Individual-Based Allometric Equations Accurately Measure Carbon Storage and Sequestration in Shrublands

Mason, Norman W. H.; Beets, Peter N.; Payton, I. J.; Burrows, Larry; Holdaway, Robert J.; Carswell, Fiona E.

doi:10.3390/f5020309

Cited by 25 publications

(12 citation statements)

References 20 publications

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“…Overman et al 1994;Grundy 1995;Eshete and Ståhl 1998;Pilli et al 2006;Salis et al 2006;Návar-Cháidez 2010;Suganuma et al 2012;Mason et al 2014), ignoring the fact that different tree components have distinguished uses and decomposition rates, affecting differently the storage time of carbon and nutrients (Magalhães and Seifert 2015a). Aware of that, here, the AGB is divided into 6 tree components (foliage, branches, crown, stem wood, stem bark, and stem).…”

Section: Discussionmentioning

confidence: 99%

Live above- and belowground biomass of a Mozambican evergreen forest: a comparison of estimates based on regression equations and biomass expansion factors

Magalhães

2015

For. Ecosyst.

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Background: Biomass regression equations are claimed to yield the most accurate biomass estimates than biomass expansion factors (BEFs). Yet, national and regional biomass estimates are generally calculated based on BEFs, especially when using national forest inventory data. Comparison of regression equations based and BEF-based biomass estimates are scarce. Thus, this study was intended to compare these two commonly used methods for estimating tree and forest biomass with regard to errors and biases. Methods: The data were collected in 2012 and 2014. In 2012, a two-phase sampling design was used to fit tree component biomass regression models and determine tree BEFs. In 2014, additional trees were felled outside sampling plots to estimate the biases associated with regression equation based and BEF-based biomass estimates; those estimates were then compared in terms of the following sources of error: plot selection and variability, biomass model, model parameter estimates, and residual variability around model prediction. Results: The regression equation based below-, aboveground and whole tree biomass stocks were, approximately, 7.7, 8.5 and 8.3 % larger than the BEF-based ones. For the whole tree biomass stock, the percentage of the total error attributed to first phase (random plot selection and variability) was 90 and 88 % for regression-and BEF-based estimates, respectively, being the remaining attributed to biomass models (regression and BEF models, respectively). The percent bias of regression equation based and BEF-based biomass estimates for the whole tree biomass stock were −2.7 and 5.4 %, respectively. The errors due to model parameter estimates, those due to residual variability around model prediction, and the percentage of the total error attributed to biomass model were larger for BEF models (than for regression models), except for stem and stem wood components. Conclusions: The regression equation based biomass stocks were found to be slightly larger, associated with relatively smaller errors and least biased than the BEF-based ones. For stem and stem wood, the percentages of their total errors (as total variance) attributed to BEF model were considerably smaller than those attributed to biomass regression equations.

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Section: Discussionmentioning

confidence: 99%

Live above- and belowground biomass of a Mozambican evergreen forest: a comparison of estimates based on regression equations and biomass expansion factors

Magalhães

2015

For. Ecosyst.

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“…This was rarely possible in field plots assessed in 2008 and 2012 because in most cases the measurement point was not permanently marked. Nevertheless, when determining stock changes, shrub basal diameter and height measurement errors comprised a relatively small proportion of the overall error in stock estimates, which were mostly related to shrub allometry [13].…”

Section: Data Qualitymentioning

confidence: 99%

“…In fact, good estimates were usually obtained using only 4 discs per plot, although this sample number produced poor estimates for several plots ( Figure 9). We further recommend that biomass measurements be undertaken for half of the felled plants, because allometry is an important source of the overall field measurement/model estimation error [13]. More than four biomass plants per plot would seem to be unnecessary, based on the results from the pilot study.…”

Section: Considerations Regarding Post-1989 Natural Forest Inventory mentioning

confidence: 99%

The Application of Stem Analysis Methods to Estimate Carbon Sequestration in Arboreal Shrubs from a Single Measurement of Field Plots

Beets¹,

Kimberley²,

Oliver³

et al. 2014

Forests

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Repeated measurements of plots are usually made to directly determine carbon stock changes over time. However, it is sometimes only practical or feasible to inventory plots at the end of a period of interest, and stock changes need to be predicted retrospectively from supplementary information on growth rate. This situation applied to the natural stratum of post-1989 forest in New Zealand, for which carbon sequestration over Commitment Period 1 (2008)(2009)(2010)(2011)(2012) of the Kyoto Protocol needed to be estimated from inventory data acquired in 2012. A pilot study was undertaken to test and refine methods that could be applied in the national inventory, utilizing plots that had been installed in eligible post-1989 natural forest in 2008. The plots had actual measurements and shrub biomass sampling to directly estimate carbon stocks in 2008. These plots were re-measured and sampled in 2012, and basal disc samples from plants growing adjacent to each plot collected to provide data to model stem annual increment in diameter and height of shrubs growing on the plot. We present the results of this test of methods, and discuss refinements to field procedures and calculation methods to be applied in the national inventory of this stratum of post-1989 forest in 2012.

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“…Berger, Gschwantner, McRoberts, & Schadauer (2014) assessed the effects of errors in measurements on estimating individual tree volume using Austrian national forest inventory data. Mason et al (2014) also assessed the effects of measurement errors on carbon storage estimates in shrubland. Only limited research has focused on errors created during tree measurement in tropical forests.…”

Section: Introductionmentioning

confidence: 99%

The Importance of Tree Height in Estimating Individual Tree Biomass while Considering Errors in Measurements and Allometric Models

et al. 2018

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This study evaluated the uncertainty of individual tree biomass estimated by allometric models by both including and excluding tree height independently. Using two independent sets of measurements on the same trees, the errors in the measurement of diameter at breast height and tree height were quantified, and the uncertainty of individual tree biomass estimation caused by errors in measurement was calculated. For both allometric models, the uncertainties of the individual tree biomass estimation caused by the use of a specific allometric model were also calculated. Finally, the overall uncertainty of individual tree biomass by combining the two uncertainties was calculated. The allometric model including tree height was 6 % more accurate than that excluding tree height when the uncertainty caused by allometric models became the only consideration. However, in terms of the uncertainty caused by measurement, the allometric model excluding tree height was three times more accurate than allometric model including tree height. As a result, the allometric model excluding tree height was 5 % more accurate than the allometric model including tree height when both causes of uncertainty, the allometric model and measurement errors were considered. In conclusion, errors in tree height measurement have the potential to increase the error of aboveground biomass estimation.

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Individual-Based Allometric Equations Accurately Measure Carbon Storage and Sequestration in Shrublands

Cited by 25 publications

References 20 publications

Live above- and belowground biomass of a Mozambican evergreen forest: a comparison of estimates based on regression equations and biomass expansion factors

Live above- and belowground biomass of a Mozambican evergreen forest: a comparison of estimates based on regression equations and biomass expansion factors

The Application of Stem Analysis Methods to Estimate Carbon Sequestration in Arboreal Shrubs from a Single Measurement of Field Plots

The Importance of Tree Height in Estimating Individual Tree Biomass while Considering Errors in Measurements and Allometric Models

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