• 中国中文核心期刊
  • 中国科学引文数据库(CSCD)核心库来源期刊
  • 中国科技论文统计源期刊(CJCR)
  • 第二届国家期刊奖提名奖
Volume 36 Issue 3
Jun.  2023
Article Contents
Turn off MathJax

Citation:

Differences in the Response of Radial Growth of Three Quercus Species to Climatic Elements at the Northern Edge of the Warm Temperate Zone and Prediction

  • Corresponding author: LIU Jian-feng, Liujf@caf.ac.cn
  • Received Date: 2023-01-16
    Accepted Date: 2023-02-22
  • Objective The aim of this study was to compare the differences of growth responses of different Quercus species to climatic factors in the same climatic region, and pay special attention to the intra- and inter- species differences at the margins of tree species distribution. Methods The response of radial growth of three dominant deciduous Quercus species (Quercus mongolica, Q. variabilis and Q. acutissima) to climatic factors in the northern margin of warm temperate zone in China was analyzed by dendrochronological method. At the same time, the relationship between radial growth and climate of three tree species was constructed by using mixed linear effect model, and their future growth trends were predicted based on future climate scenarios (RCP2.6 and RCP8.5). Results Chronology of Quercus species in the same area presented high similarity, but there were large differences among different areas. In terms of the response of radial growth to climate, the chronology of different Quercus species in the same region and the same Quercus species in different regions are also different. The radial growth of three Quercus species in Beijing was negatively correlated with the current June temperature, but there was no significant correlation with the temperature in Xianrendong (Liaoning Province). The radial growth of Q. acutissima in Beijing, Q. mongolica in Hebei and Q. variabilis in Dahei Mountain (Liaoning Province) were all limited by precipitation. The modeling results showed that by the end of this century, the radial growth of Quercus species in Beijing and Dahei Mountain would show a decreasing trend, while that in Xianrendong (Liaoning Province) an increasing trend. Conclusion There are significant differences in the growth responses of Quercus species to climate factors in different areas of the northern margin of warm temperate zone in China, which are mainly dominated by the climate features of sampling regions. In the next step, it should be necessary to clarify the relative contribution of various environmental factors (e.g., stand features and site factors) to radial growth of Quercus species.
  • 加载中
  • [1]

    STEINKAMP J, HICKLER T. Is drought‐induced forest dieback globally increasing?[J]. Journal of Ecology, 2015, 103(1): 31-43. doi: 10.1111/1365-2745.12335
    [2]

    CHAGNON C, WOTHERSPOON A R, ACHIM A. Deciphering the black spruce response to climate variation across eastern Canada using a meta-analysis approach[J]. Forest Ecology and Management, 2022, 520(15): 120375.
    [3]

    KANNENBERG S A, NOVICK K A, ALEXANDER M R, et al. Linking drought legacy effects across scales: From leaves to tree rings to ecosystems[J]. Glob Chang Biol, 2019, 25(9): 2978-2992. doi: 10.1111/gcb.14710
    [4]

    BABST F, POULTER B, TROUET V, et al. Site‐and species‐specific responses of forest growth to climate across the European continent[J]. Global Ecology and Biogeography, 2013, 22(6): 706-717. doi: 10.1111/geb.12023
    [5]

    GAO W Q, LIU J F, XUE Z M, et al. Geographical patterns and drivers of growth dynamics of Q. variabilis[J]. Forest Ecology and Management, 2018, 429: 256-266. doi: 10.1016/j.foreco.2018.07.024
    [6]

    SáNCHEZ‐SALGUERO R, CAMARERO J J, GUTIéRREZ E, et al. Assessing forest vulnerability to climate warming using a process‐based model of tree growth: Bad prospects for rear‐edges[J]. Global Change Biology, 2017, 23(7): 2705-2719. doi: 10.1111/gcb.13541
    [7]

    SáNCHEZ-SALGUERO R, CAMARERO J J, HEVIA A, et al. What drives growth of Scots pine in continental Mediterranean climates: drought, low temperatures or both?[J]. Agricultural and Forest Meteorology, 2015, 206: 151-162. doi: 10.1016/j.agrformet.2015.03.004
    [8]

    GAO W Q, NI Y Y, XUE Z M, et al. Population structure and regeneration dynamics of Q. variabilis along latitudinal and longitudinal gradients[J]. Ecosphere, 2017, 8(4): e01737.
    [9]

    CAMARERO J J, GAZOL A, SANGüESA‐BARREDA G, et al. To die or not to die: early warnings of tree dieback in response to a severe drought[J]. Journal of Ecology, 2015, 103(1): 44-57. doi: 10.1111/1365-2745.12295
    [10]

    ARZAC A, GARCIA-CERVIGON A I, VICENTE-SERRANO S M, et al. Phenological shifts in climatic response of secondary growth allow Juniperus sabina L. to cope with altitudinal and temporal climate variability[J]. Agricultural and Forest Meteorology, 2016, 217: 35-45.
    [11]

    HUANG J, TARDIF J C, BERGERON Y, et al. Radial growth response of four dominant boreal tree species to climate along a latitudinal gradient in the eastern Canadian boreal forest[J]. Global Change Biology, 2010, 16(2): 711-731. doi: 10.1111/j.1365-2486.2009.01990.x
    [12]

    TARDIF J, CONCIATORI F, NANTEL P, et al. Radial growth and climate responses of white oak (Q. alba) and northern red oak (Q. rubra) at the northern distribution limit of white oak in Quebec, Canada[J]. Journal of Biogeography, 2006, 33(9): 1657-69. doi: 10.1111/j.1365-2699.2006.01541.x
    [13]

    GOLDBLUM D. The geography of white oak's (Q. alba L. ) response to climatic variables in North America and speculation on its sensitivity to climate change across its range[J]. Dendrochronologia, 2010, 28(2): 73-83. doi: 10.1016/j.dendro.2009.07.001
    [14] 国家林业局. 中国森林资源报告 [M]. 北京: 中国林业出版社, 2019.

    [15] 李宗善, 陈维梁, 韦景树, 等. 北京东灵山辽东栎林树木生长对气候要素的响应特征[J]. 生态学报, 2021, 41(1):27-37.

    [16]

    FRITTS H C. Tree Rings and Climate. [M] London: Academic Press, 1976
    [17]

    HOLMES R L. Computer-assisted quality control in tree-ring dating and measurement [J]. Tree-Ring Bull,1983.43: 69-75.
    [18]

    ZANG C, BIONDI F. Treeclim: an R package for the numerical calibration of proxy-climate relationships[J]. Ecography, 2015, 38(4): 431-436. doi: 10.1111/ecog.01335
    [19] 王兆鹏. 罗霄山南部四种针叶树种多种树木年轮参数气候响应及气候重建研究 [D]. 乌鲁木齐: 新疆师范大学, 2022.

    [20]

    BARBER V A, JUDAY G P, FINNEY B P. Reduced growth of Alaskan white spruce in the twentieth century from temperature-induced drought stress[J]. Nature, 2000, 405(6787): 668-673. doi: 10.1038/35015049
    [21]

    JIAO L, JIANG Y, ZHANG W, et al. Assessing the stability of radial growth responses to climate change by two dominant conifer trees species in the Tianshan Mountains, northwest China[J]. Forest Ecology and Management, 2019, 433: 667-677. doi: 10.1016/j.foreco.2018.11.046
    [22]

    CORREA‐DíAZ A, SILVA L C R, HORWATH W R, et al. From trees to ecosystems: spatiotemporal scaling of climatic impacts on Montane Landscapes using dendrochronological, isotopic, and remotely sensed data[J]. Global Biogeochemical Cycles, 2020, 34(3): e2019GB006325.
    [23]

    DU F K, QI M, ZHANG Y Y, et al. Asymmetric character displacement in mixed oak stands[J]. New Phytol, 2022, 236(3): 1212-1224. doi: 10.1111/nph.18311
    [24]

    SHARMA B, FAN Z-X, PANTHI S, et al. Warming induced tree-growth decline of Toona ciliata in (sub-) tropical southwestern China[J]. Dendrochronologia, 2022, 73: 125954. doi: 10.1016/j.dendro.2022.125954
    [25] 都彦廷. 大兴安岭地区树轮宽度对气候变化的响应及NDVI重建研究 [D]. 哈尔滨: 哈尔滨师范大学, 2021.

  • 加载中
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Figures(7) / Tables(1)

Article views(2696) PDF downloads(79) Cited by()

Proportional views

Differences in the Response of Radial Growth of Three Quercus Species to Climatic Elements at the Northern Edge of the Warm Temperate Zone and Prediction

    Corresponding author: LIU Jian-feng, Liujf@caf.ac.cn
  • 1. Research Institute of Forestry, Chinese Academy of Forestry, Key Laboratory of Tree Breeding and Cultivation of National Forestry and Grassland Administration, Beijing 100091, China
  • 2. Liaoning Academy of Forestry Sciences , Shenyang 110032, Liaoning , China
  • 3. Dalian Institute of Forestry Science, Liaoning Province, Dalian 116014, Liaoning, China

Abstract:  Objective The aim of this study was to compare the differences of growth responses of different Quercus species to climatic factors in the same climatic region, and pay special attention to the intra- and inter- species differences at the margins of tree species distribution. Methods The response of radial growth of three dominant deciduous Quercus species (Quercus mongolica, Q. variabilis and Q. acutissima) to climatic factors in the northern margin of warm temperate zone in China was analyzed by dendrochronological method. At the same time, the relationship between radial growth and climate of three tree species was constructed by using mixed linear effect model, and their future growth trends were predicted based on future climate scenarios (RCP2.6 and RCP8.5). Results Chronology of Quercus species in the same area presented high similarity, but there were large differences among different areas. In terms of the response of radial growth to climate, the chronology of different Quercus species in the same region and the same Quercus species in different regions are also different. The radial growth of three Quercus species in Beijing was negatively correlated with the current June temperature, but there was no significant correlation with the temperature in Xianrendong (Liaoning Province). The radial growth of Q. acutissima in Beijing, Q. mongolica in Hebei and Q. variabilis in Dahei Mountain (Liaoning Province) were all limited by precipitation. The modeling results showed that by the end of this century, the radial growth of Quercus species in Beijing and Dahei Mountain would show a decreasing trend, while that in Xianrendong (Liaoning Province) an increasing trend. Conclusion There are significant differences in the growth responses of Quercus species to climate factors in different areas of the northern margin of warm temperate zone in China, which are mainly dominated by the climate features of sampling regions. In the next step, it should be necessary to clarify the relative contribution of various environmental factors (e.g., stand features and site factors) to radial growth of Quercus species.

  • 气候是影响全球植物分布的关键驱动因素。随着全球气候变化的不断加剧,植物的生长及其分布范围,特别是在其分布边缘将受到更大的影响[1]。有研究发现,相对于植物分布范围的变化,植物的生长对气候变化更加敏感[2]。因此,探索不同植物生长动态对气候变化的敏感性,可为预测未来植物分布动态提供重要参考。森林是陆地生态系统碳汇的主体[3],研究某一区域森林树种的生长动态及其对气候变化的响应差异,有助于理解气候变化背景下森林组成、结构及碳汇功能的变化动态,为适应性经营管理措施的制定提供科学依据。

    已有研究表明,树种分布北缘的群体生长主要受低温影响[4-6],但在其分布南缘则受到高温导致的干旱缺水的限制[1, 7]。这些研究大多基于阿尔卑斯山脉以北的高纬度地区[8]或以南的地中海地区[9-10]。然而,在暖温带气候区(如暖温带湿润-半干旱地区),树种的生长是否也存在上述现象尚缺乏研究。此外,不同分布范围的树种的生长可能会对气候变化做出不同的响应。如Huang[11]研究加拿大东部的4种北方树种时发现,毛白杨(Populus tomentosa Carr.)的径向生长主要受水分条件的影响,而白桦(Betula platyphylla Suk.)的生长受1月的温度和生长季降水影响,云杉(Picea asperata Mast.)和班克松(Pinus banksiana Lamb.)的径向生长则与当年冬季和春季或整个生长季的温度呈正相关关系。然而,Tardif等[12]发现,白栎(Quercus alba L.)和红栎(Q. rubra L.)的生长在其北部范围内对气候的响应并没有显著差异。因此,不同树种在分布范围边缘对气候的生长反应是复杂的,目前尚缺乏对同域分布但处于不同树种各自不同分布边缘的群体对气候变化响应的比较研究。气候暖化背景下森林的响应与适应是当前生态学研究的重要方向,一方面,气候变暖可以加速土壤有机质的分解速率,从而增加植物对土壤矿物质营养的吸收,特别是对最常见的限制性营养素N的吸收[11];另一方面,温室气体特别是大气CO2浓度上升,加上环境温度的升高,提高了植物光合同化物质的生产和水分利用效率,从而增加树木生物量的积累。有研究发现,气候暖化可能导致北半球温带树种在其分布北缘呈现增长趋势[5, 8, 13]。然而,在我国暖温带树种分布的边缘群体是否会有类似趋势尚缺乏研究。

    栎类是我国面积和蓄积最大的树种组[14],在木材生产、固碳增汇、土壤保持、水源涵养及生物多样性维持等方面发挥着重要的功能。在栎类树种中,栓皮栎(Q. variabilis Bl.)、麻栎(Q. acutissima Carruth.)和蒙古栎(Q. mongolica Fisch.)是我国分布最广、数量最多的3种落叶阔叶树种,其范围分别为(19°~42° N、97°~140° E)、(19°~42° N、97°~140° E)和(34°~53° N、112°~134° E),也是我国暖温带森林的主要成分。我国暖温带北缘是栓皮栎和麻栎天然分布的北缘,蒙古栎分布的南缘。有研究表明,该区域气候暖干化的趋势明显[15]。因此,本研究以生长在暖温带北缘的栓皮栎、麻栎、蒙古栎为研究对象,通过树木年轮学方法,分析径向生长与气候因子的关系;同时,考虑未来气候变化情景(RCP2.6;RCP8.5),对该区域栎类树种的未来生长展开预测,以期为本区域制定应对气候变化的森林管理对策提供依据。

    • 在我国暖温带北缘(华北地区北部和东北地区南部)选择栎树树种分布的6个典型样点,分别为西部的北京市昌平、密云、怀柔和河北省棋盘山地区;东部的辽宁省大黑山和仙人洞地区(图1)。研究区域属典型暖温带季风气候,夏季炎热多雨,冬季寒冷干燥。但3个地区的水热条件存在明显差异,如东部辽宁地区温暖湿润,降水量丰富,年平均气温为10.2 ℃,年降水量644.7 mm;其中仙人洞和大黑山年内降水季节性也存在一定差异,如仙人洞降水集中在5—7月,大黑山降水集中在6—8月。西部的北京地区气温较高,雨水相对较少,年平均气温为9.8 ℃,年降水量490.3 mm ;河北棋盘山地区气候干燥寒冷,雨量相对最少;年平均气温仅为2.3 ℃,年降水量415.1 mm(图2)。

      Figure 1.  Location of sampling sites in the study area

      Figure 2.  Monthly mean precipitation and monthly mean temperature in the study area (1930—2018)

    • 于2018年8—9月展开野外取样工作。在每个样点,选择人为干扰较小且栓皮栎、麻栎和蒙古栎为优势树种的林分,建立20 m × 20 m的临时样地,选择每个样地的冠层优势个体,按照标准树木年代学方法[16]进行采样。对于每棵样树,使用5.15 mm树木生长锥在1.3 m处按十字交叉取2个树芯,并记录胸径(离地面1.3 m)以及样地基本信息(纬度、经度、海拔、坡度、坡向等)(表1)。将样品储存在定制塑料吸管中,风干后用白胶安装木芯样品,用200目至1 000目砂纸逐级打磨,直到年轮边界清晰可判读,然后用扫描仪(中晶i800plus)扫描成TIF格式图片(分辨率1 200 dpi),再用WinDENDRO(Regent Instruments,Canada)测量(精度0.001 mm)。所有轮宽序列通过目视检查和COFECHA进行交叉定年验证[17],最后共获得329个样芯(表1)。

      项目
      Items
      北京地区
      Beijing
      辽宁大黑山地区
      Liaoning Dahei
      mountain(DHS)
      河北棋盘山
      Hebei Qipan
      mountain(QPS)
      辽宁仙人洞地区
      Liaoning Xianrendong(XRD)
      样地 SiteMY-MLPG-SPLHR-MGLDHS-MLDHS-SPLQPS-MGLXRD-SPLXRD-MLXRD-MGL
      纬度 Latitude/(°) 40.256 3 40.492 5 40.971 0 39.107 5 39.107 5 42.267 1 39.979 1 39.979 1 39.979 1
      经度 Longitude/(°) 117.159 5 117.069 9 116.484 9 121.806 6 121.806 6 117.586 8 122.939 4 122.939 4 122.939 4
      海拔 Altitude/m 294.4 288.6 1 022.5 199.4 168.5 1 458.9 234.7 234.8 615.5
      样芯数量
      Number of cores
      40 35 40 18 48 27 39 30 52
      年表长度
      Chronology length
      1931—2018 1978—2018 1943—2018 1950—2018 1950—2018 1939—2018 1944—2018 1943—2018 1948—2018
      信噪比
      Signal-to-noise ratio
      6.087 8.099 2.547 2.883 7.522 9.566 3.759 7.028 3.688
      总体代表性
      Agreement with
      population chron(EPS)
      0.859 0.893 0.671 0.792 0.883 0.905 0.798 0.875 0.787

      Table 1.  Sample plot information and chronological characteristics

    • 过去时期(1930—2018)的气候数据来自Climate Research Unit(CRU TS 4.05)地表逐月气候格点数据集(https://crudata.uea.ac.uk/cru/data/hrg/,网格距为0.05° × 0.05°)。根据样地经纬度进行提取,气候要素包括月均气温、月降水量和月尺度帕默尔干旱指数(PDSI)。未来时期(2018—2100)的气候数据来自亚太地区历史和未来气候数据集ClimateAP v2.30 (https://asiapacific.forestry.ubc.ca/research-approaches/climate-modeling/)。本研究选择了2种未来温室气体排放情景,即CanESM2-RCP2.6和CanESM2-RCP8.5。未来气候要素包括年平均温度(MAT)、年降水量(MAP)、Hargreaves参考蒸发散(EREF)和哈格里夫斯气候水分亏缺(CMD)。

    • 由于当年的气象因子会影响树木次年或后几年的径向生长,存在一定的“滞后效应”,本研究用上年6月至当年9月的气象数据与当年的轮宽指数(RWI)进行相关分析。为了确定研究区域栎类树种生长趋势是否趋同或趋异,根据RWI进行了主成分分析(PCA)和聚类分析。未来气候变化下的树木径向生长预测使用线性混合效应模型(LMM)。以上分析均利用R软件(V4.1.3)完成,使用R中树轮气候分析程序包“treeclim”(V 2.0.5.1)中的“dcc”函数来进行树轮年表与气候要素的相关性分析[18],使用“corrplot”(V 0.92)程序包绘制上述分析的相关关系图;使用“vegan”(V2.6-4)包来进行主成分分析,使用“factoextra”(V1.0.7)包来进行聚类分析,使用“lme4”(V1.1-31)包进行混合效应模型的拟合。

    2.   结果与分析
    • 根据1930年至2018年的气候数据(图3),研究区域各样点的年平均温度增幅为0.015 ℃。年平均温度由高到低依次为辽宁仙人洞(8.76~11.90 ℃)、辽宁大黑山(7.41~11.70 ℃)、北京(8.38~11.55 ℃)、河北棋盘山(0.60~4.25 ℃)。年总降水量由高到低依次为辽宁大黑山(466.32~1 147.03 mm)、辽宁仙人洞(378.41~1 008.51 mm)、北京(243.77~735.82 mm)、河北棋盘山(293.74~579.22 mm)。年降水量在1950年至2018年明显有下降趋势,降幅由高至低依次为辽宁仙人洞、辽宁大黑山、北京、河北棋盘山。

      Figure 3.  Climatic characteristics of the study sites based on CRU gridded data

      为更好保留年表的低频气候信息,本研究构建了标准化年表,最终建立9个年表(表1图4)。由表1可知,在3个树种中,北京怀柔地区麻栎年表最长(1931—2018),北京栓皮栎年表最短(1978—2018)。栓皮栎的样本总体代表性最大,北京、河北地区树木年表相对于辽宁地区有更高的样本总体代表性。

      Figure 4.  Ring width index of three Quercus species in the study area

    • 不同地区栎类树种年表PCA显示,第一主成分(PC1)的方差累积贡献率为38.56%;第二主成分贡献率为14.43%。可以看出,不同栎树的RWI在同一地区具有更高的相似性。除河北棋盘山地区蒙古栎生长与其他地区差异较大外,北京地区栓皮栎、麻栎、蒙古栎生长相似,辽宁仙人洞地区麻栎、栓皮栎生长相似,大黑山地区麻栎、栓皮栎和仙人洞地区蒙古栎生长相似(图5A)。聚类分析结果进一步验证了PCA分析的结果,如辽宁大黑山地区栎类树种为一类,辽宁仙人洞地区和北京地区栎类树种聚为一类,而棋盘山地区栎类树种则单独为一类(图5B)。

      Figure 5.  Principal component analysis (A) and cluster analysis (B) based on the Rings width index (RWI)

    • 各树种对主要气候变量的相关分析如图6所示。在本研究区域的西部(华北地区北部),北京地区栓皮栎和麻栎的RWI与冬季(上年12月)温度呈负相关关系;而北京地区和河北棋盘山地区的蒙古栎的RWI则分别与上年12月和当年2月温度表现出正相关关系;华北北部的3种栎类树种均与夏季(5—7月)温度呈负相关关系。北京地区栓皮栎和麻栎的RWI对逐月降水量的敏感性(正相关关系)要高于本地区的蒙古栎,河北棋盘山蒙古栎的RWI与月降水量也表现出较高的敏感性,且全年均呈显著正相关关系。北京地区的蒙古栎RWI与冬季PDSI(上年11月至当年1月)呈现负相关关系,北京地区的栓皮栎、麻栎及河北棋盘山的蒙古栎RWI与PDSI多表现出正相关关系。

      Figure 6.  Response relationship between annual ring width chronology and main climate factors

      在研究区东部(东北地区南部),辽宁大黑山地区的栓皮栎和麻栎的RWI较之仙人洞地区3个栎类树种对春季(当年2—4月)温度的敏感性更高,均表现为显著的负相关关系,而仙人洞地区的栎类树种则与春季温度无显著相关关系;但上年11—12月温度对仙人洞地区栓皮栎RWI的正相关显著。东北地区南部的所有栎类树种对各月降水量均不敏感,但与干旱指数PDSI多表现为正相关关系。

    • 基于CanESM2-RCP2.6和CanESM2RCP8.5两种气候变化情景,通过构建混合效应模型,对不同地区栎类树种生长的模拟预测时发现(图7),在RCP2.6情景下,研究区域的栎类树种生长状况较为稳定;而在RCP8.5预测情景下,仅北京地区栎类树种生长状况较为稳定,辽宁地区栎类树种在2050年左右开始出现较大变化,其中仙人洞地区栎类树种径向生长加快,但大黑山地区的径向生长开始逐渐减弱。

      Figure 7.  Prediction value of tree growth index for 2018 —2100 based on climate data of RCP2.6 and RCP8.5 scenarios

    3.   讨论
    • 识别森林群落中不同树种生长对气候响应的差异,是评价气候变化下森林动态变化的重要前提。本研究研究了我国暖温带北缘栓皮栎、麻栎、蒙古栎径向生长对气候的响应差异,发现生长在同一地区的不同树种存在较高的相似性,但在不同地区差别较大。这与王兆鹏[19]对福建柏(Fokienia hodginsii Dunn.)、铁杉(Tsuga chinensis Franch.)、冷杉(Abies beshanzuensis Mast.)马尾松(Pinus massoniana Lamb.)的研究结果相一致。如罗霄山南部4个针叶树种的径向生长与单月和季节性气候因子的相关结果大致相同;气温发生突变后,4个树种树轮宽度指数的变化趋势也相似[19]。聚类分析中,河北棋盘山栎树(蒙古栎)年表与其他区域差异较大,被最先单独分离出来,可能的原因是由于河北棋盘山地区纬度较高,年降水量、年均温明显低于其他地区 。

      整体上,相对于蒙古栎,栓皮栎、麻栎对温度和降水具有更高的敏感性。本研究结果显示,北京地区栓皮栎和麻栎的RWI与冬季(上年12月)温度呈显著负相关关系;而北京地区和河北棋盘山地区的蒙古栎的RWI则分别与上年12月和当年2月温度表现出显著的正相关关系。可以认为,华北地区冬季增温会导致该地区的栓皮栎和麻栎生长下降,而蒙古栎生长增加;但夏季温度的升高会导致整个区域栎类树种生长的下降。华北北部的3个栎类树种均与夏季(5—7月)温度呈负相关关系,这可能是由于夏季高温会诱导植物叶片气孔关闭,进而导致光合同化物质生产的下降[20-21]。在华北地区,同域分布的栓皮栎北缘群体和蒙古栎南缘群体的生长与当年冬春降水存在正相关[8],表明生长均受到降水的限制[11]。北京地区麻栎和河北棋盘山地区蒙古栎RWI与全年降水呈显著正相关,辽宁大黑山栓皮栎RWI与当年4月降水及上年6—10月降水呈显著正相关,表明北京地区麻栎、河北棋盘山地区蒙古栎、辽宁大黑山地区栓皮栎生长均受到降水制约。可以认为,不同区域树木生长的限制因子有所不同,但在同一区域,不同树种生长的限制因素也存在差异。如本研究发现北京地区麻栎与河北地区蒙古栎受干旱制约,但在辽宁仙人洞地区3种栎树均与降水、温度无明显相关,表明该地区水热条件较为适宜栎类树种生长。有研究表明,较低的水分可利用性是干旱、半干旱地区森林生态系统发育和林木生长受到限制的主要原因[3, 22-23]。相对于华北北部,虽然东北南部的辽宁大黑山地区降水更丰沛,但该地区栓皮栎RWI与降水却表现出正相关关系,这与Bimal对红椿(Toona ciliata Roem.)的研究结果一致[24]。这可能与降水的季节性差异有关,比如大黑山地区降水主要集中在6—9月,生长季前期降水较少,水热的不同步限制了树木的初生生长。

      为了对未来树木生长作出评估,本研究采用了IPCC第五份评估报告4个温室气体浓度情景中的最理想的RCP2.6情景和最极端的RCP8.5情景下的气候数据进行预测,分别表示到2100年辐射强度为2.6 W·m−2和8.5 W·m−2。RCP2.6情景下,北京-河北地区增温2.6 ℃,降水量增加156.35 mm;辽宁仙人洞地区增温2.5 ℃,降水量增加117.22 mm;辽宁大黑山地区增温2.4 ℃,降水量增加175.54 mm。RCP8.5情景下,北京-河北地区增温6.6 ℃,降水量增加341.38 mm;辽宁仙人洞地区增温5.3 ℃,降水量增加318.74 mm;辽宁大黑山地区增温5.3 ℃,降水量增加385.45 mm。根据模型预测,截至本世纪末,北京、辽宁大黑山地区栎类树种生长量将会持续减少,特别是在RCP8.5情景下,栎类树种生长下降愈加明显。这与李宗善[15]对北京东灵山辽东栎(Q. wutaishanica)的预测一致。可能的解释是,北京地区处于半干旱地区,气候变暖导致蒸散量增加,树木的可利用水分降低,水分限制愈加严重[25]。辽宁仙人洞地区栎类树种径向增长预计会增加,可能的原因是辽宁仙人洞地区有适宜的温度和相对丰沛的降水,RWI与气候因子的相关性分析中,显著相关的气候因子均为正相关,因此降水量和气温的增加导致了树木的加速生长。然而,树木生长适宜温度的上限是多少,超过适宜温度对树木的限制作用、立地条件及林分结构等因素也应该进行考虑。

    4.   结论
    • 本研究利用年轮生态学研究了我国暖温带北缘3个栎类树种对气候要素的响应差异,发现同一地区的栎类树种生长对气候响应相似;不同区域的同一栎树的生长对气候响应存在差别,可以认为在北京、河北地区,水分和低温是制约栎类树种生长的主要因素。模型预测还发现,至本世纪末,北京、辽宁大黑山地区栎类树种的生长可能发生衰退,而辽宁仙人洞地区栎类树种的生长则表现出增加趋势。然而,除气候要素外,树木生长还受到立地条件、林分结构与树木年龄等因素及各类因子间交互作用的影响,下一步需要结合更多环境因子展开更深入的研究,以提高模拟预测的可靠性。

Reference (25)

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return