Citizen science networks in natural history and the collective validation of biodiversity data

Biodiversity data are in increasing demand to inform policy and management. A substantial portion of these data is generated in citizen science networks. To ensure the quality of biodiversity data, standards and criteria for validation have been put in place. We used interviews and document analysis from the United Kingdom and The Netherlands to examine how data validation serves as a point of connection between the diverse people and practices in natural history citizen science networks. We found that rather than a unidirectional imposition of standards, validation was performed collectively. Specifically, it was enacted in ongoing circulations of biodiversity records between recorders and validators as they jointly negotiated the biodiversity that was observed and the validity of the records. These collective validation practices contributed to the citizen science character or natural history networks and tied these networks together. However, when biodiversity records were included in biodiversity‐information initiatives on different policy levels and scales, the circulation of records diminished. These initiatives took on a more extractive mode of data use. Validation ceased to be collective with important consequences for the natural history networks involved and citizen science more generally.     

HYDROLOGIC AND HYDRAULIC RESEARCH IN MOUNTAIN RWERS1

ABSTRACT: Although our current (1990) knowledge of hydrologic and hydraulic processes is based on many years of study, there are river environments where these processes are complex and poorly understood. One of these environments is in mountainous areas, which cover about 25 percent of the United States. Use of conventional hydrologic and hydraulic techniques in mountain-river environments may produce erroneous results and interpretations in a wide spectrum of water-resources investigations. An ongoing U.S. Geological Survey research project is being conducted to improve the understanding of hydrologic and hydraulic processes of mountainous areas and to improve the results of subsequent hydrologic investigations. Future hydrologic and hydraulic research needs in mountainous areas are identified.     

CONFLICTING PERSPECTWES ABOUT DETECTION LIMITS AND ABOUT THE CENSORING OF ENVIRONMENTAL DATA1

ABSTRACT: Current conventions for reporting analytical results from environmental samples brings the objectives of laboratory scientists into conflict with those of environmental scientists. The objective of chemical analyses is to provide estimates of the true composition of samples. Reported results must reflect the analytical uncertainty. Current conventions require left-censoring of those results below the Limit of Detection. The objective of statistical interpretation of environmental data is to provide estimates of the characteristics of ecosystems. Such statistical analyses are often confounded by left-censoring of analytical results. We review the different points of view and propose a compromise which recognizes these conflicting perspectives.     

IDENTIFICATION OF AQUIFER DISPERSIVITIES: METHODS OF ANALYSIS AND PARAMETER UNCERTAINTY1

ABSTRACT: This paper presents a method for estimating aquifer dispersivities in solute transport models. Sensitivity equations are derived for the calculation of sensitivity coefficients. A modified Gauss-Newton algorithm is used to perform the least-squares minimization. A statistical procedure is outlined to assess reliability of the estimated parameters. The solute transport model is solved by the upstream weighted, multiple cell balance method which combines the concepts of local mass balance and finite element approximations. A one-dimensional solute transport problem in a vertical column system is first used to illustrate the inverse technique. A second example considers the parameter identification problem for three-dimensional solute transport with a unidirectional steady and uniform flow field. The third example solves the parameter identification problem in a three-dimensional, stream-aquifer, solute transport system with steady state flow. Numerical experiments are conducted to study data requirements for parameter identification.     

DEVELOPMENT OF EARTH SATELLITE TECHNOLOGY FOR THE TELEMETRY OF HYDROLOGIC DATA1

ABSTRACT The use of satellite telemetry is playing a major role in the collection of hydrologic data. Advancing technology and availability of government satellites have permitted many agencies to take advantage of new procedures for acquiring data from automated remote data collection stations. Experiments with Earth satellite technology started in the 1960's and 1970's, with the polar-orbiting National Aeronautics and Space Administration Nimbus and Landsat satellites. Subsequent advancements took place through the development phase to operational systems using the Geostationary Operational Environmental Satellite (GOES) of the National Oceanic and Atmospheric Administration. This satellite system supports more than 2,500 active telemetry sites, of which approximately 1,200 are Geological Survey stream-gaging stations for the collection of hydrologic data. A satellite data collection system is made up of three primary components; a small battery-operated radio, and Earth-orbiting satellite, and an Earth receive and data processing station. The data relay satellites' vast aerial view of the Earth's surface gives satellite telemetry a large advantage over ground-based systems for the collection of real-time hydrologic data for flood warning, reservoir management, irrigation water control, hydropower generation, and the operation of hydrologic stations.     

淮南市防震减灾决策系统的建立

在机制上将一个地市(淮南市)的地震预报与防震决策融为一个动态整体,从而建立起一个实用性强的防震减灾决策系统,使城市各种防震对策的生成有了更科学的基础。成为市政府在防震减灾决策中不可缺少的工具。     

Estimation of Cumulative Frequency Distribution for Carbon Monoxide Concentration from Wind-Speed Data, in Buenos Aires (Argentina)

In this article we apply and test a methodology to estimate cumulative frequency distribution for air pollutant concentration from wind-speed data. We use the inverse relationship after Simpson et al. (Atmospheric Environment, 19, 75–82, 1985) between the opposing percentile values in the statistical distributions for air pollutant concentrations and wind-speed data. This relationship is valid, irrespective of the statistical distributions of both variables, if an inverse relationship between them is also applicable. The available data are five years of 8-h average carbon monoxide concentration and 8-h mean wind-speed, observed in Buenos Aires (Argentina). The performance of the obtained empirical expressions in estimating cumulative frequency distributions for 8-h CO is statistically evaluated. The results show that it is possible to obtain an acceptable cumulative frequency distribution for 8-h CO concentration at the site if the cumulative frequency distribution for wind-speed is known. Q–Q plots show a good agreement between estimated and observed values. From our data, the mean relative error of the estimations was found to be as much as 8.0%.     

Potential and Shortcomings of Numerical Weather Prediction Models in Providing Meteorological Data for Urban Air Pollution Forecasting

The last decade progress in numericalweather prediction (NWP) modelling and studies of urbanatmospheric processes for providing meteorological data forurban air pollution forecasting is analysed on examples ofseveral European meteorological centres. Modern nested NWP models are utilising land-use databasesdown to 1 km resolution or finer, and are approaching thenecessary horizontal and vertical resolution suitable forcity scale. The recent scientific developments in the fieldof urban atmospheric physics and the growing availabilityof high-resolution urban surface characteristics datapromise further improvements of the capability of NWPmodels for this aim. A strategy to improve NWP data forthe urban air pollution forecasting is suggested.     

SUBWATERSHED SPATIAL ANALYSIS TOOL: DISCRETIZATION OF A DISTRIBUTED HYDROLOGIC MODEL BY STATISTICAL CRITERIA1

ABSTRACT: Complex hydrologic models, designed for simulating larger watersheds, require a huge amount of input data. Most of these models use spatially distributed data as inputs. Spatial data can be aggregated or disaggregated for use as input to a model, which can impact model outputs. Although, it is efficient to minimize data redundancy by aggregating the spatial data, upscaling reduces the detail/resolution of input information and increases model uncertainty. On the other hand, a large number of model inputs with high degrees of disaggregation take more computer time and space to process. Hence, a balance between striving for a maximum level of aggregation and a minimum level of information loss has to be achieved. This study presents a definition of an appropriate level of discretization, derived by establishing a relationship between a model's efficiency and the number of subwater‐sheds modeled. An entropy based statistical approach/tool called Subwatershed Spatial Analysis Tool (SUSAT) was developed to find an objective choice of an appropriate level of discretization. The new approach/tool was applied to three watersheds, each representing different hydrologic conditions, using a hydrologic model. Coefficients of efficiency and entropy estimated at different levels of discretization were used to validate the success of the new approach.