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Plant and Soil

, Volume 437, Issue 1–2, pp 215–239 | Cite as

Land-use intensity shapes kinetics of extracellular enzymes in rhizosphere soil of agricultural grassland plant species

  • Alexander Tischer
  • Livia Sehl
  • Ulf-Niklas Meyer
  • Till Kleinebecker
  • Valentin Klaus
  • Ute HamerEmail author
Regular Article
  • 340 Downloads

Abstract

Aims

The aim of this study was to identify how land-use intensity shapes the kinetic properties of extracellular hydrolytic enzymes (EHEs) in rhizosphere soil among and within plant species representing different i) resource acquisition strategies (exploitative (ex) vs. conservative (co) plant species) and ii) response types to land-use intensification (winner (Wi) vs. loser (Lo), i.e. species that increase in abundance due to land-use intensification vs. species that decrease in abundance).

Methods

The potential enzyme activities (Vmax) and the apparent substrate affinities (Km) of β-cellobiohydrolase (CBH), β-glucosidase (BG), xylanase (XYL), N-acetylglucosaminidase (NAG), and phosphomonoesterase (PH) were determined in rhizosphere samples of Agrimonia eupatoria (co, Lo), Dactylis glomerata (ex, Wi), Lotus corniculatus (co, Lo), Taraxacum sect. Ruderalia (ex, Wi) and Trifolium repens (ex, Wi). Samples (n = 37) were taken on six permanent grasslands along a gradient in land-use intensity in central Germany.

Results

Plant species identity and performance of species to land-use intensity are less important for explaining enzyme kinetics than are land-use intensity and associated changes in soil properties (especially organic carbon, pH and C:N ratio) and composition of the surrounding plant community, i.e. the abundance of herbs and plant diversity. However, the rhizosphere of winner species of intensive land-use was characterized by higher Km of CBH and two out of the three winners were associated with lower Km of PH. Higher Vmax of XYL in the rhizosphere of winner species suggest higher production of hemicellulose-degrading enzymes in rhizospheres of higher land-use intensity.

Conclusions

This study demonstrates that both land-use intensity and to a lower degree the type of plants’ resource acquisition strategy affect EHEs of C-, N-, and P-cycles in the rhizosphere. Rhizospheres of common grassland species are hotspots of hemicellulose, chitin, and organic P degradation but not of cellulose degradation. Further studies should consider variations in the kinetics of EHEs as a function of root orders and soil depths.

Keywords

Michaelis-Menten kinetics C-, N- and P- cycling enzyme activities Permanent grassland Fertilization Plant species identity Hainich region 

Notes

Acknowledgements

We thank the two anonymous reviewers for their highly valuable comments which helped us to substantially improve the manuscript. The authors gratefully acknowledge the financial support by the DFG (German Research Foundation) for the subprojects HA 4597/6-3 and KL 2265/5-1 within the DFG Priority Program 1374 “Biodiversity-Exploratories”. The contribution of AT was partly funded by the Collaborative Research Centre AquaDiva (CRC 1076 AquaDiva) of the Friedrich Schiller University Jena, funded by DFG. We thank the team of the ILOEK-laboratory in Münster for help during lab analyses and the manager of the Hainich-Dün Exploratory Katrin Lorenzen for their work in realizing this experiment and maintaining the sites and project infrastructure, Christiane Fischer and Jule Mangels for giving support through the central office, Michael Owonibi for managing the central data base, and Markus Fischer, Eduard Linsenmair, Dominik Hessenmöller, Daniel Prati, Jens Nieschulze, François Buscot, Ernst-Detlef Schulze, Wolfgang W. Weisser and the late Elisabeth Kalko for their role in setting up the Biodiversity Exploratories project. Field work permits were issued by the responsible state environmental office of Thüringen. We also thank Svenja Kunze for untiring commitment during fieldwork campaigns.

Supplementary material

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References

  1. Adler PR, Sanderson MA, Weimer PJ, Vogel KP (2009) Plant species composition and biofuel yields of conservation grasslands. Ecol Appl 19:2202–2209.  https://doi.org/10.1890/07-2094.1 Google Scholar
  2. Aerts R, Berendse F (1988) The effect of increased nutrient availability on vegetation dynamics in wet heathlands. Vegetatio 76:63–69.  https://doi.org/10.1007/BF00047389 Google Scholar
  3. Ågren GI (2004) The C : N : P stoichiometry of autotrophs – theory and observations. Ecol Lett 7:185–191.  https://doi.org/10.1111/j.1461-0248.2004.00567.x Google Scholar
  4. Alef K, Nannipieri P (1995) Cellulase activity. In: Alef K, Nannipieri P (eds) Methods in applied soil microbiology and biochemistry. Academic Press, London, pp 345–349Google Scholar
  5. Alef K, Nannipieri P, Trazar-Cepeda C (1995) Phosphatase activity. In: Alef K, Nannipieri P (eds) Methods in applied soil microbiology and biochemistry. Academic Press, London, pp 335–344Google Scholar
  6. Allison SD (2017) Building predictive models for diverse microbial communities in soil. In: Tate KR (ed), Microbial biomass. A paradigm shift in terrestrial biochemistry. World Scientific, New Jersey, London, Singapore, pp 141–166.Google Scholar
  7. Allison SD, Vitousek PM (2005) Responses of extracellular enzymes to simple and complex nutrient inputs. Soil Biol Biochem 37:937–944.  https://doi.org/10.1016/j.soilbio.2004.09.014 Google Scholar
  8. Alt F, Oelmann Y, Herold N, Schrumpf M, Wilcke W (2011) Phosphorus partitioning in grassland and forest soils of Germany as related to land-use type, management intensity, and land use-related pH. J Plant Nutr Soil Sci 174:195–209.  https://doi.org/10.1002/jpln.201000142 Google Scholar
  9. Baldrian P (2009) Microbial enzyme-catalyzed processes in soils and their analysis. Plant Soil Environ 55:370–378Google Scholar
  10. Bartoń K (2013) MuMIn: Multi-model inference. R core team.Google Scholar
  11. Bell C, Carrillo Y, Boot CM, Rocca JD, Pendall E, Wallenstein MD (2014) Rhizosphere stoichiometry. Are C : N : P ratios of plants, soils, and enzymes conserved at the plant species-level? New Phytol 201:505–517.  https://doi.org/10.1111/nph.12531 Google Scholar
  12. Berg B, McClaugherty C (2008) Plant litter. Decomposition, humus formation, carbon sequestration, 3rd edn. Springer Berlin Heidelberg, BerlinGoogle Scholar
  13. Blagodatskaya E, Littschwager J, Lauerer M, Kuzyakov Y (2010) Growth rates of rhizosphere microorganisms depend on competitive abilities of plants and N supply. Plant Biosyst (in revision) 144:408–413.  https://doi.org/10.1080/11263501003718596 Google Scholar
  14. Blagodatskaya EV, Anderson T-H (1998) Interactive effects of pH and substrate quality on the fungal-to-bacterial ratio and qCO2 of microbial communities in forest soils. Soil Biol Biochem 30:1269–1274.  https://doi.org/10.1016/S0038-0717(98)00050-9 Google Scholar
  15. Blüthgen N, Dormann CF, Prati D, Klaus VH, Kleinebecker T, Hölzel N, Alt F, Boch S, Gockel S, Hemp A, Müller J, Nieschulze J, Renner SC, Schöning I, Schumacher U, Socher SA, Wells K, Birkhofer K, Buscot F, Oelmann Y, Rothenwöhrer C, Scherber C, Tscharntke T, Weiner CN, Fischer M, Kalko EKV, Linsenmair KE, Schulze E-D, Weisser WW (2012) A quantitative index of land-use intensity in grasslands: integrating mowing, grazing and fertilization. Basic Appl Ecol 13:207–220.  https://doi.org/10.1016/j.baae.2012.04.001 Google Scholar
  16. Boeddinghaus RS, 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 Biol Biochem 88:430–440.  https://doi.org/10.1016/j.soilbio.2015.05.026 Google Scholar
  17. Bünemann EK (2008) Enzyme additions as a tool to assess the potential bioavailability of organically bound nutrients. Special Section: Enzymes in the Environment Enzymes in the Environment III. Soil Biol Biochem 40:2116–2129.  https://doi.org/10.1016/j.soilbio.2008.03.001 Google Scholar
  18. Burnham KP, Anderson DR (2002) Model selection and multimodel inference. A practical information-theoretic approach, 2nd edn. Springer, New YorkGoogle Scholar
  19. Busch V, Klaus VH, Schäfer D, Prati D, Boch S, Müller J, Chisté M, Mody K, Blüthgen N, Fischer M, Hölzel N, Kleinebecker T (2018) Will I stay or will I go? Plant species specific response and tolerance to high land-use intensity in temperate grassland ecosystems. J Veg SciGoogle Scholar
  20. Butchart SHM, Walpole M, Collen B, van Strien A, Scharlemann JPW, Almond REA, Baillie JEM, Bomhard B, Brown C, Bruno J, Carpenter KE, Carr GM, Chanson J, Chenery AM, Csirke J, Davidson NC, Dentener F, Foster M, Galli A, Galloway JN, Genovesi P, Gregory RD, Hockings M, Kapos V, Lamarque J-F, Leverington F, Loh J, McGeoch MA, McRae L, Minasyan A, Hernández Morcillo M, Oldfield TEE, Pauly D, Quader S, Revenga C, Sauer JR, Skolnik B, Spear D, Stanwell-Smith D, Stuart SN, Symes A, Tierney M, Tyrrell TD, Vié J-C, Watson R (2010) Global biodiversity: indicators of recent declines. Science (New York, NY) 328:1164–1168.  https://doi.org/10.1126/science.1187512. Google Scholar
  21. Chen X, Ding Z, Tang M, Zhu B (2018) Greater variations of rhizosphere effects within mycorrhizal group than between mycorrhizal group in a temperate forest. Soil Biol Biochem 126:237–246Google Scholar
  22. Cheng W, Gersbenson A (2007) Carbon fluxes in the rhizosphere. In: Cardon ZG, Whitbeck JL (eds) The rhizosphere: An ecological perspective. Elsevier Academic Press, Amsterdam, pp 31–56Google Scholar
  23. Cheng W, Johnson DW, Fu S (2003) Rhizosphere effects on decomposition. Controls of plant species, phenology, and fertilization. Soil Sci Soc Am J 67:1418–1427Google Scholar
  24. Cusack DF, Silver WL, Torn MS, McDowell WH (2011) Effects of nitrogen additions on above- and belowground carbon dynamics in two tropical forests. Biogeochemistry 104:203–225Google Scholar
  25. de Cesare F, Garzillo AMV, Buonocore V, Badalucco L (2000) Use of sonication for measuring acid phosphatase activity in soil. Soil Biol Biochem 32:825–832.  https://doi.org/10.1016/S0038-0717(99)00212-6 Google Scholar
  26. de Deyn GB, Cornelissen JHC, Bardgett RD (2008) Plant functional traits and soil carbon sequestration in contrasting biomes. Ecol Lett 11:516–531.  https://doi.org/10.1111/j.1461-0248.2008.01164.x Google Scholar
  27. DeForest JL (2009) The influence of time, storage temperature, and substrate age on potential soil enzyme activity in acidic forest soils using MUB-linked substrates and l-DOPA. Soil Biol Biochem 41:1180–1186.  https://doi.org/10.1016/j.soilbio.2009.02.029 Google Scholar
  28. DeForest JL, Scott LG (2010) Available organic soil phosphorus has an important influence on microbial community composition. Soil Sci Soc Am J 74:2059–2066Google Scholar
  29. FAO (2014) World reference base for soil resources 2014. International soil classification system for naming soils and creating legends for soil maps. Update 2015. Food and Agriculture Organization of the United Nations., RomeGoogle Scholar
  30. Fierer N, Bradford MA, Jackson RB (2007) Toward an ecological classification of soil bacteria. Ecology 88:1354–1364Google Scholar
  31. Finzi AC, Abramoff RZ, Spiller KS, Brzostek ER, Darby BA, Kramer MA, Phillips RP (2015) Rhizosphere processes are quantitatively important components of terrestrial carbon and nutrient cycles. Glob Chang Biol 21:2082–2094.  https://doi.org/10.1111/gcb.12816 Google Scholar
  32. Fischer M, Bossdorf O, Gockel S, Hänsel F, Hemp A, Hessenmüller D, Korte G, Nieschulze J, Pfeiffer S, Prati D, Renner S, Schöning I, Schumacher U, Wells K, Buscot F, Kalko EKV, Linsenmair KE, Schulze E-D, Weisser WW (2010) Implementing large-scale and long-term functional biodiversity research. The Biodiversity Exploratories. Basic Appl Ecol 11:473–485.  https://doi.org/10.1016/j.baae.2010.07.009. Google Scholar
  33. German DP, Chacon SS, Allison SD (2011a) Substrate concentration and enzyme allocation can affect rates of microbial decomposition. Ecology 92:1471–1480.  https://doi.org/10.1890/10-2028.1 Google Scholar
  34. German DP, Weintraub MN, Grandy AS, Lauber CL, Rinkes ZL, Allison SD (2011b) Optimization of hydrolytic and oxidative enzyme methods for ecosystem studies. Soil Biol Biochem 43:1387–1397.  https://doi.org/10.1016/j.soilbio.2011.03.017 Google Scholar
  35. German DP, Marcelo KRB, Stone MM, Allison SD (2012a) The Michaelis–Menten kinetics of soil extracellular enzymes in response to temperature: a cross-latitudinal study. Glob Chang Biol 18:1468–1479.  https://doi.org/10.1111/j.1365-2486.2011.02615.x Google Scholar
  36. German DP, Weintraub MN, Grandy AS, Lauber CL, Rinkes ZL, Allison SD (2012b) Corrigendum to “optimization of hydrolytic and oxidative enzyme methods for ecosystem studies” [soil biol. Biochem. 43 (2011) 1387–1397]. Soil Biol Biochem 44:151.  https://doi.org/10.1016/j.soilbio.2011.11.002 Google Scholar
  37. Ginteeová A, Lazarová A (1987) Degradation dynamics of lignocellulose materials by wood-rottingPleurotus fungi. Folia Microbiol 32:434–437.  https://doi.org/10.1007/BF02887576 Google Scholar
  38. Glendining MJ, Mytton LR (1989) The response of white clover (Trifolium repens L.) seedlings to spring root temperatures: The relative roles of the plant and the Rhizobium bacteria. Plant and Soil 113(2):147–154Google Scholar
  39. Goverde M, Bazin A, Shykoff JA, Erhardt A (1999) Influence of leaf chemistry of Lotus corniculatus (Fabaceae) on larval development of Polyommatus icarus (Lepidoptera, Lycaenidae): effects of elevated CO2 and plant genotype. Functional Ecology 13(6):801–810Google Scholar
  40. Gregory PJ (2006) Roots, rhizosphere and soil: the route to a better understanding of soil science? Eur J Soil Sci 57:2–12.  https://doi.org/10.1111/j.1365-2389.2005.00778.x Google Scholar
  41. Grime JP, Hodgson JG, Hunt R (1989) Comparative plant ecology. Chapman & Hall, London. ISBN: 978-0-412- 74170-8Google Scholar
  42. Hamer U, Makeschin F (2009) Rhizosphere soil microbial community structure and microbial activity in set-aside and intensively managed arable land. Plant Soil 316:57–69Google Scholar
  43. Hättenschwiler S, Vitousek PM (2000) The role of polyphenols in terrestrial ecosystem nutrient cycling. Trends Ecol Evol 15:238–242Google Scholar
  44. Hayes JE, Richardson AE, Simpson RJ (1999) Phytase and acid phosphatase activities in extracts from roots of temperate pasture grass and legume seedlings. Aust J Plant Physiol 26:801.  https://doi.org/10.1071/PP99065 Google Scholar
  45. Heiland L (2016) Reduced phosphorus ratio homeostasis of grassland plant species declining due to increased land-use intensity. Bachelor thesis, MünsterGoogle Scholar
  46. Herold N, Schöning I, Berner D, Haslwimmer H, Kandeler E, Michalzik B, Schrumpf M (2014) Vertical gradients of potential enzyme activities in soil profiles of European beech, Norway spruce and scots pine dominated forest sites. Pedobiologia 57:181–189.  https://doi.org/10.1016/j.pedobi.2014.03.003 Google Scholar
  47. Hill MO (1973) Diversity and evenness. A unifying notation and its consequences. Ecology 54:427–432.  https://doi.org/10.2307/1934352 Google Scholar
  48. Hoang DTT, Pausch J, Razavi BS, Kuzyakova I, Banfield CC, Kuzyakov Y (2016a) Hotspots of microbial activity induced by earthworm burrows, old root channels, and their combination in subsoil. Biol Fertil Soils 52:1105–1119.  https://doi.org/10.1007/s00374-016-1148-y Google Scholar
  49. Hoang DTT, Razavi BS, Kuzyakov Y, Blagodatskaya E (2016b) Earthworm burrows: kinetics and spatial distribution of enzymes of C-, N- and P- cycles. Soil Biol Biochem 99:94–103.  https://doi.org/10.1016/j.soilbio.2016.04.021 Google Scholar
  50. Hobbie J, Hobbie E (2012) Amino acid cycling in plankton and soil microbes studied with radioisotopes: measured amino acids in soil do not reflect bioavailability. Biogeochemistry 107:339–360.  https://doi.org/10.1007/s10533-010-9556-9 Google Scholar
  51. Ieno EN, Zuur AF (2015) A beginner's guide to data exploration and visualization with R. Highland Statistics Ltd, NewburghGoogle Scholar
  52. Isobe K, Ohte N (2014) Ecological perspectives on microbes involved in N-cycling. Microbes Environ 29:4–16.  https://doi.org/10.1264/jsme2.ME13159 Google Scholar
  53. Johnson NC, Rowland DL, Corkidi L, Allen EB (2008) Plant winners and losers during grassland N-eutrophication differ in biomass allocation and mycorrhizas. Ecology 89:2868–2878.  https://doi.org/10.1890/07-1394.1 Google Scholar
  54. Kandeler E, Luxhøi J, Tscherko D, Magid J (1999) Xylanase, invertase and protease at the soil–litter interface of a loamy sand. Soil Biol Biochem 31:1171–1179.  https://doi.org/10.1016/S0038-0717(99)00035-8. Google Scholar
  55. Kazakou E, Vile D, Shipley B, Gallet C, Garnier E (2006) Co-variations in litter decomposition, leaf traits and plant growth in species from a Mediterranean old-field succession. Functional Ecology 20(1):21–30Google Scholar
  56. Klaus VH, Kleinebecker T, Hölzel N, Blüthgen N, Boch S, Müller J, Socher SA, Prati D, Fischer M (2011) Nutrient concentrations and fibre contents of plant community biomass reflect species richness patterns along a broad range of land-use intensities among agricultural grasslands. Perspect Plant Ecol Evol Syst 13:287–295.  https://doi.org/10.1016/j.ppees.2011.07.001 Google Scholar
  57. Klaus VH, Kleinebecker T, Prati D, Gossner MM, Alt F, Boch S, Gockel S, Hemp A, Lange M, Müller J, Oelmann Y, Pašalić E, Renner SC, Socher SA, Türke M, Weisser WW, Fischer M, Hölzel N (2013) Does organic grassland farming benefit plant and arthropod diversity at the expense of yield and soil fertility? Agric Ecosyst Environ 177:1–9.  https://doi.org/10.1016/j.agee.2013.05.019. Google Scholar
  58. Klaus VH, Kleinebecker T, Busch V, Fischer M, Hölzel N, Nowak S, Prati D, Schäfer D, Schöning I, Schrumpf M, Hamer U (2018) Land use intensity, rather than plant species richness, affects the leaching risk of multiple nutrients from permanent grasslands. Glob Chang Biol 24:2828–2840.  https://doi.org/10.1111/gcb.14123 Google Scholar
  59. Koch AL (1985) The macroeconomics of bacterial growth. In: Fletcher M, Floodgate GD (eds), Bacteria in their natural environments, Vol 16. Published for the Society for General Microbiology by Academic Press, London, Orlando, pp 1–42Google Scholar
  60. Kögel-Knabner I (2002) The macromolecular organic composition of plant and microbial residues as inputs to soil organic matter. Soil Biol Biochem 34:139–162.  https://doi.org/10.1016/S0038-0717(01)00158-4 Google Scholar
  61. Kritzler UH, Johnson D (2010) Mineralisation of carbon and plant uptake of phosphorus from microbially-derived organic matter in response to 19 years simulated nitrogen deposition. Plant Soil 326:311–319.  https://doi.org/10.1007/s11104-009-0009-y Google Scholar
  62. Kuzyakov Y, Blagodatskaya E (2015) Microbial hotspots and hot moments in soil. Concept & review. Soil Biol Biochem 83:184–199.  https://doi.org/10.1016/j.soilbio.2015.01.025 Google Scholar
  63. Lee B-R, Kim K-Y, Jung W-J, Avice J-C, Ourry A, Kim T-H (2007) Peroxidases and lignification in relation to the intensity of water-deficit stress in white clover (Trifolium repens L.). Journal of Experimental Botany 58(6):1271–1279Google Scholar
  64. Leinweber P, Jandl G, Baum C, Eckhardt K-U, Kandeler E (2008) Stability and composition of soil organic matter control respiration and soil enzyme activities. Special section: functional microbial ecology: molecular approaches to microbial ecology and microbial habitats 18th world congress of soil science. Soil Biol Biochem 40:1496–1505.  https://doi.org/10.1016/j.soilbio.2008.01.003. Google Scholar
  65. Loeppmann S, Semenov M, Blagodatskaya E, Kuzyakov Y (2016) Substrate quality affects microbial- and enzyme activities in rooted soil. J Plant Nutr Soil Sci 179:39–47.  https://doi.org/10.1002/jpln.201400518 Google Scholar
  66. Lunt HA, Jacobson HGM (1944) The chemical composition of earthworm casts. Soil Sci 58:367–376Google Scholar
  67. Maire V, Gross N, Da Silveira Pontes L, Picon-Cochard C, Soussana J-F (2009) Trade-off between root nitrogen acquisition and shoot nitrogen utilization across 13 co-occurring pasture grass species. Funct Ecol 23:668–679.  https://doi.org/10.1111/j.1365-2435.2009.01557.x Google Scholar
  68. Marx M-C, Wood M, Jarvis SC (2001) A microplate fluorimetric assay for the study of enzyme diversity in soils. Soil Biol Biochem 33:1633–1640.  https://doi.org/10.1016/S0038-0717(01)00079-7 Google Scholar
  69. Marx M-C, Kandeler E, Wood M, Wermbter N, Jarvis SC (2005) Exploring the enzymatic landscape: distribution and kinetics of hydrolytic enzymes in soil particle-size fractions. Soil Biol Biochem 37:35–48.  https://doi.org/10.1016/j.soilbio.2004.05.024 Google Scholar
  70. Mary B, Mariotti A, Morel JL (1992) Use of 13C variations at natural abundance for studying the biodegradation of root mucilage, roots and glucose in soil. Soil Biol Biochem 24:1065–1072.  https://doi.org/10.1016/0038-0717(92)90037-X Google Scholar
  71. Maseko ST, Dakora FD (2013) Rhizosphere acid and alkaline phosphatase activity as a marker of P nutrition in nodulated Cyclopia and Aspalathus species in the cape fynbos of South Africa. South Afri J Botany 89:289–295.  https://doi.org/10.1016/j.sajb.2013.06.023 Google Scholar
  72. Matson PA, Parton WJ, Power AG, Swift MJ (1997) Agricultural intensification and ecosystem properties. Science 277:504–509.  https://doi.org/10.1126/science.277.5325.504. Google Scholar
  73. Meier IC, Finzi AC, Phillips RP (2017) Root exudates increase N availability by stimulating microbial turnover of fast-cycling N pools. Soil Biol Biochem 106:119–128.  https://doi.org/10.1016/j.soilbio.2016.12.004 Google Scholar
  74. Meyer A, Focks A, Radl V, Keil D, Welzl G, Schöning I, Boch S, Marhan S, Kandeler E, Schloter M (2013) Different land use intensities in grassland ecosystems drive ecology of microbial communities involved in nitrogen turnover in soil. PLoS One 8:e73536.  https://doi.org/10.1371/journal.pone.0073536 Google Scholar
  75. Min BR, Barry TN, Attwood GT, McNabb WC (2003) The effect of condensed tannins on the nutrition and health of ruminants fed fresh temperate forages: a review. Animal Feed Science and Technology 106(1-4):3–19Google Scholar
  76. Nakagawa S, Schielzeth H, O'Hara RB (2013) A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods Ecol Evol 4:133–142.  https://doi.org/10.1111/j.2041-210x.2012.00261.x Google Scholar
  77. Nannipieri P, Gianfreda L (1998) Kinetics of enzyme reactions in soil environments. In: Huang PM, Senesi N, Buffle J (eds), Structure and surface reactions of soil particles. Wiley, Chichester, New York, pp 449–479Google Scholar
  78. Neumann G, Römheld V (2011) Rhizosphere chemistry in relation to plant nutrition. In: Marschner P (ed) Mineral nutrition of higher plants, 3rd edn. Academic Press, London, pp 347–368Google Scholar
  79. Nguyen C, Froux F, Recous S, Morvan T, Robin C (2008) Net N immobilisation during the biodegradation of mucilage in soil as affected by repeated mineral and organic fertilisation. Nutr Cycl Agroecosyst 80:39–47.  https://doi.org/10.1007/s10705-007-9119-1 Google Scholar
  80. Olander LP, Vitousek PM (2000) Regulation of soil phosphatase and chitinase activityby N and P availability. Biogeochemistry 49:175–191.  https://doi.org/10.1023/A:1006316117817. Google Scholar
  81. Orwin KH, Buckland SM, Johnson D, Turner BL, Smart S, Oakley S, Bardgett RD (2010) Linkages of plant traits to soil properties and the functioning of temperate grassland. J Ecol 98:1074–1083.  https://doi.org/10.1111/j.1365-2745.2010.01679.x Google Scholar
  82. Panikov NS, Blagodatsky SA, Blagodatskaya JV, Glagolev MV (1992) Determination of microbial mineralization activity in soil by modified Wright and Hobbie method. Biol Fertil Soils 14:280–287.  https://doi.org/10.1007/BF00395464 Google Scholar
  83. Paul EA (ed) (2014) Soil microbiology, ecology, and biochemistry, 4th edn. Academic Press, Amsterdam etc.Google Scholar
  84. Philippot L, Raaijmakers JM, Lemanceau P, van der Putten WH (2013) Going back to the roots: the microbial ecology of the rhizosphere. Nat Rev Microbiol 11:789–799.  https://doi.org/10.1038/nrmicro3109 Google Scholar
  85. Phillips RP, Fahey TJ (2006) Tree species and mycorrhizal associations influence the magnitude of rhizosphere effects. Ecology 87:1302–1313. https://doi.org/10.1890/0012-9658(2006)87[1302:TSAMAI]2.0.CO;2Google Scholar
  86. Pierce S, Brusa G, Vagge I, Cerabolini BEL, Thompson K (2013) Allocating CSR plant functional types: the use of leaf economics and size traits to classify woody and herbaceous vascular plants. Functional Ecology 27(4):1002–1010Google Scholar
  87. Poorter H (1989) Interspecific variation in relative growth rate: On ecological and physiological consequences. In: Lambers et al (eds) Causes and consequences of variation in growth rate and productivity of higher plants. SPB Academic Publishing, NL, pp 45–68Google Scholar
  88. Poorter H, Remkes C (1990) Leaf area ratio and net assimilation rate of 24 wild species differing in relative growth rate. Oecologia 83(4):553–559Google Scholar
  89. R core team (2013) R: a language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
  90. Ray TC, Callow JA, Kennedy JF (1988) Composition of root mucilage polysaccharides from Lepidium sativum. J Exp Bot 39:1249–1261.  https://doi.org/10.1093/jxb/39.9.1249 Google Scholar
  91. Razavi BS, Blagodatskaya E, Kuzyakov Y (2016a) Temperature selects for static soil enzyme systems to maintain high catalytic efficiency. Soil Biol Biochem 97:15–22.  https://doi.org/10.1016/j.soilbio.2016.02.018 Google Scholar
  92. Razavi BS, Zarebanadkouki M, Blagodatskaya E, Kuzyakov Y (2016b) Rhizosphere shape of lentil and maize. Spatial distribution of enzyme activities. Soil Biol Biochem 96:229–237.  https://doi.org/10.1016/j.soilbio.2016.02.020 Google Scholar
  93. Schimel JP, Schaeffer SM (2012) Microbial control over carbon cycling in soil. Front Microbiol 3.  https://doi.org/10.3389/fmicb.2012.00348
  94. Schimel JP, Weintraub MN (2003) The implications of exoenzyme activity on microbial carbon and nitrogen limitation in soil: a theoretical model. Soil Biol Biochem 35:549–563.  https://doi.org/10.1016/S0038-0717(03)00015-4. Google Scholar
  95. Sinsabaugh RL (1994) Enzymic analysis of microbial pattern and process. Biol Fertil Soils 17:69–74.  https://doi.org/10.1007/BF00418675 Google Scholar
  96. Sinsabaugh RL, Follstad Shah JJ (2012) Ecoenzymatic stoichiometry and ecological theory. Annu Rev Ecol Evol Syst 43:313–343.  https://doi.org/10.1146/annurev-ecolsys-071112-124414 Google Scholar
  97. Solly EF, Schöning I, Boch S, Kandeler E, Marhan S, Michalzik B, Müller J, Zscheischler J, Trumbore SE, Schrumpf M (2014) Factors controlling decomposition rates of fine root litter in temperate forests and grasslands. Plant Soil 382:203–218.  https://doi.org/10.1007/s11104-014-2151-4 Google Scholar
  98. Spohn M, Treichel NS, Cormann M, Schloter M, Fischer D (2015) Distribution of phosphatase activity and various bacterial phyla in the rhizosphere of Hordeum vulgare L. depending on P availability. Soil Biol Biochem 89:44–51.  https://doi.org/10.1016/j.soilbio.2015.06.018 Google Scholar
  99. Stemmer M, Gerzabek MH, Kandeler E (1998) Organic matter and enzyme activity in particle-size fractions of soils obtained after low-energy sonication. Soil Biol Biochem 30:9–17.  https://doi.org/10.1016/S0038-0717(97)00093-X Google Scholar
  100. Stemmer M, Gerzabek MH, Kandeler E (1999) Invertase and xylanase activity of bulk soil and particle-size fractions during maize straw decomposition. Soil Biol Biochem 31:9–18.  https://doi.org/10.1016/S0038-0717(98)00083-2 Google Scholar
  101. Sterner RW, Elser JJ (2002) Ecological stoichiometry. The biology of elements from molecules to the biosphere. Princeton University Press, PrincetonGoogle Scholar
  102. Strickland MS, Rousk J (2010) Considering fungal. Bacterial dominance in soils - methods, controls, and ecosystem implications. Soil Biol Biochem 42:1385–1395Google Scholar
  103. Swift MJ, Heal OW, Anderson JM (1979) Decomposition in terrestrial ecosystems, vol 5. Blackwell Scientific Publications, OxfordGoogle Scholar
  104. Tarafdar JC, Chhonkar PK (1978) Status of phophatases in the root-soil interface of leguminous and non-leguminous crops. J Plant Nutr Soil Sci 141:347–351.  https://doi.org/10.1002/jpln.19781410310 Google Scholar
  105. Tarafdar JC, Jungk A (1987) Phosphatase activity in the rhizosphere and its relation to the depletion of soil organic phosphorus. Biol Fertil Soils 3:199–204.  https://doi.org/10.1007/BF00640630 Google Scholar
  106. Tischer A, Blagodatskaya E, Hamer U (2014) Extracellular enzyme activities in a tropical mountain rainforest region of southern Ecuador affected by low soil P status and land-use change. Appl Soil Ecol 74:1–11.  https://doi.org/10.1016/j.apsoil.2013.09.007 Google Scholar
  107. Tischer A, Blagodatskaya E, Hamer U (2015a) Microbial community structure and resource availability drive the catalytic efficiency of soil enzymes under land-use change conditions. Soil Biol Biochem 89:226–237.  https://doi.org/10.1016/j.soilbio.2015.07.011 Google Scholar
  108. Tischer A, Werisch M, Döbbelin F, Camenzind T, Rillig M, Potthast K, Hamer U (2015b) Above- and belowground linkages of a nitrogen and phosphorus co-limited tropical mountain pasture system – responses to nutrient enrichment. Plant Soil 391:1–20.  https://doi.org/10.1007/s11104-015-2431-7 Google Scholar
  109. Turner BL (2008) Resource partitioning for soil phosphorus: a hypothesis. J Ecol 96:698–702.  https://doi.org/10.1111/j.1365-2745.2008.01384.x Google Scholar
  110. Turner BL (2010) Variation in pH optima of hydrolytic enzyme activities in tropical rain Forest soils. Appl Environ Microbiol 76:6485–6493.  https://doi.org/10.1128/AEM.00560-10 Google Scholar
  111. Tušek AJ, Benković M, Belščak Cvitanović A, Valinger D, Jurina T, Gajdoš Kljusurić J (2016) Kinetics and thermodynamics of the solid-liquid extraction process of total polyphenols, antioxidants and extraction yield from Asteraceae plants. Industrial Crops and Products 91:205–214Google Scholar
  112. Vance ED, Brookes PC, Jenkinson DS (1987) An extraction method for measuring soil microbial biomass C. Soil Biol Biochem 19:703–707Google Scholar
  113. Velbert F, Kleinebecker T, Mudrák O, Schwartze P, Hölzel N (2017) Time lags in functional response to management regimes - evidence from a 26-year field experiment in wet meadows. J Veg Sci 28:313–324.  https://doi.org/10.1111/jvs.12497 Google Scholar
  114. Wallenstein M, Allison SD, Ernakovich J, Steinweg JM, Sinsabaugh R (2011) Controls on the temperature sensitivity of soil enzymes: a key driver of in situ enzyme activity rates. In: Shukla G, Varma A (eds) Soil enzymology, vol 22. Springer, Berlin, pp 245–258Google Scholar
  115. Wallenstein MD, Weintraub MN (2008) Emerging tools for measuring and modeling the in situ activity of soil extracellular enzymes. Soil Biol Biochem 40:2098–2106.  https://doi.org/10.1016/j.soilbio.2008.01.024 Google Scholar
  116. Whittingham MJ, Swetnam RD, Wilson JD, Chamberlain DEN, Freckleton RP (2005) Habitat selection by yellowhammers Emberiza citrinella on lowland farmland at two spatial scales: implications for conservation management. J Appl Ecol 42:270–280.  https://doi.org/10.1111/j.1365-2664.2005.01007.x Google Scholar
  117. Wong KK, Tan LU, Saddler JN (1988) Multiplicity of beta-1,4-xylanase in microorganisms: functions and applications. Microbiol Rev 52:305–317Google Scholar
  118. Zelenev VV, van Bruggen AHC, Semenov AM (2005) Modeling wave-like dynamics of oligotrophic and copiotrophic bacteria along wheat roots in response to nutrient input from a growing root tip. Ecol Model 188:404–417Google Scholar
  119. Zuur AF, Ieno EN, Walker N, Saveliev AA, Smith GM (2009) Mixed effects models and extensions in ecology with R. Springer New York, New YorkGoogle Scholar

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Soil ScienceFriedrich-Schiller University JenaJenaGermany
  2. 2.Institute of Landscape EcologyUniversity of MünsterMünsterGermany
  3. 3.Institute of Landscape Ecology and Resource ManagementJustus-Liebig-University GießenGiessenGermany
  4. 4.Institute of Agricultural SciencesETH ZürichZürichSwitzerland

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