A regional allometry for the Congo basin forests based on the largest ever destructive sampling

Fayolle, Adeline; Ngomanda, Alfred; Mbasi, Michel; Barbier, Nicolas; Bocko, Yannick E.; Boyemba, Faustin; Couteron, Pierre; Fonton, Noël; Kamdem, Narcisse Guy; Katembo, John; Kondaoule, Henriette Josiane; Loumeto, Jean Joël; Maïdou, Hervé; Mankou, Géraud Sidoine; Mengui, Thomas; Mofack, Gislain Ii; Moundounga, Cynel; Moundounga, Quentin; Nguimbous, Lydie; Nchama, Norberto Nsue; Obiang, Diosdado; Asue, Francisco Ondo Meye; Picard, Nicolas; Rossi, Vivien; Senguela, Yvon-Patrick; Sonké, Bonaventure; Viard, Lionel; Yongo, Olga Diane; Zapfack, Louis; Medjibe, Vincent P.

doi:10.1016/j.foreco.2018.07.030

Cited by 50 publications

(65 citation statements)

References 43 publications

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“…Allometric models are calibrated through destructive tree harvests requiring enormous amounts of fieldwork to cut down and weigh every tree compartment. Despite the growing number of studies aimed at calibrating allometric equations [4][5][6] , only a few thousand tropical trees have been sampled for this purpose so far, including very few large trees despite their specific architecture 7 and disproportionate contribution to forest AGB 8 . This destructive method therefore offers limited promise for providing representative allometric equations for the estimated three trillion trees on Earth 9 .…”

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confidence: 99%

“…Here, we use a unique destructive dataset collating six sampling sites in different countries and contrasted types of terra firme forests across the Congo basin 5 to determine the vertical variation in WD among 822 individuals (sampled across size classes) representing a total of 51 tropical tree species; we examine possible evolutive or functional drivers and implications for AGB estimation from volumetric (TLS) data; and we propose a way to correct the aforementioned bias in a cost-efficient way.…”

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confidence: 99%

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Leveraging Signatures of Plant Functional Strategies in Wood Density Profiles of African Trees to Correct Mass Estimations From Terrestrial Laser Data

Takoudjou¹,

Ploton²,

Martin-Ducup³

et al. 2020

Sci Rep

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Wood density (WD) relates to important tree functions such as stem mechanics and resistance against pathogens. this functional trait can exhibit high intraindividual variability both radially and vertically. With the rise of LiDAR-based methodologies allowing nondestructive tree volume estimations, failing to account for WD variations related to tree function and biomass investment strategies may lead to large systematic bias in AGB estimations. Here, we use a unique destructive dataset from 822 trees belonging to 51 phylogenetically dispersed tree species harvested across forest types in Central Africa to determine vertical gradients in WD from the stump to the branch tips, how these gradients relate to regeneration guilds and their implications for AGB estimations. We find that decreasing WD from the tree base to the branch tips is characteristic of shade-tolerant species, while light-demanding and pioneer species exhibit stationary or increasing vertical trends. Across all species, the WD range is narrower in tree crowns than at the tree base, reflecting more similar physiological and mechanical constraints in the canopy. Vertical gradients in WD induce significant bias (10%) in AGB estimates when using database-derived speciesaverage WD data. However, the correlation between the vertical gradients and basal WD allows the derivation of general correction models. With the ongoing development of remote sensing products providing 3D information for entire trees and forest stands, our findings indicate promising ways to improve greenhouse gas accounting in tropical countries and advance our understanding of adaptive strategies allowing trees to grow and survive in dense rainforests. Terrestrial plants account for 83% of the living carbon on Earth 1 , of which tropical forests are estimated to account for close to half 2 , principally contained within woody plant parts. Tropical forests are therefore becoming a key element in international carbon trading schemes despite obvious difficulties in accurately estimating stocks

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confidence: 99%

mentioning

confidence: 99%

Leveraging Signatures of Plant Functional Strategies in Wood Density Profiles of African Trees to Correct Mass Estimations From Terrestrial Laser Data

Takoudjou¹,

Ploton²,

Martin-Ducup³

et al. 2020

Sci Rep

Self Cite

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“…A recently updated georegional model by Fayolle et al. () performed similarly to the previously published N1 and N2 equations, overestimating total AGB by an average of 5% (minimum = −6%; maximum = +13%; Appendix : Fig. S2).…”

Section: Resultsmentioning

confidence: 58%

“…5c) variation in AGB/ha, whereas the published equations varied between overestimating total AGB by up to 21% (equivalent to 80 Mg/ha) to underestimating total AGB by 38% (equivalent to 150 Mg/ha). A recently updated georegional model by Fayolle et al (2018) performed similarly to the previously published N1 and N2 equations, overestimating total AGB by an average of 5% (minimum = À6%; maximum = +13%; Appendix S1: Fig. S2).…”

Section: Soil Type Is the Key Driver Of Bias In Allometric Modelsmentioning

confidence: 89%

Landscape‐level validation of allometric relationships for carbon stock estimation reveals bias driven by soil type

Beirne

Miao

Núñez

et al. 2019

Ecological Applications

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Mitigation of climate change depends on accurate estimation and mapping of terrestrial carbon stocks, particularly in carbon dense tropical forests. Allometric equations can be used to robustly estimate biomass of tropical trees, but often require tree height, which is frequently unknown. Researchers and practitioners must, therefore, decide whether to directly measure a subset of tree heights to develop diameter : height (D:H) equations or rely on previously published generic equations. To date, studies comparing the two approaches have been spatially restricted and/or not randomly allocated across the landscape of interest, making the implications of deciding whether or not to measure tree heights difficult to determine. To address this issue, we use inventory data from a systematic-random forest inventory across Gabon (102 forest sites; 42,627 trees, including 7,036 height-measured trees). Using plot-specific models of D:H as a benchmark, we compare the performance of a suite of locally fitted and commonly used generic models (parameterized national, georegional, and pantropical equations) across a variety of scales, and assess which abiotic, anthropogenic, and topographical covariates contribute the most to bias in height estimation. We reveal marked spatial structure in the magnitude and direction of bias in tree height estimation using all generic models, due at least in part to soil type, which compounded to substantial error in site-level AGB estimates (of up to 38% or 150 Mg/ha). However, two generic pantropical models (Chave 2014; Feldpausch 2012) converged to within 2.5% of mean AGB at the landscape scale. Our results suggest that some (not all) pantropical equations can extrapolate AGB across large spatial scales with minimal bias in estimated mean AGB. However, extreme caution must be taken when interpreting the AGB estimates from generic models at the site-level as they fail to capture substantial spatial variation in D:H relationships, which could lead to dramatic under-or over-estimation of site-level carbon stocks. Validated allometric models derived at site-or soil-type-levels may be the best way to reduce such biases arising from landscape-level heterogeneity in D:H model fit in the Afrotropics.

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“…This holds true across a wide range of values for the predictor variables and broad bioclimatic gradients, from dry forest woodlands to tropical rainforests. Recent work based on an extensive destructive harvest experiment in African tropical forests suggests that relatively simple biomass models are transferable (Fayolle et al, 2018), and could therefore be useful in biomass assessments across the tropics. However, in most cases, allometries are influenced by environmental factors, both abiotic and biotic, and are not easily transferable.…”

Section: Reviewmentioning

confidence: 99%

Improving plant allometry by fusing forest models and remote sensing

2019

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Summary Allometry determines how tree shape and function scale with each other, related through size. Allometric relationships help scale processes from the individual to the global scale and constitute a core component of vegetation models. Allometric relationships have been expected to emerge from optimisation theory, yet this does not suitably predict empirical data. Here we argue that the fusion of high‐resolution data, such as those derived from airborne laser scanning, with individual‐based forest modelling offers insight into how plant size contributes to large‐scale biogeochemical processes. We review the challenges in allometric scaling, how they can be tackled by advances in data‐model fusion, and how individual‐based models can serve as data integrators for dynamic global vegetation models.

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A regional allometry for the Congo basin forests based on the largest ever destructive sampling

Cited by 50 publications

References 43 publications

Leveraging Signatures of Plant Functional Strategies in Wood Density Profiles of African Trees to Correct Mass Estimations From Terrestrial Laser Data

Leveraging Signatures of Plant Functional Strategies in Wood Density Profiles of African Trees to Correct Mass Estimations From Terrestrial Laser Data

Landscape‐level validation of allometric relationships for carbon stock estimation reveals bias driven by soil type

Improving plant allometry by fusing forest models and remote sensing

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