Above- and Belowground Biomass Models for Trees in the Miombo Woodlands of Malawi

Kachamba, Daud Jones; Eid, Tron; Gobakken, Terje

doi:10.3390/f7020038

Cited by 56 publications

(56 citation statements)

References 36 publications

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“…The RS-ratio varied significantly between dbh classes with a high RS-ratio for small trees and lower RS-ratios for larger trees (Table 3). A similar pattern for miombo woodland trees was observed by [22] who found that the RS-ratio was decreasing significantly and non-linearly with increasing dbh. The use of RS-ratio is recommended for estimating belowground biomass in cases where models are not available [23] and mean RS-ratios are frequently applied to estimate belowground biomass [24].…”

Section: Discussionsupporting

confidence: 84%

Models Predicting Above- and Belowground Biomass of Thicket and Associate Tree Species in Itigi Thicket Vegetation of Tanzania

Makero¹

2016

AFF

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Itigi thicket is a unique vegetation type for Tanzania and is regarded as ecologically sensitive, thus earmarked for conservation. The objective of this study was to develop species-specific biomass models for two dominating thicket species and mixed-species biomass models for associate trees in Itigi thicket vegetation. Data were collected through destructive sampling (60 thicket clumps and 30 associate trees) and covered two dominant thicket species: Combretum celastroides Laws and Pseudoprosopsis fischeri (Tab) Harms and five dominant associate tree species: Canthium burtii Bullock sensu R. B. Drumm, Cassipourea mollis (R. E. Fr.) Alston, Haplocoelum foliolosum L, Lannea fulva (Engl.) England Vangueria madagascariensis J. F. Gmelin. Different nonlinear multiplicative model forms were tested, and models were selected based on Akaike Information Criterion. Large parts of the variation in biomass of thicket clumps were explained by basal area weighed mean diameter at breast height of stems in the clump and number of stems in the clump, i.e. for aboveground biomass (AGB) and belowground biomass (BGB) of C. celastroides up to 89% and 82% respectively and for AGB and BGB of P. fischeri up to 96% and 95% respectively. For associate trees most variation was explained by diameter at breast height (dbh) alone, i.e. up to 85% and 69% for ABG and BGB respectively. Although there will be some uncertainties related to biomass estimates for large areas, for practical reasons, we recommend the selected models to be applied to the entire area where Itigi thicket extends outside our study site, and also to those thicket and associate tree species present that were not included in the data used for modelling.

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Section: Discussionsupporting

confidence: 84%

Models Predicting Above- and Belowground Biomass of Thicket and Associate Tree Species in Itigi Thicket Vegetation of Tanzania

Makero¹

2016

AFF

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“…This strongly indicates that the species allocates more biomass to root in colder sites, namely, the root-shoot ratio increases latitudinally [37]. In addition, the root-shoot ratio is an important factor for estimating belowground biomass when biomass models are not available [38].…”

Section: Discussionmentioning

confidence: 99%

Fine Root Biomass and Its Relationship with Aboveground Traits of Larix gmelinii Trees in Northeastern China

Meng

Jia

Zhou

et al. 2018

Forests

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Fine roots play a prominent role in forest carbon flux, nutrient and water acquisition; however, information on fine roots remains scarce due to the limitation of measuring methods. In this study, a nested regression method was used to estimate the biomass and surface area of fine roots of individual Larix gmelinii trees that dominate northernmost China. Aboveground traits including leaf biomass, leaf area, stem volume and aboveground biomass were also investigated. In particular, the relationships between leaves and fine roots, in terms of biomass and area, were examined. The results revealed that allometric models of fine roots, total roots, and leaves consistently fit well with Adj. R 2 = 0.92-0.97. The root-shoot ratio at the individual tree level was approximately 0.28. There were robust positive linear correlations between absorption (fine root biomass, fine root surface area) and production (leaf biomass, leaf area) (Adj. R 2 = 0.95, p < 0.001). In conclusion, the close coupling between fine roots and leaves presented in this study provides support for the theory of functional equilibrium.

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“…For each tree in respective sample plots, we calculated biomass by using a model developed by Kachamba, et al [47] with dbh and ht as independent variables: Before calculating biomass, we predicted the ht of trees whose heights were not measured in the respective sample plots using a height-diameter model developed from the sample trees from all sample plots:…”

Section: Sampling Design and Ground Reference Data Collectionmentioning

confidence: 99%

Biomass Estimation Using 3D Data from Unmanned Aerial Vehicle Imagery in a Tropical Woodland

et al. 2016

Self Cite

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Application of 3D data derived from images captured using unmanned aerial vehicles (UAVs) in forest biomass estimation has shown great potential in reducing costs and improving the estimates. However, such data have never been tested in miombo woodlands. UAV-based biomass estimation relies on the availability of reliable digital terrain models (DTMs). The main objective of this study was to evaluate application of 3D data derived from UAV imagery in biomass estimation and to compare impacts of DTMs generated based on different methods and parameter settings. Biomass was modeled using data acquired from 107 sample plots in a forest reserve in miombo woodlands of Malawi. The results indicated that there are no significant differences (p = 0.985) between tested DTMs except for that based on shuttle radar topography mission (SRTM). A model developed using unsupervised ground filtering based on a grid search approach, had the smallest root mean square error (RMSE) of 46.7% of a mean biomass value of 38.99 Mg·ha −1 . Amongst the independent variables, maximum canopy height (Hmax) was the most frequently selected. In addition, all models included spectral variables incorporating the three color bands red, green and blue. The study has demonstrated that UAV acquired image data can be used in biomass estimation in miombo woodlands using automatically generated DTMs.

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Above- and Belowground Biomass Models for Trees in the Miombo Woodlands of Malawi

Cited by 56 publications

References 36 publications

Models Predicting Above- and Belowground Biomass of Thicket and Associate Tree Species in Itigi Thicket Vegetation of Tanzania

Models Predicting Above- and Belowground Biomass of Thicket and Associate Tree Species in Itigi Thicket Vegetation of Tanzania

Fine Root Biomass and Its Relationship with Aboveground Traits of Larix gmelinii Trees in Northeastern China

Biomass Estimation Using 3D Data from Unmanned Aerial Vehicle Imagery in a Tropical Woodland

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