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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): Multitrophic energy dynamics (energy-use efficiency, energy flow, and energy storage) in the Jena Experiment (Main Experiment). PANGAEA, https://doi.org/10.1594/PANGAEA.910659, Supplement to: Buzhdygan, OY et al. (2020): Biodiversity increases multitrophic energy use efficiency, flow and storage in grasslands. Nature Ecology & Evolution, https://doi.org/10.1038/s41559-020-1123-8

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Abstract:
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.
Keyword(s):
Biodiversity; Biomass; energay flow; energy budget; energy storage; energy-use efficiency; grassland
Project(s):
Coverage:
Latitude: 50.946100 * Longitude: 11.611300
Event(s):
Jena_Experiment (Jena Experiment) * Latitude: 50.946100 * Longitude: 11.611300 * Location: Thuringia, Germany * Method/Device: Experiment (EXP)
Comment:
Most of the data used to parameterize these trophic networks were collected in 2010.
A diagram depicting the conceptual trophic-network model developed to describe multitrophic ecosystem functioning can be found in the paper (REF to the NEE paper). This paper also shows the relationship between the individual flows and compartment sizes as well as the network-wide measures with plant species richness. Further sensitivity analyses for the influence of including the highest diversity level are also provided in the paper.
Parameter(s):
#NameShort NameUnitPrincipal InvestigatorMethod/DeviceComment
1PlotPlotDetailed explanations of plots and the plant diversity gradient are provided in the section about the Jena Experiment "Further Info".
2Carbon uptake by plantC uptake plantg/m2/dayMass-balancing (MB)System energy input flow (flows entering the system) via carbon uptake by plants
3Aboveground, flux, plant to aboveground herbivore, dry massAbovegr flux plant to abovegr herbiv dmg/m2/dayEmpirically measured (EM)Aboveground herbivory by herbivores
4Aboveground, flux, herbivore to carnivore, dry massAbovegr flux herbiv to carnivore dmg/m2/dayEmpirically measured (EM)Aboveground predation of herbivores by carnivores
5Aboveground, flux, decomposer to carnivore, dry massAbovegr flux decomp to carnivore dmg/m2/dayEmpirically measured (EM)Aboveground predation of decomposers by carnivores
6Aboveground, flux, plant to aboveground omnivore, dry massAbovegr flux plant to abovegr omniv dmg/m2/dayEmpirically measured (EM)Aboveground herbivory by omnivores
7Aboveground, flux, herbivore to omnivore, dry massAbovegr flux herbiv to omniv dmg/m2/dayEmpirically measured (EM)Aboveground predation of herbivores by omnivores
8Aboveground, flux, decomposer to omnivore, dry massAbovegr flux decomp to omniv dmg/m2/dayEmpirically measured (EM)Aboveground predation of decomposers by omnivores
9Aboveground, flux, litter to omnivore, dry massAbovegr flux litter to omniv dmg/m2/dayEmpirically measured (EM)Aboveground decomposition by omnivores
10Aboveground, flux, litter to decomposer, dry massAbovegr flux litter to decomp dmg/m2/dayEmpirically measured (EM)Aboveground decomposition by decomposers
11Belowground, flux, herbivore to carnivore, dry massBelowgr flux herbiv to carnivore dmg/m2/dayMass-balancing (MB)Belowground predation of herbivores by carnivores
12Belowground, flux, decomposer to carnivore, dry massBelowgr flux decomp to carnivore dmg/m2/dayMass-balancing (MB)Belowground predation of decomposers by carnivores
13Belowground, flux, plant to belowground herbivore, dry massBelowgr flux plant to belowgr herbivg/m2/dayMass-balancing (MB)Belowground herbivory by herbivores
14Belowground, flux, soil organic matter to belowground decomposer, dry massBelowgr flux soil OM to belowgr decompg/m2/dayMass-balancing (MB)Belowground decomposition by decomposers
15Belowground, flux, plant to belowground omnivore, dry massBelowgr flux plant to belowgr omnivg/m2/dayMass-balancing (MB)Belowground herbivory by omnivores
16Belowground, flux, herbivore to omnivore, dry massBelowgr flux herbiv to omniv dmg/m2/dayMass-balancing (MB)Belowground predation of herbivores by omnivores
17Belowground, flux, decomposer to omnivore, dry massBelowgr flux decomp to omniv dmg/m2/dayMass-balancing (MB)Belowground predation of decomposers by omnivores
18Belowground, flux, soil organic matter to belowground omnivore, dry massBelowgr flux soil OM to belowgr omniv dmg/m2/dayMass-balancing (MB)Belowground decomposition by omnivores
19Belowground, flux, soil microorganism to belowground omnivore, dry massBelowgr flux soil microorg to belowgg/m2/dayMass-balancing (MB)Belowground microbivory by omnivores
20Belowground, flux, plant to soil organic matter, dry massBelowgr flux plant to soil OM dmg/m2/dayMass-balancing (MB)Root mortality
21Belowground, flux, carnivore to soil organic matter, dry massBelowgr flux carnivore to soil OM dmg/m2/dayLiterature based (LB)Excretion and natural mortality by belowground carnivores
22Belowground, flux, herbivore to soil organic matter, dry massBelowgr flux herbiv to soil OM dmg/m2/dayLiterature based (LB)Excretion and natural mortality by belowground herbivores
23Belowground, flux, decomposer to soil organic matter, dry massBelowgr flux decomp to soil OM dmg/m2/dayLiterature based (LB)Excretion and natural mortality by belowground decomposers
24Belowground, flux, omnivore to soil organic matter, dry massBelowgr flux omniv to soil OM dmg/m2/dayLiterature based (LB)Excretion and natural mortality by belowground omnivores
25Flux, aboveground litter to soil organic matter, dry massFlux abovegr litter to soil OM dmg/m2/dayEmpirically measured (EM)Mechanical transformation of surface litter due to bioturbation
26Belowground, flux, soil microorganism to soil organic matter, dry massBelowgr flux soil microorg to soil Og/m2/dayLiterature based (LB)Natural mortality of soil microorganisms
27Aboveground, flux, plant to aboveground litter, dry massAbovegr flux plant to abovegr litter dmg/m2/dayMass-balancing (MB)Aboveground plant mortality
28Aboveground, flux, herbivore to aboveground litter, dry massAbovegr flux herbiv to abovegr litter dmg/m2/dayMass-balancing (MB)Excretion and natural mortality by aboveground herbivores
29Aboveground, flux, carnivore to aboveground litter, dry massAbovegr flux carnivore to abovegr litterg/m2/dayMass-balancing (MB)Excretion and natural mortality by aboveground carnivores
30Aboveground, flux, omnivore to aboveground litter, dry massAbovegr flux omniv to abovegr litter dmg/m2/dayMass-balancing (MB)Excretion and natural mortality by aboveground omnivores
31Aboveground, flux, decomposer to aboveground litter, dry massAbovegr flux decomp to abovegr litter dmg/m2/dayMass-balancing (MB)Excretion and natural mortality by aboveground decomposers
32Belowground, flux, soil organic matter to soil microorganism, dry massBelowgr flux soil OM to soil microorg dmg/m2/dayMass-balancing (MB)Belowground decomposition by soil microorganisms
33Respiration, flux, plant, dry massResp plant dmg/m2/dayAllometric equations (AE)System energy output flow (flows leaving the system) via plant respiration
34Respiration, flux, aboveground, herbivore, dry massResp abovegr herbiv dmg/m2/dayAllometric equations (AE)System energy output flow (flows leaving the system) via respiration of aboveground herbivores
35Respiration, flux, aboveground, carnivore, dry massResp abovegr carnivore dmg/m2/dayAllometric equations (AE)System energy output flow (flows leaving the system) via respiration of aboveground carnivores
36Respiration, flux, aboveground, omnivore, dry massResp abovegr omniv dmg/m2/dayAllometric equations (AE)System energy output flow (flows leaving the system) via respiration of aboveground omnivores
37Respiration, flux, aboveground, decomposer, dry massResp abovegr decomp dmg/m2/dayAllometric equations (AE)System energy output flow (flows leaving the system) via respiration of aboveground decomposers
38Respiration, flux, belowground, carnivore, dry massResp belowgr carnivore dmg/m2/dayAllometric equations (AE)System energy output flow (flows leaving the system) via respiration of belowground carnivores
39Respiration, flux, belowground, herbivore, dry massResp belowgr herbiv dmg/m2/dayAllometric equations (AE)System energy output flow (flows leaving the system) via respiration of belowground herbivores
40Respiration, flux, belowground, decomposer, dry massResp belowgr decomp dmg/m2/dayAllometric equations (AE)System energy output flow (flows leaving the system) via respiration of belowground decomposers
41Respiration, flux, belowground, omnivore, dry massResp belowgr omniv dmg/m2/dayAllometric equations (AE)System energy output flow (flows leaving the system) via respiration of belowground omnivores
42Respiration, flux, soil microorganism, dry massResp soil microorg dmg/m2/dayEmpirically measured (EM)System energy output flow (flows leaving the system) via respiration of soil microorganisms
43Biomass, plant, dry massBiom plant dmg/m2Empirically measured (EM)Standing biomass of plant community (includingboth aboveground biomass and roots)
44Biomass, aboveground, herbivore, dry massBiom abovegr herbiv dmg/m2Empirically measured (EM)Standing biomass of aboveground herbivores
45Biomass, aboveground, carnivore, dry massBiom abovegr carnivore dmg/m2Empirically measured (EM)Standing biomass of aboveground carnivores
46Biomass, aboveground, omnivore, dry massBiom abovegr omniv dmg/m2Empirically measured (EM)Standing biomass of aboveground omnivores
47Biomass, aboveground, decomposer, dry massBiom abovegr decomp dmg/m2Empirically measured (EM)Standing biomass of aboveground decomposers
48Biomass, belowground, herbivore, dry massBiom belowgr herbiv dmg/m2Empirically measured (EM)Standing biomass of belowground herbivores
49Biomass, belowground, carnivore, dry massBiom belowgr carnivore dmg/m2Empirically measured (EM)Standing biomass of belowground carnivores
50Biomass, belowground, omnivore, dry massBiom belowgr omniv dmg/m2Empirically measured (EM)Standing biomass of belowground omnivores
51Biomass, belowground, decomposer, dry massBiom belowgr decomp dmg/m2Empirically measured (EM)Standing biomass of belowground decomposers
52Biomass of soil microorganism, dry massBiom soil microorg dmg/m2Empirically measured (EM)Standing biomass of soil microorganisms
53Biomass of aboveground litter, dry massBiom abovegr litter dmg/m2Empirically measured (EM)Standing biomass of aboveground litter
54Biomass of soil organic matter, dry massBiom soil OM dmg/m2Empirically measured (EM)Standing biomass of soil organic matter
55Total network, energy flow, dry massTotal network energy flow dmg/m2/dayModelled, Ecological Network Analysis (Modelled - ENA)Total energy flow is the total amount of flows that pass through the system (including energy flows that enter the system).
56Total network, biomass, dry massTotal network biom dmg/m2Modelled, Ecological Network Analysis (Modelled - ENA)Total-network standing biomass is the summed standing biomass across all ecosystem compartments
57Total network, community maintenance costs per dayTotal network community main costs per ddayModelled, Ecological Network Analysis (Modelled - ENA)Community maintenance costs is the ratio of total community respiration flow to community standing biomass (includes only living trophic compartments).
58Total network, energy flow uniformityTotal network energy flow uniformityModelled, Ecological Network Analysis (Modelled - ENA)Flow uniformity is the ratio of the mean of summed flows through each trophic compartment to its standard deviation
Size:
4640 data points

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