Developing general allometric relationships for regional estimates of carbon sequestration—an example using Eucalyptus pilularis from seven contrasting sites

Montagu, KD; Duttmer, K; Barton, C. V.M.; Cowie, Annette

doi:10.1016/j.foreco.2004.09.003

Cited by 115 publications

(80 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…For example, Dietz and Kuyah (2011) recommend first identifying the likely diameter range of application, and then dividing that range into 5-6 equal strata, with random selection of an equal number of individuals per stratum. An example of the implementation of this strategy is Montagu et al (2005). This approach has also been specified in carbon sequestration legislation (CFI 2013).…”

Section: Simulation Designmentioning

confidence: 99%

“…What is clear is that differences in the variability of tree sizes within the population that an allometric model is to be applied, relative to the variability of tree sizes used to construct the model, can have an important implications for the resulting biomass predictions. This should be taken into account wherever possible, e.g., whenever allometric models have been constructed with individuals sampled evenly on the natural or logarithmic scales (Scenarios 2-6; Montagu et al 2005, Dietz and Kuyah 2011, CFI 2013.…”

Section: Recommendationsmentioning

confidence: 99%

See 1 more Smart Citation

Guidelines for constructing allometric models for the prediction of woody biomass: How many individuals to harvest?

et al. 2015

View full text Add to dashboard Cite

Abstract. The recent development of biomass markets and carbon trading has led to increasing interest in obtaining accurate estimates of woody biomass production. Aboveground woody biomass (B) is often estimated indirectly using allometric models, where representative individuals are harvested and weighed, and regression analyses used to generalise the relationship between individual mass and more readily measured non-destructive attributes such as plant height and stem diameter (D). To satisfy regulatory requirements and/or to provide market confidence, allometric models must be based on sufficient data to ensure predictions are accurate, whilst at the same time being practically and financially achievable.Using computer resampling experiments and allometric models of the form B ¼ aD b the trade-off between increasing the sample size of individuals to construct an allometric model and the accuracy of the resulting biomass predictions was assessed. A range of algorithms for selecting individuals across the stem diameter size-class range were also explored. The results showed marked variability across allometric models in the required number of individuals to satisfy a given level of precision. A range of 17-95 individuals were required to achieve biomass predictions with a standard deviation within 5% of the mean for the best performing stem diameter selection algorithm, while 25-166 individuals were required for the poorest. This variability arises from (a) inherent uncertainty in the relationship between diameter and biomass across allometric models, and (b) differences between the diameter size-class distribution of individuals used to construct a model, and the diameter size-class distribution of the population to which the model is applied. Allometric models are a key component of quantifying land-based sequestration activities, but despite their importance little attention has been given to ensuring the methods used in their development will yield sufficiently accurate biomass predictions. The results from this study address this gap and will be of use in guiding the development of new allometric models; in assessing the suitability of existing allometric models; and in facilitating the estimation of uncertainty in biomass predictions.

show abstract

Section: Simulation Designmentioning

confidence: 99%

Section: Recommendationsmentioning

confidence: 99%

Guidelines for constructing allometric models for the prediction of woody biomass: How many individuals to harvest?

et al. 2015

View full text Add to dashboard Cite

show abstract

“…Therefore, estimates of the total above-ground biomass in forest ecosystems are critical for carbon dynamics studies, as plant biomass is an important indicator in carbon sequestration. The amount of carbon sequestered can be inferred from the biomass change since 50% of the forest dry biomass is approximately carbon (Losi et al 2003;Montagu et al 2005). For this purpose, one needs to know how much biomass is lost or accumulated over time.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Timber Harvest in Tropical Rainforest Ecosystem of South West Nigeria and Its Implication on Carbon Sequestration

Adekunle¹,

Lawal²,

Olagoke³

2014

Journal of Forest and Environmental Science

View full text Add to dashboard Cite

Timber harvest in natural forests and its implications on carbon sequestration were investigated in the Southwestern Nigeria. Data on timber harvest from forest estates for a 3-year period were collected from the official record of States' Forestry Department. The data registered the species, volume and number of timbers exploited during the study period. The data were analyzed accordingly for rate of timber harvest and carbon value of the exploited timbers using existing biomass functions. Values were compared for significant differences among states using one way analysis of variance. The results showed that the most exploited logs, in terms of volume and number of trees, have the highest amount of carbon removal. There was a variation in type of timber species being exploited from each state. The total number of harvested trees from Oyo, Ondo, Ogun, Ekiti and Osun were estimated at 100,205; 111,789; 753; 15,884 and 18,153 respectively. Total quantity of carbon removed for the 3-year period stood at 2.3 million metric tons, and this translated to 8.4 million metric tons of CO2. The annual carbon and CO2 removal therefore were estimated at 760,120.73 tons and 2.8 million tons/ year respectively. There were significant differences (p＜0.05) in the amount of CO2 removed from the five states. Based on our result, we inferred that there is increasing pressure on economic tree species and it is plausible that they are becoming scarce from the forests in Southwestern Nigeria.. If the present rate of log removal is not controlled, forests could become carbon source rather than carbon sink and the on biological conservation, wood availability and climate change may turn out grave. For the forest to perform its environmental role as carbon sink, urgent conservation measures and logging policies are needed to be put in place.

show abstract

“…Further, the Ratio estimate was found to have lower bias and increased accuracy at the plot level than the Smearing and REML estimates when validated against whole-plot harvests of woody vegetation in the Sonoran Desert (Búrquez and Martínez-Yrízar 2011). Based on its low bias relative to these two other correction factors, Snowdon's Ratio correction factor has been commonly applied in the field of tree allometrics (e.g., Montagu et al 2005;Paul et al 2008). Here we found that although Snowdon's Ratio estimate performed better than several of the other estimates in terms of bias (see Table 2), as a predictor it performed relatively poorly.…”

Section: Discussionmentioning

confidence: 99%

Correction factors for unbiased, efficient estimation and prediction of biomass from log–log allometric models

Clifford

Cressie

England

et al. 2013

Forest Ecology and Management

View full text Add to dashboard Cite

Highlights:• We review nine alternatives for correcting bias in log-log allometrics.• We use simulations to evaluate the ability of these to estimate average biomass.• We evaluate their ability to predict biomass of new trees.• Methods not commonly used in forest science performed best. AbstractAllometric relationships are commonly used to estimate average biomass of trees of a particular size and to predict biomass of individual trees based on an easily measured covariate variable such as stem diameter. They are typically power relationships which, for the purpose of data fitting, are transformed using natural logarithms to convert the model to its linear equivalent.Implementation of these equations to estimate the relationships and to predict biomass of new trees on the natural (i.e., actual) scale requires back-transforming the logarithmic predictions.Because these transformations involve non-linearity, care must be taken during this step to avoid bias. Several correction factors have been proposed in the literature for removing the gross bias in estimates, but their performance as predictors of biomass has not yet been examined. This is a very important problem, and here we review nine such correction factors in terms of their abilities to estimate biomass and predict biomass for new trees. We compare their performance by examining their bias and variability based on large datasets of above-ground biomass and stem diameter for eight species of harvested trees and shrubs in the genera Eucalyptus and Acacia (n = 102-365 individuals per species). We found that good estimates of average biomass turned out to be good predictors of biomass for new trees. The linear model fitted has log of the above-ground biomass as the response variable and log of the stem diameter as the covariate. The only exactly unbiased estimate among those considered was the uniform minimum variance unbiased (UMVU) estimate, which involves evaluating a confluent hypergeometric function to obtain its correction factor. Three alternative correction factors that are easy to compute also performed well. One of these minimises mean squared error and was found to result in low bias, low prediction bias, the lowest mean squared error, and the lowest mean squared prediction error among all correction factors examined.

show abstract

Developing general allometric relationships for regional estimates of carbon sequestration—an example using Eucalyptus pilularis from seven contrasting sites

Cited by 115 publications

References 25 publications

Guidelines for constructing allometric models for the prediction of woody biomass: How many individuals to harvest?

Guidelines for constructing allometric models for the prediction of woody biomass: How many individuals to harvest?

Assessment of Timber Harvest in Tropical Rainforest Ecosystem of South West Nigeria and Its Implication on Carbon Sequestration

Correction factors for unbiased, efficient estimation and prediction of biomass from log–log allometric models

Contact Info

Product

Resources

About