Received: 1 August 2017
|
Accepted: 5 October 2017
DOI: 10.1111/gcb.13963
PRIMARY RESEARCH ARTICLE
Warming-induced upward migration of the alpine treeline in the Changbai Mountains, northeast China € ntgen2,4,5,6 | Yue Yang1 | Lei Wang1,7 | Haibo Du1 | Jie Liu1 | Mai-He Li2,3 | Ulf Bu Zhengfang Wu1 | Hong S. He1,8 1
School of Geographical Sciences, Northeast Normal University, Changchun, China
Abstract Treeline responses to environmental changes describe an important phenomenon in
2
Swiss Federal Research Institute WSL, Birmensdorf, Switzerland
global change research. Often conflicting results and generally too short observa-
3
tions are, however, still challenging our understanding of climate-induced treeline
Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, China 4
Department of Geography, University of Cambridge, Cambridge, UK 5 Department of Geography, Masaryk University, Brno, Czech Republic 6
Global Change Research Institute CAS, Brno, Czech Republic 7 Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China 8
School of Natural Resources, University of Missouri, Columbia, MO, USA
dynamics. Here, we use a state-of-the-art dendroecological approach to reconstruct long-term changes in the position of the alpine treeline in relation to air temperature at two sides in the Changbai Mountains in northeast China. Over the past 160 years, the treeline increased by around 80 m, a process that can be divided into three phases of different rates and drives. The first phase was mainly influenced by vegetation recovery after an eruption of the Tianchi volcano in 1702. The slowly upward shift in the second phase was consistent with the slowly increasing temperature. The last phase coincided with rapid warming since 1985, and shows with 33 m per 1°C, the most intense upward shift. The spatial distribution and age structure of trees beyond the current treeline confirm the latest, warming-induced
Correspondence Hong S. He and Zhengfang Wu, School of Geographical Sciences, Northeast Normal University, Changchun, China. Emails:
[email protected];
[email protected] Funding information National Key R&D Program of China, Grant/ Award Number: 2016YFA0602301; National Natural Science Foundation of China, Grant/ Award Number: 41601052, 41471085, 41371076; China Postdoctoral Science Foundation, Grant/Award Number: 2016M600225; Fundamental Research Funds for the Central Universities, Grant/ Award Number: 2412016KJ025; Youth and Sports of Czech Republic within the National Sustainability Program I, Grant/ Award Number: LO1415
upward shift. Our results suggest that the alpine treeline will continue to rise, and that the alpine tundra may disappear if temperatures will increase further. This study not only enhances mechanistic understanding of long-term treeline dynamics, but also highlights the effects of rising temperatures on high-elevation vegetation dynamics. KEYWORDS
altitudinal transect, Betula ermanii, Changbai Mountains, climate change, dendroecology, forest growth, treeline dynamics
1 | INTRODUCTION
Hik, 2007; Kammer et al., 2009; Kelly & Goulden, 2008; Kirdyanov gout, Marquet, De Ruffray, & Brisse, 2008). Some et al., 2011; Lenoir, Ge
The upper distribution of alpine ecosystems is highly sensitive to tem-
disparities or even downward shifts from more drought-prone environ-
€rner & Riedl, 2012). Upward shifts of the alpine perature changes (Ko
ments have recently been reported as well (Crimmins, Dobrowski,
treeline in relation to global warming have been observed in many
Greenberg, Abatzoglou, & Mynsberge, 2011; Foster & D’amato, 2015;
mountain systems around the world (Beckage et al., 2008; Danby &
Hartl-Meier, Dittmar, Zang, & Rothe, 2014; Rabasa et al., 2013).
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© 2017 John Wiley & Sons Ltd
wileyonlinelibrary.com/journal/gcb
Glob Change Biol. 2018;24:1256–1266.
DU
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ET AL.
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The driving factors of treeline dynamics are complex (Malanson
mountain system (Foster & D’amato, 2015) although the treeline
et al., 2007; Tognetti & Palombo, 2013). Warming may promote the
position (i.e. elevation) varies with slope aspect. Moreover, air warm-
upward shift of treelines because productivity and functioning of
ing will release the low temperature constraints on tree flowering,
€ rner & Riedl, such ecotones are generally temperature-limited (Ko
pollination, seed maturation, seed dispersal, seed germination,
2012; Pauli et al., 2012). Microbial activity and plant metabolism are
€ rner & Riedl, 2012; Morin, Auggrowth and survival of seedlings (Ko
both temperature-dependent (Zhu, Cao, Wang, Xiao, & Li, 2012;
spurger, & Chuine, 2007), which will then result in expansion of
Zhu, Xiang, Wang, & Li, 2012). Tree recruitment and growth within
young recruits above the treeline (Truong, Palm, & Felber, 2007).
€ rner & the ecotone are mainly limited by low temperatures (Ko
We thus further hypothesize that tree populations will be more
€ rner & Riedl, 2012; Li, Kr€auchi, & Dobbertin, Paulsen, 2004; Ko
abundant and occur beyond the current treeline with global warm-
2006; Li, Yang, & Kr€auchi, 2003). Recent studies, however, demon-
ing. The third hypothesis reinforces the first two hypotheses if they
strated that species interaction (Liang et al., 2016) and geomorphic
are accepted.
processes (Macias-Fauriaa & Johnsonb, 2013) can slow down
To test these three hypotheses, we analysed the treeline shifts
warming-induced upward shifts, and that life stage (Malis et al.,
and the corresponding temperature changes in the last 160 years on
2016) and land-use legacies (Ameztegui, Coll, Brotons, & Ninot,
two sides of the Changbai Mountains and investigated the distribu-
2016), rather than warming, control treeline shifts. It has also been
tion and age structure of trees above the current treeline (TACT).
suggested that changes in soil nutrients, permafrost depth and snow
We aimed to answer the following questions: (i) How did tempera-
cover, mediated by topography and wind exposure (Frost & Epstein, € 2014; Kullman & Oberg, 2009; Lloyd, 2005; Macias-Fauriaa &
ture change and the treeline shift during the last 160 years? (ii) Did
Johnsonb, 2013; Richardson, 2004; Wilmking et al., 2012), influence
growth of TACT reflect temperature changes on the Changbai
treeline movements.
Mountains?
temperature changes coincide with treeline shifts? (iii) Did the
Previous studies mainly used remote sensing images (Ameztegui et al., 2016), historic photographs (Hagedorn et al., 2014) and treering data (Devi et al., 2008; Elliott, 2011) to identify treeline locations or changes in tree density in relation to global warming. The detected changes were often correlated against changes in tempera-
2 | MATERIALS AND METHODS 2.1 | Study area
ture to derive the causal effects of temperature on treeline dynamics
The Changbai Mountains (41°410 49″ to 42°250 18″N and 127°420 55″
(Gaire, Koirala, Bhuju, & Borgaonkar, 2014), or simply on variation in
to 128°160 48″E) is located in the northeast China at the border to
stem density within the upper ecotone (Liang, Wang, Eckstein, &
North Korea (Cao & Guo, 2000) (Figure 1). Its altitude ranges from
Luo, 2011; Wang et al., 2016). Although remote sensing images have
713 to 2,691 m above sea level (a.s.l.), and the climate is temperate
proven to be efficient at analysing large-scale and consecutive tree-
continental, with annual mean temperatures from 7.3 to 4.9°C and
line variation, they are mainly limited in their temporal scale that is
annual precipitation from 800 to 1,800 mm. The Changbai Moun-
100 years) and high temporal resolution data on treeline position,
2.2 | Historical treeline reconstruction
in tandem with reliable meteorological measurements. In addition,
We established two altitudinal transects on the north side of the
although global temperature has increased over the last decades, the
Changbai Mountains in 2014 (North1 and North2) and two transects
increase was not uniform around the world, with some areas experi-
on the west side (West1 and West2) in 2015 (Figure 1 and Table 1).
encing no increase or even cooling (Harsch et al., 2009). Conse-
North1 was a protected slope and North2 was an exposed slope,
quently, upward shifts of treeline did not occur uniformly (Holtmeier
whereas West1 and West2 were both exposed slopes. We did not
& Broll, 2007) and particularly corresponded to local temperature
sample the protected slope of the west side of the Changbai Moun-
€rner, 2007). Therefore, we hypothesize that the rate of change (Ko
tains because of safety issues. Instead, we used an unmanned aerial
treeline shift is similar for all sides of a mountain because tempera-
vehicle and measured the altitude of the current treeline of the pro-
ture change (warming or cooling) is generally uniform in a single
tected slope (Fig. S6). Selecting exposed and protected slopes
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ET AL.
F I G U R E 1 Geographical features of the study area at regional and local scales. (a) Satellite image of the study area showing the location of sampling sites (red and black dots, and blue box); (b) location of the study area at the regional scale and (c) observed summer mean temperature (red line) and summer precipitation (blue bars) of the study area during 1959–2015. TACT represents the trees above the current treeline. North1, north side transect 1; North2, north side transect 2; West1, west side transect 1; West2, west side transect 2 [Colour figure can be viewed at wileyonlinelibrary.com]
allowed us to account for the terrain effects on treeline altitudes
model (described later). We found that the age of the current tree-
(Zhang, Zhang, & Mian, 2016; Zhao et al., 2016). These transects
line trees was ~10 years according to this model. We thus defined
were from the current treeline downward to lower altitudes at 10 m
the historic treeline position (altitude) as the location where B. er-
intervals. The plot size (100 m2) was 5 m (altitudinal direc-
manii had established and grown for 10 years. Therefore, the time of
tion) 9 20 m (along contour line). We defined the current treeline
tree establishment plus 10 years was the time when the treeline
position as the canopy cover of ≥0.2 (20%) of trees with an average
reaches a given altitude. Because the average tree’s canopy in the
height of >2 m. For the small trees in the current treeline, tree age
current treeline is about 1 m2, our treeline definition meant that a
was determined by a tree age-DB (diameter at base) regression
treeline plot (100 m2) required a minimum 20 such trees.
DU
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ET AL.
We sampled increment cores or discs at various altitudes on the two sides of the Change Mountains to determine how tree age
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2.3 | Sampling of trees above the current treeline
changes with altitude. We used the locations of the old tree ages to
To analyse the distribution and age structure of B. ermanii trees
delineate the treeline locations of different historic periods. For his-
above the current treeline (TACTs), in 2015 we established a big
toric treelines at lower altitudes, where the current tree height and
B. ermanii plot with 450 9 50 m (altitudinal length 9 width) ranging
canopy cover exceed the treeline criterion very much (Table 1), we
from 2,074 to 2,194 m a.s.l. above the current treeline on the west
assumed that the same treeline criterion was met at some time in the
side of the Changbai Mounts (Figure 1). We counted all B. ermanii
past. Thus, the historic treeline position was determined using the
TACTs in this plot by dividing the plot into nine subplots of
oldest 20 trees in the 100 m2 plot. The corresponding time and tree-
50 9 50 m and then recording B. ermanii in each subplot. In total, we
line reaching that plot location was determined by the ages of the 20
found 598 B. ermanii TACTs. Most TACTs were smaller than 1.3 m in
trees. We randomly sampled at least five such trees to determine
height, and therefore we measured diameter at base (DB) for all
their ages. Tree age changes by altitude were revealed by averaging
TACTs. Because these trees were too small to drill cores, we ran-
the samples in each altitudinal plot. The largest one or two trees,
domly selected 35 nearby B. ermanii, measured DB of each tree, and
however, were abnormally larger than other trees in some plots
took their trunks to laboratory to determine their ages using TSAPwin
(random establishment before large number of trees moved up and
system (LINTAB 6). We built regression models of tree age with DB
formed the treelines), and these trees were excluded from determin-
and tree height for the 35 trees. Compared to the tree age-tree
ing tree ages. In total, 186 trees were sampled in the four transects.
height regression model, the tree age-DB regression model performed
We drilled two tree cores per tree, parallel to contour, at 1.3 m for trees with DBH >5 cm and height >2 m. Tree cores were held in
better (Appendix S1, Fig. S2). Therefore, we estimated the ages of all B. ermanii in this plot using the regression of tree age with DB.
self-made paper tubes in the field and were mounted as wooden stripes in laboratory. We sanded the cores using coarse-to-fine sandpaper. Cores were then measured using the TSAPwin4.7 system (LINTAB 6, with precision of 0.001 mm) and cross-dated using the
2.4 | Deriving weather data of the past five decades for the current treeline areas
COFECHA program (Holmes, 1983). For some cores hitting the pith,
Observed climatic data from 1959 onward (the Tianchi weather sta-
the distance to the centre of the tree was estimated by fitting a cir-
tion, 42°10 N, 128°50 E, 2,623 m near the volcanic lake on the moun-
cular template to the innermost curved ring or by subtracting core
tain top) were provided by the China meteorological data network
length from the radius at core height (Hollingsworth, Walker, Chapin
(http://data.cma.gov.cn/). We performed quality control based on
Iii, & Parsons, 2006). The years of this segment were determined
the method by Alexander et al. (2006) and performed homogeneity
from the regression of tree age with DB (discussed later; also see
test using the RHtestV4 software (Wang & Feng, 2013) (the nearby
Appendix S1). Cores with unrecognized rings were rejected, and ser-
reference stations were also provided by the China meteorological
ies not correlated with the entire dataset were also discarded. We
data network). The data proved to be homogeneous by this test;
then reconstructed treeline changes using the altitudinal changes in
however, the altitude difference between our study sites and Tianchi
tree age. For North1, however, we sampled tree cores along the
station was between 400 and 700 m, and the temperature differ-
ridge upward to the mountain-top rather than from the valley
ence was notable. Therefore, we set up an automatic meteorological
upward to the mountain-top. Many trees in lower altitudes were
station (Weather hawk) at 2,050 m a.s.l. (41°590 22″N, 128°000 11.37″
smaller than in higher altitudes, and therefore data in North1 were
E) in 2015. We compared the temperature recordings between the
not used to analyse the altitudinal changes in B. ermanii’s age. In
two sites and established a regression model (p < .001, R2 = 0.96)
total, 163 cores were available for analysing the altitudinal changes
(Appendix S2, Fig. S3) that was used to construct the temperature
using tree age after cross-dating (Table 1).
data near the current treeline.
T A B L E 1 Characteristics of the four Betula ermanii transects on the Changbai Mountains No. of cores (trees) Transects
Altitude range (m a.s.l.)
No. of plots
a
1892–2115
9
0 (0)
40 (26)
6.4–38.5
—
4.2–18.8
40–207
North2b
1940–2025
8
71 (37)
16 (11)
13.7–40.4
—
11.4–17.9
8–188
North1
a
b
DBH (cm)
West1
1991–2062
8
54 (42)
15 (9)
7.2–26.4
West2c
1994–2060
4
38 (19)
16 (9)
8.8–32.6
DB (cm)
2.9–6.3 —
Height (m)
Age (year)
1.4–18.8
10–182
5.2–17.5
26–178
North1, north side transect 1; North2, north side transect 2; West1, west side transect 1; West2, west side transect 2; DBH, diameter at breast height; DB, diameter at base. DB was measured for trees with a height of 200 cm. The DB of 90%
(p < .01) on the Changbai Mountains. This finding further indicates
of trees was
