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Title:
CSPs: Tree neighbour competitive traits in the comparative study plots - target groups
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., Härdtle, W. and von Oheimb, G.(2013): Tree neighbour competitive traits in the comparative study plots - target groups. BEF-China data portal (Accessed through URL http://china.befdata.biow.uni-leipzig.de/datasets/136)
Published:
Lang et al. 2010, FORECO 260, 1708-1715; http://dx.doi.org/10.1016/j.foreco.2010.08.015
Abstract:
This research is done to quantifiy individual tree growth and mortality within and among different species in the comparative study plots. Local neighbourhood interactions are analysed by the means of competition indices. Questions are: (a) does diversity reduce competition? (b) does competition change with successional stage? The data might provide valuable information to be compared with data from the main experiment. We chose 20 target trees each of the two most abundant evergreen species (Castanopsis eyrei FAGACEAE and Schima superba THEACEAE ) and of the two most abundant decidious species (Quercus serrata and Castanea henryi FAGACEAE). Competitors were defined as all trees with a dbh> 10 cm in middle and old successional forests and >3 cm in early successional forests and within a radius that is 1/2 of the height of the target tree. The positions of the competitors in relation to the respective target tree were evaluated (distance and azimuth). Following parameters were measured of all trees: total height, heigth of bifurcatin point, dbh and the crown width in 8 directions.
Design:
Study design We decided on an individual-based approach to elucidate our hypotheses. We selected four tree species of high abundance (Yu et al., 2001): S. superba Gardn. et Champ., C. eyrei (Champ. ex Benth.) Hutch., Q. serrata var. brevipetiolata and C. henryi (Skan) Rehd. et Wils. called target species. The target species belong to different functional groups, since S. superba and C. eyrei are evergreen and Q. serrata and C. henryi are deciduous. Data sampling was conducted during summer and autumn 2008 on the 27CSPs Twenty target trees per species were chosen randomly within the plots from all individuals complying with the following criteria: (i) single stemmed; (ii) diameter at breast height (dbh, 1.3m above ground) >10cm (intermediate and old permanent plots) or dbh >3cm (in young permanent plots); (iii) crown position in the upper canopy layer; (iv) each target species could only be selected once per plot. Thus, the 20 target trees of each species were spread over 20 of the 27 permanent plots with the exception of C. henryi (10 trees in 10 plots) for which only 10 individuals fulfilling all the criteria were found. Local biotic conditions (local species richness, local functional diversity, competition) were assessed by recording the position, size and identity of the neighbours of each target tree. Neighbours were defined as all individuals whose top height (corrected for the slope position (z-axis)) cut the hull of a reversed cone with an opening angle of 70◦ and positioned with its tip at the foot of the target tree (following the method of Biging and Dobbertin, 1992). They also had to fulfil the minimum dbh criterion (criterion (ii) above). Each target tree, together with its local neighbours formed a group.Each target tree had a mean number of 10.9 (±6.0 SD) neighbours, resulting in a total number of 837 surveyed individuals.
Spatial extent:
CSPs 29°08'-29°17'N 118°02'-118°11'E Measurements and calculated variables Crown radii in the eight subcardinal directions were determined by means of a crown mirror. The crown projection area (hereafter crown area) was calculated using the formula for a polygon. In cases of extraordinary crown displacement – the crown projection did not include the stem base – the distances to the proximal and distal edge of the crown were measured in all possible directions (if this was only possible for one direction, four crown radii were measured as follows: the distances to the proximal and distal edge of the crown were determined and, starting at the centre of this crown diameter, on the axis perpendicular to it. In this case, crown area was approximated as a quadrangle). Relative crown displacement (rd) was considered to be the distance of the centre of gravity of the crown area from the stem base, divided by the mean crown radius (Longuetaud et al., 2008). In cases where the centre of gravity perfectly matches the stem base, rd is equal to 0. Main tree stems may deviate from vertical stature in two different ways: stem inclination and stem bendiness, with the former involving straight but leaning stems and the latter bent or curved stems (Schamp et al., 2007). In the forest interior of Gutianshan NNR bent growth forms are confined to a relatively small number of trees. To obtain the degree of stem inclination, we first measured the height of the bifurcation point (height at which the lowest living crown branch of the tree branches off, excluding epicormics or springs), and then the horizontal distance of the bifurcation point from the stem in the direction of the slope. The angle of inclination was calculated as tan alpha of these two distances. If the stem was inclined towards the slope, stem inclination was considered to be negative. This method is similar to that used by Matsuzaki et al. (2006), where stem inclination was defined by referring to a straight line between the stem base and the top of the tree. However, in our study we used the bifurcation point as a reference point in order to separate the effect of crown asymmetry from that of stem inclination.The dbh (measured with a diameter measurement tape) and total height were recorded for all trees. The relative position of the neighbours to the target tree was measured as the horizontal distance from stem base to stem base. All height and distance measurements were conducted using a Forester Vertex Hypsometer (Haglöf, Sweden). All neighbours were determined to species. Local species richness (i.e. the species richness of the group) was estimated using the rarefaction method (Hurlbert’s formula, 1971) of the vegan package in R (subsample size: two trees). We applied the same method to obtain ameasure for local functional diversity. For this purpose we classified the species into seven functional groups. Since our hypotheses are based on growth characteristics of crown and stem, the trees were allocated to the functional groups according to adult tree height (canopy tree vs. sub-canopy tree) (Poorter et al., 2006), leaf longevity (evergreen vs. deciduous) (Deng et al., 2008) and leaf morphology (simple leaves, compound leaves, needles). We decided to establish an additional functional group for Fabaceae, because of their well known ability to fix nitrogen and the resulting differential preconditions for growth.To characterise the competitive power of the target trees competition indices have been calculated. Upper canopy heightwasdefined as themeanheight of the highest 20% trees in the respective group.For each tree group, data for slope inclination and aspect were collected and transformed after Beers et al. (1966).
Temporal extent:
No information available
Taxonomic extent:
Target tree species are: Schima superba, Quercus serrata, Castanopsis eyrei, Castanea henryi
Measurement cirumstances:
very steep terrain, very hot, multilayer canopy -> difficult to see the crowns of upper canopy individuals, long sampling period
Data analysis:
We tested speciesspecific differences of crown area, relative crown displacement and stem inclination using a mixed effects model with species as fixed effect and plot as random effect. We refined our models by testing for main effects of abiotic and biotic environmental variables in order to verify their effects on crown and stem parameters. Biotic variables included species richness, functional diversity, competition index, the dbh of the target tree and mean upper canopy height, while the abiotic variables were slope inclination, slope aspect and soil depth. Target species identity was also included as a categorical predictor variable. Similar to the previous models, plot was included as random effect.

Filter:
Dataset column

Name:
CSP
Definition:
name of the CSP in the Nature ReserveBEF research plot nameReasearch plots of the Biodiversity - Ecosystem functioning experiment (BEF-China). There are three main sites for research plots in the BEF Experiment: Comparative Study Plots (CSP) in the Gutianshan Nature Reserve, having a size of 30x30m^2, measured on the ground.
Unit:
No information available
Datagroup:
BEF research plot name
Keywords:
CSP
Values:
CSP03
CSP02
CSP01
CSP04
CSP05
Contributors:
No information available

Dataset column

Name:
target_group
Definition:
CSP + target tree species
Unit:
No information available
Datagroup:
Group of competitors around a target tree for tree tree interaction.
Keywords:
competitive neighbourhood
Values:
CSP_02Ce
CSP_02Ch
CSP_02Qs
CSP_01Qs
CSP_02Ss
Contributors:
No information available

Dataset column

Name:
fct_gr
Definition:
functional group of target, deciduous or evergreen. As this is specified for each species in a species trait file already, it is included as helper here.
Unit:
No information available
Datagroup:
Leaf habit
Keywords:
No information available
Values:
d
e
Contributors:
No information available

Dataset column

Name:
species
Definition:
species
Unit:
No information available
Datagroup:
Scientific plant species name
Keywords:
species
Values:
Castanea henryi
Castanopsis eyrei
Quercus serrata
Schima superba
Contributors:
No information available

Dataset column

Name:
silverID
Definition:
Silver ID also used by Martin Baruffol
Unit:
No information available
Datagroup:
CSP metal tag number (trees, woody debris)
Keywords:
tree
Values:
363627
369039
369045
363512
369118
Contributors:
No information available

Dataset column

Name:
dbh_08
Definition:
diameter at breast height in 2008
Unit:
cm
Datagroup:
Diameter at breast height
Keywords:
dbh
Values:
10.9
11.050955414012739
10.4
10.095541401273884
11.146496815286623
Contributors:
No information available

Dataset column

Name:
tot_hi
Definition:
total height
Unit:
m
Datagroup:
Plant height
Keywords:
height
Values:
10.8
10
10.6
10.7
10.3
Contributors:
No information available

Dataset column

Name:
bifurcat
Definition:
height of first living branch
Unit:
m
Datagroup:
Bifurcation point
Keywords:
bifurcation point, crown architecture
Values:
10
10.3
0.3
10.8
11.2
Contributors:
No information available

Dataset column

Name:
st_incl
Definition:
stem inclination
Unit:
°
Datagroup:
Stem morphology
Keywords:
stem morphology
Values:
10.533745405717044
10.130387543012215
10.09603821003296
0
10.016797334527386
Contributors:
No information available

Dataset column

Name:
stem_azi
Definition:
azimuth of stem inclination
Unit:
gon
Datagroup:
Stem morphology
Keywords:
No information available
Values:
170
100
160
120
130
Contributors:
No information available

Dataset column

Name:
stem_azi_grad
Definition:
azimuth of stem inclination
Unit:
grad
Datagroup:
Stem morphology
Keywords:
No information available
Values:
108
144
153
162
117
Contributors:
No information available

Dataset column

Name:
stem_azi_rad
Definition:
azimuth of stem inclination
Unit:
rad
Datagroup:
Stem morphology
Keywords:
No information available
Values:
0.47123889803846897
1.2566370614359172
0.7853981633974483
0.3141592653589793
0.9424777960769379
Contributors:
No information available

Dataset column

Name:
mean_rad
Definition:
mean crown radius
Unit:
No information available
Datagroup:
Crown architecture
Keywords:
tree performance, crown architecture
Values:
0.2125
0.425
0.375
0.5
0.5125
Contributors:
No information available

Dataset column

Name:
cr_a
Definition:
crown area
Unit:
No information available
Datagroup:
Crown architecture
Keywords:
No information available
Values:
0.36267027304758787
1.0591704525163363
1.1
10.910265422649871
10.405226086436942
Contributors:
No information available

Dataset column

Name:
ad
Definition:
absolute crown displacement
Unit:
No information available
Datagroup:
Crown architecture
Keywords:
No information available
Values:
0.0014463968646899
0.01599532100933678
0.024982126756529718
0.009758214696380845
0.017820489875381137
Contributors:
No information available

Dataset column

Name:
CI_BD
Definition:
competition index (Biging and Dobbertin, 1992)
Unit:
No information available
Datagroup:
Competition index
Keywords:
competition, light
Values:
0.38715515354767416
0.3762285377054865
0.33516310551431067
0.29549764244903803
0.28791657888980754
Contributors:
No information available

Dataset column

Name:
CI_H
Definition:
competition index (Hegyi, 1974)
Unit:
No information available
Datagroup:
Competition index
Keywords:
competition, light
Values:
0.5136162817330516
0.8549424128427012
0.5800504184834592
0.4519965063494266
0.8587182294986402
Contributors:
No information available

Dataset column

Name:
CI_ME
Definition:
competition index (Martin and Ek 1984)
Unit:
No information available
Datagroup:
Competition index
Keywords:
light, competition
Values:
0.26646389033352885
0.31283826413681987
0.28101154425023644
0.2563999417676191
0.35327493540754534
Contributors:
No information available

Dataset column

Name:
n_neigh
Definition:
number of neighbours
Unit:
No information available
Datagroup:
Abundance
Keywords:
competition
Values:
10
14
12
11
13
Contributors:
No information available

Dataset column

Name:
area_neigh
Definition:
area of circular plot of neighbour evaluation, used as area basis for determination of neighbour indices
Unit:
square meter
Datagroup:
Projected area
Keywords:
No information available
Values:
128.67963509103794
116.89866264007618
124.68981242097888
120.76282160399167
102.07034531513239
Contributors:
No information available

Dataset column

Name:
neigh_a
Definition:
neighbours per area
Unit:
No information available
Datagroup:
Density measure
Keywords:
competition, density, abundance
Values:
0.03221216591504038
0.030450563091561612
0.03396081699872786
0.02192216846995804
0.02065159296175113
Contributors:
No information available

Dataset column

Name:
loc_asp
Definition:
local aspect of target group
Unit:
gon
Datagroup:
Aspect
Keywords:
topography
Values:
110
140
0
120
100
Contributors:
No information available

Dataset column

Name:
loc_asp_grad
Definition:
local aspect of target group
Unit:
rad
Datagroup:
Aspect
Keywords:
No information available
Values:
126
108
144
0
135
Contributors:
No information available

Dataset column

Name:
loc_incl
Definition:
local inclination of target group
Unit:
°
Datagroup:
Inclination
Keywords:
No information available
Values:
22
16
20
24
23
Contributors:
No information available

Dataset column

Name:
n_sp_neigh
Definition:
number of species of neighbours
Unit:
No information available
Datagroup:
Taxonomic biodiversity
Keywords:
biodiversity
Values:
3
4
2
5
10
Contributors:
No information available

Dataset column

Name:
rat_e
Definition:
ratio of evergreens to deciduous of neighbours
Unit:
No information available
Datagroup:
Helper
Keywords:
No information available
Values:
0.56
0.23076923076923078
0.2
0
0.5714285714285714
Contributors:
No information available

Dataset column

Name:
age_pl
Definition:
age of plot, defined in a different dataset on CSP age
Unit:
1,2,3,4,5,
Datagroup:
Helper
Keywords:
No information available
Values:
4
2
1
3
5
Contributors:
No information available

Dataset column

Name:
incl_pl
Definition:
inclination of plot, defined on a different dataset on CSP topography
Unit:
°
Datagroup:
Helper
Keywords:
No information available
Values:
28
20
26
24
25
Contributors:
No information available

Dataset column

Name:
rare_s
Definition:
rarefaction of species number of target groups
Unit:
No information available
Datagroup:
Taxonomic biodiversity
Keywords:
biodiversity
Values:
1.59340659340659
1.57142857142857
1.52380952380952
1.62857142857143
1.28571428571429
Contributors:
No information available

Dataset column

Name:
rare_s_se
Definition:
standard error of rarefaction of species number of target groups
Unit:
No information available
Datagroup:
Taxonomic biodiversity
Keywords:
No information available
Values:
0.185576872239493
0.257539376818848
0.259688306492488
0.238606299212404
0.227872981904675
Contributors:
No information available

Dataset column

Name:
shannon
Definition:
shannon index of target groups
Unit:
No information available
Datagroup:
Taxonomic biodiversity
Keywords:
No information available
Values:
0.95
0.991
0.41
0.796
0.683
Contributors:
No information available

Dataset column

Name:
rare_fg
Definition:
rare faction of functional groups of target group. This was calculated by using the following functional groups: !!!
Unit:
No information available
Datagroup:
Functional biodiversity
Keywords:
functional biodiversity
Values:
1.17316017316017
1.13333333333333
1
1.11931818181818
1.07692307692308
Contributors:
No information available

Dataset column

Name:
rare_fg_se
Definition:
standard error of rare faction of functional groups of target group
Unit:
No information available
Datagroup:
Functional biodiversity
Keywords:
No information available
Values:
0.372677996249965
0.324162541490809
0.266469355010596
0.33993463423952
0
Contributors:
No information available

Dataset column

Name:
rd
Definition:
relative crown displacement
Unit:
ad/mean radius
Datagroup:
Crown architecture
Keywords:
tree performance, crown architecture
Values:
0.006756583839007066
0.009758214696380847
0.007294051607745903
0.00934033343610907
0.0013300201054619772
Contributors:
No information available

Dataset column

Name:
can_hi
Definition:
Upper canopy height wasdefined as themeanheight of the highest 20% trees in the respective group.
Unit:
No information available
Datagroup:
Vegetation layer height
Keywords:
tree layer, height
Values:
11.425
11.38
12
12.1
10.333333333333334
Contributors:
No information available

Dataset column

Name:
mean_can_hi
Definition:
mean canopy height of target groups
Unit:
No information available
Datagroup:
Vegetation layer height
Keywords:
No information available
Values:
11.363888888888889
11.866666666666667
11.36
10.33
10.35
Contributors:
No information available

No information available


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11 h%c3%a4rdtle medium

Werner
Härdtle

Owner of:
39 Datasets

Involved in:
3 Projects

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12 von%20oheimb medium

Goddert
von Oheimb

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41 Datasets

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3 Projects

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10 lang medium

Anne
Lang

Owner of:
11 Datasets

Involved in:
2 Projects

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