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Whereas temporal patterns of soil microbial abundance and function are well known for different agricultural ecosystems, it was not clear whether the spatial distribution of soil organisms is constant within a season. Therefore, it was interesting to know whether the spatial distance of different taxa and different soil microbial processes change during a vegetation period. Interactions of microorganisms with their micro-environment might have consequences for their functioning at the plot scale. For example, high sensitivity of specific bacterial taxa to drought would increase the spatial distance between these microorganisms in summer, whereas drought tolerance of other bacterial taxa could induce a rather constant pattern of these tolerant microorganisms. At the level of community functioning, the local stability of enzymes could induce seasonal shifts in local degradation of different substrates. Seasonal pattern of biogeography need to be tested at the molecular, cellular and community levels.


This study provided a platform for different Biodiversity Explorers to clarify the spatial and temporal distribution of soil bacteria, genetic structure of bacterial populations and their functions at grassland sites under different land-use intensities. During the first phase (2008 -2011) of the project we focused on spatial patterns of chemical and biological properties at a scale of 10 x 10 m2 using nine plots from each exploratory (VIP). During the second phase (2011-2014) we extended our concept and invited colleagues with different expertise in soil ecology and molecular microbiology to broaden our research at this scale. The most important goal was to investigate whether seasonal changes in biotic and abiotic factors modify the biogeography of soil microorganisms at the plot scale (10 x 10 m2).


We hypothesized that (i) by a temporally and spatially intensive examination of an unimproved grassland at the plot scale (10 m x 10 m) we could distinguish spatial changes in microbial biogeography, and (ii) this sampling approach would clarify the degree to which the microbial spatial structures we observed could be correlated with stages of plant growth and soil abiotic properties. We expected also to gain insight into the persistence of microbial spatial structure and the relationships of microbial communities with their environment.


Soil sampling was performed on one low land-use intensity grassland in the Schwäbische Alb (AEG31) at six times within one season to cover the following stages of substrate release from plant communities: at the beginning of the vegetation period, during the main growth phase, at around peak plant biomass, two weeks after the grassland was mown, nine weeks after mowing and two weeks after it was lightly grazed, and after the first frost. At each sampling date we have chosen 60 points for local estimation of plant community composition and for soil sampling. The total number of 60 samples guarantees that we had a minimum of 30 pairs of short lag distances (min. 50 cm). Members of the group of D. Prati (Bern) was responsible for quantification of plant biomass, relative abundance, and developmental stage of plants within an area around each sampling point (20 x 20 cm). The central part of this area was used for soil sampling using a soil corer (58 mm diameter) to a depth of 10 cm.


The multidisciplinary approach allowed elucidating the spatio-temporal variation of functional traits and diversity of plants, animals and microorganisms at different taxonomical levels (please see list of publications below).

Microbial community spatial structure was positively correlated with the local environment, i.e. physical and chemical soil properties, in spring and autumn, while the density and diversity of plants had an additional effect in the summer period (Regan et al. 2014, 2015). Spatial relationships among plant and microbial communities were detected only in the early summer and autumn periods when aboveground biomass increase was most rapid and its influence on soil microbial communities was greatest due to increased demand by plants for nutrients. Individual properties exhibited varying degrees of spatial structure over the season. Differential responses of Gram positive and Gram negative bacterial communities to seasonal shifts in soil nutrients were detected. We concluded that spatial distribution patterns of soil microorganisms change over a season and that chemical soil properties are more important controlling factors than plant density and diversity.

Presenting N cycling microorganisms as an example, we revealed that the seasonal changes in abundances of marker genes for total archaea and bacteria (16S rRNA), nitrogen fixing bacteria (nifH), ammonia oxidizing archaea (amoA AOA) and bacteria (amoA AOB), and denitrifying bacteria (nirS, nirK and nosZ) were associated with changes in substrate availability associated with plant growth stages (Regan et al. 2017). Potential nitrification and denitrification enzyme activities were strongly spatially structured at the studied scale, corresponding to periods of rapid plant growth, June and October, and their spatial distributions were similar, providing visual evidence of highly localized spatial and temporal conditions at this scale. Temporal variability in the N-cycling communities versus the stability of their respective potential activities provided evidence of both short-lived temporal niche partitioning and a degree of microbial functional redundancy. Our results indicate that in an unfertilized grassland, at the meter scale, abundances of microbial N-cycling organisms can exhibit transient changes, while N cycling processes remain stable.


Doc
Freitag M., Hölzel N., Neuenkamp L., van der Plas F., Manning P., Abrahão A., Bergmann J., Boeddinghaus R., Bolliger R., Hamer U., Kandeler E., Kleinebecker T., Knorr K.-H., Marhan S., Neyret M., Prati D., Le Provost G., Saiz H., van Kleunen M., Schäfer M., Klaus V. H. (2023): Increasing plant species richness by seeding has marginal effects on ecosystem functioning in agricultural grasslands. Journal of Ecology 111 (9), 1968-1984. doi: 10.1111/1365-2745.14154
More information:  doi.org
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Abrahão A., Marhan S., Boeddinghaus R. S., Nawaz A., Wubet T., Hölzel N., Klaus V. H., Kleinebecker T., Freitag M., Hamer U., Oliveira R. S., Lambers H., Kandeler E. (2022): Microbial drivers of plant richness and productivity in a grassland restoration experiment along a gradient of land use intensity. New Phytologist 236 (5), 1936-1950. doi: 10.1111/nph.18503
More information:  doi.org
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Lineare gemischte Modelle und Geostatistik für geplante Experimente in den Bodenwissenschaften – zwei unversöhnliche Methoden oder zwei Seiten derselben Medaille
Slaets J., Boeddinghaus R. S., Piepho H.-P. (2021): Linear mixed models and geostatistics for designed experiments in soil science ‐ two entirely different methods or two sides of the same coin? European Journal of Soil Science 72 (1), 47-68. doi: 10.1111/ejss.12976
More information:  doi.org
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Boeddinghaus R. S., Marhan S., Gebala A., Haslwimmer H., Vieira S., Sikorski J., Overmann J., Soares M., Rousk J., Rennert T., Kandeler E. (2021): The Mineralosphere – Interactive zone for microbial colonization and carbon use in grassland soils. Biology and Fertility of Soils 57, 587–601. doi: 10.1007/s00374-021-01551-7
More information:  doi.org
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Goldmann K., Boeddinghaus R. S., Klemmer S., Regan K. M., Heintz-Buschart A., Fischer M., Prati D., Piepho H.-P., Berner D., Marhan S., Kandeler E., Buscot F., Wubet T. (2020): Unraveling spatio‐temporal variability of arbuscular mycorrhiza fungi in a temperate grassland plot. Environmental Microbiology 22 (3), 873-888. doi: 10.1111/1462-2920.14653
More information:  doi.org
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Nach welchen Regeln besiedeln Bakterien den Boden?
Vieira S., Sikorski J., Gebala A., Boeddinghaus R. S., Marhan S., Rennert T., Kandeler E., Overmann J. (2020): Bacterial colonization of minerals in grassland soils is selective and highly dynamic. Environmental Microbiology 22 (3), 917-933. doi: 10.1111/1462-2920.14751
More information:  doi.org
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Richter-Heitmann T., Hofner B., Krah F.-S., Sikorski J., Wüst P. K., Bunk B., Huang S., Regan K., Berner D., Boeddinghaus R. S., Marhan S., Prati D., Kandeler E., Overmann J., Friedrich M. W. (2020): Stochastic dispersal rather than deterministic selection explains the spatio-temporal distribution of soil bacteria in a temperate grassland. Frontiers in Microbiology 11: 1391. doi: 10.3389/fmicb.2020.01391
More information:  doi.org
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Erholung von Ökosystemfunktionen nach experimenteller Störung in 73 Grünlandflächen mit unterschiedlicher Landnutzungsintensität, Artenvielfalt und Zusammensetzung der Pflanzengesellschaft
Schäfer D., Klaus V. H., Kleinebecker T., Boeddinghaus R. S., Hinderling J., Kandeler E., Marhan S., Nowak S., Sonnemann I., Wurst S., Fischer M., Hölzel N., Hamer U., Prati D. (2019): Recovery of ecosystem functions after experimental disturbance in 73 grasslands differing in land‐use intensity, plant species richness and community composition. Journal of Ecology 107 (6), 2635-2649. doi: 10.1111/1365-2745.13211
More information:  doi.org
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Veränderungen von funktionellen Pflanzeneigenschaften erklären parallele Veränderungen in der Struktur und Funktion mikrobieller Gemeinschaften in Grünlandböden
Boeddinghaus R. S., Marhan S., Berner D., Boch S., Fischer M., Hölzel N., Kattge J., Klaus V. H., Kleinebecker T., Oelmann Y., Prati D., Schäfer D., Schöning I., Schrumpf M., Sorkau E., Kandeler E., Manning P. (2019): Plant functional trait shifts explain concurrent changes in the structure and function of grassland soil microbial communities. Journal of Ecology 107 (5), 2197-2210. doi: 10.1111/1365-2745.13182
More information:  doi.org
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Fiore-Donno A. M., Richter-Heitmann T., Degrune F., Dumack K., Regan K. M., Mahran S., Boeddinghaus R. S., Rillig M. C., Friedrich M. W., Kandeler E., Bonkowski M. (2019): Functional Traits and Spatio-Temporal Structure of a Major Group of Soil Protists (Rhizaria: Cercozoa) in a Temperate Grassland. Frontiers in Microbiology 10:1654. doi: 10.3389/fmicb.2019.01654
More information:  doi.org
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Die Mineralosphäre – Sukzession und Physiologie von Bakterien und Pilzen während der Besiedlung reiner Minerale in Grünlandböden mit unterschiedlicher Landnutzungsintensität
Kandeler E., Gebala A., Boeddinghaus R. S., Müller K., Rennert T., Soares M., Rousk J., Marhan S. (2019): The mineralosphere – Succession and physiology of bacteria and fungi colonising pristine minerals in grassland soils under different land-use intensities. Soil Biology and Biochemistry 136: 107534. doi: 10.1016/j.soilbio.2019.107534
More information:  doi.org
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Räumliche und zeitliche Variationen von Mikroorganismen in Grünlandböden - Einflüsse von Landnutzungsintensität, Pflanzen und Bodeneigenschaften
Boeddinghaus R. S. (2019): Spatial and temporal variations of microorganisms in grassland soils - influences of land-use intensity, plants and soil properties. Dissertation, University Hohenheim
More information:  opus.uni-hohenheim.de
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Einfluss der Landnutzungsintensität auf die mikrobielle Bio-masse von Grünlandböden
Bauer C. (2018): Einfluss der Landnutzungsintensität auf die mikrobielle Bio-masse von Grünlandböden. Bachelor thesis, University Hohenheim
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Long-term effects of disturbance and seed addition on soil microbial biomass in grassland with high and low land-use intensity
Langzeit Effect von Störung und Ansaat auf die mikrobielle Biomasse in Grünlandböden mit hoher und niedriger Landnutzungsintensität
Lang K. (2018): Long-term effects of disturbance and seed addition on soil microbial biomass in grassland with high and low land-use intensity. Bachelor thesis, University Hohenheim
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Regan K., Stempfhuber B., Schloter M., Rasche F., Prati D., Philippot L., Boeddinghaus R. S., Kandeler E., Marhan S. (2017): Spatial and temporal dynamics of nitrogen fixing, nitrifying and denitrifying microbes in an unfertilized grassland soil. Soil Biology and Biochemistry 109, 214–226. doi: 10.1016/j.soilbio.2016.11.011
More information:  doi.org
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Die potentielle Methan-Oxidation des Bodens in Abhängigkeit von der Landnutzungsintensität am Beispiel von Grünland und Wald
Rohrbach K. (2017): Die potentielle Methan-Oxidation des Bodens in Abhängigkeit von der Landnutzungsintensität am Beispiel von Grünland und Wald. Bachelor thesis, University Hohenheim
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Impact of soil disturbance on microorganisms in differently managed grassland soils linked to the ecosystem resilience
Binder I. (2016): Impact of soil disturbance on microorganisms in differently managed grassland soils linked to the ecosystem resilience. Master thesis, University Hohenheim
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Regan K. M. (2016): Linking Microbial Abundance and Function to Understand Nitrogen Cycling in Grassland Soils. Dissertation, University Hohenheim
More information:  opus.uni-hohenheim.de
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Gibt es allgemeine räumliche Verteilungsmuster von mikrobieller Biomasse und Enzymaktivitäten in Grünlandböden?
Boeddinghaus R. S., Nunan N., Berner D., Marhan S., Kandeler E. (2015): Do general spatial relationships for microbial biomass and soil enzyme activities exist in temperate grassland soils? Soil Biology & Biochemistry 88, 430-440. doi: 10.1016/j.soilbio.2015.05.026
More information:  doi.org
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Einfluss von Temperaturerhöhung und Dürre auf Lachgasemissionen und die Häufigkeit von denitrifizierenden Bakterien in Grünlandböden mit unterschiedlicher Landnutzungsintensität
Keil D., Niklaus P. A., von Riedmatten L. R., Boeddinghaus R. S., Dormann K. F., Scherer-Lorenzen M., Kandeler E., Marhan S. (2015): Effects of warming and drought on potential N2O emissions and denitrifying bacteria abundance in grasslands with different land use. FEMS Microbiology Ecology 91(7), pii: fiv066. doi: 10.1093/femsec/fiv066
More information:  doi.org
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Einfluss der Landnutzungsintensität auf die mikrobielle Biomasse und Enzymaktivitäten im Rhizosphärenboden verschiedener Grünlandpflanzenarten
Boob M. (2015): Einfluss der Landnutzungsintensität auf die mikrobielle Biomasse und Enzymaktivitäten im Rhizosphärenboden verschiedener Grünlandpflanzenarten. Master thesis, Universität Hohenheim
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Einfluss von Landnutzung auf Abundanz, Funktion und räumliche Verteilung von N-umsetzenden Mikroorganismen in Grünlandböden
Keil D. (2015): Influence of land use on abundance, function and spatial distribution of N-cycling microorganisms in grassland soils. Dissertation, University of Hohenheim
More information:  opus.uni-hohenheim.de
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Zeigen Pflanzen oder abiotische Bodeneigenschaften saisonal bedingt mehr Einfluss auf die Verteilung von Mikroorganismen in Grünlandböden?
Regan K. M., Nunan N., Boeddinghaus R. S., Baumgarten V., Berner D., Boch S., Oelmann Y., Overmann J., Prati D., Schloter M., Schmitt B., Sorkau E., Steffens M., Kandeler E., Marhan S. (2014): Seasonal controls on grassland microbial biogeography: Are they governed by plants, abiotic properties or both? Soil Biology and Biochemistry 71, 21–30. doi: 10.1016/j.soilbio.2013.12.024
More information:  doi.org
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Eine neue Methode (midDRIFTS basierte Spektroskopie) erlaubt die schnelle und kostengünstige Vorhersage von mikrobieller Biomasse und Aktivität in Grünlandböden
Rasche F., Marhan S., Berner D., Keil D., Kandeler E., Cadisch G. (2013): midDRIFTS-based partial least square regression analysis allows predicting microbial biomass, enzyme activities and 16S rRNA gene abundance in soils of temperate grasslands. Soil Biology and Biochemistry 57, 504–512. doi: 10.1016/j.soilbio.2012.09.030
More information:  doi.org
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Einfluss von Landnutzungsintensität auf die räumliche Verteilung Stickstoff umsetzender Mikroorganismen in Grünlandböden
Keil D., Meyer A., Berner D., Poll A., Schützenmeister A., Piepho H.-P., Vlasenko A., Philippot L., Schloter M., Kandeler E., Marhan S. (2011): Influence of land-use intensity on spatial distribution of N-cycling microorganisms in grassland soils . FEMS Microbiology Ecology 77 (1), 95-106. doi: 10.1111/j.1574-6941.2011.01091.x
More information:  doi.org
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Die Landnutzungsintensität verändert die räumliche Verteilung und Funktion von Bodenmikroorganismen im Grünland
Berner D., Marhan S., Keil D., Schützenmeister A., Piepho H.-P., Poll C., Kandeler E. (2011): Land-Use Intensity Modifies Spatial Distribution and Function of Soil Microorganisms in Grasslands. Pedobiologia 54 (5-6), 341-351. doi:10.1016/j.pedobi.2011.08.001
More information:  doi.org
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Einfluss von Landnutzungsintensität auf Mikroorganismen in Grünlandböden der Schwäbischen Alb
Breuer B.S. (2008): Einfluss von Landnutzungsintensität auf Mikroorganismen in Grünlandböden der Schwäbischen Alb. Bachelor Thesis, University Hohenheim
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Räumliche Heterogenität mikrobieller Enzymaktivitäten in Grünlandböden der Schwäbischen Alb
Glatzle S.(2008): Räumliche Heterogenität mikrobieller Enzymaktivitäten in Grünlandböden der Schwäbischen Alb. Bachelor thesis, University Hohenheim

Public Datasets

Dataset
Abrahão, Anna (2022): Plant species richness and biomass, and soil microbial properties data used in "Microbial drivers of plant richness and productivity in a grassland restoration experiment along a gradient of land-use intensity". Version 13. Biodiversity Exploratories Information System. Dataset. https://doi.org/10.25829/bexis.31348-12
Dataset
Marhan, Sven (2022): Metabolic quotient of soil microorganisms, grassland EPs, soil sampling campaign 2017. Version 5. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/31315?version=5/ddm/data/Showdata/31315?version=5
Dataset
Boeddinghaus, Runa; Berner, Doreen; Marhan, Sven; Kandeler, Ellen (2020): FTIR measures of burried mineral containers with labelled artificial root exudates on 10 ALB sites, SCALEMIC Phase 4 (2014-2017) WP1. Version 2. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/26150?version=2/ddm/data/Showdata/26150?version=2
Dataset
Boeddinghaus, Runa; Berner, Doreen; Marhan, Sven; Kandeler, Ellen (2020): FTIR measures of standards for burried mineral containers with labelled artificial root exudates on 10 ALB sites, SCALEMIC Phase 4 (2014-2017) WP1. Version 2. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/26149?version=2/ddm/data/Showdata/26149?version=2
Dataset
Boeddinghaus, Runa; Marhan, Sven; Kandeler, Ellen (2020): Soil physico-chemical and root biomass data for 2015 and 2018 of 25 HAI grassland MIPs, cooperation SADE-SCALEMIC . Version 3. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/26146?version=3/ddm/data/Showdata/26146?version=3
Dataset
Boeddinghaus, Runa; Berner, Doreen; Marhan, Sven; Kandeler, Ellen (2020): Soil enzyme activities of all grassland EPs, soil sampling campaign (SSC) 2017, SCALEMIC. Version 3. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/26147?version=3/ddm/data/Showdata/26147?version=3
Dataset
Boeddinghaus, Runa; Gebala, Aurelia; Berner, Doreen; Marhan, Sven; Kandeler, Ellen (2020): Microbiological and chemical data of burried mineral containers with labelled artificial root exudates on 10 ALB sites, SCALEMIC Phase 4 (2014-2017) WP1. Version 2. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/26148?version=2/ddm/data/Showdata/26148?version=2
Dataset
Kandeler, Ellen; Marhan, Sven; Abrahao, Anna; Boeddinghaus, Runa (2020): Soil microbial phospholipid fatty acids (PLFAs) and soil enzyme activities measured on 10 SADE plots in the ALB, 2015-2018, cooperation SADE-SCALEMIC. Version 2. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/27646?version=2/ddm/data/Showdata/27646?version=2
Dataset
Boeddinghaus, Runa; Mayer-Gruner, Paula; Marhan, Sven; Kandeler, Ellen (2020): Approximated pore size distribution of grassland EPs (SSC 2014) SCALEMIC. Version 4. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/26207?version=4/ddm/data/Showdata/26207?version=4
Dataset
Boeddinghaus, Runa; Marhan, Sven; Berner, Doreen; Boch, Steffen; Fischer, Markus; Hoelzel, Norbert; Kattge, Jens; Klaus, Valentin; Kleinebecker, Till; Oelmann, Yvonne; Prati, Daniel; Schäfer, Deborah; Schöning, Ingo; Schrumpf, Marion; Sorkau, Elisabeth; Kandeler, Ellen; Manning, Pete (2019): Dataset used in Boeddinghaus et al. (2019) "Plant functional trait shifts explain concurrent changes in the structure and function of grassland soil microbial communities" Journal of Ecology. Version 4. Biodiversity Exploratories Information System. Dataset. https://doi.org/10.25829/bexis.24867-1.1.23
Dataset
Boeddinghaus, Runa; Bauer, Christina; Marhan, Sven; Kandeler, Ellen (2019): Physico-chemical soil properties of all grassland EPs, soil sampling campaign (SSC) 2017, SCALEMIC. Version 3. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/25586?version=3/ddm/data/Showdata/25586?version=3
Dataset
Boeddinghaus, Runa; Müller, Karolin; Bauer, Christina; Marhan, Sven; Kandeler, Ellen (2019): Microbial soil properties of all grassland EPs, soil sampling campaign (SSC) 2017, SCALEMIC. Version 3. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/25408?version=3/ddm/data/Showdata/25408?version=3
Dataset
Boeddinghaus, Runa; Marhan, Sven; Kandeler, Ellen (2019): Soil physico-chemical and root biomass data for 2015 and 2018 of 25 SCH grassland MIPs, cooperation SADE-SCALEMIC . Version 3. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/25706?version=3/ddm/data/Showdata/25706?version=3
Dataset
Boeddinghaus, Runa; Gebala, Aurelia; Berner, Doreen; Marhan, Sven; Kandeler, Ellen (2019): Microbiological and chemical data of burried mineral containers with labelled roots on 10 ALB sites, SCALEMIC Phase 4 (2014-2017) WP2. Version 2. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/24708?version=2/ddm/data/Showdata/24708?version=2
Dataset
Boeddinghaus, Runa; Regan, Kathleen; Marhan, Sven; Kandeler, Ellen (2019): Soil enzyme activities of the SCALEMIC Experiment (AEG31, 2011). Version 2. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/25409?version=2/ddm/data/Showdata/25409?version=2
Dataset
Boeddinghaus, Runa; Kandeler, Ellen (2019): Soil water and dry matter content of SADE samples 2015-2018 ALB (SCALEMIC). Version 2. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/25226?version=2/ddm/data/Showdata/25226?version=2
Dataset
Richter-Heitmann, Tim; Friedrich, Michael (2018): SCALEMIC - Acidobacterial rRNA sampled from top soil at six dates in 2011 on one ALB grassland plot. Version 2. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/22406?version=2/ddm/data/Showdata/22406?version=2
Dataset
Richter-Heitmann, Tim; Friedrich, Michael (2017): SCALEMIC - Inventory of active Bacteria - Data. Version 14. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/21566?version=14/ddm/data/Showdata/21566?version=14
Dataset
Richter-Heitmann, Tim; Friedrich, Michael (2017): SCALEMIC - Inventory of active Bacteria - Codelist. Version 2. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/21606?version=2/ddm/data/Showdata/21606?version=2
Dataset
Bonkowski, Michael; Fiore-Donno, Anna Maria (2017): Metacommunity analysis of seasonal and spatial variation of Cercozoa in a grassland soil. Version 2. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/22147?version=2/ddm/data/Showdata/22147?version=2
Dataset
Bonkowski, Michael; Fiore-Donno, Anna Maria (2017): Metacommunity analysis of seasonal and spatial variation of Cercozoa in a grassland soil - Data. Version 2. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/22166?version=2/ddm/data/Showdata/22166?version=2
Dataset
Kandeler, Ellen; Berner, Doreen; Marhan, Sven; Boeddinghaus, Runa (2016): Soil enzyme activities of all grassland EPs, soil sampling campaign (SSC) 2014, SCALEMIC. Version 4. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/20247?version=4/ddm/data/Showdata/20247?version=4
Dataset
Kandeler, Ellen; Berner, Doreen; Marhan, Sven; Boeddinghaus, Runa (2016): Soil enzyme activities of all grassland EPs, soil sampling campaign (SSC) 2011, SCALEMIC. Version 4. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/20246?version=4/ddm/data/Showdata/20246?version=4
Dataset
Kandeler, Ellen; Boeddinghaus, Runa; Marhan, Sven; Binder, Ines (2016): Microbial and physico-chemical soil properties, Alb grassland, 2015, cooperation SADE-SCALEMIC. Version 2. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/20227?version=2/ddm/data/Showdata/20227?version=2
Dataset
Kandeler, Ellen; Marhan, Sven; Berner, Doreen; Boeddinghaus, Runa (2016): Physico-chemical soil properties of all grassland EPs, soil sampling campaign (SSC) 2014, SCALEMIC. Version 5. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/20249?version=5/ddm/data/Showdata/20249?version=5
Dataset
Kandeler, Ellen; Marhan, Sven; Berner, Doreen; Boeddinghaus, Runa (2016): Microbial soil properties of all grassland EPs, soil sampling campaign (SSC) 2011, SCALEMIC. Version 3. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/20250?version=3/ddm/data/Showdata/20250?version=3
Dataset
Kandeler, Ellen; Marhan, Sven; Boeddinghaus, Runa; Gebala, Aurelia; Berner, Doreen; Boob, Meike (2016): Microbial rhizosphere and bulk soil properties, Alb grassland, 2014, cooperation BELOW-SCALEMIC. Version 2. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/20206?version=2/ddm/data/Showdata/20206?version=2
Dataset
Kandeler, Ellen; Marhan, Sven; Berner, Doreen; Boeddinghaus, Runa (2016): Physico-chemical soil properties of all grassland EPs, soil sampling campaign (SSC) 2011, SCALEMIC. Version 5. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/20248?version=5/ddm/data/Showdata/20248?version=5
Dataset
Kandeler, Ellen; Marhan, Sven; Berner, Doreen; Boeddinghaus, Runa (2016): Microbial soil properties of all grassland EPs, soil sampling campaign (SSC) 2014, SCALEMIC. Version 3. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/20251?version=3/ddm/data/Showdata/20251?version=3
Dataset
Richter-Heitmann, Tim; Friedrich, Michael; Marhan, Sven (2015): SCALEMIC - LINK to Short Read Archive - Bacterial Activity. Version 3. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/19466?version=3/ddm/data/Showdata/19466?version=3
Dataset
Regan, Kathleen; Berner, Doreen; Boeddinghaus, Runa; Marhan, Sven; Kandeler, Ellen (2014): Physico-chemical and microbial soil properties and plant diversity of AEG31, 2011, SCALEMIC-Experiment. Version 2. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/17707?version=2/ddm/data/Showdata/17707?version=2
Dataset
Prati, Daniel; Fischer, Markus (2014): SCALEMIC - Plant diversity, 2011. Version 2. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/17446?version=2/ddm/data/Showdata/17446?version=2
Dataset
Baumgartner, Vanessa; Kandeler, Ellen (2012): Number of cells in soil samples of plot AEG31, 2011, SCALEMIC-Experiment. Version 2. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/14946?version=2/ddm/data/Showdata/14946?version=2
Dataset
Berner, Doreen; Boeddinghaus, Runa; Regan, Kathleen; Keil, Daniel; Marhan, Sven; Kandeler, Ellen (2012): Soil physical and chemical properties of grassland VIPs in Hainich, SCALEMIC 2008. Version 3. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/14668?version=3/ddm/data/Showdata/14668?version=3
Dataset
Berner, Doreen; Regan, Kathleen; Keil, Daniel; Marhan, Sven; Kandeler, Ellen (2012): Physico-chemical soil properties of all grassland VIPs, SCALEMIC 2008. Version 4. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/14666?version=4/ddm/data/Showdata/14666?version=4
Dataset
Berner, Doreen; Boeddinghaus, Runa; Regan, Kathleen; Keil, Daniel; Marhan, Sven; Kandeler, Ellen (2012): Soil microbiological properties of grassland VIPs in Hainich, SCALEMIC 2008. Version 2. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/14667?version=2/ddm/data/Showdata/14667?version=2
Dataset
Berner, Doreen; Regan, Kathleen; Keil, Daniel; Marhan, Sven; Kandeler, Ellen (2010): Soil microbiological properties of grassland VIPs of ALB, SCALEMIC 2008. Version 3. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/11323?version=3/ddm/data/Showdata/11323?version=3
Dataset
Berner, Doreen; Regan, Kathleen; Keil, Daniel; Marhan, Sven; Kandeler, Ellen (2010): Soil physical and chemical properties of grassland VIPs in ALB, SCALEMIC 2008. Version 5. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de/ddm/data/Showdata/11320?version=5/ddm/data/Showdata/11320?version=5

Non-public datasets

Dataset
Hyphobox experiment, Heidfeldhof Hohenheim, 2020
Brandt, Luise; Abrahao, Anna (2024): Hyphobox experiment, Heidfeldhof Hohenheim, 2020. Version 2. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de. Dataset ID= 31933
Dataset
Soil mineral nitrogen (Nmin) of REX 1 and LUX grassland plots, Soil sampling campaign (SSC) 2021
Marhan, Sven (2023): Soil mineral nitrogen (Nmin) of REX 1 and LUX grassland plots, Soil sampling campaign (SSC) 2021. Version 7. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de. Dataset ID= 31634
Dataset
Soil mineral nitrogen (Nmin) of all grassland plots, Soil sampling campaign (SSC) 2021
Marhan, Sven (2023): Soil mineral nitrogen (Nmin) of all grassland plots, Soil sampling campaign (SSC) 2021. Version 7. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de. Dataset ID= 31630
Dataset
Soil water content of REX 1 and LUX grassland plots, Soil sampling campaign (SSC) 2021
Marhan, Sven (2023): Soil water content of REX 1 and LUX grassland plots, Soil sampling campaign (SSC) 2021. Version 2. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de. Dataset ID= 31636
Dataset
Microbial biomass C (Cmic) and N (Nmic) and soil microbial C to N ratio of REX 1 and LUX grassland plots, Soil sampling campaign (SSC) 2021
Marhan, Sven (2023): Microbial biomass C (Cmic) and N (Nmic) and soil microbial C to N ratio of REX 1 and LUX grassland plots, Soil sampling campaign (SSC) 2021. Version 2. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de. Dataset ID= 31638
Dataset
Gene abundances 16S Bacteria, nirK, nirS, nosZ clade I, II, soil sampling campaigns (SSC) 2011, 2014, 2017
Marhan, Sven (2023): Gene abundances 16S Bacteria, nirK, nirS, nosZ clade I, II, soil sampling campaigns (SSC) 2011, 2014, 2017. Version 3. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de. Dataset ID= 31648
Dataset
Soil extractable organic carbon and extractable total nitrogen – soil sampling campaign 2021, all grassland experimental plots (EPs), 0-10 cm
Marhan, Sven (2023): Soil extractable organic carbon and extractable total nitrogen – soil sampling campaign 2021, all grassland experimental plots (EPs), 0-10 cm. Version 13. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de. Dataset ID= 31629
Dataset
Microbial biomass C (Cmic) and N (Nmic) and soil microbial C to N ratio of all grassland EP plots, Soil sampling campaign (SSC) 2021
Marhan, Sven (2023): Microbial biomass C (Cmic) and N (Nmic) and soil microbial C to N ratio of all grassland EP plots, Soil sampling campaign (SSC) 2021. Version 4. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de. Dataset ID= 31637
Dataset
Soil extractable organic carbon and extractable total nitrogen of REX 1 and LUX grassland plots, Soil sampling campaign (SSC) 2021
Marhan, Sven (2023): Soil extractable organic carbon and extractable total nitrogen of REX 1 and LUX grassland plots, Soil sampling campaign (SSC) 2021. Version 8. Biodiversity Exploratories Information System. Dataset. https://www.bexis.uni-jena.de. Dataset ID= 31635

Project in other funding periods

Picture: The photo shows a hand in a turquoise glove lifting a piece of soil between meadow grass. The thickness of the piece of soil is estimated at ten to fifteen centimetres.
SCALEMIC (Contributing project)
#Microorganisms & Fungi  #2008 – 2011  #Carbon cycle […]
Picture: The photo shows a hand in a turquoise glove lifting a piece of soil between meadow grass. The thickness of the piece of soil is estimated at ten to fifteen centimetres.
SCALEMIC (Contributing project)
#Microorganisms & Fungi  #2014 – 2017  #Carbon cycle […]
Picture: The photo shows a hand in a turquoise glove lifting a piece of soil between meadow grass. The thickness of the piece of soil is estimated at ten to fifteen centimetres.
SCALEMIC (Contributing project)
#Microorganisms & Fungi  #BEF  #Soil Ecology  #2023 – 2026  #2020 – 2023  #Interaction […]

Scientific assistants

Prof. Dr. Ellen Kandeler
Project manager
Prof. Dr. Ellen Kandeler
Universität Hohenheim
Dr. Sven Marhan
Project manager
Dr. Sven Marhan
Universität Hohenheim
Doreen Berner
Alumni
Doreen Berner
Dr. Runa Boeddinghaus
Alumni
Dr. Runa Boeddinghaus
Kathleen Regan
Alumni
Kathleen Regan
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