基于DPSIR的吉林省白山市生态安全评价

通过对白山市的生态安全现状和问题进行分析,探究其生态环境改变的主要驱动力因子和胁迫因子;基于DPSIR模型提出了白山市生态安全综合评价指标体系,并进一步构建了适于山地地区的生态安全评价模型;利用1989年、1999年和2006年的3期TM遥感影像,结合研究区的DEM数据和实地调查数据建立解译标志,对白山市土地覆被进行景观分类,借助Fragstats分析景观指数,提取重要的生态安全评价指标,对白山市所辖各区县进行生态安全综合评价.结果表明： 白山市生态安全的空间差异显著,整体生态安全状况呈现出一种恶化趋势,人为活动对地表景观格局和物种栖息地分布产生了深刻的影响,已成为生态安全格局变化的主要驱动力因子.     

1995-2015年武汉城市湖泊景观生态安全格局演化

以1995、2005、2015年3期遥感影像为数据源,通过景观指数和GIS空间分析方法研究武汉中心城区湖泊系统景观格局的演化特征,进而构建湖泊景观生态安全评价模型,以揭示武汉中心城区湖泊系统景观生态安全格局演变规律,并探讨其驱动因素。研究结果表明：（1）近20年来武汉中心城区湖泊系统总面积呈现不断下降趋势,1995-2005年以年均2.4%的速率缩减了28.95 km²,2005-2015年以年均1.8%的速率缩减了17.47 km²。（2）研究期湖泊系统的斑块密度、分维数呈现不断降低趋势,这表明武汉中心城区湖泊破碎化程度在不断降低,湖泊形状趋于简化;而连接度呈现不断增加趋势,湖泊分布集聚趋势不断加强,空间结构趋于紧凑集中。（3）武汉城市湖泊系统总体景观生态安全呈现不断恶化趋势,而次级湖泊水系景观生态安全呈现不同的演化特征。城市建成区的迅速扩展、湖泊由农业生产对象转化为可利用发展用地、房地产事业成为支柱产业是湖泊系统遭填占最主要的动力,直接危害了其景观生态安全,而市民环境意识提高引发湖泊保护倡议和实践,对湖泊景观生态安全产生着积极影响。对湖泊景观生态安全格局演变特征及驱动因素的研究,可以为武汉制定行之有效的生态管理政策和环境治理措施提供重要支撑。     

巢湖流域生态安全评价研究

目前,巢湖流域的生态安全问题非常突出,已严重影响流域社会经济的可持续发展。基于巢湖流域社会经济、水体环境质量及水生生态系统的数据资料,应用驱动力-压力-状态-影响-响应(DPSIR)模型,提出了基于水环境和水生态的巢湖流域生态安全评价框架模型和指标体系,并采用熵权物元模糊评价法进行巢湖流域生态安全评价研究。研究结果表明,2003和2007年巢湖流域整体处于生态安全中度风险状态,水体环境质量的变化和水生生态系统的演替将严重威胁巢湖流域的生态安全,水体中的TP浓度、NH-N浓度以及TN浓度是决定巢湖流域生态安全的最关键因子。     

A predictive model for water clarity following dreissenid invasion

Optical transparency, or water clarity, is a fundamental property of lake ecosystems which influences a wide range of physical, chemical and biological variables and processes. The establishment of non-native dreissenid mussels in lake and river ecosystems across North America and Europe has been associated with often dramatic, but highly variable, increases in water clarity. The objective of this study was to develop a predictive model for water clarity (Secchi depth, m) in lakes following the establishment of dreissenids. We compiled water clarity data before and after dreissenid invasion from North American lakes that varied in size and nutrient status. An AIC model averaging approach was used to generate post-invasion water clarity predictions based on pre-invasion water clarity and lake morphometric characteristics from a 53 lake dataset. The accuracy of the model was verified using cross-validation. We then extended this model to existing empirical models of lake mixing depth and Walleye (Sander vitreus) yield, to demonstrate that increased water clarity associated with dreissenid invasion may have far-reaching physical and ecological consequences in lakes, including deeper thermoclines and context-dependent changes in fish yields.     

Assessing ecological quality of shallow lakes: Does knowledge of transparency suffice?

The European Water Framework Directive (WFD) requires that all aquatic ecosystems in their member states should reach ‘good’ ecological quality by 2015. To assess ecological quality, the WFD requires the definition of reference conditions using biological, physical and chemical indicators and the assignment of each water body to one of five quality classes using these indicators. Elaborate assessment schemes using large sets of variables are now being developed. Here we address the question whether all this is really needed and what the simplest assessment approach would be for the case of shallow lakes. We explore the relationships between the quality class assigned to a lake by experts in shallow lake ecology and a rich set of biological, physical, and chemical data. Multinomial logistic regression analyses were carried out based on data from 86 shallow lakes throughout Europe that were sampled in 2000 and/or 2001. Ecological quality of shallow lakes judged by experts was strongly correlated to physical and chemical variables associated with light regime and nutrients and much less to biological variables.Our regression model showed that ecological quality of this set of shallow lakes judged by experts could be predicted quite well from water transparency expressed as Secchi depth and that other variables did not contribute to it significantly. According to the WFD, lakes should at least have a ‘good’ ecological quality. Quality judged by experts and predicted quality were similar for 78% of the lakes with respect to meeting this standard. As a cautionary note we stress that Secchi depth alone will be a less useful indicator if effects of stressors other than eutrophication (e.g. lake acidification and toxic pollution) are to be considered.     

基于系统动力学的重庆三峡库区生态安全情景模拟及指标阈值确定

根据重庆三峡库区生态系统的特征,建立了经济子系统、人口子系统和环境子系统的系统动力学模型,并在此基础上确定了其模型的主要参数和反馈关系,通过历史值与仿真值的对比进行了检验。选择了可持续发展型、资源衰竭型和自然状态型3种情景进行模拟最终确定其生态安全的指标阈值,并将其确定的阈值应用于生态安全评价指标,得出重庆三峡库区生态安全指标的综合得分,由此看出库区生态安全呈逐年递增的趋势,但仍然处于较为敏感的时期,需要相关部门的配合,从而最终实现库区的可持续发展。     

Development of a fish-based index to assess the eutrophication status of European lakes

The use of the CEN (European Committee for Standardization) standard method for sampling fish in lakes using multi-mesh gillnets allowed the collection of fish assemblages of 445 European lakes in 12 countries. The lakes were additionally characterised by environmental drivers and eutrophication proxies. Following a site-specific approach including a validation procedure, a fish index including two abundance metrics (catch per unit effort expressed as fish number and biomass) and one functional metric of composition (abundance of omnivorous fish) was developed. Correlated with the proxy of eutrophication, this index discriminates between heavily and moderately impacted lakes. Additional analyses on a subset of data from Nordic lakes revealed a stronger correlation between the new fish index and the pressure data. Despite an uneven geographical distribution of the lakes and certain shortcomings in the environmental and pressure data, the fish index proved to be useful for ecological status assessment of lakes applying standardised protocols and thus supports the development of national lake fish assessment tools in line with the European Water Framework Directive.     

The current status of heavy metal in lake sediments from China: Pollution and ecological risk assessment

Heavy metal contamination in lake sediments is a serious problem, particularly in developing countries such as China. To evaluate heavy metal pollution and risk of contamination in lake sediments on a national scale in China, we collated available data in the literature of the last 10 years on lake sediments polluted with heavy metals from 24 provinces in China. Based on these data, we used sediment quality guidelines, geoaccumulation index, and potential ecological risk index to assess potential ecological risk levels. The results showed that approximately 20.6% of the lakes studied exceeded grade II level in Chinese soil quality standards for As, 31.3% for Cd, 4.6% for Cu, 20.8% for Ni, 2.8% for Zn, and 11.1% for Hg, respectively. Besides, the mean concentrations for As in 10.3% of lakes, Hg in 11.9% of lakes, and Ni in 31.3% of lakes surpassed the probable effect level. The potential ecological risk for toxic metals decreased in the order of Cd > Hg > As > Cu > Pb > Ni > Cr > Zn, and there were 21.8% of the lakes studied in the state of moderate risk, 10.9% in high risk, and 12.7% in very high risk. It can be concluded that Chinese lake sediments are polluted by heavy metals to varying degrees. In order to provide key management targets for relevant administrative agencies, based on the results of the pollution and ecological risk assessments, Cd, Hg, As, Cu, and Ni were selected as the priority control heavy metals, and the eastern coastal provinces and Hunan province were selected as the priority control provinces. This article, therefore, provides a comprehensive assessment of heavy metal pollution in lake sediments in China, while providing a reference for the development of lake sediment quality standards.     

A Model to Predict Lake Water Colour

This study is an attempt to quantitatively determine variables of significance for predicting colour in small glacial lakes. Lake colour is an important variable in many lake ecological contexts. The data emanate from two extensive data-sets from Sweden, one of which concerns 1456 lakes, and the other 91 more well-suited lakes. Four year average values of lake colour were compared to catchment and morphometric parameters to help identify the processes which influence variability in colour between lakes. Various hypotheses concerning the factors regulating colour in lakes were formulated and tested. Various statistical tests were used to separate random influences from causal influences. Those “map parameters” with the most significant influence on colour were the theoretical lake water retention time, the percent of rocks, lakes and mires of the drainage area, the ratio between lake area and drainage area and the lake mean depth. Each model parameter provides only a limited explanation (statistical) of the variability in colour between lakes. The predictability of colour by these models can not be markedly improved by accounting for the distribution of the characteristics in the drainage area. The stability of the final model, which gives an r²-value of 0.74, has been tested with positive results. The model allows lake colour to be estimated from knowledge of “geological” characteristics of the lake and its drainage area. The variability between lakes from other factors, such as temperature, precipitation and/or contamination of acidifying substances and nutrients, may then be quantitatively differentiated from the impact of these “geological” factors.     

An integrated ecological security early-warning framework in the national nature reserve based on the gray model

Nature reserves (NRs) play a pivotal role in minimizing habitat loss and protecting wild animals and plants, which are critical for human ecological security. However, focusing only on the construction of ecological security patterns of NRs without understanding their ecological security early-warning situations and their driving factors may fail to achieve protection goals. This study constructed an ecological security early-warning framework and index system based on the Driving force-Pressure-State-Impact-Response (DPSIR) framework model. The gray model (GM) was used to predict the ecological security early-warning situation, and the Geo-detector model was applied to explore the driving factors of the ecological security early-warning system in the Baishuijiang National Nature Reserve (BNNR). The results showed that the average ecological security index (ESI) value increased from 0.2796 in 2005 to 0.3171 in 2017, with an average increase of 11.82%. The ecological security early-warning index (ESEWI) value increased from 0.3171 in 2018 to 0.3622 in 2030, which was an average increase of 12.46%. These results indicated that the ecological security situation continually improved from 2005 to 2030. By 2030, the number of towns with a “no warning” grade increased to four, the number of towns with an “extreme warning” grade was zero, and the proportion of areas with early-warnings decreased from 100% to 33%. The q values of per capita forest land areas and per capita grassland areas were both 0.9334, which indicated that environmental characteristic factors were the primary driving factors in ecological security early-warning. Our results demonstrated that the ecological security early-warning index system based on the DPSIR model and grey model can well prediction ecological security situation and provide scientific support for the ecological protection and management of NRs.     

高原湖泊城市生态安全格局构建——以大理市为例

合理构建生态安全格局是高原湖泊城市健康发展的重要保障。以大理市为研究区,将生态系统健康和生态系统服务统筹到生态安全评估,尝试采用土地发展概率修正生态阻力面,运用电路理论构建生态安全格局,并提出优化方案。结果表明：大理市生态安全水平呈现出“高-低-高”圈层结构空间分布特征;确定生态源地53块,生成顾及未来土地发展的生态阻力面,识别生态廊道111条,筛选生态夹点23处,划分三级生态改善区。提出以洱海为一核,以苍山和南部林区为两屏,以大理市东北部生态保护区、海东生态修复区和满江—凤仪生态城市建设区为三区,以城镇区之间的多个生态修复区为多组团共同构成“一核、两屏、三区、多组团”的生态安全优化格局。将生态系统健康和生态系统服务统筹到生态安全评估及利用土地发展概率修正阻力面所构建的生态安全格局,能更加真实的反映未来发展趋势下生态安全格局构建的需要,为城市生态安全格局构建方法提供了新视角和新方法,以期为城市生态文明建设的区域理论提供借鉴,助力高原湖泊城市的生态宜居。     

Quantifying uncertainties in biologically-based water quality assessment: A pan-European analysis of lake phytoplankton community metrics

Lake phytoplankton are adopted world-wide as a sensitive indicator of water quality. European environmental legislation, the EU Water Framework Directive (WFD), formalises this, requiring the use of phytoplankton to assess the ecological status of lakes and coastal waters. Here we provide a rigorous assessment of a number of proposed phytoplankton metrics for assessing the ecological quality of European lakes, specifically in response to nutrient enrichment, or eutrophication, the most widespread pressure affecting lakes. To be useful indicators, metrics must have a small measurement error relative to the eutrophication signal we want them to represent among lakes of different nutrient status. An understanding of variability in metric scores among different locations around a lake, or due to sampling and analytical variability can also identify how best this measurement error is minimised.To quantify metric variability, we analyse data from a multi-scale field campaign of 32 European lakes, resolving the extent to which seven phytoplankton metrics (including chlorophyll a, the most widely used metric of lake quality) vary among lakes, among sampling locations within a lake and through sample replication and processing. We also relate these metrics to environmental variables, including total phosphorus concentration as an indicator of eutrophication.For all seven metrics, 65–96% of the variance in metric scores was among lakes, much higher than variability occurring due to sampling/sample processing. Using multi-model inference, there was strong support for relationships between among-lake variation in three metrics and differences in total phosphorus concentrations. Three of the metrics were also related to mean lake depth. Variability among locations within a lake was minimal (<4%), with sub-samples and analysts accounting for much of the within-lake metric variance. This indicates that a single sampling location is representative and suggests that sub-sample replication and standardisation of analyst procedures should result in increased precision of ecological assessments based upon these metrics.For three phytoplankton metrics being used in the WFD: chlorophyll a concentration, the Phytoplankton Trophic Index (PTI) and cyanobacterial biovolume, >85% of the variance in metric scores was among-lakes and total phosphorus concentration was well supported as a predictor of this variation. Based upon this study, we can recommend that these three proposed metrics can be considered sufficiently robust for the ecological status assessment of European lakes in WFD monitoring schemes.     

太湖湖滨带生态系统健康评价

根据湖滨带生态系统的特点,运用综合健康指数法建立了湖滨带生态系统健康评价体系,由目标层、准则层、指标层构成,其中准则层由湖滨带水质状况、底泥状况、植被状况、其它生物状况(浮游动物、浮游植物、底栖动物)、岸带物理状况5项组成,指标层由总氮、总磷、溶解氧、挺水植物覆盖率等15项指标构成。采用专家打分法、熵值法分别确定了准则层、指标层的权重系数。对太湖湖滨带33个点位进行了采样分析,并进行无量纲化处理后应用到所建立的评价体系中。评价结果显示33个点位中为"很健康"、"健康"、"亚健康"、"疾病"、"严重疾病"的分别占0%、24.2%、21.2%、51.5%及3.0%,也即超过一半的点位处于"疾病"状态。只有东太湖刚刚超过"健康"分数的下限,东部沿岸、贡湖、南部沿岸均处于"亚健康"状态,而梅梁湾、竺山湾、西部沿岸属于"疾病"状态,且竺山湾的生态健康状态最差。该评价结果与太湖湖滨带各分区的实际调查情况相符合,评价方法可靠性、可行性较强,可为其它湖泊湖滨带的生态系统健康评价提供一定的参照。     

A hitchhiker's guide to European lake ecological assessment and intercalibration

The Water Framework Directive is the first international legislation to require European countries to establish comparable ecological assessment schemes for their freshwaters. A key element in harmonising quality classification within and between Europe's river basins is an “Intercalibration” exercise, stipulated by the WFD, to ensure that the good status boundaries in all of the biological assessment methods correspond to similar levels of anthropogenic pressure. In this article, we provide a comprehensive overview of this international comparison, focusing on the assessment schemes developed for freshwater lakes. Out of 82 lake ecological assessment methods reported for the comparison, 62 were successfully intercalibrated and included in the EC Decision on intercalibration, with a high proportion of phytoplankton (18), macrophyte (17) and benthic fauna (13) assessment methods. All the lake assessment methods are reviewed in this article, including the results of intercalibration. Furthermore, the current gaps and way forward to reach consistent management objectives for European lakes are discussed.     

Ecological classification of lakes: Uncertainty and the influence of year-to-year variability

Regular monitoring of lakes is important to determine their ecological state and development and of key significance when deciding whether action should be taken to improve their quality, for instance by reducing the external loading of nutrients. Imprecise or inadequate knowledge of the ecological state increases the risk of misclassification and of wrong management decisions. Based on Danish lake data, we aimed to determine temporal variations, in particular natural year-to-year differences, and to describe the uncertainty in assessing the ecological state of lakes. We analysed environmental data from ca. 350 Danish lakes (1100 lake years), including three case studies, with long-term data series (up to 24 years), with no significant changes in external nutrient loading. We used summer means of selected water chemical variables, phytoplankton and submerged macrophytes as indicators of ecological state and found considerable variations in all indicators, which could not be ascribed alone to meteorological variation. In shallow lakes, chlorophyll a concentrations exhibited large year-to-year variations, especially at TP ranging between 0.05 and 0.15 mg L⁻¹ where the lakes may shift between a macrophyte- and a phytoplankton-dominated state. For example, chlorophyll a varied by a factor 5–10 between years and was particularly low when submerged macrophyte coverage exceeded 20% compared with lakes without macrophytes. Use of a multimetric index including four phytoplankton indicators reduced the coefficient of variation. Generally, the 95% confidence interval of ecological classification was approximately 50% lower when the assessment of ecological state was based on 4–5 years’ measurements than if based on only one year's measurements. Knowledge and awareness of the uncertainty of indicators used in ecological classification are highly relevant for lake managers and policy makers when defining efficient monitoring and restoration strategies.     

沉积硅藻揭示的历史时期水生植被信息以梁子湖为例

水生植被是浅水湖泊生态系统最重要的生态特征之一, 了解其群落历史演化特征, 对生态退化湖泊的修复有着重要指导意义。研究选择长江中下游地区代表性草型湖泊梁子湖, 基于梁子湖沉积岩芯210Pb/137Cs测年、沉积硅藻序列和梁子湖长期水生植被监测记录, 探讨利用沉积硅藻记录来重建该湖历史时期水生植被演替特征的可行性。研究结果表明: 梁子湖沉积硅藻记录对历史时期水生植被的演替有较好的反映; 基于此, 对梁子湖过去近200年的水生植被覆盖度进行了重建; 与湖泊流域历史环境信息的对比分析表明洪水是影响该湖水生植被发育的一个重要因素。研究结果证实了在浅水湖泊中, 沉积硅藻可揭示历史水生植被的信息, 并为该湖的水生植被保护提供科学依据, 同时对该区富营养湖泊的生态修复有重要的指导价值。       

太湖流域生态安全格局构建与调控——基于空间形态学-最小累积阻力模型

构建生态安全网络是在快速城镇化和生态环境恶化的背景下保护生物多样性的重要举措。以典型跨界的太湖流域为地理研究单元,使用多源空间数据,采用空间形态学方法(Morphological spatial pattern analysis, MSPA)和最小累积阻力模型(Minimal cumulative resistance, MCR)以及地理学统计方法建立“生态源地-活动廊道-保护网络-阻力特征-分区调控”的生态安全模式。研究结果显示：(1)太湖流域20个具有保护生物多样性功能的生态源地主要分布在浙西区和湖西区,包括大型湖体和丘陵森林等;(2)流域内重要性廊道贯穿太湖连接大型湖体和森林,一般性廊道集中分布在浙西-湖西区,将生态源地两两相连;(3)根据节点-廊道-源地网络分布,参考生态阻力和生境质量的空间性特征,构建流域“四区一带”生态安全格局并提出分区管控措施,为经济发展快速但生境脆弱的太湖流域生态体系建设与生物多样性保护提供参考。     

A fish-based index for the assessment of the ecological quality of temperate lakes

A fish – based index for the assessment of the ecological quality of natural temperate lakes was developed, in accordance to the requirements of the Water Framework Directive (WFD) 2000/60/EC. As a case study, 11 natural lakes located at northern and western Greece were selected. Fish surveys were conducted during mid summer to mid autumn in 2010, 2011 and 2012 using Nordic gillnets and electrofishing. Environmental parameters and anthropogenic pressures were assessed for each lake. Fish species richness, abundance, trophic, reproductive and habitat functional guilds were used for extracting a set of 107 metrics, meeting the requirements of the WFD. All metrics were initially tested as candidates for the index development. A stepwise linear regression of each metric against environmental parameters (lake area, altitude, maximum depth, alkalinity) and anthropogenic pressures (drainage area covered by non-natural land uses – NNLC, water total phosphorus concentrations – TP, Lake Habitat Modification Score – LHMS) was initially conducted for ensuring pressure-response relationships. Reference conditions for each lake were estimated by the hindcasting procedure and the ecological quality for each lake was expressed as the ecological quality ratio (EQR) by a value ranging from 0 (poor quality) to 1 (excellent quality). Two fish fauna metrics, the relative numerical abundance of introduced species (Introduced_a) and the relative biomass of omnivorous species (OMNI_b) were finally extracted as the most significant, responding to LHMS and TP, respectively. The final index was expressed as the mean values of the EQRs of these two metrics. The multimetric fish index presented herein could serve as a tool for assessing the ecological quality of natural lakes at broad geographical scale and generally, in the Mediterranean temperate lakes with similar hydromorphological characteristics.     

中国中东部平原亚热带湿润区湖泊营养物生态分区

湖泊营养物生态分区是实现湖泊分区控制的前提和基础。以中国中东部平原亚热带湿润区为案例区,根据区域特点,从自然地理要素、生态系统和人类活动三方面建立指标体系,对各指标进行归一化得到各指标数据的分值;采用AHP方法确定各指标的权重值,结合各指标分值计算栅格尺度上湖泊营养物生态分区综合评价分值;根据研究区域DEM数据划分小流域,将栅格尺度的湖泊营养物生态分区综合评价分值投影到小流域尺度上,采用双约束空间聚类算法对小流域尺度上湖泊营养物生态分区评价分值进行聚类得到湖泊营养物生态分区结果。结果表明:(1)AHP可以用来确定复杂指标体系中各指标的权重,适合用于确定湖泊营养物生态分区指标体系中各指标的权重;(2)采用双约束空间聚类进行湖泊营养物生态分区,保证了分区结果在空间上的连续性和评价分值上的接近性;(3)根据自然地理条件、土地利用和人类活动强度的不同,可以将中东部平原亚热带湿润区划分为长江中下游平原湖区、湘赣平原丘陵湖区、湘渝山地湖区、四川盆地湖区、川西—大巴山山地湖区5个营养物生态区。