Patterns and dynamics of tree-line response to climate change in the eastern Qilian Mountains, northwestern China

Patterns and dynamics of tree-line response to climate change in the eastern Qilian Mountains, northwestern China

Dendrochronologia 30 (2012) 121–126 Contents lists available at SciVerse ScienceDirect Dendrochronologia journal homepage: www.elsevier.de/dendro P...

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Dendrochronologia 30 (2012) 121–126

Contents lists available at SciVerse ScienceDirect

Dendrochronologia journal homepage: www.elsevier.de/dendro

Patterns and dynamics of tree-line response to climate change in the eastern Qilian Mountains, northwestern China Xiaohua Gou a,∗ , Fen Zhang a , Yang Deng a , Gregory J. Ettl b , Meixue Yang c , Linlin Gao a , Keyan Fang a a Research School of Arid Environment and Climate Change, Key Laboratory of West China’s Environmental System, Ministry of Education, Lanzhou University, Lanzhou 730000, PR China b Center for Sustainable Forestry at Pack Forest, School of Forest Resources, University of Washington, Box 352100, Seattle, WA 98195, USA c State Key Laboratory of Cryospheric Sciences, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, PR China

a r t i c l e

i n f o

Article history: Received 30 June 2010 Accepted 3 May 2011 Keywords: Dendrochronology Tree-line Age structure Tree density Climate change, Juniperus przewalskii

a b s t r a c t Tree-line ecotones are strongly climatically limited and serve as potential monitors of climate change. We employed annual growth increment from tree-rings, and tree density and age structure data derived from two Juniperus przewalskii tree-line sites in the eastern part of the Qilian Mountains, northeastern Tibetan Plateau, to detect the responses of tree growth and population dynamics to climate change. High temperature favors tree growth and is associated with increased tree density at tree-line, and an advance in tree-line position. Significantly positive correlations were found between ring-width and mean monthly air temperatures in current and previous June, July and August. Tree recruitment began to increase rapidly at the two sites after the Little Ice Age, but then decreased starting in the 1970s. The number of trees established coincides with temperature changes. The warming trend after the Little Ice Age favors increases of tree density and an advance of tree-line. The majority of trees established during the period of 1931–1970, which coincides well with the rapid radial growth of the trees. © 2011 Istituto Italiano di Dendrocronologia. Published by Elsevier GmbH. All rights reserved.

Introduction Global climate change and its impact on the environment are of serious concern, and it is thought that the dynamics of the tree-line are very sensitive to a change in climate (Holtmeier, 2009). In this paper, “tree-line” is applied to the transition zone extending from closed subalpine forests, to the uppermost stunted and usually scattered, individuals, regardless of their height (Holtmeier, 1981, 2003). Several studies show that treeline changes with latitude on global and regional scales. Jobbagy and Jackson (2000) demonstrated the importance of warm season temperature in limiting the position of alpine tree-line, and Malyshev (1993) the importance of July temperature in the position of the arctic–boreal ecotone. Tree-line ecotones are sensitive to climate change with increases in temperature being associated with an increase in tree density and tree-line position (Camarero and Gutiérrez, 2004; Fang et al., 2009a). Numerous studies have demonstrated climate-induced community level responses in treeline dynamics using climate–growth relationships and changes in stand structure and density at high-elevation tree-line ecotones (Harcombe, 1987; Liang et al., 2001; Wang et al., 2006;

∗ Corresponding author. Tel.: +86 0931 8915309; fax: +86 0931 8912330. E-mail address: [email protected] (X. Gou).

Pederson et al., 2008; Fang et al., 2009a). Tree-line advances to higher elevations in mountain areas in recent decades have been widely reported (Bradley and Jones, 1993; MacDonald et al., 1998; Camarero and Gutiérrez, 2004). In addition, many dendroecological studies have revealed that stand density also increases (Szeicz and Macdonald, 1995; MacDonald et al., 1998; Camarero and Gutiérrez, 2004) with increased recruitment in response to recent warming at tree-line (Kullman, 1986, 1990; Lavoie and Payette, 1994). However, the responses of tree-line to climatic change are likely complex and other studies have not found significant tree-line advances in response to recent warming trend (Lloyd et al., 2002; Dalen and Hofgaard, 2005; Goldblum and Rigg, 2005; Pfeifer et al., 2005; Wang et al., 2006). Tree-line responses to recent climate warming are based mainly on the study of tree growth and recruitment within these ecological boundaries using retrospective approaches that take advantage of information stored in tree rings (Tranquillini, 1979; Payette and Filion, 1985; Slatyer and Noble, 1992; Lescop-Sinclair and Payette, 1995; Paulsen et al., 2000). Since the 1990s, many tree-ring studies have been conducted in north central China (Liu et al., 2005; Gou et al., 2007, 2008a,b; Fang et al., 2009b; Shao et al., 2009) including tree-line studies in western China. Previous work has focused on the Taibai Mountains (Liu et al., 2003a), Wutai Mountains (Liu et al., 2003b), and Tianshan Mountains (Wang et al., 2006). To date, few studies have investigated tree-line responses to climate change in

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the Qilian Mountains (Fang et al., 2009a); however this area is an important climatic transition representing the northern boundary of the Tibet Plateau. Our study region located in the Qilian Mountains is little influenced by Asian monsoons and vegetation of this area is sensitive to changes in temperature and precipitation. In this study, we focus on the tree-line ecotone of Juniperus przewalskii forest to examine the spatial and temporal dynamics of the tree-line response to climate change by evaluating climate–growth relationships using tree rings, and tree age structure and tree density at tree-line. Materials and methods Study areas The Qilian Mountains (93.52–103.00◦ E, 36.50–39.50◦ N; Fig. 1) are located in the marginal areas of Asian monsoon, where the Chinese Loess Plateau meets the Tibetan Plateau. This mountain system is about 850 km long and 200–300 km wide with peaks over 4000 m a.s.l. The precipitation decreases from east to west and mainly occurs in the summer. The mean temperature is 0–5 ◦ C within the elevation of 2000–3000 m a.s.l. The dominant tree species in this region are Qilian juniper (J. przewalskii Kom.), Qinghai spruce (Picea crassifolia Kom.), aspen (Populus davidiana Dode), and birch (Betula platyphylla Suk.). Qilian juniper grows in open stands on dry, exposed slopes at elevations ranging from 2700 to 3400 m a.s.l. Forest soils are typically montane, brownish grey, and subjected to serious erosion where not protected by vegetation cover (Liu et al., 2005). Sampling strategy and dendrochronological methods Field measurements and sampling were carried out in August 2008 in the Shiyang river basin, the eastern part of the Qilian Mountains. The tree-ring samples were collected at sites JinDongGou (JDGs: JDG01, 101◦ 37 17 E, 37◦ 43 52 N, 3558–3680 m a.s.l.; JDG02, 101◦ 37 18 E, 37◦ 43 52 N, 3592–3700 m a.s.l.) from living J. przewalskii trees generally growing on steep south-facing slopes (Fig. 1). Two rectangular plots (35 m × 160 m at JDG01 site; 30 m × 120 m at JDG02 site) were established at each site in topographically uniform parts of the tree-line ecotones. The two rectangular plots had their longer side (120 or 160 m), y axis, parallel to maximum slope

and included current tree-line, and the x (short) axis (30 or 35 m) follows the altitudinal gradient upslope. Tree locations (x and y coordinates) and size (diameter at cored height as close to the ground as possible) were recorded in the field for individual J. przewalskii trees within the plot. Individuals with heights less than or equal to 0.5 m were regarded as seedlings and were not sampled. One to two tree cores were extracted from trees over 0.5 m in each plot. At site JDG01, 160 cores (from 80 trees) were collected and the position of 167 trees was recorded within the plot. At site JDG02, 77 cores (from 37 trees) were collected and the position of 50 trees was recorded. All cores were mounted, air dried, sanded and cross-dated using standard dendrochronological methodology (Stokes and Smiley, 1968). The rings were counted, and visually cross-dated; the ring widths were then measured to 0.001 mm precision using Velmex TBA. Cross-dated series were verified using the cross-dating program COFECHA (Holmes, 1983). In this study, we only included trees older than 100 years to develop a chronology. Age-related trend in growth was removed conservatively from raw series by fitting either a straight line or a negative exponential curve with the program ARSTAN (Cook and Holmes, 1986). For some tree-ring series, this conservative approach left substantial decadal variation in growth which was removed by fitting a conservative cubic spline equal to 67% of the series length spline functions. Thirty-four detrended cores representing 19 trees were used to produce mean standard chronologies (STD) using a bi-weight mean calculation (Cook and Holmes, 1986). Increment cores sometimes failed to reach the pith of the tree because of incorrect borer alignment, eccentric growth rings or rotten tree centers. We adopted the Initial Radial Growth model of Rozas (2003) in order to extrapolate the ages for the missing portion of tree cores. The model is based on the assumption that the growth of individuals of the same species from a region is similar. Finally, a linear multiple regression function was used to predict the number of rings in the missing radius from the length of missing radius and the mean growing rate of rings adjacent to the pith as predictors. In addition, we adopted Duncan’s geometrical model to estimate the length of the missing radius (Duncan, 1989). We established the age–diameter relationships at the cored height to estimate the J. przewalskii ages. A regression of tree diameter at the cored height and age was developed from 79 cores to estimate the ages of all trees which were too young to be sampled in the plots (Fig. 2). Cores were then sorted into age groups of 10-year intervals (Fig. 4a and b).

Results and discussion Radial growth and its climate associations

Fig. 1. Locations of the sampling sites (JDG01, JDG02) and meteorological stations along the Qilian Mountains.

Meteorological data from Wuwei meteorological station, which is about 100 km away from the sampling sites, was used in analyses (Fig. 1). Correlation coefficients were calculated to quantify relationships between tree-ring chronologies and monthly mean air temperature and monthly precipitation from 1961 to 2004. Tree growth can be influenced by climate conditions in previous and current years (Fritts, 1976), and therefore correlation analysis was performed from June of the previous year to September of the current year. Climate–growth correlations indicate growth was mainly limited by monthly mean air temperature with positive temperature– growth correlations for all months (Fig. 3). The mean air temperature in the summer season (June–August) was significantly positively correlated with ring-width indices, especially for current June (r = 0.543, p < 0.01). No significant correlations were found

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Fig. 2. Select 78 cores of accurate age at JDG01 site to calculate the relationship between tree age and the diameter of the trunk at cored height of a Juniperus przewalskii population at the tree-line ecotone in the eastern part of the Qilian Mountains.

between ring-width indices and precipitation except for both previous and current September (Fig. 3). This result suggests that precipitation is less influential on tree growth at tree-line than temperature, and the summer mean air temperature is the major limiting factor for growth at tree-line. Previous studies carried out at the higher elevations also showed that the radial growth had higher correlations with temperature than precipitation (Liu et al., 2005).

Fig. 4. Comparison of age structure variations of trees at the tree-line ecotones in eastern (a and b) and middle (c) of the Qilian Mountains with temperature variations in the northern hemisphere (d) (D’Arrigo et al., 2006). (a) Age structure of 167 trees from the JDG01 site (35 m × 160 m) at tree-line. (b) Age structure of 50 trees from the JDG02 site (30 m × 120 m) at tree-line. (c) Age structure of 58 trees from the JDG01 site (20 m × 40 m) at tree-line (Fang et al., 2009a). (d) Northern hemisphere temperature (D’Arrigo et al., 2006).

Tree-line dynamics and climate change

Fig. 3. Correlation coefficients between the chronology and monthly mean air temperatures (a) and precipitation (b) from previous June (P6) to current September (9) at Wuwei meteorological station (1961–2004).

Kullman (1991) demonstrated that detailed analysis of the age structure of a stand can provide a fairly accurate picture of temporal variation in recruitment. There are less than 50 years of temperature observations for this area; however this is the best available data. Fang et al. (2009a) demonstrated that temperature change in the Qilian Mountains is consistent with the northern hemisphere temperature record on the whole. Therefore we chose the northern hemisphere temperature reconstruction (D’Arrigo et al., 2006) to compare the age structure variations of trees at tree-line ecotone in this study. The age structure of the J. przewalskii forest growing at tree-line showed that the appearance of trees goes back to the 19th century at site JDG01 and back to the 16th century at site JDG02 (Fig. 4). However, a very limited number of trees were found before the 1890s. Tree recruitment began to increase rapidly at the two sites in the 1890s (Fig. 4), with the most recruitment in the 1930s and 1950s. Tree recruitment began to decrease in the 1970s to the present, and although our methods precluded looking for small seedlings, we believe this decrease in establishment may also represent a lower establishment from peak periods of the 1930s and 1950s. In fact, the warm episode in the study region may favor tree germination as more trees germinated in a relatively warm period in the 1920s–1960s, as indicated by reconstructed temperature for northern hemisphere (D’Arrigo et al., 2006; Liu et al., 2007). Our previous research shows similar results (Fang et al., 2009a). Tree recruitment almost stopped in the period of the Little Ice Age, which would be consistent with cold conditions. In contrast the late 19th century shows a rapid temperature increase. Increased moisture availability and high temperature can promote the faster growth (Black and Bliss, 1980; Kullman, 1983), which

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Fig. 5. Spatiotemporal variability in tree density and tree-line position at site JDG01. The figure shows the same plot (35 m × 160 m; the y axis follows the altitudinal gradient upslope) during the different time periods (before1850, 1850–1890, 1891–1930, 1931–1970, 1971–2008). Each filled black symbol represents an individual that established during the specific period indicated above and unfilled symbols represent trees established during the corresponded previous period. Different symbols represent different periods.

is consistent with greater seedling establishment and survival, as indicated by rapid increase in recruitment in the two sites since the 1890s. In addition, the existence of early 20th century J. przewalskii trees may have improved the micro-environmental conditions for

tree growth during the warm period, facilitating establishment and survival of more trees, and expanding the tree-line ecotone since the end of the Little Ice Age, especially during the warm period of 1920s–1960s.

Fig. 6. Spatiotemporal variability in tree density and tree-line position at site JDG02. The figure shows the same plot (30 m × 120 m; the y axis follows the altitudinal gradient upslope) during the different time periods (before 1890, 1891–1930, 1931–1970, 1971–2008). Each filled black symbol represents an individual that established during the specific period indicated above and unfilled symbols represent trees established during the corresponded previous period. Different symbols represent different periods.

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Very few tree recruits were found in the sampling plots before the Little Ice Age, then the number of trees increased accompanied with the increasing temperature. It is important to note that trees less than 20 years old were not counted, as they are much smaller than bushes and it is hard to determine their exact ages. Therefore this work does not apply to tree-line dynamics after the 1990s. This ecological process of expanding tree-line dynamics is consistent with previous results in the Central Qilian Mountains where temperature plays an important role in shaping tree-line dynamics (Fang et al., 2009a). Some differences in the generation periods of trees at the three sites of Qilian Mountain might be related to the varying site-specific factors. The temperature limitation on tree-line trees in the Qilian Mountains is similar to the results of Northern Quebec (Payette and Filion, 1985), Churchill (Scott et al., 1987), Mackenzie Mountains (Szeicz and Macdonald, 1995), and Seward Peninsula tree-line (Lloyd et al., 2002). Spatiotemporal variability in tree density and tree-line position We found spatiotemporal changes in tree-line at both sites (Figs. 5 and 6). A clear increase in tree density through time and the advances of the tree-line position, especially after 1895, further support the influence of temperature on tree-line dynamics (Figs. 5 and 6). Tree density is very low during the period of the Little Ice Age. There has been an increase in tree germination and density within the ecotones since the 1890s, especially during the period

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of 1931–1970; at least 65.6% of the seedlings germinated in this period at JDG01 and 50% of the seedlings germinated in this period at JDG02 (Fig. 7b). The tree density increased along the length of plot with increasing elevation, instead of only increasing at the highest point. However, the tree recruitment decreased in the last 20–30 years, which coincides well with the decrease of tree growth when the temperature decreased in 1970s–2000s (D’Arrigo et al., 2006). Second, the tree-line ascended greatly in the JDG01 sites during the late 19th and early 20th centuries (Fig. 5); and at the JDG02 sites the tree-line increased at all times (Fig. 6). The tree density and tree-line position of the two sites increased significantly during the period of 1891–1970. The tree density reached the maximum value in the two sites during the period of 1971–2008, and there are 275 trees/ha and 138 trees/ha respectively (Fig. 7a), but fewer trees were added after 1971 (Fig. 7b). The oldest tree in the JDG01 sites germinated prior to 1848 (Fig. 5), and in the JDG02 sites germinated prior to 1888 (Fig. 6). In summary, density and tree-line position progressed rapidly after the Little Ice Age, especially during the warm period 1931–1970. This coincides well with the rapid radial growth of the trees.

Conclusions We investigated the response of J. przewalskii tree radial growth, tree density and age structure at high-elevation tree-line to climate change in the eastern part of the Qilian Mountains, northwestern China. Temperature was the most important limiting factor of tree growth at tree-line, with June, July, and August (i.e. summer) temperature significantly and positively related to tree growth in both the current and previous growing season. Tree recruitment began to increase rapidly at two sites since the 1890s, particularly in the 1930s and 1950s, and recruitment began to decrease after 1970. The tree density and tree-line position progressed very rapidly after the Little Ice Age, especially during the warm period of 1931–1970. Tree density increase and the tree-line position advance further demonstrate the influence of temperature on tree-line dynamics.

Acknowledgements This research was supported by the National Basic Research Program of China (973 Program) (No. 2009CB421306), National Science Foundation of China (No. 40971119), the NSFC Innovation Team Project (No. 41021091), the Chinese 111 Project (B06026), and the One Hundred Talents Program of CAS (Grant No. 29O827B11).

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Fig. 7. The tree density (a) and percentage distribution pattern of new trees in the plot (b) of the Juniperus przewalskii population at the tree-line ecotone in the Qilian Mountains.

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