Kelvin S.-H. Peh

Dr. Kelvin S.-H. Peh

orcid

Research Focus & Metrics

Academic Career Length

25Years (2002-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 February 2009 in Nature
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SLSimon L. Lewis
Simon L. Lewis
GLGabriela Lopez-Gonzalez
Gabriela Lopez-Gonzalez
BSBonaventure Sonké
Bonaventure Sonké
KAKofi Affum-Baffoe
Kofi Affum-Baffoe
TBTimothy R. Baker
Timothy R. Baker
HWHannsjörg Wöll
Hannsjörg Wöll

19 July 2010 in New Phytologist
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Journal Article
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OPOliver L. Phillips
Oliver L. Phillips
GHGeertje Van Der Heijden
Geertje Van Der Heijden
SLSimon L. Lewis
Simon L. Lewis
GLGabriela López‐González
Gabriela López‐González
LALuiz E. O. C. Aragão
Luiz E. O. C. Aragão
Emilio VilanovaEmilio Vilanova
Emilio Vilanova
Featured paper: See Editorial p553

5 May 2011 in Biogeosciences
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Journal Article
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TFTed Feldpaush
Ted Feldpaush
LBL. Banin
L. Banin
OPOliver L. Phillips
Oliver L. Phillips
TBT. R. Baker
T. R. Baker
SLS. L. Lewis
S. L. Lewis
JLJ. Lloyd
J. Lloyd
Tropical tree height-diameter (H:D) relationships may vary by forest type and region making large-scale estimates of above-ground biomass subject to bias if they ignore these differences in stem allometry. We have therefore developed a new global tropical forest database consisting of 39 955 concurrent H and D measurements encompassing 283 sites in 22 tropical countries. Utilising this database, our objectives were: 1. to determine if H:D relationships differ by geographic region and forest type (wet to dry forests, including zones of tension where forest and savanna overlap). 2. to ascertain if the H:D relationship is modulated by climate and/or forest structural characteristics (e.g. stand-level basal area, A). 3. to develop H:D allometric equations and evaluate biases to reduce error in future local-to-global estimates of tropical forest biomass. Annual precipitation coefficient of variation (PV), dry season length (SD), and mean annual air temperature (TA) emerged as key drivers of variation in H:D relationships at the pantropical and region scales. Vegetation structure also played a role with trees in forests of a high A being, on average, taller at any given D. After the effects of environment and forest structure are taken into account, two main regional groups can be identified. Forests in Asia, Africa and the Guyana Shield all have, on average, similar H:D relationships, but with trees in the forests of much of the Amazon Basin and tropical Australia typically being shorter at any given D than their counterparts elsewhere. The region-environment-structure model with the lowest Akaike's information criterion and lowest deviation estimated stand-level H across all plots to within amedian −2.7 to 0.9% of the true value. Some of the plot-to-plot variability in H:D relationships not accounted for by this model could be attributed to variations in soil physical conditions. Other things being equal, trees tend to be more slender in the absence of soil physical constraints, especially at smaller D. Pantropical and continental-level models provided less robust estimates of H, especially when the roles of climate and stand structure in modulating H:D allometry were not simultaneously taken into account.

27 August 2012 in Biogeosciences
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TFTed Feldpaush
Ted Feldpaush
JLJ. Lloyd
J. Lloyd
SLS. L. Lewis
S. L. Lewis
RBR. J. W. Brienen
R. J. W. Brienen
MGM. Gloor
M. Gloor
OPOliver L. Phillips
Oliver L. Phillips
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.

21 August 2007 in Global Change Biology
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Corey BradshawCorey Bradshaw
Corey Bradshaw
NSNavjot S. Sodhi
Navjot S. Sodhi
KPKelvin S.-H. Peh
Kelvin S.-H. Peh
BBBarry Brook
Barry Brook

5 September 2013 in Philosophical Transactions of the Royal Society B: Biological Sciences
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Journal Article
Open access
SLSimon L. Lewis
Simon L. Lewis
BSBonaventure Sonké
Bonaventure Sonké
TSTerry Sunderland
Terry Sunderland
SBSerge K. Begne
Serge K. Begne
GLGabriela Lopez-Gonzalez
Gabriela Lopez-Gonzalez
LZLise Zemagho
Lise Zemagho
We report above-ground biomass (AGB), basal area, stem density and wood mass density estimates from 260 sample plots (mean size: 1.2 ha) in intact closed-canopy tropical forests across 12 African countries. Mean AGB is 395.7 Mg dry mass ha −1 (95% CI: 14.3), substantially higher than Amazonian values, with the Congo Basin and contiguous forest region attaining AGB values (429 Mg ha −1 ) similar to those of Bornean forests, and significantly greater than East or West African forests. AGB therefore appears generally higher in palaeo- compared with neotropical forests. However, mean stem density is low (426 ± 11 stems ha −1 greater than or equal to 100 mm diameter) compared with both Amazonian and Bornean forests (cf. approx. 600) and is the signature structural feature of African tropical forests. While spatial autocorrelation complicates analyses, AGB shows a positive relationship with rainfall in the driest nine months of the year, and an opposite association with the wettest three months of the year; a negative relationship with temperature; positive relationship with clay-rich soils; and negative relationships with C : N ratio (suggesting a positive soil phosphorus–AGB relationship), and soil fertility computed as the sum of base cations. The results indicate that AGB is mediated by both climate and soils, and suggest that the AGB of African closed-canopy tropical forests may be particularly sensitive to future precipitation and temperature changes.