Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Hotspots of biogeochemical activity linked to aridity and plant traits across global drylands

Subjects

Abstract

Perennial plants create productive and biodiverse hotspots, known as fertile islands, beneath their canopies. These hotspots largely determine the structure and functioning of drylands worldwide. Despite their ubiquity, the factors controlling fertile islands under conditions of contrasting grazing by livestock, the most prevalent land use in drylands, remain virtually unknown. Here we evaluated the relative importance of grazing pressure and herbivore type, climate and plant functional traits on 24 soil physical and chemical attributes that represent proxies of key ecosystem services related to decomposition, soil fertility, and soil and water conservation. To do this, we conducted a standardized global survey of 288 plots at 88 sites in 25 countries worldwide. We show that aridity and plant traits are the major factors associated with the magnitude of plant effects on fertile islands in grazed drylands worldwide. Grazing pressure had little influence on the capacity of plants to support fertile islands. Taller and wider shrubs and grasses supported stronger island effects. Stable and functional soils tended to be linked to species-rich sites with taller plants. Together, our findings dispel the notion that grazing pressure or herbivore type are linked to the formation or intensification of fertile islands in drylands. Rather, our study suggests that changes in aridity, and processes that alter island identity and therefore plant traits, will have marked effects on how perennial plants support and maintain the functioning of drylands in a more arid and grazed world.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Average function for the 288 plots at 88 sites across global drylands and examples of fertile islands at selected sites.
Fig. 2: The fertile island effect, as measured with the RII, beneath perennial dryland plants for the 24 soil attributes measured across three functions.
Fig. 3: Impacts of recent grazing and climate on the fertile island effect.
Fig. 4: SEM assessing direct and indirect effects on the fertile island effect.

Similar content being viewed by others

Data availability

The data used for this study are available via Figshare67 at https://doi.org/10.6084/m9.figshare.25283074.v1. The other databases used in this study are: Global Aridity Index and Potential Evapotranspiration Climate Database v2 aridity database (https://cgiarcsi.community/2019/01/24/global-aridity-index-and-potential-evapotranspiration-climate-database-v2/), WorldClim version 2.0 (http://www.worldclim.org/), Woody Plants Database (http://woodyplants.cals.cornell.edu), TRY Database (https://www.try-db.org/TryWeb/Home.php), PLANTS Database (https://plants.usda.gov/) and BROT Database (https://www.uv.es/jgpausas/brot.htm). Source data are provided with this paper.

References

  1. Thiery, J. M., d’Herbes, J. M. & Valentin, C. A model simulating the genesis of banded vegetation patterns in Niger. J. Ecol. 459, 497–507 (1995).

    Article  Google Scholar 

  2. Aguiar, M. R. & Sala, O. E. Patch structure, dynamics and implications for the functioning of arid ecosystems. Trends Ecol. Evol. 14, 273–277 (1999).

    Article  CAS  PubMed  Google Scholar 

  3. Tongway, D. J. & Ludwig, J. A. Small-scale resource heterogeneity in semi-arid landscapes. Pac. Conserv. Biol. 1, 201 (1994).

    Article  Google Scholar 

  4. Ochoa‐Hueso, R. et al. Soil fungal abundance and plant functional traits drive fertile island formation in global drylands. J. Ecol. 106, 242–253 (2018).

    Article  Google Scholar 

  5. Alary, V., Lasseur, J., Frija, A. & Gautier, D. Assessing the sustainability of livestock socio-ecosystems in the drylands through a set of indicators. Agric. Syst. 198, 103389 (2022).

    Article  Google Scholar 

  6. Eldridge, D. J., Delgado‐Baquerizo, M., Travers, S. K., Val, J. & Oliver, I. Do grazing intensity and herbivore type affect soil health? Insights from a semi‐arid productivity gradient. J. Appl. Ecol. 54, 976–985 (2017).

    Article  Google Scholar 

  7. Middleton, N. Rangeland management and climate hazards in drylands: dust storms, desertification and the overgrazing debate. Nat. Hazards 92, 57–70 (2018).

    Article  Google Scholar 

  8. Ding, J. & Eldridge, D. J. The fertile island effect varies with aridity and plant patch type across an extensive continental gradient. Plant Soil 459, 1–11 (2020).

    Google Scholar 

  9. Cai, Y. et al. The fertile island effect collapses under extreme overgrazing: evidence from a shrub-encroached grassland. Plant Soil 448, 201–212 (2020).

    Article  CAS  Google Scholar 

  10. Pei, S., Fu, H., Wan, C., Chen, Y. & Sosebee, R. E. Observations on changes in soil properties in grazed and nongrazed areas of Alxa Desert Steppe, Inner Mongolia. Arid Land Res. Manag. 20, 161–175 (2006).

    Article  CAS  Google Scholar 

  11. Allington, G. R. & Valone, T. Islands of fertility: a byproduct of grazing? Ecosystems 17, 127–141 (2014).

    Article  Google Scholar 

  12. Maestre, F. T. et al. Grazing and ecosystem service delivery in global drylands. Science 378, 915–920 (2022).

    Article  CAS  PubMed  Google Scholar 

  13. Schade, J. D. & Hobbie, S. E. Spatial and temporal variation in islands of fertility in the Sonoran Desert. Biogeochemistry 73, 541–553 (2005).

    Article  Google Scholar 

  14. Ridolfi, L., Laio, F. & D’Odorico, P. Fertility island formation and evolution in dryland ecosystems. Ecol. Soc. 13, 5 (2008).

    Article  Google Scholar 

  15. Maestre, F. T. et al. Structure and functioning of dryland ecosystems in a changing world. Ann. Rev. Ecol. Evol. Syst. 47, 215–237 (2016).

    Article  Google Scholar 

  16. Charley, J. L. & West, N. E. Plant-induced soil chemical patterns in some shrub-dominated semi-desert ecosystems of Utah. J. Ecol. 63, 945–963 (1975).

    Article  CAS  Google Scholar 

  17. DeLuca, T. H. & Zackrisson, O. Enhanced soil fertility under Juniperus communis in arctic ecosystems. Plant Soil 294, 147–155 (2007).

    Article  CAS  Google Scholar 

  18. Whitford, W. G., Anderson, J. & Rice, P. M. Stemflow contribution to the ‘fertile island’ effect in creosotebush, Larrea tridentata. J. Arid Environ. 35, 451–457 (1997).

    Article  Google Scholar 

  19. Dunkerley, D. Systematic variation of soil infiltration rates within and between the components of the vegetation mosaic in an Australian desert landscape. Hydrol. Process. 16, 119–131 (2002).

    Article  Google Scholar 

  20. Ward, D. et al. Large shrubs increase soil nutrients in a semi-arid savanna. Geoderma 310, 153–162 (2018).

    Article  CAS  Google Scholar 

  21. Hollister, G. B. et al. Shifts in microbial community structure along an ecological gradient of hypersaline soils and sediments. ISME J. 4, 829–838 (2010).

    Article  CAS  PubMed  Google Scholar 

  22. Van Der Heijden, M. G., Bardgett, R. D. & Van Straalen, N. V. The unseen majority: soil microbes as drivers of plant diversity and productivity in terrestrial ecosystems. Ecol. Lett. 11, 296–310 (2008).

    Article  PubMed  Google Scholar 

  23. Berg, G. Plant–microbe interactions promoting plant growth and health: perspectives for controlled use of microorganisms in agriculture. Appl. Microbiol. Biotech. 84, 11–18 (2009).

    Article  CAS  Google Scholar 

  24. Dohn, J. et al. Tree effects on grass growth in savannas: competition, facilitation and the stress‐gradient hypothesis. J. Ecol. 101, 202–209 (2013).

    Article  Google Scholar 

  25. Lai, L. & Kumar, S. A global meta-analysis of livestock grazing impacts on soil properties. PLoS ONE 15, e0236638 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Schlesinger, W. H. et al. Biological feedbacks in global desertification. Science 247, 1043–1048 (1990).

    Article  CAS  PubMed  Google Scholar 

  27. Reynolds, J. F., Virginia, R. A., Kemp, P. R., De Soyza, A. G. & Tremmel, D. C. Impact of drought on desert shrubs: effects of seasonality and degree of resource island development. Ecol. Monogr. 69, 69–106 (1999).

    Article  Google Scholar 

  28. Funk, J. L. et al. Revisiting the Holy Grail: using plant functional traits to understand ecological processes. Biol. Rev. 92, 1156–1173 (2017).

    Article  PubMed  Google Scholar 

  29. Grace, J. B. Structural Equation Modeling and Natural Systems (Cambridge Univ. Press, 2006).

  30. Chen, S., Cao, R., Yoshitake, S. & Ohtsuka, T. Stemflow hydrology and DOM flux in relation to tree size and rainfall event characteristics. Agric. For. Meteorol. 279, 107753 (2019).

    Article  Google Scholar 

  31. Fischer, M. et al. Plant species richness and functional traits affect community stability after a flood event. Phil. Trans. R. Soc. B 371, 20150276 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  32. Verheyen, K. et al. Can complementarity in water use help to explain diversity–productivity relationships in experimental grassland plots? Oecologia 156, 351–361 (2008).

    Article  PubMed  Google Scholar 

  33. Hook, P. B., Burke, I. C. & Lauenroth, W. K. Heterogeneity of soil and plant N and C associated with individual plants and openings in North American shortgrass steppe. Plant Soil 138, 247–256 (1991).

    Article  CAS  Google Scholar 

  34. Ludwig, J. A., Wilcox, B. P., Breshears, D. D., Tongway, D. J. & Imeson, A. C. Vegetation patches and runoff—erosion as interacting ecohydrological processes in semiarid landscapes. Ecology 86, 288–297 (2005).

    Article  Google Scholar 

  35. Eldridge, D. J., Beecham, G. & Grace, J. B. Do shrubs reduce the adverse effects of grazing on soil properties? Ecohydrology 8, 1503–1513 (2015).

    Article  Google Scholar 

  36. Travers, S. K. & Berdugo, M. Grazing and productivity alter individual grass size dynamics in semi-arid woodlands. Ecography 43, 1003–1013 (2020).

    Article  Google Scholar 

  37. Piluzza, G., Sulas, L. & Bullitta, S. Tannins in forage plants and their role in animal husbandry and environmental sustainability: a review. Grass Forage Sci. 69, 32–48 (2014).

    Article  CAS  Google Scholar 

  38. De Soyza, A. G., Franco, A. C., Virginia, R. A., Reynolds, J. F. & Whitford, W. G. Effects of plant size on photosynthesis and water relations in the desert shrub Prosopis glandulosa (Fabaceae). Am. J. Bot. 83, 99–105 (1996).

    Article  Google Scholar 

  39. Dean, W. R. G., Milton, S. J. & Jeltsch, F. Large trees, fertile islands, and birds in arid savanna. J. Arid Environ. 41, 61–78 (1999).

    Article  Google Scholar 

  40. Gibb, H. Effects of planting method on the recovery of arboreal ant activity on revegetated farmland. Austral Ecol. 37, 789–799 (2012).

    Article  Google Scholar 

  41. Bolling, J. D. & Walker, L. R. Fertile island development around perennial shrubs across a Mojave Desert chronosequence. West. N. Am. Nat. 62, 88–100 (2002).

    Google Scholar 

  42. Tiedemann, A. R. & Klemmedson, J. O. Long-term effects of mesquite removal on soil characteristics: I: Nutrients and bulk density. Soil Sci. Soc. Am. J. 50, 472–475 (1986).

    Article  CAS  Google Scholar 

  43. Belsky, A. J., Mwonga, S. M. & Duxbury, J. M. Effects of widely spaced trees and livestock grazing on understory environments in tropical savannas. Agrofor. Syst. 24, 1–20 (1993).

    Article  Google Scholar 

  44. Maestre, F. T. et al. The BIODESERT survey: assessing the impacts of grazing on the structure and functioning of global drylands. Web Ecol. 22, 75–96 (2022).

    Article  Google Scholar 

  45. Turner, M. D. Long-term effects of daily grazing orbits on nutrient availability in Sahelian West Africa: I: Gradients in the chemical composition of rangeland soils and vegetation. J. Biogeogr. 25, 669–682 (1998).

    Article  Google Scholar 

  46. Rasmussen, H. B., Kahindi, O., Vollrath, F. & Douglas‐Hamilton, I. Estimating elephant densities from wells and droppings in dried out riverbeds. Afr. J. Ecol. 43, 312–319 (2005).

    Article  Google Scholar 

  47. Guerra Alonso, C., Zurita, G. & Bellocq, M. Response of dung beetle taxonomic and functional diversity to livestock grazing in an arid ecosystem. Ecol. Entomol. 46, 582–591 (2020).

    Article  Google Scholar 

  48. Dickinson, C. H., Underhay, V. S. H. & Ross, V. Effect of season, soil fauna and water content on the decomposition of cattle dung pats. New Phytol. 88, 129–141 (1981).

    Article  Google Scholar 

  49. Eldridge, D. J., Poore, A. G. B., Ruiz-Colmenero, M., Letnic, M. & Soliveres, S. Ecosystem structure, function and composition in rangelands are negatively affected by livestock grazing. Ecol. Appl. 36, 1273–1283 (2016).

    Article  Google Scholar 

  50. Travers, S. K., Eldridge, D. J., Koen, T. B., Val, J. & Oliver, I. Livestock and kangaroo grazing have little effect on biomass and fuel hazard in semi-arid woodlands. For. Ecol. Manag. 467, 118165 (2020).

    Article  Google Scholar 

  51. Goutte, C., Toft, P., Rostrup, E., Nielsen, F. A. & Hansen, L. K. On clustering fMRI time series. Neuroimage 9, 298–310 (1999).

    Article  CAS  PubMed  Google Scholar 

  52. Lange, R. T. The piosphere: sheep track and dung patterns. J. Range Manag. 22, 396–400 (1969).

    Article  Google Scholar 

  53. Pringle, H. J. R. & Landsberg, J. Predicting the distribution of livestock grazing pressure in rangelands. Austral Ecol. 29, 31–39 (2004).

    Article  Google Scholar 

  54. Tavşanoğlu, Ç. & Pausas, J. A functional trait database for Mediterranean Basin plants. Sci. Data 5, 180135 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  55. National Plant Data Team. The PLANTS Database (USDA, 2019).

  56. Kattge, J. et al. TRY—a global database of plant traits. Glob. Change Biol. 17, 2905–2935 (2011).

    Article  Google Scholar 

  57. Kettler, T. A., Doran, J. W. & Gilbert, T. L. Simplified method for soil particle-size determination to accompany soil-quality analyses. Soil Sci. Soc. Am. J. 65, 849–852 (2001).

    Article  CAS  Google Scholar 

  58. Armas, C., Ordiales, R. & Pugnaire, F. I. Measuring plant interactions: a new comparative index. Ecology 85, 2682–2686 (2004).

    Article  Google Scholar 

  59. R Core Team. R: a language and environment for statistical computing (R Foundation, 2018).

  60. Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1‐km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).

    Article  Google Scholar 

  61. Zomer, R. J., Xu, J. & Trabucco, A. Version 3 of the Global Aridity Index and Potential Evapotranspiration Database. Sci. Data 9, 409 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  62. Zhang, Y.-W., Wang, K.-B., Wang, J., Liu, C. & Shangguan, Z. P. Changes in soil water holding capacity and water availability following vegetation restoration on the Chinese Loess Plateau. Sci. Rep. 11, 9692 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Carpenter, B. et al. Stan: a probabilistic programming language. J. Stat. Softw. 76, 1–32 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  64. Goodrich, B., Gabry, J., Ali, I. & Brilleman, S. rstanarm: Bayesian applied regression modeling via Stan. R package version 2.21.1 https://mc-stan.org/rstanarm (R Foundation, 2020).

  65. McElreath, R. Statistical Rethinking 2nd edn (CRC, 2020).

  66. Archer E. rfPermute: estimate permutation P-values for random forest importance metrics. R package version 1. 5. 2 (R Foundation, 2016).

  67. Eldridge, D., Ding, J., Maestre, F. T. BIODESERT Fertile Island. Figshare https://doi.org/10.6084/m9.figshare.25283074.v1 (2024).

Download references

Acknowledgements

Funding: This research was supported by the European Research Council (ERC grant 647038 (BIODESERT) awarded to F.T.M.) and Generalitat Valenciana (CIDEGENT/2018/041). D.J.E. was supported by the Hermon Slade Foundation (HSF21040). J. Ding was supported by the National Natural Science Foundation of China Project (41991232) and the Fundamental Research Funds for the Central Universities of China. M.D.-B. acknowledges support from TED2021-130908B-C41/AEI/10.13039/501100011033/Unión Europea Next Generation EU/PRTR and the Spanish Ministry of Science and Innovation for the I + D + i project PID2020-115813RA-I00 funded by MCIN/AEI/10.13039/501100011033. O.S. was supported by US National Science Foundation (Grants DEB 1754106, 20-25166), and Y.L.B.-P. by a Marie Sklodowska-Curie Actions Individual Fellowship (MSCA-1018 IF) within the European Program Horizon 2020 (DRYFUN Project 656035). K.G. and N.B. acknowledge support from the German Federal Ministry of Education and Research (BMBF) SPACES projects OPTIMASS (FKZ: 01LL1302A) and ORYCS (FKZ: FKZ01LL1804A). B.B. was supported by the Taylor Family-Asia Foundation Endowed Chair in Ecology and Conservation Biology, and M. Bowker by funding from the School of Forestry, Northern Arizona University. C.B. acknowledges funding from the National Natural Science Foundation of China (41971131). D.B. acknowledges support from the Hungarian Research, Development and Innovation Office (NKFI KKP 144096), and A. Fajardo support from ANID PIA/BASAL FB 210006 and the Millennium Science Initiative Program NCN2021-050. M.F. and H.E. received funding from Ferdowsi University of Mashhad (grant 39843). A.N. and M.K. acknowledge support from FCT (CEECIND/02453/2018/CP1534/CT0001, SFRH/BD/130274/2017, PTDC/ASP-SIL/7743/2020, UIDB/00329/2020), EEA (10/CALL#5), AdaptForGrazing (PRR-C05-i03-I-000035) and LTsER Montado platform (LTER_EU_PT_001) grants. O.V. acknowledges support from the Hungarian Research, Development and Innovation Office (NKFI KKP 144096). L.W. was supported by the US National Science Foundation (EAR 1554894). Y.Z. and X.Z. were supported by the National Natural Science Foundation of China (U2003214). H.S. is supported by a María Zambrano fellowship funded by the Ministry of Universities and European Union-Next Generation plan. The use of any trade, firm or product names does not imply endorsement by any agency, institution or government. Finally, we thank the many people who assisted with field work and the landowners, corporations and national bodies that allowed us access to their land.

Author information

Authors and Affiliations

Authors

Contributions

F.T.M. designed and coordinated the field survey. D.J.E. and J. Ding conceived the study. J. Dorrough undertook the Bayesian analyses, M.M-C. drafted the figures and J. Ding produced the map. Laboratory analyses were performed by V.O., B.G., B.J.M., S.A., A.R., P.D.-M., C.P., N.E., M.C.R., S.C. and M.D.-B. The other authors collected and managed the collection of field data. D.J.E. and J. Ding wrote the draft paper in collaboration with F.T.M. and O.S. and with contributions from all authors.

Corresponding author

Correspondence to Jingyi Ding.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Plants thanks the anonymous reviewers for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Tables 1–3, Supplementary Figs. 1–8, Supplementary Texts 1–3 and Supplementary References.

Reporting Summary

Source data

Source Data Fig. 1

Source data for Fig. 1.

Source Data Fig. 2

Source data for Fig. 2.

Source Data Fig. 3

Source data for Fig. 3.

Source Data Fig. 4

Source data for Fig. 4.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Eldridge, D.J., Ding, J., Dorrough, J. et al. Hotspots of biogeochemical activity linked to aridity and plant traits across global drylands. Nat. Plants (2024). https://doi.org/10.1038/s41477-024-01670-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41477-024-01670-7

Search

Quick links

Nature Briefing Microbiology

Sign up for the Nature Briefing: Microbiology newsletter — what matters in microbiology research, free to your inbox weekly.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing: Microbiology