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.
Ecological Archives M075-001-S1.
File list (downloads)
Correspondent: Andy Hector
Institute of Environmental Sciences
University of Zürich
Zürich 8057, Switzerland
Phone: ++41 (0)1 635 4804, Fax: ++41 (0)1 635 5711
E. M. Spehn2
M. C. Caldeira6
P. G. Dimitrakopoulos7
J. A. Finn8, 24
H. Freitas6, 17
P. S. Giller8
A. Jumpponen9, 19
P. W. Leadley13
A. Minns1, 23
C. P. H. Mulder10, 20
G. O’Donovan8, 21
S. J. Otway1
J. S. Pereira6
A. B. Pfisterer3
A. Prinz5, 22
D. J. Read14
A-S. D. Siamantziouras7
A. C. Terry14
A. Y. Troumbis7
F. I. Woodward14
J. H. Lawton1
1 Natural Environmental Research Council (NERC) center for Population Biology, Imperial College London, Silwood Park campus, Ascot, Berkshire, U.K., SL5 7PY.
2 Institute of Botany, University of Basel, Schoenbeinstrasse 6, Basel, Switzerland, Switzerland CH-4056.
3 Institute of Environmental Sciences, University of Zurich, Winterthurerstrasse 190, Zürich, Switzerland, Switzerland CH-8057.
4 Max-Planck-Institute for Biogeochemistry, Postfach 10 01 64, Jena, Germany, D-07701.
5 Lehrstuhl Biogeographie, Universität Bayreuth, Bayreuth, Germany, D-95440.
6 Departmentos de Engenharia Florestal e de Botânica, Universidade Tecnica de Lisboa, Tapada da Ajuda, Lisboa, Portugal, PT-1399.
7 Biodiversity Conservation Laboratory, Department of Environmental Studies, University of the Aegean, Karadoni 17, Mytilene, Lesbos, Greece, Greece-81100.
8 Department of Zoology, Ecology and Plant Science, University College Cork, Lee Maltings, Prospect Row, Cork, Ireland.
9 Department of Forest Ecology, Swedish University of Agricultural Sciences, Umeå, Sweden, SE-90183.
10 Crop Science Section, Department of Agricultural Research for Northern Sweden, Box 4097, Swedish University of Agricultural Sciences, Umeå, Sweden, SE-90403.
11 Section of Ecology, Department of Biology, University of Turku, 20014 Turku, Finland.
12 Laboratoire d’Ecologie, UMR 7625, Ecole Normale Supérieure, 46 Rue d’Ulm, F-72530 Paris Cedex 05, France, FR-75230.
13 Ecologie des Populations et Communautés, Université Paris Sud XI, URA CNRS 2154, Bâtiment 326, Orsay Cedex, France, FR-91405.
14 Department of Animal and Plant Sciences, University of Sheffield, South Yorkshire, U.K., GB-S10 2TN.
15 Research Institute for Humanity and Natue (RINH), Kamigyo-Ku, Kyoto 606-0878 Japan.
16 Present address: Institute of Environmental Sciences, University of Zurich, Winterthurerstrasse 190, Zürich, Switzerland, Switzerland-8057.
17 Present address: Departamento de Botânica, Universidade de Coimbra, 3000 Coimbra, Portugal.
18 Present address: Swiss Federal Institute of Technology (ETH), Institute of Plant Sciences, Universitätsstrasse 2, Zürich, Switzerland CH-8092.
19 Present address: Division of Biology, Kansas State University, Manhattan, Kansas 66506 USA.
20 Present address: Department of Biology and Wildlife and Institute of Arctic Biology, University of Alaska, Fairbanks, Alaska 99775-7000 USA.
21 Present address: Department of Environmental Resource Management, University College of Dublin, Belfield, Dublin, Ireland.
22 Landesbund für Vogelschutz, Hilpoltstein, Germany, D-91157.
23 Present address: Tyndall Center for Climate Change Research, School of Environmental Sciences, University of East Anglia, Norwich, Norfolk, NR4 7TJ, UK.
24 Present address: Teagasc Environmental Research Centre, Johnston Castle, Wexford, Ireland.
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; (58) 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; (1315) 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: “firstname.lastname@example.org”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 DescriptorsResearch Project Title: “BIODEPTH: BIOdiversity and Ecosystem Processes in Terrestrial Herbaceous ecosystems”Name of Principle Investigator: “Prof. John Lawton”Address1 of Principle Investigator: “Imperial College London”Address2 of Principle Investigator: “Silwood Park campus”Address3 of Principle Investigator: “Ascot, Berks, SL5 7PY, UK”Email Address of Principle Investigator: “HQPO@nerc.ac.uk”Phone Number of Principle Investigator: “00 44 (0)1793 411599”Scope and Purpose of Research Programme: “Biodiversity and ecosystem functioning experiments in European grasslands”Research Abstract: “see Abstract”Citation for Funding Agency: “European Commission, Framework IV Environment and Climate programme (ENV-CT95-0008)”Research Site description: “see Methods”Research Site size: “see Methods”Habitat Characteristics: “Grassland”Geology: “see Methods”Hydrology: “see Methods”History: “see Methods”Climate: “see Methods”Experimental Design: “Gradients of species and functional-group richness (numbers) nested within eight sites. Richness gradients repeated within sites in two blocks to replicate species composition”Permanent Plot Characteristics: “see Methods”Sampling Regime: “see Methods”Field/Laboratory Methods: “see Methods”Instrumentation: “see Methods”Taxonomy and Systematics: “species-level data and analysis in preparation for publication in a following pair of papers”Personnel: “see Methods”
Class III: Data Set Status and AccessibilityDate of Last Data Update: “7 January 2002”Date of Last Data Archival: “7 January 2002”Date of Last Data Metadata Update and Current Status: “This data set: 7 January 2002 (it does not include some additional variables and data from later years (>3) measured only at a one or a few sites”Status of Data Quality Assurance Checking: “See Methods”Where Data Reside: “NERC center for Population Biology, Imperial College London.”Data Access Contact: “Andy Hector”Address1 of Data set Contact: “Institute of Environmental Sciences”Address2 of Data set Contact: “University of Zurich”Address3 of Data set Contact: “Winterthurerstrasse 190, CH-8057 Zürich”Email Address of Data set Contact “email@example.com”Phone Number of Data set Contact: “+41 (0) 1 635 5711”Intellectual Property Restrictions: “Cite as below”Expiration Date of Restrictions: “NA”How the Data Should be Cited: “Spehn et al. (2005: supplement) in text and the full citation should be to the original article, Spehn et al. 2005. Ecosystem effects of biodiversity manipulations in European grasslands. Ecological Monographs 75:3763.”Disclaimers: “Data correct at dates given above but later additions and corrections may still continue to be made”Cost for Data: “None”
Class IV: Data Set Structural DescriptorsUnique File Name: “BIODEPTH.PROCESSES.zip”File Size: “77 KB”File Type: “txt, tab delimited”Header Information: “variable.name”Alphanumeric Case Attributes: “”Special Characters: “NA = not available (missing values)”Authentication Procedures: “”
Class V: Supplemental DescriptorsLarge amounts of climate data were collected from the eight field sites. These data can be summarized to varying degrees of detail (i.e., monthly, weekly, daily - down to half-hourly values for some variables) depending on aims. Due to the large amount of data and the different ways it could be summarized we have not included this data here. Instead, these data are available at: http://www.cpb.bio.ic.ac.uk/biodepth/data/index.html.
This study was carried out at eight European locations: Bayreuth, Germany; Cork, Ireland; Lupsingen, Switzerland; Lezirias, Portugal; Umeå, Sweden; Lesbos, Greece; and in Sheffield and at Silwood Park (Ascot, near London) in the UK. Sites differed widely in climate, soil conditions, and other major environmental factors (Table 1) - Further information can be found in the main article associated with this supplement by Spehn et al. and in Hector et al. (1999). The following references give more detailed information on the individual sites: Switzerland (Diemer et al. 1997, Joshi et al. 2000, Koricheva et al. 2000, Spehn et al. 2000a, Spehn et al. 2000b, Diemer and Schmid 2001; Pfisterer and Schmid 2002; Pfisterer, Diemer and Schmid 2003, ; Pfisterer et al. 2004), Sweden (Mulder et al. 1999, Koricheva et al. 2000, Jumpponen et al. 2002, Mulder et al. 2002) Germany (Scherer-Lorenzen et al. 2003), Greece (Troumbis et al. 2000, Troumbis et al. 2002), Portugal (Caldeira et al. 2001) and Silwood Park (Hector et al. 2000, Hector et al. 2001; Otway, Hector and Lawton, in press).
Establishment of the experimental communities
The field experiments were established in spring 1995 in Switzerland, autumn 1996 in Portugal, and spring 1996 at all other sites. Plots of at least 2 × 2 m (Switzerland: 2 × 8 m, Sweden: 2.2 × 5.2 m) were seeded with 2000 viable seeds m2 divided equally between the number of species in each plant assemblage. Seeds were locally collected as far as possible, or otherwise purchased from national commercial sources avoiding agricultural cultivars. Prior to sowing, the existing vegetation was removed and the soil seed bank was eliminated by continuous weeding (Switzerland, Sweden), steam sterilization (Germany), heat (soil was covered with black plastic for 2.5 months, Portugal) or methyl-bromide application (UK, Ireland, Greece). To reduce post-application effects of methyl bromide on legumes, an inoculum of Rhizobium was applied. plots were regularly weeded to remove unwanted species emerging from the remaining seed bank or invading from outside. Plots were separated by 1.5-m wide borders sown with slow-growing grass species that were regularly mowed (Switzerland, Germany, Ireland, UK, Sweden, Portugal) or were not separated (Greece). The plots were not fertilized during the experimental period.
We established five levels of species richness, ranging from monocultures to higher diversity mixtures. The highest diversities approximately matched background levels of diversity in comparable semi-natural grasslands at each site (Hector et al. 1999: Table 1). In addition, we varied the number of functional groups — grasses, nitrogen-fixing legumes and other herbaceous dicots (forbs) — within the different levels of species richness. Further, we constrained our random selection of species from the local pool of grassland species so that all assemblages included grasses. Each particular combination of species richness and number of functional groups, hereafter called a diversity level, was replicated, with several different species compositions, hereafter called an assemblage (both monocultures and mixtures), at each site to separate the effects of species richness from the effects of species identity (Givnish 1994, Tilman 1997, Allison 1999, Schmid et al. 2002). At each site all assemblages were randomly allocated within two replicated blocks (except Portugal with fully randomized plots). In total, the experiment comprised eight sites, 480 plots, and 200 different plant assemblages, with the same assemblage sometimes occurring at more than one site. In addition, at some sites (Portugal, Germany, Greece, Ireland, UK Silwood) we established unmanipulated "reference" plots in neighboring grasslands to provide a natural comparison for the variables measured in our experimental plots.
Realized species richness
Realized plant species richness was assessed from cover estimates and biomass samples taken over the entire growing season. From all the surveys that have been made during the year we compiled a list of all the plant species present in each plot and year.
Aboveground biomass of plants was determined by harvesting standing crop above 5 cm in one or two sampling areas of 20 × 50 cm per plot once (UK, Portugal, Sweden, Greece) or twice (Germany, Switzerland, Ireland) a year. Then the entire plots were mowed to 5 cm, following the traditional management or harvesting regime used in agriculture of most areas. plant samples were dried at 80°C for 24 h before they were weighed.
Canopy structure and light use
The total cover of vegetation, i.e., the percentage of ground area covered by live plants, and the ground cover by dead plants and litter was estimated visually before each main harvest. The average canopy height was measured with an HFRO sward stick (Hill Farming Research Institute, Edinburgh, UK) at the time of the biomass harvests. A clear window of 2 × 1 cm was lowered vertically down the stick towards the canopy (Bartham 1986). When it first touched a green leaf of the canopy, the height of contact was recorded. The mean of 10 samples at random positions within each plot is reported. At the time of peak biomass each year, aboveground biomass was harvested in canopy layers in a 20 × 50 cm permanent quadrat. We used different strata at different sites depending on total canopy height: for Portugal, Greece, Sweden, and UK Silwood, 520, 2035, 3550, and >50 cm; for Ireland and UK Sheffield, 520, 2035, and >35 cm, for Switzerland, 515, 1520, 2035, 3550, and >50 cm; for Germany, 520, 2035, 3550, then every 15 cm. Samples were dried to constancy and weighed. We then calculated biomass density per layer as a measure of three-dimensional space filling by dividing the height of each layer by biomass. In order to get a measure of vertical biomass density distribution in the canopy, we calculated the height of the center of gravity by multiplying the biomass of each layer with the mean height of the layer (z) and dividing the sum of z by the total biomass (Spehn et al. 2000). Photosynthetically active photon flux density (PPFD) was measured with a ceptometer (Delta-T Sunscan ceptometer (Delta-T Devices, Cambridge, UK) or LI-COR Line Quantum Sensor, (Lincoln, Nebraska, USA) at the base of the canopy in each plot before the main biomass harvests was taken.
We measured total community root biomass by taking two soil cores from each plot, avoiding the central area containing the permanent sampling area of the aboveground biomass harvests. Soil cores (4 cm in diameter) were divided into four strata (05, 510, 1015, and 1520 cm) and roots extracted by washing and sieving. Fine roots (<1-mm diameter) were separated from coarse roots (>1-mm diameter), but for the analysis only fine roots were considered. Samples were dried until constancy and weighed.
As an indicator for short-term decomposition we measured the dry mass loss of cotton per day of exposure in the top soil layer. Cotton is a standard organic substrate containing ca. 95% cellulose, with an initial N concentration of 0.09%. Strips of cotton (12.2 × 12.5 cm) were buried vertically (010 cm) over several months during the main growing period. Cotton strips were protected against rodents with a nylon mesh with a mesh size of 1 mm (Germany, Greece, Silwood, Sweden, Switzerland). Long-term decomposition was measured by dry weight loss of wooden birch-sticks. Sets of three flat birch sticks (11.5 × 0.9 × 0.2 cm) were bundled using polyester thread, and buried vertically 1 cm below the surface during once or twice per growing season. Four bundles of sticks were used per plot and mean estimates of yearly decomposition were obtained from differences in dry mass. Only the central stick in the bundle was monitored. Initial N concentration of the sticks was 0.08%.
Initial soil conditions were measured either in each plot or, where plots had not yet been established, by using a stratified random sampling scheme in which the experimental area was divided into a grid of at least 10 cells per block. Soil cores (4 cm in diameter × 20 cm deep) were taken at random within each plot or cell, mixed, and a subsample taken to assess soil pH, available phosphorous, total carbon, total nitrogen, ammonium, and nitrate. At some sites information on other nutrients was also collected, depending on the methods of local laboratories. To allow comparison between sites, one composite sample (250 g after removal of stones, etc.) from each block at each site was analyzed for total C, total N, and pH (in CaCl2) at the Institute of Environmental Sciences, University of Zurich, following standard methods (Anonymous 1995).
Soil soluble or exchangeable nitrogen concentrations were determined according to a general pre-agreed sampling protocol, but with different intensity and methods of chemical analysis across sites due in part to different soil types. These differences in methods will partly account for the observed variability between sites making a biological interpretation of site differences difficult. Samples were taken with soil cores (the diameter ranged from 25 cm) within the main rooting depth (010 cm in Portugal, Switzerland and Ireland; 015 cm in Germany; 020 cm in Greece and Silwood). Note that shallower sampling may better reflect plant root activity since this is where most roots are concentrated while the sites that sampled to greater depth may dilute this signal. Two to ten samples per plot were taken and pooled for the analysis. From the sieved samples (<2 mm mesh size), aliquots were extracted either with KCl solution (Switzerland, Germany, Greece, and UK Silwood), or H2SO4 (Kjeldahl-procedure: Portugal and Ireland) and ammonia and nitrate concentrations were determined using standard soil laboratory procedures. A second subsample was dried and the water content was used to calculate total plant-available mineral nitrogen (Nmin) as NH4+ plus NO3-N mg/kg dry mass. Data are reported for samples taken during the third year early in the season (Portugal and Ireland), mid-season (Germany, Switzerland, Greece) and from the end of the growing season (UK Silwood). Soil nitrogen was not measured in Sweden and UK Sheffield during the third year. The categorization of seasons was made according to growing seasons of the sites, i.e., mid season in Switzerland is in June, whereas mid season in Greece is April, etc. As all sites did not sample at all three times of the third year a mixture of start, mid-or end-of-season samples had to be taken. We selected samples to allow the best possible comparison between sites within these constraints giving priority to mid-season samples (as the time of peak plant growth), following by end-of-season (the outcome of a whole season’s growth) and finally early season (note that this may reflect levels of N at the start of the season). A more detailed analysis of N dynamics from sample to sample within the third year for individual sites is in preparation for publication elsewhere (M. Scherer-Lorenzen et al., unpublished data).
Additive partitioning of biodiversity effects
The effect of biodiversity on aboveground biomass production can be partitioned into a "selection effect" and a "complementarity effect" (which sum to the "net biodiversity effect") following Loreau and Hector (Loreau and Hector 2001). The selection effect is measured by the covariance between the monoculture yield of species and their change in relative yield in the mixture. The complementarity effect measures the net change in the average relative yield of species, that is increases in some species that are not compensated by decreases in others (and vice versa) which can indicate resource-partitioning and related niche-differentiation processes. As the approach requires a comparison between performances of species in mixture and in monoculture, it can only be applied to the subset of experimental mixtures that contained species for which all monoculture yields were available. The additive partitioning calculations follow Loreau and Hector (2001) with a few modifications for dealing with missing species (Spehn et al. 2005, M. Caldeira et al., unpublished manuscript).
Data processing and database compilation
Data were collected according to standard protocols established at project meetings and circulated to all data collectors. Data were checked by read-back, followed by tabulation and on-screen plotting to look for outliers. Checked data were emailed to Silwood Park and collated into a relational database using Microsoft Access-97. The database was set up with constraints placed on acceptable column headers and column formats. Data with incorrect headers, column formatting (text numerical, etc.) could not be entered into the database and were returned to sites for further checking until correctly reformatted and entered. This provided a second round of checking. The raw data were then processed (e.g., to produce means per plot) and derived variables (e.g., complementarity and selection effects) calculated. A third round of data checking occurred during data processing and at the first stage of analysis.
We are grateful to Tim Wong and Robert Anderson for advice on database design and data processing; Maja Weilenmann for her work on the manuscript; and to Charles Godfray for the logistical support that enabled us to complete this database.
Allison, G. W. 1999. The implications of experimental design for biodiversity manipulations. American Naturalist 153:2645.
Anonymous. 1995. Schweizerische Referenzmethoden der Eidenössischen landwirtschaftlichen Forschungsanstalten.
Barthram, G. T. 1986. Experimental techniques: the HFRO swardstick. Biennial report, 19841985:2930.
Caldeira, M. C., R. J. Ryel, J. H. Lawton, and J. S. Pereira. 2001. Mechanisms of positive biodiversity-production relationships: insights provided by 13C analysis in experimental Portuguese grassland plots. Ecology Letters 4:439443.
Diemer, M., J. Joshi, C. Körner, B. Schmid, and E. Spehn. 1997. An experimental protocol to assess the effects of plant diversity on ecosystem functioning utilised in a European research network. Bulletin of the Geobotanical Institute ETH 63:95107.
Diemer, M., and B. Schmid. 2001. Effects of biodiversity loss and disturbance on the survival and performance of two Ranunculus species with differing clonal architectures. Ecography 24:5967.
Givnish, T. J. 1994. Does diversity beget stability? Nature 371:113114.
Hector, A., A. Beale, A. Minns, S. Otway, and J. H. Lawton. 2000. Consequences of loss of plant diversity for litter decomposition: mechanisms of litter quality and microenvironment. Oikos 90:357371.
Hector, A., K. Dobson, A. Minns, E. Bazeley-White, and J. H. Lawton. 2001. Community diversity and invasion resistance: an experimental test in a grassland ecosystem and a review of comparable studies. Ecological Research 16:819831.
Hector, A., B. Schmid, C. Beierkuhnlein, M. C. Caldeira, M. Diemer, P. G. Dimitrakopoulos, J. Finn, H. Freitas, P. S. Giller, J. Good, R. Harris, P. Högberg, K. Huss-Danell, J. Joshi, A. Jumpponen, C. Körner, P. W. Leadley, M. Loreau, A. Minns, C. P. H. Mulder, G. O'Donovan, S. J. Otway, J. S. Pereira, A. Prinz, D. J. Read, M. Scherer-Lorenzen, E.-D. Schulze, A.-S. D. Siamantziouras, E. M. Spehn, A. C. Terry, A. Y. Troumbis, F. I. Woodward, S. Yachi, and J. H. Lawton. 1999. Plant diversity and productivity experiments in European grasslands. Science 286:11231127.
Joshi, J., D. Matthies, and B. Schmid. 2000. Root hermiparasites and plant diversity in experimental grassland communities. Journal of Ecology 88:634644.
Jumpponen, A., P. Högberg, K. Huss-Danell, and C. P. H. Mulder. 2002. Interspecific and spatial differences in N uptake in monocultures and two-species mixtures in north European grasslands. Functional Ecology 16:454461.
Koricheva, J., C. P. H. Mulder, B. Schmid, J. Joshi, and K. Huss-Danell. 2000. Numerical responses of different trophic groups of invertebrates to manipulations of plant diversity in grasslands. Oecologia 125:271282.
Loreau, M., and A. Hector. 2001. Partitioning selection and complementarity in biodiversity experiments. Nature 412:7276.
Mulder, C. P. H., A. Jumpponen, P. Hogberg, and K. Huss-Danell. 2002. How plant diversity and legumes affect nitrogen dynamics in experimental grassland communities. Oecologia 133:412421. [Online, doi:// 10.1007/s00442-00002-01043-00440].
Mulder, C. P. H., J. Koricheva, K. Huss-Danell, P. Högberg, and J. Joshi. 1999. Insects affect relationships between plant species richness and ecosystem processes. Ecology Letters 2:237246.
Otway, S., A. Hector, and J. H. Lawton. In press. Resource dilution effects on specialist insect herbivores in a grassland biodiversity experiment. Journal of Animal Ecology.
Pfisterer, A. B., and B. Schmid. 2002. Diversity-dependent production can decrease the stability of ecosystem functioning. Nature 416:8486.
Pfisterer A. B., M. Diemer, and B. Schmid. 2003. Dietary shift and lowered biomass gain of a generalist herbivore in species-poor experimental plant communities. Oecologia 135:234241.
Pfisterer, A. B., B. Schmid, J. Joshi, and M. Fischer. 2004. Rapid decay of diversity-productivity relationships after invasion of experimental plant communities. Basic and Applied Ecology 5:514
Scherer-Lorenzen, M., C. Palmborg, A. Prinz, and E.-D. Schulze. 2003. The role of plant diversity and composition for nitrate leaching in grasslands. Ecology 84:15391552.
Schmid, B., A. Hector, M. A. Huston, P. Inchausti, I. Nijs, P. W. Leadley, and D. Tilman. 2002. The design and analysis of biodiversity experiments. Pages 61-78 in M. Loreau, S. Naeem, and P. Inchausti, editors. Biodiversity and Ecosystem Functioning. Oxford University Press, Oxford, UK.
Spehn, E. M., et al. 2005. Ecosystem effects of biodiversity manipulations in European grasslands. Ecological Monographs 75:3763.
Spehn, E. M., J. Joshi, B. Schmid, J. Alphei, and C. Körner. 2000a. Plant diversity effects on soil heterotrophic activity in experimental grassland ecosystems. Plant and Soil 224:217230.
Spehn, E. M., J. Joshi, B. Schmid, M. Diemer, and C. Körner. 2000b. Aboveground resource use increases with plant species richness in experimental grassland ecosystems. Functional Ecology 14:326337.
Tilman, D. 1997. Distinguishing between the effects of species diversity and species composition. Oikos 80:185.
Troumbis, A. Y., P. G. Dimitrakopoulos, A.-S. D. Siamantziouras, and D. Memtsas. 2000. Hidden diversity and productivity patterns in mixed Mediterranean grasslands. Oikos 90:549559.
Troumbis, A. Y., A. Galanidis, and G. Kokkoris. 2002. Components of short-term invasibility in experimental Mediterranean grasslands. Oikos 98:239250.
TABLE S1: Geographic information and soil chemical properties of the eight different European grassland field sites.
Total N (%)
Inorg. C (%)
Total C (%)
Note: m.a.s.l. = meters above sea level; n.m. = not measured.
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