Title:
Weight and nutrient content of understorey vegetation in biomass subplots in May 2012 in the exploratory region in Germany
Access rights:
Free within projects
Usage rights:
FunDiv-intern
Published:
No information available
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).
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 cirumstances:
rain showers on certain days
Data analysis:
No information available
Filter:
Dataset column
Name:
plot number
Definition:
unique number ascribed to each plot
Unit:
No information available
Datagroup:
Exploratory plot id
Keywords:
No information available
Values:
GER02 |
GER03 |
GER05 |
GER04 |
GER01 |
Contributors:
No information available
Dataset column
Name:
subplot number
Definition:
indicates which subplot within the plot is considered
Unit:
No information available
Datagroup:
Sub plot id
Keywords:
No information available
Values:
10c |
10a |
10b |
11a |
11b |
Contributors:
No information available
Dataset column
Name:
diversity
Definition:
Number of target tree species present in subplot
Unit:
No information available
Datagroup:
Species richness
Keywords:
diversity
Values:
3 |
1 |
4 |
2 |
Contributors:
No information available
Dataset column
Name:
target Fagus sylvatica
Definition:
Absence/presence of Fagus sylvatica in overstorey as target tree species
Unit:
No information available
Datagroup:
Presence data
Keywords:
No information available
Values:
0 |
1 |
Contributors:
No information available
Dataset column
Name:
target Fraxinus excelsior
Definition:
Absence/presence of Fraxinus excelsior in overstorey as target tree speciesv
Unit:
No information available
Datagroup:
Presence data
Keywords:
No information available
Values:
1 |
0 |
Contributors:
No information available
Dataset column
Name:
target Quercus spp.
Definition:
Absence/presence of Quercus spp. (mainly petraea) in overstorey as target tree species
Unit:
No information available
Datagroup:
Presence data
Keywords:
No information available
Values:
0 |
1 |
Contributors:
No information available
Dataset column
Name:
target Picea abies
Definition:
Absence/presence of Picea abies in overstorey as target tree species
Unit:
No information available
Datagroup:
Presence data
Keywords:
No information available
Values:
1 |
0 |
Contributors:
No information available
Dataset column
Name:
target Acer pseudoplatanus
Definition:
Absence/presence of Acer pseudoplatanus in overstorey as target tree species
Unit:
No information available
Datagroup:
Presence data
Keywords:
No information available
Values:
0 |
1 |
Contributors:
No information available
Dataset column
Name:
Weight non-woody
Definition:
Weight of non-woody biomass present in biomass sample
Unit:
g
Datagroup:
Biomass
Keywords:
process, understorey productivity
Values:
0.47736363636363777 |
0.233 |
0.349 |
0 |
0.499 |
Contributors:
No information available
Dataset column
Name:
P non-woody
Definition:
P content of non-woody biomass present in biomass sample
Unit:
mg/kg
Datagroup:
Biomass nutrient concentration
Keywords:
process, P
Values:
1409.3970420932876 |
1507.057803468208 |
1407.1420118343194 |
1674.611872146119 |
1546.310307017544 |
Contributors:
These persons could not be matched within the portal: Luc Willems, Greet De bruyn
Dataset column
Name:
C non-woody
Definition:
C content of non-woody biomass present in biomass sample
Unit:
%
Datagroup:
Biomass nutrient concentration
Keywords:
process, C
Values:
38.539 |
40.399 |
40.41 |
39.692 |
39.643 |
Contributors:
These persons could not be matched within the portal: Luc Willems, Greet De bruyn
Dataset column
Name:
N non-woody
Definition:
N content of non-woody biomass present in biomass sample
Unit:
%
Datagroup:
Biomass nutrient concentration
Keywords:
process, N
Values:
2.403 |
2.485 |
2.608 |
2.46 |
2.484 |
Contributors:
These persons could not be matched within the portal: Luc Willems, Greet De bruyn
Dataset column
Name:
Weight woody
Definition:
Weight of woody biomass present in biomass sample
Unit:
g
Datagroup:
Biomass
Keywords:
process, understorey productivity
Values:
0.068 |
0.172 |
0.129 |
0.053 |
0 |
Contributors:
No information available
Dataset column
Name:
P woody
Definition:
P content of woody biomass present in biomass sample
Unit:
mg/kg
Datagroup:
Biomass nutrient concentration
Keywords:
process, P
Values:
1006.1158536585364 |
1044.212454212454 |
1013.0546623794213 |
1028.3765432098764 |
1076.4285714285713 |
Contributors:
These persons could not be matched within the portal: Luc Willems, Greet De bruyn
Dataset column
Name:
C woody
Definition:
C content of woody biomass present in biomass sample
Unit:
%
Datagroup:
Biomass nutrient concentration
Keywords:
process, C
Values:
1.5750000000000002 |
44.206 |
45.393 |
1.449 |
44.864 |
Contributors:
These persons could not be matched within the portal: Luc Willems, Greet De bruyn
Dataset column
Name:
N woody
Definition:
N content of woody biomass present in biomass sample
Unit:
%
Datagroup:
Biomass nutrient concentration
Keywords:
process, N
Values:
0.819 |
0.845 |
0.818 |
0.766 |
0.753 |
Contributors:
These persons could not be matched within the portal: Luc Willems, Greet De bruyn
Dataset column
Name:
Remarks
Definition:
Remarks about plot/subplot/sample
Unit:
No information available
Datagroup:
Helper
Keywords:
No information available
Values:
2m² bare soil, caused by earthworm sampling |
dead tree across the subplot |
big dead spruce across the subplot, big gap at northern end of plot --> light! |
biomass sample in very bad condition (mouldy), much dead wood in plot |
biomass sample in very bad condition (mouldy) |
Contributors:
No information available
No information available
No information available
No information avialable
Filter:
No information available
No information available
No information available
No information available
No information available