Diminishing prospects for environmental preservation under climate change are intensifying efforts to boost capture, storage and sequestration (long-term burial) of carbon. However, as Earth\uffe2\uff80\uff99s biological carbon sinks also shrink, remediation has become a key part of the narrative for terrestrial ecosystems. In contrast, blue carbon on polar continental shelves have stronger pathways to sequestration and have increased with climate-forced marine ice losses\uffe2\uff80\uff94becoming the largest known natural negative feedback on climate change. Here we explore the size and complex dynamics of blue carbon gains with spatiotemporal changes in sea ice (60\uffe2\uff80\uff93100 MtCyear\uffe2\uff88\uff921), ice shelves (4\uffe2\uff80\uff9340 MtCyear\uffe2\uff88\uff921\uffe2\uff80\uff89=\uffe2\uff80\uff89giant iceberg generation) and glacier retreat (<\uffe2\uff80\uff891 MtCyear\uffe2\uff88\uff921). Estimates suggest that, amongst these, reduced duration of seasonal sea ice is most important. Decreasing sea ice extent drives longer (not necessarily larger biomass) smaller cell-sized phytoplankton blooms, increasing growth of many primary consumers and benthic carbon storage\uffe2\uff80\uff94where sequestration chances are maximal. However, sea ice losses also create positive feedbacks in shallow waters through increased iceberg movement and scouring of benthos. Unlike loss of sea ice, which enhances existing sinks, ice shelf losses generate brand new carbon sinks both where giant icebergs were, and in their wake. These also generate small positive feedbacks from scouring, minimised by repeat scouring at biodiversity hotspots. Blue carbon change from glacier retreat has been least well quantified, and although emerging fjords are small areas, they have high storage-sequestration conversion efficiencies, whilst blue carbon in polar waters faces many diverse and complex stressors. The identity of these are known (e.g. fishing, warming, ocean acidification, non-indigenous species and plastic pollution) but not their magnitude of impact. In order to mediate multiple stressors, research should focus on wider verification of blue carbon gains, projecting future change, and the broader environmental and economic benefits to safeguard blue carbon ecosystems through law.
", "keywords": ["0301 basic medicine", "0303 health sciences", "Blue carbon", "Ecologie", "Climate Change", "Sea ice", "Nature-based solutions", "Antarctic Regions", "Review", "Evolution des esp\u00e8ces", "Hydrogen-Ion Concentration", "15. Life on land", "7. Clean energy", "Carbon", "Feedback", "03 medical and health sciences", "13. Climate action", "Blue carbon \u00b7 Ecosystem services \u00b7 Sea ice \u00b7 Nature-based solutions \u00b7 Southern Ocean", "Ecosystem services", "Ice Cover", "Seawater", "14. Life underwater", "Southern Ocean", "Ecosystem"]}, "links": [{"href": "https://link.springer.com/content/pdf/10.1007/s00114-021-01748-8.pdf"}, {"href": "https://dipot.ulb.ac.be/dspace/bitstream/2013/332392/3/Barnes2021_Article_SocietalImportanceOfAntarcticN.pdf"}, {"href": "https://doi.org/10.1007/s00114-021-01748-8"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/The%20Science%20of%20Nature", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s00114-021-01748-8", "name": "item", "description": "10.1007/s00114-021-01748-8", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s00114-021-01748-8"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-09-07T00:00:00Z"}}, {"id": "10.1016/j.geoderma.2017.01.025", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:16:34Z", "type": "Journal Article", "created": "2017-02-09", "title": "Soil C Quantities Of Mangrove Forests, Their Competing Land Uses, And Their Spatial Distribution In The Coast Of Honda Bay, Philippines", "description": "Mangrove forests provide many ecosystem goods and services and they contain large amount of carbon (C) especially in their soil. Yet, their global area is still declining owing to conversion to non-forest land uses. While studies have been conducted on mangrove soil C stocks, our knowledge on how C stocks of mangrove forests compare with those of non-forest land uses that replaced them is still limited. This knowledge is crucial in land use planning and decision-making in the coastal zone. Site-scale mapping and assessments of mangrove soil C stocks and the land uses that replaced them are also limited. The aim of this study was to quantify and compare the soil C stocks in mangrove forests and their competing non-forest land uses (represented by aquaculture pond, coconut plantation, salt pond and cleared mangrove), estimate soil C loss arising from conversion, and model the soil C stock distribution in the entire study site. On the average, the soil C stock of mangrove forests was 851.9 \u00b1 87 MgC ha\u2212 1 while that of their non-forest competing land uses was less than half at 365.1 \u00b1 31 MgC ha\u2212 1. Closed canopy mangrove was highest at 1040 \u00b1 104 MgC ha\u2212 1, followed by open canopy mangrove (640 \u00b1 131 MgC ha\u2212 1) while aquaculture, salt pond and cleared mangrove had comparable C stocks (454 \u00b1 32, 401 \u00b1 9, 413 \u00b1 25 MgC ha\u2212 1, respectively) and coconut plantation had the least (42 \u00b1 0.7 MgC ha\u2212 1). Overall, the reduction in soil C stock (soil C loss) due to land use conversion in mangrove ranged from 398 to 809 MgC ha\u2212 1 (mean: 486.8 MgC ha\u2212 1) or a decline of 57% in soil C stock, on the average. It was possible to model the site-scale spatial distribution of soil C stocks and predict their values with 85% overall certainty using the Ordinary Kriging approach. Results from this study could help inform current discussions on Blue Carbon and REDD + as well as policy and program development that advance research on soil C conservation and ecosystem services in coastal forested wetlands.", "keywords": ["580", "c stock", "mangrove", "spatial modelling", "570", "aquaculture", "blue carbon", "Philippines", "14. Life underwater", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.geoderma.2017.01.025"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.geoderma.2017.01.025", "name": "item", "description": "10.1016/j.geoderma.2017.01.025", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.geoderma.2017.01.025"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-05-01T00:00:00Z"}}, {"id": "10.5061/dryad.j3tx95xk8", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:21:35Z", "type": "Dataset", "title": "Patterns and determinants of plant-derived lignin phenols in coastal wetlands: implications for organic C accumulation", "description": "unspecifiedPlease see the README document\u00a0\u00a0('Lignin_content_and_monomer_composition.csv', 'Site_location.csv', 'Soil_organic_carbon_content.csv', 'Soil_properties.csv', 'Vegetation_and_climate.csv') and the accompanying published article: Shaopan Xia, Zhaoliang Song, Weiqi Wang, Yaran Fan, Laodong Guo, Lukas Van Zwieten, Iain P. Hartley, Yin Fang, Yidong Wang, Zhenqing Zhang, Cong-Qiang Liu, and Hailong Wang. 2023. Patterns and determinants of plant-derived lignin phenols in coastal wetlands: implications for organic C accumulation. Functional Ecology. Accepted. DOI: 10.5061/dryad.j3tx95xk8", "keywords": ["lignin biomarker", "salt marsh and mangrove", "13. Climate action", "plant-soil Interactions", "blue carbon", "organic C source apportionment", "14. Life underwater", "FOS: Earth and related environmental sciences", "15. Life on land", "6. Clean water"], "contacts": [{"organization": "Song, Zhaoliang, Xia, Shaopan, Wang, Weiqi, Fan, Yaran, Guo, Laodong, Van Zwieten, Lukas, Hartley, Iain P., Fang, Yin, Wang, Yidong, Zhang, Zhenqing, Liu, Cong-Qiang, Wang, Hailong,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.j3tx95xk8"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.j3tx95xk8", "name": "item", "description": "10.5061/dryad.j3tx95xk8", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.j3tx95xk8"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-02-02T00:00:00Z"}}, {"id": "10.5281/zenodo.15180620", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-07-25T16:22:58Z", "type": "Dataset", "title": "Database of the blue carbon inventory in Spain and Portugal. Organic carbon biomass and soil stocks and sequestration rates to the soil.", "description": "This database is a compilation of published and unpublished data used to estimate (i) the organic carbon biomass stocks, (ii) the soil organic carbon stock, and (iii) the rates of organic carbon sequestration to the soil associated to Spanish and Portuguese seagrass meadows and salt marshes. The database is presented in five .csv files. Specific .csv files content: \u00a0 1) General Information: Site ID: ID of the location where the samples were collected Locality: Locality where the samples were collected Region: Spanish or Portuguese region where the samples were collected Coast: Spanish or Portuguese coast where the samples were collected Ecosystem: Type of blue carbon ecosystem Predominant Species: Predominant species at the sampling location Tidal Range: Tidal range at the sampling location. Intertidal and subtidal for seagrass meadows and Low, Medium, High and Microtidal for Salt Marshes Sampling Year (yr): Year in which the sample was collected Latitude (decimal degrees, WGS84): Latitude of sampling station. Longitude (decimal degrees, WGS84): Longitude of sampling station. Water Depth (m): Water column depth at sampling station Reference: Publications where the data has been used Researcher: Name of the person responsible for the data. Contact: Email contact of person responsible for the data. \u00a0 2) Biomass: Site ID: ID of the location where the samples were collected Sample ID: ID of the sample Ecosystem: Type of blue carbon ecosystem Species: Predominant species at the sampling location Month: Month of the year in which the sample was collected Abovegr DW (km m-2): Aboveground biomass dry weight Abovegr sd (km m-2): Standard deviation of the aboveground biomass dry weight Abovegr (n): Number of samples of the aboveground biomass dry weight Belowgr DW (km m-2): Belowground biomass dry weight Belowgr sd (km m-2): Standard deviation of the belowground biomass dry weight Belowgr (n): Number of subsamples of the belowground biomass dry weight \u00a0 3) Soil: Site ID: \u00a0ID of the location where the samples were collected Core ID: ID of the soil core Ecosystem: Type of blue carbon ecosystem Dominant Species: Predominant species at the sampling location Tidal Range (m): Tidal range at the sampling location. Intertidal and subtidal for seagrass meadows and Low, Medium, High and Microtidal for Salt Marshes Year of sampling (yr): Year in which the sample was collected Core Compression (%): Percentage of compression due to core extraction Min depth (compacted, cm): Start depth of the sediment interval. Uncorrected for compression. Max depth (compacted, cm): End depth of the sediment interval. Uncorrected for compression. Dry Weight (g dw): Mass of dried sediment Dry bulk density (g dw cm-3): Mass of dried sediment to the total volume Organic matter (% dw): Percentage of organic matter in the sediment sample (based on dry weight) Organic carbon (% dw): Percentage of organic carbon in the sediment sample (based on dry weight) Estimated Age (years from sampling): Estimated age of the sediment Raw dates: Dates used to estimate age of the sediment Dating method: Dating method \u00a0 4) OC Plant: Site ID: ID of the location where the samples were collected Sample ID: ID of the sample Ecosystem: Type of blue carbon ecosystem Species: Predominant species at the sampling location Tissue: Tissues used to estimate the carbon content TOC (%): Percentage of carbon in the plant sample (based on dry weight) TOC sd: Standard deviation of the percentage of carbon in the plant sample (based on dry weight) \u00a0 5) Published: published data from the studied categories (Posidonia oceanica, Zostera marina, Zostera noltii, Cymodocea nodosa, and Low, Medium, High and Microtidal salt marshes) from outside Spain and Portugal Ecosystem: Type of blue carbon ecosystem Tidal Range: Tidal range at the sampling location. Intertidal and subtidal for seagrass meadows and Low, Medium, High and Microtidal for Salt Marshes Genus: Predominant genus Species: Predominant species at the sampling location Seagrass type: Seagrass type following the classification of Kilminster et al. 2015 (https://doi.org/10.1016/j.scitotenv.2015.04.061): Persistent, classification and opportunistic. Latitude (decimal degrees, WGS84): Latitude of sampling station. Longitude (decimal degrees, WGS84): Longitude of sampling station. Abovegr DW (kg dw m-2): Aboveground biomass dry weight Abovegr OC stock (kg dw OC m-2): Organic carbon stock in the aboveground biomass SE Abovegr OC stock (kg dw OC m-2): Standard error of the aboveground biomass organic carbon stock SD Abovegr OC stock (kg dw OC m-2): Standard deviation of the aboveground biomass organic carbon stock Abovegr OC stock n: Number of subsamples of the aboveground biomass organic carbon stocks Soil Stock 1m (kg dw OC m-2): Soil organic carbon stocks at 1m depth SE Soil Stock 1m (kg dw OC m-2): Standard error of the soil organic carbon stocks at 1m depth SD Soil Stock 1m (kg dw OC m-2): Standard deviation of the soil organic carbon stocks at 1m depth Soil Stock (n): Number of cores used to estimate the soil organic carbon stocks at 1m depth OC sequestration rate (kg dw OC m-2 yr-1): Average organic carbon sequestration rates OC sequestration rate SE (kg dw OC m-2 yr-1): Standard error of the average organic carbon sequestration rates Time frame (years): Time frame used to estimate the average organic carbon sequestration rates OC sequestration rate last 100 years (kg dw OC m-2 yr-1): Average organic carbon sequestration rates in the last 100 years OC sequestration rate last 100 SE (kg dw OC m-2 yr-1): Standard error of the average organic carbon sequestration rates in the last 100 years OC sequestration rate last 100 (n): Number of cores used to estimate the average organic carbon sequestration rates in the last 100 years Reference: DOI of the data origin", "keywords": ["Blue Carbon"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15180620"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15180620", "name": "item", "description": "10.5281/zenodo.15180620", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15180620"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-04-09T00:00:00Z"}}, {"id": "10.5281/zenodo.7572718", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:23:42Z", "type": "Dataset", "title": "Mangroves in the lagoon of the protected Aldabra Atoll: a dataset on species, structure, biomass and the environment", "description": "Open AccessMangroves are vital for climate change mitigation since they store vast quantities of carbon as biomass and in the soil. Global mangrove biomass estimates are derived from climate-based relationships of mangroves with precipitation and temperature. However, the carbon stored locally is highly variable depending on environmental conditions. This uncertainty highlights the importance of local mangrove surveys and the need to explore factors that regulate forest structure and, therefore, carbon storage. In this study, we investigate the mangrove forest structure, seedling growth, species composition, aboveground biomass, soil organic carbon, and local environmental factors related to variation in mangrove carbon in the lagoonal mangroves on the protected Aldabra Atoll, Seychelles. We present a database from an extensive field survey of Aldabra's mangrove ecosystem using 54 plots of 5 m x 5 m along a mangrove coverage gradient. From November 2019 to November 2020, we measured the structural attributes and identified six mangrove species from >750 adult mangrove trees on Aldabra. We used the height and diameter of adult trees to derive aboveground biomass and carbon from a tropical allometric equation. We measured the height of 59 mangrove seedlings over three sampling periods. In addition, environmental factors were recorded for each plot. We measured soil salinity repeatedly along the soil column. From 90 soil samples, we measured the physical and chemical properties of the soil, including soil organic carbon and elemental concentrations for >20 elements. Autonomous measures of the water level, temperature and conductivity were made every 10 minutes over 1 year in a subset of 36 plots. The database provides 60% more information that is currently available for Seychelles regarding mangrove forest structure and biomass and is essential for research on several globally threatened and endemic species that depend on the mangroves on Aldabra. Furthermore, the database allows the incorporation of data and insights for the Western Indian Ocean and lagoonal mangroves, where few studies have been conducted on mangrove aboveground biomass and soil organic carbon. No copyright restrictions apply to the use of this data set. Please cite this data paper when using the current data in publications.", "keywords": ["13. Climate action", "aboveground biomass", " blue carbon", " field survey", " islands", " lagoon", " one-year field period", " protected area", " Seychelles", " soil nutrients", " water level", " water temperature", " Western Indian Ocean.", "14. Life underwater", "15. Life on land"], "contacts": [{"organization": "Constance, Annabelle", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.7572718"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.7572718", "name": "item", "description": "10.5281/zenodo.7572718", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.7572718"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-08-10T00:00:00Z"}}, {"id": "10.6086/D1TX0T", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:24:28Z", "type": "Dataset", "title": "Mangrove sediment blue carbon estimates", "description": "Carbon accumulation in coastal wetlands is normally assessed by extracting a sediment core and estimating its carbon content and bulk density. Because carbon content and bulk density are functionally related, the latter can be estimated gravimetrically from a section of the core or, alternatively, from the carbon content in the sample using the Mixing Model equation from soil science. We analyzed the effect that the choice of corer and the method used to estimate bulk density could have on the final estimates of carbon storage in the sediments. The choice of corer did not have much influence on the final estimates of carbon density; the main factor in selecting a corer is the operational difficulties that each corer may have in different types of sediments. Because of the multiplication of errors in a product of two variables subject to random sampling error, when using gravimetric estimates of bulk density, the dispersion of the data points in the estimation of total carbon density rises rapidly as the amount of carbon in the soil increases. For this reason, the estimation of carbon densities in peaty soils with this method can be very imprecise in peaty sediments. In contrast, the estimation of total carbon density using only the carbon fraction as a predictor is very precise, especially in sediments rich in organic matter. This method, however, depends critically on an accurate estimation of the two parameters of the Mixing Model (the bulk density of pure peat and the bulk density of pure mineral sediment). If these parameters are not estimated accurately, the calculation of total carbon density can be biased.", "keywords": ["Sediment Core", "mangrove", "bulk density", "precision and accuracy", "13. Climate action", "blue carbon", "FOS: Earth and related environmental sciences", "15. Life on land"], "contacts": [{"organization": "Ezcurra, Exequiel", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.6086/D1TX0T"}, {"rel": "self", "type": "application/geo+json", "title": "10.6086/D1TX0T", "name": "item", "description": "10.6086/D1TX0T", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.6086/D1TX0T"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-12-13T00:00:00Z"}}, {"id": "2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/332392", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:25:35Z", "type": "Journal Article", "created": "2021-09-07", "title": "Societal importance of Antarctic negative feedbacks on climate change: blue carbon gains from sea ice, ice shelf and glacier losses", "description": "AbstractDiminishing prospects for environmental preservation under climate change are intensifying efforts to boost capture, storage and sequestration (long-term burial) of carbon. However, as Earth\uffe2\uff80\uff99s biological carbon sinks also shrink, remediation has become a key part of the narrative for terrestrial ecosystems. In contrast, blue carbon on polar continental shelves have stronger pathways to sequestration and have increased with climate-forced marine ice losses\uffe2\uff80\uff94becoming the largest known natural negative feedback on climate change. Here we explore the size and complex dynamics of blue carbon gains with spatiotemporal changes in sea ice (60\uffe2\uff80\uff93100 MtCyear\uffe2\uff88\uff921), ice shelves (4\uffe2\uff80\uff9340 MtCyear\uffe2\uff88\uff921\uffe2\uff80\uff89=\uffe2\uff80\uff89giant iceberg generation) and glacier retreat (<\uffe2\uff80\uff891 MtCyear\uffe2\uff88\uff921). Estimates suggest that, amongst these, reduced duration of seasonal sea ice is most important. Decreasing sea ice extent drives longer (not necessarily larger biomass) smaller cell-sized phytoplankton blooms, increasing growth of many primary consumers and benthic carbon storage\uffe2\uff80\uff94where sequestration chances are maximal. However, sea ice losses also create positive feedbacks in shallow waters through increased iceberg movement and scouring of benthos. Unlike loss of sea ice, which enhances existing sinks, ice shelf losses generate brand new carbon sinks both where giant icebergs were, and in their wake. These also generate small positive feedbacks from scouring, minimised by repeat scouring at biodiversity hotspots. Blue carbon change from glacier retreat has been least well quantified, and although emerging fjords are small areas, they have high storage-sequestration conversion efficiencies, whilst blue carbon in polar waters faces many diverse and complex stressors. The identity of these are known (e.g. fishing, warming, ocean acidification, non-indigenous species and plastic pollution) but not their magnitude of impact. In order to mediate multiple stressors, research should focus on wider verification of blue carbon gains, projecting future change, and the broader environmental and economic benefits to safeguard blue carbon ecosystems through law.