Allometric equations for estimating biomass in agricultural landscapes: II. Belowground biomass

Kuyah, Shem; Dietz, Johannes; Muthuri, Catherine; Jamnadass, Ramni; Mwangi, Peter; Coe, R.; Neufeldt, Henry

doi:10.1016/j.agee.2012.05.010

Cited by 113 publications

(73 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Use of a 0.2 ratio clearly underestimated belowground biomass compared with empirical data. Differences in the below to aboveground ratio results can be due to planting material and tree age, also the agro-ecological conditions of soil, climate and management practises, but also measurement methods, especially for belowground biomass (Mokany et al 2006;Kuyah et al 2012).…”

Section: Ratio Below To Aboveground Biomassmentioning

confidence: 99%

Tree or shrub: a functional branch analysis of Jatropha curcas L.

Tjeuw¹,

Mulia²,

Slingerland³

et al. 2015

Agroforest Syst

View full text Add to dashboard Cite

Jatropha curcas is an oil-bearing semievergreen shrub or small tree with potential as a source of sustainable biofuel, yet information regarding vegetative and fruit biomass in relation to plant architecture is lacking. Research conducted in Indonesia used the tree based functional branch analysis (FBA) model as a non-destructive method to estimate above and belowground biomass, and plant architecture. The FBA utility for shrubs was unknown and required modification. This research used destructive measurements to validate modifications to the FBA model that included subcategorisation of the tapering coefficient for twig, branch, and wood diameter classes, and addition of a fruit load parameter in the distal link. The modified FBA model confirmed jatropha to be a shrub rather than a tree, producing variable estimates for aboveground biomass. This variation was due to morphological plasticity in the length-diameter relationship of the branches that diverged from fractal branching architecture. Fruit biomass variation between replicates was not well estimated and total proximal root diameter was a poor predictor of total root biomass, due to the proximal roots having enlarged water storage structures that do not follow fractal branching assumptions. Jatropha fruit was shown to predominate on twigs with a diameter between 0.9 and 1.4 cm. Understanding the correlation between fruit development and plant architecture will be necessary for fine-tuning the FBA model for future commercial breeding and selection. The high degree of morphological plasticity displayed by jatropha requires consideration when determining plant biomass.

show abstract

Section: Ratio Below To Aboveground Biomassmentioning

confidence: 99%

Tree or shrub: a functional branch analysis of Jatropha curcas L.

Tjeuw¹,

Mulia²,

Slingerland³

et al. 2015

Agroforest Syst

View full text Add to dashboard Cite

show abstract

“…Many variables have proved useful for predicting BGB, such as DBH (Petersson and Ståhl 2006;Konopka et al 2011;Blujdea et al 2012), crown size (Lufafa et al 2009;Kuyah et al 2012b) and diameter at stem base (Wang 2006;Peichl and Arain 2007;Blujdea et al 2012;). In this study, we obtained good model fit using BA 0.2 , BA 1.3 and H. A major advantage of these factors is that they are variable that are biologically meaningful trait since they expressed well water-conducting area scales within a plant for optimum conductivity .…”

Section: Discussionmentioning

confidence: 99%

“…Finally, we assessed local effects on biomass allocation in the focal system by comparing equations developed in this study with previously published equations constructed for estimating BGB in dry tropical forest areas (Cairns et al 1997;Mokany et al 2006;Kuyah et al 2012b). For comparison, the best general allometric equation obtained in this study and the published equations were applied to the same data.…”

Section: Biomass Model Developmentmentioning

confidence: 99%

See 1 more Smart Citation

Allometric equations for below-ground biomass of four key woody species in West African savanna-woodlands

Koala¹,

Sawadogo²,

Savadogo³

et al. 2017

Silva Fenn.

View full text Add to dashboard Cite

Highlights• Species-specific equations for belowground biomass (BGB) predicted biomass with less bias than generic equations.• All the generic equations underestimated BGB.• For accurate estimation of BGB in savanna-woodlands, species-specific equations are needed for more species. AbstractAccurate estimates of both above-ground biomass (AGB) and below-ground biomass (BGB) are essential for estimating carbon (C) balances at various geographical scales and formulating effective climate change mitigation programs. However, estimating BGB is challenging, particularly for forest ecosystems, so robust allometric equations are needed. To obtain such equations for savanna-woodlands of the West African north sudanian zone, we selected four common native woody species (Anogeissus leiocarpa (DC.) Guill. & Perr., Detarium microcarpum Guill. & Perr., Piliostigma thonningii (Schumach.) Milne-Redh. and Vitellaria paradoxa C.F. Gaertn.). At two sites in Burkina Faso, we determined the BGB of 30 trees of each of these species by excavation, and measured various above-ground dimensional variables. The root:shoot ratio varied widely among the species, from 0.1 to 3.4. Depending on the species, allometric equations based on stem basal area at 20 cm height, basal area at breast height and tree height explained 50-95% of the variation in BGB. The best generic equation we obtained, based on basal area at 20 cm, explained 60% of the variation in BGB across the species. Three previously published generic allometric equations underestimated BGB by 8 to 63%. The presented equations should significantly improve the accuracy of BGB estimates in savanna-woodlands and help avoid costly needs to excavate root systems.

show abstract

“…While the sampling error can be reduced by optimizing the sampling design, improving the quality of the equations and the methodology to select and use them can reduce the model error. Various authors report significant differences in forest biomass and carbon stock estimates depending on the used model (Kenzo et al 2009;Melson et al 2011;Alvarez et al 2012;Kuyah et al 2012;Ngomanda et al 2014). The adequate development and use of tree models are a key to improve the robustness of forest carbon and stock change estimates.…”

Section: Introductionmentioning

confidence: 99%