Grassland Degradation Remote Sensing Monitoring and Driving Factors Quantitative Assessment in China from 1982 to 2010
Grassland Degradation Remote Sensing Monitoring and Driving Factors Quantitative Assessment in China from 1982 to 2010
复制标题
DOI：
10.1007/978-981-32-9382-3_6
复制
发表时间：
2019-09
期刊：
影响因子：
--
通讯作者：
Wei Zhou;Jian-long Li;T. Yue
中科院分区：
文献类型：
--
作者：
Wei Zhou;Jian-long Li;T. Yue
对草地退化的遥感监测，将使中国的草地退化状况一目了然。同时，对驱动因素进行定量评价，有助于了解退化机理和草地退化控制。本研究以草地净第一性生产力(NPP)和草地盖度为指标，分析草地退化动态。并设计了基于净第一性生产力的草地退化驱动力评价方法。具体而言，利用潜在NPP和LNPP(人类活动造成的NPP损失)，即潜在NPP与实际NPP之间的差值，分别计算气候和人为因素对草地退化的贡献。结果表明，1982-2010年，中国草地退化面积占草地总面积的22.7%。气候变化和人类活动对草地退化的贡献基本平衡(47.9%vs46.4%)。总体而言，人类活动是草地恢复的主要驱动因素，占78.1%，而气候变化的贡献率仅为21.1%。但驱动因素存在明显的空间异质性。气候变化的贡献大于人类活动的贡献。但对于草地恢复而言，人类活动是主导因素。暖干气候不利于牧草生长，但有效的恢复措施有利于草地恢复。本研究方法可广泛应用于其他地区的草地退化评价。7种优势草地类型的生境适宜性概率分布函数不同。其中，白玉兰和金龟子的pdf分布比较均匀，主要分布在中国的东南部。芦荟Pdf。前列为正态分布，广泛分布于中国全境。针茅和紫针茅的pdf呈“尖峰状”，集中在青藏高原。
Remote sensing monitoring of grassland degradation will make a clear of the grassland degradation status of China. At the same time, quantitative assessment of the driving factors will benefit to the understanding of degradation mechanism and grassland degradation control. In this study, net primary productivity (NPP) and grass coverage were selected as indicators to analyze grassland degradation dynamics. And we designed a method to assess the driving force of grassland degradation based on NPP. Specifically, the potential NPP and LNPP (NPP loss because of human activities), which is the difference between potential NPP and actual NPP, were used to calculate the contribution of climate and human factors to grassland degradation, respectively. Results showed that grassland degradation area accounted for 22.7% of the total grassland area in China from 1982 to 2010. The contribution of climate change and human activities to grassland degradation was almost equilibrium (47.9% vs 46.4%). Overall, on the grassland restoration, human activities were the dominant driving factors, accounting for 78.1%, whereas the contribution of climate change was only 21.1%. However, there are obviously spatial heterogeneous on driving factors. And the contribution of climate change was larger than human activities. But for the grassland restoration, human activities were the dominant factors. Warm-dry climate was harmful to grass growth but useful restoration measurements were benefit to grassland restoration. Methods in this study can be widely used in other regions of grassland degradation evaluation. The probability distribution functions (pdfs) of habitat suitability were different for the 7 dominant grassland types. Among, the pdfs ofImperata cylindrica(Linn.)Beauv.andThemeda japonica(Willd.)Tanakawas uniform distribution and mainly distributed in the southeastern of China. The pdf ofPhragmites australis(Cav.)Trin. ex Steud.was normal distribution and widely spread all over of China. The pdfs of theKobre siapygmaea C.B. ClarkeandStipa purpurea Grisebwere “leptokurtic shape” and concentrated in the Tibetan Plateau.