Wang2011

Report for study: Wang2011

Contact Information

Data contributor: Wang Feng

Email: [email protected]

Address:

• Institute of Desertification Studies, Chinese Academy of Forestry, Beijing, 100091, China

Data source

Citation: Wang F, Kang M, Lu Q, Letort V, Han H, Guo Y, Reffye PD and Li B (2011). 'A stochastic model of tree architecture and biomass partitioning: application to Mongolian Scots Pines.' Annals of Botany, 107(5), pp. 781-792.

DOI: 10.1093/aob/mcq218

Abstract: Background and Aims Mongolian Scots pine (Pinus sylvestris var. mongolica) is one of the principal species used for windbreak and sand stabilization in arid and semi-arid areas in northern China. A model-assisted analysis of its canopy architectural development and functions is valuable for better understanding its behaviour and roles in fragile ecosystems. However, due to the intrinsic complexity and variability of trees, the parametric identification of such models is currently a major obstacle to their evaluation and their validation with respect to real data. The aim of this paper was to present the mathematical framework of a stochastic functional-structural model (GL2) and its parameterization for Mongolian Scots pines, taking into account inter-plant variability in terms of topological development and biomass partitioning. \nMethods In GL2, plant organogenesis is determined by the realization of random variables representing the behaviour of axillary or apical buds. The associated probabilities are calibrated for Mongolian Scots pines using experimental data including means and variances of the numbers of organs per plant in each order-based class. The functional part of the model relies on the principles of source-sink regulation and is parameterized by direct observations of living trees and the inversion method using measured data for organ mass and dimensions. \nKey Results The final calibration accuracy satisfies both organogenetic and morphogenetic processes. Our hypothesis for the number of organs following a binomial distribution is found to be consistent with the real data. Based on the calibrated parameters, stochastic simulations of the growth of Mongolian Scots pines in plantations are generated by the Monte Carlo method, allowing analysis of the inter-individual variability of the number of organs and biomass partitioning. Three-dimensional (3D) architectures of young Mongolian Scots pines were simulated for 4-, 6- and 8-year-old trees. \nConclusions This work provides a new method for characterizing tree structures and biomass allocation that can be used to build a 3D virtual Mongolian Scots pine forest. The work paves the way for bridging the gap between a single-plant model and a stand model.

Overview of data provided

The dataset includes records for 20 individuals from 1 species belonging to 1 family(ies), presenting 1 functional type(s), growing in 1 condition(s) within 1 major type(s) of habitat, with data included for the following variables:

Variable	Label	Units	N	Min	Median	Max
latitude	Latitude	deg	20	43	43	43
longitude	Longitude	deg	20	122	122	122
age	Age	yr	13	2	3	6
a.lf	Leaf area	m2	13	0.012	0.067	1.4
a.stba	Stem area at base	m2	13	0.00001	0.000058	0.00071
h.t	Height	m	13	0.16	0.26	0.83
d.ba	Basal diameter	m	13	0.0036	0.0086	0.03
m.lf	Leaf mass	kg	13	0.0015	0.01	0.21
m.st	Total stem mass	kg	13	0.00054	0.0046	0.12
m.so	Aboveground mass	kg	13	0.0023	0.015	0.33
m.br	Branch mass	kg	13	0	0.0013	0.082
m.to	Total mass	kg	13	0.0023	0.016	0.41

And locally within the country:

The sites sampled are:

Location	Longitude	Latitude	Vegetation
Zhanggutai, Zhangwu County, Liaoning Province, China	122.3667	42.72	Temperate forest

The growing conditions of sampled plants was:

Location	growingCondition
Zhanggutai, Zhangwu County, Liaoning Province, China	plantation managed

Species sampled

Species	Family	Pft
Pinus sylvestris var. mongolica	Pinaceae	evergreen gymnosperm

Methods used

Sampling strategy: Samples of 1-, 2-, 3-, 5- and 6-year-old trees were also taken for destructive measurements of biomass and geometry with four replications for each tree age.

Leaf area: A needle area is computed from its length L and diameter R based on the allometric relationship provided for Mongolian Scots pine. S=2.57*R(L-0.1167) (Jiao, 1982). I randomly sampled more than 20 needles in the experiments. I didn't take the samples for each individual and didn't consider the position of leaves in the plant. The specific leaf area can be fitted by leaves area and biomass of these samples. Finally, the Leaf Area was calculated by their biomass and specific leaf area.

Stem cross sectional area: We have provide the 'Stem diameter at base(d)', then the stem cross sectional area(S) can be calculated as equation S=pi/4*d^2.

Height: Because trees are young, the heights of most samples are less than one meter. We directly measured the tree height by tape.

Biomass: Samples were taken for destructive measurements of biomass and geometry. To prevent water loss during measurement, plants were dug up with their roots and soil and transported to the laboratory.

Year collected: 2006-2007

Plots of data

This is how the study Wang2011 fits in the entire dataset (grey). each colour represents a species. A legend of species names with colours is included at the end for reports with 1 < n < 20 species.