Computational protocol: Tree functional types simplify forest carbon stock estimates induced by carbon concentration variations among species in a subtropical area

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Protocol publication

[…] Traits that evolve slowly are considered subject to phylogenetic “constraint” and, thus, have a phylogenetic signal. The phylogenetic signal in C concentrations of stem, bark, branch, leaf, coarse root and fine root as well as functional traits (i.e. WD, LA, SLA, MAI and RGR), was quantified using the K statistic performed in the “picante” package in R. The K statistic compares a trait distribution from a phylogenetic tree to a distribution expected under a Brownian motion model of evolution that represents a continuous evolutionary change and random distribution across the phylogenetic tree. The K value was calculated by the following formula:3K=observed(MSE0/MSE)/expected(MSE0/MSE)where the MSE0 is the mean squared error of the tip data calculated by the phylogenetically correct mean (MSE0) and the MSE is the mean squared error of the data measured by the variance-covariance matrix derived from the candidate tree. A K = 1 implies that the observed trait distribution matches the Brownian motion model, while K < 1 implies more randomly distribution than a Brownian motion model and K > 1 implies higher phylogenetic signal or more conservatism than a Brownian motion model (i.e. trait similarity of related taxa), , . Statistical significance was tested by random permutation of traits across the tips of the phylogeny (n = 999). Traits were deemed significantly conserved if the observed K was in the upper 2.5% of the randomised K distributions. It should be noted that this null model of randomised K distributions corresponds to no phylogenetic signal, with Knull << 1. Phylogenetic trees were created with Phylomatic (v3) based on the Angiosperm Phylogeny Group (APG) III system.Estimates of forest stand C stock. We used the measurements from four forests in Dashanchong Forest Park (28°23′–28°24′N, 113°17′–13°19′E), Changsha County, Hunan Province, China, to quantify the error in stand C stock estimated using the generic C concentration constant (50.0%) and the C concentrations measured in this study. A 1-ha permanent plot was established for each forest and, within each, 20 m × 30 m subplots were established. There were seven subplots for C. lanceolata plantation (CLF), 15 for coniferous mixed forest (PMF), 16 for deciduous mixed forest (CAF) and 14 for evergreen broadleaved forest (CGF), .The inventory of tree species, according to percentage of biomass, for all four forests was: (1) 97% C. lanceolata biomass and 3% other deciduous and evergreen angiosperm biomass in CLF; (2) 49% P. massoniana biomass, 7% C. glauca biomass and 44% other deciduous and evergreen angiosperm biomass in PMF; (3) 58% C. axillaris biomass, 2% L. rotundifolia biomass and 40% other deciduous angiosperm biomass in CAF; and (4) 14% C. glauca biomass, 13% C. axillaris biomass and 73% other evergreen broadleaved biomass in CGF. C stocks (t C ha−1) were estimated using the generic C concentration, C concentrations of tree species and tissues, and C concentrations of average value of all tree species in specific functional type measured, given as CSg, CSm and CSf, respectively. […]

Pipeline specifications

Software tools PHYSIG, Picante, Phylomatic
Application Phylogenetics
Chemicals Carbon, Carbon Dioxide