基金项目:国家自然科学基金项目?1877416),中央高校基本科研业务费专项(2572019CP09),中国科学院青年创新促进会项目?019235),国家自然科学基金项目?1971065(/div>
详细信息
苏远航。主要研究方向:气候变化、森林生态学。Email9a href="//www.inggristalk.com/j/article/doi/10.12171/mailto:suyuanhang@126.com">suyuanhang@126.com 地址?50040黑龙江省哈尔滨市香坊区和兴路26号东北林业大学林学院
刘滨辉,教授,博士生导师。主要研究方向:树轮与气候变化 Email9a href="//www.inggristalk.com/j/article/doi/10.12171/mailto:lbinhui2021@163.com">lbinhui2021@163.com 地址:同三/span>
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出版历程
- 收稿日期:2021-09-15
- 录用日期:2023-02-08
- 修回日期:2022-03-14
- 网络出版日期:2023-02-10
- 刊出日期:2023-03-25
Response of forest vegetation phenology to climate change in Xiaoxing’an Mountains of northeastern China
College of Forestry, Northeast Forestry University, Harbin 150040, Heilongjiang, China
摘要:
目的采用遥感提取植被物候的方法,以小兴安岭为研究区,构建森林植被物候时空变化,分析森林植被物候变化对气候变化的响应、/sec>
方法基于GIMMS NDVI 3g影像,运用一元六次多项式拟合植被生长曲线,并结合逐像元动态阈值法提取小兴安岭1982?015年森林植被生长开始期(SOS)、生长结束期(EOS)和生长季长度(LOS)共3种物候参数;利用ArcGIS软件,将气温、降水以及日照时数数据与植被物候参数逐像元分析,得到物候参数与气象因子偏相关系数的空间分布特征、/sec>
结果?)植被物候多年平均值空间分布特征呈现由西北向东南方向,植被SOS逐渐提前,植被EOS逐渐推迟,植被LOS逐渐延长的规律。(2)小兴安岭森林植被SOS集中在日序第112.1~128.3天,年际变化?998年前后出现转折,1998年前呈显著提前趋势(
R
2= 0.284+i>P= 0.028),1998年后呈不显著推迟趋势'i>R
2= 0.002+i>P= 0.86),导致整个时间段(1982?015年)变化不显著,变化幅度为每10年提?.12 d'i>R
2= 0.001+i>P= 0.872);森林植被EOS集中在第277.3~294.8天,年际变化呈现显著推迟趋势,变化幅度为?0年推?.33 d'i>R
2= 0.294+i>P< 0.01);森林植被LOS集中?49.5 ~ 167.5 d,年际变化呈现显著延长趋势,变化幅度为每10年延?.45 d'i>R
2= 0.231+i>P< 0.01)。(3)小兴安岭森林植被SOS对当?月温度的响应最明显,其次是当年2月温度;植被EOS对当?月降水响应最明显,其次是当年6月温度、/sec>
结论?)小兴安岭森林植被物候多年平均值与水热条件多年平均值呈现出比较一致的空间规律特征。(2)研究期植被EOS的变化主要受8月降水的变化驱动?月降水的下降是导致植被EOS显著推迟的主要原因。(3?0世纪末出现的全球变暖停滞引起2月温度在1998年前后呈现由显著上升转变为不显著下降,引起植被SOS变化趋势?998年前后发生突变,导致整个时间段植被SOS变化不显著、/sec>
Abstract:
ObjectiveUsing the method of extracting vegetation phenology by remote sensing,taking Xiaoxing’an Mountains of northeastern China as the study area, this paper analyzes the temporal and spatial changing characteristics of forest vegetation phenology and the response of forest vegetation phenology change to climate change.
MethodBased on GIMMS NDVI 3g image, the forest vegetation growth curve was fitted by univariate sixth order polynomial, and the phenological parameters of forest vegetation SOS, vegetation EOS and vegetation LOS in Xiaoxing’an Mountains from 1982 to 2015 were extracted by pixel dynamic threshold method. Using ArcGIS software, the temperature, precipitation and sunshine duration data were analyzed pixel by pixel with vegetation phenological parameters to obtain partial correlation coefficients between phenological parameters and meteorological factors.
Result(1) The characters in spatial distribution of multi-year mean value of vegetation phenology showed a kind of gradual change from northwest to southeast, including the advance of vegetation SOS, the delay of vegetation EOS and the extension of vegetation LOS. (2) The SOS of forest vegetation in Xiaoxing’an Mountains was concentrated among 112.1th?28.3th day of the year, with an abrupt change around 1998. Before 1998, it showed a significant advancing trend (
R
2= 0.284,
P= 0.028), and after 1998, it showed a non-significant delaying trend (
R
2= 0.002,
P= 0.86), resulting in a non-significant change during the whole analysis period (1982?015), with a rate of change at 0.12 d per ten years (
R
2= 0.001,
P= 0.872). The forest vegetation EOS was concentrated among 277.3th?94.8th day of the year, and showed a significant delaying trend during the whole analysis period, with a rate range of 2.33 d per ten years (
R
2= 0.294,
P< 0.01). The LOS of forest vegetation was concentrated among 149.5?67.5 days, and showed a significant extension trend during the whole analysis period, with a rate of change at 2.45 d per ten years (
R
2= 0.231,
P< 0.01). (3) The forest vegetation SOS was correlated with the April temperature of current year, followed by the February temperature of current year. The vegetation EOS was correlated with the precipitation in August of current year, followed by the June temperature in current year.
Conclusion(1) The multi-year average value of forest vegetation phenology and the multi-year average value of hydrothermal conditions in Xiaoxing’an Mountains show relatively consistent spatial characteristics. (2) The change of vegetation EOS during the study period is mainly driven by the change of precipitation in August. The decline of precipitation in August is the main reason for the significant delay of vegetation EOS. (3) The stagnation of global warming at the end of the 20th century causes the temperature in February to change from a significant increase to a non-significant decrease around 1998, causing a sudden change in the trend of vegetation SOS around 1998, leading to a non-significant change in vegetation SOS during the whole period.
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