Estimation of Biomass Dynamics and Allocation in Chinese Fir Trees Using Tree Ring Analysis in Hunan Province, China

Studying tree biomass dynamics and allocation is crucial to understanding the forest carbon cycle and the adaptation of trees to the environment. However, traditional biomass surveys are time-consuming and labor-intensive, so few studies have specifically examined biomass formation in terms of the increase in individual tree biomass, and the role that tree age and site conditions play in this process, especially tree roots, is unclear. We studied the tree ring characteristics of 87 sample trees (8–40 years old) from 29 Chinese fir plantations with different site conditions and measured the biomass of their stems, crowns, and roots. The biomass increment at various age stages during tree growth was determined via using tree ring analysis, and a generalized additive mixed model (GAMM) was used to analyze biomass formation and allocation, as well as the specific impact of site conditions on them. The results showed that the biomass increment of Chinese fir trees first increased and then decreased with age, and improving site conditions delayed the carbon maturation of the trees. The proportion of stem biomass increased with age, while the proportion of crown biomass decreased and the proportion of root biomass increased and then decreased. The effect of the site conditions on the tree biomass allocation showed a nonlinear trend. Tree ring analysis provides a feasible and effective method for assessing tree growth and biomass dynamics. Forest managers can use the findings of this study to scientifically optimize the management of increasing forest carbon sequestration.

[1]  Qingfen Li,et al.  Allocation Patterns and Temporal Dynamics of Chinese Fir Biomass in Hunan Province, China , 2023, Forests.

[2]  Al Gore.  Measure emissions to manage emissions , 2022, Science.

[3]  Qi-jing Liu,et al.  Aboveground biomass allocation and additive allometric models of fifteen tree species in northeast China based on improved investigation methods , 2022, Forest Ecology and Management.

[4]  Yanhui Wang,et al.  Impacts of Site Conditions and Stand Structure on the Biomass Allocation of Single Trees in Larch Plantations of Liupan Mountains of Northwest China , 2022, Forests.

[5]  J. Merganic,et al.  Modelling Impact of Site and Terrain Morphological Characteristics on Biomass of Tree Species in Putorana Region , 2021, Plants.

[6]  Justin T. Maxwell,et al.  Joint effects of climate, tree size, and year on annual tree growth derived from tree‐ring records of ten globally distributed forests , 2021, Global change biology.

[7]  P. Beets,et al.  Early rotation biomass and nutrient accumulation of Pinus radiata forests after harvest residue management and fertiliser treatment on contrasting types of soil , 2021 .

[8]  A. Barbosa,et al.  On the use of tree‐ring area as a predictor of biomass accumulation and its climatic determinants of coffee tree growth , 2021 .

[9]  María Triviño,et al.  Data from: Optimizing management to enhance multifunctionality in a boreal forest landscape , 2017, JYX.

[10]  Wenfa Xiao,et al.  Effects of stand age on tree biomass partitioning and allometric equations in Chinese fir (Cunninghamia lanceolata) plantations , 2020, European Journal of Forest Research.

[11]  J. Coulston,et al.  Long-term dynamics of loblolly pine crown structure and aboveground net primary production as affected by site quality, planting density and cultural intensity , 2020 .

[12]  A. Mäkelä,et al.  Age effect on tree structure and biomass allocation in Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies [L.] Karst.) , 2020, Annals of Forest Science.

[13]  S. Huang,et al.  Climate-sensitive height–age models for top height trees in natural and reclaimed oil sands stands in Alberta, Canada , 2019 .

[14]  W. Kurz,et al.  Tree Ring Reconstructions of Stemwood Biomass Indicate Increases in the Growth Rate of Black Spruce Trees Across Boreal Forests of Canada , 2019, Journal of Geophysical Research: Biogeosciences.

[15]  Chi Xie,et al.  Promoting carsharing attractiveness and efficiency: An exploratory analysis , 2018, Transportation Research Part D: Transport and Environment.

[16]  P. Horodecki,et al.  Tree- and Stand-Level Biomass Estimation in a Larix decidua Mill. Chronosequence , 2018, Forests.

[17]  A. Duan,et al.  Predicting total and component biomass of Chinese fir using a forecast combination method , 2017 .

[18]  G. Berndes,et al.  The potential role of forest management in Swedish scenarios towards climate neutrality by mid century , 2017 .

[19]  Sudipto Banerjee,et al.  Predicting tree biomass growth in the temperate–boreal ecotone: Is tree size, age, competition, or climate response most important? , 2016, Global change biology.

[20]  L. Xiaojing,et al.  Review on forest carbon sequestration counting methodology under global climate change. , 2016 .

[21]  Pengfei Wu,et al.  Biomass production, nutrient cycling and distribution in age-sequence Chinese fir (Cunninghamia lanceolate) plantations in subtropical China , 2016, Journal of Forestry Research.

[22]  L. Fehrmann,et al.  Estimation of stand-level aboveground biomass dynamics using tree ring analysis in a Chinese fir plantation in Shitai County, Anhui Province, China , 2016, New Forests.

[23]  Hailemariam Temesgen,et al.  A Call to Improve Methods for Estimating Tree Biomass for Regional and National Assessments , 2015 .

[24]  刘世荣 Liu Shirong,et al.  The concept and application of carbon sequestration potentials in plantation forests , 2015 .

[25]  W. Ting,et al.  Carbon storage dynamics of Pinus armandii forest at different diameter levels based on tree ring data in the Baotianman National Nature Reserve, central China , 2014 .

[26]  Pete Smith,et al.  Co‐benefits, trade‐offs, barriers and policies for greenhouse gas mitigation in the agriculture, forestry and other land use (AFOLU) sector , 2014, Global change biology.

[27]  S. Fraver,et al.  Influence of stocking, site quality, stand age, low-severity canopy disturbance, and forest composition on sub-boreal aspen mixedwood carbon stocks , 2014 .

[28]  M. Verstraete,et al.  Allometric models for aboveground biomass in dry savanna trees of the Sudan and Sudan–Guinean ecosystems of Southern Senegal , 2014, Journal of Forest Research.

[29]  Yu Yang.  Dynamic changes of biomass and its allocation in Cunninghamia lanceolata plantations of different stand ages , 2013 .

[30]  O. Phillips,et al.  Detecting trends in tree growth: not so simple. , 2013, Trends in plant science.

[31]  K. T. Vashum,et al.  Methods to Estimate Above-Ground Biomass and Carbon Stock in Natural Forests - A Review , 2012 .

[32]  Yuandong Zhang,et al.  Dynamics of stand biomass and volume of the tree layer in forests with different restoration approaches based on tree-ring analysis: Dynamics of stand biomass and volume of the tree layer in forests with different restoration approaches based on tree-ring analysis , 2012 .

[33]  Ulf Dieckmann,et al.  Modeling carbon allocation in trees: a search for principles. , 2012, Tree physiology.

[34]  C. Peng,et al.  A long-term evaluation of biomass production in first and second rotations of Chinese fir plantations at the same site , 2011 .

[35]  G. Rubio,et al.  Allometric relations for biomass partitioning of Nothofagus antarctica trees of different crown classes over a site quality gradient , 2010 .

[36]  E. Dufrene,et al.  Age-related variation in carbon allocation at tree and stand scales in beech (Fagus sylvatica L.) and sessile oak (Quercus petraea (Matt.) Liebl.) using a chronosequence approach. , 2010, Tree physiology.

[37]  Gao Yongjun,et al.  Effects of site conditions on the biomass of Phyllostachys bambusoides f.shouzhu Yi , 2010 .

[38]  O. Phillips,et al.  Contrasting patterns of diameter and biomass increment across tree functional groups in Amazonian forests , 2008, Oecologia.

[39]  Matthias Peichl,et al.  Allometry and partitioning of above- and belowground tree biomass in an age-sequence of white pine forests , 2007 .

[40]  E. Gustafson.  Relative influence of the components of timber harvest strategies on landscape pattern , 2007 .

[41]  N. Breda,et al.  Is ring width a reliable proxy for stem-biomass increment? A case study in European beech , 2005 .

[42]  A. Lehtonen.  Estimating foliage biomass in Scots pine (Pinus sylvestris) and Norway spruce (Picea abies) plots. , 2005, Tree physiology.

[43]  J. Chambers,et al.  Tree allometry and improved estimation of carbon stocks and balance in tropical forests , 2005, Oecologia.

[44]  R. Houghton,et al.  Aboveground Forest Biomass and the Global Carbon Balance , 2005 .

[45]  A. Mäkelä,et al.  Effects of age and site quality on the distribution of biomass in Scots pine (Pinus sylvestris L.) , 1996, Trees.

[46]  J. Houghton.  Global warming , 2005 .

[47]  Christopher B. Field,et al.  Current status and past trends of the global carbon cycle , 2004 .

[48]  N. Mizoue,et al.  Estimating forest biomass increment based on permanent sample plots in relation to woodfuel consumption: a case study in Kampong Thom Province, Cambodia , 2004, Journal of Forest Research.

[49]  D. A. King.  Allocation of above-ground growth is related to light in temperate deciduous saplings , 2003 .

[50]  S. Wood.  Thin plate regression splines , 2003 .

[51]  S. Garman,et al.  Promoting old-growth characteristics and long-term wood production in Douglas-fir forests , 2002 .

[52]  K. Niklas,et al.  Canonical rules for plant organ biomass partitioning and annual allocation. , 2002, American journal of botany.

[53]  X. Lin,et al.  Inference in generalized additive mixed modelsby using smoothing splines , 1999 .

[54]  Lonnie W. Aarssen,et al.  The interpretation of stem diameter–height allometry in trees: biomechanical constraints, neighbour effects, or biased regressions? , 1999 .

[55]  R. K. Dixon,et al.  Carbon Pools and Flux of Global Forest Ecosystems , 1994, Science.

[56]  H. Mooney,et al.  Resource Limitation in Plants-An Economic Analogy , 1985 .

[57]  Forest Biomass.  Forest Biomass , 1982, Forestry Sciences.

[58]  K. Vogt,et al.  Biomass distribution and above- and below-ground production in young and mature Abiesamabilis zone ecosystems of the Washington Cascades , 1981 .