The growth of trees is controlled by genetic factors and natural environment. Multiple climatic factors of the growth environment directly influence the development of tree rings (Esper
Tree-ring samples in the Greater Higgnan Mountains have been systematically collected since the year 2000 (He
Given the above, the purposes of this study are to (1) develop tree-ring chronologies for the southern Greater Higgnan Mountains, (2) explore the climate controls of radial growth of larch trees, (3) and statistically assess signals inherent in a newly developed regional tree-ring chronology.
The Greater Higgnan Mountains, extending more than 1200 km in lengthways direction and 200–300 km in sideways direction, are on the northeastern Asian continent. These huge mountain ranges merge with the Stanovoy Mountains in the north and their southern extent meets the eastern Ortindag Sand Land. Our sampling targeted the southern Greater Higgnan Mountains (Fig. 1a). The tree species studied was the larch (
Information on sampling sites.Site code Latitude (N) Longitude (E) Number of trees/cores Elevation (m) Aspect Slope Maximum tree-age The rate of absent rings (%) BYH 44.44° 118.85° 21/42 ~1530 NW 30° 224 (1791–2014) 0.24 QMG 44.20° 118.77° 20/40 ~1310 NW 25° 102 (1913–2014) 0.36
According to standard dendrochronological techniques (Speer, 2010), the sampled tree-ring cores were dried naturally and mounted on a wooden plank with grooves. Then, each tree-ring core was sanded with abrasive papers and marked with needles under a microscope. Every ring on the sanded tree-ring cores was measured by a Velmex Measuring System at resolution 0.001 mm. The COFECHA and ARSTAN programs were run to control cross-dating quality and develop chronologies (Grissino-Mayer, 2001; Cook and Krusic, 2005). A negative exponential function was executed for tree-ring width series detrending. Then, all individual detrended ring-width series were combined into a single chronology by computing a bi-weight robust mean. Eventually, standardized, residual and autoregressive standardized tree-ring chronologies were obtained (Cook and Kairiukstis, 1990). The reliability of the tree-ring chronology was evaluated by an expressed population signal (EPS) (Wigley
For calibration, we selected monthly precipitation and mean temperature at the Balinzuoqi (119°24′E, 43°59′N, 485.9 m a.s.l., 1955–2012), Xiwuzhumuqinqi (117°36′E, 44°35′N, 996.6 m a.s.l., 1955–2012) and Linxi (118°04′E, 43°36′N, 800.3 m a.s.l., 1955–2012) meteorological stations, and monthly 118.25°E–44.25°N Palmer Drought Severity Index (PDSI), which is derived from a Climatic Research Unit (CRU) self-calibrating PDSI dataset (Mitchell and Jones, 2005). The above climatic data were acquired from the China Monthly Surface Climatological Database (NMIC, 2008) and Royal Netherlands Meteorological Institute Climate Explorer, respectively.
Fig. 2 shows that the highest temperature periods were in summer (June–August) in the study area, with peaks in July. June–August precipitation comprises the major portion of annual rainfall, with maximum precipitation in July. Climate data recorded since 1955 show a significant increasing trend of annual mean temperature in the study area, but a decreasing trend of annual precipitation is not significant. Fig. 3a reveals that the driest period peaks in August (PDSI of –0.63), and the wettest month is in April (–0.28). And Fig. 3b shows that the decreasing trend of annual PDSI is not significant. Furthermore, correlation coefficients of the annual precipitation and mean temperature from the three meteorological stations are all significant in the original and first differences domain (Table 2). Owing to their similar monthly and annual variations, simple averaging was done on the instrumental data from those meteorological stations to obtain overall climatic conditions in the study area.
Coherence among annual total precipitation and annual mean temperature from three meteorological stations over the common period 1955–2012. Correlation coefficients are listed. Results for the original and first differences filtered climatic data are shown. Significant at Significant at Significant at Significant at Significant at Significant at Significant at Significant at Significant at Significant at Significant at Significant at Original ( Annual total precipitation Annual mean temperature Balinzuoqi Xiwuzhumuqinqi Linxi Balinzuoqi Xiwuzhumuqinqi Linxi Balinzuoqi / 0.599 0.638 / / / Annual total precipitation Xiwuzhumuqinqi / / 0.646 / / / Linxi / / / / / / Balinzuoqi / / / / 0.904 0.947 Annual mean temperature Xiwuzhumuqinqi / / / / / 0.950 Linxi / / / / / /
A 13-year reciprocal filter was used to decompose the newly developed tree-ring width chronologies into high- and low-frequency domains (Yuan
A standardized chronology not only contains common variations among each tree-ring series but also retains high- and low-frequency common variance (Cook, 1985). Thus, the standardized chronologies of two sampling sites were used in the following analyses. Because of the weak correlations between subsequences from each tree-ring width series and the master series, 10 cores from 9 trees at the BYH and QMG sites were not used to develop chronologies. Thus, the BYH and QMG chronologies were developed based on 38 cores from 20 trees and 34 tree-ring cores from 20 larch trees, respectively. The BYH and QMG chronologies are displayed with their EPS values in Fig. 4. Statistics of these chronologies for a common period analysis of 1950 to 2010 are listed in Table 3.
Statistics of chronologies from two sampling sites (BYH and QMG) and regional chronology (SGH) over common period 1950–2010.Statistic BYH QMG SGH Standard deviation (SD) 0.35 0.38 0.35 Mean sensitivity (MS) 0.33 0.30 0.32 First-order autocorrelation (AC1) 0.46 0.60 0.44 Interseries correlation (trees) 0.40 0.47 0.33 Interseries correlation (all series) 0.41 0.48 0.34 Mean within-tree correlation 0.82 0.70 0.79 Signal-to-noise ratio (SNR) 19.95 17.81 25.14 Expressed population signal (EPS) 0.95 0.95 0.96 The first principal component (PC#1) 0.44 0.52 0.37
Both tree-ring width chronologies were decomposed into high- and low-pass components using 13-year reciprocal filters. Next, Pearson correlation was performed on three sets of data,
Coherence among chronologies from two sampling sites over common period 1950–2014. Correlation coefficients are listed. Results for the original, high- and low-pass filtered chronologies are shown.Original High-frequency Low-frequency 0.572 0.681 0.501 < 0.001 < 0.001 < 0.001 65 53 53
The main descriptive statistics of this regional chronology are listed in Table 3. Values of standard deviation (0.35) and mean sensitivity (0.32), indicators of climatic signals inherent in the regional chronology, are similar to those of chronologies from a single sample site. The first-order autocorrelation estimates relationships between present tree rings and growth in a previous year. These values (from 0.44 to 0.60) indicate that the chronologies contain low-frequency variance caused by climate and tree-physiological lag effects. These interseries correlations of the SGH chronology are relatively weak, owing to an increase of sample depth from two individual sites. EPS values exceeding 0.85 reveal that the credible regional chronology spans 185 years (1830–2014). Ten highest values of the SGH chronology are in 1848 (1.957), 1837 (1.881), 1876 (1.829), 1977 (1.807), 1836 (1.767), 1838 (1.655), 2014 (1.654), 1921 (1.617), 1874 (1.606) and 1978 (1.598), and ten lowest values are in 1981 (0.019), 1942 (0.087), 1961 (0.136), 1939 (0.193), 1907 (0.219), 1886 (0.392), 2000 (0.441), 1883 (0.455), 1924 (0.466) and 1922 (0.479).
The high AC1 values of two individual and one composite chronologies (0.46, 0.60, and 0.44, respectively) indicates a significant biological lag effect in the process of tree growth (Table 3). Thus, average meteorological data of the previous August–December and current January–October during 1955–2012 were selected to evaluate how variations of precipitation and temperature influenced the radial growth of larch trees in the southern Greater Higgnan Mountains.
The results of correlation (Fig. 5) indicate that the relationship between ring width and precipitation was generally positive, and a significant correlation coefficient was found for August of the previous year (
The photosynthetic optimum temperature for evergreen conifer ranges from 10°C to 25°C. Photosynthesis in these conifer trees may cease at temperatures below –3°C to –5°C or above 35°C to 42°C (Wang, 2000). Fig. 2j reveals that the mean temperature from April to October changed from 6.0°C to 4.9°C, and those in March and November were –4.5°C and –5.5°C, respectively. Therefore, April–October has been regarded as the growth season of larch trees in the study area. Furthermore, Li
Studies of conifers and the relationship between treering width and climate in arid and semiarid locations have gradually demonstrated that ring-width growth is not only influenced by climate during the growing season but also that in autumn, winter, and spring prior to the growing season (Kitin
Temperature always affects the radial growth of trees by modulating the amount of soil moisture in arid and semiarid areas (Zhang
The significant positive correlations between the radial growth of trees and PDSI demonstrate the primary combined influence of precipitation and mean temperature. Greater moisture from the previous August to current June may reduce water stress and benefit cambial cell division in the rapid growth season. Thus, the positive relationship with rainfall, negative response to temperature, and positive correlations with PDSI indicate that moisture was the main climatic limitation on tree-ring development of larch trees in the study area. The above results show that the influence of moisture on tree-ring growth in the southern Greater Higgnan Mountains is the same as indicated by dendroclimatic studies of northern China, such as
The spatial correlation was determined to evaluate regional significance of the tree-ring width series. The PDSI periods were used in the spatial correlation based on the results of correlation analysis mentioned above. The results show that the SGH chronology is correlated (< 0.3) with the August–June gridded PDSI data for the eastern Mongolian Plateau and Nuluerhu Mountains during the period 1955–2012 (Fig. 6). This suggests that the radial growth of trees in the study area not only reflect local climate change but also contain large-scale climatic signals.
A May–July PDSI reconstruction for the Ortindag Sand Land based on tree-ring width (Liang
The SGH chronology is positively correlated with the PDSI reconstruction over the common period 1847–2004, at the 99.9% confidence level (
A 185-year regional tree-ring width chronology was developed using 41 living larch trees selected from two sampling sites in the southern Greater Higgnan Mountains. The relationship between precipitation and tree growth was generally positive, but correlations between monthly mean temperature and the regional chronology are mostly negative. The results of tree growth climate response revealed that moisture was the main climatic limitation on the radial growth of larch trees at the sampling sites. The analyses of spatial correlation reveal positive correlations between the regional chronology and gridded PDSI dataset for the Nuluerhu Mountains and eastern Mongolian Plateau. The comparison between the regional chronology and May–July PDSI reconstruction for Ortindag Sand Land indicates that the radial growth of larch trees in the southern Greater Higgnan Mountains and moisture variations in adjacent areas were roughly synchronous over the last nearly 160 years, especially in the low-frequency domain. Furthermore, two lowest values in the newly developed chronology coincided with a severe and sustained drought in the 1920s across a wide area of northern China.