Allometric biomass equations for shrub and small tree species in subtropical China

Ali, Arshad; Xu, Ming‐Shan; Zhao, Yan-Tao; Zhang, Qingqing; Zhou, Lihua; Yang, Xiaodong; Yan, En‐Rong

doi:10.14214/sf.1275

Cited by 83 publications

(67 citation statements)

References 19 publications

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“…does not substantially jeopardize their accuracy of prediction. Our results provide further evidence of the effectiveness of generic AGB Indiv allometric models developed from large, compiled data sets, consistent with comparable studies in tropical forests (Chave et al ., , ; Vieilledent et al ., ); for different forest types in the U.S.A (Chojnacky et al ., ); and for different forest types in China (Ali et al ., ). Development of such generalized models is an appropriate approach to extending the geographical application range of otherwise limited, and often localized, species‐specific models.…”

Section: Discussionmentioning

confidence: 97%

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Testing the generality of above‐ground biomass allometry across plant functional types at the continent scale

Paul

Roxburgh

Chave

et al. 2016

Global Change Biology

154

129

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Accurate ground-based estimation of the carbon stored in terrestrial ecosystems is critical to quantifying the global carbon budget. Allometric models provide cost-effective methods for biomass prediction. But do such models vary with ecoregion or plant functional type? We compiled 15 054 measurements of individual tree or shrub biomass from across Australia to examine the generality of allometric models for above-ground biomass prediction. This provided a robust case study because Australia includes ecoregions ranging from arid shrublands to tropical rainforests, and has a rich history of biomass research, particularly in planted forests. Regardless of ecoregion, for five broad categories of plant functional type (shrubs; multistemmed trees; trees of the genus Eucalyptus and closely related genera; other trees of high wood density; and other trees of low wood density), relationships between biomass and stem diameter were generic. Simple power-law models explained 84-95% of the variation in biomass, with little improvement in model performance when other plant variables (height, bole wood density), or site characteristics (climate, age, management) were included. Predictions of stand-based biomass from allometric models of varying levels of generalization (species-specific, plant functional type) were validated using whole-plot harvest data from 17 contrasting stands (range: 9-356 Mg ha(-1) ). Losses in efficiency of prediction were <1% if generalized models were used in place of species-specific models. Furthermore, application of generalized multispecies models did not introduce significant bias in biomass prediction in 92% of the 53 species tested. Further, overall efficiency of stand-level biomass prediction was 99%, with a mean absolute prediction error of only 13%. Hence, for cost-effective prediction of biomass across a wide range of stands, we recommend use of generic allometric models based on plant functional types. Development of new species-specific models is only warranted when gains in accuracy of stand-based predictions are relatively high (e.g. high-value monocultures).

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Section: Discussionmentioning

confidence: 97%

“…These results were therefore consistent with previous work showing that generic multispecies models perform almost as well as the species‐specific ones developed for that region (e.g. Feller, ; Williams et al ., ; Montagu et al ., ; Mugasha et al ., ; Paul et al ., ,b; Mbow et al ., ; Ali et al ., ).…”

Section: Discussionmentioning

confidence: 97%

Testing the generality of above‐ground biomass allometry across plant functional types at the continent scale

Paul

Roxburgh

Chave

et al. 2016

Global Change Biology

154

129

View full text Add to dashboard Cite

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“…Model Y8 produced the lowest average relative error (PBIAS %) compared to the error produced using previously published equations (figures 4(a)-(h)). The equations used by Negash [33] and Ali [40] Brown [42], Mugasha [43] and Zewdie [44] overestimated total AGB by 6.4%, 17.2%, 33.4%, 34.6%, and 94.3%, respectively (figures 4(b)-(h)). More importantly, the spread of error in estimated AGB was stable across different diameter classes in Y8, ranging from −5.2% to 8.7%, however, it was considerably higher in previously published biomass estimation models (SI appendix, figure S4).…”

Section: Comparison Of Aboveground Biomass Equations With Previously mentioning

confidence: 97%

Mixed-species allometric equations and estimation of aboveground biomass and carbon stocks in restoring degraded landscape in northern Ethiopia

Mokria

Mekuria

Gebrekirstos

et al. 2018

Environ. Res. Lett.

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Accurate biomass estimation is critical to quantify the changes in biomass and carbon stocks following the restoration of degraded landscapes. However, there is lack of site-specific allometric equations for the estimation of aboveground biomass (AGB), which consequently limits our understanding of the contributions of restoration efforts in mitigating climate change. This study was conducted in northwestern Ethiopia to develop a multi-species allometric equation and investigate the spatial and temporal variation of C-stocks following the restoration of degraded landscapes. We harvested and weighed 84 trees from eleven dominant species from six grazing exclosures and adjacent communal grazing land. We observed that AGB correlates significantly with diameter at stump height D 30 (R 2 = 0.78; P < 0.01), and tree height H (R 2 = 0.41, P < 0.05). Our best model, which includes D 30 and H as predictors explained 82% of the variations in AGB. This model produced the lowest bias with narrow ranges of errors across different diameter classes. Estimated C-stock showed a significant positive correlation with stem density (R 2 = 0.80, P < 0.01) and basal area (R 2 = 0.84, P < 0.01). At the watershed level, the mean C-stock was 3.8 (±0.5) Mg C ha −1 . Plot-level C-stocks varied between 0.1 and 13.7 Mg C ha −1 . Estimated C-stocks in three-and seven-year-old exclosures exceeded estimated C-stock in the communal grazing land by 50%. The species that contribute most to C-stocks were Leucaena sp. (28%), Calpurnia aurea (21%), Euclea racemosa (20.9%), and Dodonaea angustifolia (15.8%). The equations developed in this study allow monitoring changes in C-stocks and C-sequestration following the implementation of restoration practices in northern Ethiopia over space and time. The estimated C-stocks can be used as a reference against which future changes in C-stocks can be compared.

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“…Our results thus contribute to achieving the much needed standardization of non‐destructive biomass estimation of high‐mountain vegetation (Oliveras, Van der Eynden et al., ). Plant height and basal diameter have been used before to estimate biomass for tussocks (Guevara, Gonnet, & Estevez, ; Oliveras, Girardin et al., ) and shrubs (Ali et al., ). We refrained from using canopy diameter as suggested by others (Guevara et al., ; Oliveras, Girardin et al., ; Oliveras, Van der Eynden et al., ).…”

Section: Discussionmentioning

confidence: 99%

Non‐destructive allometric estimates of above‐ground and below‐ground biomass of high‐mountain vegetation in the Andes

Cabrera

Samboni-Guerrero

Duivenvoorden

2018

Applied Vegetation Science

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Aim: Studies that monitor high-mountain vegetation, such as paramo grasslands in the Andes, lack non-destructive biomass estimation methods. We aimed to develop and apply allometric models for above-ground, below-ground and total biomass of paramo plants. Location:The paramo of southern Colombia between 1°09′N and 077°50′W, at 3,400 and 3,700 m a.s.l. Methods:We established 61 1-m 2 plots at random locations, excluding disturbed, inaccessible and peat bog areas. We measured heights and basal diameters of all vascular plants in these plots and classified them into seven growth forms. Near each plot, we sampled the biomass from plants of abundant genera, after having measured their height and basal diameter. Hence, we measured the biomass of 476 plants (allometric set). For each growth form we applied power-law functions to develop allometric models of biomass against basal diameter, height, height x basal diameter and height × basal area. The best models were selected using AIC c weights. Using the observed and predicted plant biomass of the allometric set we calculated absolute percentage errors using crossvalidation. The biomass of a plot was estimated by summing the predicted biomass of all plants in a plot. Confidence limits around these sums were calculated by bootstrapping.Results: For groups of <20 plants the biomass predictions yielded large (>15%) errors.Applying groups that resembled the 1-m 2 plots in density and composition, the errors for above-ground and total biomass estimates were <15%. Across all plots, we obtained an above-ground, below-ground and total plot biomass of 329 ± 190, 743 ± 486 and 1011 ± 627 g/m 2 (mean ± SD), respectively. These values were within the range of biomass estimates obtained destructively in the tropical Andes. Conclusions: In new applications, if target vegetation samples are similar regarding growth forms and genera to our allometric set, their biomass might be predicted applying our equations, provided they contain at least 50-100 plants. In other situations, we would recommend gathering additional biomass measurements from local plants to evaluate new regression equations. K E Y W O R D S basal diameter, Colombia, grassland, growth form, paramo, plant height 478 | Additional supporting information may be found online in the Supporting Information section at the end of the article. APPENDIX S1. Location map showing the distribution of the 61 plots in the paramos of Cumbal, Ovejas-Tauso and Paja Blanca, southern Colombia. APPENDIX S2. Biomass and predictor values of the allometric set. APPENDIX S3. Results of allometric models of biomass. N = number of plants used in the allometric modelling. APPENDIX S4. Plot data. APPENDIX S5. Aboveground and belowground biomass of plant communities in extra-Andean and temperate biomes, obtained by destructive harvesting. If available, the standard deviation is added in parentheses. How to cite this article: Cabrera M, Samboni-Guerrero V, Duivenvoorden JF. Non-destructive allometric estimates of above-ground and below-ground biomass ...

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Allometric biomass equations for shrub and small tree species in subtropical China

Cited by 83 publications

References 19 publications

Testing the generality of above‐ground biomass allometry across plant functional types at the continent scale

Testing the generality of above‐ground biomass allometry across plant functional types at the continent scale

Mixed-species allometric equations and estimation of aboveground biomass and carbon stocks in restoring degraded landscape in northern Ethiopia

Non‐destructive allometric estimates of above‐ground and below‐ground biomass of high‐mountain vegetation in the Andes

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