• Energy Research
• Open Access close
• Embargo close
• 14. Life underwater close

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

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).

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.

We simulated an experimental summer storm in large-volume (~1200 m3, ~16m depth) enclosures in Lake Stechlin by mixing deeper water masses from the meta- and hypolimnion into the mixed layer (epilimnion). The mixing included the disturbance of a deep chlorophyll maximum (DCM) which was present at the same time of the experiment in Lake Stechlin and situated in the metalimnion of each enclosure during filling. Copepod and Cladocera biomass was monitored for 42 days after the experimental disturbance event (Utermöhl counting at 60x magnification and biomass calculation from length-dry mass relationships). Sampling was performed using a 90 µm mesh size Apstein-cone. Method: 90 µm mesh size Apstein-cone, Utermöhl counting at 60x, TSO image analysis program (KIO VIDMESS-2011, Version 2.60.50, including a TSO-KST1003832 camera, TSO - Thalheim-Spezial-Optik-Gerätebau, Pulsnitz, Germany), biomass calculations from length-dry mass relationships (Bottrell et al. 1976; Kasprzak 1983).Further Project information:Core Facility grant; Award: GE 1775/2-1

The dataset comprises full list of species of macrozoobenthos collected from the Pechora Sea (SE Barents Sea). Grab samples were collected from 10 stations in the Pechora Bay from aboard RV Kartesh in 2020-2021. Macrobenthic invertebrates were identified with the maximum level of certainty through optical microscopy using regional taxonomic keys. All taxonomic names were standardised using the World Register of Marine Species (WoRMS). All specimens have been counted and weighted (wet biomass) on Ohaus Adventurer scales with reported accuracy to 0.01 g. Bivalve molluscs and gastropods were weighed in shells. Biomass (g. m-2) and abundance (ind m-2) are used to characterise macrozoobenthos. The sampling and identification work was carried out in collaboration with specialists from Lomonosov Moscow State University Marine Research Center and P.P. Shirshov Institute of Oceanology.

Project: IPCC Data Distribution Centre : Supplementary data sets for the Sixth Assessment Report - For the Sixth Assessment Report of the IPCC (AR6) input/source and intermediate datasets underlying the AR6 were collected and long-term archived. This project compliments CMIP6 data subset and snapshot analyzed for the WGI AR6. Summary: This data set contains detailed elements the sea level projections associated with the Intergovernmental Panel on Climate Change Sixth Assessment Report. In particular, it contains relative sea level projections that exclude the background term (representing primarily land subsidence or uplift). It includes probability distributions for all the workflows described in AR6 WGI 9.6.3.2. P-boxes derived from these distributions are available in the sister entry 'IPCC-DDC_AR6_Sup_PBox'. These data may be of use for users who want to substitute their own estimates of the background term. Regional projections can also be accessed through the NASA/IPCC Sea Level Projections Tool at https://sealevel.nasa.gov/ipcc-ar6-sea-level-projection-tool. See https://zenodo.org/communities/ipcc-ar6-sea-level-projections for additional related data sets.

TEMPERSEA is a gridded temperature product for the Red Sea covering in the period 1958-2017 at monthly resolution. The product covers the Red Sea and the Gulf of Aden with a spatial resolution of 0.25°x 0.25° and 23 vertical levels. This product is based on a large number of in-situ observations collected in the region. After a specific quality control, a mapping algorithm has been applied to homogenize the data. Also, an estimate of the accuracy of the product has been generated to accurately define the uncertainties of the product. Supplement to: Agulles, Miguel; Jordà, Gabriel; Jones, Burt; Agustí, Susana; Duarte, Carlos Manuel (2020): Temporal evolution of temperatures in the Red Sea and the Gulf of Aden based on in situ observations (1958-2017). Ocean Science, 16(1), 149-166

The samples were concentrated down to 50 cm**3 by slow decantation after storage for 20 days in a cool and dark place. The species identification was done under light microscope OLIMPUS–BS41 connected to a video-interactive image analysis system at magnification of the ocular 10X and objective – 40X. A Sedgwick-Rafter camera (1ml) was used for counting. 400 specimen were counted for each sample, while rare and large species were checked in the whole sample (Manual of phytoplankton, 2005). Species identification was mainly after Carmelo T. (1997) and Fukuyo, Y. (2000). Total phytoplankton abundance was calculated as sum of taxon-specific abundances. Total phytoplankton biomass was calculated as sum of taxon-specific biomasses.The cell biovolume was determined based on morpho-metric measurement of phytoplankton units and the corresponding geometric shapes as described in detail in (Edier, 1979).