Dataset Information

Models for Predicting the Biomass of Cunninghamialanceolata Trees and Stands in Southeastern China.

ABSTRACT: Using existing equations to estimate the biomass of a single tree or a forest stand still involves large uncertainties. In this study, we developed individual-tree biomass models for Chinese Fir (Cunninghamia lanceolata.) stands in Fujian Province, southeast China, by using 74 previously established models that have been most commonly used to estimate tree biomass. We selected the best fit models and modified them. The results showed that the published model ln(B(Biomass)) = a + b * ln(D) + c * (ln(H))2 + d * (ln(H))3 + e * ln(WD) had the best fit for estimating the tree biomass of Chinese Fir stands. Furthermore, we observed that variables D(diameter at breast height), H (height), and WD(wood density)were significantly correlated with the total tree biomass estimation model. As a result, a natural logarithm structure gave the best estimates for the tree biomass structure. Finally, when a multi-step improvement on tree biomass model was performed, the tree biomass model with Tree volume(TV), WD and biomass wood density conversion factor (BECF),achieved the highest simulation accuracy, expressed as ln(TB) = -0.0703 + 0.9780 * ln(TV) + 0.0213 * ln(WD) + 1.0166 * ln(BECF). Therefore, when TV, WD and BECF were combined with tree biomass volume coefficient bi for Chinese Fir, the stand biomass (SB)model included both volume(SV) and coefficient bi variables of the stand as follows: bi = Exp(-0.0703+0.9780*ln(TV)+0.0213 * ln(WD)+1.0166*ln(BECF)). The stand biomass model is SB = SV/TV * bi.

SUBMITTER: Guangyi M

PROVIDER: S-EPMC5241017 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Models for Predicting the Biomass of Cunninghamialanceolata Trees and Stands in Southeastern China.

Guangyi Mei M Yujun Sun S Saeed Sajjad S

PloS one 20170117 1

Using existing equations to estimate the biomass of a single tree or a forest stand still involves large uncertainties. In this study, we developed individual-tree biomass models for Chinese Fir (Cunninghamia lanceolata.) stands in Fujian Province, southeast China, by using 74 previously established models that have been most commonly used to estimate tree biomass. We selected the best fit models and modified them. The results showed that the published model ln(B(Biomass)) = a + b * ln(D) + c * ...[more]

PMID: 28095512

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Project description:Across the semiarid ecosystems of the southwestern USA, there has been widespread encroachment of woody shrubs and trees including Juniperus species into former grasslands. Quantifying vegetation biomass in such ecosystems is important because semiarid ecosystems are thought to play an important role in the global land carbon (C) sink, and changes in plant biomass also have implications for primary consumers and potential bioenergy feedstock. Oneseed juniper (Juniperus monosperma) is common in desert grasslands and pinyon-juniper rangelands across the intermountain region of southwestern North America; however, there is limited information about the aboveground biomass (AGB) and sapwood area (SWA) for this species, causing uncertainties in estimates of C stock and transpiration fluxes. In this study, we report on canopy area (CA), stem diameter, maximum height, and biomass measurements from J. monosperma trees sampled from central New Mexico. Dry biomass ranged between 0.4 kg and 625 kg, and cross-sectional SWA was measured on n = 200 stems using image analysis. We found a strong linear relationship between CA and AGB (r2 = 0.96), with a similar slope to that observed in other juniper species, suggesting that this readily measured attribute is well suited for upscaling studies. There was a 9% bias between different approaches to measuring CA, indicating care should be taken to account for these differences to avoid systematic biases. We found equivalent stem diameter (ESD) was a strong predictor of biomass, but that existing allometric models underpredicted biomass in larger trees. We found SWA could be predicted from individual stem diameter with a power relationship, and that tree-level SWA should be estimated by summing the SWA predictions from individual stems rather than ESD. Our improved allometric models for J. monosperma support more accurate and robust measurements of C storage and transpiration fluxes in Juniperus-dominated ecosystems.

Project description:The above and below-ground biomass (AGB and BGB) relationship is often used to assess the impact of biotic and abiotic effects on the growth and development of individual plants. The AGB and BGB relationship of the same tree species in different habitats can change significantly because of environmental stress. To investigate how the tree size, the biomass allocation and BGB/AGB ratio of Leucaena leucocephala (Lam.) de Wit varied according to spacing and mixed plant patterns in a valley-type savanna of southwest China, we examined the growth of L. leucocephala, and sampled 23 individuals for biomass measurement in each of four treatments (close/wide spacing of Leucaena leucocephala monocultures, mixed plantation of Leucaena leucocephala and Eucalyptus camaldulensis, and mixed plantation of Leucaena leucocephala and Eucalyptus citriodora), and then determined the regression relationships between AGB and BGB of L. leucocephala in different plant stands. Our results indicated that mixed planting significantly reduced all growth metrics for the tree sizes of L. leucocephala and increased the value of BGB/AGB. Changing plant spacing in monocultures had a significant impact on AGB and TB (Total Biomass) of L. leucocephala, but it had no significant effect on the other metrics. Within mixed plant schemes, L. leucocephala significantly reduced the biomass allocation to leaves and small roots and increased the allocation to coarse root biomass. There were no significant differences in tree size and biomass allocation of L. leucocephala between different spacing regimes in monocultures or between different mixtures in mixed plant stands. The correlation between BGB and AGB of L. leucocephala in all plant stands was consistent with the model of allometric growth, and AGB can be used to accurately estimate BGB. Interestingly, the correlations were not exactly the same. BGB and AGB in monoculture showed isometric growth, and their values in mixed plant stands showed allometric growth. BGB also increased faster than AGB. The findings indicated that L. leucocephala allocated more biomass to the root system when it was planted with Eucalyptus.

Dataset Information

Models for Predicting the Biomass of Cunninghamialanceolata Trees and Stands in Southeastern China.

Publications

Models for Predicting the Biomass of Cunninghamialanceolata Trees and Stands in Southeastern China.

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