Forest Ecology and Management 474 (2020) 118357

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Forest Ecology and Management

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Radial growth response of Pinus yunnanensis to rising temperature and drought stress on the Plateau, southwestern T

Jiayan Shena,b,c, Zongshan Lid, Chengjie Gaoa, Shuaifeng Lia,c, Xiaobo Huanga,c, Xuedong Langa,c, ⁎ Jianrong Sua,c, a Research Institute of Resources Insects, Chinese Academy of Forestry, 650224, China b Nanjing Forestry University, Nanjing 210037, China c Puèr Forest Ecosystem Research Station, National Forestry and Grassland Administration of China, Puèr 665000, China d State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China

ARTICLE INFO ABSTRACT

Keywords: The relative influence of energy and water availability on tree growth at specific sites under warming conditions Tree radial growth remains insufficiently understood on the Yunnan Plateau, which obstructs the rational selection and develop- Warming ment of forest management measures in the context of climate change. In this study, a dendroecological in- Drought stress vestigation was conducted in four sites on the Yunnan Plateau to evaluate growth trends and climate responses P. yunnanensis of Pinus yunnanensis under warming and drought stress across cold-dry (CD), warm-humid (WH), warm (WR), Climate zones and hot-dry (HD) zones. The effects of energy and water availability on the radial growth of P. yunnanensis varied Yunnan Plateau in different sites and showed site-specific characteristics. The radial growth of P. yunnanensis in the CD zone benefited from rising temperatures, especially in the pre-growing season and core growing season. However the radial growth of P. yunnanensis in the WH zone was restricted by excess water in the core growing season. The radial growth of P. yunnanensis in the WR and HD zones became increasingly limited by temperature and drought stress, and the growth switched from responding to energy stress to moisture stress. The sensitivity of P. yun- nanensis to climate factors in the warm-humid zone and humid seasons was relatively stable; in contrast, this species was vulnerable to warming and drought stress under harsh growth conditions and showed considerable instability. Intense warming in the future may cause a significant variation of tree growth response to climate. It would trigger a noticeable redistribution effect of energy and water availability on forest growth, which moti- vates assessments of climate-growth relationships, not only at large spatial scales, but also in specific sites. This research provides a basis for the adoption of effective forest management measures for specific sites according to their response characteristics associated with the distribution of climate drivers.

1. Introduction season can decrease photosynthesis. All these situations may not be conductive to the storage of photosynthetic products for growth (Sidor Forests are essential components of the Earth’s ecosystem, and cli- et al., 2015; Ponocná et al., 2016; Conlisk et al., 2017). However, the mate change has severely influenced the productivity, carbon stocks, synergistic effect of temperature and moisture may affect tree growth in community structure, and species compositions of forest in recent different ways at specific sites and among seasons (Gao et al., 2018). decades (Seidl et al., 2017; Ponocná et al., 2018). Environmental var- For instance, tree growth at high elevations is mostly temperature- iations in tree growth are typically attributed to the comprehensive limited, whereas that at lower elevations is more sensitive to pre- impact of temperature, precipitation, and other environmental factors cipitation variations (Fritts, 1976; Fan et al., 2008a; Salzer et al., 2009; rather than a single driver (Walther, 2004; Piao et al., 2014; Seddon Körner, 2012; Huo et al., 2017). Tree growth in cold environments will et al., 2016; Jung et al., 2017). Temperature and precipitation are two benefit from warming, whereas in moisture-limited regions, growth will distinct climate factors that can balance and interact with each other. be restricted by drought stress caused by warming (Dang et al., 2012; High temperature and low precipitation enhance drought stress, Liu et al., 2013; Conlisk et al., 2017). whereas low temperature and high precipitation during the growing Precipitation in the growing season and even pre-growing season

⁎ Corresponding author. E-mail address: [email protected] (J. Su). https://doi.org/10.1016/j.foreco.2020.118357 Received 8 April 2020; Received in revised form 19 June 2020; Accepted 21 June 2020 Available online 08 July 2020 0378-1127/ © 2020 Elsevier B.V. All rights reserved. J. Shen, et al. Forest Ecology and Management 474 (2020) 118357 has apparent effects on trees: adequate rainfall during the growing The current research provides insight into whether distantly spaced season facilitates the photosynthetic process and promotes growth. For individuals share common climatic constraints and how these climatic example, the impacts of spring precipitation on tree growth are parti- constrains vary with the warming effect. cularly evident in arid and semi-arid regions (Antonova and Stasova, In this study, we aim to examine how the relative importance of 1993; Caritat et al., 2000; Gruber et al., 2010; Ren et al., 2015). Tem- climatic drivers of tree growth vary with climate warming across spe- perature and water availability are projected to change dramatically in cific sites, and to investigate how the variation in temperature and the future, and many studies have revealed noticeable warming and water availability affect the growth trajectory of P. yunnanensis on the drying characteristics in many areas around the world (Truettner et al., Yunnan Plateau. Based on the hypothesis that plant growth in cold 2018; Babst et al., 2019; Schurman et al., 2019). Rising temperature environments is controlled by temperature, whereas in drought en- and drought stress may seriously affect the growth trajectories of forests vironments, plant growth controlled by moisture (Körner, 2015; (Tei et al., 2017). Thus, a better understanding of the interplay between Ponocná et al., 2016; Conlisk et al., 2017), we hypothesize that the temperature and water effects is essential to predict changes in the radial growth of P. yunnanensis in cold environments would benefit growth dynamics of forests and to assess potential ecosystem vulner- from warming, whereas more severe drought stress would be en- ability (Fan et al., 2009a). Recent studies have revealed that the re- countered in moisture-limited regions under warming. We tested the lationship between regional vegetation growth and large-scale climate radial growth trends of P. yunnanensis in response to climate change variability shows a temporally weakening phenomenon (Carrer and across different climate zones based on the tree-ring width index (RWI). Urbinati, 2006; Gao et al., 2018; Fkiri et al., 2019). The relationship Furthermore, we tested the temporal stability of the climate growth between vegetation productivity and temperature changes over time relationships of P. yunnanensis, which not only has fundamental im- following the alterations in other environmental factors; and the plications for reconstructions of natural climate variability on the strength of this relationship decreases with an increase of drought (Shi Yunnan Plateau but could also provide an opportunity to determine et al., 2010; Piao et al., 2014). In response, researchers have focused on whether the year-to-year climate growth response is stationary over the stability of the relationship between climate change and the radial time. The findings of this research will contribute to simulating the growth of trees (Porter and Pisaric, 2011; Li et al., 2010); however, radial growth and distribution dynamics of P. yunnanensis under various further studies are needed to explore the occurrence and possible causes climate change scenarios and aid in predicting the performance of of variation in growth-climate relationships to assess the nature of these forests in the southwestern region of China under global climate change changes in detail (Carrer and Urbinati, 2006). to allow the rational formulation of forest management policies at P. yunnanensis is the most typical dry and warm coniferous species specific sites. in southwestern China. It is ranked within the top ten dominant tree species in China, in terms of area and volume (Forest Resources 2. Materials and methods Management Division, SFA of China, 2010) and is mainly distributed in the western part of southwestern China from 1 500 to 3 000 m above 2.1. Study area and climate sea level. The Yunnan Plateau, located in the west of southwestern China, is the central region for the growth of P. yunnanensis (Deng et al., This study was conducted in the P. yunnanensis natural forest eco- 2013, 2014) and is the core drought region in the area, with seasonal system of the Yunnan Plateau, southwestern China. Previous research drought and multiple recurrence trends (Wang et al., 2010; Xing and on P. yunnanensis divided the distribution region of P. yunnanensis Ree, 2017). The severe drought on the Yunnan Plateau is mainly due to forests into distinct groups for the stereo climate on the Yunnan Plateau much lower precipitation and much warmer temperature than normal (Jin and Peng, 2004). Thus, we divided our research region into four years or seasons (Wang and Meng, 2013; Zhang et al., 2013). distinct groups that correspond to cold-dry (CD), warm-humid (WH), In consideration of the effect of the redistribution of climatic drivers warm (WR), and hot-dry (HD) climate zones based on the growing on global tree growth, several studies have found that the importance season temperature from April to October and the total annual pre- and seasonality of temperature and water availability on tree growth cipitation of each meteorological site (Babst et al., 2019) in the P. vary among different climate regions around the world (Babst et al., yunnanensis distribution area using cluster analysis (Frey and Dueck, 2019; Schurman et al., 2019). Most previous studies mainly focused on 2007)(Fig. S1). We calibrated the temperature data of each station by climate-growth response heterogeneity across latitude and altitude using the lower limit distribution of the P. yunnanensis forest according changes based on single samples and the alpine tree-line ecotone of to the theory that the temperature drops by 0.6 °C per 100 m of altitude high mountains (Fan et al., 2008a, b, 2009b; Liang et al., 2014, 2015; (Fang, 1992; Wang et al., 2014) prior to cluster analysis. We selected a Lyu et al., 2016, 2017; Wang et al., 2017), or at a larger regional scale representative sample point for each climate zone for tree ring samples (Babst et al., 2019; Zhang et al., 2019). However, the latest research collection after clustering was completed. (JC), suggests that the impact of drought on tree growth is dependent on the County (TC), Xinping (XP) and (YM) re- type of sites where trees grow and on their growth performances rather present CD, WH, WR and HD climate zones, respectively. The four sites than their latitudinal location (Bose et al., 2020). Large regional and are within the typical distribution area of the P. yunnanensis forest spatial studies on the climate-growth response usually minimized or (Fig. 1). even ignored the effects of potentially confounding factors, such as Jianchuan County is located on the northwestern Yunnan Plateau geographic location and local site conditions (Maes et al., 2019; Bose (Fig. 1). The climate is cold and dry with an average annual tempera- et al., 2020). Instead, many studies characterized growing season and ture of 12.6 °C and a growing season temperature of 16.5 °C. The climate changes according to a pre-defined meteorological season, average annual rainfall is 749 mm (Fig. 2a). Tengchong County is lo- which overlooks the site-specific climate-growth signals for the study cated at the junction of Yunnan Province and Myanmar (Fig. 1); the season is not the most relevant period for tree radial growth. The var- region has a tropical monsoon climate characterized by warm and iations of climate-growth responses across a specific site are a crucial humid conditions, and the climate is favorable for plant growth during factor in understanding how forests respond to climate change and summer and autumn (June to November) and is warm in winter and make up for the limitation of the spatial explanatory power of single- spring (December to May). The average annual temperature is 15.4 °C, site research as well as the lack of site-specific climate-growth signals and the temperature of the growing season is 18.6 °C. The average (Lévesque et al., 2014; Vila-Cabrera et al., 2015; López et al., 2016; annual rainfall is 1532 mm, and more than 85% of rainfall is con- Bose et al., 2020). These studies provide a foundation for the current centrated between May and October (Fig. 2b). Xinping County is lo- study to investigate the relative importance and spatial manifestation of cated on the central Yunnan Plateau (Fig. 1) and has a warm climate. climate drivers of P. yunnanensis at specific sites on the Yunnan Plateau. The average annual temperature is 17.5 °C, the temperature of the

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yunnanensis forest along elevation gradients from the forest lower limit edge to the middle area and upper edge. Two increment cores per tree were collected at a height of 1.3 m with a 5.15-mm-diameter increment borer. At least 60 trees were sampled at each specific site, with a minimum of 20 trees at each elevation. We followed standard dendrochronological techniques for sample preparation and chronology development (Cook and Briffa, 1990). The collected cores were air-dried, fixed in a wooden trough, and polished with 120-, 400-, and 600-grit sandpaper until ring boundaries were distinct and visible under magnification (Stokes and Smiley, 1996). Tree-ring width was measured at 0.001-mm resolution under a stereo- microscope, which was linked to a LINTAB digital positioning table (LINTAB™ 6, Rinntech, Germany). We precisely confirmed the year of each annual ring, which was cross-dated through curve comparison, and we determined the quality of the cross-dating with the COFECHA program (Holmes, 1983). We then removed the autocorrelation and low-frequency signals of tree growth. The sliding correlation coefficient between sequences (or between sequence and chronology) were cal- culated to test and correct the cross-dating results. The series of suc- cessful dating was highly correlated; the rings that had a low correla- tion with the main series and those that could not be accurately dated were rejected. Finally, a total of 309 cores from 192 P. yunnanensis trees Fig. 1. Map of the study region, the sampling sites, and the nearest meteor- (59 cores from 38 trees at the JC site, 65 cores from 41 trees at the TC ological stations in Yunnan Province. site, 93 cores from 59 trees at the XP site, and 92 cores from 54 trees at the YM site) were cross-dated (Table 1). growing season is 19.6 °C, and the average annual rainfall is 951 mm We standardized the raw ring-width measurements into a di- (Fig. 2c). Yuanmou County is located on the central Yunnan Plateau mensionless time series of ring-width indices with the negative-ex- (Fig. 1), and the climate is hot and dry. The average annual temperature ponential curve function or the spline function in the ARSTAN program is 21.7 °C, and the temperature of the growing season is 23.3 °C, with an (Cook, 1985). This was done to remove age-related biological growth average annual rainfall of 632 mm (Fig. 2d). trends and the incongruent fluctuation from inhibition and release of interference competition among trees while preserving growth varia- 2.2. Tree-ring sampling and chronology development tions that are likely to be related to climate variability (Fritts, 1976). Finally, we built four standard chronologies (STD) (Fig. 5), the statistics At each site, we randomly selected healthy adult trees that domi- for which are provided in Table 1. The expressed population signal nated the canopy layer to sample cores in a well-protected natural P. (EPS) was calculated for the common analysis period to evaluate

Fig. 2. Climate diagrams of the study area showing monthly air temperatures and precipitation at the Jianchuan site from 1951 to 2016 (a), Tengchong site from 1951 to 2016 (b), Xinping site from 1951 to 2016(c) and Yuanmou site from 1956 to 2016 (d).

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Table 1 Statistics of P. yunnanensis tree-ring width standard chronologies for each representative site.

Residual chronology Site name

Jianchuan (JC) Tengchong (TC) Xinping (XP) Yuanmou (YM)

Elevation (m) 2700–3100 2000–2500 1250–1580 1850–2430 Sample size(trees/radii) 38/59 41/65 59/93 54/92 Chronology span 1961–2018 1978–2018 1965–2018 1956–2018 Mean sensitivity (MS) 0.11 0.080 0.16 0.14 First-order autocorrelation (AC1) 0.748 0.700 0.569 0.442 Correlations between cores 0.200 0.308 0.313 0.272 Variance in the first eigenvector (%) 29.25 40.16 34.92 33.56 Standard deviation (SD) 0.18 0.14 0.22 0.17 Signal-to-noise ratio (SNR) 6.76 11.56 14.56 10.85 Expressed population signal (EPS) 0.871 0.920 0.936 0.916 whether the chronology was representative of the sampled populations, relationships of radial growth to climate change (Mérian et al., 2011). based on the commonly used threshold of 0.85, which is considered to We analyzed the radial growth trend by evaluating the variation in indicate a satisfactory quality of a chronology (Fritts and Shatz, 1975; the tree-ring width index (RWI) to identify whether the radial growth of Wigley et al., 1984). The EPS for all sites exceeded 0.85, indicating that P. yunnanensis declined under warming and drought conditions at each the theoretical population for each chronology was well represented. site. We calculated the percentage change in tree ring width on a 10- year time scale with the following equation (Payette et al., 1990):

2.3. Evaluation of climate growth relationships %GCiiiiiii=−[( M,4+−−−− M 5,1)/ M 5,1 ] × 100% fi At each sampling point, we quantified the response of interannual where GCi is the rate of growth change of trees in the second and rst fi variability in tree growth to four climate parameters before and after ve years in the i-th year, Mi,i+4 and Mi−5,i−1 represent the average − − climate warming and drying. The temperature and precipitation were ring width index of year i to i+4and year i 5 to i 1, respectively. used as metrics of energy and water availability, respectively. The A negative rate indicates suppression of tree growth, and when the rate vapor pressure deficit (VPD) and standardized precipitation evapo- is less than 25%, it indicates that the growth of P. yunnanensis declined transpiration index (SPEI) are widely used to reflect drought conditions during the study period. (Zhang et al., 2019). The meteorological data were selected from the meteorological station nearest to each sampling point. The JC site used 3. Results data from meteorological station, the TC site used data from Tengchong meteorological station, the XP site used data from 3.1. Climate variation meteorological station, and the YM site used data from Yuanmou me- 2 teorological station (Fig. 1). The data were from 1951 to 2016 for the The temperature significantly increased at the JC (R = 0.46, 2 2 JC, TC, and XP sites, and from 1956 to 2016 for the YM site. The P < 0.001), TC (R = 0.36, P < 0.001), and XP (R = 0.29, monthly average temperature and monthly precipitation were obtained P < 0.01) sites during the late sub-period (1985–2016), whereas the from the China Meteorological Science Data Sharing Service Network temperature at the YM site showed no significant increasing trend 2 (http://data.cma.cn/data/weatherBk.html). The VPD was calculated (R = 0.112, P > 0.05) (Fig. 3a, b). The annual total precipitation at based on temperature and relative humidity (Almeida and Landsberg, all sites showed an indistinctive decreasing trend (P > 0.05) (Fig. 3d). 2 2 2003; Şahin et al., 2013). The SPEI (1901–2013) was extracted from the The VPD at the JC (R = 0.403, P < 0.001), TC (R = 0.218, 2 CRU grids of the Royal Netherlands Meteorological Service website P < 0.01), XP (R = 0.389, P < 0.001) sites significantly increased, (https://climexp.knmi.nl/start.cgi) at a resolution of 0.5° × 0.5°. The but an indistinctive increasing trend was found at the YM site in the late 2 SPEI series was used to quantitatively describe the precipitation and sub-period (R = 0.046, P > 0.05) (Fig. 3c), revealing that the potential evapotranspiration, as well as rising temperature-induced drought stress of the four sites strengthened from 1985 to 2016. water demand (Vicente-Serrano et al., 2010). The climate-growth relationships were determined using Pearson’s 3.2. Climate-growth relationships correlation analyses. Considering the lag effects of the climate response. We calculated correlations between the tree-ring data (STD chronology) The climate-growth response relationships varied across different of each site and monthly climate data (including temperature, pre- time periods and climate zones. In the CD zone (JC site) (Fig. 4a, Table cipitation, VPD, and regional SPEI) over an 18-month period from May S1a), compared to the early sub-period (1961–1984), the correlations of of the previous year to October of the current year. In order to test the radial growth with temperature (P < 0.05), VPD (P < 0.01) and growth sensitivity to the temporal change in climate at each site, we precipitation (P < 0.01) in February of the current year significantly analyzed the climate-growth response relationships over two different strengthened in the late sub-period (1985–2016); the positive correla- sub-periods: 1961–1984 and 1985–2016 for the JC site, 1972–1984 and tion of radial growth with temperature (P < 0.05) significantly 1985–2016 for the TC site, 1965–1984 and 1985–2016 for the XP site, strengthened but significantly weakened with precipitation (P > 0.05) 1956–1984 and 1985–2016 for the YM site with the Dendroclim2002 in August of the current year in the late sub-period (1985–2016). In the program (Biondi and Waikul, 2004). In order to investigate the tem- WH zone (TC site) (Fig. 4b, Table S1b), compared to the early sub- poral stability of the climate-growth relationships of each site, we cal- period (1961–1984), the correlations of radial growth with temperature culated the slipping response correlation coefficient between tree-ring (P < 0.05), VPD (P < 0.05) and precipitation (P < 0.01) in May of width chronologies and climate factors for a 25-year period using the the current year significantly strengthened in the late sub-period mdcc function in the bootRes package in R (R Development Core Team, (1985–2016); the negative correlations between growth and SPEI 2012), and a sliding response color temperature map was created using (P < 0.05) in June to August of the current year significantly the mdcplot function (Zang and Biondi, 2013). This analysis has been strengthened in the late sub-period (1985–2016). In the WR zone (XP previously shown to accurately describe the dynamic response site) (Fig. 4c, Table S1c), compared to the early sub-period

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Fig. 3. Annual climate trends at Jianchuan (1951–2016), Tengchong (1951–2016), Xinping (1951–2016) and Yuanmou (1956–2016) climate stations. (a) Mean air temperature, (b) minimum air temperature, (c) VPD, and (d) total precipitation.

(1961–1984), the correlations of radial growth with temperature period (1961–1984), the negative correlations of radial growth with (P < 0.05), VPD (P < 0.05), precipitation (P < 0.05) and SPEI temperature in February and May to July of the current year sig- (P < 0.05) in May of the current year significantly strengthened in the nificantly strengthened in the late sub-period (1985–2016); the nega- late sub-period (1985–2016); the negative correlations of radial growth tive correlations of radial growth with VPD in November and December with temperature (P > 0.05) and VPD (P > 0.05) in March of the of the previous year and February, March, May to July of the current current year significantly weakened in the late sub-period year significantly strengthened (P < 0.05) in the late sub-period (1985–2016); the positive correlations of radial growth with SPEI (1985–2016); the positive correlations of radial growth with pre- strengthened significantly in the late sub-period (1985–2016). In the cipitation (P < 0.05) in May significantly strengthened in the late sub- HD zone (YM site) (Fig. 4d, Table S1d), compared to the early sub- period (1985–2016); the positive correlations of radial growth with

(a) Jianchuan (b) Tengchong

Tmp -+++- +-Tmp +--+--- -- +---- VPD - ----+++VPD + + ++- +- ++- - Pre + --+--+++----Pre - -++ - +-+ - SPEI ------SPEI ---- m j j a so n d JFMAMJ JASO mj j a so n d JFMAMJ JASO

(c) Xinping (d) Yuanmou Tmp ++ ++ +---+- Tmp ------VPD ++++---+VPD ------+ Pre - + +++ -- Pre + +++ + ++ +-- SPEI ++ SPEI ++++++++++++++++++ m j j a so n d JFMAMJ JASO mj j a so n d JFMAMJ JASO

Early sub-period Late sub-period Label Early sub-period Late sub-period Label Early sub-period Late sub-period Label Variation patterns of correlation P >0.05 P >0.05 P<0.05 P<0.05 Positive Negative - P >0.05 P <0.05 P<0.05 P>0.05 Negative Positive +

Fig. 4. Variation of correlation coefficients of standard chronologies at each site with monthly climate data from May of the previous year to October of the current year across the early sub-periods and late sub-period. Small and capital letters refer to the respective previous and current years. The early sub-period at the Jianchuan site is 1961–1984, at the Tengchong site is 1972–1984, at the Xinping site is 1965–1984, and at the Yuanmou site is 1956–1984; the late sub-period at all sites is 1985–2016.

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Fig. 5. Growth variations (tree-ring width index, RWI) (red line) and the rate of change of growth in the second and first five years in the i-th year (GCi) (green line) of P. yunnanensis. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

SPEI (P < 0.05) in June to November of the current year significantly unstable and changed to negative during the period of 1984–2016. The strengthened in the late sub-period (1985–2016). correlations of chronology with temperature and precipitation in May were stable at the TC site (Fig. 7B). At the XP site (Fig. 7C), the cor- relation between chronology and temperature in May was unstable and 3.3. Growth trend of P. Yunnanensis in response to climate variation changed to significantly negative during the period of 1975–2016, and the positive correlations with precipitation in May were significantly We used the tree-ring width index (RWI) to analyze the growth strengthened during the period of 1981–2016. At the YM site (Fig. 7D), trend of P. yunnanensis in response to climate variation at each specific the correlation between chronology and temperature in June was site (Fig. 5 and Fig. 6). The RWI showed a significant increasing trend at stable, but unstable in July and August. The correlations of chronology the JC site (P < 0.001) but an insignificant increasing trend at the TC with precipitation in February and April were stable, but unstable in site (P > 0.05) and XP site (P > 0.05), and an insignificant downward March and May. trend at the YM site (P > 0.05). The climate-growth relationships varied clearly in different time periods and at different sites. The po- sitive correlation of RWI with precipitation (P < 0.05) and SPEI 4. Discussion (P > 0.05) at the JC site changed to negative in the late sub-period (1985–2016) (Fig. 6a). The negative correlation of RWI with SPEI 4.1. Site-specific growth responses to warming and drought stress (P < 0.05) significantly strengthened at the TC site in the late sub- period (1985–2016) (Fig. 6b). At the XP site, the positive correlation of Our results revealed that the degrees of warming and drying showed RWI with precipitation (P < 0.01) significantly strengthened in the site-specific characteristics during the period of 1985–2016 (Fig. 3). late sub-period (1985–2016) (Fig. 6c). At the YM site, the negative Climate change in recent decades is likely to modify the climate-growth correlations of RWI with temperature (P < 0.01) and VPD (P < 0.01), response relationships, showing variation in intensity and seasonal and the positive correlations with precipitation (P < 0.05) and SPEI differences across different climate zones. The radial growth of P. (P < 0.05), significantly strengthened in the late sub-period yunnanensis trees in the cold-dry zone (JC site) showed a greater sen- (1985–2016) (Fig. 6d). sitivity to energy and water availability in February (Fig. 4 and Table S1a), while that in the warm-humid zone (TC site) was more sensitive to 3.4. Stability of radial growth response to climate change energy and water availability in May, and drought stress as well as the excessive humid environment of the core growing season (June to The dynamic responses of radial growth to climate factors from August) (Fig. 4 and Table S1b). The results indicated that the effect of December of the previous year to August of the current year were warming on tree growth in a cold-dry environment was more focused evaluated by the slipping correlation function during the period of on the periods of cambium activity and differentiation. The rising 1962–2016 at the JC site, 1973–2016 at the TC site, 1966–2016 at the temperature and precipitation during the cambium active phase could XP site, and 1957–2016 at the YM site. At the JC site (Fig. 7A), the supply the energy and soil moisture for xylem cell production and the correlations of chronology with temperature in May and June were onset of xylogenesis (Liang et al., 2014; Ren et al., 2015; Li et al., 2017; significantly strengthened during the period of 1971–1998; the corre- Panthi et al., 2017) as well as lengthen the period of wood formation lations of chronology with precipitation in July and August were (Rossi et al., 2016). In the warm-humid zone, warming moved up the

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Fig. 6. The relationships of the tree-ring width index (RWI) with four climate factors (annual mean temperature/Tmp, annual total precipitation/Pre, vapor pressure deficit/VPD and standardized precipitation evapotranspiration index /SPEI) at each site during different periods. The asterisks (*) and (**) indicate that the variable had a significant (P < 0.05) or extremely significant (P < 0.01) influence, respectively, on RWI. core growing season (June to August) of trees to May, and appropriate 4.2. Site-specific growth trend in response to warming and drought stress rainfall and temperature during this period could help to promote cambium activity and benefit growth (Begum et al., 2012; Ren et al., We compared the growth trends of P. yunnanensis at the four sites 2015). However, precipitation in May in this region reached a sufficient through the RWI and the growth rate change (GCi) under warming and level (Fig. 2b), which is likely to cause the temperature to drop, in- drought conditions. P. yunnanensis growth in the cold-dry zone (JC site) hibiting radial growth. The warming could compensate for the negative gradually strengthened and became less sensitive to precipitation and effects of too much rainfall and promote growth throughout the core drought stress (Fig. 6a). The JC site is located at an altitude of 3000 m; growing season (June to August) (Lévesque et al., 2013). Trees in the the temperature is very low in the pre-growing season (February to warm zone (XP site) became more sensitive to drought stress, energy, May), and the warming effect could advance and prolong the growing and water availability in May and June. By contrast, trees growing in season, particularly at high elevations where tree growth is limited by the hot-dry zone (YM site) were more sensitive to the energy and water low temperature (Jiang et al. 2014; Cuny et al., 2015; Yang et al., availability in pre-growing season (February to May) and core growing 2017). The results further indicate that tree radial growth at high ele- season (June to August), as well as the drought stress in core growing vations is more strongly related to ontogeny and temperature than to season (June to August). The warming in the warm zone (XP site) is water availability (Babst et al., 2013; Hagedorn et al., 2014; Camarero likely to enhance the moisture stress and cause the growth of P. yun- et al., 2015). In contrast to the cold-dry zone, the growth of P. yunna- nanensis to become increasingly sensitive to moisture availability nensis in the warm-humid (TC site) and warm (XP site) zones showed an (Bryukhanova et al., 2013), which is consistent with previous findings insignificant increasing trend and an insignificant decreasing trend in that growth is most sensitive to drought at sites with a low water- the hot-dry zone (YM site). The promoting effect of warming on growth holding capacity (Biondi, 2000; Rigling et al., 2002). This is also con- would increasingly weaken with the decreased response of P. yunna- sistent with the finding that global warming can cause boreal forest nensis to temperature (Shen et al., 2019). Heat waves and drought stress trees to become more sensitive to moisture (Babst et al., 2019). The hot- have negative impacts on vegetation, even in humid areas (Allen et al., dry zone (YM site) is located in a hot-dry valley area in which 90% of 2010; Babst et al., 2019), as temperature-related increases in atmo- the rainfall occurs between May and October, leading to severe water spheric water demand may offset the beneficial effect of warming shortages and drought stress during the dry season. Drought conditions (Barber et al., 2000). Combined with the variation of GCi, we found that severely restrict the utilization of the thermal advantage of energy the growth of trees in the warm-humid zone declined during the period (Anderegg et al., 2012; Garcia-Forner et al., 2016). Higher energy in- of 1995–2001, and the growth of P. yunnanensis in the warm zone de- puts in warmer summers could negatively influence the water status in clined during the period of 2002–2012. However, the recovery rate of the core growing season (June to August) and shorten the growing tree growth in the warm zone was faster than that in the warm-humid season (Lévesque et al., 2014; Will et al., 2013). Lower winter tem- zone as the climate conditions improved, which further supports the perature is the main climatic constraint on tree growth at temperature- idea that changes in drought seasonality or increases in drought se- limited sites, while water deficits in spring to summer are the main verity and duration might be detrimental for tree survival, especially in constraint at moisture-limited sites. regions with optimal climate conditions for plants (Anderegg et al.,

7 J. Shen, et al. Forest Ecology and Management 474 (2020) 118357

Fig. 7. The moving correlation results of tree-ring width chronologies with monthly climate factors from December of the previous year to August of the current year

(Tmp: monthly mean temperature, Pre: monthly total precipitation). Moving window: 25 years. Small and capital letters refer to the respective previous and current years.

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2013). The results reflects that the trees living in arid environments are annual variability in precipitation. The stability of climate-growth re- able to improve water use efficiency or adopt hysteresis growth re- lationships is geographically limited and species-specific, and we sug- sponses to resist the adverse effects of drought (Bréda et al., 2006; gest that time-dependent variables should be considered in further re- Eilmann et al., 2009; Martín-Benito et al., 2008). The restrictive func- search to prevent inaccurate reconstruction of past climate variability tion of high temperature and low water availability and drought stress and to allow the establishment of a climate-growth model (Marco and on the growth of trees at the hot-dry site strengthened with warming. Carlo, 2006; Li et al., 2014). Combined with the variation of GCi, the growth of trees was restricted and thus declined during the periods of 1983–1987 and 2009–2011. 5. Conclusion Trees growing in hot-dry zones are likely to grow under moisture lim- itation during extended periods of the years; the variation of pre- Our analysis indicates a clear site-specific response of P. yunnanensis cipitation or evaporative demand during these periods will directly radial growth to warming and drought stress on the Yunnan Plateau. affect the water availability of the trees and thus their physiological Tree growth is highly dependent on local climate characteristics rather responses, resulting in lower growth (Cabon et al., 2020). The phy- than on large-scale climate change. Large regional climate changes siology and growth of trees at a site without limitation of moisture will generally have indirect effects on tree growth by changing the site- be less restricted by precipitation (Martínez-Vilalta et al., 2009). Thus, specific climate characteristics. Our results support the hypothesis that it is reasonable that climate control on tree growth is stronger in warm growth of P. yunnanensis in cold regions becomes more sensitive to (XP site) and hot-dry (YM site) zones than in cold-dry (JC site) and temperature, whereas in hot and dry regions, growth of P. yunnanensis warm-humid (TC site) zones (Fig. 6 and Table S2). becomes more sensitive to moisture and is increasingly temperature restricted. The climate drivers for tree growth are redistributed under 4.3. The effect of climate change on the response stability of different climate warming. A gradually warming climate would reduce the regions growth of trees in water-limited areas. The site-specific response of P. yunnanensis to warming and drought stress provides useful information Tree rings are the most widely used and most valuable materials to to understand the redistribution of energy and moisture factors under substitute for climate data measurements at the millennium scale different climate zones, which may help to understand the adaptive (Carrer and Urbinati, 2006). The ‘uniformitarian principle’ generally strategies and ecological thresholds of P. yunnanensis. This information assumes that the relationship between tree growth and limiting climate could be used to construct corresponding measures of forest manage- factors is stable over time (Fritts, 1976; Britannica Concise ment based on the different response characteristics of different climate Encyclopædia, 2005); however, the temporal stability of radial growth zones to minimize the impact of climate change on forests. Our analysis in response to climate variation remains a matter of debate (Hu et al., has revealed that the sensitivity of radial growth to climate in the 2016; D’Orangeville et al., 2018; Shi et al., 2018). A reduction in the warm-humid regions and humid seasons is relatively stable compared sensitivity of tree-ring records to temperature since the mid-20th cen- with harsh growth conditions and dry seasons. The knowledge not only tury has been found in several circumpolar northern latitude sites provides new insights into the temporally varying patterns of the re- (D’Arrigo et al., 2008), which is a challenge to the application of tra- lationships between tree growth and climate factors, but also provides ditional dendrochronological theory (D’Arrigo et al., 2008). It is an opportunity to better test the concept that the effects of climate therefore necessary to determine the stability of the response relation- forcing on tree growth are changing. The sensitivity of trees of different ships between the radial growth of trees and climate factors over larger ages and different species to climate varies greatly, but available data areas (Jiao et al., 2019). do not allow us to quantify the effects of these factors, which will be the The results of our study indicated that the stability of the climate subject of subsequent analyses. signal varied with warming, which was also supported by the monthly correlation variables in different sub-periods. Similar phenomena have Declaration of Competing Interest been found extensively in the mid-to-high latitudes of the Northern Hemisphere (Jump et al., 2007; Zhang et al., 2009; Li et al., 2011). The The authors declare that they have no known competing financial relationships of radial growth with temperature and precipitation in the interests or personal relationships that could have appeared to influ- warm-humid region and humid season were relatively stable but ence the work reported in this paper. showed clear instability under harsh growth conditions, especially in dry seasons. Similar results have been reported in dendroclimatic stu- Acknowledgements dies in central Asia on Sabina przewalskii in the Qilian Mountains (Gao et al., 2013) and Picea jezoensis in the Xiaoxinganling Mountains (Yu This research was supported by the Fundamental Research Funds et al., 2017). The magnitude of climate factor limitation on growth is for the Central Non-profit Research Institution of CAF fl synchronously in uenced by regional climatic variability (Peterson (CAFYBB2017ZX002) and the Yunnan Science and Technology ff ff et al., 2002). The warming e ect in di erent climate zones would cause Innovation Talent Program (2018HC013). We especially thank Shiquan ff ff di erent degrees variation of other climate factors and further a ect the Song and Mingtan Shen for sampling work in the field. We thank Let- ff sensitivity of trees. A warming e ect might trigger a shift in response to Pub (www.letpub.com) for its linguistic assistance during the pre- climate factors via a type of threshold mechanism (Li et al., 2016; Tian paration of this manuscript. We also thank the anonymous referees for et al., 2017). The growth sensitivity in our research in certain months helpful comments on the manuscript. showed a step-wise increase, which may suggest the presence of un- derlying threshold-controlled mechanisms. The unstable response of Appendix A. Supplementary data radial growth to climate can be interpreted as an excessive response to the rate of warming by plant respiration and the consumption of Supplementary data to this article can be found online at https:// available carbohydrates (Schaberg, 2000). Warming in a harsh en- doi.org/10.1016/j.foreco.2020.118357. vironment could enhance drought stress, which would slow the growth of trees, reduce the sensitivity of radial growth to temperature, and lead References to divergent growth-temperature relationships (Carrer and Urbinati, ’ 2006; D Arrigo et al., 2008). However, trees growing in humid regions Allen, C.D., Macalady, A.K., Chenchouni, H., Bachelet, D., McDowell, N., Vennetier, M., and seasons could better buffer against drought and thus have relatively Kitzberger, T., Rigling, A., Breshears, D.D., (Ted) Hogg, E.H., Gonzalez, P., Fensham, stable sensitivity to climate due to the abundant rainfall and low inter- R., Zhang, Z., Castro, J., Demidova, N., Lim, J.H., Allard, G., Running, S.W., Semerci,

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