• Energy Research
• 2016-2025close
• 14. Life underwater close

Preliminary ages were assigned to sample datasets by assigning seasonal trace element ratios minima and maxima in datasets to warmest and coolest months in satellite SST records and then linearly interpolating in-between

This dataset contains measurements of downwelling short wave irradiance, measured in a small scale grid setup at Falkenberg: 20 sensors in 4 by 5 grid with a 50 meter grid spacing. Another 4 sensors were placed in all direction about 5 km away from the main grid at Falkenberg. The sampling rate is 10 Hz, to catch all irradiance variability, and is calibrated against a high quality sun tracker. The strength of this dataset is not the absolute accuracy, but rather the spatial measurements and ability to catch variability. Quality: Accuracy is estimated to be within 5% of a conventional pyranometer. Quality varies depending on weather type, but is best for high solar elevation angles (solar noon +/- 4 hours). Data is manually quality controlled, with detailed quality flags included in the dataset. Some anomalous data is not caught, in particular noisy data due to many insects on the sensor or small dirt from birds that reduces the signal slightly. These effects are much smaller than the driving weather patterns. The data is unsuitable for calculating radiation balances, but it is particularly useful for studying variability and patterns of solar irradiance on small scales. Funding: Dutch Research Council (NWO), Shedding Light On Cloud Shadows: VI.Vidi.192.068 Project: FESSTVaL (Field Experiment on submesoscale spatio-temporal variability in Lindenberg), a measurement campaign initiated by the Hans-Ertel-Center for Weather Research.

Supplementary file for "Genetic Diversity and Structure of Tropical Porites lutea Populations Highlight Their High Adaptive Potential to Environmental Changes in the South China Sea"Three Tables and three figures in it.

This dataset gathers data used to determine the temporal variability of couplings between pelagic and benthic habitats for fish assemblages at five periods. Organic matter fluxes were assessed using stable isotopes analysis. Species relative biomass was considered to explore energy fluxes within the fish assemblage

Penguins (Sphenisciformes) are a highly diverse order of seabirds distributed widely across the Southern Hemisphere. They shared a common ancestor with Procellariiformes about 60 million years ago, and have subsequently transited from flying seabirds to flightless marine divers. Approximately 20 extant penguin species are recognized across six well-defined genera, ranging from the Galápagos Islands on the equator, to the oceanic temperate forests of New Zealand, the rocky coastlines of the sub-Antarctic islands, and the sea-ice around Antarctica. To inhabit such diverse and extreme environments, this speciose order has evolved many physiological and morphological adaptations. However, penguins are also highly sensitive to climate change, and most species are already declining or are predicted to decline under future climate change scenarios. Therefore, penguins are an exciting system for understanding the evolutionary processes of speciation, adaptation and demography. Genomic data are an emerging resource for addressing questions about such processes. Here we present 19 new high-coverage genomes that, together with two previously published genomes also available in GigaDB, encompass all extant penguin species. As such, this dataset provides a novel resource for understanding the evolutionary history within penguins, and between penguins and other avifauna. We believe that our dataset and project will be important for cultural heritage and the conservation of this iconic Southern Hemisphere species assemblage. Comparative and evolutionary genomic analyses are currently being carried out, and the consortium welcomes new members interested in contributing to this work. While this work is still underway we have published these 19 penguin genomes to provide early-release, while requesting researchers intending to use this data for similar cross-species comparisons to continue to follow the Fort Lauderdale and Toronto rules.

Data from "Heat and carbon coupling reveals ocean warming due to circulation changes" by Bronselaer & Zanna, 2020, Nature, https://doi.org/10.1038/s41586-020-2573-5 The files contain Linear Change in Ocean Heat Content (top 2000 m) relative to 1951 for observations and CMIP5 data, and the decomposition into added and redistributed (due to changes in ocean circulation).

Data files for the NWEI Azura grid-connected deployment at the 30-meter berth of the US Navys Wave Energy Test Site (WETS 30m Site) at the Kaneohe Marine Corps Base Hawaii (MCBH) on the windward (northeast) coast of the island of Oahu, HI. See general documentation describing specifics of the data files and formats in a separate submission.

The Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3 data set contains land areas with urban, quasi-urban, rural, and total populations (counts) within the LECZ for 234 countries and other recognized territories for the years 1990, 2000, and 2015. This data set updates initial estimates for the LECZ population by drawing on a newer collection of input data, and provides a range of estimates for at-risk population and land area. Constructing accurate estimates requires high-quality and methodologically consistent input data, and the LECZv3 evaluates multiple data sources for population totals, digital elevation model, and spatially-delimited urban classifications. Users can find the paper "Estimating Population and Urban Areas at Risk of Coastal Hazards, 1990-2015: How data choices matter" (MacManus, et al. 2021) in order to evaluate selected inputs for modeling Low Elevation Coastal Zones. According to the paper, the following are considered core data sets for the purposes of LECZv3 estimates: Multi-Error-Removed Improved-Terrain Digital Elevation Model (MERIT-DEM), Global Human Settlement (GHSL) Population Grid R2019 and Degree of Urbanization Settlement Model Grid R2019a v2, and the Gridded Population of the World, Version 4 (GPWv4), Revision 11. This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) and the City University of New York (CUNY) Institute for Demographic Research (CIDR).

Methane emissions from aquatic and terrestrial ecosystems play a crucial role in global warming, which is particularly affecting high-latitude ecosystems. As major contributors to methane emissions in natural environments, the microbial communities involved in methane production and oxidation deserve a special attention. Microbial diversity and activity are expected to be strongly affected by the already observed (and further predicted) temperature increase in high-latitude ecosystems, eventually resulting in disrupted feedback methane emissions. The METHANOBASE project has been designed to investigate the intricate relations between microbial diversity and methane emissions in Arctic, Subarctic and Subantarctic ecosystems, under natural (baseline) conditions and in response to simulated temperature increments. We report here a small subunit ribosomal RNA (16S rRNA) analysis of lake, peatland and mineral soil ecosystems.