Brief description
The dataset contains maps of total % C3 and C4 plant cover, proportional C3 and C4 vegetation (relative to combined C3 and C4 cover), and vegetation δ13C isoscape (stable carbon isotope values) across Australia. Data are centered on year 2015. We used vegetation and land-use rasters to categorize grid-cells (100 m2) into woody (C3), native herbaceous (C3 and C4), and herbaceous cropland (C3 and C4) cover. TERN Ecosystem Surveillance field surveys and environmental factors were regressed to predict native C4 herbaceous cover. These layers were combined and a δ13C mixing model was used to calculate site-averaged δ13C values.Notes
Data ProcessingData were analysed in the R statistical environment (R Core Team 2019). TERN plot data were imported using the ‘ausplotsR’ package, a package which enables the import and analysis TERN plot survey data
The Australian δ13C vegetation isoscape was constructed using data primarily sourced for the year 2015. Climate conditions in 2015 for Australia were considered average and fire occurrence and intensity were relatively low. Thus, a 2015 isoscape should be a good representation of modern average conditions in Australia. The % woody cover layer was designated 100% C3 vegetation. This introduces a potential source of error because some groups of shrubs may use either C3 or C4 photosynthesis. We were unable to identify an accurate way to distinguish and model C4 shrub cover. Consequently, we made the simplifying assumption that all woody cover is C3. In some grid cells the total % C3 cover values exceed 100%. This is because % C3 cover includes both % woody cover and the % C3 herbaceous cover that may be growing beneath the % woody cover, as described in Munroe et al. (2022). Because our approach assumed all woody cover was C3, % C4 cover never exceeded 100%.
C3, C4 and δ13C maps can be used to quantify and compare C3 and C4 distribution at a landscape scale. Isoscapes are useful in the study of food web dynamics and animal migration. These data could also be used to calculate fractional productivity of different photosynthetic pathways.
Lineage
We used vegetation and land-use rasters to categorize grid-cells (100 m2) into woody (C3), native herbaceous, and herbaceous cropland (C3 and C4) cover. Field surveys and environmental factors were regressed to predict native C4 herbaceous cover. These layers were combined and a δ13C mixing model was used to calculate site-averaged δ13C values.
Notes
CreditWe at TERN acknowledge the Traditional Owners and Custodians throughout Australia, New Zealand and all nations. We honour their profound connections to land, water, biodiversity and culture and pay our respects to their Elders past, present and emerging.
This work was funded by the Terrestrial Ecosystem Research Network (TERN), an Australian Government National Collaborative Research Infrastructure Strategy (NCRIS) project.
The purpose of this work was to create maps of C3 and C4 abundance in Australia, and a vegetation δ13C isoscape for the continent. Maps of C3 and C4 plant abundance and stable carbon isotope values (δ13C) across terrestrial landscapes are valuable tools in ecology to investigate species distribution and carbon exchange. Australia has a predominance of C4-plants, thus monitoring change in C3:C4 cover and δ13C is essential to national management priorities.
Data Quality Assessment Scope
local :
dataset
To assess the accuracy of the final % C<sub>4</sub> vegetation layer, we compared the predicted % C<sub>4</sub> vegetation layer outputs to the proportional % C<sub>4</sub> vegetation observed at all TERN Ecosystem Surveillance plots. We used a linear regression to quantify relationships between predicted and observed % C<sub>4</sub> vegetation values. We also compared the residual values of predicted and observed % C<sub>4</sub> vegetation in different major vegetation groups (MVG), as determined by onsite evaluations by TERN survey teams. We compared predicted leaf-δ<sup>13</sup>C values to soil organic matter (SOM) δ<sup>13</sup>C values determined samples collected at 51 TERN plots.
Data Quality Assessment Result
local :
Quality Result
Comparisons between predicted and observed % C<sub>4</sub> vegetation at TERN plots returned residuals ranging from -63.4 to 73.4% (mean ± sd = 9.1 ± 24.5) and a RMSE of 26.1%. Linear regression analysis comparing predicted and observed proportional C<sub>4</sub> vegetation resulted in an adjusted-R<sup>2</sup> of 0.44. Comparisons of residuals between major vegetation group classifications revealed that residuals were smallest in heathlands, eucalypt woodlands and forests, and tussock grasses, but were largest in <em>Acacia</em>- and <em>Melaleuca</em>- dominated habitats. Comparisons between predicted leaf and soil δ<sup>13</sup>C isotope values returned a RMSE of 2.1‰. Residuals ranged from -5.40‰ to 5.44‰ with a mean value of 0.26‰ (±2.12). The line of best fit had a slope of 0.74, an intercept of -6.0, and an adjusted-R<sup>2</sup> of 0.71.
Created: 2018-09-15
Issued: 2024-09-19
Modified: 2024-09-24
Data time period: 2018-09-15
text: Continental Australia
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Point-of-truth metadata URL
A vegetation carbon isoscape for Australia built by combining continental-scale field surveys with remote sensing
- URI : geonetwork.tern.org.au/geonetwork/srv/eng/catalog.search#/metadata/dea845e6-f053-409a-b0ae-c37e3af3e9bb
- global : dea845e6-f053-409a-b0ae-c37e3af3e9bb
