oak species. This approach may, however, not be as successful when applied to material with weaker climatic signal (more complacent material) and more research with such material and/or species is needed (Weber, 1995). As with ring width, the portion of the signal due to endogenous/ exogenous disturbances also needs to be considered. In our data, no major episodes of sustained growth suppression were observed making it possible to make use of all negative and positive event years. The number of trees and sites to analyse may also be factors to consider when choosing to use event-year chronologies over the more commonly used ring-width ones. Our results indicated that PCA was an effective method of analysis and that sample size had a negligible impact on the analyses. Finally, we concur with Weber (1995), that the ability to recognize narrow and large rings may vary from one observer to the other despite establishing similar procedures and this variability also needs to be better quantified.
Acknowledgments Many thanks to field assistants P. Boivin, D. De´ry, J.-F. Dubuc, S. Grignon, L. Lauzon, M.-A. Martin and H. Williams. We thank M.-P. Girardin for calculating the Canadian Drought Code and P. Nantel and D. Gagnon for providing the wood samples. We thank P. Cherubini, C. Urbinati and an anonymous reviewer for their constructive comments on a previous draft of the manuscript. This research was supported by the Natural Sciences and Engineering Research Council of Canada and the University of Winnipeg.
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