Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Joint International Research Laboratory of Climate and Environment Change (ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Jiangsu Key Laboratory of Agricultural Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China.
Center for Forest Disturbance Science, Southern Research Station, USDA Forest Service, Athens, GA 30602, USA.
Sci Total Environ. 2017 Jul 1;589:73-88. doi: 10.1016/j.scitotenv.2017.02.210. Epub 2017 Mar 6.
Leaf area index (LAI) is a key parameter to characterize vegetation dynamics and ecosystem structure that determines the ecosystem functions and services such as clean water supply and carbon sequestration in a watershed. However, linking LAI dynamics and environmental controls (i.e., coupling biosphere, atmosphere, and anthroposphere) remains challenging and such type of studies have rarely been done at a watershed scale due to data availability. The present study examined the spatial and temporal variations of LAI for five ecosystem types within a watershed with a complex topography in the Upper Heihe River Basin, a major inland river in the arid and semi-arid western China. We integrated remote sensing-based GLASS (Global Land Surface Satellite) LAI products, interpolated climate data, watershed characteristics, and land management records for the period of 2001-2012. We determined the relationships among LAI, topography, air temperature and precipitation, and grazing history by five ecosystem types using several advanced statistical methods. We show that long-term mean LAI distribution had an obvious vertical pattern as controlled by precipitation and temperature in a hilly watershed. Overall, watershed-wide mean LAI had an increasing trend overtime for all ecosystem types during 2001-2012, presumably as a result of global warming and a wetting climate. However, the fluctuations of observed LAI at a pixel scale (1km) varied greatly across the watershed. We classified the vegetation changes within the watershed as 'Improved', 'Stabilized', and 'Degraded' according their respective LAI changes. We found that climate was not the only driver for temporal vegetation changes for all land cover types. Grazing partially contributed to the decline of LAI in some areas and masked the positive climate warming effects in other areas. Extreme weathers such as cold spells and droughts could substantially affect inter-annual variability of LAI dynamics. We concluded that temporal and spatial LAI dynamics were rather complex and were affected by both climate variations and human disturbances in the study basin. Future monitoring studies should focus on the functional interactions among vegetation dynamics, climate variations, land management, and human disturbances.
叶面积指数(LAI)是描述植被动态和生态系统结构的关键参数,它决定了生态系统的功能和服务,如流域内的清洁水供应和碳封存。然而,将 LAI 动态与环境控制(即生物圈、大气圈和人类圈)联系起来仍然具有挑战性,由于数据的可得性,这种类型的研究在流域尺度上很少进行。本研究以内陆干旱半干旱区的中国主要河流——黑河流域上游为研究区,以复杂地形的流域为研究单元,分析了流域内五种生态系统类型的时空变化。我们综合了基于遥感的 GLASS(全球陆面卫星)LAI 产品、插值气候数据、流域特征和土地管理记录,研究时段为 2001-2012 年。我们采用多种先进的统计方法,确定了五种生态系统类型的 LAI 与地形、气温和降水以及放牧历史之间的关系。结果表明,在一个丘陵流域,LAI 的长期平均分布受降水和温度的垂直控制,表现出明显的垂直格局。总体而言,在 2001-2012 年期间,所有生态系统类型的流域平均 LAI 呈增加趋势,这可能是全球变暖及气候变湿的结果。然而,在整个流域范围内,像元尺度(1km)上观测到的 LAI 波动变化很大。我们根据各自的 LAI 变化,将流域内的植被变化分为“改善”、“稳定”和“退化”。我们发现,气候并不是所有土地覆盖类型植被时间变化的唯一驱动因素。放牧在一定程度上导致了一些地区 LAI 的下降,并掩盖了其他地区气候变暖的积极影响。极端天气,如寒潮和干旱,会显著影响 LAI 动态的年际变化。研究结论认为,研究流域的时空 LAI 动态较为复杂,既受到气候变化的影响,也受到人类干扰的影响。未来的监测研究应重点关注植被动态、气候变化、土地管理和人类干扰之间的功能相互作用。