Research Article

Species interactions slow warming-induced upward shifts of treelines on the Tibetan Plateau

Eryuan Liang, Yafeng Wang, Shilong Piao, Xiaoming Lu, Jesús Julio Camarero, Haifeng Zhu, Liping Zhu, Aaron M. Ellison, Philippe Ciais, and Josep Peñuelas
PNAS first published April 4, 2016 https://doi.org/10.1073/pnas.1520582113

  1. Edited by Christopher B. Field, Carnegie Institution of Washington, Stanford, CA, and approved March 3, 2016 (received for review October 19, 2015)

Significance

Climatic warming is expected to shift alpine treelines upward because regeneration and growth of trees there are limited by low temperature. However, treeline displacement is spatially heterogeneous, despite warming climate. Using data on undisturbed spruce and fir treeline plots located on the Tibetan Plateau between 28.4 and 38.5°N, we showed that climatic warming tended to promote an upward shift of alpine treelines at local and regional scales. However, upslope migration rates were controlled largely by interspecific interactions. The species interaction mechanism both helps to explain why many treelines have not advanced in response to climatic warming and highlights that predictions of treeline shifts based solely on climate may be misleading, because interspecific interactions can temper effects of climatic change.

Abstract

The alpine treeline is commonly regarded as being sensitive to climatic warming because regeneration and growth of trees at treeline generally are limited by low temperature. The alpine treelines of the Tibetan Plateau (TP) occur at the highest elevations (4,900 m above sea level) in the Northern Hemisphere. Ongoing climatic warming is expected to shift treelines upward. Studies of treeline dynamics at regional and local scales, however, have yielded conflicting results, indicating either unchanging treeline elevations or upward shifts. To reconcile this conflict, we reconstructed in detail a century of treeline structure and tree recruitment at sites along a climatic gradient of 4 °C and mean annual rainfall of 650 mm on the eastern TP. Species interactions interacted with effects of warming on treeline and could outweigh them. Densification of shrubs just above treeline inhibited tree establishment, and slowed upward movement of treelines on a time scale of decades. Interspecific interactions are major processes controlling treeline dynamics that may account for the absence of an upward shift at some TP treelines despite continued climatic warming.

The boundary of vegetation formed by alpine treelines is expected to be sensitive to effects of climatic warming on subalpine and alpine ecosystems (1⇓–3). Despite complex mechanisms controlling treeline ecotones (4), the mean root-zone and air temperature is thought to be the primary constraint on tree growth at the high elevations reached by particular tree species (3). As the temperature warms, therefore, treelines are expected to increase in elevation (“shift upward”) (e.g., refs. 5⇓–7).

In a global meta-analysis, however, Harsch et al. (8) found that treelines shifted upward during the last century at only 52% of 166 locations examined; the majority of treelines upward shifts was attributed to improved winter conditions. Elsewhere, changes in treeline (“treeline displacement”) were spatially heterogeneous and slow despite accelerating warming (9, 10). In general, treelines are not always keeping pace with climatic warming on multidecadal time scales, suggesting that upward migration and adjustment of alpine trees to warmer climate conditions may take from several decades to centuries (11), given biotic and climatic factors (e.g., drought, changes in frost damage and insect and pathogen attacks, soil nutrients, or water availability limitations). However, little is known about processes that control upward displacement of treelines in response to long-term warming, and whether alpine tree lines will respond quickly or not to climate warming occurring since the mid-1800s and accelerating today.

Treeline displacement results from changes in tree recruitment, growth, and mortality (11, 12). These demographic processes are controlled by different drivers and involve biotic and climatic responses and limitations (4, 13⇓⇓–16). In addition to physiological responses to temperature warming (3), geomorphic or topographic conditions also limit upward shifts in alpine treelines (17⇓–19). Species competition often is an important force driving stand dynamics and suppression (e.g., refs. 20⇓⇓–23). Theoretically, altered disturbance regimes and interactions between trees and shrubs or grasses also can affect demographic parameters and determine whether treelines shift upward.

Interactions among plants also may shift from competition to facilitation as environmental stress increases (24), but the role of species interactions as regulators of alpine treeline shifts has been little studied. There are some data that suggest that the presence of shrubs may limit recruitment and tree establishment above the treeline (15, 25⇓–27), but regional studies and transplant experiments have not allowed for quantitative assessment of long-term changes in species interactions at treeline.

Treelines provide a valuable place for investigating interactions between plant species because prevailing environmental conditions are harsh and this could lead to shifts from negative (competition) to positive interactions (facilitation) (cf. refs. 24, 28, and 29). The natural treeline on the Tibetan Plateau (TP) is at the highest elevation—4,900 m above sea level—in the Northern Hemisphere (30). Several climatic proxies show that the past century was the warmest period on the TP over the last millennium (Fig. S1). The TP treelines also are virtually undisturbed by human activities, and both edaphic constraints and slope features allow trees to colonize new areas above the current TP treeline, making the area a good locale for investigating climatic and biotic factors influencing treeline changes (31, 32). Along the eastern TP, tree growth of alpine trees is limited primarily by spring and summer temperatures (Fig. S1) (33⇓⇓⇓⇓⇓–39). In the past 100 y, the region experienced a warming of 1.2–1.5 °C (Fig. S1). Based on an observed temperature-lapse rate of 0.65 °C /100 m on the southeastern TP, an upward displacement of more than 200 m in elevation should be expected on the TP if spring and summer temperature were the single factor limiting tree growth and regeneration, and if treelines were in equilibrium with climate.

Fig. S1.
Fig. S1.

Variations in temperature on the Tibetan Plateau as indicated by tree-ring and ice-core δ18O series. (A) Standardized December–April temperature-sensitive tree-ring width index in the Qilian Mountains of the northeastern Tibetan Plateau (37). (B) Annual temperature reconstruction based on tree rings (40-y moving average) on the northeastern Tibetan Plateau (38). (C) Reconstructed mean temperatures from the previous September to the current April for the Wulan area based on tree-ring chronologies (44). (D) Mean early-summer (June–July) temperature reconstruction based on tree rings in the Hengduan Mountains of the southeastern Tibetan Plateau (34). (E) Mean summer minimum temperature based on tree rings on the southeastern Tibetan Plateau (43). (F) Decadal ice-core δ18O series (an indicator of summer temperature) from the Dunde, Guliya, Puruogangri, and Dasuopu glaciers on the Tibetan Plateau (42). Except for B, the thick gray curves represent the 10-y low-pass–filtered values, and the horizontal lines represent the long-term means. The z-score is calculated by dividing the score deviation (data of each year − mean of the series) by the SD of the series. In addition to the research presented above, tree growth at the treelines/timberlines in our study area responded significantly and positively to summer temperature in the Baima Snow Mountains (33) and the Sygera Mountains (35) of the southeastern TP, Yushu in the source region of the Yangtze River (36), and the Qilian Mountains (39).

Recent studies have reported a range of different changes in treelines on the TP. For example, Baker and Moseley (40) estimated an upward shift of the fir treeline by 67 m from comparisons of repeated photographs from 1923 and 2003 taken at the same points in the Baima Snow Mountains (southeastern margin of TP). Plot-based dendroecological reconstructions, however, showed little changes of fir and spruce treelines in the past 200 y on the eastern and southeastern TP (32, 41). Both local and regional studies are needed to determine why upward treeline shifts occur in some sites and not in others. Based on data from 14 treeline plots located on the eastern TP between 28.4 and 38.5°N (Fig. 1), we addressed two questions: (i) has climatic warming been associated with an upward shift of treeline during the past 100 y; and (ii) could biotic interactions between trees and other plants modulate treeline responses to warming and account for the inconsistent observations of previous studies?

Fig. 1.
Fig. 1.

Location of treeline plots along a latitudinal transect across the eastern Tibetan Plateau (Upper). Variations in the mean temperature and total precipitation in summer (June–August) since the year with available instrumental records at five meteorological stations located close to the study treeline plots (Lower): (A) Zhangye in the middle Qilian Mountains; (B) Yushu in the source region of the Yangtze River; (C) Nyingchi in the valley of the Sygera Mountains; (D) Bomi close to the Ranwu Lake; (E) Deqin close to the Baima Snow Mountains. The instrumental records at Wulan only began in 2001 and are thus not shown. The mean summer temperature at the five stations showed significant and sustained warming trends (statistics are presented), but summer precipitation did not present significant trends.

Results and Discussion

A pronounced warming trend is apparent across the TP (Fig. 1 and Figs. S1–S3). A total of 14 treeline fir and spruce sites in the eastern part of the region showed increased density of tress (“densification”) during the past 100 y (Fig. S4), in line with previous studies in that region (32, 41). A global meta-analysis of treeline response to climate warming also found an increase in stand density during the last century (8). Based on stand age structure of the studied treeline plots in the TP, we found that tree recruitment increased by more than 50% across all sites in the 1950s and 1960s (Fig. 2). Decadal tree recruitment was significantly correlated (P < 0.01) (Table S1) with summer and winter temperatures reconstructed from climatic proxies based on 18O/16O ratios in ice cores and tree-ring widths (42⇓–44) (Fig. 2). Given that the establishment of new trees at treeline usually is limited more by climate than by the distance that seeds can disperse upwards (45), our null hypothesis is that climatic warming of the TP has accelerated and increased tree establishment at the studied sites, and that the treeline moved upwards.

Fig. 2.
Fig. 2.

Trends in: (A) winter-temperature reconstruction based on timberline tree rings on the northeastern Tibetan Plateau (44); (B), ice-core δ18O (18O/16O ratios) series integrated from the Dunde, Guliya, Puruogangri, and Dasuopu glaciers on the Tibetan Plateau (42) indicating summer temperature; (C) summer-temperature reconstruction based on timberline tree rings on the southeastern Tibetan Plateau (43); and decadal tree regeneration at treelines in the six studied regions (D–I) across the Tibetan Plateau and related proxies. The two summer climatic proxies are correlated for decadal intervals back to 1601 (r = 0.77; P < 0.001). See Table 1 and Fig. 1 for research regions and forest plots. Red lines in A and C show decadal moving averages.

Fig. S2.
Fig. S2.

(A–E) The annual mean temperatures showed a significant and sustained warming tendency at five meteorological stations located close to the study treeline plots, whereas precipitation values did not show such a trend (see Fig. 1), except for a slight increasing trend in Bomi. The instrumental records at Wulan only began in 2001 and are thus not shown.

Fig. S3.
Fig. S3.

(A–E) The mean temperatures during the half year when study sites were covered by snow (November–April) showed a significant and sustained warming tendency at five meteorological stations located close to the study treeline plots (see Fig. 1). Except for a significant and increasing trend in precipitation during winter-half year at Yushu and Bomi, the other stations did not show significant trends. The instrumental records at Wulan began in 2001 and they are too short to analyze trends.

Fig. S4.

(A–N) Spatiotemporal variability in tree density and treeline position (maximum elevation reached by trees with stems at least 2-m high indicated in each plot) reconstructed at the alpine treeline plots along a north–south latitudinal transect across the eastern Tibetan Plateau. Each closed symbol represents an individual that was established during the period indicated at the top of the rectangular plot, and open symbols represent trees established during periods previous to that indicated at the top. Different symbols correspond to different establishment periods (e.g., triangles indicate trees established 1661–1710). Plot LZ3 corresponds to the treeline dataset presented in Liang et al. (32).

View this table:
Table S1.

Pearson correlation coefficients (first row for each plot) and significance levels (second row for each plot) calculated by relating tree recruitment data at 14 treeline plots and reconstructed mean summer and winter temperatures in decadal intervals

Based on population age structure in the investigated plots across the treeline ecotone, we reconstructed treeline elevation based on the presence of the tallest trees (≥2 m) in 50-y intervals. A treeline shift of >10 m (equal to the maximum tree height in all study plots) in the last 100 y was considered to be biologically meaningful. Except in the Sygera Mountains, treelines shifted upslope by >10 m during the past century (Table 1 and Fig. S4). At one extreme, treeline of a fir-dominated plot in the Ranwu Lake area (RW3) advanced upward in elevation by 69 m, a spruce-dominated plot by 65 m, and three of four Picea crassifolia-dominated plots in the northeastern TP by 52–80 m.

View this table:
Table 1.

Characteristics of the 14 treeline plots covering six regions from the southeastern to the northern margins of the Tibetan Plateau (site locations in Fig. 1)

However, the average rate of upward shift overall was only 2.9 ± 2.9 m per decade (range: 0–8.0 m per decade), far less than rates reported in previous meta-analyses (6.1–11.0 m per decade) of alpine plants (46, 47). The average rate over the eastern TP also was much less than the rapid upward shift of 91–119 m reported since the 1960s for the Green Mountains in Vermont (7). It also is somewhat less than the upward shift of 4–15 m per decade in High Asia (southern Siberia and along the Urals mountain range) (48⇓–50). The average treeline shift rate we found for the TP, however, was close to that reported for other alpine treelines in the Spanish Pyrenees and northern Siberia (9, 51), With a warming in summer and annual mean temperature of around 1.2–1.5 °C in the past 100 y on the TP (Fig. S1), a slower upward shift implies that drivers other than temperature must be considered to understand treeline dynamics on the TP.

Species interactions could modulate treeline responses to climatic change. Based on the coverage by shrubs (mainly Rhododendron species) or herbs and their mean heights above the treeline, we defined a thickness index (TI) of short vegetation as the product of shrub and grass cover multiplied by their mean height (Materials and Methods). A generalized linear model that included species above the treeline, TI, treeline elevation, mean slope of treeline ecotone, changes in winter temperature and precipitation, and mean winter temperature and precipitation near the study sites explained 97.2% of the variance in treeline dynamics (Table S2). However, only two predictor variables—either TI and species composition or TI and vegetation height—were needed to explain 86.6% of the variance in treeline dynamics. TI alone accounted for over 50% of the variance in treeline dynamics in either model (Table S2). Thus, it appears to be reasonable to use TI as a predictor of the rate of upward motion of treelines in response to warming and shrub-herb abundance (Fig. 3).

Fig. 3.
Fig. 3.

The vegetation TI relates changes in treeline elevation across the Tibetan Plateau in the past 100 y to the product of cover and height of shrubs and herbs.

View this table:
Table S2.

Percentage of variance explained by the models predicting treeline migration rate

A higher coverage index implies stronger interspecific competition that may counteract the effects of warming on tree establishment. The TI ranged from 0.9 to 3.0 in five of the six treeline plots near the Ranwu Lake and in the Sygera Mountains, where the alpine vegetation is dominated by dense Rhododendron mats 1–3 m in height, and the treelines were stable over the past 100 y. In Plot LZ1–3, fir saplings in dense Rhododendron patches have difficulty surviving more than 3 y because the saplings are smothered by fallen shrub litter. Only one treeline in these two regions (RW3) with a low coverage of herbs (TI = 0.30) shifted significantly upward (69 m). In this case, low vegetation cover may have facilitated seedling establishment. Overall, the rate of upward shift in treeline was associated significantly and negatively with TI, suggesting that in addition to climatic amelioration, competition with shrubs and grass controls tree recruitment at treeline on the TP. Under a warming climate, increasing shrub coverage will restrict treeline upward shifts.

In the four regions where the TI ranged from 0.14 to 0.64, we observed upward shifts in treeline from 13 to 80 m over the past century. These low-to-moderate TI values represented conditions where shrubs did not prevent establishment of fir and spruce seedlings above the treeline, but rather created environmental conditions suitable for recruitment and growth. Species above the treeline (tall shrub, short shrub, grass) were used as separate predictors in evaluating treeline changes. Shrubs seem to be stronger inhibitors of tree seedling growth than grasses because the former begin to grow earlier than the latter (52) and outcompete small tree seedlings. At the site with the lowest TI (0.14) spruce treelines moved upslope by ∼80 m. Overall, our results illustrate that tree–shrub competition is unlikely to limit recruitment of tree seedlings when TI < 0.8; under these conditions, upward movement of treeline as a consequence of climatic warming is likely to be observed. Unfortunately, coverage by shrub or grass species above the treeline across all of the investigated plots was never sparse enough to capture a lower TI threshold (which we hypothesize as a TI that is << 0.14); that is, most alpine communities studied did not act as “tree nurseries” and tree recruitment was prevented.

In summary, spatially explicit and quantitative assessments of empirical data on TP treeline dynamics in the past century illustrate that climatic warming tended to promote an upward shift of alpine treelines at local and regional scales. Upslope migration rates, however, were controlled largely by interspecific interactions. Given the lack or low intensity of local disturbances to the TP treelines by herbivores, land use, and the lack of local geomorphic constraints (i.e., availability of sites with regolith above the treeline) on tree regeneration at most sites, interactions between trees and short-statured vegetation could well account for the discrepancy between treeline dynamics and climatic warming. The species interaction mechanism not only helps to explain why many treelines have not advanced in response to climatic warming on a global scale (8), but also highlights that predictions of treeline shifts based on climate envelopes may be misleading because interspecific interactions can temper effects of climatic change.

Materials and Methods

The study area encompassed six regions along a latitudinal transect between the southernmost and northernmost regions of the eastern TP (28.4–38.5°N; linear distance = 1,150 km). The climates of these two regions are influenced strongly by the southern (Baima Snow Mountains, Ranwu Lake, and Sygera Mountains) and East Asian (the source region of Yangtze River) monsoons and westerlies (Qilian Mountains), respectively. Annual precipitation decreases from ∼1,000 mm in the south to ∼350 mm in the north. Annual mean air temperature ranges from 8.5 °C at Bomi (2,800 m) in the south to 4.7 °C at Wulan (2,600 m) in the north. Neither annual nor summer precipitation showed significant trends across all six regions, whereas annual, summer, and winter temperatures showed significant warming trends (Fig. 1 and Figs. S2 and S3). An automated weather station situated at the treeline (4,360 m) in the Sygera Mountains, southeastern Tibetan Plateau recorded a mean air temperature during the growing season of 6.0 ± 0.3 °C from 2007 to 2014, being at its global thermal threshold (5.5–7.5 °C) (3). The growing season is defined as the interval at which soil temperatures at 10-cm depth are higher than 3.2 °C (3).

The treeline research plots were established on gentle to moderately steep slopes with substrates dominated by regolith and located away from talus slopes and avalanche paths (i.e., study plots were in locations more likely to experience warming-induced changes in treeline). The elevations of the alpine treelines declined from 4,478 m on the southeastern TP to 3,386 m on the northeastern TP as latitude increased. These treelines are much lower than the permafrost zone, which has a lower altitudinal limit (i.e., the zone above which permafrost occurs) running from 4,800 m above sea level in the south to 4,200 m above sea level in the north (53). These treelines are usually diffuse in shape and are characterized by dominant tree species in each region (Fig. S5), including Abies georgei, A. georgei var. smithii, Picea likiangensis var. balfouriana, and P. crassifolia (Table 1). There are no krummholz mats or flagged trees in the investigated treeline ecotones.

Fig. S5.
Fig. S5.

A typical Smith fir (Abies georgei var. smithii) treeline ecotone (plot LZ1) where dense rhododendron shrub (Rhododendron aganniphum var. schizopeplum) dominates above the treeline ecotone (photo by E.L.).

The position of the upper treeline was defined by the presence of upright trees with a minimum height of 2 m at the maximum altitude and a continuous distribution above the timberline (forest coverage of more than 30%) in the plot (2, 9, 11). The treeline ecotone refers to the transition from the timberline to the treeless alpine vegetation (3). The upper species limit refers to the highest elevation at which species height is generally shorter than 2 m. One to three spatially independent and rectangular plots (30 ×150 m or 30 × 200 m) were established in each region on a topographically uniform area of the treeline ecotone to include the timberline and the species’ upper limit (9). The longest side (y axis) of each plot was parallel to the elevational gradient formed by the transition from subalpine forest to alpine shrubland or tundra. The bottom left corner of each plot was designated the origin (x, y) = (0, 0). The altitudes of the lower and upper parts of the plots were determined by GPS at a resolution of ±5 m. The location of each tree within the plots was mapped by recording the x and y coordinates at the center of the main stem. Coordinates were measured to the nearest 0.1 m and then corrected by accounting for the mean slope of each plot. Diameter at breast height (DBH, 1.3 m), tree height, and horizontal projection of the tree canopy along the x and y axes were measured for all trees. Tree height was measured directly for trees shorter than 2 m or with a clinometer for trees taller than 2 m.

The cover and height of the vegetation above the treelines were quantified using the point-intercept method (54, 55). Six transects along the elevational (y) axis of each plot were established from the upper treeline to 20 m above the treeline. Transects were spaced 6-m apart perpendicular to the slope: that is, along the axis perpendicular to the maximum slope (x axis) at 0, 6, 12, 18, 24, and 30 m. Percent vegetation cover was calculated based on the number of contacts between plants and a rod located every meter along the elevational axis, and the height of the vegetation was calculated as the mean height of the vegetation at each sample point. A total of 126 points were recorded above the treeline for each plot. To ensure that maximum cover was 100%, multiple contacts at a single sample point were considered to be one contact. The vegetation was dominated by sparse Rhododendron shrubs above the fir treeline in the Baima Snow Mountains (Table 1). Near Ranwu Lake and in the Sygera Mountains, however, Rhododendron shrubs had an extremely high coverage (>90%), and the height of the shrubs ranged from 1.0 to 3.1 m. In Yushu and the Qilian Mountains, the area above the treeline was occupied by dwarf-shrub species with a mean height of 0.45–0.70 m, respectively.

The TI of short vegetation was calculated as percent cover × vegetation height (m) (Table 1). Cover of plants above treelines can act either as nurseries or biotic bottlenecks for seedling survival, depending on cover and plant height (25, 27). The TI contains the effects of both shrub/herb cover and their height on interspecific interactions. However, the shrub or herb cover above the treeline was >20% at all sites. A generalized linear model was used to estimate effects of each predictor variable on treeline changes. We estimated the variance explained by each predictor variable using the R software system and the package relaimpo (56). Based on the “successive sweep method,” we determined whether TI was a significant predictive variable.

Age structures of tree populations at each site were reconstructed using several methods. First, trees with a DBH > 5 cm were cored to the pith at 1.3 m above ground using an increment borer. When cores could not reach the pith, we estimated the number of missing innermost rings with a geometric pith locator. Second, ages of saplings and seedlings (height < 2.5 m and DBH ≤ 5 cm) were nondestructively determined in the field by counting terminal bud scars (internodes or branch whorls) along the main stem (9, 32). Counting internodes, however, may underestimate true seedling ages by up to 4 y (32). Third, to obtain a more accurate estimate of tree age in two height classes (1.3–2 m and ≥2 m) we determined the age of 20 individuals by counting the internodes (Table S3). As in previous studies (9, 32), we assumed that the times required for seedlings to reach 1.3 or 2 m were statistically the same within each plot. Finally, DBH–age relationships established for each plot were used to estimate ages of trees with rotten stems (Fig. S6).

View this table:
Table S3.

Ages of trees reaching heights of 1.3 and 2 m in the treeline plots across the eastern Tibetan Plateau

Fig. S6.
Fig. S6.

Relationships between tree age and DBH (measured at 1.3 m aboveground) in the treeline plots along a latitudinal transect across the eastern Tibetan Plateau.

A simple descriptor of an upward shift of an alpine treeline ecotone is the change in elevation at which the uppermost tree ≥2 m was found during successive time periods. The location of the treeline was reconstructed at 50-y intervals using standard dendrochronological methods (32). Based on population age structures in each plot and the uppermost tree ≥2 m corresponding to an estimated maximum age, treeline position and recruitment in the following 50-y intervals were reconstructed: 1611–1660, 1661–1710, 1711–1760, 1761–1810, 1811–1860, 1861–1910, 1911–1960, and 1961–2011/2012/2013. Fieldwork was done from mid-May to mid-October in 2011, 2012, and 2013. On this timescale, the expected 5-y error associated with the estimated age for trees 2-m tall is negligible. Maximum tree height was ∼10 m at the treelines, so we regarded an upward shift of the treeline of more than 10 m in the past 100 y to be significant (32). The presence of old trees at some sites allowed for reconstruction of treeline position back to the early 17th century (Fig. S4). It was evident that there were no remains of dead trees at or above current treeline at all 14 study sites.

Acknowledgments

We thank Dieter Eckstein for comments on an early version, and the support from the Southeast Tibet Station for Alpine Environment, Observation and Research, Chinese Academy of Sciences, and Third Pole Environment Database (www.tpedatabase.cn). This work was supported by the National Basic Research Program of China (Grant 2012FY111400); the National Natural Science Foundation of China (Grants 41525001, 41130529, and 41301207); the Youth Innovation Promotion Association, CAS; and European Research Council Synergy Grant SyG-2013-610028 IMBALANCE-P (to P.C. and J.P.).

Footnotes

  • ↵1To whom correspondence should be addressed. Email: liangey{at}itpcas.ac.cn.

  • Author contributions: E.L. designed research; E.L., Y.W., and X.L. performed research; E.L., Y.W., S.P., X.L., J.J.C., H.Z., L.Z., A.M.E., P.C., and J.P. analyzed data; and E.L., Y.W., S.P., X.L., J.J.C., H.Z., L.Z., A.M.E., P.C., and J.P. wrote the paper.

  • The authors declare no conflict of interest.

  • This article is a PNAS Direct Submission.

  • This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1520582113/-/DCSupplemental.

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References

  1. ↵
    1. Walther GR, et al.
    (2002) Ecological responses to recent climate change. Nature 416(6879):389–395
    .
    OpenUrlCrossRefPubMed
  2. ↵
    1. Holtmeier FK
    (2003) Mountain Timberlines: Ecology, Patchiness and Dynamics (Kluwer, Dordrecht, The Netherlands)
    .
  3. ↵
    1. Körner C
    (2012) Alpine Treelines: Functional Ecology of the Global High Elevation Tree Limits (Springer, Basel)
    .
  4. ↵
    1. Malanson GP, et al.
    (2007) Alpine treeline of western North America: Linking organism-to-landscape dynamics. Phys Geogr 28(5):378–396
    .
    OpenUrlCrossRef
  5. ↵
    1. Grace J,
    2. Berninger F,
    3. Nagy L
    (2002) Impacts of climate change on the tree line. Ann Bot (Lond) 90(4):537–544
    .
    OpenUrlAbstract/FREE Full Text
  6. ↵
    1. Peñuelas J,
    2. Ogaya R,
    3. Boada M,
    4. Jump A
    (2007) Migration, invasion and decline: Changes in recruitment and forest structure in a warming-linked shift of European beech forest in Catalonia. Ecography 30(6):829–838
    .
    OpenUrlCrossRef
  7. ↵
    1. Beckage B, et al.
    (2008) A rapid upward shift of a forest ecotone during 40 years of warming in the Green Mountains of Vermont. Proc Natl Acad Sci USA 105(11):4197–4202
    .
    OpenUrlAbstract/FREE Full Text
  8. ↵
    1. Harsch MA,
    2. Hulme PE,
    3. McGlone MS,
    4. Duncan RP
    (2009) Are treelines advancing? A global meta-analysis of treeline response to climate warming. Ecol Lett 12(10):1040–1049
    .
    OpenUrlCrossRefPubMed
  9. ↵
    1. Camarero JJ,
    2. Gutiérrez E
    (2004) Pace and pattern of recent treeline dynamics: Response of ecotones to climatic variability in the Spanish Pyrenees. Clim Change 63(1):181–200
    .
    OpenUrlCrossRef
  10. ↵
    1. Danby RK,
    2. Hik DS
    (2007) Variability, contingency and rapid change in recent subarctic alpine tree line dynamics. J Ecol 95(2):352–363
    .
    OpenUrlCrossRef
  11. ↵
    1. Kullman L
    (2007) Tree line population monitoring of Pinus sylvestris in the Swedish Scandes, 1973–2005: Implications for tree line theory and climate change ecology. J Ecol 95(1):41–52
    .
    OpenUrlCrossRef
  12. ↵
    1. Lloyd AH,
    2. Graumlich LJ
    (1997) Holocene dynamics of treeline forests in the Sierra Nevada. Ecology 78(4):1199–1210
    .
    OpenUrlCrossRef
  13. ↵
    1. Cairns DM,
    2. Moen J
    (2004) Herbivory influences tree lines. J Ecol 92(6):1019–1024
    .
    OpenUrlCrossRef
  14. ↵
    1. Wiegand T,
    2. Camarero JJ,
    3. Ruger N,
    4. Gutiérrez E
    (2006) Abrupt population changes in treeline ecotones along smooth gradients. J Ecol 94(4):880–892
    .
    OpenUrlCrossRef
  15. ↵
    1. Smith WK,
    2. Germino MJ,
    3. Johnson DM,
    4. Reinhardt K
    (2009) The altitude of alpine treeline: A bellwether of climate change effects. Bot Rev 75(2):163–190
    .
    OpenUrlCrossRef
  16. ↵
    1. Speed JDM,
    2. Austrheim G,
    3. Hester AJ,
    4. Mysterud A
    (2010) Experimental evidence for herbivore limitation of the treeline. Ecology 91(11):3414–3420
    .
    OpenUrlCrossRefPubMed
  17. ↵
    1. Resler LM,
    2. Butler DR,
    3. Malanson GP
    (2005) Topographicshelter and conifer establishment and mortality in an alpine environment, Glacier National Park, Montana. Phys Geogr 26(2):112–125
    .
    OpenUrlCrossRef
  18. ↵
    1. Butler DR,
    2. Malanson GP,
    3. Walsh SJ,
    4. Fagre DB
    (2007) Influences of geomorphology and geology on alpine treeline in the American West—More important than climatic influences? Phys Geogr 28(5):434–450
    .
    OpenUrlCrossRef
  19. ↵
    1. Macias-Fauria M,
    2. Johnson EA
    (2013) Warming-induced upslope advance of subalpine forest is severely limited by geomorphic processes. Proc Natl Acad Sci USA 110(20):8117–8122
    .
    OpenUrlAbstract/FREE Full Text
  20. ↵
    1. Franklin JF,
    2. Shugart HH,
    3. Harmon ME
    (1987) Tree death as ecological process. Biosciences 37(8):550–556
    .
    OpenUrlCrossRef
  21. ↵
    1. Turner MG
    (2010) Disturbance and landscape dynamics in a changing world. Ecology 91(10):2833–2849
    .
    OpenUrlCrossRefPubMed
  22. ↵
    1. Stueve KM,
    2. Isaacs RE,
    3. Tyrrell LE,
    4. Densmore RV
    (2011) Spatial variability of biotic and abiotic tree establishment constraints across a treeline ecotone in the Alaska range. Ecology 92(2):496–506
    .
    OpenUrlCrossRefPubMed
  23. ↵
    1. Zhang J,
    2. Huang S,
    3. He F
    (2015) Half-century evidence from western Canada shows forest dynamics are primarily driven by competition followed by climate. Proc Natl Acad Sci USA 112(13):4009–4014
    .
    OpenUrlAbstract/FREE Full Text
  24. ↵
    1. Callaway RM
    (1995) Positive interactions among plants. Bot Rev 61(4):306–349
    .
    OpenUrlCrossRef
  25. ↵
    1. Batllori E,
    2. Camarero JJ,
    3. Gutiérrez E
    (2010) Current regeneration patterns at the tree line in the Pyrenees indicate similar recruitment processes irrespective of the past disturbance regime. J Biogeogr 37(10):1938–1950
    .
    OpenUrl
  26. ↵
    1. Elliott GP
    (2011) Influences of 20th century warming at the upper tree line contingent on local-scale interactions: Evidence from a latitudinal gradient in the Rocky Mountains, USA. Glob Ecol Biogeogr 20(1):46–57
    .
    OpenUrlCrossRef
  27. ↵
    1. Grau O, et al.
    (2012) Shrub-tree interactions and environmental changes drive treeline dynamics in the Subarctic. Oikos 121(10):1680–1690
    .
    OpenUrlCrossRef
  28. ↵
    1. Germino MJ,
    2. Smith WK,
    3. Resor AC
    (2002) Conifer seedling distribution and survival in an alpine-treeline ecotone. Plant Ecol 162(2):157–168
    .
    OpenUrlCrossRef
  29. ↵
    1. Greenwood S,
    2. Chen JC,
    3. Chen CT,
    4. Jump AS
    (2015) Temperature and sheltering determine patterns of seedling establishment in an advancing subtropical treeline. J Veg Sci 26(4):711–721
    .
    OpenUrlCrossRef
  30. ↵
    1. Miehe G,
    2. Miehe S,
    3. Vogel J,
    4. Co S,
    5. Duo L
    (2007) Highest treeline in the northern hemisphere found in southern Tibet. Mt Res Dev 27(2):169–173
    .
    OpenUrlCrossRef
  31. ↵
    1. Xu J, et al.
    (2009) The melting Himalayas: Cascading effects of climate change on water, biodiversity, and livelihoods. Conserv Biol 23(3):520–530
    .
    OpenUrlCrossRefPubMed
  32. ↵
    1. Liang E,
    2. Wang Y,
    3. Eckstein D,
    4. Luo T
    (2011) Little change in the fir tree-line position on the southeastern Tibetan Plateau after 200 years of warming. New Phytol 190(3):760–769
    .
    OpenUrlCrossRefPubMed
  33. ↵
    1. Li Z,
    2. Zhang Q,
    3. Ma K
    (2012) Summer temperature variations based on tree-ring data in the central Hengduan Mountains, Northwestern Yunnan, China, AD1475-2003. Clim Change 110(1):455–467
    .
    OpenUrlCrossRef
  34. ↵
    1. Deng Y,
    2. Gou X,
    3. Gao L,
    4. Yang T,
    5. Yang M
    (2014) Early-summer temperature variations over the past 563 yr inferred from tree rings in the Shaluli Mountains, southeastern Tibet Plateau. Quat Res 81(3):513–519
    .
    OpenUrlCrossRef
  35. ↵
    1. Liang E,
    2. Shao X,
    3. Xu Y
    (2009) Tree-ring evidence of recent abnormal warming on the southeast Tibetan Plateau. Theor Appl Climatol 98(1):9–18
    .
    OpenUrlCrossRef
  36. ↵
    1. Liang E,
    2. Shao X,
    3. Qin N
    (2008) Tree-ring based summer temperature reconstruction for the source region of the Yangtze River on the Tibetan Plateau. Global Planet Change 61(3-4):313–320
    .
    OpenUrlCrossRef
  37. ↵
    1. Liu X,
    2. Qin D,
    3. Shao X,
    4. Chen T,
    5. Ren J
    (2005) Temperature variations recovered from tree-rings in the middle Qilian Mountain over the last millennium. Sci China Ser D Earth Sci 48(4):521–529
    .
    OpenUrl
  38. ↵
    1. Liu Y, et al.
    (2009) Annual temperatures during the last 2485 years in the Eastern Tibetan Plateau inferred from tree rings. Sci China Ser D Earth Sci 52(3):348–359
    .
    OpenUrlCrossRef
  39. ↵
    1. Zhang Y,
    2. Shao X,
    3. Yin Z-Y,
    4. Wang Y
    (2014) Millennial minimum temperature variations in the Qilian Mountains, China: Evidence from tree rings. Clim Past 10(5):1763–1778
    .
    OpenUrlCrossRef
  40. ↵
    1. Baker BB,
    2. Moseley RK
    (2007) Advancing treeline and retreating glaciers: implications for conservation in Yunnan, PR China. Arct Antarct Alp Res 39(2):200–209
    .
    OpenUrlCrossRef
  41. ↵
    1. Lv L
    (2011) Timberline dynamics and its response to climate change on the Tibetan Plateau. PhD dissertation (Institute of Botany, Chinese Academy of Sciences, Beijing, China)
    .
  42. ↵
    1. Thompson LG, et al.
    (2006) Abrupt tropical climate change: Past and present. Proc Natl Acad Sci USA 103(28):10536–10543
    .
    OpenUrlAbstract/FREE Full Text
  43. ↵
    1. Zhu H, et al.
    (2011) August temperature variability in the southeastern Tibetan Plateau since AD 1385 inferred from tree rings. Palaeogeogr Palaeoclimatol Palaeoecol 305(1-4):84–92
    .
    OpenUrlCrossRef
  44. ↵
    1. Zhu H, et al.
    (2008) Millennial temperature reconstruction based on tree-ring widths of Qilian juniper from Wulan, Qinghai Province, China. Chin Sci Bull 53(24):3914–3920
    .
    OpenUrl
  45. ↵
    1. Dullinger S,
    2. Dirnböck T,
    3. Grabherr G
    (2004) Modelling climate change-driven treeline shifts: Relative effects of temperature increase, dispersal and invasibility. J Ecol 92(2):241–252
    .
    OpenUrlCrossRef
  46. ↵
    1. Parmesan C,
    2. Yohe G
    (2003) A globally coherent fingerprint of climate change impacts across natural systems. Nature 421(6918):37–42
    .
    OpenUrlCrossRefPubMed
  47. ↵
    1. Lenoir J,
    2. Gégout J-C,
    3. Marquet PA,
    4. de Ruffray P,
    5. Brisse H
    (2008) A significant upward shift in plant species optimum elevation during the 20th century. Science 320(5884):1768–1771
    .
    OpenUrlAbstract/FREE Full Text
  48. ↵
    1. Shiyatov SG
    (2003) Rates of change in the upper treeline ecotone in the Polar Ural mountains. PAGES News 11(1):8–10
    .
    OpenUrl
  49. ↵
    1. Kharuk VI,
    2. Ranson KJ,
    3. Im ST,
    4. Vdovin AS
    (2010) Spatial distribution and temporal dynamics of high-elevation forest stands in southern Siberia. Glob Ecol Biogeogr 19(6):822–830
    .
    OpenUrlCrossRef
  50. ↵
    1. Hagedorn F, et al.
    (2014) Treeline advances along the Urals mountain range—Driven by improved winter conditions? Glob Change Biol 20(11):3530–3543
    .
    OpenUrlCrossRef
  51. ↵
    1. Kirdyanov AV, et al.
    (2012) 20th century tree-line advance and vegetation changes along an altitudinal transect in the Putorana Mountains, northern Siberia. Boreas 41(1):56–67
    .
    OpenUrlCrossRef
  52. ↵
    1. Chapin FS 3rd, et al.
    (2005) Role of land-surface changes in arctic summer warming. Science 310(5748):657–660
    .
    OpenUrlAbstract/FREE Full Text
  53. ↵
    1. Wang B,
    2. French HM
    (1995) Permafrost on the Tibet Plateau, China. Quat Sci Rev 14(3):255–274
    .
    OpenUrlCrossRef
  54. ↵
    1. Barbour MG,
    2. Burk JH,
    3. Pitts WD
    (1987) Terrestrial Plant Ecology (Benjamin Cummings, Menlo Park, CA)
    .
  55. ↵
    1. Camarero JJ,
    2. Gutiérrez E,
    3. Fortin M-J
    (2006) Spatial patterns of plant richness across treeline ecotones in the Pyrenees reveal different locations for richness and tree-cover boundaries. Glob Ecol Biogeogr 15(2):182–191
    .
    OpenUrlCrossRef
  56. ↵
    1. R Development Core Team
    (2013) R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, Vienna). Available at www.r-project.org. Accessed June 24, 2014
    .
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Species interactions slow treeline upward shifts
Eryuan Liang, Yafeng Wang, Shilong Piao, Xiaoming Lu, Jesús Julio Camarero, Haifeng Zhu, Liping Zhu, Aaron M. Ellison, Philippe Ciais, Josep Peñuelas
Proceedings of the National Academy of Sciences Apr 2016, 201520582; DOI: 10.1073/pnas.1520582113
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