Weight and nutrient content of understorey vegetation in biomass subplots in May 2012 in the exploratory region in Germany

Usage Rights

This data is Free within projects.

FunDiv-intern

Dataset Abstract

Most of the plant diversity in European forests is found in the understorey, and despite its relatively low biomass compared to the forest overstorey, its functional importance is high (nectar source for pollinators, habitat for small mammals, affects tree regeneration, invasion resistance, decomposition and nutrient cycling (Gilliam 2007). Relationships between overstorey and understorey diversity and composition is tackled. For each of the plots per focal region, the core plot is divided in nine quadrants.For each of the plots per focal region, the core plot is divided in nine quadrants. In three quadrants (upper right, central, lower left), a vegetation subplot of 5 m x 5 m (as close as possible to the central quadrant; subplot in the central quadrant located in the upper half) is marked for identification and estimation of cover of understorey vascular plant species. Location of subplots exclude major heterogeneities at any scale of sampling (tree trunks, tracks and paths, streams and ponds, peaty pools, boulders and cliffs…). Thus, terricolous plants growing on mineral and organic soil of the undisturbed forest floor are represented. Within this subplot, understorey vegetation is identified (species, cover) and afterwards clipped in a zone of 0.5 m x 0.5 m (biomass subplot), where understorey vegetation is relatively abundant and where vegetation composition is representative for the whole subplot. Then, biomass is divided into 'woody' (woody juveniles, woody plants) and 'non-woody' (young seedlings, 'green' herbs). The biomass samples are dried for 24 to 48h at 70°C . Then they are weighed and analysed for P, C, N (Forest & Nature Lab, Ghent University).

Dataset Design

For each of the plots per focal region, the core plot is divided in nine quadrants. In three quadrants (upper right, central, lower left), a subplot of 5 m x 5 m (as close as possible to the central quadrant; subplot in the central quadrant located in the upper half) is marked for identification and estimation of cover of understorey vascular plant species (species, cover, maximum height, development stage). Within this subplot, understorey vegetation is identified (species, cover) and afterwards clipped in a zone of 0.5 m x 0.5 m, where understorey vegetation is relatively abundant and where vegetation composition is representative for the whole subplot. Then, biomass is divided into 'woody' (woody juveniles, woody plants) and 'non-woody' (young seedlings, 'green' herbs). Preparation of biomass samples for chemical analyses: dried at 70°C, grinded using a sieve of 1mm. Before analyses of P-content, grinded biomass samples are 'destroyed' with HNO3/HClO4, diluted with demineralised water and filtered according to the method of Varian Instruments at work, AA-24 (McKenzie T., 1982. Automated multielement analysis of plant material by flame atomic absorption spectroscopy. Varian Instruments at work, AA-24)
Analysis for P-content: destruction of biomass sample with the above mentioned method, then reaction of the destroyed biomass sample with metholsulphite, ammoniumheptamolybdate and sodiumacetate solution. Finally, measurement of the total P-content with a spectrophotometer type Varian Cary 50 at 700nm (Chemical analysis of plants and soils. Cottenie, Verloo,... Laboratory of analytical and agrochemistry, RUG). Analyses for C,N: analysis is done using an Elementar analyzer, type Vario Macro Cube in configuration CNS, with Argon as carrier gas. Catalytic combustion of the sample (1.5g) is carried out at a permanent temperature of up to 1200°C. This is followed by reduction of the combustion gasses on hot copper in the refuction tube. The formed gasses N2, CO2, H2O, SO2 are separated via purge and trep chromatography and afterwards detected on a thermal conductivity detector (TCD). A connected PC computes the element concentration from the detector signal, and the sample weight on the basis of stored calibration curves.

Spatial Extent

Germany, Hainich region

Temporal Extent

Spring 2012

Taxonomic Extent

understorey vegetation: woody and non-woody vascular species (herbs, seedlings) < 1.3m

Measurement Circumstances

rain showers on certain days

Data columns available in the raw data part of this dataset

plot number
unique number ascribed to each plot
Data group: Exploratory plot id
Values
GER01
GER05
GER03
GER02
GER04
subplot number
indicates which subplot within the plot is considered
Data group: Sub plot id
Values
10a
10c
11a
10b
11b
diversity
Number of target tree species present in subplot
Data group: Species richness
Keywords: diversity
Values
1
4
2
3
target Fagus sylvatica
Absence/presence of Fagus sylvatica in overstorey as target tree species
Data group: Presence data
Values
1
0
target Fraxinus excelsior
Absence/presence of Fraxinus excelsior in overstorey as target tree speciesv
Data group: Presence data
Values
0
1
target Quercus spp.
Absence/presence of Quercus spp. (mainly petraea) in overstorey as target tree species
Data group: Presence data
Values
0
1
target Picea abies
Absence/presence of Picea abies in overstorey as target tree species
Data group: Presence data
Values
0
1
target Acer pseudoplatanus
Absence/presence of Acer pseudoplatanus in overstorey as target tree species
Data group: Presence data
Values
0
1
Weight non-woody
Weight of non-woody biomass present in biomass sample
Unit: g
Data group: Biomass
Keywords: process, understorey productivity
Values
0.233
0.499
0.47736363636363777
0.349
0
P non-woody
P content of non-woody biomass present in biomass sample
Unit: mg/kg
Data group: Biomass nutrient concentration
Keywords: process, P
Values
1546.310307017544
1407.1420118343194
1674.611872146119
1507.057803468208
1409.3970420932876
* These persons could not be matched within the portal: Luc Willems, Greet De bruyn also contributed to this column.
C non-woody
C content of non-woody biomass present in biomass sample
Unit: %
Data group: Biomass nutrient concentration
Keywords: process, C
Values
39.643
39.692
38.539
40.41
40.399
* These persons could not be matched within the portal: Luc Willems, Greet De bruyn also contributed to this column.
N non-woody
N content of non-woody biomass present in biomass sample
Unit: %
Data group: Biomass nutrient concentration
Keywords: process, N
Values
2.608
2.485
2.403
2.46
2.484
* These persons could not be matched within the portal: Luc Willems, Greet De bruyn also contributed to this column.
Weight woody
Weight of woody biomass present in biomass sample
Unit: g
Data group: Biomass
Keywords: process, understorey productivity
Values
0
0.172
0.129
0.053
0.068
P woody
P content of woody biomass present in biomass sample
Unit: mg/kg
Data group: Biomass nutrient concentration
Keywords: process, P
Values
1006.1158536585364
1028.3765432098764
1013.0546623794213
1044.212454212454
1076.4285714285713
* These persons could not be matched within the portal: Luc Willems, Greet De bruyn also contributed to this column.
C woody
C content of woody biomass present in biomass sample
Unit: %
Data group: Biomass nutrient concentration
Keywords: process, C
Values
44.864
44.206
1.449
45.393
1.5750000000000002
* These persons could not be matched within the portal: Luc Willems, Greet De bruyn also contributed to this column.
N woody
N content of woody biomass present in biomass sample
Unit: %
Data group: Biomass nutrient concentration
Keywords: process, N
Values
0.753
0.819
0.766
0.818
0.845
* These persons could not be matched within the portal: Luc Willems, Greet De bruyn also contributed to this column.
Remarks
Remarks about plot/subplot/sample
Data group: Helper
Values
2m² bare soil, caused by earthworm sampling
biomass sample in very bad condition (mouldy), much dead wood in plot
biomass sample in very bad condition (mouldy)
dead tree across the subplot
big dead spruce across the subplot, big gap at northern end of plot --> light!
* Berger, S. also contributed to this column.