Equations for estimating the above-ground biomass of Larix sibirica in the forest-steppe of Mongolia

Purevragchaa, Battulga; Tsogtbaatar, Jamsran; Dulamsuren, Choimaa; Hauck, Markus

doi:10.1007/s11676-013-0375-4

Cited by 28 publications

(42 citation statements)

References 20 publications

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“…However, adding tree height as an additional predictor into biomass equations can significantly improve the model fitting and performance [21,28]. Our results demonstrated that adding tree height into the additive system marginally improved two-thirds of the biomass equations for the three plantation species, and were consistent with the literature (e.g., [20,26,28]). …”

Section: Discussionsupporting

confidence: 86%

“…Three forms of allometric biomass equations, i.e., W = aˆD b , W = aˆ(D 2ˆH ) b , and W = aˆD bˆHc , are commonly used in the literature (e.g., [3,10,11,26,27]). In many cases, the allometric biomass equation W = aˆ(D 2ˆH ) b can improve model fitting and performance for total, aboveground, stem and root biomass, but not so for branch, foliage and crown biomass, whereas the function W = aˆD bˆHc is more flexible and can generally improve model accuracy for total, sub-totals, and component biomass [3,26].…”

Section: Allometric Equations Development and Error Structure Evaluationmentioning

confidence: 99%

“…In many cases, the allometric biomass equation W = aˆ(D 2ˆH ) b can improve model fitting and performance for total, aboveground, stem and root biomass, but not so for branch, foliage and crown biomass, whereas the function W = aˆD bˆHc is more flexible and can generally improve model accuracy for total, sub-totals, and component biomass [3,26]. Therefore, we decided to use both W = aˆD b and W = aˆD bˆHc as the basic model formats to construct the additive systems of biomass equations with three constraints.…”

Section: Allometric Equations Development and Error Structure Evaluationmentioning

confidence: 99%

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Developing Two Additive Biomass Equations for Three Coniferous Plantation Species in Northeast China

Dong

Zhang

2016

Forests

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Accurate quantification of tree biomass is critical and essential for calculating carbon storage, as well as for studying climate change, forest health, forest productivity, nutrient cycling, etc. Tree biomass is typically estimated using statistical models. In this study, a total of 289 trees were harvested and measured for stem, root, branch, and foliage biomass from three coniferous plantation species in northeastern P.R. China. We developed two additive systems of biomass equations based on tree diameter (D) only and both tree diameter (D) and height (H). For each system, likelihood analysis was used to verify the error structures of power functions in order to determine if logarithmic transformation should be applied on both sides of biomass equations. The model coefficients were simultaneously estimated using seemingly unrelated regression (SUR). The results indicated that stem biomass had the largest relative contribution to total biomass, while foliage biomass had the smallest relative proportion for the three species. The root to shoot ratio averaged 0.27 for Korean pine, 0.25 for larch, and 0.23 for Mongolian pine. The two additive biomass systems obtained good model fitting and prediction performance, of which the model R a 2 > 0.80, and the percent mean absolute bias (MAB%), was <17%. The second additive system (D and H) had a relatively greater R a 2 and smaller root mean square error (RMSE). The model coefficient for the predictor H was statistically significant in eight of the twelve models, depending on tree species and biomass component. Adding tree height into the system of biomass equations can marginally improve model fitting and performance, especially for total, aboveground, and stem biomass. The two additive systems developed in this study can be applied to estimate individual tree biomass of three coniferous plantation species in the Chinese National Forest Inventory.

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Section: Discussionsupporting

confidence: 86%

Section: Allometric Equations Development and Error Structure Evaluationmentioning

confidence: 99%

Section: Allometric Equations Development and Error Structure Evaluationmentioning

confidence: 99%

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Developing Two Additive Biomass Equations for Three Coniferous Plantation Species in Northeast China

Dong

Zhang

2016

Forests

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“…Consistent with earlier results from other tree species (Edwards and Jarvis 1982;Domec and Gartner 2002), early growing season climate seems to be most influential on the hydraulic architecture of L. sibirica, since K p , d h , and d were significantly higher in earlywood than in latewood, and tracheid diameters and conductivity are related to the climatic conditions during tree-ring formation (Fonti et al 2010). Lower TD and higher d h in the trees from the Ore Mountains than from Mongolia match with the observation that biomass equations established for planted L. sibirica in Iceland led to the underestimation of biomass of L. sibirica from Mongolia, which was attributed to higher wood density in semi-arid Mongolia than in oceanic Iceland (Battulga et al 2013).…”

Section: Discussionsupporting

confidence: 53%

Stem increment and hydraulic architecture of a boreal conifer (Larix sibirica) under contrasting macroclimates

Chenlemuge

Schuldt

Dulamsuren

et al. 2014

Trees

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Key message Hydraulic conductivity and wood anatomical traits in Larix sibirica are correlated with macroclimate, and growing season precipitation in particular, along a precipitation gradient of 700 mm year 21 . Abstract Empirical (K s ) and theoretical (K p ) sapwood area-specific hydraulic conductivity, hydraulically weighted (d h ) and simple (d) tracheid diameters as well as tracheid density (TD) in roots, stems, and branches were studied in Larix sibirica trees, the dominant conifer at the southern, drought-affected range limit of the boreal forest in Inner Asia. We compared the hydraulic architecture of L. sibirica in two stands in Mongolia to larch trees grown in Central Europe under moist conditions and related hydraulics to macroclimate (precipitation, temperature) and productivity (basal area increment, BAI). K s , K p , d h , and d correlated positively, and TD negatively with precipitation, temperature, and also BAI. Mean growing season precipitation (MGSP) seemed to affect the hydraulic traits more than temperature. A meta-analysis covering data of 14 conifer species from the northern hemisphere revealed a general relationship between MGSP and hydraulic traits. In contrast to expectation, K p and d h did not show a steady decline from roots through the stem to branches in L. sibirica, but were of similar size or larger in the stem. Our results suggest that considerable plasticity in the hydraulic architecture is an important element of the drought adaptation of L. sibirica. It combines with drought-induced fine root abscission (as reported from earlier work) which may help to protect larger roots and the stem from cavitation.

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“…The studies of model comparison indicate that using the equation W = aÁ(D 2 ÁH) b can improve model fitting and performance for total, aboveground, stem and root biomass, but not for branch, foliage and crown biomass, whereas the equation W = aÁD b ÁH c is more flexible than other functions, and can generally improve model accuracy for total, sub-totals and component biomass (Bi et al 2004;Battulga et al 2013;Cai et al 2013).…”

Section: Introductionmentioning

confidence: 99%

Developing additive systems of biomass equations for nine hardwood species in Northeast China

Dong

Zhang

2015

Trees

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Key message We developed two additive systems of biomass equations based on diameter and tree height for nine hardwood species by SUR, and used a likelihood analysis to evaluate the model error structures. Abstract In this study, a total of 472 trees were harvested and measured for stem, root, branch, and foliage biomass from nine hardwood species in Northeast China. Two additive systems of biomass equations were developed, one based on tree diameter (D) only and one based on both tree diameter (D) and height (H). For each system, three constraints were set up to account for the cross-equation error correlations between four tree component biomass, two sub-total biomass, and total biomass. The model coefficients were simultaneously estimated using seemly unrelated regression (SUR). Likelihood analysis was used to verify the error structures of power functions in order to determine if logarithmic transformation should be applied on both sides of biomass equations. Jackknifing model residuals were used to validate the prediction performance of biomass equations. The results indicated that (1) stem biomass accounted for the largest proportion (62 %) of the total tree biomass; (2) the two additive systems of biomass equations obtained good model fitting and prediction, of which the model R a 2 was [0.89, and the mean absolute percent bias (MAB %) was \35 %; (3) the system of biomass equations based on both D and H significantly improved model fitting and performance, especially for total, aboveground, and stem biomass; and (4) the anti-log correction was not necessary in this study. The established additive systems of biomass equations can provide reliable and accurate estimation for individual tree biomass of the nine hardwood species in Chinese National Forest Inventory.

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Equations for estimating the above-ground biomass of Larix sibirica in the forest-steppe of Mongolia

Cited by 28 publications

References 20 publications

Developing Two Additive Biomass Equations for Three Coniferous Plantation Species in Northeast China

Developing Two Additive Biomass Equations for Three Coniferous Plantation Species in Northeast China

Stem increment and hydraulic architecture of a boreal conifer (Larix sibirica) under contrasting macroclimates

Developing additive systems of biomass equations for nine hardwood species in Northeast China

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