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Title:
Pilot experiment: tree sapling biomass allocation to strata
Access rights:
Free for public
Usage rights:
Permission is granted to anybody to access, use and publish all open for public data freely. The commercial use of any data is prohibited. The quality and completeness of data cannot be guaranteed. Users employ these data at their own risk. In order to make attribution of use for owners of the data possible, the identifier of ownership of data must be retained with every data record. Users must publicly acknowledge, in conjunction with the use of the data, the data owners. Cite the data as follows: Lang, A., von Oheimn, G. and Härdtle, W. (2013): Competition of tree saplings -Pilot- Biomass of target saplings - biomass allocation to strata. BEF-China data portal (Accessed through URL http://china.befdata.biow.uni-leipzig.de/datasets/145)
Published:
Mechanisms promoting tree species coexistence: Experimental evidence with saplings of subtropical forest ecosystems of China ;submitted to JVS (This dataset represents only one part of the analyses for the mentioned manuscript)
Abstract:
Questions: One tenet of biodiversity and ecosystem functioning research is the dependence of ecosystem functions on species-specific differences in traits. Community assembly theory predicts niche differentiation among the constituent species, for which there is as yet no empirical evidence for subtropical forest ecosystems.We thus ask: (1) Which mechanisms promote sapling coexistence in the four abundant early-successional subtropical species Schima superba, Elaeocarpus decipiens, Quercus serrata and Castanea henryi? (2) Do species richness, species composition, species identity and stand density have an impact on growth patterns and crown architecture of tree saplings?
Design:
In a field experiment, we manipulated the local neighbourhood of saplings with regard to species richness (1, 2 and 4 species), species composition (monocultures, six two-species combinations and one four-species combination) and stand density (low, intermediate and high).
Spatial extent:
Pilot Experiment 29°06'N 117°55' E To analyse biomass allocation patterns with regard to stratification (i.e. height layers) and to different constitutents (stem, branches and leaves), the four central individuals per plot were harvested in September 2010 in 50 cm strata starting from ground. Saplings were divided into stem, branches and leaves for each stratum. Biomass was dried at 70° C for 48 h and weighed to 0.01 g precision. Biomass data were logarithmically transformed prior to analyses.To analyse the vertical above-ground biomass distribution, we calculated the cumulative biomass fraction C, i.e. the proportion of cumulative above-ground biomass, summed up from the ground to the height strata hs (50, 100, 150, 200, 250 cm).
Temporal extent:
trees have been planted in 2009 and harvested in autumn 2010
Taxonomic extent:
4 Species: Schima superba, Elaeocarpus decipiens, Quercus serrata, Castanea henryi
Measurement cirumstances:
The medium density plots of block 4 were harvested in July 2010 by SP1.
Data analysis:
The overall aim of this study was to disentangle neighbourhood effects on growth, biomass allocation, crown architecture and branch demography of saplings. Firstly, the complete dataset was used to test for diversity effects by fitting mixed effects models (Model 1) including species richness and density as factorial variables and the initial diameter as fixed effect. The initial diameter was used to account for differences in size at the beginning of the experiment. Secondly, all two species combinations were analysed for species composition. Mixed effects models (Model 2a) were fitted using species composition, density and initial diameter as fixed effect. The analyses with Model 2b were performed for the high density treatment data divided by species to exclude density effects and to test for composition effects on the individual-level of each species. Model 2b contained species composition and initial diameter as fixed effects. Thirdly, mixed effects models (Model 3) for all monocultures were calculated to test for species identity. They were fitted by the predictor variables species identity, density and initial diameter as fixed effects. Random effects for all models were plot nested in block. Model simplification was performed by stepwise backward selection of fixed factors, removing the least significant variables until only significant predictory variables remained (p < 0.05). The significant categorical variables were further examined by a Tukey post-hoc test.

Filter:
Dataset column

Name:
plot_id
Definition:
Individual complex ID for identifying exactly each plot; it connects with underline character the block number and the community code, i. e. the block number with the plots treatment. The plot identifier contains the information, which block the plot is in and which community is is comprised of.
Unit:
No information available
Datagroup:
BEF research plot name
Keywords:
Pilot experiment
Values:
2_AE01
2_AE04
2_AE03
2_AE05
2_AE02
Contributors:
No information available

Dataset column

Name:
species_diversity
Definition:
tree species diversity level within the pilot plot
Unit:
No information available
Datagroup:
Taxonomic biodiversity
Keywords:
biodiversity, diversity treatment
Values:
4
2
1
Contributors:
No information available

Dataset column

Name:
species_code
Definition:
2-character abbreviation encoding the species name and epithet of the tree species located within the plot
Unit:
No information available
Datagroup:
Species community code in the pilot experiment
Keywords:
species
Values:
ch_ed
ch_qs
ch
ch_ss
ch_ed_qs_ss
Contributors:
No information available

Dataset column

Name:
species_combination
Definition:
unique species combination code as number
Unit:
No information available
Datagroup:
Helper
Keywords:
No information available
Values:
1
3
2
11
10
Contributors:
No information available

Dataset column

Name:
Ind_pos
Definition:
number of individual, Individuals were consecutively numbered starting from the SW corner of the plot
Unit:
No information available
Datagroup:
Individual position within Pilot experiment
Keywords:
No information available
Values:
11
7
1
10
6
Contributors:
No information available

Dataset column

Name:
Code
Definition:
individual related unique code
Unit:
No information available
Datagroup:
Individual related unique code for the Pilot experiment
Keywords:
tree individual, tree position
Values:
1AE01_07
1AE01_10
1AE01_11
1AE02_06
1AE02_07
Contributors:
No information available

Dataset column

Name:
density
Definition:
density of planted saplings, Saplings were planted in low, medium and high density. The low density treatment was one individual per plot. The medium and high density treatment comprised 16 individuals, planted with 25 cm and 15 cm planting distance respectively.
Unit:
No information available
Datagroup:
Density class
Keywords:
competition, abundance
Values:
medium
high
low
Contributors:
No information available

Dataset column

Name:
Spp
Definition:
species identity of individual
Unit:
No information available
Datagroup:
Scientific plant species name
Keywords:
species
Values:
Quercus serrata
Elaeocarpus decipiens
Castanea henryi
Schima superba
Contributors:
No information available

Dataset column

Name:
hs
Definition:
height stratum from ground
Unit:
No information available
Datagroup:
Vegetation layer height
Keywords:
height
Values:
s1
s4
s2
s3
s5
Contributors:
No information available

Dataset column

Name:
l.fresh
Definition:
leaf biomass fresh per stratum
Unit:
g
Datagroup:
Above and below ground biomass measurement
Keywords:
fresh weight, aboveground biomass
Values:
0.07
0
0.11
0.1
0.08
Contributors:
No information available

Dataset column

Name:
l.dry
Definition:
leaf biomass dry weight per stratum
Unit:
g
Datagroup:
Above and below ground biomass measurement
Keywords:
biomass, leaf, dry weight
Values:
0.06
0.03
0.05
0
0.04
Contributors:
No information available

Dataset column

Name:
b.fresh
Definition:
branch biomass fresh weight per stratum
Unit:
g
Datagroup:
Above and below ground biomass measurement
Keywords:
branch, fresh weight, aboveground biomass
Values:
0.04
0.08
0
0.17
0.05
Contributors:
No information available

Dataset column

Name:
b.dry
Definition:
branch biomass dry weight per stratum
Unit:
g
Datagroup:
Above and below ground biomass measurement
Keywords:
biomass, branch, dry weight
Values:
0.07
0.03
0.02
0.05
0
Contributors:
No information available

Dataset column

Name:
s.fresh
Definition:
stem biomass fresh weight per stratum
Unit:
g
Datagroup:
Above and below ground biomass measurement
Keywords:
stem, fresh weight, aboveground biomass
Values:
0.28
0
0.14
0.23
0.18
Contributors:
No information available

Dataset column

Name:
s.dry
Definition:
stem biomass dry weight per stratum
Unit:
g
Datagroup:
Above and below ground biomass measurement
Keywords:
biomass, stem, dry weight
Values:
0.16
0.13
0.1
0.06
0
Contributors:
No information available

Dataset column

Name:
tot.bio.fresh
Definition:
total biomass fresh weight per stratum
Unit:
g
Datagroup:
Above and below ground biomass measurement
Keywords:
fresh weight, aboveground biomass
Values:
0
0.89
0.81
0.45
0.55
Contributors:
No information available

Dataset column

Name:
tot.bio.dry
Definition:
total biomass dry weight per stratum
Unit:
g
Datagroup:
Above and below ground biomass measurement
Keywords:
biomass, tree performance, tree, dry weight
Values:
0.43
0.29
0.41
0.32
0
Contributors:
No information available

Dataset column

Name:
C
Definition:
cumulative biomass dry weight per stratum
Unit:
g
Datagroup:
Cumulative proportion of biomass from ground along strata
Keywords:
biomass allocation
Values:
0.269828179
0.25866649
0.266843745
0.270359239
0.274185612
Contributors:
No information available

Dataset column

Name:
gbd_T0
Definition:
ground basal diameter at time of planting; asal diameter was measured (5cm above ground) at the time of planting (March 2009).
Unit:
mm
Datagroup:
Basal diameter
Keywords:
tree performance, basal diameter
Values:
10
11
1
14
13
Contributors:
No information available

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11 h%c3%a4rdtle medium

Werner
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