Title:
Cover of understorey vegetation in biomass subplots in June 2012 in the exploratory region in Spain
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' (seedlings, 'green' herbs). The biomass samples are dried for 24 to 48h at 70°C . Then they are weighed and analysed for P, Ca, K, Mg, 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' (seedlings, 'green' herbs). Preparation of biomass samples for chemical analyses: dried at 70°C, grinded using a sieve of 1mm. Before analyses of Ca, Mg, K en 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 Ca-content: destruction of biomass sample with the above mentioned method. Then the sample is diluted, 10% CsCI is added as modifer on the AAS (Varian SpectrAA 220) and calibrated to 5mg Ca/l and atomized in a nitrous oxide-acetylene flame, absorption is measured at 422.7nm. The analytical quality of the analysis is verified by repeated measurement of blanco and control samples.
Analysis for K-content: destruction of biomass sample with the above mentioned method. Then the sample is diluted, 10% CsCI is added as modifer on the AAS (Varian SpectrAA 220) and calibrated to 1mg K/l and atomized in a air-acetylene flame, absorption is measured at 766.5nm. The analytical quality of the analysis is verified by repeated measurement of blanco and control samples.
Analysis for Mg-content: destruction of biomass sample with the above mentioned method. Then the sample is diluted, 10% CsCI is added as modifer on the AAS (Varian SpectrAA 220) and calibrated to 0.5mg Mg/l and atomized in a air-acetylene flame, absorption is measured at 258.2nm. The analytical quality of the analysis is verified by repeated measurement of blanco and control samples.
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:
Spain
Temporal extent:
Spring 2012
Taxonomic extent:
understorey vegetation: woody and non-woody vascular species (herbs, seedlings) < 1.3m
Measurement cirumstances:
Dry weather
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:
SPA02 |
SPA04 |
SPA05 |
SPA03 |
SPA01 |
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:
10a |
10b |
11a |
10c |
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:
1 |
2 |
4 |
3 |
Contributors:
No information available
Dataset column
Name:
target Pinus nigra
Definition:
Absence/presence of Pinus nigra in overstorey as target tree species; Datagroup description: Presence data
Unit:
No information available
Datagroup:
Presence data
Keywords:
No information available
Values:
1 |
0 |
Contributors:
No information available
Dataset column
Name:
target Pinus sylvestris
Definition:
Absence/presence of Pinus sylvestris in overstorey as target tree species; Datagroup description: Presence data
Unit:
No information available
Datagroup:
Presence data
Keywords:
No information available
Values:
0 |
1 |
Contributors:
No information available
Dataset column
Name:
target Quercus faginea
Definition:
Absence/presence of Quercus faginea in overstorey as target tree species; Datagroup description: Presence data
Unit:
No information available
Datagroup:
Presence data
Keywords:
No information available
Values:
1 |
0 |
Contributors:
No information available
Dataset column
Name:
target Quercus ilex
Definition:
Absence/presence of Quercus ilex in overstorey as target tree species; Datagroup description: Presence data
Unit:
No information available
Datagroup:
Presence data
Keywords:
No information available
Values:
1 |
0 |
Contributors:
No information available
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Name:
Coronilla minima
Definition:
% cover by Coronilla minima
Unit:
%
Datagroup:
Species composition
Keywords:
process, understorey productivity
Values:
0 |
0.1 |
Contributors:
No information available
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Name:
Hypochoeris achyrophorus
Definition:
% cover by Hypochoeris achyrophorus
Unit:
%
Datagroup:
Species composition
Keywords:
process, understorey productivity
Values:
0.1 |
0 |
Contributors:
No information available
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Name:
Plantago holosteum
Definition:
% cover by Plantago holosteum
Unit:
%
Datagroup:
Species composition
Keywords:
process, understorey productivity
Values:
0.1 |
3 |
0 |
Contributors:
No information available
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Name:
Vicia angustifolia
Definition:
% cover by Vicia angustifolia
Unit:
%
Datagroup:
Species composition
Keywords:
process, understorey productivity
Values:
0.1 |
0 |
Contributors:
No information available
Dataset column
Dataset column
Dataset column
Name:
Remarks
Definition:
Remarks about plot/subplot
Unit:
No information available
Datagroup:
Helper
Keywords:
No information available
Values:
bare soil = rocks |
a dry pasture land with no trees and shrubs - species rich, many annuals! |
grazed by sheep |
bare soil: rocks! |
a grassy meadow |
No information available
No information available
No information avialable
Filter:
No information available
No information available
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No information available