地理学报 ›› 2020, Vol. 75 ›› Issue (1): 53-67.doi: 10.11821/dlxb202001005

• 气候变化 • 上一篇    下一篇

中国东北地区植被生产力控制因素分析

周玉科   

  1. 中国科学院地理科学与资源研究所 生态系统网络观测与模拟重点实验室,北京 100101
  • 收稿日期:2019-01-05 修回日期:2019-12-20 出版日期:2020-01-25 发布日期:2020-03-25
  • 作者简介:周玉科(1984-), 男, 山东济宁人, 博士, 副研究员, 主要从事生态遥感与时空大数据分析研究。E-mail: zhouyk@igsnrr.ac.cn
  • 基金资助:
    国家重点研发计划(2016YFC0500103);国家重点研发计划(2018YFB0505301);国家自然科学基金项目(41601478);南方海洋科学与工程广东省实验室(广州)人才引进专项(GML2019ZD0301)

Analysis of controlling factors for vegetation productivity in Northeast China

ZHOU Yuke   

  1. Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • Received:2019-01-05 Revised:2019-12-20 Online:2020-01-25 Published:2020-03-25
  • Supported by:
    National Key R&D Program Project of China(2016YFC0500103);National Key R&D Program Project of China(2018YFB0505301);National Natural Science Foundation of China(41601478);Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou),(GML2019ZD0301)

摘要:

植被生长季长度和生长强度是形态上影响植被生产力变化的重要因子。全球变暖情景下,北半球中高纬度大部分地区植被生长季显著延长并对植被生产力产生正向反馈,而植被生长强度变化情形及对生产力的控制作用并不清晰。中国东北地区属于中纬度温带地区,具有较高的植被覆盖度和丰富的植被类型,探索其植被生长季长度和强度的变化及对生产力的控制作用有利于理解和应对该地区的生态系统变化。以中国东北为研究区,基于1982—2015年长时序遥感植被指数数据(NDVI3g),利用曲率求导法确定植被生长季开始点(SOS)、结束点(EOS)、生长季长度(LOS)和夏季最大生长季强度(GM)等关键物候参数,然后利用相对重要性(RI)方法定量分析了生长季长度和强度对植被生产力长期变化趋势的相对贡献及时空格局。结果表明:① 研究区整体的植被生产力和生长强度呈现增强趋势,而生长季长度呈现缩短趋势,导致生长强度成为控制生产力变化趋势的主要因素(RI = 70%);② 在不同植被覆盖区域,生长季长度和生长强度对生产力的影响程度具有显著的空间差异。西部草原区植被生产力受生长强度控制最为显著(RI = 93%),其次为针叶林(RI = 66%)和阔叶林区(RI = 62%),农作物区生产力受生长强度影响最小(RI = 56%)。生长季长度对植被生产力的控制在农作物区最为显著(RI = 40%),在其他区域的影响约为27%~35%。各植被覆盖区生长强度与生产力均为正相关,生长季长度与生产力均为负相关;③ 气候因素(降水、温度)和物候变化均对主要贡献因子生长强度产生影响,其中SOS的变化对生长强度的影响程度和空间范围最为显著,主要表现为SOS推迟促进生长强度增强。本研究基于遥感数据发现1982—2015年间中国东北地区植被生长更加旺盛,但是植被生长活动主要受生长强度的影响,该研究可以为植被生产力变化模拟的参数选择提供新的线索。

关键词: 植被物候, 植被生产力, 生长季长度, 生长强度, 长期趋势, NDVI

Abstract:

The length and magnitude of vegetation growing season are important factors affecting the change of vegetation productivity during the growth process. Under the context of global warming, vegetation growing season at the middle and high latitudes of the Northern Hemisphere has prolonged significantly and caused positive feedback on vegetation productivity. However, the change of vegetation growth magnitude and its impact on vegetation productivity are still unclear. Northeast China is located in the mid-latitude temperate zone with high vegetation coverage and various vegetation types. Exploring the change of vegetation growth season length and magnitude and their influence on productivity is meaningful for understanding and coping with ecosystem changes in the study area. Based on the long-term GIMMS NDVI3g remote sensing data (1982-2015), the curvature derivation method was used to extract the key vegetation phenological parameters such as start of season (SOS), end of season (EOS), growth season length (LOS) and growth magnitude (GM). Then the relative importance (RI) method was employed to detect the relative contribution of LOS and GM to vegetation productivity (expressed as mean NDVI value in growing season, MGS) in growing season. The results showed that: (1) The overall vegetation productivity and growth magnitude in the study area showed an increasing trend, while the LOS showed a decreasing trend, which led to the GM becoming the main factor controlling the change trend of productivity (RI = 70%); (2) In different vegetation coverage areas, the impact of growth season length and magnitude on productivity showed significant spatial discrepancy. Vegetation productivity in the western grassland region was most significantly controlled by GM (RI = 93%), followed by coniferous forest and broad-leaved forest (RI = 66%, 62%) and crop area was least affected by GM (RI = 56%). The impact of LOS on vegetation productivity is most significant in croplands (RI = 40%) and affects about 27%-35% in other areas. GM was positively correlated with productivity in all vegetation cover areas, while LOS was negatively correlated with productivity; (3) Both climate factors (precipitation, temperature) and phenological changes affect the main contributing factor GM. In detail, the change of SOS has the most significant effect on the GM in a large spatial range. The main manifestation is that delayed SOS can promote GM. Based on remote sensing technique, this study found that vegetation in Northeast China is generally growing more vigorously, but vegetation growth activities are mainly affected by growth magnitude. This study can provide direct evidence for the study of vegetation phenological changes and productivity response under the background of global change.

Key words: vegetation phenology, vegetation productivity, growth season length, growth magnitude, long-term trend, NDVI