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  • 1
    facet.materialart.
    Unknown
    PANGAEA
    In:  Supplement to: Ebeling, Anne; Rzanny, Michael; Lange, Markus; Eisenhauer, Nico; Hertzog, Lionel R; Meyer, Sebastian Tobias; Weisser, Wolfgang W (2018): Plant diversity induces shifts in the functional structure and diversity across trophic levels. Oikos, 127(2), 208-219, https://doi.org/10.1111/oik.04210
    Publication Date: 2023-06-24
    Description: This data set contains information about the functional structure (overall biomass; abundance of consumers: in different habitat strata; of different food resource specialization, feeding strategies and aerial mobility) of aboveground consumers (herbivores, carnivores, omnivores and decomposers) per plots from a grassland plant diversity experiment (the Jena Experiment; Roscher et al. 2004). The experiment was established in 2002, and consists of 80 grassland plots. Plots vary in plant species richness (1, 2, 4, 8, 16, or 60 species). All plots are mown twice per year, and weeded three times per year to maintain the experimental diversity gradient. We collected ground-associated arthropods over 125 days from May until September 2010 using two pitfall traps of 4.5 cm diameter per plot. During the sampling periods, the field traps were filled with 3% formalin and after emptying the traps, animals were stored in 70% ethanol. Vegetation-associated arthropods were collected by suction sampling in early June and August (during the peak biomass of the plant communities) using a modified commercial vacuum cleaner. We randomly chose three subplots of 0.75 m x 0.75 m within each plot, covered them with a gauze cage of the same size, and sampled arthropods by vacuuming the inside of the cages until we spotted no arthropods anymore. Samples were identified to species level, except for Hymenoptera, which were identified to the level of family or subfamily. We pooled data of all sampling campaigns in 2010 and standardized the resulting abundances between zero and one, separately for pitfall and suction sampling to account for different sampling intensities between the two methods (Hertzog et al. 2016). We focused on species that we sampled more than once during the whole vegetation period.
    Keywords: JenExp; The Jena Experiment
    Type: Dataset
    Format: application/zip, 2 datasets
    Location Call Number Limitation Availability
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  • 2
    Publication Date: 2023-06-24
    Description: This collection contains measurements of abundance and diversity of different groups of aboveground invertebrates sampled on the plots of the different sub-experiments at the field site of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. The following series of datasets are contained in this collection: 1. Measurements of ant abundance (number of individuals attracted to baits) and ant occurrence (binary data) in the Main Experiment in 2006 and 2013. Ants where sampled using two types of baited traps receiving ~10g of Tuna or ~10g of honey/Sucrose. After 30min the occurrence (presence = 1 / absence = 0) and abundance (number) of ants at the two types of baits was recorded and pooled per plot.
    Keywords: JenExp; The Jena Experiment
    Type: Dataset
    Format: application/zip, 2 datasets
    Location Call Number Limitation Availability
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  • 3
    Publication Date: 2023-06-24
    Description: This data contains species richness, abundance and functional diversity of arthropod communities per plot from a grassland biodiversity experiment (the Jena Experiment). Functional diversity here is expressed by functional richness (FRic), evenness (FEve) and divergence (FDiv). These three measures give an impression about the niches filled by members of a community and the range, dispersion, and value of organismal traits, whereby traits are measurable features of individuals affecting their performance or fitness (Villéger et al. 2008). For each consumer species we used the following five traits to calculate the above mentioned indices: feeding mode, food/ host specialization, stratum, aerial mobility, body mass.
    Keywords: Block; Carnivore; Decomposer; EXP; Experiment; Functional divergence; Functional evenness; Functional richness; Herbivore; Jena Experiment 2010; JenExp; JenExp_2010; Number; Omnivore; Plot; Species richness; The Jena Experiment; Thuringia, Germany
    Type: Dataset
    Format: text/tab-separated-values, 1837 data points
    Location Call Number Limitation Availability
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  • 4
    Publication Date: 2023-06-24
    Description: This data contains information on the functional structure of consumer communities per plot from a grassland biodiversity experiment (the Jena Experiment). For each consumer species we assigned the four categorical traits feeding mode, food/ host specialization, stratum, and aerial mobility, and the numerical trait body mass (mg). Functional structure here is expressed by number of individuals belonging to the different categories within each trait and the community weighted mean of body mass.
    Keywords: Block; Calculated; Carnivore; Carnivore, biomass; Decomposer; Decomposer, biomass; EXP; Experiment; Herbivore; Herbivore, biomass; Jena Experiment 2010; JenExp; JenExp_2010; Number; Omnivore; Omnivore, biomass; Plot; The Jena Experiment; Thuringia, Germany
    Type: Dataset
    Format: text/tab-separated-values, 4960 data points
    Location Call Number Limitation Availability
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  • 5
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    Unknown
    PANGAEA
    In:  Supplement to: Buzhdygan, Oksana Y; Meyer, Sebastian Tobias; Weisser, Wolfgang W; Eisenhauer, Nico; Ebeling, Anne; Borrett, Stuart R; Buchmann, Nina; Cortois, Roeland; De Deyn, Gerlinde B; de Kroon, Hans; Gleixner, Gerd; Hertzog, Lionel R; Hines, Jes; Lange, Markus; Mommer, Liesje; Ravenek, Janneke; Scherber, Christoph; Scherer-Lorenzen, Michael; Scheu, Stefan; Schmid, Bernhard; Steinauer, Katja; Strecker, Tanja; Tietjen, Britta; Vogel, Anja; Weigelt, Alexandra; Petermann, Jana S (2020): Biodiversity increases multitrophic energy use efficiency, flow and storage in grasslands. Nature Ecology & Evolution, https://doi.org/10.1038/s41559-020-1123-8
    Publication Date: 2023-11-09
    Description: This data set contains measures of energy-use efficiency, energy flow, and energy storage in units of dry biomass that quantify the multitrophic ecosystem functioning realized in grassland ecosystems of differing plant diversity. Given are both the measures integrated over whole ecosystems (total network measures) as well as the energy dynamics associated with individual ecosystem compartments including the entire biological community and detrital compartments across the above- and belowground parts of the ecosystem. Data presented here is from the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment, see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Study plots are grouped in four blocks in parallel to the river in order to account for any effect of a gradient in abiotic soil properties. Each block contains an equal number of plots of each plant species richness and plant functional group richness level. Plots were maintained in general by bi-annual weeding and mowing. Since 2010, plot size was reduced to 5.5 x 6 m and plots were weeded three times per year. Trophic-network models were constructed for 80 of the experimental plots, and represent the ecosystem energy budget in the currency of dry-mass (g m-2 for standing stocks and g m-2 d-1 for flows). All trophic networks have the same topology, but they differ in the estimated size of the standing stock biomass of individual compartments (g m-2) and flows among the compartments (g m-2 d-1). Each trophic network contains twelve ecosystem compartments representing distinct trophic groups of the above- and belowground parts of the ecosystem (i.e., plants, soil microbial community, and above- and belowground herbivores, carnivores, omnivores, decomposers, all represented by invertebrate macro- and mesofauna) and detrital pools (i.e., surface litter and soil organic matter). Vertebrates were not considered in our study due to limitations of data availability and because the impact of resident vertebrates in our experimental system is expected to be minimal. Larger grazing vertebrates were excluded by a fence around the field site, though there was some occasional grazing by voles. Compartments are connected by 41 flows. Flows (fluxes) constitute 30 internal flows within the system, namely feeding (herbivory, predation, decomposition), excretion, mortality, and mechanical transformation of surface litter due to bioturbation plus eleven 11 external flows, i.e. one input (flows entering the system, namely carbon uptake by plants) and ten output flows (flows leaving the system, namely respiration losses). The ecosystem inflow (a flow entering the system) and outflows (flows leaving the system) represent carbon uptake and respiration losses, respectively. In the case of consumer groups, the food consumed (compartment-wide input flow) is further split into excretion (not assimilated organic material that is returned to detrital pools in the form of fecesfaeces) and assimilated organic material, which is further split into respiration (energy lost out of the system to the environment) and biomass production, which is further consumed by higher trophic levels due to predation or returned to detrital pools in the form of mortality (natural mortality or prey residues). In case of detrital pools (i.e. surface litter and soil organic matter), the input flows are in the form of excretion and mortality from the biota compartments, and output flows are in the form of feeding by decomposers and soil microorganisms (i.e. decomposition). Surface litter and soil organic matter are connected by flows in the form of burrowing (mechanical transportation) of organic material from the surface to the soil by soil fauna. Organism immigration and emigration are not considered in our study due to limited data availability. Flows were quantified using resource processing rates (i.e. the feeding rates at which material is taken from a source) multiplied with the standing biomass of the respective source compartment. To approximate resource processing rates, different approaches were used: (i) experimental measurements (namely the aboveground decomposition, fauna burial activity (bioturbation), microbial respiration, and aboveground herbivory and predation rates); (ii) allometric equations scaled by individual body mass, environmental temperature and phylogenetic group (for the above- and belowground fauna respiration rates and plant respiration); (iii) assimilation rates scaled by diet type (for quantification of belowground fauna excretion and natural mortality); (iv) literature-based rates scaled by biomass of trophic groups (for microbial mortality); and (v) mass-balance assumptions (carbon uptake, plant and aboveground fauna mortality, belowground decomposition, belowground herbivory, and belowground predation). Mass-balance assumption means that the flows are calculated assuming that resource inputs into the compartment (i.e. feeding) balance the rate at which material is lost (i.e. the sum of through excretion, respiration, predation, and natural death). We used constrained nonlinear multivariable optimization to perturb the initial flow rates estimated from the various sources. We assigned confidence ratings for each flow rate, reflecting the quality of empirical data it is based on. We then used the 'fmincon' function from Matlab's optimization toolbox, which utilizes the standard Moore-Penrose pseudoinverse approach to achieve a balanced steady state ecological network model that best reflects the collected field data. Measured data used to parameterize the trophic network models were collected mostly in the year 2010. Network-wide measures that quantify proxies for different aspects of multitrophic ecosystem functioning were calculated for each experimental plot using the 'enaR' package in R. In particular, total energy flow was measured as the sum of all flows through each ecosystem compartment. Flow uniformity was calculated as the ratio of the mean of summed flows through each individual ecosystem compartment divided by the standard deviation of these means. Total-network standing biomass was determined as the sum of standing biomass across all ecosystem compartments. Community maintenance costs were calculated as the ratio of community-wide respiration related to community-wide biomass.
    Keywords: Aboveground, flux, carnivore to aboveground litter, dry mass; Aboveground, flux, decomposer to aboveground litter, dry mass; Aboveground, flux, decomposer to carnivore, dry mass; Aboveground, flux, decomposer to omnivore, dry mass; Aboveground, flux, herbivore to aboveground litter, dry mass; Aboveground, flux, herbivore to carnivore, dry mass; Aboveground, flux, herbivore to omnivore, dry mass; Aboveground, flux, litter to decomposer, dry mass; Aboveground, flux, litter to omnivore, dry mass; Aboveground, flux, omnivore to aboveground litter, dry mass; Aboveground, flux, plant to aboveground herbivore, dry mass; Aboveground, flux, plant to aboveground litter, dry mass; Aboveground, flux, plant to aboveground omnivore, dry mass; AE; Allometric equations; Belowground, flux, carnivore to soil organic matter, dry mass; Belowground, flux, decomposer to carnivore, dry mass; Belowground, flux, decomposer to omnivore, dry mass; Belowground, flux, decomposer to soil organic matter, dry mass; Belowground, flux, herbivore to carnivore, dry mass; Belowground, flux, herbivore to omnivore, dry mass; Belowground, flux, herbivore to soil organic matter, dry mass; Belowground, flux, omnivore to soil organic matter, dry mass; Belowground, flux, plant to belowground herbivore, dry mass; Belowground, flux, plant to belowground omnivore, dry mass; Belowground, flux, plant to soil organic matter, dry mass; Belowground, flux, soil microorganism to belowground omnivore, dry mass; Belowground, flux, soil microorganism to soil organic matter, dry mass; Belowground, flux, soil organic matter to belowground decomposer, dry mass; Belowground, flux, soil organic matter to belowground omnivore, dry mass; Belowground, flux, soil organic matter to soil microorganism, dry mass; Biodiversity; Biomass; Biomass, aboveground, carnivore, dry mass; Biomass, aboveground, decomposer, dry mass; Biomass, aboveground, herbivore, dry mass; Biomass, aboveground, omnivore, dry mass; Biomass, belowground, carnivore, dry mass; Biomass, belowground, decomposer, dry mass; Biomass, belowground, herbivore, dry mass; Biomass, belowground, omnivore, dry mass; Biomass, plant, dry mass; Biomass of aboveground litter, dry mass; Biomass of soil microorganism, dry mass; Biomass of soil organic matter, dry mass; Carbon uptake by plant; EM; Empirically measured; energay flow; Energy budget; energy storage; energy-use efficiency; EXP; Experiment; Flux, aboveground litter to soil organic matter, dry mass; grassland; Jena_Experiment; Jena Experiment; JenExp; Literature based; Mass-balancing; Modelled, Ecological Network Analysis; Modelled - ENA; Plot; Respiration, flux, aboveground, carnivore, dry mass; Respiration, flux, aboveground, decomposer, dry mass; Respiration, flux, aboveground, herbivore, dry mass; Respiration, flux, aboveground, omnivore, dry mass; Respiration, flux, belowground, carnivore, dry mass; Respiration, flux, belowground, decomposer, dry mass; Respiration, flux, belowground, herbivore, dry mass; Respiration, flux, belowground, omnivore, dry mass; Respiration, flux, plant, dry mass; Respiration, flux, soil microorganism, dry mass; The Jena Experiment; Thuringia, Germany; Total network, biomass, dry mass; Total network, community maintenance costs per day; Total network, energy flow, dry mass; Total network, energy flow uniformity
    Type: Dataset
    Format: text/tab-separated-values, 4640 data points
    Location Call Number Limitation Availability
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  • 6
    Publication Date: 2024-01-26
    Description: This data set contains measurements of ant abundance (number of individuals observed at the baits) and ant occurrence (binary data) measured in the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). Ants were sampled in 80 plots of the Main Experiment using baited traps in July 2006. In each plot two petri dishes were set on the ground, one received ~10g of Tuna the other ~10g of sugar (Sucrose). After 30min the occurrence (presence = 1 / absence = 0) and abundance (number) of ants at the two baits was recorded. Given is, per plot, the sum of ants attracted to the two different baits. In the Main Experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown in the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, or 4 functional groups). Plots were maintained by bi-annual weeding and mowing.
    Keywords: Ant abundance; Ant occurence; Date/time end; Date/time start; EXP; Experiment; Experimental plot; HEIGHT above ground; Height aboveground, maximum; Height aboveground, minimum; Jena Experiment 2006; JenExp; JenExp_2006; The Jena Experiment; Thuringia, Germany; Treatment: aboveground: pesticide; Treatment: below pesticide; Treatment: drought; Treatment: eartworm exclosure; Treatment: fertilizing; Treatment: molluscide; Treatment: mowing; Treatment: nematicide; Treatment: phytometers; Treatment: seed addition; Treatment: special; Treatment: weeding; Treatment: weeding history
    Type: Dataset
    Format: text/tab-separated-values, 1600 data points
    Location Call Number Limitation Availability
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  • 7
    Publication Date: 2024-01-26
    Description: This data set contains measurements of ant abundance (number of individuals attracted to baits) and ant occurrence (binary data) measured in the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the Main Experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown in the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, or 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Ants where sampled in 80 plots of the Main Experiment using baited traps end of July/ beginning of August 2013. Sampling took place 36 days after the end of a major flooding of the field site that lasted for several weeks (see DOI flood descriptor). In each plot two petri dishes were set on the ground, one received ~10g of Tuna the other ~10g of Honey. After 30min the occurrence (presence = 1 / absence = 0) and abundance (number) of ants at the two baits was recorded. Given is, per plot, the sum of ants attracted to the two different baits.
    Keywords: Ant abundance; Ant occurence; Date/time end; Date/time start; EXP; Experiment; Experimental plot; HEIGHT above ground; Height aboveground, maximum; Height aboveground, minimum; Jena Experiment 2013; JenExp; JenExp_2013; The Jena Experiment; Thuringia, Germany; Treatment: aboveground: pesticide; Treatment: below pesticide; Treatment: drought; Treatment: eartworm exclosure; Treatment: fertilizing; Treatment: molluscide; Treatment: mowing; Treatment: nematicide; Treatment: phytometers; Treatment: seed addition; Treatment: special; Treatment: weeding; Treatment: weeding history
    Type: Dataset
    Format: text/tab-separated-values, 1600 data points
    Location Call Number Limitation Availability
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