Title:
Cover of understorey vegetation in vegetation subplots in June 2012 in the exploratory region in Spain: 1 of 2
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 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 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. The biomass samples are dried for 24 to 48h at 70°C . Then they are weighed and analysed for P, Ca, K, Mg (Laboratory of Forestry, Gontrode, Belgium) and C and N (Institut für Walbau, Universität Freiburg).
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 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, vegetation is subdivided 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 (for analyses of P, Mg, Ca en K content) and afterwards further grinded with a ball mill (MM301, Retsch, Hahn, Germany) in Freiburg (for analysis fo C/N). 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: C/N analysis is done by dry combustion with an elemental analyzer leco truspec™ (Leco, St. Joseph USA). 100-200 mg finely ground sample is wrapped in tin foil and burned with pure oxygen at 950°C. Tin foil rises temperature additionally throughout the burning process. Carbon is detected as CO2 with an infrared measuring cell, nitrogen is reduced to N2 and detected with a thermal conductivity cell. For prediction of C and N content with near infrared spectroscopy spectra are taken from finely ground material with a Tensor 37 spectrometer (Bruker, Ettlingen, Germany). The wavenumber range is 12000 to 3800 cm-1, Resolution is 16 cm-1 with 64 scans for each spectrum. Five spectra are measured for each sample. For at least 100 samples the dry combustion reference analysis is done. With Opus 6.5 software (Bruker, Ettlingen, Germany) spectral information is combined with the corresponding reference value and models to predict unknown samples are developed using PLS (partial least square) regression.
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 |
SPA03 |
SPA04 |
SPA01 |
SPA05 |
Contributors:
No information available
Dataset column
Name:
subplot number
Definition:
plot number followed by a, b, c to indicate which subplot within the plot is considered
Unit:
No information available
Datagroup:
Sub plot id
Keywords:
No information available
Values:
10b |
11a |
10c |
10a |
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:
4 |
1 |
3 |
2 |
Contributors:
No information available
Dataset column
Name:
target Pinus nigra
Definition:
Absence/presence of Pinus nigra 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 Pinus sylvestris
Definition:
Absence/presence of Pinus sylvestris 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 Quercus faginea
Definition:
Absence/presence of Quercus faginea 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 Quercus ilex
Definition:
Absence/presence of Quercus ilex in overstorey as target tree species
Unit:
No information available
Datagroup:
Presence data
Keywords:
No information available
Values:
1 |
0 |
Contributors:
No information available
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Name:
Carduncellus monspeliensium
Definition:
% cover by Carduncellus monspeliensium
Unit:
%
Datagroup:
Species composition
Keywords:
No information available
Values:
0 |
0.1 |
Contributors:
No information available
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Name:
Centaurea sp.
Definition:
% cover by Centaurea sp.
Unit:
%
Datagroup:
Species composition
Keywords:
No information available
Values:
0.1 |
0 |
Contributors:
No information available
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Name:
Coronilla minima
Definition:
% cover by Coronilla minima
Unit:
%
Datagroup:
Species composition
Keywords:
No information available
Values:
0 |
0.1 |
Contributors:
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Name:
Erodium cicutarium
Definition:
% cover by Erodium cichutarium
Unit:
%
Datagroup:
Species composition
Keywords:
No information available
Values:
0.1 |
0 |
Contributors:
No information available
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