Seawater carbonate chemistry and coverage and dry weight of Ecklonia radiata during experiments, 2010

Predictions about the ecological consequences of oceanic uptake of CO2 have been preoccupied with the effects of ocean acidification on calcifying organisms, particularly those critical to the formation of habitats (e.g. coral reefs) or their maintenance (e.g. grazing echinoderms). This focus overlooks the direct effects of CO2 on non-calcareous taxa, particularly those that play critical roles in ecosystem shifts. We used two experiments to investigate whether increased CO2 could exacerbate kelp loss by facilitating non-calcareous algae that, we hypothesized, (i) inhibit the recovery of kelp forests on an urbanized coast, and (ii) form more extensive covers and greater biomass under moderate future CO2 and associated temperature increases. Our experimental removal of turfs from a phase-shifted system (i.e. kelp- to turf-dominated) revealed that the number of kelp recruits increased, thereby indicating that turfs can inhibit kelp recruitment. Future CO2 and temperature interacted synergistically to have a positive effect on the abundance of algal turfs, whereby they had twice the biomass and occupied over four times more available space than under current conditions. We suggest that the current preoccupation with the negative effects of ocean acidification on marine calcifiers overlooks potentially profound effects of increasing CO2 and temperature on non-calcifying organisms.

Global Ocean Colour for Carbon Cycle Research (full product set)

In 2005, the International Ocean Colour Coordinating Group (IOCCG) convened a working group to examine the state of the art in ocean colour data merging, which showed that the research techniques had matured sufficiently for creating long multi-sensor datasets (IOCCG, 2007). As a result, ESA initiated and funded the DUE GlobColour project (http://www.globcolour.info/) to develop a satellite based ocean colour data set to support global carbon-cycle research. It aims to satisfy the scientific requirement for a long (10+ year) time-series of consistently calibrated global ocean colour information with the best possible spatial coverage. This has been achieved by merging data from the three most capable sensors: SeaWiFS on GeoEye's Orbview-2 mission, MODIS on NASA's Aqua mission and MERIS on ESA's ENVISAT mission. In setting up the GlobColour project, three user organisations were invited to help. Their roles are to specify the detailed user requirements, act as a channel to the broader end user community and to provide feedback and assessment of the results. The International Ocean Carbon Coordination Project (IOCCP) based at UNESCO in Paris provides direct access to the carbon cycle modelling community's requirements and to the modellers themselves who will use the final products. The UK Met Office's National Centre for Ocean Forecasting (NCOF) in Exeter, UK, provides an understanding of the requirements of oceanography users, and the IOCCG bring their understanding of the global user needs and valuable advice on best practice within the ocean colour science community. The three year project kicked-off in November 2005 under the leadership of ACRI-ST (France). The first year was a feasibility demonstration phase that was successfully concluded at a user consultation workshop organised by the Laboratoire d'Océanographie de Villefranche, France, in December 2006. Error statistics and inter-sensor biases were quantified by comparison with insitu measurements from moored optical buoys and ship based campaigns, and used as an input to the merging. The second year was dedicated to the production of the time series. In total, more than 25 Tb of input (level 2) data have been ingested and 14 Tb of intermediate and output products created, with 4 Tb of data distributed to the user community. Quality control (QC) is provided through the Diagnostic Data Sets (DDS), which are extracted sub-areas covering locations of in-situ data collection or interesting oceanographic phenomena. This Full Product Set (FPS) covers global daily merged ocean colour products in the time period 1997-2006 and is also freely available for use by the worldwide science community at http://www.globcolour.info/data_access_full_prod_set.html. The GlobColour service distributes global daily, 8-day and monthly data sets at 4.6 km resolution for, chlorophyll-a concentration, normalised water-leaving radiances (412, 443, 490, 510, 531, 555 and 620 nm, 670, 681 and 709 nm), diffuse attenuation coefficient, coloured dissolved and detrital organic materials, total suspended matter or particulate backscattering coefficient, turbidity index, cloud fraction and quality indicators. Error statistics from the initial sensor characterisation are used as an input to the merging methods and propagate through the merging process to provide error estimates for the output merged products. These error estimates are a key component of GlobColour as they are invaluable to the users; particularly the modellers who need them in order to assimilate the ocean colour data into ocean simulations. An intensive phase of validation has been undertaken to assess the quality of the data set. In addition, inter-comparisons between the different merged datasets will help in further refining the techniques used. Both the final products and the quality assessment were presented at a second user consultation in Oslo on 20-22 November 2007 organised by the Norwegian Institute for Water Research (NIVA); presentations are available on the GlobColour WWW site. On request of the ESA Technical Officer for the GlobColour project, the FPS data set was mirrored in the PANGAEA data library.

Database of Ice-Rich Yedoma Permafrost (IRYP)

Vast portions of Arctic and sub-Arctic Siberia, Alaska and the Yukon Territory are covered by ice-rich silty to sandy deposits that are containing large ice wedges, resulting from syngenetic sedimentation and freezing. Accompanied by wedge-ice growth in polygonal landscapes, the sedimentation process was driven by cold continental climatic and environmental conditions in unglaciated regions during the late Pleistocene, inducing the accumulation of the unique Yedoma deposits up to >50 meters thick. Because of fast incorporation of organic material into syngenetic permafrost during its formation, Yedoma deposits include well-preserved organic matter. Ice-rich deposits like Yedoma are especially prone to degradation triggered by climate changes or human activity. When Yedoma deposits degrade, large amounts of sequestered organic carbon as well as other nutrients are released and become part of active biogeochemical cycling. This could be of global significance for future climate warming as increased permafrost thaw is likely to lead to a positive feedback through enhanced greenhouse gas fluxes. Therefore, a detailed assessment of the current Yedoma deposit coverage and its volume is of importance to estimate its potential response to future climate changes. We synthesized the map of the coverage and thickness estimation, which will provide critical data needed for further research. In particular, this preliminary Yedoma map is a great step forward to understand the spatial heterogeneity of Yedoma deposits and its regional coverage. There will be further applications in the context of reconstructing paleo-environmental dynamics and past ecosystems like the mammoth-steppe-tundra, or ground ice distribution including future thermokarst vulnerability. Moreover, the map will be a crucial improvement of the data basis needed to refine the present-day Yedoma permafrost organic carbon inventory, which is assumed to be between 83±12 (Strauss et al., 2013, doi:10.1002/2013GL058088) and 129±30 (Walter Anthony et al., 2014, doi:10.1038/nature13560) gigatonnes (Gt) of organic carbon in perennially-frozen archives. Hence, here we synthesize data on the circum-Arctic and sub-Arctic distribution and thickness of Yedoma for compiling a preliminary circum-polar Yedoma map. For compiling this map, we used (1) maps of the previous Yedoma coverage estimates, (2) included the digitized areas from Grosse et al. (2013) as well as extracted areas of potential Yedoma distribution from additional surface geological and Quaternary geological maps (1.: 1:500,000: Q-51-V,G; P-51-A,B; P-52-A,B; Q-52-V,G; P-52-V,G; Q-51-A,B; R-51-V,G; R-52-V,G; R-52-A,B; 2.: 1:1,000,000: P-50-51; P-52-53; P-58-59; Q-42-43; Q-44-45; Q-50-51; Q-52-53; Q-54-55; Q-56-57; Q-58-59; Q-60-1; R-(40)-42; R-43-(45); R-(45)-47; R-48-(50); R-51; R-53-(55); R-(55)-57; R-58-(60); S-44-46; S-47-49; S-50-52; S-53-55; 3.: 1:2,500,000: Quaternary map of the territory of Russian Federation, 4.: Alaska Permafrost Map). The digitalization was done using GIS techniques (ArcGIS) and vectorization of raster Images (Adobe Photoshop and Illustrator). Data on Yedoma thickness are obtained from boreholes and exposures reported in the scientific literature. The map and database are still preliminary and will have to undergo a technical and scientific vetting and review process. In their current form, we included a range of attributes for Yedoma area polygons based on lithological and stratigraphical information from the original source maps as well as a confidence level for our classification of an area as Yedoma (3 stages: confirmed, likely, or uncertain). In its current version, our database includes more than 365 boreholes and exposures and more than 2000 digitized Yedoma areas. We expect that the database will continue to grow. In this preliminary stage, we estimate the Northern Hemisphere Yedoma deposit area to cover approximately 625,000 km². We estimate that 53% of the total Yedoma area today is located in the tundra zone, 47% in the taiga zone. Separated from west to east, 29% of the Yedoma area is found in North America and 71 % in North Asia. The latter include 9% in West Siberia, 11% in Central Siberia, 44% in East Siberia and 7% in Far East Russia. Adding the recent maximum Yedoma region (including all Yedoma uplands, thermokarst lakes and basins, and river valleys) of 1.4 million km² (Strauss et al., 2013, doi:10.1002/2013GL058088) and postulating that Yedoma occupied up to 80% of the adjacent formerly exposed and now flooded Beringia shelves (1.9 million km², down to 125 m below modern sea level, between 105°E - 128°W and >68°N), we assume that the Last Glacial Maximum Yedoma region likely covered more than 3 million km² of Beringia. Acknowledgements: This project is part of the Action Group "The Yedoma Region: A Synthesis of Circum-Arctic Distribution and Thickness" (funded by the International Permafrost Association (IPA) to J. Strauss) and is embedded into the Permafrost Carbon Network (working group Yedoma Carbon Stocks). We acknowledge the support by the European Research Council (Starting Grant #338335), the German Federal Ministry of Education and Research (Grant 01DM12011 and "CarboPerm" (03G0836A)), the Initiative and Networking Fund of the Helmholtz Association (#ERC-0013) and the German Federal Environment Agency (UBA, project UFOPLAN FKZ 3712 41 106).