Shan Baoqing, Ding Yuekui, Zhao Yu
State Key Laboratory on Environmental Aquatic Chemistry, Research Center for Eco-Environmental Science, Chinese Academy of Science, Beijing 100085, China.
State Key Laboratory on Environmental Aquatic Chemistry, Research Center for Eco-Environmental Science, Chinese Academy of Science, Beijing 100085, China; University of Chinese Academy of Science, Beijing 100049, China.
J Environ Sci (China). 2016 Jan;39:144-154. doi: 10.1016/j.jes.2015.10.006. Epub 2015 Dec 8.
The river ecosystem in the Hai River Basin (HRB), an important economic region in China, is seriously degraded. With the aim of river restoration in the HRB, we developed a method to assess the river's ecological status and conducted a preliminary application of the method. The established method was a predictive model, which used macroinvertebrates as indicator organisms. The river's ecological status was determined by calculating the ratio of observed to expected values (O/E). The method included ecoregionalization according to natural factors, and the selection of reference sites based on combinations of habitat quality and macroinvertebrate community. Macroinvertebrate taxa included Insecta, Crustacea, Gastropoda, and Oligochaeta, with 39 families and 95 genera identified in the HRB. The HRB communities were dominated by pollution tolerant taxa, such as Lymnaeidae, Chironomus, Limnodrilus, Glyptotendipes, and Tubifex. The average Shannon-Wiener index was 1.40±0.5, indicating a low biodiversity. In the river length of 3.31×10(4) km, 55% of the sites were designated poor, with a bad ecological status. Among nine secondary river systems, Luan and Zi-ya had the best and worst river conditions, respectively. Only 17 reference site groups were selected for river management in the 41 ecoregions examined. This study lays the foundation for river restoration and related research in the HRB, and we anticipate further developments of this novel method.
海河流域是中国重要的经济区，其河流生态系统严重退化。为了恢复海河流域的河流生态，我们开发了一种评估河流生态状况的方法并进行了初步应用。所建立的方法是一个预测模型，该模型将大型无脊椎动物用作指示生物。通过计算观测值与预期值的比率（O/E）来确定河流的生态状况。该方法包括根据自然因素进行生态分区，以及基于栖息地质量和大型无脊椎动物群落的组合选择参考站点。大型无脊椎动物分类群包括昆虫纲、甲壳纲、腹足纲和寡毛纲，在海河流域共鉴定出39科95属。海河流域的群落以耐污分类群为主，如椎实螺科、摇蚊属、水丝蚓属、长足摇蚊属和颤蚓属。平均香农-威纳指数为1.40±0.5，表明生物多样性较低。在3.31×10⁴千米的河流长度中，55%的站点被判定为差，生态状况不佳。在九个二级河系中，滦河和子牙河的河流状况分别最好和最差。在所考察的41个生态区域中，仅选择了17个参考站点组用于河流管理。本研究为海河流域的河流恢复及相关研究奠定了基础，我们期待这种新方法能有进一步发展。
