生态环境的层次性、复杂性和多变性,决定了对其质量进行评价的难度.确立构建一套合理、科学,在解决同一类问题中具有代表性的指标体系和评价方法,是众多学者长久以来关注的关键问题.该文以延安水土保持与生态环境建设试验示范区为实证对象,选取灰色关联度法、综合评价法和驱动力-压力-状态-影响-响应多方案综合决策支持系统(driving force pressure state impact response framework-multiple decision support system, DPSIR-mDSS)对研究区域1999-2009年水土流失综合治理生态恢复环境效应进行了评家,结果表明:DPSIR-mDSS 模型在构建水土流失综合治理生态恢复环境效应评价指标体系时将人类社会行为和经济行为与环境系统间复杂的相互关系简化为一对一因果链,评价过程得以分解、简化,且评价结果与研究区域生态恢复环境效应实际变化情况一致,能较好的解释研究区域水土流失综合治理生态恢复环境效应随时间的变化情况,为生态恢复环境效应评价提供了一种新的评价思路和方法.总体而言,退耕还林(草)工程的实施极大的促进了研究区生态环境状况,但一些新的问题诸如耕地压力、生态需水亏缺等接踵而至,应在今后予以重视.
长时间序列的土地利用数据集,不仅可以反映土地变化的驱动力因素,并且被用作下垫面资料来研究气候变化情况。1990年代以来,土地利用/覆盖变化作为全球变化的重要组成部分和主要原因,日益受到国际组织和世界各国的普遍关注,目前己成为国际上全球变化研究的前沿和热点课题。作为一种长期的积累效应,历史时期的土地利用/覆被变化与全球性问题之间有密切联系。国内的长时间序列土地利用数据集主要基于调查与统计数据进行历史重建,空间重建资料较少;部分区域,已有时空重建数据资料可参考,但可仅占全国较小范围。目前,国外已有一些全球历史土地利用空间数据集,被广泛用于全球气候预测以及土地利用变化历史驱动力研究包括中国。主要有:威斯康星大学全球环境和可持续发展中心(Center for Sustainability and the Global Environment,SAGE)的"全球土地利用数据集"(Global Land Use Database)(Ramankutty N等,1999)和荷兰环境评价局(Netherlands Environment Assessment Agency)的"全球历史环境数据集"(Historical Database of the Global Environment)(Goldewijk K K等,2006)。但是全球数据集在中国区域的精度没有较为全面的研究资料可供参考,因此针对我国的气候预测结果的准确性难以保证。因此,评价全球数据集在历史时期中国范围内主要地利用类型的精度对于准确模拟我国气候变化至关重要。李蓓蓓等仅对东北地区且仅对耕地一种土地利用类型与上述两类数据集进行了对比(李蓓蓓等,2010),研究区域较小,研究的类型较少;Ran等对2000年全球1公里四种土地覆被数据在中国区域的精度进行了对比(Youhua Ran等,2008),研究年限较短,不能反映出历史时期的模拟精度。因此,利用国内的权威统计资料以及空间数据,与全球土地利用数据集进行对比,验证全球数据集在中国区域的精度高低,对于分析气候预测的准确性、土地利用变化驱动力变化以及是否有必要建立适用于气候变化及土地利用驱动力研究的中国区域高精度数据集具有十分重要的参考价值。
We examined stable isotope signals of precipitation, soil water, and xylem water and ran the multi-source linear mixing model （IsoSource） to determine water uptake depths and estimate proportional contribution of po...
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We examined stable isotope signals of precipitation, soil water, and xylem water and ran the multi-source linear mixing model （IsoSource） to determine water uptake depths and estimate proportional contribution of possible water pools to the water use of Mongolian pine （Pinus sylvestris var. mongolica） plantation in southeast Horqin Sandy Land. We also examined variations of the water use by Mongolian pine trees before and after a heavy precipitation event. The closeness of isotopic composition between xylem water and potential water pools presented that most of water uptake by the trees occurred in the depth of below 20 cm soil （up to 80 cm in this study）. Estimate from the IsoSource model agrees well with observation, and the model yielded that over 60% of the water was derived from 20–80 cm soil layer under relatively higher soil moisture conditions, contribution from much deeper soil depth may increase when the soil in this layer became dry. The contribution from the groundwater was very low since water table was much deeper than rooting depth of the trees. Isotopic signals of xylem water of Mongolian pine trees before and after a heavy precipitation of 14.4 mm on July 13 in 2009 exhibited that the trees could sense and use recent rain-charged soil water at the upper 20 cm soil layer 36 hours after the rain, and this contribution decreased rapidly in the following 24 hours. The ability of accessing different water pools of Mongolian pine trees under various soil moisture conditions is likely a good indicator of their adaptability to dry habitats in sandy lands.
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