Changes In Index Values Research Articles

CitarumView: A Google Earth Engine–based application for Citarum River monitoring

The Citarum River is a vital waterway in West Java, Indonesia, that sustains life along its sub-watershed. However, the river is facing significant environmental challenges, such as deforestation, and land-use changes, which have led to a decline in its ecosystem quality. To address this issue, the study aimed to develop an application called “CitarumView” that uses remote sensing methods to assess changes in index values focused on the condition of vegetation, built-up, soil moisture, water body, and surface temperature and obtain a description of the Citarum watershed condition in 2019 and 2020. The Google Earth Engine was used to collect and process satellite imagery data, including visual bands B4 (red), B3 (green), B2 (blue), Near-infrared (NIR), thermal infrared (B10 Landsat-8), and short-wave infrared (SWIR), from Sentinel-2 and Landsat-8 satellites. The CitarumView application provides a tool for decision-makers, researchers, and the general public to continuously monitor the river’s condition. The application also provides information on the changes in the ecosystem quality over time, allowing for more informed decisions to be made concerning river management. The analysis conducted using CitarumView revealed that the average of vegetation index increased by 6% with low to mid vegetation level, the max of water index increased by 4.5%, the average of moisture index increased by 39% with mid canopy water, the average of built-up index decreased by 28%, the average of soil adjusted vegetation index increased by 12% with mid to high vegetation, and the average of surface temperature decreased by 5% for 2019-2020.

Effect of a Combined Cognitive and Vocational Intervention on Change in HRQoL after TBI

<h3>Research Objectives</h3> To compare the effect of a combined cognitive and vocational intervention to treatment as usual (TAU) on change in health-related quality of life (HRQoL) after mild-to-moderate traumatic brain injury (TBI). <h3>Design</h3> Randomized controlled trial. <h3>Setting</h3> Specialized TBI outpatient clinic at Oslo University Hospital, Norway. <h3>Participants</h3> 116 patients aged 18-60 years with mild-to-moderate TBI were recruited 8-12 weeks post injury and randomized to the study intervention (n=60) or TAU (n=56). The participants' mean age was 42 years (SD 9.8) and 60% (n = 69) were female. Injury severity was mild in 94% of cases and the most frequent cause of injury were falls (43%). <h3>Interventions</h3> Compensatory Cognitive Training (CCT) and Supported Employment (SE) or multidisciplinary TAU provided for a maximum of six months. <h3>Main Outcome Measures</h3> HRQoL assessed at baseline, 3, 6 and 12 months using the 5-level EQ-5D version (EQ-5D-5L). EQ-5D-5L scores were converted into an index value ranging from 1 (full health) to 0 (worst possible health) using the Danish value set. <h3>Results</h3> At baseline, the mean (SD) EQ-5D-5L index values were 0.65 (0.15) for CCT-SE and 0.71 (0.12) for TAU. At 3 months, the index values were 0.71 (0.13) for CCT-SE and 0.75 (0.11) for TAU. At 6 months, the index value was 0.74 (0.15) for CCT-SE and 0.75 (0.16) for TAU. At 12 months, the index value was 0.76 (0.13) for CCT-SE and 0.78 (0.15) for TAU. Change in index value from baseline to 12 months was 0.11 in CCT-SE and 0.07 in the TAU group. <h3>Conclusions</h3> The CCT-SE intervention was associated with a greater improvement in HRQoL over 12 months when compared to TAU with improvement in the range of previously reported minimum clinically important difference for EQ-5D. <h3>Author(s) Disclosures</h3> The authors report no conflicts of interest.

Identifying Western North American Tree Populations Vulnerable to Drought under Observed and Projected Climate Change

Global climate change has affected forest health and productivity. A highly visible, direct climate impact is dieback caused by drought periods in moisture-limited forest ecosystems. Here, we have used a climate moisture index (CMI), which has been developed in order to map forest–grassland transitions, to investigate the shifts of the zero-CMI isopleths, in order to infer drought vulnerabilities. Our main objective was to identify populations of the 24 most common western North American forest tree species that are most exposed to drought conditions by using a western North American forest inventory database with 55,700 plot locations. We have found that climate change projections primarily increase the water deficits for tree populations that are already in vulnerable positions. In order to test the realism of this vulnerability assessment, we have compared the observed population dieback with changes in index values between the 1961–1990 reference period and a recent 1991–2020 average. The drought impacts that were predicted by negative CMI values largely conformed to the observed dieback in Pinus edulis, Populus tremuloides, and Pinus ponderosa. However, there was one notable counter-example. The observed dieback in the Canadian populations of Populus tremuloides were not associated with directional trends in the drought index values but were instead caused by a rare extreme drought event that was not apparently linked to directional climate change. Nevertheless, a macro-climatic drought index approach appeared to be generally suitable to identify and forecast the drought threats to the tree populations.

Application of Artificial Neural Network Technology for Prediction of Sunflower Harvest Losses

Introduction The current stage of economic development is characterized by digitalization. Digital technologies in crop production occupy leading positions in agrocybernetics. The digitalization of society has brought to the fore new methods of studying development processes, among which a significant role is played by deep learning and its most successful methods such as artificial neural networks. “Artificial neural networks (ANNs) have gained popularity an effective tool for offering solutions to a wide variety of different case studies of biological and agricultural background. Their effectiveness emanates from their ability to model complex relationships between observation data from sensors and predicted variables without relying on assumptions about the model structure hence they can predict the real nature of the nonlinear relation between input and output data.” Yield prediction is a major challenge in precision agriculture, closely associated to the adoption of best management practices, crop pricing and security. Various techniques and methodologies have been developed to predict crop yield in agriculture. Yield forecasting requires control of many parameters, including Moisture Content pH, Soil Organic Matter, Total Nitrogen and Organic Carbon, which complicates the forecasting process . The purpose of the paper. The purpose of this paper is to find out and substantiate the possibility of predicting the probable loss of the sunflower crop by the farmer based on the analysis of the distribution of the vegetation index in the field. Our hypothesis is that the distribution of the vegetation index significantly affects the percentage of losses, of course, with additional parameters. Results. The influence of parameters that characterize the harvest on its losses is, but a clear regression relationship can not be built. Therefore, the technology of artificial neural networks is used to build the model. The model is formed in the form of an algorithm at the input of which input parameters are given (value of vegetation index at the beginning of the study, change of index value during the study period, seed moisture in the accounting area, percentage of study area from field area), at the output we get the percentage of possible crop losses. The algorithm is automatically translated into a program in the C ++ programming language (or another programming language), which allows in practice to model the farmer's possible crop losses depending on his actions in relation to growing crops. Keywords: sunflower, machine learning, artificial neural networks, forecast model.

PSXI-20 Satellite analysis and monitoring of rangelands of the Republic of Kazakhstan

Abstract Kazakhstan ranks 5th in the world in terms of pasture area, with 30% of land used as pasture. Evaluating pasture resources is relevant for improving the pasture lands regulation system. Since 2018, National Space Agency has carried out the Ministry of Agriculture space pastures monitoring program. The main task is a seasonal satellite evaluation of the degradation productivity degree pasture vegetation. Thematic analysis remote sensing data from KazEOSat-1, 2 satellites and territory geoinformation made it possible to determine, with a high accuracy: land boundaries and areas, seasonal state and average vegetation type pastures productivity evaluation, integration with land cadastre data identified unaccounted pastures, and animal identification system made it possible to assess pastures load. Seasonal state pastures evaluation done by satellite parameter choice. The main factor influencing vegetation spectral properties is biomass increase. Spectral reflectance decreases in spectrum’s red part and near-IR range increases, vegetation index value changes. The vegetation index was used to create correct linear weighing system: vegetation parameters values (the green plant biomass volume projective leaf cover of the soil). To calculate seasonal productivity, GNDVI vegetation index used to more chlorophyll concentration than NDVI index. GNDVI showed best correlation calculating productivity, concidering exposed soil atmosphere influence. Satellite evaluation showed digital maps (pasture.gharysh.kz). The area was counted according to condition degradation and productivity. In Karaganda region’s Zhanaarkinsky district brown soils are widespread, with little humus, natural and man-made desertification is observed. The minimum productivity of pastures was 0–3 c / ha, average - 7.7 c / ha, maximum - 12–15 c / ha. In 2020, 73% (4,364.0 thousand hectares) pastures were poor assessed, 18.4% (1,104.3 thousand hectares) - very poor. The reason is the location in the desert and semi-desert zones, the annual rainfall is 150 mm. Degraded pastures in 2020 amounted to 449.1 thousand hectares (93.8% degradation of a low degree, 5.8% of a medium degree, 0.4% of a strong degree).

Developing Digital Economy and Society in the Light of the Issue of Digital Convergence of the Markets in the European Union Countries

The main objective of the paper is to present the development of digital economy and society in the Countries of the European Union in the light of the digital convergence of these markets. The analysis was based on the data on the Digital Economy and Society Index (DESI) from 2015 and 2020. Empirical studies have been conducted in two stages. First, basic measures of time series dynamics were used to determine the dynamics of changes in index values. On the other hand, in order to classify countries in terms of similarity of value and structure of the DESI, a cluster analysis was used as one of the basic methods of the so-called unsupervised statistical grouping. The studies presented confirm that the levels of indicators and the dynamics of changes in their value at the level of the synthetic DESI indicator, and in the five underlying areas of analysis, vary despite the fact that almost all are pro-growth, including for isolated clusters of EU-28 countries. When analyzing the DESI synthetic index and its components, it was concluded that there is generally an increase in convergence between the EU-28 countries in terms of the level of development of the digital economy and society, as well as in four components: Connectivity, Human Capital, Use of Internet Services and Digital Public Services. The Integration of Digital Technology area was the only one where increasing polarization of results was observed. The added value of the paper is to fill the research gap in research on the digital convergence of markets in the Countries of the European Union.

Insights on expected streamflow response to land-cover restoration

Ecosystem service approaches to watershed management have grown quickly, increasing the importance of understanding the streamflow response to realistic land-cover change. Previous work has investigated the relationship between watershed characteristics and streamflow in catchments around the world, but little has focused on systematic relationships between watershed characteristics and streamflow change after land-cover restoration. To address this gap, we simulate streamflow responses to restoring 10% of watershed area from agricultural land to forest and natural pasture in 29 watersheds around the world. This change is consistent with that performed in watershed-service programs. We calculate the change in a broad array of streamflow indices for each site and use a graph-connectedness approach to cluster the sites based on the sign of the index value changes. We find three primary clusters with distinct responses to restoration. Permutation tests and effect sizes demonstrate the difference in watershed characteristics and streamflow indices across clusters. The low-flow intensifying sites have shallower soils and smaller saturated soil volumes. After restoration, simulated streamflow in these sites increases during relatively dry periods and declines during high-flow periods. The high-flow intensifying sites have larger saturated soil volumes. After restoration, simulated dry-season flow in these sites decreases. The high-flow enhancing sites have larger soil hydraulic conductivities than the high-flow intensifying sites. After restoration, simulated dry-season flow in these sites decreases less than in high-flow intensifying sites. The soil depth and hydraulic conductivity appear to be the characteristics that determine clusters, as clusters are not statistically related to climate, watershed location, proximity, size and shape, elevation, or pre-existing land cover. This study provides valuable understanding of land-cover restoration and the watershed characteristics that most impact streamflow change.

Ecoacoustics in the rain: understanding acoustic indices under the most common geophonic source in tropical rainforests

AbstractRainfall is one of the most predominant geophonic sources in nature, and the major climatic phenomenon influencing species biology in tropical ecosystems. Although its effects on acoustic indices have been studied, rainfall is recognized as a nuisance factor affecting their estimation. Consequently, files with rainfall sounds are typically removed from ecoacoustic analyses. In tropical rainforests, where rainfall is a common and unpredictable event, its influence on acoustic indices needs to be explicitly examined before implementing acoustic passive monitoring. Using mixed‐effects models we assessed the effect of different rainfall conditions on the direction and magnitude of the values of eight commonly used acoustic indices. We obtained 18336 1‐min recordings from 28 sampling sites in a montane forest on the northern Andes of Colombia between May‐July 2018. We identified 2867 1‐min recordings containing light to heavy rainfall. We found that both rainfall occurrence and its variation in intensity were associated with increases in ACI, ADI, H, and M index values, and decreases in AEI, BI, NDSI, and NP values. The estimated indices exhibited differential sensitivity to rainfall, with M, NDSI, and NP showing higher differences associated with increasing frequency and intensity of rainfall. Regardless the direction of change in index values caused by rainfall, we found that the magnitude of variation depended on the index. For instance, ACI and BI indices showed low sensitivity and can be considered as reliable acoustic metrics, even during heavy intensity rainfall. In contrast, M, NDSI, and NP might lead to misleading inferences, if rainfall events are not considered during calculation. We stress the importance of careful interpretation of biological inferences based on these sensitive indices and encourage an explicit assessment of rainfall, particularly in short‐term acoustic surveys in highly pluvious regions where rainfall is a conspicuous component of the soundscape.

Text-Mining in Streams of Textual Data Using Time Series Applied to Stock Market

Each day, a lot of text data is generated. This data comes from various sources and may contain valuable information. In this article, we use text mining methods to discover if there is a connection between news articles and changes of the S&amp;P 500 stock index. The index values and documents were divided into time windows according to the direction of the index value changes. We achieved a classification accuracy of 65–74 %.

Contribution of humic substances to dissolved organic matter optical properties and iron mobilization

Humic substances (HS) are the primary constituents of dissolved organic matter (DOM) and play pivotal roles in aquatic systems. Optical indices of DOM, such as specific UV absorbance (SUVA254), the fluorescence index (FI) and biological index (BIX), have gained wide interest because of their ease of use. In this study, we explored the relationship between HS and the indices in the Trat River Basin (eastern Thailand) from headwaters to the river mouth through the distinct dry and rainy seasons to examine whether changes in index values reflect variability in the relative contribution of HS to DOM, or %HS. The results show that %HS and the indices did not exhibit significant linear relationships (FI and BIX, P > 0.05), or the relationships changed seasonally (SUVA254). However, analyzing the indices versus %HS did show clear DOM composition changes by season with more humic-like or terrestrial material in the rainy season. Relationships between DOM and dissolved iron (dFe) concentrations were also explored. Separating the relationships of DOM versus dFe into HS versus dFe and non-HS versus dFe provides us the opportunity to better understand which fraction contributes more to dFe mobilization. The results indicate stronger positive linear relationships between HS and dFe concentrations independent of river tributary. Overall, this study highlights the importance of quantifying HS for the study of DOM dynamics or compositional changes along a river transect as well as for DOM-induced iron mobilization.

Natalizumab therapy is associated with changes in serum JC virus antibody indices over time

To examine changes in anti-JC Virus (JCV) index measurements over time in multiple sclerosis (MS) patients to better understand this test, which is used in assessing risk of progressive multifocal leukoencephalopathy (PML) with natalizumab. We aim to describe and compare seroconversion rates, variability of JCV antibody index values, and changes in index values over time between patients on natalizumab therapy and patients naïve to natalizumab. Anti-JCV index values are used to help decide whether to start, continue, or stop treatment. Assessing how index values vary over time is interpreted to allow a patient's risk of PML to be better characterized. Retrospective analysis was conducted using records of patients with multiple JCV antibody index measurements exposed to therapy with natalizumab (N=150) or not (N=145). Rates of seroconversion, variability of indices, and changes in index values over time were calculated and compared. Patients on natalizumab who were initially JCV antibody negative seroconverted at a significantly higher rate than patients naïve to natalizumab (23.9 vs. 9.1%, p<0.01). Variability of anti-JCV indices was also found to be significantly higher for patients on natalizumab (p<0.05). Patients on natalizumab additionally trended towards a larger increase in index values over time. Therapy with natalizumab was associated with higher rates of seroconversion and greater anti-JCV index variability, suggesting that therapy with natalizumab may influence this test used to assess risk of treatment with it.

A hydrologically sensitive invertebrate community index for New Zealand rivers

Identifying ecological response variables sensitive to hydrological change is a key step in determining the impacts of river flow alterations on aquatic ecosystems and in setting environmental flows that sustain certain ecological values. Building on the successful use of flow regime sensitive aquatic invertebrate indices in other countries, particularly the UK based Lotic Index for Flow Evaluation (LIFE), we provide two variants of a similar index for use in New Zealand (LIFENZ and a weighted variant: LIFENZ_W). As in the original LIFE, the New Zealand indices were based on water velocity preference categories assigned to aquatic invertebrate taxa using professional judgement. To calculate the indices a lookup table is used to assign a score to each taxon based on their velocity category and abundance. For the LIFENZ_W variant an additional step down weighted the scores if the taxon has a general compared to a more specific velocity preference. The two index variants were correlated with each other and to similar environmental parameters. Across a total of 74 sites, both indices were correlated with depth-averaged water velocity. Changes in index values, both between sites and temporally within sites, were predominantly associated with changes in hydrological parameters, such as the magnitude and length of time since a recent high flow, and to a lesser degree with other physico-chemical parameters. Commonly used indices in New Zealand designed to respond to nutrient enrichment (MCI and variants) were not correlated with local water velocity, but were correlated with antecedent flow conditions and were likely influenced by effects of flow stability on algal growth. Further testing of LIFENZ and LIFENZ_W in combination with MCI is recommended, particularly in rivers subject to more extreme hydrological and water quality stresses and with regard to other physical parameters such as hydraulic habitat. However, the LIFENZ and its weighted variant (LIFENZ_W) appear to be useful tools for understanding and managing the effects of hydrological alteration on aquatic invertebrate communities in New Zealand. As LIFENZ and LIFENZ_W were strongly correlated and only showed a relatively small deviation from a slope of 1 we recommend the use of the more straightforward LIFENZ in almost all circumstances.

Віталітетна структура та її динаміка у Quercus robur на початкових етапах онтогенезу

Наведено результати оцінювання віталітетної структури онтогенетичних субценопопуляцій ювенільних (j) та імматурних (im1 та im2) рослин Quercus robur L. у семи угрупованнях лісової рослинності Кролевецько-Глухівського геоботанічного району. Встановлено, що онтогенетичні субценопопуляції молодого покоління Q. robur, які формуються під наметом широколистяних лісів регіону, вирізняються високим рівнем різноманіття віталітетної структури та належністю до трьох якісних типів: процвітаючих, врівноважених і депресивних. Перехід до кожного наступного етапу розвитку (від j до im1, а також від im1 до im2) супроводжується проявом у молодого покоління Q. robur віталітетної пластичності (тобто зміни величин індексу Q) та, відповідно, віталітетної мінливості (зміни частки особин різних класів віталітету). Кількісні та якісні аспекти реалізації віталітетної пластичності оцінено з опорою на оригінальний показник – індекс віталітетної динаміки (IVD). У Q. robur на початкових фазах онтогенезу негативні зміни віталітетної структури відбуваються частіше, ніж позитивні. Вони здебільшого супроводжуються зниженням «якісного» статусу когорт. Установлено факти щодо віталітетної структури онтогенетичних субценопопуляцій ювенільних та імматурних (im1 та im2) рослин, які об’єктивно свідчать про ускладненість формування у фітоценозах за участі Q. robur безперервного потоку поколінь цього виду, та, відповідно, забезпечення стійкого та довготривалого існування його ценопопуляцій.

Workspace optimization for a planar cable-suspended direct-driven robot

Abstract The present work is inspired by an industrial task, i.e. spray painting a large area by means of a robotic system consisting in a Cable-Driven Parallel Robot (CDPR). In many cases, the area of the robot workspace is smaller than the area to be painted. For this reason, the base of the robot has to be shifted several times during the painting process. These robots are referred to as Repetitive Workspace Robots (RWR). In other words, in order to accomplish the whole task, they need to be moved after they have completed a sub-task locally. A cable suspended CDPR is an ideal candidate for such tasks; it can be thin, light, flexible and cost-efficient. The question is: which is the best shape of the local workspace in these conditions? In fact, not always a larger area of the local workspace guarantees an efficient painting process. This is because the efficiency relies mainly on the shape rather than on the local workspace area itself. In this work we employ an index [Seriani S, Gallina P, Gasparetto A, 2014] to evaluate the efficiency of the workspace of a 2-link CDPR. Finally, we show how the index value changes in relation to some geometrical parameters of the robot, thus laying the foundations for a general design methodology.

Relationship of IAD index to internal quality attributes of apples treated with 1-methylcyclopropene and stored in air or controlled atmospheres

The research was conducted to evaluate the relationship between IAD index (index of absorption difference between 670 and 720nm) values and internal quality attributes of apples treated with 1-methylcyclopropene (1-MCP) and stored in air and controlled atmospheres (CA). Apples of ‘8S6923’ (Aurora Golden Gala™), ‘Fuji’ and ‘Royal Gala’ were tested. The results with Aurora Golden Gala™ show that IAD index values were maintained at higher levels if the fruit were stored in CA and that 1-MCP had no significant effect on retaining at-harvest values. The IAD values correlated with chlorophyll a content in the peel (R2=0.95, P<0.0001), but not with chlorophyll b content, internal ethylene levels, firmness or titratable acidity. ‘Royal Gala’ apples showed a similar response to Aurora Golden Gala™ apples, showing no correlation between IAD index values and internal quality attributes of those apples when treated with 1-MCP and/or CA. In contrast, ‘Fuji’ apples showed a relationship between IAD index value changes and internal ethylene concentrations (R2=0.67, P<0.05) and titratable acidity changes (R2=0.89, P<0.01), but not firmness. These results suggest that when 1-MCP and/or CA are applied to apples after harvest, that IAD index values do not consistently correlate to any internal quality attributes other than peel chlorophyll a content.

Modeling the response time of diatom assemblages to simulated water quality improvement and degradation in running waters

The objective of this study was to measure and model the response time of the Eastern Canadian Diatom Index (IDEC: Indice Diatomées de l’Est du Canada), a diatom-based index of biological integrity, following substrate translocation from altered sites (nutrient-enriched) to pristine sites and vice-versa. The frequency of sampling, duration (time after substrate translocation), and variety of site conditions in the present study provide strong evidence for an accelerated response of diatoms to a degradation reflecting eutrophication (within a week in certain cases) and a slower path to recovery (up to 4 weeks). Diatom response varied as a function of trophic status; oligotrophic rivers responded rapidly to a degradation, and mesotrophic or eutrophic rivers responded more slowly to an amelioration of the conditions. Variation in response time as a function of trophic status seemed to be partly linked to the diversity and complexity of the assemblages. The less diverse assemblages observed in oligotrophic waters were highly sensitive to nutrient enrichment, whereas the more diverse assemblages sampled in mesotrophic–eutrophic rivers were less sensitive to nutrient fluctuations, and major variations in nutrient concentrations took a longer time to induce a change in index values.

Effects of CT Section Thickness and Reconstruction Kernel on Emphysema Quantification: Relationship to the Magnitude of the CT Emphysema Index

Computed tomography (CT) section thickness and reconstruction kernel each influence CT measurements of emphysema. This study was performed to assess whether their effects are related to the magnitude of the measurement. Low-radiation-dose multidetector CT was performed in 21 subjects representing a wide range of emphysema severity. Images were reconstructed using 20 different combinations of section thickness and reconstruction kernel. Emphysema index values were determined as the percentage of lung pixels having attenuation lower than multiple thresholds ranging from -960 HU to -890 HU. The index values obtained from the different thickness-kernel combinations were compared by repeated measures analysis of variance and Bland-Altman plots of mean versus difference in all subjects, and correlated with quantitative histology (mean linear intercept, Lm) in a subset of resected lung specimens. The effects of section thickness and reconstruction kernel on the emphysema index were significant (P < .001) and diminished as the index attenuation threshold was raised. The changes in index values from changing the thickness-kernel combination were largest for subjects with intermediate index values (10%-30%), and became progressively smaller for those with lower and higher index values. This pattern was consistent regardless of the thickness-kernel combinations compared and the HU threshold used. Correlations between the emphysema index values obtained with each thickness-kernel combination and Lm ranged from r = 0.55-0.68 (P = .007-.03). The effects of CT section thickness and kernel on emphysema index values varied systematically with the magnitude of the emphysema index. All reconstruction techniques provided significant correlations with quantitative histology.

Spot Natural Gas Prices: A Theoretical Party to Party Bargaining Framework

Whilst some regional energy markets appear to be integrating, modelling the pricing of natural gas exports in an imperfect global spot market remains a difficult task. For the sake of analysis, this paper proposes the expansion of a theoretical global party to party spot gas price bargaining model to capture lagged daily prices of the major competing fuels and values of a global economic indicator in the world stock market price index. Vector autoregressive based tests provide no evidence of cointegration, however tests of exogeneity show that gas prices and gas price changes are primarily influenced by oil prices and oil price changes. Within this framework, it is found that the oil price and oil price changes are influenced significantly by global stock price index values and index value changes and the coal price index values and index value changes. The model put forward is purely for preliminary analysis but it shows potential. All markets need to become larger, more globally integrated, more informationally efficient and mechanisms to arbitrage the various energy markets would need to be established before a final global gas spot price index is possible.

A linguistic communication measure for monitoring changes in Chinese aphasic narrative production

This study investigated the usefulness of the Cantonese Linguistic Communication Measure (CLCM) in monitoring changes of narrative production in five Chinese adults with aphasia in the period of spontaneous recovery (SR group) and four who underwent anomia therapies (Tx group). Language samples elicited from a picture description task were collected among SR participants at regular intervals within the first 6 months post‐onset and among Tx participants before and after treatment. Results showed that the CLCM indices could reflect changes of language production in these individuals over time. The changes of index values were consistent with the expectations of performance during early stages after stroke for the SR participants and treatment outcomes of the Tx participants. While the CLCM has previously been shown to be useful in measuring aphasic narratives on a single occasion, this study has provided further evidence of its capability to monitor changes of language production over time.

Can macroinvertebrate rapid bioassessment methods be used to assess river health during drought in south eastern Australian streams?

Summary Despite significant concern about drought impacts in Australia, there have been no broad‐scale studies of drought effects on river health. A severe and prolonged drought has been acting on many streams in south eastern Australia over the past decade. EPA Victoria has undertaken rapid bioassessment (RBA) of over 250 stream reference sites since 1990, providing an opportunity for a before‐after‐control‐impact investigation of drought related changes to macroinvertebrate indices and water quality. This study uses data from 1990 to 2004 to critically evaluate the effectiveness of using RBA methods and indices, which were designed for assessment of human impacts, for monitoring streams during drought. Reference stream sites across Victoria (those with minimal anthropogenic disturbances and repeatedly sampled) were classified as being ‘in drought’ or ‘not in drought’ using the Bureau of Meteorology’s rainfall deficiency definition. Four biological indices (SIGNAL, EPT, Family Richness and AUSRIVAS) were calculated for combined autumn and spring samples for edge and riffle habitats for the selected sites. General linear models and paired t‐tests were used to detect drought related changes to index and water quality values at state‐wide and bioregional scales. Changes in taxa constancy were examined to determine which taxa were sensitive to or benefited from drought conditions. Frequency of site failure against biological objectives specified in the State Environment Protection Policy (Waters of Victoria) (herein termed ‘SEPP WoV’) before and during drought was also examined to detect changes in a management context. Few significant changes in index values were detected for riffle habitat samples. Rates of failure against biological objectives were similar before and during drought for riffle samples. In contrast, edge habitat AUSRIVAS and SIGNAL scores were significantly reduced at the state‐wide scale and most indices showed significant declines in the lower altitude forests, and foothills and coastal plains bioregions. Generally, more pollution tolerant, lentic taxa replaced sensitive and flow‐requiring taxa in edge samples during drought. In contrast, there were few reductions in the taxa of riffle samples during drought. However, many pool preferring, but pollution sensitive taxa occurred more frequently in riffle areas. Hence, the riffle community began to resemble that of pools and edges. This was attributed to decreased flow and increased ‘lentic’ habitat opportunities in riffles. Detection of a drought effect was confined to the edge habitat and site failure could be assigned to drought and anthropogenic impacts, in conjunction or alone. The riffle sampling protocol was resistant to detection of drought effects as samples were only taken when sufficient water was present within this habitat. Therefore, biological changes at sites not meeting policy objectives for riffle habitats can be attributed to anthropogenic rather than drought impacts.