Search

There are several standardized meteorological, hydrological, agricultural, and environmental indices for drought classification into a set of dry categories all of which are derived from the basic concept of standardized precipitation index (SPI). Almost all these indices are based on crisp (bivalent) logic where boundary limits between neighboring categories are numbers without transboundary inclusiveness. The SPI procedure depends on the standard normal (Gaussian) probability distribution function (PDF) with zero mean and standard deviation equal to one. This paper proposed fuzzification of the SPI limits among categories for the inclusion of more than one category with different membership degrees. This method is referred to as the fuzzy SPI (FSPI) procedure, which provides drought tracing possibility and categorization. At the end for a numerical value, one can defuzzify the fuzzy result through defuzzification methods. FSPI provides preliminary warning system in terms of two or more fuzzy rule propositions and categories. Thus, one can know the logical alternatives of the drought behavior of a given hydro-meteorology variable. The application of the FSPI is presented for New Jersey State wise and Istanbul annual precipitation records. [ABSTRACT FROM AUTHOR]

Multi-sensor fire detection has been widely used, which allows monitoring multiple environmental indicators. However, most multi-sensor detection methods detect fires only by comparing the measurements of environmental indicators at each detection time with the preset thresholds. It is prone to fire false alarms due to neglecting the time series characteristics of environmental information. To improve the robustness and accuracy of fire detection, this paper proposes a new multi-sensor fire detection method based on long short-term memory (LSTM) networks, named EIF-LSTM. EIF-LSTM integrates environmental information fusion, which is divided into two steps. First, EIF-LSTM extracts the time series characteristics of the monitoring environment by processing multi-sensor time series readings, including environmental indicator variation information and environmental level information. Second, the normalized multi-sensor time series readings, environmental indicator variation information and environmental level information are fused together for fire prediction. The LSTM network realizes the extraction of environmental time series characteristics due to its ability to learn long-term dependencies. The addition of two kinds of time series information increases the detection dimension and enhances the fusion effect. Experimental results on a real-world fire dataset show that EIF-LSTM is capable of achieving state-of-the-art detection performance. [ABSTRACT FROM AUTHOR]

Seismic losses due to earthquakes have been shown to have significant economic, social and environmental consequences. Over recent years, research to predict potential economic and social impact due to seismic risk has been increasing. Recognizing that the traditional philosophy of life safety design can lead to extensive damage and demolition which has a large environmental cost, incorporating environmental impacts associated with the expected seismic damage over a building's life is a key step as the building industry moves towards both sustainable and seismically resilient design. This paper introduces a framework that uses environmental indicators quantifying losses from seismic response that can then be used to advocate for a change in seismic performance objectives. First, existing literature and previously developed approaches for quantifying potential environmental impact due to seismic damage are summarized. Next, performance based earthquake engineering concepts are used to demonstrate a probabilistic approach to quantify potential environmental impacts using a range of environmental and resource use indicators over the life span of a case study building. In addition, a case study is presented to compare different environmental indicators between a Code Minimum building and the same building redesigned for a higher seismic performance. The majority of the composition of the environmental indicator values are from the inclusion of the non-repairable scenario, and from the repair activities, the majority of the impacts are from damage to drift sensitive components including curtains walls, partitions and elevators. For the Code Minimum building the non-repairable scenario contributes to between 8 to 11% the total seismic cost. For the Stronger Stiffer building, the non-repairable scenario contributes around 3% of the initial impact. Neglecting non-repairable scenarios does significantly reduce the potential environmental impacts when analyzing buildings designed for current code minimum structural standards. [ABSTRACT FROM AUTHOR]

The paper compares different approaches to the reconstruction of environmental conditions from rodent fossil complexes, namely, the bioclimatic method and the method of reconstructing soil and plant conditions considering voles. For the reconstruction, data from ten localities in Western Siberia dated to the second half of the Middle Pleistocene were analyzed. The bioclimatic method allowed us to reconstruct the arid climatic zone in the south of Western Siberia (the Pre-Altai Plain and the Middle Irtysh) and the moderately cold and arctic climate for the localities situated northwards. The method of reconstruction of soil and vegetation conditions showed the predominance of xerophytic plant communities for the southern localities and mesophytic, mesohygrophytic, and hygrophytic for the northern ones. As additional indicators of environmental conditions, specialized species were proposed: subterranean animals (Siberian zokor and northern mole voles) and briophages (West Siberian lemming). [ABSTRACT FROM AUTHOR]

The total electric field on the roof platform of buildings becomes a new and important indicator of the environmental assessment of HVDC projects. In this paper, the upper-stream finite element method is used to simulate and calculate the distribution characteristics of the total electric field on the roof platform of the flat-roofed building adjacent to an HVDC line, from the factors of material conductivity and three-dimensional structure. The results show that when the conductivity of the building is greater than 10−10 S/m, it can be regarded as an equipotential body with the ground. Therefore, when the field mill measures the electric field on the roof platform, the field mill can be connected to the building to achieve the purpose of grounding. Otherwise, additional appropriate grounding treatment is required. Moreover, the protrusions such as parapets and stairwells on the roof platform of the building have both distortion and shielding effects on the total electric field. The larger the area of the protrusions, the better the shielding effect, making the total electric field on the roof platform weaker. Therefore, when measuring the total electric field on the roof platform, to avoid the unpredictability of the measurement results of the field mill, the field mill should be arranged in the center flat area at least 2 m away from the protrusions. [ABSTRACT FROM AUTHOR]

Livestock production is confronted with significant challenges across all dimensions of sustainability. There is an urgent need to identify sustainable livestock systems that are environmentally friendly, economically viable for farmers, and socially acceptable. To this end, diversity assessments and data-driven indicator-based sustainability assessments can be helpful tools. These two mutually reinforcing approaches each have their own dilemmas and strengths; however, their combination is not straightforward. In this paper, we propose a method that simultaneously assesses the diversity and sustainability of production systems within one agricultural sector, without compromising either aspect, while overcoming the dilemmas of diversity and sustainability assessments. We test our method on the Walloon dairy and beef sectors (Belgium) and base our assessment on data from the European Farm Accountancy Data Network (FADN). We apply relevant classification criteria to the sample farms to group them into production systems. The core data was complemented with calculated environmental indicators to perform a comprehensive sustainability assessment, including structural, socio-economic, and environmental indicators. Our results confirm the importance of complementing sustainability assessments with diversity assessments. Our case study results show that a diversity of livestock systems coexist and that it is possible to overcome trade-offs between economic and environmental performances. Extensive grass-based systems present the best combination of economic and environmental results, which highlights the importance of preserving grassland resources at the regional level. The proposed method proves effective to improve the relevance of FADN data and supports the ongoing call to transform the FADN into a more comprehensive database that satisfactorily covers all dimensions of sustainability. [ABSTRACT FROM AUTHOR]

The present paper explains the development and validation of four new eco-friendly and stability-indicating spectroscopic methods of estimating a calcimimetic drug, i.e., cinacalcet hydrochloride (CIN), in its different pharmaceutical formulations. In these methods, the response of the standard solution is measured in 0.1N HCl as a diluent (nonhazardous) at 279, 294, and 299 nm for UV, first-, and second-order derivative spectrophotometric tools, respectively. The AUC-spectrophotometric technique is carried out by calculating the area under the curve (AUC) between the wavelength regions ranging from 266 to 286 nm. The linearity graph of the methods is plotted by taking response [Absorbance/(dA/dλ)/(d2A/dλ2) or AUC] values against the concentration and shows that the drug obeys Beer's law within the concentration range 2.5 to 200 μg/mL for all the methods. The drug is exposed to various stress conditions as recommended by the ICH Q1A-Q1E guideline. The different method validation parameters are within the acceptable limit as per the ICH Q2R(1) guideline. The greenness profile of the developed UV spectroscopic tools is evaluated using the National Environmental Methods Index, the Analytical Eco-Scale, and the Analytical GREEnness (AGREE) metric approach. All approaches prove the greenness of the methods concerning solvent, chemicals, energy consumed, and waste produced. Eco-friendly spectroscopic methods can determine the quantity of CIN in various pharmaceutical dosage forms without influencing the environment and analysts. [ABSTRACT FROM AUTHOR]

Fano resonance is based on plasmonic metasurfaces and has many applications in all kinds of fields. In this paper, we propose an independently switchable double-layer raster structure based on graphene. Depending on the highly adjustable nature of graphene, the Fermi energy level can be adjusted to control the Fano resonance at different wavelengths. The equivalent resonator coupling mode method is used to simulate the Fano resonance, and the transmission spectrum fits well. Functional switch at different wavelengths can be achieved using Fano resonance technology. The simulation obtained a fantastic group refractive index of the designed structure, indicating that there is a possibility to apply it in slow light. The effect of the environmental refractive index on sensing performance was studied and we found the structure has great potential in making high-sensitivity sensors. To sum up, it is hoped that this structure can make a great contribution to the manufacture of integrated optics. [ABSTRACT FROM AUTHOR]

This study contributes to the debate on the development of aggregate metrics of societal progress. Summarising societal progress into a single number poses various methodological challenges, including the choice of indicators, normalisation, weighting and aggregation. This paper addresses the issue of aggregation in the case of metrics of well-being and uses as a case study the European Union regional Social Progress Index—EU-SPI—published by the European Commission. The index is an aggregate measure of 55 social and environmental indicators observed for all the European regions grouped into 12 components. In metrics of this type, while complete substitutability among components is rarely acceptable, controlling their level of substitutability is highly desirable. To this aim, we adopt a modified version of the unbalance penalisation approach originally proposed by Casadio Tarabusi and Guarini (Soc Indic Res 112:9–45, 2013). A penalisation is applied to the regions whose performance across the index components is unbalanced, that is when they perform well on some components but worse on others. The penalisation applied by this approach depends on two parameters that, in its original formulation, are generally arbitrarily chosen. We design a data-driven approach allowing for an informed choice of the penalisation parameters. The comparison between the EU-SPI original and penalised scores shows that the penalisation effect is particularly evident for regions with a strongly unbalanced profile across the components. The proposed method allows for adjusting the level of substitutability between components when constructing an aggregate metric, an important functionality especially when measuring societal progress for policy-making. [ABSTRACT FROM AUTHOR]

This paper proposes the concept of green institutional environment, and constructs China's green institutional environmental system from the three dimensions of green supervision and public institution, green standardized institution and green accounting institution. Based on the relevant data from 2007 to 2017, this paper simulates China's green institutional environmental index through the Functional Data Analysis method and the functional entropy weight method. The results show that, first, there is a general upward trend in China's green institutional environmental index, with a range of [0.2–0.8]; the minimum value of this index is 0, and there is no maximum value. The larger the value, the higher the level of green institutional environment. Second, at the present stage, China's green standardized institution is relatively well-developed, accounting for the largest weight (i.e., [0.932–0.940]) in the green institutional environmental index system; the green accounting institution plays a supporting role, with a weight of [0.030–0.040], due to the fact that the Chinese government has made great efforts to implement policies at this level; the development of green supervision and public institution is under-developed and has little influence on the green institutional environmental index, with a weight of [0.0285–0.0305]. Finally, the proposed green institutional environmental index remains robust when equalizing the weights of the three dimensions. [ABSTRACT FROM AUTHOR]

Birds are a kind of environmental indicator organism, which can reflect the changes in the ecological environment and biodiversity, and recognition of birdsongs can further help understand and protect birds and natural environment. Extreme learning machine (ELM) has the advantages of fast learning speed and good generalization ability, which is widely used in classification and recognition problems. Input layer weights and hidden layer thresholds are two key factors affecting ELM performance. As one of swarm intelligence optimization methods, differential evolution (DE) can be used to optimize the parameters of ELM. In order to enhance the diversity, convergence speed and global search ability of the DE population, and improve the accuracy and stability of the classification model, this paper proposes a multi-strategy differential evolution method (M-SDE) to optimize the parameters of the ELM. And the differential MFCC feature parameters, extracted from birdsongs, are applied to build classification models of M-SDE_ELM and an ensemble M-SDE_EnELM with optimized ELM for bird species recognition. In the experiments, the ELM models optimized by the swarm intelligence algorithms PSO and GOA are compared and analyzed by hypothesis tests with the M-SDE_ELM and M-SDE_EnELM. Results show that the M-SDE_ELM and M-SDE_EnELM can achieve a classification accuracy of 86.70% and 89.05% in the classification of nine species of birds respectively, and the recognition effect and stability of the M-SDE_EnELM model outperform other models. [ABSTRACT FROM AUTHOR]

Key message: We evaluate self-organizing maps (SOM) to identify adaptation zones and visualize multi-environment genotypic responses. We apply SOM to multiple traits and crop growth model output of large-scale European sunflower data. Genotype-by-environment interactions (G × E) complicate the selection of well-adapted varieties. A possible solution is to group trial locations into adaptation zones with G × E occurring mainly between zones. By selecting for good performance inside those zones, response to selection is increased. In this paper, we present a two-step procedure to identify adaptation zones that starts from a self-organizing map (SOM). In the SOM, trials across locations and years are assigned to groups, called units, that are organized on a two-dimensional grid. Units that are further apart contain more distinct trials. In an iterative process of reweighting trial contributions to units, the grid configuration is learnt simultaneously with the trial assignment to units. An aggregation of the units in the SOM by hierarchical clustering then produces environment types, i.e. trials with similar growing conditions. Adaptation zones can subsequently be identified by grouping trial locations with similar distributions of environment types across years. For the construction of SOMs, multiple data types can be combined. We compared environment types and adaptation zones obtained for European sunflower from quantitative traits like yield, oil content, phenology and disease scores with those obtained from environmental indices calculated with the crop growth model Sunflo. We also show how results are affected by input data organization and user-defined weights for genotypes and traits. Adaptation zones for European sunflower as identified by our SOM-based strategy captured substantial genotype-by-location interaction and pointed to trials in Spain, Turkey and South Bulgaria as inducing different genotypic responses. [ABSTRACT FROM AUTHOR]

In the last years, there has been a growing interest in composite indices, whether they be social, socio-economic or environmental indices. In this paper, we propose a new approach to the composite indices construction which consists in computing an interval of possible values, for each statistical unit, rather than a single value. The interval is called 'performance interval' and it is constructed depending on the level of compensability of individual indicators. As an example of application, we considered a set of indicators of well-being in Italy and we constructed the performance intervals for the Italian Regions. Finally, we compared the midpoint of the performance intervals with the geometric mean, a classic partially compensatory aggregation function. [ABSTRACT FROM AUTHOR]

The development of industry has brought about the pollution of the atmospheric environment. Pollution is harmful to people's health. Realizing the real-time monitoring of atmospheric environmental quality parameters can improve the above-mentioned effects. China's existing environmental monitoring systems focus on the accuracy of the system hardware itself for assessment, lack of data analysis and forecasting and early warning, and cannot provide managers and ordinary people with decision-making and activity guidance. This paper develops an IPV6-based high-spatial–temporal precision air pollutant monitoring and early warning platform. The feasibility of the system is verified through networking tests, operation tests, and early warning tests. Through actual data analysis and comparison, it is concluded that the monitoring system has field feasibility, and the atmospheric environment monitoring for the target observation area has achieved the desired observation function. This system integrates GIS technology and B/S architecture to analyze changes in the regional environment to provide support for regional environmental air quality management. The forecast and early warning module constructed by combining the weight method of the influence of different input factors on the environmental quality index and minute-level observations can provide technical support for the government to improve the level of supervision. [ABSTRACT FROM AUTHOR]

In this paper, we introduce and test a framework to qualitatively assess the environmental impact of climate adaptation innovations with the ambition to facilitate the implementation of these adaptations. The framework was designed to enable continuous environmentally conscious benchmarking based on three environmental performance indicators: sustainable design, environmental impact and ecological impact. It was pilot tested by uninvolved experts and key-persons for two large-scale nature-based flood adaptation innovations in the Netherlands and discussed with environmental assessment professionals. Our findings indicate how the inclusion of our framework helps to identify important knowledge gaps regarding environmental co-benefits and trade-offs, and can be beneficial to both those developing the innovation and the local authorities charged with assessing the suitability of innovations. We conclude by noting how the incorporation of environmental impact assessment from the design stage of adaptations could supplement existing environmental assessment regulations pre-empting concerns rather than reacting to them. [ABSTRACT FROM AUTHOR]

Five core sandstone and carbonate rock samples from the Cretaceous Harshiyat Formation containing oil stains were collected from two wells in the North Hadramaut High area (eastern Yemen) and geochemically analyzed by their sterane and terpane biomarker and stable carbon isotope (δ13C) compositions. This paper studied the geochemical characteristics of the oil stains and their relation to probable potential source rocks. The source rock characteristics include the origin of organic matter input; redox depositional conditions, lithology, and degree of thermal maturity were investigated. The saturated and aromatic hydrocarbon fractions of the analyzed oil stain samples have δ13C values in the range of − 26.5‰ – − 28.6‰ and − 26.3‰ – − 26.7‰, respectively. These δ13C values indicate that the oil stain samples originated from a mixed organic matter input in their source rock. The presence of mixed marine and terrestrial organic matter in the source rock is further concluded from biomarker distributions of n-alkane, isoprenoid, terpane, and sterane. These biomarkers and their ratio parameters suggest that the analyzed oil stain samples were sourced from clay-rich rock deposited in marine-reducing environmental conditions and likely contained mixed planktonic/bacterial organic matter and land plant inputs. Both saturated and aromatic maturity biomarkers suggest that the analyzed oil stains were from a mature source rock, equivalent to a moderate to peak-mature oil window. The environmental biomarker indicators of the studied oil stain samples correlated well with the shales in the Late Cretaceous Harshiyat Formation in the onshore Jiza-Qamar Basin (eastern Yemen), indicating that the analyzed oil stains were generated from a mature Harshiyat source rock in the onshore Jiza-Qamar Basin and subsequently migrated into the Cretaceous Harshiyat sandstone and limestone reservoirs in the North Hadramaut High area (eastern Yemen) through normal faults system. [ABSTRACT FROM AUTHOR]

The use of chemical substances in clean rooms (CRs), most of which are aggressive and toxic, requires an analysis of the air removal system (ARS) not only from functionally determined but also from energy and environmental points of view. This paper explores the possibility of using the energy and environmental analysis methodology to compare the environmental friendliness of various CR ARSs in microelectronics. It is shown that direct air removal, despite its thermodynamic advantage over a purification system, is less favorable for the environment due to the significant level of the environmental index (EI), which reflects the potential economic damage to the atmosphere from emissions. The dominant contaminants in the composition of emissions that determine the validity of the decision on the structure of a CR's ARS, taking into account the environmental, economic, and biomedical aspects of its operation, are established. [ABSTRACT FROM AUTHOR]

Urban comprehensive carrying capacity is an important guarantee and external representation of regional sustainable development. Based on urban comprehensive carrying capacity, this paper constructed a performance evaluation index system of urban comprehensive carrying capacity, and used entropy method, urban comprehensive carrying capacity measurement model and urban sustainable development model to measure spatial and temporal comprehensive carrying capacity of Harbin City in Heilongjiang Province from 2012 to 2017. The results show that: 1) index weight analysis suggested the regional development mode in Harbin still followed an epitaxial development mode, which pursued the expansion of scale and the growth of total amount of regional development, neglecting the effective utilization of resources and the improvement of structural benefits. 2) In the pressure system, the index of resource support has dropped sharply. The index of environmental capacity and social progress has risen circuitously, while the degree of agglomeration and the value of transportation facilities have risen steadily; in the pressure system, the index of population development and economic growth tended to fluctuate, while energy consumption and environmental pollution showed a more synchronous change in characteristics, and the livable demand remained at a high level. 3) The carrying capacity index of resources and environment in Harbin has been declining, and the acquired carrying capacity index fluctuated. The long-term regional development model has severely impaired the carrying capacity of resources and environment. 4) The comprehensive carrying capacity of Harbin has clear spatial differentiation characteristics. Finally, the paper proposes that location conditions, economic development level, government regulation, and science and technology are the main factors influencing the spatial differentiation of urban comprehensive carrying capacity. [ABSTRACT FROM AUTHOR]

Environmental variability often has substantial impacts on natural populations and communities through its effects on the performance of individuals. Because organisms' responses to environmental conditions are often nonlinear (e.g., decreasing performance on both sides of an optimal temperature), the mean response is often different from the response in the mean environment. Ye et al. (Ann Appl Stat 14(3):1326–12341, 2020) proposed testing for the presence of such variance effects on individual or population growth rates by estimating the "Jensen Effect", the difference in average growth rates under varying versus fixed environments, in functional single index models for environmental effects on growth. In this paper, we extend this analysis to effects of environmental variance on reproduction and survival, which have count and binary outcomes. In the standard generalized linear models used to analyze such data the direction of the Jensen Effect is tacitly assumed a priori by the model's link function. Here we extend the methods of Ye et al. (2020) using a generalized single index model to test whether this assumed direction is contradicted by the data. We show that our test has reasonable power under mild alternatives, but requires sample sizes that are larger than are often available. We demonstrate our methods on a long-term time series of plant ground cover in Idaho sagebrush steppe. [ABSTRACT FROM AUTHOR]

In the past decades, new indicators have been developed to provide alternatives to gross domestic product (GDP) at the macro level and to financial indicators at the business level (businesses' social and environmental indicators). However, these new indicators are poorly articulated between the business and the macro level. This paper aims to discuss the different possibilities of articulation that exist and outline a framework for a better micro–macro articulation. Firstly, we draw from the example of GDP and traditional business indicators by analysing the way they are articulated. Secondly, we review how sets of alternative indicators aim to articulate the macro and micro level by analysing indicators constructed around gross national happiness (GNH) and sustainable development goals (SDGs). This research shows that two specific types of articulation exist between indicators at different levels, one referred to as the 'accounting' type and the other called the 'conceptual' type. Their strengths and limits will be discussed, as well as how they can be combined. Finally, recommendations will be provided on how to best articulate beyond GDP and business level indicators. [ABSTRACT FROM AUTHOR]

Several episodes of extreme precipitation excess and extreme precipitation deficit, with considerable economic and social impacts, have occurred in Europe and in Poland in the last decades. However, the changes of related indices exhibit complex variability. This paper analyses changes in indices related to observed abundance and deficit of precipitated water in Poland. Among studied indices are maximum seasonal 24-h precipitation for the winter half-year (Oct.-March) and the summer half-year (Apr.-Sept.), maximum 5-day precipitation, maximum monthly precipitation and number of days with intense or very intense precipitation (respectively, in excess of 10 mm or 20 mm per day). Also, the warm-seasonal maximum number of consecutive dry days (longest period with daily precipitation below 1 mm) was examined. Analysis of precipitation extremes showed that daily maximum precipitation for the summer half-year increased for many stations, and increases during the summer half-year are more numerous than those in the winter half-year. Also, analysis of 5-day and monthly precipitation sums show increases for many stations. Number of days with intense precipitation increases especially in the north-western part of Poland. The number of consecutive dry days is getting higher for many stations in the summer half-year. Comparison of these two periods: colder 1961-1990 and warmer 1991-2015, revealed that during last 25 years most of statistical indices, such as 25th and 75th percentiles, median, mean and maximum are higher. However, many changes discussed in this paper are weak and statistically insignificant. The findings reported in this paper challenge results based on earlier data that do not include 2007-2015. [ABSTRACT FROM AUTHOR]

In this paper, six types of air pollutant concentrations are taken as the research object, and the data monitored by the micro air quality detector are calibrated by the national control point measurement data. We use correlation analysis to find out the main factors affecting air quality, and then build a stepwise regression model for six types of pollutants based on 8 months of data. Taking the stepwise regression fitting value and the data monitored by the miniature air quality detector as input variables, combined with the multilayer perceptron neural network, the SRA-MLP model was obtained to correct the pollutant data. We compared the stepwise regression model, the standard multilayer perceptron neural network and the SRA-MLP model by three indicators. Whether it is root mean square error, average absolute error or average relative error, SRA-MLP model is the best model. Using the SRA-MLP model to correct the data can increase the accuracy of the self-built point data by 42.5% to 86.5%. The SRA-MLP model has excellent prediction effects on both the training set and the test set, indicating that it has good generalization ability. This model plays a positive role in scientific arrangement and promotion of miniature air quality detectors. It can be applied not only to air quality monitoring, but also to the monitoring of other environmental indicators. [ABSTRACT FROM AUTHOR]

Globally, agriculture is recognized as a highly vulnerable sector to climate change and risks from climatic aberrations pose an imminent danger to the food security and sustainability of livelihoods. To bring robustness in climate adaptation planning, evaluation of resilience across homogenous regions is essential for developing and scaling suitable location-need-context specific interventions and policies that build the resilience of the agricultural system. In this paper, we present an analysis and discussion of multi-scalar and multi-indicator assessment, by profiling resilience across agro-climatic zones of India, based on the development of a Climate-Resilient Agriculture Index embracing environmental, technological, socio-economic, and institutional and infrastructural dimension. A total of 26 indicators, spread across these four dimensions, were employed to purport inter- and intra-agro-climatic zone differentials in the level of resilience. Among the zones, it was found that West Coast Plains & Ghats and Tans-Gangetic Plains had the highest degree of resilience to manage climate risks. Most of the districts lying within Eastern Himalayan Region, Middle Gangetic Plains, Eastern Plateau & Hills, and Western Dry Region had a lower degree of resilience. The study places greater emphasis on deciphering region-specific drivers and barriers to resilience at a further disaggregated scale for improving rural well-beings. It is construed that devising action plans emphasizing awareness, preservation of natural resources, diversification, building physical infrastructure, strengthening of grass-root institutions, and mainstreaming climate adaptation in the developmental policy is crucial for climate-resilient pathways. [ABSTRACT FROM AUTHOR]

Are countries at a low level of socio-economic development catching up with developed countries over time or rather falling further behind? Existing work on the subject is not conclusive, partially due to methodological differences. The aim of the paper is to carry out a broader analysis with longer time series and a more diverse set of indicators. The study divides countries of the world into 21 developed "benchmark" countries and 156 developing countries. The distance between the benchmark and developing countries is measured using the "time lags" method, applied here to nine indicators covering topics such as the economy, health, education and the environment. The study further utilizes a probabilistic approach to extrapolate missing historical data for developing countries, so that the analysis can cover a full century starting in 1920 and ending with short-term projections to year 2020. The study finds that a majority of developing countries, and the population-weighted developing world as a whole, has reduced its lag in most indicators between 1920 and 2020. Progress was unevenly distributed, with East Asian and European countries converging the most with the benchmark, while most African countries have diverged along with some American ones. Catch-up in education attainment and life expectancy has been more successful than in infant survival rate, GDP per capita or technology adoption. The findings are put in context of United Nations' Sustainable Development Goals, showing how the time lag method could improve setting targets for some of the goals. Further, time lags are used to analyze the current demographic, economic and political situation of developing countries, identifying opportunities and risks for future catch-up with developed countries. [ABSTRACT FROM AUTHOR]

A group event such as human and traffic congestion can be very roughly divided into three stages: converging stage before congestion, gathered stage when congestion happens, and dispersing stage that congestion disappears. It is of great interest in modeling and identifying converging behaviors before gathered events actually happen, which helps to proactively predict and handle potential public incidents such as serious stampedes. However, most of existing literature put too much emphasis on the second stage, only a few of them is dedicated to the first stage. In this paper, we propose a novel group pattern, namely converging, which refers to a group of moving objects converging from different directions during a certain period before gathered. To discover efficiently such converging patterns, we develop a framework for converging pattern mining (CPM) by examining how moving objects form clusters and the process of the "cluster containment". The framework consists of three phases: snapshot cluster discovery phase, cluster containment join phase, and converging detection phase. As cluster containment mining is the key step, we develop three algorithms to discover cluster containment matches: a containment-join-algorithm, called SSCCJ, by using spatial proximity; a signature tree-based cluster-containment-join-algorithm, called STCCJ, which takes advantage of the cluster containment relations and signature techniques to filter enormous unqualified candidates in an efficient and effective way; and third, to keep the advantages of the above algorithms while avoiding their flaws, we further propose a signature quad-tree based cluster-containment-join algorithm, called SQTCCJ, which can identify efficiently matches by considering cluster spatial proximity as well as containment relations simultaneously. To assess the proposed methods, we redefine two evaluation metrics based on the concept of "Precision and Recall" in the field of information retrieval and the characteristics of converging patterns. We also propose a new indicator for measuring the duration of the converging stage in a group event. Finally, the effectiveness of the CPM and the efficiency of the mining algorithms are evaluated using three types of trajectory datasets, and the results show that the SQTCCJ algorithm demonstrates a superior performance. [ABSTRACT FROM AUTHOR]

Key message: Multi-parent populations multi-environment QTL experiments data should be analysed jointly to estimate the QTL effect variation within the population and between environments. Commonly, QTL detection in multi-parent populations (MPPs) data measured in multiple environments (ME) is done by analyzing genotypic values 'averaged' across environments. This method ignores the environment-specific QTL (QTLxE) effects. Running separate single environment analyses is a possibility to measure QTLxE effects, but those analyses do not model the genetic covariance due to the use of the same genotype in different environments. In this paper, we propose methods to analyse MPP-ME QTL experiments using simultaneously the data from several environments and modelling the genotypic covariance. Using data from the EU-NAM Flint population, we show that these methods estimate the QTLxE effects and that they can improve the quality of the QTL detection. Those methods also have a larger inference power. For example, they can be extended to integrate environmental indices like temperature or precipitation to better understand the mechanisms behind the QTLxE effects. Therefore, our methodology allows the exploitation of the full MPP-ME data potential: to estimate QTL effect variation (a) within the MPP between sub-populations due to different genetic backgrounds and (b) between environments. [ABSTRACT FROM AUTHOR]

The electromagnetically induced transparency (EIT) effect has been widely studied in metamaterials, which has potential applications in optical storage and sensors due to its less stringent implementation conditions. Especially, EIT with reciprocity is flexibility which is not limited by the incident direction of electromagnetic field. In this paper, a reciprocal and large angle electromagnetically induced transparency (EIT) effect in the terahertz range is proposed. The tri-layer metamaterial structure is consisted of one opening ring and four sectors which represented the bright and dark modes, respectively. The physical mechanism of the EIT effect can be attributed to Fano resonance coupling with the bright and dark modes. Influence of structure parameters on the performance of the structure is discussed. The EIT effect is affected by the length of the gaps and environmental refractive index. In addition, changing the incident angle, the EIT effect always exists until the angle of the incidental electromagnetic wave is 60°. The group delay is calculated and shown potential application in slow light effect. These results have many potential applications for slow light devices, terahertz filtering, large-angle switching and sensors. [ABSTRACT FROM AUTHOR]

The sorting of small parts is one of the common tasks in the field of industrial manufacturing. Vibratory bowl feeders (VBF) are commonly used to accomplish this task. Nowadays, the design process of the VBF is based on a manual and expensive trial-and-error approach, in which different traps are arranged and tuned. This paper outlines a method which modifies this conventional process using Reinforcement Learning to automate the VBF design. To enable this, a software agent is used to model the placement of traps on multiple positions and measure the subsequent configuration efficiency. A physics simulation provides the characteristics of the individual traps. During the training, Q-learning is applied to determine the environmental indicators under which a certain trap should be replaced. A 3D matrix is used to store information in a problem-related representation. Due to the trial-and-error principle of Reinforcement Learning, this training is comparable with the traditional proceedings. In addition, valuable action paths are stored in a memory and the agent frequently is trained on these paths in order to remember good solutions. Additionally, a knowledge base is used to exclude inefficient sets of traps. The rules for the knowledge base are built upon knowledge from the conventional design process. In first test cases, the trained agent is able to assemble traps achieving promising configurations. The results of the agent will be validated in the next step using physics simulation. [ABSTRACT FROM AUTHOR]

Composite materials are demonstrating the ability to face the challenge of competitive markets where high-performance, low costs, and reduced manufacturing time are mandatory. Vacuum bagging with autoclave curing is one of the most used manufacturing methods for carbon fiber composite parts. However, it shows some limitations, mainly due to manual operations and long processing time. Out-of-autoclave (OOA) methods, such as pressure bag molding (PBM), can lead to a strong reduction of the manufacturing time through the simplification of lay-up and curing phases. In this paper, a comparative analysis between the autoclave and the PBM processes has been performed, jointly considering both the economic and environmental aspects. An evaluation of the environmental impacts has been carried out following the standardized life cycle assessment (LCA) methodology. In addition, costs related to these two manufacturing techniques have been estimated through a parametric approach and successively compared. Different scenarios have been considered to take into account various production batches, mold manufacturing techniques, and end of life alternatives. The analyses show conflicting results demonstrating that a global optimum scenario does not exist and, depending on the chosen indicator and production batch, the best alternative varies. Considering only the environmental indicators, the autoclave process can be considered the most sustainable option, due to the lower consumption of energy. [ABSTRACT FROM AUTHOR]

Because of differences in energetic investments in reproduction, natural and sexual selection are expected to impact males and females differentially, driving the evolution of sexual dimorphism. Thus, males and females are predicted to also differ in how they respond to environmental stressors and how they restore and maintain body homeostasis. Oxidative stress has been suggested to be one potential indicator of the impact of environmental stressors on wildlife. In this paper, we evaluate, for the first time, the oxidative stress in two sympatric lekking species of Neotropical manakins: the Red-headed Manakin (Ceratopipra rubrocapilla) and the White-crowned Manakin (Pseudopipra pipra). Specifically, we test the hypothesis that females of these two species have higher levels of oxidative stress than males because, among Neotropical manakins, only females provide parental care. We found no support for this hypothesis. In fact, males had higher levels of oxidative stress than females. All three hypotheses (predation stress, oxidation handicap, and aerobic activity) available to explain our results have limitations, so further field and laboratory studies on oxidative stress in manakins are required. [ABSTRACT FROM AUTHOR]

Implementing an effective climate policy is one of the main challenges for the future. Curbing greenhouse gas emissions can prevent future irreversible impacts of climate change. Climate policy is therefore crucial for present and future generations. Nonetheless, one may wonder whether future economic and social development could be harmed by climate policy. This paper addresses this question by examining recent developments in international climate policy and considering different levels of cooperation that may arise in light of the outcomes of the Conference of the Parties held in Doha. The paper analyses how various climate policy scenarios would enhance sustainability and whether there is a trade-off between climate policy and economic development and social cohesion. This is done by using a new comprehensive indicator, the FEEM Sustainability Index (FEEM SI), which aggregates several economic, social, and environmental indicators. The FEEM SI is built into a recursive-dynamic computable general equilibrium model of the world economy, thus offering the possibility of projecting all indicators into the future and of delivering a perspective assessment of sustainability under different future climate policy scenarios. We find that the environmental component of sustainability improves at the regional and world level thanks to the implementation of climate policies. Overall sustainability increases in all scenarios since the economic and social components are affected negatively yet marginally. This analysis does not include explicitly climate change damages and this may lead to underestimating the benefits of policy actions. If the USA, Canada, Japan and Russia did not contribute to mitigating emissions, sustainability in these countries would decrease and the overall effectiveness of climate policy in enhancing global sustainability would be offset. [ABSTRACT FROM AUTHOR]

This paper presents the results of the design and implementation of a new geological tool, named as HUMGEOSTAT, for advanced geostatistical analysis of mineral deposit, a case study at the Sin Quyen, one of the important mines for the Vietnam mining industry in Vietnam. The tool is developed based on the Stanford Geostatistical Modeling Software (SgeMS) platform, which is an open-source computer package for solving problems involving spatially related variables. The tool is capable of supporting users in reducing uncertainty and improving the quality of mining exploration tasks. The tool has all the functions needed to solve a complete geostatistical issues i.e. Variogram models (such as Spherical, Exponential, Gausian, Linear and Pure nugget effect); and four commonly used Kriging methods (Ordinary Kriging, Simple Kriging, Indicator Kriging, Co-Kriging). The tool was applied to test various types of input data and particularly for complex copper ore bodies of Sin Quyen mine. The results of analysis of orebody spatial structure has found that Cu content has non-uniform change, regional anisotropy in north-south (0±22.50) direction, and anisotropic index is around 1.3. The mineral reserves are estimated according to sub-blocks and points in the orebody-space. The results indicate that the Ordinary Kriging (OK) has reliable results, variance estimation is small; the predicted result gained from OK have strong correlation (K=0.905) with ore samples. HUMGEOSTAT was applied at the Sin Quyen mine and various coal mines, the results were adapted with reality of mines. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSN) are finding increasing use in all-metal marine environments such as ships, oil and gas rigs, freight container terminals, and marine energy platforms. However, wireless propagation in an all-metal environment with ducting and sealed doors between compartments is difficult to model, and the operating machinery further complicates wireless network planning. This makes it necessary to characterize the performance of the physical wireless links in the actual operating environments. However, little has been reported in the literature on methodologies for measuring the full range of physical link quality indicators. In this paper, we present a methodology for doing this that we have verified by the deployment of a 2.4 GHz network of 18 nodes in three different all-metal scenarios: a cluster of freight containers, a full-sized shore-based working ship's engine room training facility, and an operational ship's engine room. The output variables included the key link quality indicators of packet delivery ratio (PDR), RSSI, and LQI for every possible link, as well as the performance of every node. We believe that this is the first time that this full range of physical link quality indicators has been measured in this type of application environment. We found that in all three scenarios the network performed with over 90% PDR average. However, as the scenarios become more complex, the communications become more unpredictable, yielding a wider transition zone, indicating that although a WSN could operate in these scenarios under different conditions, a pre-deployment practical study is essential for each new scenario. [ABSTRACT FROM AUTHOR]

Sustainability is an increasingly important factor in today's globally competitive environment. How sustainability features are prioritized in terms of relevance and significance is a function of many factors, including variations in types of business, operational conditions, history and other characteristics particular to a company. The purpose of this paper is to propose a stochastic model that explicitly addresses the potential barriers and enablers to sustainability in order to measure and assess the sustainability level of a company. Given that the potential barriers and enablers to sustainability are context dependent, the stochastic model developed in this paper assumes that a variable characterization of sustainability functions can describe a realistic analytical model for a company's sustainability behavior. By adopting the strong sustainability perspective, a case scenario is used to demonstrate the application of the proposed model in a major Canadian electric utility. By providing relatively simple and informative measurement, the proposed sustainability model can be used as a practical and effective tool to assess the sustainability level of any company under consideration and to evaluate sustainability fluctuation of the company over time. [ABSTRACT FROM AUTHOR]

The objective of sustainability measurement is to move environmental decision making toward more rigorous, quantitative and empirical foundations. One of the most comprehensive attempts to lay out the foundations for sustainability measurement has been offered by the Environmental Sustainability Index (ESI). This paper aims to advance the science of sustainability measurement by assessing the validity and reliability of this composite index in order to provide new insights for future indicator development. The architecture of the ESI is validated against the Pressure-State-Response (PSR) model, after which an exploratory factor analysis is conducted to reveal the latent structure of the index. Further, the performance of the ESI is tested in cross-national regression models. The results indicate a lack of consistency with the well established PSR model and a potential bias towards economically developed countries grounded in the architecture and weighting mechanism of the index. A re-weighted index (Equivalised ESI) is constructed, resulting in a new ranking of countries' sustainability. The Equivalised ESI improves the measurement qualities of the index, and in so doing actually reinforces the rich-country bias of the ESI. Put differently, the Equivalised ESI brings the deficiencies of the original ESI to the fore. This paper illustrates that there are serious conceptual problems and validity concerns with defining the ESI as a sustainability measure. Taken together, the findings reinforce the need to reconsider future foundations of sustainability measurement in order to ensure that it is clear both what is being measured and how well. [ABSTRACT FROM AUTHOR]

The objective of this paper is to compile selected caesium-137 concentrations in seafood and seawater (the key OSPAR indicators) from the data submitted by the United Kingdom to the OSPAR Commission. The impact upon the surrounding environment of the Irish Sea and North Sea has been determined from trends of caesium-137 concentration data over time, from the start of the OSPAR evaluation period to the present date. Generally, caesium-137 concentrations, in each of the key OSPAR indicators (by sample type and site locations), have declined in both the Irish and North Sea environments over the long time period. [ABSTRACT FROM AUTHOR]

Research has demonstrated that, in a variety of settings, environmental factors influence migration. Yet much of the existing work examines objective indicators of environmental conditions as opposed to the environmental perceptions of potential migrants. This paper examines migration decision-making and individual perceptions of different types of environmental change (sudden vs. gradual environmental events) with a focus on five developing countries: Vietnam, Cambodia, Uganda, Nicaragua, and Peru. The survey data include both migrants and non-migrants, with the results suggesting that individual perceptions of long-term (gradual) environmental events, such as droughts, lower the likelihood of internal migration. However, sudden-onset events, such as floods, increase movement. These findings substantially improve our understanding of perceptions as related to internal migration and also suggest that a more differentiated perspective is needed on environmental migration as a form of adaptation. [ABSTRACT FROM AUTHOR]

As a result of climatic change associated with global warming, aridity is an increasing problem in many parts of the world, including south-eastern and southern regions of Romania. This paper clarifies the concept of aridity, and discusses related concepts including indices of aridity, and their influence on some landscape and soil features including climatic water deficit (WD) and the depth to soil carbonates (DC). As used here, WD is calculated as the difference between precipitation sum (P) and the Penman-Monteith reference evapotranspiration sum (ETo-PM) over certain periods. Another three well-known aridity indices are also considered: De Martonne’s index (Iar-DM), Thornthwaite’s index (Iar-TH), the UNESCO (1979) P/ETo-PM ratio index (Iar-P/ETo-PM). WD is as high as −450 mm during the growing season in the most arid, south-eastern and southern regions of Romania, especially in the Dobrogea and Baragan areas. In other regions of Romania, including most of the plains and plateaus where agriculture is an important branch of the economy, WD reaches −100 to −300 mm during the growing season. The above aridity indices were spatially interpolated for specific periods by kriging, to generate relatively homogeneous areas. WD can also be seen as an aridity index which has the advantage of a more accurate quantification of the water supply needed for a reference crop, e.g. grass under standardised conditions, for various geographical regions. WD is significantly correlated with the other aridity indexes and with DC. This paper also examines the risk of aridity spreading, and suggests improvements to the water management system for agriculture in Romania. [ABSTRACT FROM AUTHOR]

This paper provides an economic perspective of adaptation to climate change. The paper specifically examines the role of markets and government in efficient adaptation responses. For adaptations to be efficient, the benefits from following adaptations must exceed the costs. For private market goods, market actors will follow this principle in their own interest. For public goods, governments must take on this responsibility. Governments must also be careful to design institutions that encourage efficiency or they could inadvertently increase the damages from climate change. Finally, although in a few cases actors must anticipate climate changes far into the future, generally it is best to learn and then act with respect to adaptation. [ABSTRACT FROM AUTHOR]

During the development of the Third U.S. National Climate Assessment, an indicators system was recommended as a foundational product to support a sustained assessment process (Buizer et al. ). The development of this system, which we call the National Climate Indicators System (NCIS), has been an important early product of a sustained assessment process. In this paper, we describe the scoping and development of recommendations and prototypes for the NCIS, with the expectation that the process and lessons learned will be useful to others developing suites of indicators. Key factors of initial success are detailed, as well as a robust vision and decision criteria for future development; we also provide suggestions for voluntary support of the broader scientific community, and for funding priorities, including a research team to coordinate and prototype the indicators, system, and process. Moving forward, sufficient coordination and scientific expertise to implement and maintain the NCIS, as well as creation of a structure for scientific input from the broader community, will be crucial to its success. [ABSTRACT FROM AUTHOR]

This paper proposes a mathematical model for allocating water to stakeholders of a shared watershed. Each stakeholder in the basin has a water demand and a water profit; however, the available water cannot meet the demands of all stakeholders. This shortage raises a conflict between stakeholders as they use a common resource. To reach an agreement between the stakeholders in water allocation, first a model was developed to obtain the highest possible profit that a stakeholder can achieve if the stakeholder is allowed to utilize as much as possible water after satisfying the basin environmental demands (flows). Then, another model was introduced which allocates water to each stakeholder such that the minimum ratio of stakeholders' profits to their highest possible profits is maximized. It is shown that the obtained solution is non-dominated in terms of considering each stakeholder profit as an objective, which means that none of the objective functions can be improved in value without degrading some of the other objective values. The proposed method is applied to the Sefidrud River basin, which is one of the biggest rivers in Iran. The stakeholders of this basin are eight administrative provinces that compete for utilizing more water while the Basin's water resources could not satisfy all stakeholders' water requirements. The model's results show that it can successfully be used for sustainable conflict resolution in a shared basin because the model satisfies the environmental water requirement in the entire basin and provides equitably the same ratio of the stakeholders' highest possible profits for them. For the case of this study, the proposed approach allocates water to the stakeholders in such a way that they could obtain at least 65 % of their highest possible profits in average. [ABSTRACT FROM AUTHOR]

This paper presents a method for identifying a representative subset of global climate models (GCMs) for use in large-scale climate impact research. Based on objective criteria (GCM performance in reproducing the seasonal cycle of temperature and precipitation, and a subset ability to represent future inter-GCM variability), two candidate subsets are selected from a reference set of 16 GCMs. An additional subset based on subjective expert judgement is also analysed. The representativeness of the three subsets is validated (with respect to the reference set) and compared for future changes in temperature, precipitation and Palmer drought index Z (direct validation), and occurrence of the European corn borer and snow-cover characteristics implemented in the CLIMSAVE Integrated Assessment Platform (indirect validation). The direct validation indicates that one of the objective-based subsets (ECHAM5/MPI-OM, CSIRO-Mk3.0, HadGEM1, GFDL-CM2.1 and IPSL-CM4 models) provides the best choice for the Europe-wide climate change impact study. Its performance is balanced between regions, seasons and validation statistics. However, the expert-judgement-based subset achieved slightly better results in the indirect validation. The differences between the subsets and the reference set are generally much lower for the impact indices compared to their mean (across all GCMs in the subset) changes due to projected climate change. The ranking of the candidate subsets differs between regions, climatic characteristics and seasons, demonstrating that the subset suitability for a specific impact study depends on the target region and the roles of individual seasons and/or climatic variables on the processes being studied. [ABSTRACT FROM AUTHOR]

Studies on persistence are important for the clarification of statistical properties of the analyzed time series and for understanding the dynamics of the systems which create these series. In climatology, the analysis of the autocorrelation function has been the main tool to investigate the persistence of a time series. In this paper, we propose to use a more sophisticated econometric instrument. Using this tool, we obtain an estimate of the persistence in global land and ocean and hemispheric temperature time series. [ABSTRACT FROM AUTHOR]

The arid region of northwest China is a large area with complex topography. Hydrological research is limited by scarcity and uneven distribution of rain gauges. Satellite precipitation products provide wide coverage and high spatial-temporal resolutions, but the accuracy needs to be evaluated before application. In this paper, the reliability of four satellite precipitation products (CMORPH [Climate Prediction Center's morphing technique], PERSIANN [Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks], TRMM [Tropical Rainfall Measuring Mission] 3B42, and TRMM 3B43) were evaluated through comparison with ground data or reported values on daily, monthly, and annual scales from 2003 to 2010. Indices including frequency bias index, probability of detection, and false alarm ratio were used to evaluate recorded precipitation occurrences; relative mean bias, the correlation coefficient, and the Nash coefficient were used to assess precipitation amount. Satellite precipitation products were more accurate in the warm than in the cold season, and performed better in northern Xinjiang than in other regions during the cold season. CMORPH and PERSIANN tended to overestimate precipitation. TRMM 3B42 and TRMM 3B43 performed best because the former most accurately detected precipitation occurrences on a daily scale, and both produced accurate space-time distribution of precipitation and the best consistency with rain gauge observations. Only a few monthly precipitation values for TRMM 3B42 and TRMM 3B43, and annual precipitation values for TRMM 3B42 were with satisfactory precision. TRMM3B42 and TRMM 3B43 are therefore recommended, but correction will be needed before application. Factors including elevation, relative relief, longitude, and latitude had significant effects on the performance of satellite precipitation products, and these factors may be helpful in correcting satellite precipitation. [ABSTRACT FROM AUTHOR]

In this paper we use sea surface height (SSH) derived from satellite altimetry and an analytical linear equatorial wave model to interpret the evolution of the Indian Ocean Dipole (IOD) in the framework of recharge oscillator theory. The specific question we address is whether heat content in the equatorial band, for which SSH is a proxy, is a predictor of IOD development as it is for El Niño and the Southern Oscillation (ENSO) in the Pacific. We find that, as in the Pacific, there are zonally coherent changes in heat content along the equator prior to the onset of IOD events. These changes in heat content are modulated by wind-forced westward propagating Rossby waves in the latitude band 5°-10°S, which at the western boundary reflect into Kelvin waves trapped to the equator. The biennial character of the IOD is affected by this cycling of wave energy between 5° and 10°S and the equator. Heat content changes are a weaker leading indicator of IOD sea surface temperature anomaly development than is the case for ENSO in the Pacific though because other factors are at work in generating IOD variability, one of which is ENSO forcing itself through changes in the Walker Circulation. [ABSTRACT FROM AUTHOR]

Local dry/wet conditions and extreme rainfall events are of great concern in regional water resource and disaster risk management. Extensive studies have been carried out to investigate the change of dry/wet conditions and the adaptive responses to extreme rainfall events within the context of climate change. However, applicable tools and their usefulness are still not sufficiently studied, and in Hunan Province, a major grain-producing area in China that has been frequently hit by flood and drought, relevant research is even more limited. This paper investigates the spatiotemporal variation of dry/wet conditions and their annual/seasonal trends in Hunan with the standardized precipitation index (SPI) at various time scales. Furthermore, to verify the potential usefulness of SPI for drought/flood monitoring, the correlation between river discharge and SPI at multiple time scales was examined, and the relation between extreme SPI and the occurrence of historical drought/flood events is explored. The results indicate that the upper reaches of the major rivers in Hunan Province have experienced more dry years than the middle and lower reaches over the past 57 years, and the region shows a trend of becoming drier in the spring and autumn seasons and wetter in the summer and winter seasons. We also found a strong correlation between river discharge and SPI series, with the maximum correlation coefficient occurred at the time scale of 2 months. SPI at different time scales may vary in its usefulness in drought/flood monitoring, and this highlights the need for a comprehensive consideration of various time scales when SPI is employed to monitor droughts and floods. [ABSTRACT FROM AUTHOR]

In this article, the development and operationalisation of forestry-wood chain indicators within the frame of sustainability impact assessment are discussed. The analytical framework follows a distinction between indicator definition and selection in a first phase, and a second operational phase of indicator application in terms of interconnecting material flows, calculation of chain performance and utilisation within evaluation components. A clear boundary drawing effort in terms of the development of indicator definitions, related subclasses, and measurement units as well as the creation of conversion factors between indicator values and individual chain stages supports this. Economic, social and environmental indicators have to respond to data collection needs on individual process levels (that correspond to sub-divisions of the forestry-wood chain). For the usage of indicators within evaluation tools, a functional hierarchy has to be provided that supports clear preference elicitation as well as information on related externalities. In total, this paper aims at demonstrating an enhanced spectrum in the use of sustainability indicators, and the challenges that arise from a developing and applying multi-functional indicators in sustainability impact assessment. [ABSTRACT FROM AUTHOR]

Despite common acknowledgement of the value of protected areas as instruments in ensuring sustainability, and their promotion for the achievement of policies on halting the loss of biodiversity, there is no common approach today for monitoring and evaluating them. This paper presents a novel integrated nature conservation management procedure developed to monitor and evaluate the sustainability of Mediterranean protected areas. This procedure was successfully implemented and formally evaluated by protected area managers in six Mediterranean countries, results of which are presented here together with an overview of the web-based Decision Support System (DSS) developed to facilitate its wide adoption. The DSS and procedure has been designed and evaluated by managers as a useful tool, which facilitates and provides needed procedural guidance for protected area monitoring whilst minimizing input requirements to do so. The procedure and DSS were developed following a review of existing protected area assessment tools and a detailed primary investigation of the needs and capacity of its intended users. Essentially, the procedure and DSS guides provide the facilities for protected area managers, in following a participatory approach to develop a context-specific sustainability monitoring strategy, for their protected area. Consequently, the procedure is, by design, participatory, context specific, holistic and relevant to protected area management and institutional procedures. The procedure was piloted and formally evaluated in Greece, Italy, Turkey, Egypt, Malta and Cyprus. Feedback collected from the pilot evaluations is also summarised herein. [ABSTRACT FROM AUTHOR]