Supplement 1. Data from the BIODEPTH project (15 ecosystem-process variables measured at eight different European grassland field sites over three years) together with metadata and a table with site information.
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
Data files are in ASCII format (tab-delimited text files).
The file convention is: variable.name.ext
File extensions: ASCII = .txt ; compressed files = .zip ; PDF = .pdf.
Data and metadata files have been compressed using Microsoft Windows XP file manager (right click / send to / compressed (zipped) folder).
Eleven tab-delimited text files have been grouped and compressed as BIODEPTH.PROCESSES.zip
BIODEPTH.PROCESSES.zip 100 kilobytes, (11 files)
1. Design.txt (lines=481, columns=9)
plot, location, block, composition, species.richness, functional.richness, grasses, legumes, forbs
2. Observed.Species.Richness.txt (lines=1441, columns=9)
year, plot, location, block, composition, species.richness, functional.richness, legumes, species.observed
3. Cover.txt (lines=1441; columns=9)
year, plot, location, block, composition, species.richness, functional.richness, legumes, cover
4. Shoots.txt (lines=1441; columns=9)
year, plot, location, block, composition, species.richness, functional.richness, legumes, biomass
5. Partitioning.txt (lines=1129; columns=11)
year, plot, location, block, composition, species.richness, functional.richness, legumes, net.effect, complementarity.effect, selection.effect
6. Canopy.txt (lines=481; columns=10)
plot, location, block, composition, species.richness, functional.richness, legumes, height3, light3, gravity3
7. Canopy.Layers.txt (lines=2003; columns=13)
plot, location, block, composition, species.richness, functional.richness, legumes, layer.top, layer.bottom, layer.thickness, midpoint, biomass, density
8. N.vegetation.txt (lines=481; columns=10)
plot, location, block, composition, species.richness, functional.richness, legumes, mass.g.m2, N.percent, N.g.m2
9. Roots.txt (lines=481; columns=8)
plot, location, block, composition, species.richness, functional.richness, legumes, root3
10. N.soil.txt (lines=368; columns=8)
plot, location, block, composition, species.richness, functional.richness, legumes, N.total
11. Decomposition.txt (lines=481; columns=9)
plot, location, block, composition, species.richness, functional.richness, legumes, cotton3, wood3.
We present a database of 15 response variables documenting the relationship between plant diversity and ecosystem functioning within the European BIODEPTH network of plant-diversity manipulation experiments. The data quantify key ecosystem processes and related variables: (1) Observed species richness; (2) Vegetation percent cover; (3, 4) Plant biomass above- and belowground; (5–8) Average height of leaf canopy, canopy biomass density and center of gravity, percentage of transmitted PAR at ground level; (9, 10) Decomposition of wooden sticks and cotton strips; (11, 12) Nitrogen pools in aboveground vegetation and available soil nitrogen; (13–15) The net, selection, and complementarity effects following the additive-partitioning method.
Plant diversity was manipulated in terms of richness -- both species richness (numbers of species per plot) and functional-group richness (numbers of plant functional groups per plot) and species composition. Our plant functional-group categorization separated N-fixing legumes from other herbaceous species and grasses from the remaining herbaceous species. Results of the analysis of the 15 ecosystem-process response variables in relation to the explanatory variables given in the description of the experimental design above are reported in a companion paper for which this paper is a linked supplement.
Differences between sites explained substantial and significant amounts of the variation of most of the ecosystem processes examined. However, against this background of geographic variation, all the aspects of plant diversity and composition we examined (i.e., both numbers and types of species and functional groups) produced significant, mostly positive impacts on ecosystem processes. Analyses using the additive-partitioning method revealed consistent complementarity effects, which were stronger than the more variable selection effect. In general, communities with a higher diversity of species and functional groups were more productive and utilized resources more completely by intercepting more light, taking up more nitrogen and occupying more of the available space. The ecosystem effects of plant diversity varied between sites and between years. However, in general, diversity effects were lowest in the first year and stronger later in the experiment. These analyses of our complete ecosystem process dataset largely reinforce our previous results, and those from comparable biodiversity experiments, and extend the generality of diversity–ecosystem functioning relationships to multiple sites, years, and processes.
Key words: BIODEPTH, European plant-experiment network; biodiversity; complementarity; ecosystem functioning; ecosystem processes; functional groups; grassland field sites, European; plant diversity; selection effect; species richness.
Class I: Data set descriptorsTitle or Theme of Data set: “BIODEPTH ecosystem processes”Name of Dataset Originator/Owner: “Prof. John Lawton”Citation for Data use: “Data provided by the BIODEPTH project”Data Abstract(purpose or context): “Ecosystem process responses to manipulation of plant diversity in European grasslands”E-mail Address of Data set Contact: “email@example.com”Key words: Ecosystem processes, biodiversity, grasslands”Research Period: “ 19950501 19991231”Location: “see Methods”Location: “see Methods ”Phone Number of Data set Contact: “00 41 (0)1 635 4804”Address1 of Data set Contact: “Institute of Environmental Sciences”Address2 of Data set Contact: “University of Zürich”Address3 of Data set Contact: “Winterthurerstrasse 190, Zürich 8057, Switzerland”Control Number: “[to be assigned by Ecological Archives?]”
Class II: Research Origin Descriptors