CSPs: Tree neighbour competitive traits in the comparative study plots - target groups

Usage Rights

This data is Free for public.

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)

Dataset 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.

Dataset 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).

Published

Lang et al. 2010, FORECO 260, 1708-1715; http://dx.doi.org/10.1016/j.foreco.2010.08.015

Taxonomic Extent

Target tree species are: Schima superba, Quercus serrata, Castanopsis eyrei, Castanea henryi

Measurement Circumstances

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.

Paper proposal submissions

Published

2011

2010

Data columns available in the raw data part of this dataset

CSP
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.
Data group: BEF research plot name
Keywords: CSP
Values
CSP02
CSP04
CSP01
CSP05
CSP03
target_group
CSP + target tree species
Data group: Group of competitors around a target tree for tree tree interaction.
Keywords: competitive neighbourhood
Values
CSP_02Ch
CSP_02Qs
CSP_02Ce
CSP_01Qs
CSP_02Ss
fct_gr
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.
Data group: Leaf habit
Values
d
e
species
species
Data group: Scientific plant species name
Keywords: species
Values
Schima superba
Quercus serrata
Castanopsis eyrei
Castanea henryi
silverID
Silver ID also used by Martin Baruffol
Data group: CSP metal tag number (trees, woody debris)
Keywords: tree
Values
369039
363512
369045
363627
369118
dbh_08
diameter at breast height in 2008
Unit: cm
Data group: Diameter at breast height
Keywords: dbh
Values
10.9
10.095541401273884
10.4
11.146496815286623
11.050955414012739
tot_hi
total height
Unit: m
Data group: Plant height
Keywords: height
Values
10.3
10
10.7
10.6
10.8
bifurcat
height of first living branch
Unit: m
Data group: Bifurcation point
Keywords: bifurcation point, crown architecture
Values
0.3
10.3
10.8
10
11.2
st_incl
stem inclination
Unit: °
Data group: Stem morphology
Keywords: stem morphology
Values
10.533745405717044
10.016797334527386
10.130387543012215
10.09603821003296
0
stem_azi
azimuth of stem inclination
Unit: gon
Data group: Stem morphology
Values
160
100
130
120
170
stem_azi_grad
azimuth of stem inclination
Unit: grad
Data group: Stem morphology
Values
117
144
162
108
153
stem_azi_rad
azimuth of stem inclination
Unit: rad
Data group: Stem morphology
Values
0.7853981633974483
0.3141592653589793
0.47123889803846897
1.2566370614359172
0.9424777960769379
mean_rad
mean crown radius
Data group: Crown architecture
Keywords: tree performance, crown architecture
Values
0.375
0.5
0.5125
0.2125
0.425
cr_a
crown area
Data group: Crown architecture
Values
0.36267027304758787
10.910265422649871
10.405226086436942
1.1
1.0591704525163363
ad
absolute crown displacement
Data group: Crown architecture
Values
0.017820489875381137
0.01599532100933678
0.024982126756529718
0.0014463968646899
0.009758214696380845
CI_BD
competition index (Biging and Dobbertin, 1992)
Data group: Competition index
Keywords: competition, light
Values
0.3762285377054865
0.38715515354767416
0.28791657888980754
0.33516310551431067
0.29549764244903803
CI_H
competition index (Hegyi, 1974)
Data group: Competition index
Keywords: competition, light
Values
0.8549424128427012
0.4519965063494266
0.5136162817330516
0.5800504184834592
0.8587182294986402
CI_ME
competition index (Martin and Ek 1984)
Data group: Competition index
Keywords: light, competition
Values
0.2563999417676191
0.35327493540754534
0.31283826413681987
0.26646389033352885
0.28101154425023644
n_neigh
number of neighbours
Data group: Abundance
Keywords: competition
Values
11
14
10
13
12
area_neigh
area of circular plot of neighbour evaluation, used as area basis for determination of neighbour indices
Unit: square meter
Data group: Projected area
Values
124.68981242097888
128.67963509103794
116.89866264007618
120.76282160399167
102.07034531513239
neigh_a
neighbours per area
Data group: Density measure
Keywords: competition, density, abundance
Values
0.02065159296175113
0.03221216591504038
0.02192216846995804
0.030450563091561612
0.03396081699872786
loc_asp
local aspect of target group
Unit: gon
Data group: Aspect
Keywords: topography
Values
120
100
110
0
140
loc_asp_grad
local aspect of target group
Unit: rad
Data group: Aspect
Values
126
135
108
0
144
loc_incl
local inclination of target group
Unit: °
Data group: Inclination
Values
20
22
16
23
24
n_sp_neigh
number of species of neighbours
Data group: Taxonomic biodiversity
Keywords: biodiversity
Values
4
5
10
3
2
rat_e
ratio of evergreens to deciduous of neighbours
Data group: Helper
Values
0
0.2
0.56
0.5714285714285714
0.23076923076923078
age_pl
age of plot, defined in a different dataset on CSP age
Unit: 1,2,3,4,5,
Data group: Helper
Values
1
5
3
4
2
incl_pl
inclination of plot, defined on a different dataset on CSP topography
Unit: °
Data group: Helper
Values
20
26
25
24
28
rare_s
rarefaction of species number of target groups
Data group: Taxonomic biodiversity
Keywords: biodiversity
Values
1.62857142857143
1.57142857142857
1.28571428571429
1.59340659340659
1.52380952380952
rare_s_se
standard error of rarefaction of species number of target groups
Data group: Taxonomic biodiversity
Values
0.185576872239493
0.238606299212404
0.257539376818848
0.259688306492488
0.227872981904675
shannon
shannon index of target groups
Data group: Taxonomic biodiversity
Values
0.796
0.95
0.683
0.991
0.41
rare_fg
rare faction of functional groups of target group. This was calculated by using the following functional groups: !!!
Data group: Functional biodiversity
Keywords: functional biodiversity
Values
1.13333333333333
1.07692307692308
1.17316017316017
1
1.11931818181818
rare_fg_se
standard error of rare faction of functional groups of target group
Data group: Functional biodiversity
Values
0
0.372677996249965
0.266469355010596
0.33993463423952
0.324162541490809
rd
relative crown displacement
Unit: ad/mean radius
Data group: Crown architecture
Keywords: tree performance, crown architecture
Values
0.0013300201054619772
0.007294051607745903
0.009758214696380847
0.00934033343610907
0.006756583839007066
can_hi
Upper canopy height wasdefined as themeanheight of the highest 20% trees in the respective group.
Data group: Vegetation layer height
Keywords: tree layer, height
Values
11.425
10.333333333333334
12.1
11.38
12
mean_can_hi
mean canopy height of target groups
Data group: Vegetation layer height
Values
10.33
11.36
10.35
11.866666666666667
11.363888888888889