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Sensitivity of Above-Ground Biomass Estimates to Height-Diameter Modelling in Mixed-Species West African Woodlands.

Valbuena R, Heiskanen J, Aynekulu E, Pitkänen S, Packalen P - PLoS ONE (2016)

Bottom Line: The most important differences were found between including H or not in the AGB estimation.Regarding the H-D modelling, the most relevant effect was found when species was included as an additive term.Based on the results, our final choice was the single-level mixed-effects model (B3), which accounts for the species but also for the plot random effects reflecting site-specific factors such as soil properties and degree of disturbance.

View Article: PubMed Central - PubMed

Affiliation: School of Forest Sciences, University of Eastern Finland, Joensuu, Finland.

ABSTRACT
It has been suggested that above-ground biomass (AGB) inventories should include tree height (H), in addition to diameter (D). As H is a difficult variable to measure, H-D models are commonly used to predict H. We tested a number of approaches for H-D modelling, including additive terms which increased the complexity of the model, and observed how differences in tree-level predictions of H propagated to plot-level AGB estimations. We were especially interested in detecting whether the choice of method can lead to bias. The compared approaches listed in the order of increasing complexity were: (B0) AGB estimations from D-only; (B1) involving also H obtained from a fixed-effects H-D model; (B2) involving also species; (B3) including also between-plot variability as random effects; and (B4) involving multilevel nested random effects for grouping plots in clusters. In light of the results, the modelling approach affected the AGB estimation significantly in some cases, although differences were negligible for some of the alternatives. The most important differences were found between including H or not in the AGB estimation. We observed that AGB predictions without H information were very sensitive to the environmental stress parameter (E), which can induce a critical bias. Regarding the H-D modelling, the most relevant effect was found when species was included as an additive term. We presented a two-step methodology, which succeeded in identifying the species for which the general H-D relation was relevant to modify. Based on the results, our final choice was the single-level mixed-effects model (B3), which accounts for the species but also for the plot random effects reflecting site-specific factors such as soil properties and degree of disturbance.

No MeSH data available.


Sensitivity of tree height (H) and tree-level above-ground biomass (AGB) predictions to changes in the environmental stress parameter (E).(a) Tree H predictions by Eq 16, including (white colour) those obtained by the value of E = 0.7 extracted from Chave et al. [24] (B0; Fig 3A) and the calibrated baseline value (B0*; Table 5), and compared with those measured in the field (black colour). (b) Pair-wise differences of those H predictions against measured values. (c) Tree-level AGB predictions, also including B0 and B0* (white colour), and compared with the AGB predictions obtained directly from field measurements, applying the corresponding Eq 13 (black colour). (d) Pair-wise differences of those AGB predictions and those obtained directly from field measurements. Outliers have been omitted from (c) and (d) to improve the clarity of figures.
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pone.0158198.g006: Sensitivity of tree height (H) and tree-level above-ground biomass (AGB) predictions to changes in the environmental stress parameter (E).(a) Tree H predictions by Eq 16, including (white colour) those obtained by the value of E = 0.7 extracted from Chave et al. [24] (B0; Fig 3A) and the calibrated baseline value (B0*; Table 5), and compared with those measured in the field (black colour). (b) Pair-wise differences of those H predictions against measured values. (c) Tree-level AGB predictions, also including B0 and B0* (white colour), and compared with the AGB predictions obtained directly from field measurements, applying the corresponding Eq 13 (black colour). (d) Pair-wise differences of those AGB predictions and those obtained directly from field measurements. Outliers have been omitted from (c) and (d) to improve the clarity of figures.

Mentions: Since the AGB estimations not using H as predictor in the allometry (Eq 14; B0), were notably different from all those including a H-D model, we considered it relevant to further investigate the reasons for what seemed an overestimation in B0. In order to investigate the sensitivity of the AGB estimations to changes in the E parameter, we employed Eq 16, which tells us the H that on average corresponds each D under the environmental stress conditions defined by a given value of E. In Fig 3A, the dashed line depicts that model for the exact case of E = 0.70 applied in this study site (M0). Fig 6 shows how changing values of E within a range of 0.6–0.9 affects the prediction of H from D, and how this propagates to AGB predictions at the tree level (B0).


Sensitivity of Above-Ground Biomass Estimates to Height-Diameter Modelling in Mixed-Species West African Woodlands.

Valbuena R, Heiskanen J, Aynekulu E, Pitkänen S, Packalen P - PLoS ONE (2016)

Sensitivity of tree height (H) and tree-level above-ground biomass (AGB) predictions to changes in the environmental stress parameter (E).(a) Tree H predictions by Eq 16, including (white colour) those obtained by the value of E = 0.7 extracted from Chave et al. [24] (B0; Fig 3A) and the calibrated baseline value (B0*; Table 5), and compared with those measured in the field (black colour). (b) Pair-wise differences of those H predictions against measured values. (c) Tree-level AGB predictions, also including B0 and B0* (white colour), and compared with the AGB predictions obtained directly from field measurements, applying the corresponding Eq 13 (black colour). (d) Pair-wise differences of those AGB predictions and those obtained directly from field measurements. Outliers have been omitted from (c) and (d) to improve the clarity of figures.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4930180&req=5

pone.0158198.g006: Sensitivity of tree height (H) and tree-level above-ground biomass (AGB) predictions to changes in the environmental stress parameter (E).(a) Tree H predictions by Eq 16, including (white colour) those obtained by the value of E = 0.7 extracted from Chave et al. [24] (B0; Fig 3A) and the calibrated baseline value (B0*; Table 5), and compared with those measured in the field (black colour). (b) Pair-wise differences of those H predictions against measured values. (c) Tree-level AGB predictions, also including B0 and B0* (white colour), and compared with the AGB predictions obtained directly from field measurements, applying the corresponding Eq 13 (black colour). (d) Pair-wise differences of those AGB predictions and those obtained directly from field measurements. Outliers have been omitted from (c) and (d) to improve the clarity of figures.
Mentions: Since the AGB estimations not using H as predictor in the allometry (Eq 14; B0), were notably different from all those including a H-D model, we considered it relevant to further investigate the reasons for what seemed an overestimation in B0. In order to investigate the sensitivity of the AGB estimations to changes in the E parameter, we employed Eq 16, which tells us the H that on average corresponds each D under the environmental stress conditions defined by a given value of E. In Fig 3A, the dashed line depicts that model for the exact case of E = 0.70 applied in this study site (M0). Fig 6 shows how changing values of E within a range of 0.6–0.9 affects the prediction of H from D, and how this propagates to AGB predictions at the tree level (B0).

Bottom Line: The most important differences were found between including H or not in the AGB estimation.Regarding the H-D modelling, the most relevant effect was found when species was included as an additive term.Based on the results, our final choice was the single-level mixed-effects model (B3), which accounts for the species but also for the plot random effects reflecting site-specific factors such as soil properties and degree of disturbance.

View Article: PubMed Central - PubMed

Affiliation: School of Forest Sciences, University of Eastern Finland, Joensuu, Finland.

ABSTRACT
It has been suggested that above-ground biomass (AGB) inventories should include tree height (H), in addition to diameter (D). As H is a difficult variable to measure, H-D models are commonly used to predict H. We tested a number of approaches for H-D modelling, including additive terms which increased the complexity of the model, and observed how differences in tree-level predictions of H propagated to plot-level AGB estimations. We were especially interested in detecting whether the choice of method can lead to bias. The compared approaches listed in the order of increasing complexity were: (B0) AGB estimations from D-only; (B1) involving also H obtained from a fixed-effects H-D model; (B2) involving also species; (B3) including also between-plot variability as random effects; and (B4) involving multilevel nested random effects for grouping plots in clusters. In light of the results, the modelling approach affected the AGB estimation significantly in some cases, although differences were negligible for some of the alternatives. The most important differences were found between including H or not in the AGB estimation. We observed that AGB predictions without H information were very sensitive to the environmental stress parameter (E), which can induce a critical bias. Regarding the H-D modelling, the most relevant effect was found when species was included as an additive term. We presented a two-step methodology, which succeeded in identifying the species for which the general H-D relation was relevant to modify. Based on the results, our final choice was the single-level mixed-effects model (B3), which accounts for the species but also for the plot random effects reflecting site-specific factors such as soil properties and degree of disturbance.

No MeSH data available.