Search

A well-documented, publicly available, global data set of surface ocean carbon dioxide (CO2) parameters has been called for by international groups for nearly two decades. The Surface Ocean CO2 Atlas (SOCAT) project was initiated by the international marine carbon science community in 2007 with the aim of providing a comprehensive, publicly available, regularly updated, global data set of marine surface CO2, which had been subject to quality control (QC). Many additional CO2 data, not yet made public via the Carbon Dioxide Information Analysis Center (CDIAC), were retrieved from data originators, public websites and other data centres. All data were put in a uniform format following a strict protocol. Quality control was carried out according to clearly defined criteria. Regional specialists performed the quality control, using state-of-the-art web-based tools, specially developed for accomplishing this global team effort. SOCAT version 1.5 was made public in September 2011 and holds 6.3 million quality controlled surface CO2 data points from the global oceans and coastal seas, spanning four decades (1968–2007). Three types of data products are available: individual cruise files, a merged complete data set and gridded products. With the rapid expansion of marine CO2 data collection and the importance of quantifying net global oceanic CO2 uptake and its changes, sustained data synthesis and data access are priorities.

As a response to public demand for a well-documented, quality controlled, publically available, global surface ocean carbon dioxide (CO2) data set, the international marine carbon science community developed the Surface Ocean CO2 Atlas (SOCAT). The first SOCAT product is a collection of 6.3 million quality controlled surface CO2 data from the global oceans and coastal seas, spanning four decades (1968–2007). The SOCAT gridded data presented here is the second data product to come from the SOCAT project. Recognizing that some groups may have trouble working with millions of measurements, the SOCAT gridded product was generated to provide a robust, regularly spaced CO2 fugacity (fCO2) product with minimal spatial and temporal interpolation, which should be easier to work with for many applications. Gridded SOCAT is rich with information that has not been fully explored yet (e.g., regional differences in the seasonal cycles), but also contains biases and limitations that the user needs to recognize and address (e.g., local influences on values in some coastal regions).

A vast range of research applications in biodiversity sciences requires integrating primary species, genetic, or ecosystem data with other environmental data. This integration requires a consideration of the spatial and temporal scale appropriate for the data and processes in question. But a versatile and scale flexible environmental annotation of biodiversity data remains constrained by technical hurdles. Existing tools have streamlined the intersection of occurrence records with gridded environmental data but have remained limited in their ability to address a range of spatial and temporal grains, especially for large datasets. We present the Spatiotemporal Observation Annotation Tool (STOAT), a cloud-based toolbox for flexible biodiversity-environment annotations. STOAT is optimized for large biodiversity datasets and allows user-specified spatial and temporal resolution and buffering in support of environmental characterizations that account for the uncertainty and scale of data and of relevant processes. The tool offers these services for a growing set of near global, remotely sensed, or modeled environmental data, including Landsat, MODIS, EarthEnv, and CHELSA. STOAT includes a user-friendly, web-based dashboard that provides tools for annotation task management and result visualization, linked to Map of Life, and a dedicated R package (rstoat) for programmatic access. We demonstrate STOAT functionality with several examples that illustrate phenological variation and spatial and temporal scale dependence of environmental characteristics of birds at a continental scale. We expect STOAT to facilitate broader exploration and assessment of the scale dependence of observations and processes in ecology., Competing Interests: The authors have declared that no competing interests exist.

Topographic variation underpins a myriad of patterns and processes in hydrology, climatology, geography and ecology and is key to understanding the variation of life on the planet. A fully standardized and global multivariate product of different terrain features has the potential to support many large-scale research applications, however to date, such datasets are unavailable. Here we used the digital elevation model products of global 250 m GMTED2010 and near-global 90 m SRTM4.1dev to derive a suite of topographic variables: elevation, slope, aspect, eastness, northness, roughness, terrain roughness index, topographic position index, vector ruggedness measure, profile/tangential curvature, first/second order partial derivative, and 10 geomorphological landform classes. We aggregated each variable to 1, 5, 10, 50 and 100 km spatial grains using several aggregation approaches. While a cross-correlation underlines the high similarity of many variables, a more detailed view in four mountain regions reveals local differences, as well as scale variations in the aggregated variables at different spatial grains. All newly-developed variables are available for download at Data Citation 1 and for download and visualization at http://www.earthenv.org/topography.

Possibilities of the assessment of a landscape with the use of succession development stages, monitored with the value of the Mean Individual Biomass (MIB) of carabid beetles and the occurrence of bird species are discussed on the basis of an example from Poland. Higher variability of the MIB value in space signifies a greater biodiversity. Apart from the variability of MIB, it is suggested to adopt the occurrence of the following animals as indicators, (in the order of importance), representing underlying valuable landscapes: black stork, lesser spotted eagle, white-tailed eagle, wolf, crane and white stork. The higher number of these species and their greater density indicate a higher value of the landscape for biodiversity and ecosystem services, especially carbon sequestration. All these indicators may be useful to assess measures for sustainable land use.

The aim of the study was to estimate cardiovascular diseases risk based on the concentration of total blood cholesterol, HDL-cholesterol, triglycerides, glucose, C-reactive protein determined by high sensitivity assay and platelet count. The study was carried out in a group of healthy professionally active policemen in the Lodz region. The significant factors of atherosclerosis are: life style including diet and physical activity. Policeman profession requires a greater physical activity and good physical condition. The study group consisted of 836 policemen aged 31-63 years, mean 43,5 +/- 4,9 years. The mean value of total cholesterol was 217,7 mg/dl (69% > 200 mg/dl), cholesterol HDL--53,6 mg/dl (8% < 40 mg/dl), TG--168,8 mg/dl (47% > 150 mg/dl), CRP--1,95 mg/l (median 1,30 mg/l), 19,3% > 3 mg/l, a 7,4% > 5 mg/l, glucose--92,6 mg/dl (median 91 mg/dl), 7,2% > or = 110 mg/dl, a 20% > or = 100 mg/dl. The platelet count was 245,8 (median 244 x 103/microl), 99% < 350 x 103/microl. The concentration of lipids parameters is similar both for population of Lodz region and another population. In respect to proper values of the total cholesterol and HDL-cholesterol observed for Polish population including Lodz, the number of people with abnormal values is lower. The contrary tendency concerns to triglycerides.

This paper presents a modular approach to motion control using a microconlroller-based stepper motor driver. As an application of the driver, an inexpensive and portable one-dimensional robot was built to automate an existing experimental setup for measurement of adsorption isotherms using the McBain-Bakr technique. Automatic recording of position versus time yields data for the sludy of adsorption/desorption dynamics.