Australian vegetated coastal ecosystems as global hotspots for climate change mitigation [dataset]
School or Research Centre
School of Science
Funding: CSIRO Marine & Coastal Carbon Biogeochemical Cluster, CSIRO Oceans and Atmosphere, ECU Faculty Research Grant Scheme & Early Career Research Grant Schemes, UTS Plant Functional Biology and Climate Change Cluster, NSW Southeast Local Land Services, Department of Environment, Land, Water and Planning (DELWP), Parks Victoria, Victorian Coastal Catchment Management Authorities (GHCMA,CCMA,PPWCMA,WGCMA,EGCMA), University of Queensland Centennial Scholarship, Hodgkin Trust Scholarship, Australian Institute of Nuclear Science and Engineering, Northern Territory Government Innovation Grant, Australian Research Council (DE130101084,DE140101733,DE150100581,DE160100443,DE170101524,DP150103286,DP150102092,DP160100248,DP160100248, LE140100083,LE170100219,LP150100519,LP160100242,LP110200975), Generalitat de Catalunya (MERS2014 SGR-1356), ICTA ‘Unit of Excellence’ (MinECo, MDM2015-0552), Obra Social "LaCaixa", SUMILEN,CTM 2013-47728-R, Ministry of Economy & Competitiveness UKM-DIP-2017-005
ARC Number : DE130101084 , ARC Number : DE140101733, ARC Number : DE150100581, ARC Number : DE160100443, ARC Number : DE170101524, ARC Number : DP150103286, ARC Number : DP150102092, ARC Number : DP160100248, ARC Number : DP180101285, ARC Number : LE140100083, ARC Number : LE170100219, ARC Number : LP150100519, ARC Number : LP160100242, ARC Number : LP110200975
Data on C stocks and sequestration rates in Australian tidal marshes, mangrove forests and seagrass meadows were compiled from published data. In addition, unpublished studies from the CSIRO Marine and Coastal Carbon Biogeochemistry Cluster project and other studies by the co-authors were included. Data from 1,553 study sites (593 from tidal marshes, 323 from mangrove forests and 637 from seagrass meadows) on soil C stocks (1,103 cores in total), soil C sequestration rates (352 cores in total) and standing C stocks in aboveground biomass (98 measurements in total) were used in this study. Detailed methods are provided in the manuscript linked to this dataset.
- Location details
- Max latitude: 10°7′30″ S Min latitude: 43°33′1.0044″ S Max longitude: 153°37′4.7532″ E Min longitude: 113°0′30.6792″ E Coordinate reference system: WGS84
Soil cores were sampled using different coring mechanisms. The cores were sliced at regular intervals, each slice/sample was weighed before and after oven drying to constant weight at 60-70°C (i.e. dry weight, DW). The Champagne test’ was used to determine whether soil samples contained inorganic carbon. The soil core sub-samples containing carbonates were acidified with 1 M HCl, centrifuged (3500 RPM; 5 minutes) and the supernatant with acid residues was removed, then washed in deionized water, centrifuged again and the supernatant removed and dried before C elemental analyses. Where carbonates were absent, bulk soil samples were milled and encapsulated without acid pre-treatment before C analyses. The C content was obtained using a dry combustion elemental analyser or mass spectrometer. Data on soil accumulation rates from 315 cores derived by means of 210Pb and 14C was compiled. Concentration profiles of 210Pb were determined by alpha spectrometry using Passivated Implanted Planar Silicon (PIPS) detectors after acid digestion of the samples. Selected samples from each core were analysed for 226Ra by ultra-low background liquid scintillation counting (LSC, Quantulus 1220) or gamma spectrometry. Gamma spectrometry measurements were conducted in some cores using semi-planar intrinsic germanium high purity coaxial detectors. Sediment accumulation rates were obtained by applying the Constant Rate of Supply (CRS) or the Constant Flux:Constant Sedimentation models (CF:CS). Samples of bulk soil, plant debris and shells along the cores were radiocarbon dated following standard procedures. The 14C dates from seagrass cores were calibrated using the marine13 calibration curve considering a local Delta R ranging from 3 to 71 years as a function of study site. The corrected ages were used to produce an age-depth model (linear regression) to estimate sediment accumulation rates. To allow direct comparison among study sites, the C storage per unit area (cumulative stocks, mass C m-2) was standardized to 1 m-thick deposits (extrapolating linearly integrated values of C content with depth when necessary). The C sequestration rates (mass C m-2yr-1) were calculated by multiplying average C concentration by the sediment accumulation rate (mass m-2 yr-1) in each core. Estimates of aboveground biomass per unit area were obtained by drying and weighing aboveground materials for tidal marshes and seagrasses, and using field measurements and allometric equations (specific to the region and species) for mangroves. All analyses were performed using Generalized Linear Model procedures in SPSS v. 14.0. All response variables were square-root transformed prior to analyses and had homogenous variances. Climate region (arid, semi-arid, temperate, subtropical and tropical) and ecosystem type (tidal marsh, mangrove and seagrass) were treated as fixed factors in all statistical models (probability distribution: normal; link function: identity). The upscaling of each habitat polygon was performed by multiplying the average ± SD soil C stocks, sequestration rates, and standing C stocks in the aboveground biomass for each ecosystem within each climate region by the specific ecosystem area to obtain blue carbon estimates at climate region scale (arid, semi-arid, temperate, subtropical and tropical) and administrative jurisdictions within Australia (Northern Territory, Queensland, New South Wales, Victoria, Tasmania, South Australia and Western Australia). Potential C stock losses (mass C) and CO2 emissions (mass CO2-e yr-1) were estimated based on 0.03% annual ecosystem area loss for tidal marshes and mangroves, and 0.1% yr-1 for seagrass, and accounted for the sum of C stocks in aboveground biomass and the top meter of soils, assuming that 50% of total C stocks are lost and remineralized to CO2 after disturbance.
Research Activity Title
Carbon Cluster Support
Research Activity Description
Marine and biogeochemical carbon cluster
- Project leader
CSIRO (Australia), University of Queensland (Australia), Edith Cowan University (Australia), University of Western Australia (Australia), Deakin University (Australia), Universidad Autònoma Barcelona (Australia), Charles Darwin University (Australia), Griffith University (Australia), Southern Cross University (SCU) (Australia), University of New South Wales (Australia), Macquarie University (Australia), University of Tasmania (Australia), University of Technology, Sydney (Australia)
Start of data collection time period
End of data collection time period
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Serrano, O., Lovelock, C. E., Atwood, T. B., Macreadie, P. I., Canto, R., Phinn, S., Arias-Ortiz, A., Bai, L., Baldock, J., Bedulli, C., Carnell, P., Connolly, R., Donaldson, P., Esteban, A., Ewers Lewis, C. J., Eyre, B., Hayes, M. A., Horwitz, P., Hutley, L. B., Kavazos, C. R., Kelleway, J. J., Kendrick, G. A., Kilminster, K., Lafratta, A., Lee, S. Y., Lavery, P., Maher, D. T., Marbà, N., Masque´, P., Mateo, M. A., Mount, R., Ralph, P., Roelfsema, C., Rozaimi, M., Ruhon, R., Salinas, C., Samper-Vilarreal, J., Sanderman, J., Sanders, C., Santos, I., Sharples, C., Steven, A., Cannard, T., Trevanthan-Tackett, S., & Duarte, C. M. (2019). Australian vegetated coastal ecosystems as global hotspots for climate change mitigation [dataset]. Edith Cowan University. http://dx.doi.org/10.25919/5d3a8acc9b598