The increasing frequency and severity of extreme weather events, especially droughts, arising from on-going climate changes negatively affect productivity and stability of forest ecosystems. Understanding species responses and suitable ecotypes that are able of adapting to new environmental conditions is increasingly important. The objective of this study was to quantify the relationships between the inter-annual stem circumference increase (SCI) of five European beech (
European beech (
Monitoring the dynamics of cambial activity and the development of woody cells (
Adaptive phenotypic plasticity enables plants to respond to environmental variability and is likely to buffer the impacts of climate change (
The primary objective of this study was to identify the main environmental factors, especially soil water availability and meteorological variables, that are linked to circumference increase dynamics in five central European beech provenances during three growing seasons. We hypothesized that: (1) weather fluctuations are reflected in seasonal circumference increases and that there are changes in their effects during the growing season; and (2) provenances differ in stem circumference increase.
This study is based on a provenance experiment with European beech established under the coordination of the Federal Forest Research Centre at the Institute of Forest Genetics in Grosshansdorf, Germany and was composed of 23 trials. The Slovak trial, located at Tále near the town of Zvolen in central Slovakia (
Out of each of five European provenances (
where
Meteorological conditions were continuously monitored in an open plot in the center of the provenance plot. The conditions included air temperature (°C), relative humidity (%), global incoming solar radiation (W m-2 - Minikin TH®, EMS, Brno, CZ) and rainfall (mm - MetOne 370®, Oregon, USA). The measurements of soil water potential (
Continentality was calculated as a simple index of continentality (
where T
The data of long term temperature averages for the
To calculate the average daily and weekly values used in seasonal growth dynamic analyses, the hourly meteo and
The changes in stem circumference were monitored using automatic band dendrometers (DRL, 26 application for small stems, EMS, Brno, CZ), which were non-invasively fixed to the trees at a height of 1.3 m. The hourly mean values were derived from measurements taken at 20-minute intervals. We calculated the daily stem circumference increase (SCI), extracted at 6 AM during the expansion phase of diurnal changes (
Cumulative daily and weekly SCI (growth curves) were fitted by the Gompertz (
where
The SASB growth function below was designed and long-term tested by EMS Brno in its software Mini32 (
where (
and
The first derivatives of these functions were used for comparing extracted daily and weekly SCI values with theoretical incremental processes during the seasons.
To analyze the main factors controlling circumference growth and changes and their effects during the season, we used an intra-seasonal moving correlation function (
From the chronologies of circumference increments (
Additionally, the predictors were selected in the same way (daily or average weekly) minimal temperature (AT_min), daily (or average weekly) maximal temperature (AT_max), absolute weekly minimal temperature (AT_min a), absolute weekly maximal temperature (AT_max a), average daily (or weekly) temperature on an actual day (or week) (AT_avg), average weekly temperature one day (or week) preceding the actual day (or week - AT_p1), average daily (or weekly) temperature two days (or weeks) preceding the actual day (or week - AT_p2), average daily (or weekly) temperature three days (or weeks) preceding the actual day (or week - AT_p3), average daily (or weekly) air humidity (AH), average daily (or weekly) radiation (R), precipitation amount on the actual day (or week) (Pr), daily (or weekly) precipitation amount one day (or week) preceding the actual day (or week - Pr_p1), daily (or weekly) precipitation amount two days (or weeks) preceding the actual day (or week - Pr_p2), daily (or weekly) precipitation amount three days (or weeks) preceding the actual day (or week - Pr_p3), average daily (or weekly) soil water potential (
The SCI chronologies were correlated with predictors. After this time, the windows were shifted 4 or 5 weeks (firstly to the period from May 1 to July 3 etc. -
Statistical analyses were performed using the statistical software Statistica® (Statsoft, Tulsa, OK, USA). Data were tested for normal distribution using Shapiro-Wilk’s W test. The significance of differences between the average values of annual SCI (Fig. S3 in Supplementary material) were tested using the Student’s
Intra-seasonal moving correlation functions (
Relations between 2012-2014 SCI and initial circumference, Hegyi competition index and continentality index mentioned above were calculated using Pearson’s correlation coefficients.
While the second half of March and the beginning of April were relatively warm in 2012 and 2014, a long winter followed, lasting from December 2012 to 2013 (
The subsequent growing seasons of 2012 and 2013 showed above average temperatures, including heat waves followed by some colder periods. There were no heat waves during 2014. Of particular contrast were the August temperatures of 3.3 °C and 3.5 °C higher than average in 2012 and 2013, respectively, compared to 2014. July and August 2014 had abundant precipitation (264 mm - Fig. S2b in Supplementary material) in contrast to the previous growing seasons, when 124 and 102 mm were recorded in 2012 and 2013, respectively.
These facts were reflected in decreased soil water potential (
The results indicate that all five provenances grew synchronously with high inter-correlations among them during a particular growing season (
Although in 2014 we registered the first SCI already between the weeks of April 17th - April 24th - May 1st, generally the “major growth period” began in the weeks between May 1st (
The selected groups of trees from individual provenances were homogeneous in their initial circumference values in 2012 (Fig. S4 in Supplementary material). No relationship was revealed between the initial circumferences and the 2012-2014 SCI (R2 = 0.000, P = 0.985) nor did one occur between the SCI and the Hegyi competition index (R2 = 0.000, P = 0.996).
The intra-seasonal moving correlation function results indicate distinct seasonal variability in the influence from particular factors (
At the beginning of the season, day length (DL) was the main factor promoting the increment on both time scales (
In the second examined period, DL was again the main influencing factor (
In the third period, the influence of DL disappeared, as it was near the summer solstice (
During the fourth period, the correlations between SCI and DL were restored (
In the fifth period, DL remained a positively influence on the daily and weekly SCI (
Overall, the largest differences between years were recorded in August, when individual provenances in 2013 formed only from 8 to 15% of the SCI in 2014, and from 41 to 52 % in 2012. The lack of precipitation and subsequent drought were manifested already in July in 2013, when the provenances formed from 44 to 60% of the SCI in 2014.
During all of the examined periods, the period between June 5th and August 7th was the most important for SCI formation when 75% to 78% of the total SCI for 2012-2014 was created.
We recorded a negative linear relationship (R2 = 0.91, P = 0.012) between the 2012-2014 SCI of the individual provenances and the absolute difference in continentality among the sites of origin and the Tále experimental plot.
The weekly SCI were more linked to the theoretical incremental processes described by the first derivatives of the Gompertz (
The changes in tree stem size registered by dendrometers represent a complex mix of different environmental variables. Two basic components affect stem circumference (diameter, radius): the seasonal growth of stem tissues and variations in stem tissue water balance. Reversible changes are related to the fact that plants temporarily use water stored in tissues (
Furthermore, we compared the daily and weekly SCI for seasonal dynamics analyses. According to
Hence, we believe that daily and particularly weekly SCI presented in young beech trees are appropriate proxies for studying intra-seasonal incremental processes.
Seasonal SCI of young beech trees is thus mainly linked to growth processes, consisting principally of two basic phases of cambial activity (cell division and enlargement) in the process of new tree-ring formation.
The long-term seasonal tree-growth biorhythm is partially synchronized with the photoperiod, not only because of its effects on basic physiological and growth processes (
Various research papers (
Correlations indicate that during the summer, the effect of temperatures weakened (
Nevertheless, precipitation and soil water potential affected the SCI most significantly during the summer months (
Drought can seriously affect the physiological and growth reactions of young beech trees (
Differences in the amount of SCI over the whole seasons among provenances were linked to differences between the continentality of sites of origin and provenance plot at the Tále site. A comparison of SCI with the summer heat moisture index (
The results indicated that stem circumference increase among all five provenances responded synchronously to weather conditions on a daily and weekly scale, with high inter-correlations among them during individual growing seasons. The photoperiod had a synchronizing effect on the seasonal culmination of SCI, which is a sign of tree adaptation to long-term seasonal variations in climate. Temperature was the most significant weather factor influencing the circumference increase dynamics at the beginning of the season and during the summer when soil water potential was high. During summer months, precipitation deficits, heat waves and consequently decreased soil water potential significantly affected the stem circumference increase of young beech trees, despite the fact that the provenance plot was situated in an area of optimal beech growth. While on a daily scale only precipitation on the actual day positively affected SCI, on a weekly scale precipitation in previous weeks was also important. Not only severity but also timing and duration of drought within the season were important. Within all seasons, the lowest increment was recorded at the provenance from the lowest altitude and the most oceanic climate (northern Germany).
A comparison of daily and weekly SCI values with the first derivatives of growth functions indicated that the weekly SCIs were closely related to theoretical incremental processes, suggesting that they can be recommended as appropriate proxy for studying intra-seasonal incremental processes in European beech.
The following abbreviations are used throughout the paper:
AT_min: daily (or average weekly) minimal temperature
AT_max: daily (or average weekly) maximal temperature
AT_min a: absolute weekly minimal temperature
AT_max a: absolute weekly maximal temperature
AT_avg: average daily (or weekly) temperature on an actual day (or week)
AT_p1: average weekly temperature one day (or week) preceding the actual day (or week)
AT_p2: average daily (or weekly) temperature two days (or weeks) preceding the actual day (or week)
AT_p3: average daily (or weekly) temperature three days (or weeks) preceding the actual day (or week)
AH: average daily (or weekly) air humidity
R: average daily (or weekly) radiation
Pr: precipitation amount on an actual day (or week)
Pr_p1: daily (or weekly) precipitation amount one day (or week) preceding the actual day (or week)
Pr_p2: daily (or weekly) precipitation amount two days (or weeks) preceding the actual day (or week)
Pr_p3: precipitation amount three days (or weeks) preceding the actual day (or week)
DL: average daily (or weekly) weekly day length
This work was supported by the Slovak Research and Development Agency (Contracts APVV 0135-12, APVV 0480-12) and the Grant Agency of the Ministry of Education and the Slovak Academy of Sciences (VEGA 0218-12, VEGA 0034-14 50 %).
The method of daily stem circumference increase (SCI) extraction. Seasonal curves of 1h stem circumference changes (a), rectangle indicates the part shown in detail (b), where: open grey circles represent 1 h circumferences, black line with solid black circles represents seasonal SCI at 6 CET in the morning which is situated on the plateau of expansion phase during the sunny days. During days when morning 6 CET circumferences were smaller than previous morning 6 CET maximum on the curve of stem circumferences, the previous maximum was used instead of them. Daily SCIs (c) represent the difference between two consecutive days on the curve of seasonal SCI in part b.
Seasonal dynamics of daily environmental variables and SCI. Average daily air temperature during 2012-2014 (a), average daily precipitation amounts (black bars) and average daily soil water potential (grey lines, vertical lines represent 95% confidence intervals) during 2012-2014 (b), average daily SCI of individual provenances (codes A-E are in
Seasonal dynamics of weekly SCI. Average weekly SCI of individual provenances (a-e) in 2012 (bold dark-grey), 2013 (bold light-grey) and 2014 (fine black). Vertical lines represent 95% confidence intervals.
Results of intra-seasonal moving correlation functions. Correlations between daily SCI of individual provenances (codes A-E are in
Results of intra-seasonal moving correlation functions. Correlations between weekly SCI of individual provenances (codes A-E are in
Average daily (left, black dashed line) and weekly (right, black line with black circles) SCI of all studied trees (n=30) during 2012-2014 and their fit to the first derivatives of Gompertz (light grey) and SASB (dark grey) functions. R2 represent R squared between daily and weekly SCI and the first derivatives of growth functions; the date represent the date of culmination (day or week ending by day).
Site information for the provenances used in the experiment and the experimental plot Tále. (T): long-term average yearly temperature; (Pr): long-term average yearly precipitation amount; (Ic): index of continentality.
Code | Location | Country | Latitude | Longitude | Elevation(m a.s.l.) | T(°C) | Pr(mm) | Ic(°C) |
---|---|---|---|---|---|---|---|---|
A | Postojna Javor | Slovenia | 14° 21′ N | 45° 44′ E | 1040 | 7.8 | 946 | 18.7 |
B | Jaworze | Poland | 19° 10′ N | 49° 50′ E | 450 | 6.9 | 903 | 21.7 |
C | Farchaus | Germany | 10° 40′ N | 53° 39′ E | 55 | 8.2 | 683 | 17.7 |
D | Belzig | Germany | 12° 25′ N | 52° 03′ E | 140 | 8.7 | 557 | 18.4 |
E | Eisenerz | Austria | 14° 51′ N | 47° 32′ E | 1100 | 4.2 | 1168 | 19.5 |
- | Tále | Slovakia | 18° 59′ N | 48° 38′ E | 810 | 5.7 | 905 | 20.5 |
Descriptive statistics of the beech trees at the five locations. Diameter at breast height (DBH) in spring 2012 and height in autumn 2014.
Location | Mean DBH± STD (cm) | DBH range(cm) | Mean height± STD (m) | Height range(m) |
---|---|---|---|---|
Postojna Javor | 5.7 ± 1.1 | 4.4 - 7.4 | 7.0 ± 0.7 | 6.00 - 7.50 |
Jaworze | 5.8 ± 0.6 | 5.3 - 7.0 | 6.9 ± 0.2 | 6.75 - 7.25 |
Farchaus | 6.4 ± 1.3 | 5.3 - 8.0 | 6.9 ± 0.4 | 6.50 - 7.50 |
Belzig | 6.6 ± 0.9 | 4.8 - 7.1 | 6.8 ± 0.5 | 6.50 - 7.50 |
Eisenerz | 5.9 ± 1.0 | 4.7 - 7.3 | 6.9 ± 0.6 | 6.00 - 7.50 |
Fig. S1 - Geographic origin of the provenances used in the experiment (circles) and location of the Tále experimental plot (square).
Fig. S2 - Temperature and precipitation anomalies relative to the long term average according to WorldClim (Hijmans et al. 2005) in 2012 (dark grey), 2013 (light grey) and 2014 (black).
Fig. S3 - Average values of annual SCI, relative to the inital circumference, of the five provenances in 2012 (dark grey), 2013 (light grey) and 2014 (black).
Fig. S4 - Average values of initial stem circumferences of selected trees in 2012. Vertical lines represent 95% confidence intervals.