Literature DB >> 14676030

Generic biomass functions for Norway spruce in Central Europe--a meta-analysis approach toward prediction and uncertainty estimation.

Christian Wirth1, Jens Schumacher, Ernst-Detlef Schulze.   

Abstract

To facilitate future carbon and nutrient inventories, we used mixed-effect linear models to develop new generic biomass functions for Norway spruce (Picea abies (L.) Karst.) in Central Europe. We present both the functions and their respective variance-covariance matrices and illustrate their application for biomass prediction and uncertainty estimation for Norway spruce trees ranging widely in size, age, competitive status and site. We collected biomass data for 688 trees sampled in 102 stands by 19 authors. The total number of trees in the "base" model data sets containing the predictor variables diameter at breast height (D), height (H), age (A), site index (SI) and site elevation (HSL) varied according to compartment (roots: n = 114, stem: n = 235, dry branches: n = 207, live branches: n = 429 and needles: n = 551). "Core" data sets with about 40% fewer trees could be extracted containing the additional predictor variables crown length and social class. A set of 43 candidate models representing combinations of lnD, lnH, lnA, SI and HSL, including second-order polynomials and interactions, was established. The categorical variable "author" subsuming mainly methodological differences was included as a random effect in a mixed linear model. The Akaike Information Criterion was used for model selection. The best models for stem, root and branch biomass contained only combinations of D, H and A as predictors. More complex models that included site-related variables resulted for needle biomass. Adding crown length as a predictor for needles, branches and roots reduced both the bias and the confidence interval of predictions substantially. Applying the best models to a test data set of 17 stands ranging in age from 16 to 172 years produced realistic allocation patterns at the tree and stand levels. The 95% confidence intervals (% of mean prediction) were highest for crown compartments (approximately +/- 12%) and lowest for stem biomass (approximately +/- 5%), and within each compartment, they were highest for the youngest and oldest stands, respectively.

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Year:  2004        PMID: 14676030     DOI: 10.1093/treephys/24.2.121

Source DB:  PubMed          Journal:  Tree Physiol        ISSN: 0829-318X            Impact factor:   4.196


  10 in total

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Journal:  Oecologia       Date:  2005-06-22       Impact factor: 3.225

2.  Dynamic allometric scaling of tree biomass and size.

Authors:  Xiaolu Zhou; Mingxia Yang; Zelin Liu; Peng Li; Binggeng Xie; Changhui Peng
Journal:  Nat Plants       Date:  2021-01-04       Impact factor: 15.793

3.  Top-down and bottom-up inventory approach for above ground forest biomass and carbon monitoring in REDD framework using multi-resolution satellite data.

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Journal:  Environ Monit Assess       Date:  2013-04-20       Impact factor: 2.513

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Authors:  Martin Gspaltl; William Bauerle; Dan Binkley; Hubert Sterba
Journal:  For Ecol Manage       Date:  2013-01-15       Impact factor: 3.558

5.  Is leaf area of Norway spruce (Picea abies L. Karst.) and European larch (Larix decidua Mill.) affected by mixture proportion and stand density?

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Authors:  Iris Roitman; Mercedes M C Bustamante; Ricardo F Haidar; Julia Z Shimbo; Guilherme C Abdala; George Eiten; Christopher W Fagg; Maria Cristina Felfili; Jeanine Maria Felfili; Tamiel K B Jacobson; Galiana S Lindoso; Michael Keller; Eddie Lenza; Sabrina C Miranda; José Roberto R Pinto; Ariane A Rodrigues; Wellington B C Delitti; Pedro Roitman; Jhames M Sampaio
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8.  Model errors in tree biomass estimates computed with an approximation to a missing covariance matrix.

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9.  Scaling wood volume estimates from inventory plots to landscapes with airborne LiDAR in temperate deciduous forest.

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Journal:  Carbon Balance Manag       Date:  2016-05-31

10.  Complex Physiological Response of Norway Spruce to Atmospheric Pollution - Decreased Carbon Isotope Discrimination and Unchanged Tree Biomass Increment.

Authors:  Vojtěch Čada; Hana Šantrůčková; Jiří Šantrůček; Lenka Kubištová; Meelis Seedre; Miroslav Svoboda
Journal:  Front Plant Sci       Date:  2016-06-09       Impact factor: 5.753

  10 in total

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