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Article

Expansion of Treeline in North China and Its Relationship with Altitude Sensitivity Gradient of Larix gmelinii

by
Bo Li
1,
Binhui Liu
1,*,
Mark Henderson
2,
Wanying Zhou
1 and
Mingyang Chen
1
1
School of Forestry, Northeast Forestry University, Harbin 150000, China
2
Mills College, Northeastern University, Oakland, CA 94613, USA
*
Author to whom correspondence should be addressed.
Forests 2023, 14(10), 1960; https://doi.org/10.3390/f14101960
Submission received: 7 September 2023 / Revised: 24 September 2023 / Accepted: 25 September 2023 / Published: 28 September 2023
(This article belongs to the Section Forest Ecology and Management)
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Abstract

:
As the climate has warmed, alpine treelines have moved to higher altitudes and the responses of tree growth to different climate factors have changed. We collected dendrochronologies of Larix gmelinii at different elevations on the Dabai Mountain, the highest peak in northeastern China’s Greater Khingan range, to measure the sensitivity and stability of radial growth over time. We found that the treeline has moved upslope since 1970. From the mid-1980s, radial growth increased in the treeline ecotone but decreased in the subtimberline forest, an example of “growth divergence” under warming conditions: increases in the previous October’s maximum temperatures promoted growth at higher altitudes but inhibited it at lower altitudes. The treeline ecotone appears to be more sensitive to climate change, with the effects on tree growth of different climate indicators varying by altitude in linear or U-shaped relationships. As warming continues, the management of boreal forests needs to consider the changing potential for tree growth and carbon sequestration capacity in relation to changing site conditions.

1. Introduction

Climate change is an important driver of natural systems, affecting the natural distribution of species and eliciting a physiological responses in plants [1,2,3]. Boreal forests are the second largest forest biome in the world, accounting for about 30 percent of the world’s global forest area. They provide ecosystem services that benefit society at all levels, from local to global. Boreal forests are also a large reservoir of biogenic carbon at levels comparable to (if not exceeding) those of tropical forests, accounting for 32 percent of global terrestrial carbon stocks, and it is estimated that boreal forests are responsible for 20 percent of the total carbon absorbed by the world’s forests [4].
Boreal forests are highly sensitive to climate change, and boreal forests located in high latitudes are experiencing faster warming than any other forested region on the planet [4,5]. Evidence suggests that carbon uptake rates have decreased in boreal forests since at least the 1980s, and in fact, that they could now be a net source—the world’s largest terrestrial source of carbon. How we manage these forests will have implications for future climate dynamics. For these reasons, the fate of the boreal forest should be a matter of global concern [6].
Each population of a species has a definite range of climatic factors to which it is adapted. Ecological niches are more clearly characterized along elevational gradients, but these vary by latitude as well [7]. As climate warming causes changes in those environmental conditions, species must shift their ranges or adapt to survive. Species unable to do so are doomed to extinction [8]. For example, warming, or a combination of warming and reduced rainfall, may be increasing the mortality of regenerating seedlings, especially in northern conifers [9]. This may have a depressing effect on changes in the distribution of tree species.
Treelines are the most important global bioclimatic reference line. The fact that treelines track seasonal low temperatures means that the limits of tree species’ distribution can shift with changes in extreme low temperatures. Warming varies by both latitude and altitude:higher latitude are seeing a higher rate of increase in temperature, and the rate of warming is amplified with increasing altitude [10,11]. Tree species are expected to adapt to warming by shifting their ranges to higher latitudes or elevations [12]. Thus, an increase in seasonal extreme low temperatures may allow the species distribution to expand both upslope and poleward [13]. One study showed that 66% of the timberline had shifted in terms of elevation or latitudinal distribution [14]. It is an open question how broadly this applies to the world’s many tree species across varied geographical settings. Natural ecosystems are complex and nonlinear systems, so climate change may affect natural ecosystems in different ways [15]. There is an urgent need for further research on the scale and consequences of these changes and their impact on species persistence and ecosystem functioning [16]. Understanding how climate change will affect forest ecosystems in the future will require a detailed understanding of how different tree species interact with the environment at regional scales [17,18].
The boreal forest of the Greater Khingan Mountains in northeast China represents the southernmost edge of the Asian taiga. The region ranges in latitude from 42 °N to 54 °N at the Russian border, with mean annual temperatures ranging from −4.5 °C to 5.5 °C [19]. At its southeastern end, the boreal forest gradually gives way to temperate broadleaved forests that thrive in the warmer temperatures of lower latitudes and altitudes, resulting in a boreal-temperate forest ecotone [20,21,22]. Prior research has shown that there is a huge difference in the relationship between tree growth and climate factors in the southern part of the boreal forest compared with the boreal-temperate forest transition zone, and that further studies are needed on the key growth determinants in the southern part of the boreal forest [20].
To explore possible changes in the distribution of the boreal forest, we sampled the dendrochronologies of the Gmelin larch, Larix gmelinii, at different elevations from the upper treeline to the lower extent of timber growth. Also known as the Dahurian larch, Larix gmelinii dominates the boreal forests of the Greater Khingan range. Previous studies on Larix gmeliniii have focused on the factors affecting tree-ring growth [23,24,25,26]. Models of the change in the species’ distribution predict that Larix gmeliniii will gradually move northward with the warming of the climate, eventually leaving China [25]. Therefore, building on the results of previous studies, this paper investigates the climatic factors affecting tree dynamics in the Greater Khingan Mountains, including (1) the relationship of climatic factors to the upper, lower, and ecotone extent of Larix gmeliniii; (2) the stability of these relationships under warming conditions; and (3) whether high-altitude Larix gmelinii shows an upward shift of the treeline during the rapid climate warming in recent decades. Understanding the response of Larix gmelinii to warming will help to improve forest management and make more efficient use of the forest’s carbon storage capacity [27].

2. Materials and Methods

2.1. General Description of the Study Area

Dabai Mountain is located in the northern part of the Greater Khingan Mountains in Heilongjiang Province near the border of the Inner Mongolia Autonomous Region (122°16′ E, 51°28′ N). The area around the mountain reports an average annual temperature of −4.3 °C, a minimum temperature of −53.2 °C, and a maximum temperature of 32 °C. The climate is severe and cold with a snowy period of 8–9 months. The sampling sites were located on the southern slope of Dabai Mountain, with an elevation of 1200 m at the foot of the mountain and 1528.7 m at the summit.
We define the treeline as the highest elevation at which a living, upright tree taller than 2 m can be found [28,29] (Figure 1). On Dabai Mountain, we found Larix gmelinii sporadically distributed up to the 1511 m contour, with tree heights of 0.65–2.42 m. At this elevation, vegetation was mostly bushes and the incomplete tree canopy closure at this altitude could not be described as a forest. We found that the trees were 20–50 years old, measured from the samples taken at the basal part of the trees, which was consistent with the concept of treeline.
The timberline marks the transition from closed-canopy forest below the treeline [28,29]. Although Larix gmelinii with larger diameters appeared at 1400 m, these specimens showed obvious fire scars and dead wood; living trees were small, having regenerated gradually after the year 2000. The density of regenerated seedlings was high and, above 1400 m, scrub-dominated. Although the forest canopy at that elevation had not yet closed due to the disturbance of forest fires, we considered 1400 m to be the timberline of Dabai Mountain.
The alpine treeline ecotone is the transition zone between the timberline and treeline, characterized by isolated trees [30,31]. We chose to sample the treeline ecotone at 1460 m (between the timberline and the treeline) in order to study the characteristics of the vegetation gradient. Below the timberline, 1200–1400 m constitutes a closed-canopy forest, with Larix gmelinii and Betula platyphylla as the main tree species. We took measurements at 1300 m, where Larix gmelinii is mixed with a relatively small proportion of Betula platyphylla, and at 1230 m, in the low range of Larix gmelinii where Betula platyphylla accounts for a relatively high proportion of trees.

2.2. Materials and Methods

2.2.1. Sample Collection

In field visits conducted in September 2019, we selected plots for core sample collection. We set up 20 × 30 m sample plots at the altitudes of 1511 m, 1460 m, 1400 m, 1300 m, and 1230 m. Sites were chosen to avoid the influence of anthropogenic factors. Because trees are very sparse at the altitudinal growth limit of 1511 m, we set up two plots there to achieve a sufficient sample size. At 1400 m, after a field investigation, we only found young seedlings that regenerated after the fire, so plot samples from that altitude were not analyzed.
Based on the standard of the International Tree Rotation Database (ITRDB), Larix gmelinii specimens with scar-free trunks and with a diameter at breast height (DBH) of more than 10 cm were selected for sampling. At the treeline (1511 m) and treeline ecotone (1460 m) plots, where trees were smaller, we selected Larix gmelinii with a height of approximately 2 m or more for sampling. Because of the small size of the tree at 1511 m and 1460 m, basal cores that showing the specimens’ growth rings were taken. At another latitude, tree core samples were taken at breast height (Table 1). Core samples were put into a plastic tube, and sealed with a record of the information of the sampled tree. The width of the growth rings were used for preliminary cross-dating using the skeleton diagram method: the ring width was measured using the LINTAB annual ring width meter; the COFECHA program was used to cross-date the sequence of annual ring widths; and the establishment of the chronological table was accomplished by the computer program ARSTAN [32] to compute the standardized tree chronologies (STCs) for this paper.

2.2.2. Meteorological Data

Meteorological data were obtained from the Mohe Meteorological Station, near the sampling site, including the daily average, maximum, and minimum temperatures and precipitation data from 1956 to 2019. After removing anomalous data, the data were verified to be reliable and representative of the local climatic conditions for the growth of Larix gmelinii. Monthly meteorological data were calculated using the daily data, and the temperature and precipitation from June of the previous year to August of the current year were taken due to the possible legacy effects on the growth of trees.
Since China’s national meteorological stations were first established around 1950 (and achieved more a stable data quality after 1960), we lack longer-term meteorological data to match with the tree rings of the older trees in this study. Instead, we used global estimated climate data (including the maximum temperature, minimum temperature, and precipitation) for the years 1901–2019 obtained from the Royal Netherlands Meteorological Institute (http://climexp.knmi.nl, accessed on 3 November 2021). The CRU TS4.05 gridded dataset has a spatial resolution of 0.5° × 0.5°.

2.2.3. Data Analysis Methods

We performed a Pearson correlation analysis to examine the association of meteorological factors with trees’ radial growth at different points along the altitudinal gradient. Because the tree-ring time series were short, we analyzed the sensitivity of possible changes with a moving correlation analysis with a window of 20 years (advancing one year at a time). The correlation analysis was performed using SAS 9.2 software, and the graphing was performed using Origin 8.0 software.

3. Results

3.1. Dynamics of Treeline Movement on Dabai Mountain

In order to understand the dynamics of any altitudinal shift in the treeline, we measured the ages of each Larix gmelinii in the sample plots at 1511 m and 1460 m, and compared them with the ages of the trees sampled in the subtimberline forest. Appling a backward tracing method, we could then estimate the time of tree regeneration and changes over time in the number of trees in each sample plot.
Figure 2 illustrates the dynamic change in the number of trees in each sample site. It can be seen that, before 1970, there were only a few trees distributed in the sample site higher than 1460 m. Since 1970, the number of regenerated seedlings at the treeline increased rapidly and continuously until 2000, when the number of trees reached 250 trees/ha. The same was observed for the treeline ecotone, which reached 1000 trees/ha in 2000. These two sites showed no signs of forest fires. However, in our 2019 survey, there were no young seedlings observed at the treeline, compared with 333 seedlings/ha observed at the treeline ecotone plot, indicating that natural regeneration at the treeline was concentrated during the 1970–2000 period.
At 1400 m, we found a lot of big, dead trees with fire scars. The date of the fire was unknown. Regenerating seedlings appeared to have flourished after the fire. While the forest canopy has not closed, the density of the regenerating seedlings reached 1417 trees/ha, so we judged that, if there had been no forest fire disturbance, this elevation would be the location of the timberline. A previous survey in 2005 had located the timberline at 1300 m on the north slope of Dabai Mountain [33], but as our survey was on the south slope, the difference in the location of the timberline might be explained by the slope aspect.
In our sample plot survey, Larix gmelinii below the timberline was regenerating and survived during the period of 1930–1950. The previous survey had noted fires on Dabai Mountain in the 1940s; it is possible that fire plays an important regulatory role in the soil–vegetation relationship, prompting the rapid establishment of regenerating seedlings [34]. The trees in the subtimberline ecosystem appear to have recovered quickly after the fires and stabilized around 1940–1950.
The treeline and the treeline ecotone began to expand gradually in the 1970s, coinciding with the period of global warming [2]. It is possible that the treeline altitude reflects the temperature threshold for tree growth. As the climate warms, coupled with winter winds that favor long-distance dispersal, the decreased depth of the snowpack, and the increased effectiveness of soil nutrients, conditions increasingly favor the replenishment and advance of the boreal forest [35]. Thus, climate warming is one of the dominant factors explaining the upward migration of the treeline on Dabai Mountain. Whether Larix gmelinii will continue to move up the treeline in the future as it continues to warm and how its range will change remain to be explored.

3.2. Comparison of Radial Growth at Different Altitudes

We analyzed tree-ring growth to detect changes in the growth dynamics of trees in the treeline, treeline ecotone, and subtimberline forest in recent decades. The STCs of 1511 m, 1460 m, 1300 m, and 1230 m are shown in Figure 3. The graph for the treeline shows a large fluctuation in the early years, with fewer trees established in the 1970s, and there is no significant trend. In the treeline ecotone, the surviving trees increased continuously and saw an increase in growth; this may be related to the increase in temperature that accelerated from the mid-1980s, when daytime temperatures began to rise and warming was not confined to the winter months [36,37]. In the subtimberline forest, tree growth showed an upward trend during the period of 1965–1985, a sudden decrease during the rapid warming period of 1985–2004, and no significant change after 2004, diverging from the expectations of straightforward warming-induced increases in growth.
This “growth divergence”—referring to individual trees in the same region that have divergent growth trends—has been observed in other studies, more often at mid to high latitudes and at higher altitudes [29,38]. Growth divergence was first studied in white spruce (Picea glauca) in central and northern Alaska, where it was found that, while timber-density change was not higher than some levels prior to this century, warmer temperatures combined with dry years may be changing the response of trees to climate [39,40]. Most studies have demonstrated that limiting factors differ among trees at different elevations [41,42]. Tree growth at high altitudes (>1300 m) is mainly limited by summer temperatures, while at low altitudes (<1000 m) summer precipitation is the main limiting factor [43].
The growth process of Larix gmelinii is characterized by variability under warming conditions at different altitudes. This may be related to the varying trajectories of climate change and differences in climatic backgrounds at different altitudes. Larch on the timberline in the Siberian region of Russia has shown a smaller than expected increase in STC since 1970, attributed to the reduced sensitivity of radial growth to temperature [44]. A study of Larix gmelinii at the five sampling sites in the Greater Khingan Mountains region of China found that the tree age (up to 150 years), growing period moisture conditions, and ambient air temperature varied geographically (by latitude, longitude, and elevation) in ways that would cause their relationship to be nonlinear [45].

3.3. Comparison of Climate Responses of Trees at Different Altitudes

In order to analyze the causes of growth divergence at different altitudes within the same site, we correlated the STCs at the treeline, in the treeline ecotone, and in the subtimberline forest with climatic factors. We conducted Pearson correlation analyses between STCs at the different elevations and measurements of monthly average temperature, maximum temperature, minimum temperature, and precipitation from the previous June to August of the current year. The results are shown in Figure 4.
Tree growth on the treeline is positively correlated with temperature and precipitation only in May and July of the current year. It has the highest sensitivity to temperature and precipitation in the growing season and little “legacy effect” from conditions in the previous seasons. For comparison, a study of white spruce in the North American arctic found that the radial growth of the main stem at the treeline was positively correlated with July temperatures [35].
In the treeline ecotone, tree growth is not only sensitive to the hydrothermal conditions of the current year’s growing season, but also to the hydrothermal conditions of the previous year’s growing season. We find a clear legacy effect, with positive correlations between tree growth and precipitation in the previous year’s growing season, minimum temperatures in the previous fall and spring, and maximum temperatures in the previous fall and winter. Temperature and precipitation are both positively correlated with tree growth from April to July, with the exception of June, when the response to precipitation was negative. It may be that the supply of precipitation for the radial growth of trees exceeds the demand, and too much precipitation is detrimental to photosynthesis. For comparison, a study of European larch (Larix decidua) in the treeline ecotone of the eastern Italian Alps found that the climatic effects on growth were dominated by temperature, concentrated in the five months from March to July, and that precipitation in June also had a positive effect on the growth of the larch [42].
In the subtimberline forest, tree growth is positively correlated with the minimum temperature and precipitation in the previous fall, and negatively correlated with the maximum temperature in the previous fall, previous winter, current spring, and current growing season. This suggests that the subtimberline forest has a sufficient maximum temperature to ensure tree growth; the legacy effect is not as pronounced here as in the treeline ecotone. The positive correlations with precipitation and minimum temperature and the negative correlation with the maximum temperature from the previous September may be due to the fact that climate conditions are suitable for the trees to photosynthesize in September, thus providing organic matter for the growth of trees in the following year [46,47].
In addition to differences in the tree growth processes at different elevations, we found that there were also differences in their sensitivity to climate conditions. As the elevation decreased, the sensitivity to the maximum temperatures of the previous and current years’ growing seasons went from positive to negative. This indicates that elevated high temperatures in the growing season promoted the growth of trees at high elevations (the treeline and treeline ecotone) and limited the growth of trees at low elevations (the subtimberline forest). The same pattern was previously observed in a study of European larch in the French Alps [43].
Except at the treeline, as elevation decreases, tree growth’s negative correlation with the current June precipitation decreases, and its correlation with the previous winter maximum temperature goes from positive to negative. It is possible that tree-ring growth at the treeline is not only affected by climate change, but also by the interaction between environmental and climate conditions [17]. At the treeline, some climatic factors do not meet the thresholds of suitability for tree growth in some seasons, so the effects of climatic variation on high-altitude forests are distinct from the effects in low-altitude ecosystems. Thus, models based on low-altitude forests are not necessarily applicable at higher altitudes [48]. From this, we can conclude that, with increased altitude, the sensitivity of trees to maximum temperatures in the growing season increases, as does the limiting effect of precipitation on tree growth. In the case of Dabai Mountain, this may be related to the lack of available retained moisture in the thin soil layer at high altitudes.
This result is contrary to the results of other studies that have found that the radial growth of trees is mainly limited by temperature at high altitudes and by precipitation at low altitudes [41,42]; for example, a study conducted in the eastern Tibetan Plateau reported that forest growth at high altitudes was mainly constrained by low temperatures in the growing season, while low-elevation forest growth was constrained by drought [17].

3.4. Stability of Tree Growth Response to Climate at Different Altitudes

In addition to “growth divergence” in the radial growth of trees, many studies have found that tree growth shows less consistent sensitivity to other climate factors as temperatures rise. This phenomenon is known as the “divergence problem” and manifests as temporal instability in the studies of tree growth in relation to climate factors [38,48]. In order to investigate the long-term dynamics in the relationship between tree growth and climate factors, we performed a moving correlation analysis.
Figure 5 displays the response characteristics of the radial growth to the climate variables that showed significant correlations at one or more elevations. The “divergence problem” is evident in the results for the subtimberline plots, specifically for the maximum temperature in October of the previous year (tmax_p10), which is strongly and significantly negatively correlated with tree growth, but only during the period of growth divergence. This may be explained by shifts in the seasonal pattern of defoliation: depending on when in October Larix gmelinii ends photosynthesis and drops its leaves, the amount of respiration in that month could affect the organic matter deposits available to support radial growth in the coming year. The sensitivity of radial growth to temperature did not change at the treeline and there was little change in sensitivity in the treeline ecotone, so the phenomenon of growth divergence appears only in the subtimberline forest.
The divergence problem in the subtimberline STC roughly coincides with China’s rapid warming period: China experienced an accelerated surface temperature rise in the late 1980s, before entering a warming slowdown after 2000 [36,37]. Their studies have found similar examples since the mid-20th century at high latitudes. In the Canadian Yukon, as temperatures rose, radial growth at the timberline changed from a positive to a negative correlation with mean temperature, causing a sudden decline in the annual growth of trees [49,50] in the Brooks Range and Alaska Range, whilst white spruce at the treeline showed varied responses to climate warming at different sites [39]. Researchers attributed these findings to warming surpassing the threshold of the trees’ optimum average temperatures for growth, thereby affecting the stability of trees’ response to climatic factors [48].
As temperatures continued to rise, some other climatic factors also saw changes in the stability of their association with tree growth at some elevations. The timing of these changes varied at different elevations. The correlation of growth with the maximum temperature in July of the current year is largely positive, but weakens at lower elevations and displays a shorter sensitive period. At the treeline and treeline ecotone, during the rapid warming period, the correlation of radial growth with the previous September’s minimum temperature shifted from a negative or no correlation to a positive correlation, while in the lower subtimberline forest, this relationship shifted from a positive correlation to no correlation.
Overall, warming strengthened the legacy effect at the treeline and treeline ecotone and weakened it in the subtimberline forest. The main principle of the legacy effect is the existence of non-structural carbohydrates (NSCs) in the tree, which are stored during the overproduction stage and can be reused during the growing season to satisfy plant growth requirements [51,52]. A study of mobile carbon pools in pine forests of the treeline transition zone in the Swiss Alps found that tree needles, twigs, stems, and roots took in more carbon with elevation, and concluded that the carbon sink activity of trees growing at high elevations is limited by low temperatures, rather than by carbon effectiveness [53]. Therefore, as the temperature increases, tree growth at the treeline and treeline ecotone are less limited by low temperature, the growing period of trees is extended, and less NSC is consumed to resist low temperatures, so more NSC can be used for growth in the current year and also be deposited for growth in the following year. This results in the environmental conditions of the treeline and treeline ecotone becoming more suitable for tree growth with the increase in temperature.
The legacy effect on tree growth in the subtimberline forest was weakened, probably because warming lengthened the growing period. Under these conditions, trees would use more NSC for radial growth and sustenance in the current year, leaving less for the following year [54]. Modeling based on a remote sensing analysis found that climate warming extends the growing season of boreal forest plants [55]. A study of radial growth in the Smith fir (Abies georgei var. smithii) found similar low-temperature thresholds (about 5 °C) at three elevations, with the temperature controlling the onset of the formation layer activity and the end of the xylem differentiation. The higher the altitude, the later the start of radial growth, the earlier the end, and the shorter the growing season: for every 100 m of elevation rise, the radial growth of fir was delayed by 4.7 d, it ended 7.2 d earlier, and the growing season was shortened by 12.8 d [56].
In short, the gradient characteristics of growth response to climate factors at different altitudes are not only related to the environmental conditions, but also to temporal changes in climate factors and the range of adaptation thresholds. The periods of sensitivity are short, and therefore showed no overall correlation.

4. Discussion

4.1. Characterization of the Temporal and Spatial Gradient of Larix gmelinii in Response to Climatic Factors

Previous studies have shown that the relationship between tree growth and climate varies with altitude and latitude [17,19,57]. In this study, we selected the study plots along an elevation gradient and analyzed the stability of factors affecting radial growth. Because the elevation gradient can also be taken to represent different stages in the warming process, our results can provide insights into spatial and temporal variations in the stability of the response of trees to warming. As shown in Figure 5, we found that the association of tmax_p10, tmax_c6, tmax_c7, tmin_p9, and tmin_c3 with tree growth is reduced or becomes nonsignificant over time, corresponding to increased warming. The effect is amplified with altitude, consistent with widespread reports that warming is faster at higher elevations [15].
Under warming conditions, when temperatures approach the physiological threshold for tree growth, further warming tends to make the tree growth less sensitive to temperature. If temperatures exceeds the upper limit of the optimum threshold, their effect on tree growth may be changed from promotion to inhibition, thus showing an inverted U shape rather than a continuous linear response. This is commonly called the “temperature threshold effect”.
We see this effect at the treeline, where the correlation of tmin_c3 with tree growth shifts from a negative to a positive correlation over time, and the growth promotion effect gradually strengthens with increasing temperatures. The opposite is true in the subtimberline forest, where the growth promotion effect gradually diminishes with increasing temperature. Taking the previous September’s minimum temperature as another example, tree growth is sporadically sensitive to tmin_p9 after warming at the treeline, shows enhanced sensitivity with warming in the treeline ecotone, and is sensitive for basically the whole study period in the upper subtimberline forest, while at in the lower subtimberline forest, it is sensitive before warming and less sensitive after warming.
The bifurcated legacy effects are also evident in our results: as the temperature increases, the effect of the previous year’s climatic conditions on tree growth in the treeline and treeline ecotone increases, but it decreases in the subtimberline forest. Since the treeline and the treeline ecotone are coupled boundaries, the effects there should be subject to similar underlying mechanisms [58]. As temperatures rise, the treeline ecotone may reach the optimum temperature threshold for the growth of Larix gmelinii just before the treeline does. The subtimberline forest may have already exceeded that threshold but remains within the temperature range for adapted growth; further warming only serves to limit growth. The temperature thresholds for Larix gmelinii were similar at different elevations, but as ambient temperatures differed by elevation, we observe spatiotemporal variability in the tree growth.
Studies in other ecosystems have similarly found the nonlinear responses of tree growth. In temperate and/or dry ecoregions of North America, elevated spring and summer temperatures are beneficial to neutral for tree growth, up to about 25–30 °C in wet climates or 10–15 °C in dry climates, with further elevated temperatures inhibiting growth; above the optimal temperature breakpoint of 30 °C, tree annual ring widths are reduced by an average of about 1%–5%, depending on the ecoregion, season, and the inclusion or exclusion of temperature-mediated drought effects [59]. In the coniferous forest belts of the Alps, the response curve of incense cedar pine first showed a smooth negative trend, and then a severe decrease in the curve once the temperature reached 3–4 °C; exceeding this temperature threshold can have a negative effect on tree annual growth [60]. In southwest China, Abies georgei var. smithii displayed a similarly low-temperature threshold for growth of about 5 °C [56].
Other studies have found changes in the relative influence of climate and ecological factors on tree growth under warming conditions. In the southern Canadian Rockies, research on Picea engelmanni Parry and Abies lasiocarpa (Hook.) identified non-monotonic relationships between radial growth and climate predictors that may be indicators of ecological thresholds [61]. A study of arid Central Asia found that temperature had a stable limiting effect on radial growth at the treeline over 60 years, but that the effect of precipitation on tree growth has increased due to rapid warming [62]. Where we find that May precipitation is becoming a limiting factor for tree growth at higher altitudes (but not in the subtimberline forest), this may be due to increased temperatures. Continued warming may further complicate the response of Larix gmelinii radial growth to climate.

4.2. Relationship between Tree Response Divergence and Treeline Rise

Our study shows that the treeline on Dabai Mountain began to move to higher elevations in the 1970s, gradually rising to 1511 m. Regeneration in the subtimberline forest was concentrated around the 1940s. Comparing the numbers of trees in the sample plots with estimated climate data from 1901 to 2019, we found that the period of subtimberline forest regeneration and treeline rise coincides with the period of global warming [2]. Thus, the rise in the treeline and treeline ecotone may be due to increasing temperatures and the melting of the snowpack [2], as warming temperatures at higher altitudes reach the optimum threshold for the growth of Larix gmelinii. This is not unexpected: a study of the altitudinal distribution of 171 forest plant species in Western Europe up to 2600 m above sea level found that climate warming led to a significant increase in species’ optimal altitude, with an average increase of 29 m per decade [16]. Similarly, a study in the Alps linked temperature increases to treeline expansion [63].
Warming is not all good news for Larix gmelinii: even as its range increases in altitude, we see declines in the subtimberline forest. Another study in the southern and central parts of the Greater Khingan Mountains similarly reported declining growth of Larix gmelinii [63]. If warming leads to temperature conditions that exceed the species’ threshold of the adapted temperature, this will inhibit the growth of existing trees and discourage regeneration, impacting carbon sequestration capacity.
As warming continues in the century ahead, the migration of many plant species may lag behind patterns of broad-scale climate change [64,65]. The optimal range of Larix gmelinii will gradually move up in latitude and altitude as temperatures increase. But it is not certain whether Larix gmelinii will be able to spread north and upslope as the climate shifts in the future. Multiple factors may negatively affect the growth and survival of the species in new areas [8].

5. Conclusions

We used dendrochronological methods to analyze the change in the range of Larix gmelinii in the treeline, treeline ecotone, and subtimberline forest and changes in the response of trees to climate warming at different altitudes. The study found:
  • The subtimberline forest on Dabai Mountain regenerated around 1940 and the treeline moved upward around 1970; these two expansion time points roughly coincide with the period of global warming.
  • The radial growth of trees varied by altitude with increasing temperatures, showing little change at the treeline, an increase in the treeline ecotone, and “growth divergence” in the subtimberline forest. The divergence was due to a change in response to the previous year’s October maximum temperature during the rapid warming period that began in the mid-1980s.
  • Trees at different elevations also had different sensitivities to climate: as elevation decreased, the sensitivity of the annual radial growth to the previous and current years’ growing seasons maximum temperatures changed from positive to negative, with warming promoting the growth of trees at higher elevations and limiting the growth of trees at lower elevations.
  • Rapid warming influenced the stability of trees’ response to some climate indicators at different altitudes. The relationship between growth and the previous year’s fall temperature shifted from negative or no correlation to a positive correlation at the treeline and treeline ecotone, but in the subtimberline forest, the previous correlation disappeared. Thus, we find that warming enhances the “legacy effect” at higher altitudes but reduces it at lower altitudes.
  • The stability of the influence of different climate indicators on tree growth varies by altitude and shows changes developing through the warming period. We find evidence that there is an inverted “U” relationship between radial growth and some climate conditions.
As the climate continues to warm, it remains to be seen whether the Larix gmelini distribution area will be able to move up in altitude and north in latitude to stay within its optimal growth threshold. Changes in growth patterns will affect the trees’ carbon sequestration capacity. Climate change mitigation and adaptation measures for boreal forest ecosystems will need to consider these and other factors. Because the latitudinal gradient is too extensive to be completely replaced by elevation, our study is more informative in terms of elevation gradients and tree boundaries.

Author Contributions

B.L. (Bo Li): Conceptualization, methodology, formal analysis, writing—original draft. B.L. (Binhui Liu): methodology, writing—review and editing, project administration. M.H.: writing—review and editing. W.Z. and M.C.: data curation. All authors contributed substantially to repeated reviews and revisions. All authors have read and agreed to the published version of the manuscript.

Funding

This work was funded by the National Natural Science Foundation of China (41877416).

Data Availability Statement

Climate data referenced in this paper are available through the National Meteorological Information Center through the China Meteorological Data Sharing Service Center (CMDC) (http://data.cma.cn/en, accessed on 3 November 2021). The name of the dataset is ‘Dataset of Daily Values of Climate Data from Chinese Stations for Global Exchange’.

Acknowledgments

We gratefully acknowledge the National Natural Science Foundation of China for funding this work.

Conflicts of Interest

The authors declare no conflict of interest.

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Forests 14 01960 g001
Figure 1. Overview map of the study area.
Figure 1. Overview map of the study area.
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Figure 2. Time series of the accumulated number of regenerating trees at different altitudes (20 × 30 m sample plots).
Figure 2. Time series of the accumulated number of regenerating trees at different altitudes (20 × 30 m sample plots).
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Figure 3. Dabai mountain standardized chronologies of annual tree-ring width (STCs) by elevation.
Figure 3. Dabai mountain standardized chronologies of annual tree-ring width (STCs) by elevation.
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Figure 4. Correlations from previous June (p6) through current August (c8) of annual tree growth with monthly precipitation (Prep), mean temperature (Tmean), minimum temperature (Tmin), and maximum temperature (Tmax) for trees sampled at (a) treeline, (b) treeline ecotone, (c) upper subtimberline forest, and (d) lower subtimberline forest. Asterisk (*) indicates statistical significance, p < 0.05.
Figure 4. Correlations from previous June (p6) through current August (c8) of annual tree growth with monthly precipitation (Prep), mean temperature (Tmean), minimum temperature (Tmin), and maximum temperature (Tmax) for trees sampled at (a) treeline, (b) treeline ecotone, (c) upper subtimberline forest, and (d) lower subtimberline forest. Asterisk (*) indicates statistical significance, p < 0.05.
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Forests 14 01960 g005aForests 14 01960 g005b
Figure 5. Results of moving correlation analyses at four altitudes between the annual tree growth and climatic factors: precipitation (prep) and minimum and maximum temperatures (tmin and tmax) for selected months from previous June (p6) to current August (c8). Asterisk (*) indicates statistical significance, p < 0.05.
Figure 5. Results of moving correlation analyses at four altitudes between the annual tree growth and climatic factors: precipitation (prep) and minimum and maximum temperatures (tmin and tmax) for selected months from previous June (p6) to current August (c8). Asterisk (*) indicates statistical significance, p < 0.05.
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Table 1. Sample site information and the characteristic values of the chronological statistics of Larix gmelinii.
Table 1. Sample site information and the characteristic values of the chronological statistics of Larix gmelinii.
TreelineTreeline EcotoneUpper SubtimberlineLower Subtimberline
Altitude (m)1511146013001230
Tree germination dates (SSS > 0.85)1949–20191965–20191942–20191909–2019
Mean age (years)32357074
Mean DBH (cm)4.35 (tree base)4.88 (tree base)18.5617.10
Mean height (m)1.88 (0.65–2.42)2.6213.4411.91
Sample size (tree/cores)31/3520/2125/4428/42
Express population signal (EPS)0.8600.9120.9650.974
Standard deviation (SD)0.51370.41000.26900.3685
Signal-to-noise ratio (SNR)6.12210.36727.78437.317
Mean sensitivity (MS)0.41970.28960.18680.2192
Autocorrelation order 1 (AC1)0.52650.74670.59060.7654
Mean interseries correlation (MC)0.3380.4090.4160.483
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Li, B.; Liu, B.; Henderson, M.; Zhou, W.; Chen, M. Expansion of Treeline in North China and Its Relationship with Altitude Sensitivity Gradient of Larix gmelinii. Forests 2023, 14, 1960. https://doi.org/10.3390/f14101960

AMA Style

Li B, Liu B, Henderson M, Zhou W, Chen M. Expansion of Treeline in North China and Its Relationship with Altitude Sensitivity Gradient of Larix gmelinii. Forests. 2023; 14(10):1960. https://doi.org/10.3390/f14101960

Chicago/Turabian Style

Li, Bo, Binhui Liu, Mark Henderson, Wanying Zhou, and Mingyang Chen. 2023. "Expansion of Treeline in North China and Its Relationship with Altitude Sensitivity Gradient of Larix gmelinii" Forests 14, no. 10: 1960. https://doi.org/10.3390/f14101960

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