Part of the global DOC versus AOU (dissolved organic carbon/apparent oxygen utilization) data compilation, Southern Ocean

Recent evidence that dissolved organic carbon (DOC) is a significant component of the organic carbon flux below the photic layer of the ocean (1), together with verification of high respiration rates in the dark ocean (2), suggests that the downward flux of DOC may play a major role in supporting respiration there. Here we show, on the basis of examination of the relation between DOC and apparent oxygen utilization (AOU), that the DOC flux supports ~10% of the respiration in the dark ocean. The contribution of DOC to pelagic respiration below the surface mixed layer can be inferred from the relation between DOC and apparent oxygen utilization (AOU, µM O2), a variable quantifying the cumulative oxygen consumption since a water parcel was last in contact with the atmosphere. However, assessments of DOC/AOU relations have been limited to specific regions of the ocean (3, 4) and have not considered the global ocean. We assembled a large data set (N = 9824) of concurrent DOC and AOU observations collected in cruises conducted throughout the world's oceans (fig. S1, table S1) to examine the relative contribution of DOC to AOU and, therefore, respiration in the dark ocean. AOU increased from an average (±SE) 96.3 ± 2.0 µM at the base of the surface mixed layer (100 m) to 165.5 ± 4.3 µM at the bottom of the main thermocline (1000 m), with a parallel decline in the average DOC from 53.5 ± 0.2 to 43.4 ± 0.3 µM C (Fig. 1). In contrast, there is no significant decline in DOC with increasing depth beyond 1000 m depth (Fig. 1), indicating that DOC exported with overturning circulation plays a minor role in supporting respiration in the ocean interior (5). Assuming a molar respiratory quotient of 0.69, the decline in DOC accounts for 19.6 ± 0.4% of the AOU within the top 1000 m (Fig. 1). This estimate represents, however, an upper limit, because the correlation between DOC and AOU is partly due to mixing of DOC-rich warm surface waters with DOC-poor cold thermocline waters (6). Removal of this effect by regressing DOC against AOU and water temperature indicates that DOC supports only 8.4 ± 0.3% of the respiration in the mesopelagic waters.

The CLIMATE data base of monthly normals for globally gridded climatic variables (version 2.1)

This database (Leemans & Cramer 1991) contains monthly averages of mean temperature, temperature range, precipitation, rain days and sunshine hours for the terrestrial surface of the globe, gridded at 0.5 degree longitude/latitude resolution. All grd-files contain the same 62483 pixels in the same order, with 30' latitude and longitude resolution. The coordinates are in degree-decimals and indicate the SW corner of each pixel. Topography is from ETOPO5 and indicates modal elevation. Data were generated from a large data base, using the partial thin-plate splining algorithm (Hutchinson & Bischof 1983). This version is widely used around the globe, notably by all groups participating in the IGBP NPP model intercomparison.

Reference list of 265 sources used for the discovery of relationships between data clusters and metadata properties

Visual cluster analysis provides valuable tools that help analysts to understand large data sets in terms of representative clusters and relationships thereof. Often, the found clusters are to be understood in context of belonging categorical, numerical or textual metadata which are given for the data elements. While often not part of the clustering process, such metadata play an important role and need to be considered during the interactive cluster exploration process. Traditionally, linked-views allow to relate (or loosely speaking: correlate) clusters with metadata or other properties of the underlying cluster data. Manually inspecting the distribution of metadata for each cluster in a linked-view approach is tedious, specially for large data sets, where a large search problem arises. Fully interactive search for potentially useful or interesting cluster to metadata relationships may constitute a cumbersome and long process. To remedy this problem, we propose a novel approach for guiding users in discovering interesting relationships between clusters and associated metadata. Its goal is to guide the analyst through the potentially huge search space. We focus in our work on metadata of categorical type, which can be summarized for a cluster in form of a histogram. We start from a given visual cluster representation, and compute certain measures of interestingness defined on the distribution of metadata categories for the clusters. These measures are used to automatically score and rank the clusters for potential interestingness regarding the distribution of categorical metadata. Identified interesting relationships are highlighted in the visual cluster representation for easy inspection by the user. We present a system implementing an encompassing, yet extensible, set of interestingness scores for categorical metadata, which can also be extended to numerical metadata. Appropriate visual representations are provided for showing the visual correlations, as well as the calculated ranking scores. Focusing on clusters of time series data, we test our approach on a large real-world data set of time-oriented scientific research data, demonstrating how specific interesting views are automatically identified, supporting the analyst discovering interesting and visually understandable relationships.

Web-based Biodiversity Citizen Science Database (assembled 2012)

The collective impact of humans on biodiversity rivals mass extinction events defining Earth's history, but does our large population also present opportunities to document and contend with this crisis? We provide the first quantitative review of biodiversity-related citizen science to determine whether data collected by these projects can be, and are currently being, effectively used in biodiversity research. We find strong evidence of the potential of citizen science: within projects we sampled (n = 388), ~1.3 million volunteers participate, contributing up to US Dollar 2.5 billion in-kind annually. These projects exceed most federally-funded studies in spatial and temporal extent, and collectively they sample a breadth of taxonomic diversity. However, only 12% of the 388 projects surveyed obviously provide data to peer-reviewed scientific articles, despite the fact that a third of these projects have verifiable, standardized data that are accessible online. Factors influencing publication included project spatial scale and longevity and having publically available data, as well as one measure of scientific rigor (taxonomic identification training). Because of the low rate at which citizen science data reach publication, the large and growing citizen science movement is likely only realizing a small portion of its potential impact on the scientific research community. Strengthening connections between professional and non-professional participants in the scientific process will enable this large data resource to be better harnessed to understand and address global change impacts on biodiversity.

Revised calibration of the MBT-CBT paleotemperature proxy

The MBT-CBT proxy for the reconstruction of paleotemperatures and past soil pH is based on the distribution of branched glycerol dialkyl glycerol tetraether (brGDGT) membrane lipids. The Methylation of Branched Tetraether (MBT) and the Cyclisation of Branched Tetraether (CBT) indices were developed to quantify these distributions, and significant empirical relations between these indices and annual mean air temperature (MAT) and/or soil pH were found in a large data set of soils. In this study, we extended this soil dataset to 278 globally distributed surface soils. Of these soils, 26% contains all nine brGDGTs, while in 63% of the soils the seven most common brGDGTs were detected, and the latter were selected for calibration purposes. This resulted in new transfer functions for the reconstruction of pH based on the CBT index: pH = 7.90-1.97 × CBT (r**2 = 0.70; RMSE = 0.8; n = 176), as well as for MAT based on the CBT index and methylation index based on the seven most abundant GDGTs (defined as MBT'): MAT = 0.81-5.67 × CBT + 31.0 × MBT' (r**2 = 0.59; RMSE = 5.0 °C; n = 176). The new transfer function for MAT has a substantially lower correlation coefficient than the original equation (r**2 = 0.77). To investigate possible improvement of the correlation, we used our extended global surface soil dataset to statistically derive the indices that best describe the relations of brGDGT composition with MAT and soil pH. These new indices, however, resulted in only a relatively minor increase in correlation coefficients, while they cannot be explained straightforwardly by physiological mechanisms. The large scatter in the calibration cannot be fully explained by local factors or by seasonality, but MAT for soils from arid regions are generally substantially (up to 20 °C) underestimated, suggesting that absolute brGDGT-based temperature records for these areas should be interpreted with caution. The applicability of the new MBT'-CBT calibration function was tested using previously published MBT-CBT-derived paleotemperature records covering the last deglaciation in Central Africa and East Asia, the Eocene-Oligocene boundary and the Paleocene-Eocene thermal maximum. The results show that trends remain similar in all records, but that absolute temperature estimates and the amplitude of temperature changes are lower for most records, and generally in better agreement with independent proxy data.