JSON RDF ISO19115-3 XML

Sediment accumulation and mineralization in mangrove forests, Jiulongjiang Estuary, China

Created 24/06/2017

Updated 09/10/2017

JSON RDF ISO19115-3 XML

Rates of sediment accumulation and microbial mineralisation were examined at 3 Kandelia candel forests.

Within each forest, measurements for species (6)identification, basal area, and diameter at breast height were taken. All sediment samples were taken within the same 100-200m2 plots. Root (live and dead) biomass was estimated. Triplicate surface samples were taken for percent sand, silt and clay, and water content. Soild-phase concentrations of TOC, TN, Fe and S (all % dry weights), Mn and TP (ug g-1), and C:N (molar) were determined from 2-3 cores from each site. Salinity was measured on filtered water.

Mass sediment accumulation rates were determined from gamma spectrometric measurements of 210Pb, 226Ra and 137Cs.

Sediment samples were taken in summer (July 2002) and autumn (September 2003).

Gas fluxes (CO2 and O2) were measured across the sediment-air interface. Rates of net dissolved Fe, Mn and ammonium releases from sediments and denitrification, nitrogen fixation, methane and nitrous oxide fluxes were also measured.

Files and APIs

Tags

Additional Info

Field Value
Title Sediment accumulation and mineralization in mangrove forests, Jiulongjiang Estuary, China
Language English
Licence Other
Landing Page https://devweb.dga.links.com.au/data/dataset/bf52c44f-198e-4bd0-a03c-7c60cdc3c7fd
Contact Point
Australian Institute of Marine Science
adc@aims.gov.au
Geospatial Coverage {"type": "Point", "coordinates": [117.9083, 24.39]}
Data Portal data.gov.au

Data Source

This dataset was originally found on data.gov.au "Sediment accumulation and mineralization in mangrove forests, Jiulongjiang Estuary, China". Please visit the source to access the original metadata of the dataset:
https://devweb.dga.links.com.au/data/dataset/sediment-accumulation-and-mineralization-in-mangrove-forests-jiulongjiang-estuary-china

Original dataset
Dataset copies

No duplicate datasets found.