Evaluating sustainability of community endeavours in an Indian floodplain wetland using multi‐criteria decision analysis

The floodplain wetlands of Ganga‐Ichamati interfluves in India have become severely degraded due to incessant, unsustainable utilization practices and lack of community awareness. In spite of the wetlands being the prime source of livelihood for millions, no comprehensive management strategy to accommodate the diverse aspirations and priorities of different users has been implemented for the wetlands to date. In this paper, the authors applied a framework of criteria and indicators to evaluate the status of sustainability achieved by community endeavours in one such wetland. The priorities, consumption patterns and contributions towards wetland conservation of major user groups functioning in that area were assessed by the framework developed through participatory multi‐criteria decision analysis. Results show the deteriorating status of the wetland at present regarding biodiversity conservation and livelihood generation. Fishing activities were identified as the dominant utilization option here followed by agriculture. The paper further explored the preferred alternative utilization strategies for achieving sustainability. Effectiveness of the developed framework in evaluating the extent of sustainability achieved in community endeavours was also highlighted in this context.     

Spatio-temporal dynamics of regulating ecosystem services in Europe – The role of past and future land use change

Land use is a main driver for changes in supply and demand of regulating ecosystem services (ES). Most current ES inventories are static and do not address dynamics of ES supply resulting from historic and future land use change. This paper analyzes the role of land use change for the supply of two regulating services, flood regulation and climate regulation, in the European Union (EU) for the period between 1900 and 2000 as well as for four plausible scenarios of future land use change up to 2040. We show that spatio-temporal dynamics of climate regulation are high during this time period, and that future levels of climate regulation are higher than 100 years ago. For flood regulation, we show that increases in the demand over the past century, which are continued in the future scenarios, are the main contributor for spatial mismatches of supply and demand. Our results indicate that, in spite of land use change, the overall supply of the two regulating services is expected to be moderately stable, or to even increase in the coming decades. At the same time, demands for these services are rapidly increasing, and it is unlikely that projected supply is sufficient to meet these demands. The results also indicate that land use allocation that favors the supply of regulating services can be seen as a nature-based solution in which potentials for synergies between multiple ES can be operationalized.     

基于物质流分析的城市工业经济脱钩问题研究——以天津市2001-2012年面板数据为例

随着经济的快速发展,资源约束下环境问题日益突出,生态文明建设要求社会经济系统在物质增长的同时,环境和资源日益改善以满足循环经济的发展需求。当前经济增长与环境资源状况呈现耦合关系,违背了可持续发展的要求和目标。结合天津市工业系统物质流指标,分析其当前经济耦合程度,采用物质流输入输出指标进行脱钩分析,并对主要指标的组成部分分别赋予权重,基于指数时间序列的指标组成部分进行脱钩分析。结果表明,实现工业经济脱钩的关键在于从化石能源开采、金属矿产使用等方面转变经济发展方式,达到工业系统的碳排放、废弃物及水体污染减排目标,以实现工业经济系统的可持续发展及保障生态文明建设的顺利实施。     

A time-integrated MODIS burn severity assessment using the multi-temporal differenced normalized burn ratio (dNBRMT)

Burn severity is an important parameter in post-fire management. It incorporates both the direct fire impact (vegetation depletion) and ecosystem responses (vegetation regeneration). From a remote sensing perspective, burn severity is traditionally estimated using Landsat's differenced normalized burn ratio (dNBR). In this case study of the large 2007 Peloponnese (Greece) wildfires, Landsat dNBR estimates correlated reasonably well with Geo composite burn index (GeoCBI) field data of severity (R² = 0.56). The usage of Landsat imagery is, however, restricted by cloud cover and image-to-image normalization constraints. Therefore a multi-temporal burn severity approach based on coarse spatial, high temporal resolution moderate resolution imaging spectroradiometer (MODIS) imagery is presented in this study. The multi-temporal dNBR (dNBR_MT) is defined as the 1-year integrated difference between burned pixels and their unique control pixels. These control pixels were selected based on time series similarity and spatial context and reflect how burned pixels would have behaved in the case no fire had occurred. Linear regression between downsampled Landsat dNBR and dNBR_MT estimates resulted in a moderate-high coefficient of determination R² = 0.54. dNBR_MT estimates are indicative for the change in vegetation productivity due to the fire. This change is considerably higher for forests than for more sparsely vegetated areas like shrub lands. Although Landsat dNBR is superior for spatial detail, MODIS-derived dNBR_MT estimates present a valuable alternative for burn severity mapping at continental to global scale without image availability constraints. This is beneficial to compare trends in burn severity across regions and time. Moreover, thanks to MODIS's repeated temporal sampling, the dNBR_MT accounts for both first- and second-order fire effects.     

Microbial water quality of the Georgian coastal zone of the Black Sea

From 2006 to 2008, microbial water quality was monitored along the Georgian coast of the Black Sea. Temperature, pH, salinity, and dissolved oxygen were measured, along with a variety of aquatic microbial parameters, including heterotrophic plate count (HPC), total culturable bacterial count (TCBC), and chlorophyll a (Chl-a) concentration. Total and fecal coliforms and total enterococci counts were recorded as indicators of fecal pollution. Vibrio bacteria, and Escherichia coli- and Vibrio-specific bacteriophages were isolated and enumerated to determine their relationships to standard marine pollution indicators.Persistent microbial pollution was observed, particularly in the summer months, with a higher rate of contamination in estuaries. Microbial indicators generally showed seasonal dependence, suggesting that temperature may influence bacterial dynamics in this environment. No correlation was apparent between fecal pollution indicators and physical-chemical and aquatic microbial parameters, although there were significant relationships amongst the indicators themselves, as well as with the prevalence of Vibrio bacteria and phage.     

斑岩型铜矿勘查地球化学研究现状及进展

斑岩型铜矿是我国最重要的铜矿床类型,随着矿业开发的不断深入,勘查地球化学在矿产勘查中的作用变得愈来愈重要。为此,在收集整理有关文献的基础上,对过去斑岩型铜矿勘查地球化学研究的成果进行了总结,包括地球化学特征、勘查方法、异常评价及找矿标志等方面。以富家坞铜矿为例,介绍斑岩型铜矿的最新研究进展。     

昆明北金大道CFG桩复合地基承载力研究

结合北金大道5#、6#路与20m规划路间高填方路基的工程实例,分析CFG桩复合地基的设计过程及各个参数的取值,对CFG桩复合地基的一些设计和施工问题进行讨论。     

近年来国内ENSO研究概述

综合介绍了近年来国内学者在ENSO研究中取得的一些进展，包括ENSO事件的指标和强度指数、ENSO的机制、ENSO的预测。认为ENSO研究中其指标和强度指数朝着综合指标方面发展是一种趋势；ENSO循环不仅仅是一种热带海洋气候和大气气候事件。更是一种全球性行为，其机制的研究还有待深入；对ENSO的模式预测存在不稳定，尚不能完整、准确地预报所有EI Nino/La Nina事件。     

青海绿梁山铜矿找矿信息的提取与成矿预测

绿梁山铜矿位于柴达木盆地北缘,属柴北缘成矿带,它是中国西部重要的多金属成矿区带之一。通过对绿梁山铜矿详细的地质调查、水系沉积物测量、高精度磁测扫面和遥感解译等工作,在系统研究其成矿地质条件、地球化学特征、地球物理特征和遥感影像特征的基础上,进一步筛选与矿化有关的异常信息,归纳并提取了地物化遥找矿信息:硅化、黄铁矿化、绿泥石化、绿帘石化、绢云母化等近矿围岩蚀变是寻找铜矿床的间接标志;遥感解译的复合环形构造与遥感蚀变信息叠加区是找矿有利区;在Cu、Au、Bi异常区沿铜矿化向北西存在较多的铜金矿化线索;强磁异常梯度带分布是最显著的深大断裂位置反映;显著的水热蚀变晕也是寻找该类矿床的重要遥感标志。结合以上特征在绿梁山找矿远景区内共圈定出Ⅰ、Ⅱ类靶区共3个。     

Performance of Multi Model Canonical Correlation Analysis (MMCCA) for prediction of Indian summer monsoon rainfall using GCMs output

The emerging advances in the field of dynamical prediction of monsoon using state-of-the-art General Circulation Models (GCMs) have led to the development of various multi model ensemble techniques (MMEs). In the present study, the concept of Canonical Correlation Analysis is used for making MME (referred as Multi Model Canonical Correlation Analysis or MMCCA) for the prediction of Indian summer monsoon rainfall (ISMR) during June-July-August-September (JJAS). This method has been employed on the rainfall outputs of six different GCMs for the period 1982 to 2008. The prediction skill of ISMR by MMCCA is compared with the simple composite method (SCM) (i.e. arithmetic mean of all GCMs), which is taken as a benchmark. After a rigorous analysis through different skill metrics such as correlation coefficient and index of agreement, the superiority of MMCCA over SCM is illustrated. Performance of both models is also evaluated during six typical monsoon years and the results indicate the potential of MMCCA over SCM in capturing the spatial pattern during extreme years.