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Biomass Plot Library

Biomass Plot Library

Last modified by John Armston on 2016/06/20 16:00

Biomass Plot Library - National collation of tree and shrub inventory data, allometric model predictions of above and below-ground biomass, Australia

biolib_sitemap.png

Figure 1: Location of stem inventory sites across Australia with allometric estimates of biomass

Link to the data

These datasets are not static - they are directly created from PostGIS database records and will change with ongoing data collection and improvements to the biomass plot library.

These data are currently made available via a field data portal. Information on the details of the attribute fields for the site and tree level attributes are located in this document in the section titled 'Observation attributes'.

Only the site level mean biomass estimates are currently available. The tree level data and error propagation results will be made available by May 2016.

DescriptorData link
Persistent URL or DOIhttp://www.auscover.org.au/purl/biomass-plot-library
GeoNetwork recordhttp://www.auscover.org.au/geonetwork?uuid=833bde0f-15c9-4e7a-b682-f3d7397c33ad
Field data portalhttp://qld.auscover.org.au/public/html/field/

Data licence and Access rights

ItemDetail
RightsCopyright 2016 JRSRP. Rights owned by the JRSRP. Rights licensed subject to Creative Commons Attribution (CC BY 4.0).
LicenceCreative Commons Attribution 4.0 License, https://creativecommons.org/licenses/by/4.0/.
AccessThese data can be freely downloaded and used subject to the CC BY 4.0 licence. Attribution and citation is required as described at http://www.auscover.org.au/citation. A publication on the Biomass Plot Library is forthcoming. We ask that you send us citations and copies of publications arising from work that use these data.

Overview

The Biomass Plot Library is a collation of stem inventory data across federal, state and local government departments, universities, private companies and other agencies. It was motivated to the need for calibration/validation data to underpin national mapping of above-ground biomass from integration of Landsat time-series, ICESat/GLAS lidar, and ALOS PALSAR bacscatter data under the auspices of the JAXA Kyoto & Carbon (K&C) Initiative (Armston et al., 2016). At the time of Version 1.0 publication 1,073,837 hugs of 839,866 trees across 1,467 species had been collated. This has resulted from 16,391 visits to 12,663 sites across most of Australia's bioregions. Data provided for each project by the various source organisation were imported to a PostGIS database in their native form and then translated to a common set of tree, plot and site level observations with explicit plot footprints where available (Figure 2).

biolib_plotdb (1).png

Figure 2: Plot measurement spatial database

The above-ground, below-ground and total biomass (live+dead) estimation was implemented using the generic allometric models for Australian plant functional types developed by Paul et al. (2016a,b) and decay correction factors implemented by Lucas et al. (2010). Site level estimates of biomass error were derived through comprehensive analysis of measurement and allometric model prediction errors (Roxburgh & Paul, 2016), propagating the random error (precision) associated with the development of the allometric models, all the way through to the prediction of total site biomass (Figure 3). In total eight sources of error are included, with four of these relating to errors encountered during allometric model development, with additional errors arising from diameter measurements during field inventory, allometric model prediction errors, and plot sampling and areal extent errors during field inventory. The tree level error propagation and biomass predictions were undertaken using the Carbon Analysis Tool (CAT), a software system developed by CSIRO for the Department of the Environment in support of vegetation-based greenhouse-gas mitigation activities under the Emissions Reduction Fund.

biolib_workflow_20160414.png

Figure 3: Biomass plot library workflow

Spatial and Temporal extents

ItemDetail
Typical spatial resolution0.05 - 1 ha
Spatial coverage (degrees)110.000000 to 155.001329 E, -10.000000 to -45.000512 N
Temporal resolution1 day
Temporal coverage1936-11-26 to ongoing
InstrumentDiameter tape
ItemDetail
Spatial representation typeVector
Spatial reference systemWGS 84

Point of contact

ItemDetail
NameJohn Armston
OrganisationJoint Remote Sensing Research Program (JRSRP), University of Queensland
PositionSenior Scientist
Emailj.armston@uq.edu.au
RolepointOfContact
ItemDetail
NameRichard Lucas
OrganisationJoint Remote Sensing Research Program (JRSRP), University of NSW (UNSW)
PositionProfessor
Emailrichard.lucas@unsw.edu.au
RolepointOfContact
ItemDetail
NameRebecca Trevithick
OrganisationQueensland Department of Science, Information Technology and Innovation (DSITI)
PositionSenior Scientist
Emailrebecca.trevithick@dsiti.qld.gov.au
RolepointOfContact (Field Data Portal)

Credit

The following organisations contributed to the Biomass Plot Library:

  • Commonwealth Scientific and Industrial Research Organisation (CSIRO)
  • Flinders University, South Australia
  • Victorian Department of Environment, Land, Water and Planning (DELWP)
  • Queensland Herbarium, Department of Science, Information Technology and Innovation (DSITI)
  • Western Regeneration Pty. Ltd.
  • Department of the Environment, Australia
  • Charles Darwin University, Northern Territory
  • Darwin Centre for Bushfire Research
  • NSW Office of Environment and Heritage (OEH)
  • TERN Ausplots
  • TERN Supersite Network      
  • University of New South Wales
  • University of Queensland
  • Queensland Department of Agriculture and Fisheries (DAF)
  • Forestry Tasmania
  • Queensland Remote Sensing Centre, DSITI
  • Department of Parks and Wildlife, Western Australia
  • New South Wales Forestry Corporation
  • Joint Remote Sensing Research Program

Funding for development of Biomass Plot Library and Field Data Portal was largely provided by the Queensland Department of Science, Information Technology, and Innovation through the Joint Remote Sensing Research Program.

Funding for development of the functional type allometric models was largely provided by the Department of the Environment, Australia.

Keywords

ThesauriKeyword
GCMDEARTH SCIENCE > BIOSPHERE > VEGETATION > FOREST COMPOSITION/VEGETATION STRUCTURE
EARTH SCIENCE > BIOSPHERE > VEGETATION > BIOMASS
CF
FoREnvironmental Sciences > Ecological Applications = 0501

There are three main thesauri that AusCover recommends:

  1. Global Change Master Directory (http://gcmd.nasa.gov)
  2. Climate and Forecast (CF) convention standard names (http://cfconventions.org/standard-names.html).
  3. Fields of Research codes (http://www.abs.gov.au/ausstats/abs@.nsf/0/6BB427AB9696C225CA2574180004463E?opendocument).

Data quality

Site level

  • Spatial domain - preliminary analysis indicates a relative paucity of observations in the Great Western Woodlands and Kimberley regions in Western Australia, and the savanna woodlands of Cape York in Queensland. An assessment will be presented in a forthcoming publication.
  • Temporal domain - the majority of sites were surveyed between 1995 and 2015, which is coincident with most satellite sensor data used to support regional to global above-ground biomass mapping. Site prior to 1995 are present, however additional sites will be added to the Biomass Plot Library in future in collation with state agencies that maintain long-term plot monitoring networks.
  • Attribute accuracy - A number of site observation locations were not measured using GPS units that could achieve positional accuracy <10 m. This is generally only the case for sites last surveyed prior to 2000 and is continuously improving as sites are revisited. Projects affected include long-term monitoring programs:
    • NSW Forestry Corporation commercial assets
    • WA Parks and Wildlife South-West Forests
    • Qld DSITI Herbarium Native Forest Permanent Plot Network (NFPP)
  • The Biomass Plot Library is a post-hoc collation of stem inventory data, therefore the emergent spatial and temporal distribution of data is not designed to meet the specific needs of many applications. Caveats on use include and are not limited to:
    • The Biomass Plot Library data is not the result of a stratified random sampling design, therefore should not be used directly for estimation of regional carbon stocks. This is especially the case for some projects that are biased towards large trees (e.g. sites established by Forestry Tasmania).
    • Many plots are very small in size (<0.1 ha) and should be considered in methods used to link these field data with remote sensing data.

Tree level

  • The functional type allometrics from Paul et al. (2016a,b) are not applicable to fern, palm, cycad, grass tree, and pandanus species. These are presently excluded from the Biomass Plot Library.
  • Trees less than 5 cm diameter were not included in the site level observations, so have been excluded from the tree level observations.
  • A summary of the individual tree/shrub error sources, and their relative contributions as summarised over the whole dataset, are given in Table 1. Overall, three of the error sources accounted for >98% of the total variability, with the dominant error source being the allometric model prediction error.

Table 1: The relative tree level error contributions summarised over the whole dataset   

Error sourcePercentage of total variation
Allometric model development – moisture content determination for converting fresh mass into dry mass.5.3
Allometric model development – fresh mass weighing errors0.2
Allometric model development – Diameter measurement of individual trees0.1
Allometric model development – Allometric model fit errors5.1
Inventory - individual diameter measurement errors1.1
Allometric model prediction errors88.2

References

ItemDetail or link
PresentationArmston, J., Lucas, R., Scarth, P., Gill, T., Phinn , S., Roxburgh, S. H., Paul, K. I. , Bunting, P. (2016). K&C Phase 4 – Status report. JAXA Kyoto & Carbon Initiative Phase 4 Science Team Meeting, 16th-18 February 2016, Tokyo, Japan.
PublicationLucas, R., Armston, J., Fairfax, R., Fensham, R., Accad, A., Carreiras, J., Kelley, J., Bunting, P., Clewley, D., Bray, S., Metcalfe, D., Dwyer, J., Bowen, M., Eyre, T., Laidlaw, M., & Shimada, M. (2010). An evaluation of the ALOS PALSAR L-band backscatter - Above ground biomass relationship Queensland, Australia: Impacts of surface moisture condition and vegetation structure. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 3, 576–593.
PublicationPaul, K. I., Roxburgh, S. H., Chave, J., England, J. R., Zerihun, A., Specht, A., Lewis, T., Bennett, L. T., Baker, T. G., Adams, M. A., Huxtable, D., Montagu, K. D., Falster, D. S., Feller, M., Sochacki, S., Ritson, P., Bastin, G., Bartle, J., Wildy, D., Hobbs, T., Larmour, J., Waterworth, R., Stewart, H. T., Jonson, J., Forrester, D. I., Applegate, G., Mendham, D., Bradford, M., O’Grady, A., Green, D., Sudmeyer, R., Rance, S. J., Turner, J., Barton, C., Wenk, E. H., Grove, T., Attiwill, P. M., Pinkard, E., Butler, D., Brooksbank, K., Spencer, B., Snowdon, P., O’Brien, N., Battaglia, M., Cameron, D. M., Hamilton, S., McAuthur, G., & Sinclair, J. (2016a). Testing the generality of above-ground biomass allometry across plant functional types at the continent scale. Global Change Biology, doi:10.1111/gcb.13201
PublicationPaul, K. I., Roxburgh, S. H., Chave, J., et al. (2016b). Testing the generality of total below-ground biomass allometry across plant functional types at the continent scale. In prep.
ReportRoxburgh, S. H & Paul, K. I. (2016). Comprehensive propagation of errors for the assessment of woody biomass. Report to the Department of the Environment, prepared as part of reporting requirements under the Methodology Development Grant Program (MDGP). CSIRO. Canberra.

Related products

ItemProduct link
 Terrestrial laser scanshttp://www.auscover.org.au/purl/tls-tree-models-rushworth
 Vegetation height and structurehttp://auscover.org.au/purl/icesat-vegetation-structure

Product version history

Version labelDateDetail
1.02016-04-14Initial release
1.12016-05-04Revised site level error propagation
1.22016-06-20Revised list of licenced tree level data. Inclusion of previously missing measurement data.

Observation attributes

Site level

FieldFormatDescription (units)
obs_keytextUnique identifier for site and visit for data management purposes
sourcetextOrganisation from which the data was sourced
projecttextThe project for which the data was acquired
sitetextName of the site
estsurveytextName of the survey that established the site
estdatedateStart date of the site survey that established the site (a single site survey may span several days)
surveytextName of the site survey
obs_timedateStart date of the site survey (a single site survey may span several days)
nplotsintegerNumber of plots within the site
sampledarea_hadoubleSummed area of all plots (ha)
sitearea_hadoubleSite area (ha). sitearea_ha >= totalsubplotarea_ha
sitedmindoubleMinimum tree diameter measured in the site survey
[poly_]geomgeometryMultipolygon, polygon, or point object of the plot footprint/s
longitudedoubleLongitude of site centroid
latitudedoubleLatitude of site centroid
live_basal_areadoubleLive stand basal area (m2 ha-1)
dead_basal_areadoubleDead stand basal area (m2 ha-1)
live_stem_densitydoubleLive tree number density (n ha-1)
dead_stem_densitydoubleDead tree number density (n ha-1)
agb_drymass_hadoubleAbove-ground dry standing biomass density of trees/shrubs (Mg ha-1)
agb_drymass_se_hadoubleAbove-ground dry standing biomass density standard error of trees/shrubs (Mg ha-1)
bgb_drymass_hadoubleBelow-ground dry standing biomass density of trees/shrubs (Mg ha-1)
bgb_drymass_se_hadoubleBelow-ground dry standing biomass density standard error of trees/shrubs (Mg ha-1)
tb_drymass_hadoubleTotal dry standing biomass density of trees/shrubs (Mg ha-1)
tb_drymass_se_hadoubleTotal dry standing biomass density standard error of trees/shrubs (Mg ha-1)
universal_agbdoubleFraction of above-ground dry standing biomass density predicted using the Universal allometric
universal_countdoubleFraction of individual plants that had the Universal allometric applied.
sizeclassdoubleLower bound of the 10cm diameter increment used to calculate the drymass values. Absence of this field indicates all size classes were included in the drymass values.

Tree level

FieldFormatDescription (units)
fidintegerUnique numeric identifer for data management purposes
obs_keytextUnique identifier for site and visit for data management purposes
sourcetextOrganisation from which the tree measurement was sourced
projecttextThe project for which the tree measurement was acquired
sitetextName of the site the tree is from
surveytextName of the site survey the tree was measured
obs_timedateStart date of the site survey (a single site survey may span several days)
plottextName of the plot the tree is from
subplotintegerSubplot identifier of the tree measurment for when variable size plots were used for different tree diameter classes
subplotarea_hadoubleSubplot area (ha)
subplotdmindoubleMinimum tree diameter measured in the subplot
treetextTree identifier
speciestextScientific name of the tree/shrub measured
conditionintegerTree condition code used to set the decay factor (Lucas et al., 2010)
measurementtextDiameter measurement height following tapering correction for allometric model (D10, DBH)
htdoubleTop height of tree/shrub (NULL if not measured)
nstemsintegerNumber of stems measured for the tree/shrub
diameterdoubleTaper-corrected quadratic mean diameter of the tree/shrub (explanatory variable in the allometric model)
agb_allometric_modeltextName of the functional type above-ground biomass allometric model
agb_prediction_errordoubleAbove-ground biomass allometric model prediction standard error (kg2)
agb_correction_factordoubleAbove-ground biomass correction factor
agb_predicted_lndrymassdoubleAbove-ground biomass log dry standing biomass of trees/shrubs (kg)
agb_drymass_allommcvardoubleAbove-ground biomass allometric model moisture content variance (kg2)
agb_drymass_allomfmvardoubleAbove-ground biomass allometric model fresh mass variance (kg2)
agb_drymass_allomdvardoubleAbove-ground biomass allometric model stem diameter variance (kg2)
agb_drymass_allomfitvardoubleAbove-ground biomass allometric model parameter fit variance (kg2)
agb_drymass_allompredvardoubleAbove-ground biomass allometric model prediction variance (kg2)
agb_drymass_invdvardoubleAbove-ground biomass inventory stem diameter variance (kg2)
agb_drymass_totalvardoubleAbove-ground biomass total error variance (kg2)
agb_drymassdoubleAbove-ground dry standing biomass of tree/shrub (kg)
agb_drymass_sddoubleAbove-ground dry standing biomass standard error of tree/shrub (kg)
bgb_allometric_modeltextName of the functional type below-ground biomass allometric model
bgb_prediction_errordoubleBelow-ground biomass allometric model prediction standard error (kg2)
bgb_correction_factordoubleBelow-ground biomass correction factor
bgb_predicted_lndrymassdoubleBelow-ground biomass log dry standing biomass of trees/shrubs (kg)
bgb_drymass_allommcvardoubleBelow-ground biomass allometric model moisture content variance (kg2)
bgb_drymass_allomfmvardoubleBelow-ground biomass allometric model fresh mass variance (kg2)
bgb_drymass_allomdvardoubleBelow-ground biomass allometric model stem diameter variance (kg2)
bgb_drymass_allomfitvardoubleBelow-ground biomass allometric model parameter fit variance (kg2)
bgb_drymass_allompredvardoubleBelow-ground biomass allometric model prediction variance (kg2)
bgb_drymass_invdvardoubleBelow-ground biomass inventory stem diameter variance (kg2)
bgb_drymass_totalvardoubleBelow-ground biomass total error variance
bgb_drymassdoubleBelow-ground dry standing biomass of tree/shrub (kg)
bgb_drymass_sddoubleBelow-ground dry standing biomass standard error of tree/shrub (kg)
tb_drymass_allommcvardoubleTotal biomass allometric model moisture content variance (kg2)
tb_drymass_allomfmvardoubleTotal biomass allometric model fresh mass variance (kg2)
tb_drymass_allomdvardoubleTotal biomass allometric model stem diameter variance (kg2)
tb_drymass_allomfitvardoubleTotal biomass allometric model parameter fit variance (kg2)
tb_drymass_allompredvardoubleTotal biomass allometric model prediction variance (kg2)
tb_drymass_invdvardoubleTotal biomass inventory stem diameter variance (kg2)
tb_drymass_totalvardoubleTotal biomass total error variance
tb_drymassdoubleTotal dry standing biomass of tree/shrub (kg)
tb_drymass_sddoubleTotal dry standing biomass standard error of tree/shrub (kg)

Metadata history

DateDetail
2016-04-14Metadata creation date
2016-04-21Added statement on data availability and edited tree-level attributes 
2016-05-04Edited statement on data availability and changed some attribute names 
2016-06-13Edited tree-level attributes (variance components are now reported)
Tags:
Created by John Armston on 2016/04/12 13:58

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