流域一、二级水生态分区技术及在辽河流域的应用

基于驱动力-压力-状态-影响-响应指标分析框架,提出水生态一、二级分区所适用的指标类别,在环境要素与水生态系统因子相关性分析和环境要素空间变异尺度分析基础上,建立了流域水生态一、二级分区指标体系。采用"自上而下"和"自下而上"相结合的分区方法,在辽河流域进行了水生态一、二级分区应用研究,将辽河流域划分为4个水生态一级分区和8个二级分区,并对各个水生态分区的特征进行了总结。辽河流域分区应用表明,水生态分区过程中仍然存在较大的主观因素,尤其是水生态二级分区边界的确定。     

A scalable approach to mapping annual land cover at 250 m using MODIS time series data: A case study in the Dry Chaco ecoregion of South America

Land use and land cover (LULC) maps from remote sensing are vital for monitoring, understanding and predicting the effects of complex human-nature interactions that span local, regional and global scales. We present a method to map annual LULC at a regional spatial scale with source data and processing techniques that permit scaling to broader spatial and temporal scales, while maintaining a consistent classification scheme and accuracy. Using the Dry Chaco ecoregion in Argentina, Bolivia and Paraguay as a test site, we derived a suite of predictor variables from 2001 to 2007 from the MODIS 250 m vegetation index product (MOD13Q1). These variables included: annual statistics of red, near infrared, and enhanced vegetation index (EVI), phenological metrics derived from EVI time series data, and slope and elevation. For reference data, we visually interpreted percent cover of eight classes at locations with high-resolution QuickBird imagery in Google Earth. An adjustable majority cover threshold was used to assign samples to a dominant class. When compared to field data, we found this imagery to have georeferencing error < 5% the length of a MODIS pixel, while most class interpretation error was related to confusion between agriculture and herbaceous vegetation. We used the Random Forests classifier to identify the best sets of predictor variables and percent cover thresholds for discriminating our LULC classes. The best variable set included all predictor variables and a cover threshold of 80%. This optimal Random Forests was used to map LULC for each year between 2001 and 2007, followed by a per-pixel, 3-year temporal filter to remove disallowed LULC transitions. Our sequence of maps had an overall accuracy of 79.3%, producer accuracy from 51.4% (plantation) to 95.8% (woody vegetation), and user accuracy from 58.9% (herbaceous vegetation) to 100.0% (water). We attributed map class confusion to limited spectral information, sub-pixel spectral mixing, georeferencing error and human error in interpreting reference samples. We used our maps to assess woody vegetation change in the Dry Chaco from 2002 to 2006, which was characterized by rapid deforestation related to soybean and planted pasture expansion. This method can be easily applied to other regions or continents to produce spatially and temporally consistent information on annual LULC.     

淮河流域水生态区划研究

针对水生态区划是水资源和水生态保护研究的基础和前提问题,在综合分析淮河流域自然地理特征、水资源条件、人类活动影响及水生态服务功能类型的基础上,结合国内外相关分区方法与方案的成果,探讨了淮河流域水生态区划方法体系.并提出了淮河流域三级水生态区划方案,将淮河流域划分为淮河平原区与滨海区三角洲2个水生态一级区,并进一步划分出3个水生态二级区和21个水生态三级区.     

Determining reference conditions for nutrients,chlorophyll a and Secchi depth in Yungui Plateau ecoregion lakes,China

Establishing nutrient reference condition (baseline environmental condition) of lakes in ecoregion is a critical consideration in the development of scientifically defensible aquatic nutrient criteria. Three methods were applied to determine reference conditions in Yungui Plateau ecoregion lakes with respect to total phosphorus, total nitrogen, planktonic chlorophyll a (chl a) and Secchi depth. First, minimally developed lake/catchment units were identified based on existing geographical database and visual basin survey. Lakes in these catchments were considered minimally disturbed ‘reference lakes’. Second, the frequency distribution of all of the lake data presently available by each variable was plotted, and the lower 25th percentile was selected as the reference condition for each value. Third, median nutrient, chl a and Secchi depth values were determined for the best one‐third of lakes and applied as indicators of reference condition. The result of model prediction and data from historical record were used to test three techniques for determining reference condition. Reference conditions, as determined by these three methods, broadly agreed for all parameters. Overall, the data suggest that multiple methods can be used to determine reference condition, and that in Yungui lakes, reference condition corresponds to oligotrophic–mesotrophic status.     

国外水生态区评价对我国的启示

概述国外水生态区评价研究成果:目前水生态区正确性评价方法主要以复合生物群落指标体系为主,考察水生态区之间的一致性和差异性;不同方法、不同尺度的水生态分区结果之间的相互校验也是水生态区正确性评价的一种辅助方法;水生态区边界准确性评价和特定应用方面有效性评价也渐渐得到了人们的关注。提出我国开展水生态分区及其评价研究过程中值得注意的几个问题:在选择水生态分区方法时,应将定性和定量的方法有机地结合起来,使其相互弥补,从而更准确地对我国流域水体进行水生态分区;在选择分区指标时,应综合考虑水生态系统的各方面特征指标及影响因素,结合生物量、物种组成比例、物种数等生物指标和河床类型、河道形态、水化学等非生物指标,全面地反映水生态区的特征;在借鉴国外相关研究成果的同时,评价方法的科学性、评价指标的综合性与针对性、评价对象的异质性等也是值得注意的问题。     

常州生态分区及发展对策的实证研究

利用 GIS 等技术,采取定性与定量相集合的方法对常州市区生态服务功能和生态敏感性进行评价,在此基础上将评价结果进行空间叠置,对常州市区进行生态分区,提出各生态分区空间管制措施并进行空间格局优化,为常州城市规划提供有益的借鉴,也为生态城市建设提供直接指导。     

水生态分区方法在城市规划中的应用——以北京市为例

从城市生态系统的自身需求、水生态系统的保护需求和遏制城市水生态危机角度出发,介绍了水生态分区对于城市规划的意义,探讨了水生态分区方法在城市规划中的应用。依据北京市水生态系统服务功能将北京市划分为2个水生态一级区、5个水生态二级区和24个水生态三级区。最后,提出了北京市地表水源涵养区、饮用水水源地保护区、地下水保护区、面源污染控制区、景观休闲区等五类区域的保护规划措施。将水生态分区方法引入城市规划,有助于在宏观规划层面提出对城市发展用地性质、布局的要求,同时可为城市水生态环境保护和管理提供技术支持。     

Assessing risk of large-scale habitat conversion in lightly settled landscapes

Conversion of relatively “wild” areas constitutes a rising threat to the ecological integrity of North American landscapes. As developers seek unprotected, amenity-rich lands, conservation planners require methods to recognize risk and prioritize actions. Most development models and processes are incremental, accumulating change over time and space. By contrast, large-scale amenity development can be rapid and extensive, necessitating “rapid assessment” techniques. For undeveloped lakeshores in the Northern Appalachian/Acadian ecoregion (330 000 km²), we developed a geospatial screening process based on four factors: (1) urban area proximity, (2) attractiveness of amenity (size), (3) regulatory gaps in protection, and (4) likelihood that owners will develop. To assess conversion risk, we added developable zones to the 10 783 large lakes and ponds in the ecoregion and assessed risk to these lands based on four factors at two distances from 15 major urban areas in the region. Thirty-eight of 387 landowners were classified most likely to convert their lands through development, and 11 of these accounted for 97.5% of the total high-risk habitat area (625–1118 km²). Nearly all of the at-risk land (94.6%) lay outside of currently settled areas and most (69.1%) under the purview of a single regulatory agency, the Land Use Regulatory Commission of Maine (LURC). Without rigorous planning by such agencies large-scale, highly dispersed, and rapid conversion of lightly settled, amenity-rich forestland threatens habitat degradation at multiple spatial scales, i.e., local ecosystems themselves (e.g., lakes), surrounding landscapes, and regions.     

基于主导生态功能分区的河流健康评价全指标体系

为建立全国河流健康评价标准的方法框架，从影响河流生态系统的生物、生境要素和人类活动要素出发，构建了包括水文特性、水质特性、河流地貌特性、生物特性和社会经济特性5方面、含36项指标的全国河流健康评价全指标体系；提出了基于主导生态功能和纬度、集水面积、距离河源的位置、河流所处地区等空间因子的两级水生态区划方法，根据河流所属水生态区构建了基于一级分区的特定河流健康评价指标体系，确定河流健康评价重点以及不同指标的权重；选择了5条河流作为示例划分水生态区，并明确了建立其河流健康评价指标体系需考虑的重点。     

基于水生态区的黑河流域水生态健康评价研究

本文以我国西北干旱区典型内陆河流域—黑河流域为例,基于黑河流域水生态区划,以"压力-状态-响应"(PSR)模型为基础,构建了涵盖13个指标的流域水生态健康评价体系,分析评价了流域内8个水生态区的健康状况。评价表明:黑河流域水生态区中,上游区域水生态健康状况较好,中游次之,中下游极差,下游较差。主要是因为上游地区受到外在污染最轻、人为扰动相对最小;中游地区人口密度相对较大,农业活动等外在扰动相对较多;中下游地区处于荒漠地区,河流、湖库等水体缺乏;而下游地区虽然人口数量少、水体受外来污染影响较小,流域水生态健康性压力相对较轻,但来水量相对不足、水生态系统栖息地条件极为脆弱,致使水生生物栖息地安全状况较差。