Comparison among allometric models for tree biomass estimation using non-destructive trees’ data

ABSTRACT Current tree biomass estimation techniques generally use remote sensing data and allometric models for validation, which relate non-destructive parameters to plant biomass, usually employing diameter at the plant base or breast height and plant height. In the Caatinga Biome, many plants present multiple stems, thus making it difficult to measure the plant diameter, and lost branches, which are difficult to correct for. Hence, there is a need for suitable models for Caatinga plants, as well as studies on the possibility of using other parameters. For this study, plant and branch basal diameter, plant height, and crown area of Croton sonderianus plants were measured, and plants were also collected and weighed. Several classic models and their variations were tested. The best models were variations of Naslund (R2 = 0.92; rmse = 1,221) and Schumacher & Hall (R2 = 0.92; rmse = 1,217). Plant height and crown area enables a better biomass estimation than using plant or branch basal diameter.

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Using photography to estimate above-ground biomass of small trees

Journal of Tropical Ecology ◽

10.1017/s0266467420000139 ◽

2020 ◽

pp. 1-7

Author(s):

Brandon R. Hays ◽

Corinna Riginos ◽

Todd M. Palmer ◽

Benard C. Gituku ◽

Jacob R. Goheen

Keyword(s):

Cost Effective ◽

Allometric Equation ◽

Biomass Estimation ◽

Above Ground Biomass ◽

Tree Biomass ◽

East African ◽

Ground Biomass ◽

Herbivore Exclusion ◽

Significant Difference ◽

Allometric Relation

Abstract Quantifying tree biomass is an important research and management goal across many disciplines. For species that exhibit predictable relationships between structural metrics (e.g. diameter, height, crown breadth) and total weight, allometric calculations produce accurate estimates of above-ground biomass. However, such methods may be insufficient where inter-individual variation is large relative to individual biomass and is itself of interest (for example, variation due to herbivory). In an East African savanna bushland, we analysed photographs of small (<5 m) trees from perpendicular angles and fixed distances to estimate above-ground biomass. Pixel area of trees in photos and diameter were more strongly related to measured, above-ground biomass of destructively sampled trees than biomass estimated using a published allometric relation based on diameter alone (R2 = 0.86 versus R2 = 0.68). When tested on trees in herbivore-exclusion plots versus unfenced (open) plots, our predictive equation based on photos confirmed higher above-ground biomass in the exclusion plots than in unfenced (open) plots (P < 0.001), in contrast to no significant difference based on the allometric equation (P = 0.43). As such, our new technique based on photographs offers an accurate and cost-effective complement to existing methods for tree biomass estimation at small scales with potential application across a wide variety of settings.

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Closing a gap in tropical forest biomass estimation: taking crown mass variation into account in pantropical allometries

Biogeosciences ◽

10.5194/bg-13-1571-2016 ◽

2016 ◽

Vol 13 (5) ◽

pp. 1571-1585 ◽

Cited By ~ 36

Author(s):

Pierre Ploton ◽

Nicolas Barbier ◽

Stéphane Takoudjou Momo ◽

Maxime Réjou-Méchain ◽

Faustin Boyemba Bosela ◽

...

Keyword(s):

Tropical Forest ◽

Reference Model ◽

Original Data ◽

Carbon Stocks ◽

Forest Carbon ◽

Biomass Estimation ◽

Systematic Bias ◽

Data Set ◽

Allometric Models ◽

Large Trees

Abstract. Accurately monitoring tropical forest carbon stocks is a challenge that remains outstanding. Allometric models that consider tree diameter, height and wood density as predictors are currently used in most tropical forest carbon studies. In particular, a pantropical biomass model has been widely used for approximately a decade, and its most recent version will certainly constitute a reference model in the coming years. However, this reference model shows a systematic bias towards the largest trees. Because large trees are key drivers of forest carbon stocks and dynamics, understanding the origin and the consequences of this bias is of utmost concern. In this study, we compiled a unique tree mass data set of 673 trees destructively sampled in five tropical countries (101 trees > 100 cm in diameter) and an original data set of 130 forest plots (1 ha) from central Africa to quantify the prediction error of biomass allometric models at the individual and plot levels when explicitly taking crown mass variations into account or not doing so. We first showed that the proportion of crown to total tree aboveground biomass is highly variable among trees, ranging from 3 to 88 %. This proportion was constant on average for trees < 10 Mg (mean of 34 %) but, above this threshold, increased sharply with tree mass and exceeded 50 % on average for trees ≥  45 Mg. This increase coincided with a progressive deviation between the pantropical biomass model estimations and actual tree mass. Taking a crown mass proxy into account in a newly developed model consistently removed the bias observed for large trees (> 1 Mg) and reduced the range of plot-level error (in %) from [−23; 16] to [0; 10]. The disproportionally higher allocation of large trees to crown mass may thus explain the bias observed recently in the reference pantropical model. This bias leads to far-from-negligible, but often overlooked, systematic errors at the plot level and may be easily corrected by taking a crown mass proxy for the largest trees in a stand into account, thus suggesting that the accuracy of forest carbon estimates can be significantly improved at a minimal cost.

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Estimation on the Change of Above-Ground Carbon Stock in Arboretum University of Lampung

Jurnal Sylva Lestari ◽

10.23960/jsl2651-59 ◽

2018 ◽

Vol 6 (2) ◽

pp. 51

Author(s):

Kristian Gomos Banjarnahor ◽

Agus Setiawan ◽

Arief Darmawan

Keyword(s):

Carbon Stock ◽

The Body ◽

Total Carbon ◽

Biomass Estimation ◽

Total Biomass ◽

Biomass Carbon ◽

Process Plants ◽

Carbon Dioxide Co2 ◽

Non Destructive ◽

Earth Temperature

Carbon dioxide (CO2) is a greenhouse gas that could increase earth temperature. Through the photosynthesis process, plants absorb CO2 then convert it into carbohydrates, then sequester it in the body of plants. The purpose of the study is to estimate the changes in the carbon stock at the Arboretum University of Lampung. The methods used were stock difference by counting the carbon changes or difference between carbon stored in 2010 and 2016. While the stand biomass estimation measured by trees general allometric equations with non-destructive sampling. The results showed that the total carbon was 46% of the total biomass. Carbon stock in 2016 were about 226.75 ton/ha, showing an increase of 59.72% or 84.78 ton/ha compared to in 2010’s. The increase was due to additional growth of 804 trees as a result of plantation activity and natural regeneration. Keywords: Arboretum, biomass, carbon, necromass, University of Lampung.

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Ground reference data for sugarcane biomass estimation in São Paulo state, Brazil

Scientific Data ◽

10.1038/sdata.2018.150 ◽

2018 ◽

Vol 5 (1) ◽

Cited By ~ 4

Author(s):

Ramses A. Molijn ◽

Lorenzo Iannini ◽

Jansle Vieira Rocha ◽

Ramon F. Hanssen

Keyword(s):

Reference Data ◽

Growth Dynamics ◽

Sao Paulo ◽

Biomass Estimation ◽

São Paulo ◽

Satellite Measurements ◽

Paulo State ◽

São Paulo State ◽

Non Destructive ◽

Production Dynamics

Abstract In order to make effective decisions on sustainable development, it is essential for sugarcane-producing countries to take into account sugarcane acreage and sugarcane production dynamics. The availability of sugarcane biophysical data along the growth season is key to an effective mapping of such dynamics, especially to tune agronomic models and to cross-validate indirect satellite measurements. Here, we introduce a dataset comprising 3,500 sugarcane observations collected from October 2014 until October 2015 at four fields in the São Paulo state (Brazil). The campaign included both non-destructive measurements of plant biometrics and destructive biomass weighing procedures. The acquisition plan was designed to maximize cost-effectiveness and minimize field-invasiveness, hence the non-destructive measurements outnumber the destructive ones. To compensate for such imbalance, a method to convert the measured biometrics into biomass estimates, based on the empirical adjustment of allometric models, is proposed. In addition, the paper addresses the precisions associated to the ground measurements and derived metrics. The presented growth dynamics and associated precisions can be adopted when designing new sugarcane measurement campaigns.

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