Decoupling of soil nutrient cycles as a function of aridity in global drylands (original) (raw)

References

  1. Finzi, A. C. et al. Coupled biochemical cycles: responses and feedbacks of coupled biogeochemical cycles to climate change. Examples from terrestrial ecosystems. Front. Ecol. Environ 9, 61–67 (2011)
    Google Scholar
  2. McGill, W. B. & Cole, C. V. Comparative aspects of cycling organic C, N, S and P through soil organic matter. Geoderma 26, 267–286 (1981)
    CAS ADS Google Scholar
  3. Peñuelas, J. et al. The human-induced imbalance between C, N and P in Earth’s life system. Glob. Change Biol. 18, 3–6 (2012)
    ADS Google Scholar
  4. Schlesinger, W. H. et al. Biological feedbacks in global desertification. Science 247, 1043–1048 (1990)
    CAS PubMed ADS Google Scholar
  5. Vicente-Serrano, S. M. et al. Dryness is accelerating degradation of vulnerable shrublands in semiarid Mediterranean environments. Ecol. Monogr. 82, 407–428 (2012)
    Google Scholar
  6. Austin, A. T. et al. Water pulses and biogeochemical cycles in arid and semiarid ecosystems. Oecologia 141, 221–235 (2004)
    ADS PubMed Google Scholar
  7. Schwinning, S. & Sala, O. E. Hierarchy of responses to resource pulses in arid and semi-arid ecosystems. Oecologia 141, 211–220 (2004)
    PubMed ADS Google Scholar
  8. Whitford, W. G. Ecology of Desert Systems (Academic, 2002)
    Google Scholar
  9. Gao, X. J. & Giorgi, F. Increased aridity in the Mediterranean region under greenhouse gas forcing estimated from high resolution simulations with a regional climate model. Global Planet. Change 62, 195–209 (2008)
    ADS Google Scholar
  10. Feng, S. & Fu, Q. Expansion of global drylands under a warming climate. Atmos. Chem. Phys. Discuss. 13, 14637–14665 (2013)
    ADS Google Scholar
  11. Dai, A. Increasing drought under global warming in observations and models. Nature Clim. Change 3, 52–58 (2013)
    ADS Google Scholar
  12. Schlesinger, W. H. Biogeochemistry, an Analysis of Global Change (Academic, 1996)
    Google Scholar
  13. Walker, T. W. & Syers, J. K. The fate of phosphorus during pedogenesis. Geoderma 15, 1–19 (1976)
    CAS ADS Google Scholar
  14. Vitousek, P. M. Nutrient Cycling and Limitation: Hawai’i as a Model System (Princeton Univ. Press, 2004)
    Google Scholar
  15. Nannipieri, P. et al. Phosphorus in Action (Soil Biol. 26, Springer, 2011)
  16. Liebig, J. et al. Chemistry in its Application to Agriculture and Physiology 3rd edn (Owen, 1842)
  17. Reynolds, J. F. et al. Global desertification: building a science for dryland development. Science 316, 847–851 (2007)
    CAS ADS PubMed Google Scholar
  18. Schimel, D. S. Drylands in the Earth system. Science 327, 418–419 (2010)
    CAS PubMed Google Scholar
  19. Maestre, F. T. et al. It’s getting hotter in here: determining and projecting the impacts of global environmental change on drylands. Phil. Trans. R. Soc. B 367, 3062–3075 (2012)
    PubMed PubMed Central Google Scholar
  20. Cross, A. F. & Schlesinger, W. H. Biological and geochemical controls on phosphorus fractions in semiarid soils. Biogeochemistry 52, 155–172 (2001)
    CAS Google Scholar
  21. Li, J. et al. Quantitative effects of vegetation cover on wind erosion and soil nutrient loss in a desert grassland of southern New Mexico, USA. Biogeochemistry 85, 317–332 (2007)
    Google Scholar
  22. Sinsabaugh, R. L. et al. Enzymes in the Environment (Oxford Univ. Press, 2002)
  23. Olander, L. P. & Vitousek, P. M. Regulation of soil phosphatase and chitinase activity by N and P availability. Biogeochemistry 49, 175–191 (2000)
    CAS Google Scholar
  24. Schimel, J. P. & Bennett, J. Nitrogen mineralization, challenges of a changing paradigm. Ecology 85, 591–602 (2004)
    Google Scholar
  25. Evans, S. E. & Burke, I. C. carbon and nitrogen decoupling under an 11-year drought in the shortgrass steppe. Ecosystems (N. Y.) 16, 20–33 (2013)
    CAS Google Scholar
  26. Thornton, P. E. et al. Influence of carbon–nitrogen cycle coupling on land model response to CO2 fertilization and climate variability. Glob. Biogeochem. Cycles 21, GB4018 (2007)
    ADS Google Scholar
  27. Scheffer, M. et al. Early-warning signals for critical transitions. Nature 461, 53–59 (2009)
    CAS ADS PubMed Google Scholar
  28. Maestre, F. T. et al. Plant species richness and ecosystem multifunctionality in global drylands. Science 335, 214–218 (2012)
    CAS PubMed PubMed Central ADS Google Scholar
  29. Hijmans, R. J. et al. Very high resolution interpolated climate surfaces for global areas. Int. J. Clim. 25, 1965–1978 (2005)
    Google Scholar
  30. Grace, J. B. Structural Equation Modelling Natural Systems (Cambridge Univ. Press, 2006)
    Google Scholar
  31. Robertson, G. P. & Groffman, P. Soil Microbiology and Biochemistry (Springer, 2007)
    Google Scholar
  32. Rovira, P. & Vallejo, V. R. Labile and recalcitrant pools of carbon and nitrogen in organic matter decomposing at different depths in soil: an acid hydrolysis approach. Geoderma 107, 109–141 (2002)
    CAS ADS Google Scholar
  33. Neff, J. C. et al. Breaks in the cycle: dissolved organic nitrogen in terrestrial ecosystems. Front. Ecol. Environ 1, 205–211 (2003)
    Google Scholar
  34. Sardans, J. et al. The C:N:P stoichiometry of organisms and ecosystems in a changing world: a review and perspectives. Perspect. Plant Ecol. Evol. Syst. 14, 33–47 (2012)
    Google Scholar
  35. Chantigny, M. H. et al. Soil Sampling and Methods of Analysis (CRC, 2006)
  36. Bray, R. H. & Kurtz, L. T. Determination of total, organic, and available forms of phosphorus in soils. Soil Sci. 59, 39–46 (1945)
    CAS ADS Google Scholar
  37. Olsen, S. R. et al. Estimation of available phosphorus in soils by extraction with sodium bicarbonate. USDA Circ. 939, (1954)
  38. Tiessen, H. & Moir, J. O. Characterization of Available P by Sequential Fractionation. Soil Sampling and Methods of Analysis (Lewis, 1993)
    Google Scholar
  39. Carreira, J. A. et al. Phosphorus transformations along a soil/vegetation series of fire-prone, dolomitic, semi-arid shrublands of southern Spain. Biogeochemistry 39, 87–120 (1997)
    CAS Google Scholar
  40. Schoenau, J. J. et al. Forms and cycling of phosphorus in prairie and boreal forest soils. Biogeochemistry 8, 223–237 (1989)
    CAS Google Scholar
  41. Bowman, R. A. & Cole, C. V. Transformations of organic phosphorus substrates in soils as evaluated by NaHCO3 extractions. Soil Sci. 125, 49–54 (1978)
    CAS ADS Google Scholar
  42. Cross, A. F. & Schlesinger, W. H. A literature review and evaluation of the Hedley fractionation: applications to the biogeochemical cycle of soil phosphorus in natural ecosystems. Geoderma 64, 197–214 (1995)
    CAS ADS Google Scholar
  43. Lajtha, K. & Bloomer, S. H. Factors affecting phosphate sorption and phosphate retention in a desert ecosystem. Soil Sci. 146, 160–167 (1988)
    CAS ADS Google Scholar
  44. Roberts, T. L. et al. The influence of topography on the distribution of organic and inorganic soil phosphorus across a narrow environmental gradient. Can. J. Soil Sci. 65, 651–665 (1985)
    CAS Google Scholar
  45. Anderson, J. M. & Ingramm, J. S. I. Tropical Soil Biology and Fertility: A Handbook of Methods 2nd edn (CABI, 1993)
    Google Scholar
  46. Tabatabai, M. A. & Bremner, J. M. Use of p-nitrophenyl phosphate for assay of soil phosphatase activity. Soil Biol. Biochem. 1, 301–307 (1969)
    CAS Google Scholar
  47. Delgado-Baquerizo, M. et al. A dissolved organic nitrogen in Mediterranean ecosystems. Pedosphere 21, 309–318 (2011)
    CAS Google Scholar
  48. Helmut, G. The Causes and Progression of Desertification (Ashgate, 2005)
    Google Scholar
  49. Michael, B. et al. Human Impact on Environment and Sustainable Development in Africa (Ashgate, 2003)
  50. Johnson, P. J. Governing Global Desertification: Linking Environmental Degradation, Poverty and Participation (Ashgate, 2006)
    Google Scholar
  51. Food and Agriculture Organization. Arid Zone Forestry: A Guide for Field Technicians Ch. I (Food and Agriculture Organization, 1989)
  52. Vitousek, P. M. et al. Towards an ecological understanding of biological nitrogen fixation. Biogeochemistry 57, 1–45 (2002)
    Google Scholar
  53. Maestre, F. T. et al. Potential of using facilitation by grasses to establish shrubs on a semiarid degraded steppe. Ecol. Appl. 11, 1641–1655 (2001)
    Google Scholar
  54. Reynolds, J. F. et al. Impact of drought on desert shrubs: effects of seasonality and degree of resource island development. Ecol. Monogr. 69, 69–106 (1999)
    Google Scholar
  55. Maestre, F. T. et al. Positive, negative and net effects in grass-shrub interactions in Mediterranean semiarid grasslands. Ecology 84, 3186–3197 (2003)
    Google Scholar
  56. Eldridge, D. et al. Interactive effects of three ecosystem engineers on infiltration in a semi-arid Mediterranean grassland. Ecosystems (N. Y.) 13, 499–510 (2010)
    Google Scholar
  57. Cerdà, A. The effect of patchy distribution of Stipa tenacissima L. on runoff and erosion. J. Arid Environ. 36, 37–51 (1997)
    ADS Google Scholar
  58. Cornelis, W. S. Dryland Ecohydrology (Springer, 2006)
    Google Scholar
  59. Blanco, H. & Rattan, R. Principles of Soil Conservation and Management (Springer, 2010)
    Google Scholar
  60. Yerima, P. K. et al. Introduction to Soil Science: Soils of the Tropics (Trafford, 2005)
  61. Marshall, K. C. Clay mineralogy in relation to survival of soil bacteria. Annu. Rev. Phytopathol. 13, 357–373 (1975)
    Google Scholar
  62. Stotzky, G. Activity, ecology, and population dynamics of microorganisms in soil. Rev. Microbiol. 2, 59–137 (1972)
    CAS Google Scholar
  63. Kandeler, E. Physiological and Biochemical Methods for Studying Soil Biota and Their Function. Soil Microbiology and Biochemistry (Springer, 2007)
    Google Scholar
  64. Tietjen, T. & Wetzel, R. G. Extracellular enzyme-clay mineral complexes: enzyme adsorption, alteration of enzyme activity, and protection from photodegradation. Aquat. Ecol. 37, 331–339 (2003)
    CAS Google Scholar
  65. Sugiura, N. Further analysis of the data by Akaike’s information criterion and the finite corrections. Commun. Stat. Theor. M. A7, 13–26 (1978)
    MATH Google Scholar
  66. Zomer, R. J. et al. Carbon, Land and Water: a Global Analysis of the Hydrologic Dimensions of Climate Change Mitigation Through Afforestation/Reforestation. Research Report 101 (International Water Management Institute, 2006)
  67. Schimel, D. S. et al. Climatic, edaphic, and biotic controls over storage and turnover of carbon in soils. Glob. Biogeochem. Cycles 8, 279–293 (1994)
    CAS ADS Google Scholar
  68. Schmidt, M. W. I. et al. Persistence of soil organic matter as an ecosystem property. Nature 478, 49–56 (2011)
    CAS PubMed ADS Google Scholar
  69. Oades, J. M. The retention of organic matter in soils. Biogeochemistry 5, 35–70 (1988)
    CAS Google Scholar
  70. Shipley, B. Cause and Correlation in Biology: a User’s Guide to Path Analysis Structural Equations and Causal Inference (Cambridge Univ. Press, 2001)
    Google Scholar
  71. Morford, S. L. et al. Increased forest ecosystem carbon and nitrogen storage from nitrogen rich bedrock. Nature 477, 78–81 (2011)
    CAS PubMed ADS Google Scholar
  72. Schermelleh-Engel et al. Evaluating the fit of structural equation models, tests of significance descriptive goodness-of-fit measures. Methods Psychol. Res. Online 8, 23–74 (2003)
    Google Scholar

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Acknowledgements

We thank M. Scheffer, N. J. Gotelli and R. Bardgett for comments on previous versions of the manuscript, and all the technicians and colleagues who helped with the field surveys and laboratory analyses. This research is supported by the European Research Council (ERC) under the European Community's Seventh Framework Programme (FP7/2007-2013)/ERC Grant agreement no. 242658 (BIOCOM), and by the Ministry of Science and Innovation of the Spanish Government, grant no. CGL2010-21381. CYTED funded networking activities (EPES, Acción 407AC0323). M.D.-B. was supported by a PhD fellowship from the Pablo de Olavide University.

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Authors and Affiliations

  1. Departamento de Sistemas Físicos, Químicos y Naturales, Universidad Pablo de Olavide, Carretera de Utrera, kilómetro 1, 41013 Sevilla, Spain,
    Manuel Delgado-Baquerizo & Antonio Gallardo
  2. Departamento de Biología y Geología, Area de Biodiversidad y Conservación, Escuela Superior de Ciencias Experimentales y Tecnología, Universidad Rey Juan Carlos, Calle Tulipán Sin Número, 28933 Móstoles, Spain,
    Manuel Delgado-Baquerizo, Fernando T. Maestre, Jose Luis Quero, Victoria Ochoa, Beatriz Gozalo, Miguel García-Gómez, Santiago Soliveres, Miguel Berdugo, Enrique Valencia, Cristina Escolar, Adrián Escudero & Vicente Polo
  3. School of Forestry, Northern Arizona University, Flagstaff, 86011, Arizona, USA
    Matthew A. Bowker
  4. Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, 80523, Colorado, USA
    Matthew D. Wallenstein & Pablo García-Palacios
  5. Departamento de Ingeniería Forestal, Campus de Rabanales Universidad de Córdoba, Carretera de Madrid, kilómetro 396, 14071 Córdoba, Spain,
    Jose Luis Quero
  6. Department of Biology, Colorado State University, Fort Collins, 80523, Colorado, USA
    Pablo García-Palacios
  7. División de Ciencias Ambientales, Instituto Potosino de Investigación Científica y Tecnológica, San Luis Potosí, San Luis Potosí, 78210, Mexico ,
    Tulio Arredondo & Elisabeth Huber-Sannwald
  8. Departamento de Biología, Universidad de La Serena, La Serena 599, 1700000, Chile,
    Claudia Barraza-Zepeda & Julio R. Gutiérrez
  9. Instituto Nacional de Tecnología Agropecuaria, Estación Experimental San Carlos de Bariloche 277, Bariloche, Río Negro, 8400, Argentina ,
    Donaldo Bran & Juan Gaitán
  10. Departamento de Biología Animal, Universidad de Jaen, Biología Vegetal y Ecología, 23071 Jaen, Spain,
    José Antonio Carreira
  11. Université de Sfax, Faculté des Sciences, Unité de Recherche Plant Diversity and Ecosystems in Arid Environments, Route de Sokra, kilomètre 3.5, Boîte Postale 802, 3018 Sfax, Tunisia ,
    Mohamed Chaieb & Zouhaier Noumi
  12. Departamento de Ciências Biológicas, Universidade Estadual de Feira de Santana, Avenida Transnordestina Sin Número, Bairro Novo Horizonte, Feira de Santana, 44036-900, Brasil,
    Abel A. Conceição & Roberto Romão
  13. Direction Régionale des Eaux et Forêts et de la Lutte Contre la Désertification du Rif, Avenue Mohamed 5, Boîte Postale 722, 93000 Tétouan, Morocco ,
    Mchich Derak
  14. School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, New South Wales 2052, Australia ,
    David J. Eldridge
  15. Instituto de Ecología, Universidad Técnica Particular de Loja, San Cayetano Alto, Marcelino Champagnat, Loja, 11-01-608, Ecuador ,
    Carlos I. Espinosa & Elizabeth Guzman
  16. Departamento de Biología, Facultad de Ciencias Exactas, Físicas y Naturales, Universidad Nacional de San Juan, Rivadavia, San Juan, J5402DCS, Argentina,
    M. Gabriel Gatica & Eduardo Pucheta
  17. Departamento de Ciencias Básicas, Laboratorio de Genómica y Biodiversidad, Universidad del Bío-Bío 447, Chillán, 3780000, Chile,
    Susana Gómez-González & Cristian Torres-Díaz
  18. Instituto de Edafología, Facultad de Agronomía, Universidad Central de Venezuela, Ciudad Universitaria, Caracas, 1051, Venezuela ,
    Adriana Florentino
  19. Facultad de Agronomía, Universidad Nacional de La Pampa, Casilla de Correo 300, 6300 Santa Rosa, La Pampa, Argentina ,
    Estela Hepper & Aníbal Prina
  20. Laboratorio de Biogeoquímica, Centro de Agroecología Tropical, Universidad Experimental Simón Rodríguez, Caracas, 47925, Venezuela ,
    Rosa M. Hernández & Elizabeth Ramírez
  21. Department of Range and Watershed Management, Faculty of Natural Resources and Environment, Ferdowsi University of Mashhad, Azadi Square, Mashhad 91775–1363, Iran,
    Mohammad Jankju & Kamal Naseri
  22. Institute of Grassland Science, Northeast Normal University and Key Laboratory of Vegetation Ecology, Ministry of Education, Changchun, Jilin Province 130024, China ,
    Jushan Liu & Deli Wang
  23. Department of Biological Sciences, Northern Arizona University, PO Box 5640, Flagstaff, Arizona 86011–5640, USA,
    Rebecca L. Mau
  24. Department of Evolution, Ecology and Organismal Biology, Ohio State University, 318 West 12th Avenue, Columbus, Ohio 43210, USA,
    Maria Miriti
  25. Département des Sciences Biologiques, Université du Québec à Montréal Pavillon des Sciences Biologiques, 141 Président-Kennedy, Montréal, Québec H2X 3Y5, Canada,
    Jorge Monerris
  26. Production Systems and the Environment Sub-Program, International Potato Center. Apartado 1558, Lima 12, Peru ,
    David A. Ramírez-Collantes
  27. Department of Agronomy and Soil Science, School of Environmental and Rural Science, University of New England, Armidale, New South Wales 2351, Australia,
    Matthew Tighe
  28. Departamento de Química y Suelos, Decanato de Agronomía, Universidad Centroccidental “Lisandro Alvarado”, Barquisimeto 3001, Venezuela,
    Duilio Torres
  29. Department of Agronomy and Natural Resources, Institute of Plant Sciences, Agricultural Research Organization, The Volcani Center, Bet Dagan 50250, Israel,
    Eugene D. Ungar
  30. Office of Environment and Heritage, PO Box 363, Buronga, New South Wales 2739, Australia ,
    James Val
  31. Zoology Department, National Museums of Kenya, Ngara Road, Nairobi, 78420-00500, Kenya,
    Wanyoike Wamiti
  32. Department of Natural Resources and Agronomy, Agriculture Research Organization, Ministry of Agriculture, Gilat Research Center, Mobile Post Negev 85280, Israel,
    Eli Zaady

Authors

  1. Manuel Delgado-Baquerizo
  2. Fernando T. Maestre
  3. Antonio Gallardo
  4. Matthew A. Bowker
  5. Matthew D. Wallenstein
  6. Jose Luis Quero
  7. Victoria Ochoa
  8. Beatriz Gozalo
  9. Miguel García-Gómez
  10. Santiago Soliveres
  11. Pablo García-Palacios
  12. Miguel Berdugo
  13. Enrique Valencia
  14. Cristina Escolar
  15. Tulio Arredondo
  16. Claudia Barraza-Zepeda
  17. Donaldo Bran
  18. José Antonio Carreira
  19. Mohamed Chaieb
  20. Abel A. Conceição
  21. Mchich Derak
  22. David J. Eldridge
  23. Adrián Escudero
  24. Carlos I. Espinosa
  25. Juan Gaitán
  26. M. Gabriel Gatica
  27. Susana Gómez-González
  28. Elizabeth Guzman
  29. Julio R. Gutiérrez
  30. Adriana Florentino
  31. Estela Hepper
  32. Rosa M. Hernández
  33. Elisabeth Huber-Sannwald
  34. Mohammad Jankju
  35. Jushan Liu
  36. Rebecca L. Mau
  37. Maria Miriti
  38. Jorge Monerris
  39. Kamal Naseri
  40. Zouhaier Noumi
  41. Vicente Polo
  42. Aníbal Prina
  43. Eduardo Pucheta
  44. Elizabeth Ramírez
  45. David A. Ramírez-Collantes
  46. Roberto Romão
  47. Matthew Tighe
  48. Duilio Torres
  49. Cristian Torres-Díaz
  50. Eugene D. Ungar
  51. James Val
  52. Wanyoike Wamiti
  53. Deli Wang
  54. Eli Zaady

Contributions

F.T.M., M.D.-B. and A.G. designed this study. F.T.M. coordinated all field and laboratory operations. Field data were collected by all authors except A.E., A.G., B.G., E.V., M.B. and M.D.W. Laboratory analyses were done by V.O., A.G., M.B., M.D.-B., E.V. and B.G. Data analyses were done by M.D.-B. and M.A.B. The paper was written by M.D.-B., F.T.M., M.D.W. and A.G., and the remaining authors contributed to the subsequent drafts.

Corresponding author

Correspondence toManuel Delgado-Baquerizo.

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Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 2 Relationships between aridity and the concentration of carbohydrates (C), available N, available P and their ratios at our study sites.

Available N, sum of dissolved inorganic N and amino acids; available P, Olsen inorganic P. The solid and dashed lines represent the fitted quadratic regressions and their 95% confidence intervals, respectively.

Extended Data Figure 3 Relationships between aridity and the concentration of HCl-P fraction at our study sites.

Extended Data Figure 4 A-priori structural equation model used in this study.

We included in this model aridity (Ar; composite variable formed from Ar and Ar2), percentage of plant cover (Plant), percentage of clay (Clay), spatial position (Spatial; composite variable formed from distance from Equator (De) and longitude (Lon)), activity of phosphatase, organic matter component (OMC; first component from a PCA conducted with organic C (OC) and total N (TN)) and total P. We built our structural equation model by taking into account all these relationship, as explained in Methods. There are some differences between the a-priori model and the final model structures owing to removal of paths with coefficients close to zero (Fig. 2). Hexagons are composite variables30. Squares are observable variables.

Extended Data Figure 5 Global structural equation model, depicting the effects of aridity, clay percentage, plant cover and site position on the organic matter component, the inorganic-P concentration and phosphatase activity.

Spatial coordinates of the study sites are expressed in terms of distance from Equator (De) and longitude (Lon). The organic matter component (OMC) is the first component from a PCA conducted with organic C and total N. The inorganic-P concentration is the sum of Olsen inorganic P and HCl-P. Numbers adjacent to arrows are standardized path coefficients, analogous to relative regression weights, and indicative of the effect size of the relationship. Continuous and dashed arrows indicate positive and negative relationships, respectively. The width of arrows is proportional to the strength of path coefficients. The proportion of variance explained (_R_2) appears above every response variable in the model. Goodness-of-fit statistics for each model are shown in the lower right corner. There are some differences between the a-priori model and the final model structures owing to removal of paths with coefficients close to zero (see the a-priori model in Extended Data Fig. 4). Hexagons are composite variables30. Squares are observable variables. *P < 0.05, **P < 0.01, ***P < 0.001.

Extended Data Figure 6 Standardized total effects (direct plus indirect effects) derived from the structural equation modelling.

These include the effects of aridity, percentage of clay, plant cover, distance from Equator (De) and longitude (Lon) on the organic matter component (OMC, first component from a PCA conducted with organic C and total N), inorganic P (sum of Olsen inorganic P and HCl-P) and phosphatase activity (PhA).

Extended Data Figure 7 Global structural equation model, depicting the effects of aridity, clay percentage, plant cover and site position on the labile organic matter component, available-P concentration and phosphatase activity.

The labile organic matter component (labile OMC) is the first component from a PCA conducted with soil carbohydrates and the ratio of available N to the sum of dissolved inorganic N and amino acids. Available P is the Olsen inorganic P. Numbers adjacent to arrows are standardized path coefficients, analogous to relative regression weights, and indicative of the effect size of the relationship. Continuous and dashed arrows indicate positive and negative relationships, respectively. The width of arrows is proportional to the strength of path coefficients. The proportion of variance explained (_R_2) appears above every response variable in the model. Goodness-of-fit statistics for each model are shown in the lower right corner. There are some differences between the a-priori model and the final model structures owing to removal of paths with coefficients close to zero (see the a-priori model in Extended Data Fig. 4). Hexagons are composite variables30. Squares are observable variables. *P < 0.05, **P < 0.01, ***P < 0.001.

Extended Data Figure 8 Standardized total effects (direct plus indirect effects) derived from the structural equation modelling.

These include the effects of aridity, percentage of clay, plant cover, distance from Equator (De) and longitude (Lon) on the labile organic matter component (LOMC, first component from a PCA conducted with carbohydrates and available N), available P (Olsen inorganic P) and phosphatase activity (PhA).

Extended Data Figure 9 Relationships between total N and the potential net nitrification (upper graph) and mineralization rates (lower graph) measured at our study sites.

Air-dried soil samples were re-wetted to reach 80% of field water-holding capacity and incubated in the laboratory for 14 days at 30 °C (ref. 28). Potential net nitrification and ammonification rates were estimated as the difference between initial and final nitrate and ammonium concentrations28. The solid line denotes the quadratic model fitted to the data (_R_2 and P values shown in each panel).

Extended Data Figure 10 Relationships between the total N and microbial biomass N in a subset of 50 of our 224 sites.

All air-dried soil samples were adjusted to 55% of their water-holding capacity previous to the analyses of microbial biomass N. Microbial biomass N was determined using the fumigation–extraction method. Non-incubated and incubated soil subsamples were fumigated with chloroform for five days. Non-fumigated replicates were used as controls. Fumigated and non-fumigated samples were extracted with K2SO4 0.5 M in the ratio 1:5 and filtered through a 0.45-μm Millipore filter. Concentration of microbial biomass N was estimated as the difference between total N of fumigated and non-fumigated digested extracts28 and then divided by 0.54 (that is, by Kn, the fraction of biomass N extracted after the CHC13 treatment). The solid line denotes the quadratic model fitted to the data (_R_2 and P values shown in the graph).

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Delgado-Baquerizo, M., Maestre, F., Gallardo, A. et al. Decoupling of soil nutrient cycles as a function of aridity in global drylands.Nature 502, 672–676 (2013). https://doi.org/10.1038/nature12670

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