Browsing by Autor "Lindsay F. Banin"

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Field methods for sampling tree height for tropical forest biomass estimation
(Wiley, 2018) Martin J. P. Sullivan; Simon L. Lewis; Wannes Hubau; Lan Qie; Timothy R. Baker; Lindsay F. Banin; Jérôme Chave; Aida Cuní‐Sanchez; Ted R. Feldpausch; Gabriela López‐González
Quantifying the relationship between tree diameter and height is a key component of efforts to estimate biomass and carbon stocks in tropical forests. Although substantial site-to-site variation in height-diameter allometries has been documented, the time consuming nature of measuring all tree heights in an inventory plot means that most studies do not include height, or else use generic pan-tropical or regional allometric equations to estimate height.Using a pan-tropical dataset of 73 plots where at least 150 trees had in-field ground-based height measurements, we examined how the number of trees sampled affects the performance of locally derived height-diameter allometries, and evaluated the performance of different methods for sampling trees for height measurement.Using cross-validation, we found that allometries constructed with just 20 locally measured values could often predict tree height with lower error than regional or climate-based allometries (mean reduction in prediction error = 0.46 m). The predictive performance of locally derived allometries improved with sample size, but with diminishing returns in performance gains when more than 40 trees were sampled. Estimates of stand-level biomass produced using local allometries to estimate tree height show no over- or under-estimation bias when compared with biomass estimates using field measured heights. We evaluated five strategies to sample trees for height measurement, and found that sampling strategies that included measuring the heights of the ten largest diameter trees in a plot outperformed (in terms of resulting in local height-diameter models with low height prediction error) entirely random or diameter size-class stratified approaches.Our results indicate that even limited sampling of heights can be used to refine height-diameter allometries. We recommend aiming for a conservative threshold of sampling 50 trees per location for height measurement, and including the ten trees with the largest diameter in this sample.
Height-diameter input data and R-code to fit and assess height-diameter models, from 'Field methods for sampling tree height for tropical forest biomass estimation' in Methods in Ecology and Evolution
(2018) Martin Sullivan; Simon L. Lewis; Wannes Hubau; Lan Qie; Timothy R. Baker; Lindsay F. Banin; Jérôme Chave; Aida Cuní‐Sanchez; Ted R. Feldpausch; Gabriela López‐González
1. Quantifying the relationship between tree diameter and height is a key component of efforts to estimate biomass and carbon stocks in tropical forests. Although substantial site-to-site variation in height-diameter allometries has been documented, the time consuming nature of measuring all tree heights in an inventory plot means that most studies do not include height, or else use generic pan-tropical or regional allometric equations to estimate height. 2. Using a pan-tropical dataset of 73 plots where at least 150 trees had in-field ground-based height measurements, we examined how the number of trees sampled affects the performance of locally-derived height-diameter allometries, and evaluated the performance of different methods for sampling trees for height measurement. 3. Using cross-validation, we found that allometries constructed with just 20 locally measured values could often predict tree height with lower error than regional or climate-based allometries (mean reduction in prediction error = 0.46 m). The predictive performance of locally-derived allometries improved with sample size, but with diminishing returns in performance gains when more than 40 trees were sampled. Estimates of stand-level biomass produced using local allometries to estimate tree height show no over- or under-estimation bias when compared with estimates using measured heights. We evaluated five strategies to sample trees for height measurement, and found that sampling strategies that included measuring the heights of the ten largest diameter trees in a plot outperformed (in terms of resulting in local height-diameter models with low height prediction error) entirely random or diameter size-class stratified approaches. 4. Our results indicate that even remarkably limited sampling of heights can be used to refine height-diameter allometries. We recommend aiming for a conservative threshold of sampling 50 trees per location for height measurement, and including the ten trees with the largest diameter in this sample.
Tree height integrated into pan-tropical forest biomass estimates
(2012) Ted R. Feldpausch; Jon Lloyd; Simon L. Lewis; Roel Brienen; Emanuel Gloor; Abel Monteagudo Mendoza; Gabriela López‐González; Lindsay F. Banin; Kamariah Abu Salim; Kofi Affum‐Baffoe
Abstract. Above-ground tropical tree biomass and carbon storage estimates commonly ignore tree height. We estimate the effect of incorporating height (H) on forest biomass estimates using 37 625 concomitant H and diameter measurements (n = 327 plots) and 1816 harvested trees (n = 21 plots) tropics-wide to answer the following questions: 1. For trees of known biomass (from destructive harvests) which H-model form and geographic scale (plot, region, and continent) most reduces biomass estimate uncertainty? 2. How much does including H relationship estimates derived in (1) reduce uncertainty in biomass estimates across 327 plots spanning four continents? 3. What effect does the inclusion of H in biomass estimates have on plot- and continental-scale forest biomass estimates? The mean relative error in biomass estimates of the destructively harvested trees was half (mean 0.06) when including H, compared to excluding H (mean 0.13). The power- and Weibull-H asymptotic model provided the greatest reduction in uncertainty, with the regional Weibull-H model preferred because it reduces uncertainty in smaller-diameter classes that contain the bulk of biomass per hectare in most forests. Propagating the relationships from destructively harvested tree biomass to each of the 327 plots from across the tropics shows errors are reduced from 41.8 Mg ha−1 (range 6.6 to 112.4) to 8.0 Mg ha−1 (−2.5 to 23.0) when including $H$. For all plots, above-ground live biomass was 52.2±17.3 Mg ha−1 lower when including H estimates (13%), with the greatest reductions in estimated biomass in Brazilian Shield forests and relatively no change in the Guyana Shield, central Africa and southeast Asia. We show fundamentally different stand structure across the four forested tropical continents, which affects biomass reductions due to $H$. African forests store a greater portion of total biomass in large-diameter trees and trees are on average larger in diameter. This contrasts to forests on all other continents where smaller-diameter trees contain the greatest fractions of total biomass. After accounting for variation in $H$, total biomass per hectare is greatest in Australia, the Guyana Shield, and Asia and lowest in W. Africa, W. Amazonia, and the Brazilian Shield (descending order). Thus, if closed canopy tropical forests span 1668 million km2 and store 285 Pg C, then the overestimate is 35 Pg C if H is ignored, and the sampled plots are an unbiased statistical representation of all tropical forest in terms of biomass and height factors. Our results show that tree $H$ is an important allometric factor that needs to be included in future forest biomass estimates to reduce error in estimates of pantropical carbon stocks and emissions due to deforestation.
Tree height integrated into pantropical forest biomass estimates
(Copernicus Publications, 2012) Ted R. Feldpausch; Jon Lloyd; Simon L. Lewis; Roel Brienen; Manuel Gloor; Abel Monteagudo Mendoza; Gabriela López‐González; Lindsay F. Banin; Kamariah Abu Salim; Kofi Affum‐Baffoe
Abstract. Aboveground tropical tree biomass and carbon storage estimates commonly ignore tree height (H). We estimate the effect of incorporating H on tropics-wide forest biomass estimates in 327 plots across four continents using 42 656 H and diameter measurements and harvested trees from 20 sites to answer the following questions: 1. What is the best H-model form and geographic unit to include in biomass models to minimise site-level uncertainty in estimates of destructive biomass? 2. To what extent does including H estimates derived in (1) reduce uncertainty in biomass estimates across all 327 plots? 3. What effect does accounting for H have on plot- and continental-scale forest biomass estimates? The mean relative error in biomass estimates of destructively harvested trees when including H (mean 0.06), was half that when excluding H (mean 0.13). Power- and Weibull-H models provided the greatest reduction in uncertainty, with regional Weibull-H models preferred because they reduce uncertainty in smaller-diameter classes (≤40 cm D) that store about one-third of biomass per hectare in most forests. Propagating the relationships from destructively harvested tree biomass to each of the 327 plots from across the tropics shows that including H reduces errors from 41.8 Mg ha−1 (range 6.6 to 112.4) to 8.0 Mg ha−1 (−2.5 to 23.0). For all plots, aboveground live biomass was −52.2 Mg ha−1 (−82.0 to −20.3 bootstrapped 95% CI), or 13%, lower when including H estimates, with the greatest relative reductions in estimated biomass in forests of the Brazilian Shield, east Africa, and Australia, and relatively little change in the Guiana Shield, central Africa and southeast Asia. Appreciably different stand structure was observed among regions across the tropical continents, with some storing significantly more biomass in small diameter stems, which affects selection of the best height models to reduce uncertainty and biomass reductions due to H. After accounting for variation in H, total biomass per hectare is greatest in Australia, the Guiana Shield, Asia, central and east Africa, and lowest in east-central Amazonia, W. Africa, W. Amazonia, and the Brazilian Shield (descending order). Thus, if tropical forests span 1668 million km2 and store 285 Pg C (estimate including H), then applying our regional relationships implies that carbon storage is overestimated by 35 Pg C (31–39 bootstrapped 95% CI) if H is ignored, assuming that the sampled plots are an unbiased statistical representation of all tropical forest in terms of biomass and height factors. Our results show that tree H is an important allometric factor that needs to be included in future forest biomass estimates to reduce error in estimates of tropical carbon stocks and emissions due to deforestation.