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.

Advertisement

Scientific Reports
  • View all journals
  • Search
  • My Account Login
  • Content Explore content
  • About the journal
  • Publish with us
  • Sign up for alerts
  • RSS feed
  1. nature
  2. scientific reports
  3. articles
  4. article
Land surface phenometrics and their responses to climatic variables in the semi-arid rangelands of the central Zagros mountains
Download PDF
Download PDF
  • Article
  • Open access
  • Published: 09 February 2026

Land surface phenometrics and their responses to climatic variables in the semi-arid rangelands of the central Zagros mountains

  • Fatemeh Pordel1,5,
  • Reza Jafari1,
  • Mostafa Tarkesh Esfahani1,
  • Mohsen Ahmadi1,
  • Geoffrey M. Henebry2,3,
  • Ataollah Ebrahimi4,
  • Adrià Descals5,6 &
  • …
  • Josep Penuelas5,6 

Scientific Reports , Article number:  (2026) Cite this article

  • 2071 Accesses

  • Metrics details

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Climate sciences
  • Ecology
  • Environmental sciences

Abstract

As climate change accelerates, phenological shifts in vulnerable semi-arid ecosystems remain poorly understood yet are of increasingly critical. Identifying the phenological stages of rangeland ecosystems, and quantifying how climate change affects each stage over time, is essential for effective rangeland management. This study aimed to investigate the long-term trends in land surface phenology (LSP) and the impact of climate variations on LSP in the semi-arid rangelands of Chaharmahal-Va-Bakhtiari (CVB) Province, Iran, from 2000 to 2023. Utilizing satellite data from MODIS NDVI, key LSP metrics were analyzed, including the start of the growing season (SOS), peak of the growing season (POS), end of the growing season (EOS), length of the growing season (LOS), and maximum vegetation greenness (maxNDVI). The findings indicate significant shifts: SOS, POS and EOS are occurring earlier, resulting in shorter growing season in many regions. These changes show strong correlations with climatic variables such as precipitation, temperature, and potential evapotranspiration, with temperature exhibiting the most significant relationship to changes in SOS. The Sen’s slope trend analysis showed that 25.74% of the study area experienced advancements in SOS, 23.2% % in POS, and 32.3% in EOS. Additionally, LOS has decreased in 70% of pixels with significant change. This study demonstrates that phenological patterns in the semi-arid rangelands of CVB are shifting in response to climate change. These findings highlight the need to implement adaptive management strategies to maintain the sustainability of these fragile ecosystems.

Data availability

The datasets generated during the current study are available from the corresponding author on reasonable request.

References

  1. De Beurs, K. M., Driscoll, E. & Henebry, G. M. Land surface phenology in global change studies. In Phenology: an Integrative Environmental Science (ed. Schwartz, M. D.) 505–529 (Springer Nature Switzerland, 2024).

    Google Scholar 

  2. Henebry, G. M. & De Beurs, K. M. In Phenology: An Integrative Environmental Science. 385–411 (eds Schwartz, M. D.) (Springer Netherlands, 2013).

  3. Wang, L., She, D., Xia, J., Meng, L. & Li, L. Revegetation affects the response of land surface phenology to climate in loess Plateau, China. Sci. Total Environ. 860, 160383. https://doi.org/10.1016/j.scitotenv.2022.160383 (2023).

    Google Scholar 

  4. Peñuelas, J., Filella, I. & Phenology Responses to a warming world. Science 294, 793–795. https://doi.org/10.1126/science.1066860 (2001).

    Google Scholar 

  5. Gong, Z., Ge, W., Guo, J. & Liu, J. Satellite remote sensing of vegetation phenology: Progress, challenges, and opportunities. ISPRS J. Photogrammetry Remote Sens. 217, 149–164. https://doi.org/10.1016/j.isprsjprs.2024.08.011 (2024).

    Google Scholar 

  6. Cleland, E. E., Chuine, I., Menzel, A., Mooney, H. A. & Schwartz, M. D. Shifting plant phenology in response to global change. Trends Ecol. Evol. 22, 357–365. https://doi.org/10.1016/j.tree.2007.04.003 (2007).

    Google Scholar 

  7. Shen, M. et al. Can changes in autumn phenology facilitate earlier green-up date of Northern vegetation? Agric. For. Meteorol. 291, 108077. https://doi.org/10.1016/j.agrformet.2020.108077 (2020).

    Google Scholar 

  8. Bellini, E. et al. Impacts of climate change on European grassland phenology: A 20-Year analysis of MODIS satellite data. Remote Sens. 15, 218. https://doi.org/10.3390/rs15010218 (2023).

    Google Scholar 

  9. Garonna, I., de Jong, R. & Schaepman, M. E. Variability and evolution of global land surface phenology over the past three decades (1982–2012). Glob. Change Biol. 22, 1456–1468. https://doi.org/10.1111/gcb.13168 (2016).

    Google Scholar 

  10. Song, X., Liao, J., Zhang, S. & Du, H. Land surface phenology response to climate in semi-arid desertified areas of Northern China. Land 14, 594 (2025).

    Google Scholar 

  11. Dong, T. et al. Seasonal scale climatic factors on grassland phenology in arid and Semi-Arid zones. Land 13, 653 (2024).

    Google Scholar 

  12. Araghi, A., Martinez, C. J., Adamowski, J. & Olesen, J. E. Associations between large-scale climate oscillations and land surface phenology in Iran. Agric. For. Meteorol. 278, 107682. https://doi.org/10.1016/j.agrformet.2019.107682 (2019).

    Google Scholar 

  13. Sharif, M. & Attarchi, S. Investigating the effect of temperature, precipitation, and soil salinity changes on riparian forests’ phenology using a remote sensing approach. Remote Sens. Applications: Soc. Environ. 34, 101194. https://doi.org/10.1016/j.rsase.2024.101194 (2024).

    Google Scholar 

  14. Kiapasha, K. et al. Trends in phenological parameters and relationship between land surface phenology and climate data in the hyrcanian forests of Iran. IEEE J. Sel. Top. Appl. Earth Observations Remote Sens. 10, 4961–4970. https://doi.org/10.1109/JSTARS.2017.2736938 (2017).

    Google Scholar 

  15. Wu, W. et al. Developing global annual land surface phenology datasets (1982–2018) from the AVHRR data using multiple phenology retrieval methods. Ecol. Ind. 150, 110262. https://doi.org/10.1016/j.ecolind.2023.110262 (2023).

    Google Scholar 

  16. Fatemi, S. S., Rahimi, M. & Bernardi, M. The most important Climatic factors affecting distribution of zygophyllum atriplicoides in semi-arid region of Iran (Case study: Isfahan Province). Desert 20, 145–156 (2015).

    Google Scholar 

  17. Caparros-Santiago, J. A., Rodriguez-Galiano, V. & Dash, J. Land surface phenology as indicator of global terrestrial ecosystem dynamics: A systematic review. ISPRS J. Photogrammetry Remote Sens. 171, 330–347. https://doi.org/10.1016/j.isprsjprs.2020.11.019 (2021).

    Google Scholar 

  18. Zhu, W., Chen, G., Jiang, N., Liu, J. & Mou, M. Estimating carbon flux phenology with Satellite-Derived land surface phenology and climate drivers for different biomes: A synthesis of AmeriFlux observations. PLOS ONE. 8, e84990. https://doi.org/10.1371/journal.pone.0084990 (2013).

    Google Scholar 

  19. Bolton, D. K. et al. Continental-scale land surface phenology from harmonized Landsat 8 and Sentinel-2 imagery. Remote Sens. Environ. 240, 111685. https://doi.org/10.1016/j.rse.2020.111685 (2020).

    Google Scholar 

  20. White, M. A. et al. Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982–2006. Glob. Change Biol. 15, 2335 (2009).

    Google Scholar 

  21. Alimoradi, S., Khoorani, A. & Esmaeilpour, Y. Dynamics of vegetation cover in relation to temperature and precipitation in the rangelands of the Karun Basin, Khuzestan Province. Appl. Res. Geogr. Sci. 17, 211–277 (2017).

    Google Scholar 

  22. Xie, Q. et al. Land surface phenology retrievals for arid and semi-arid ecosystems. ISPRS J. Photogrammetry Remote Sens. 185, 129–145. https://doi.org/10.1016/j.isprsjprs.2022.01.017 (2022).

    Google Scholar 

  23. Moon, M. et al. Long-term continuity in land surface phenology measurements: A comparative assessment of the MODIS land cover dynamics and VIIRS land surface phenology products. Remote Sens. Environ. 226, 74–92. https://doi.org/10.1016/j.rse.2019.03.034 (2019).

    Google Scholar 

  24. Tucker, C. J. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens. Environ. 8, 127–150. https://doi.org/10.1016/0034-4257(79)90013-0 (1979).

    Google Scholar 

  25. Tong, X. et al. Trends of land surface phenology derived from passive microwave and optical remote sensing systems and associated drivers across the dry tropics 1992–2012. Remote Sens. Environ. 232, 111307. https://doi.org/10.1016/j.rse.2019.111307 (2019).

    Google Scholar 

  26. UNESCO. Islamic Republic of Iran, U. N. E., Scientific and Cultural Organization (Directory of the World Network of Biosphere Reserves, 2015).

  27. Ghasemi, S., Malekian, M., Tarkesh, M. & Rezvani, A. Climate change alters future distribution of mountain plants, a case study of astragalus adscendens in Iran. Plant Ecol. 223, 1275–1288. https://doi.org/10.1007/s11258-022-01273-2 (2022).

    Google Scholar 

  28. Rezvani, A., Lorestani, N., Nematollahi, S., Hemami, M. R. & Ahmadi, M. Should I stay or move? Quantifying landscape of fear to enhance environmental management of road networks in a highly transformed landscape. J. Environ. Manag. 368, 122192. https://doi.org/10.1016/j.jenvman.2024.122192 (2024).

    Google Scholar 

  29. Soltani, S., Yaghmaei, L., Khodagholi, M. & Saboohi, R. Bioclimatic classification of Chahar-Mahal & Bakhtiari Province using multivariate statistical methods. J. Water Soil. Sci. 14, 53–68 (2011).

    Google Scholar 

  30. Piao, S. et al. Detection and attribution of vegetation greening trend in China over the last 30 years. Glob. Change Biol. 21, 1601–1609. https://doi.org/10.1111/gcb.12795 (2015).

    Google Scholar 

  31. Zhang, X. et al. Generation and evaluation of the VIIRS land surface phenology product. Remote Sens. Environ. 216, 212–229. https://doi.org/10.1016/j.rse.2018.06.047 (2018).

    Google Scholar 

  32. Eklundh, L. & Jonsson, P. G. in Image and Signal Processing for Remote Sensing VIII. (ed Sebastiano B. Serpico) 215–225.

  33. Padhee, S. K. & Dutta, S. Spatio-Temporal reconstruction of MODIS NDVI by regional land surface phenology and harmonic analysis of Time-Series. GIScience Remote Sens. 56, 1261–1288. https://doi.org/10.1080/15481603.2019.1646977 (2019).

    Google Scholar 

  34. Hird, J. N. & McDermid, G. J. Noise reduction of NDVI time series: an empirical comparison of selected techniques. Remote Sens. Environ. 113, 248–258. https://doi.org/10.1016/j.rse.2008.09.003 (2009).

    Google Scholar 

  35. De Beurs, K. M. & Henebry, G. M. in In Phenological Research. 177–208 (eds Hudson, I. L., Marie, R. & Keatley) (Springer Netherlands, 2010).

  36. Forkel, M. & Wutzler, T. Greenbrown: land surface phenology and trend analysis. A package for the R software. Version 2.2. (2015).

  37. Kendall, M. G. Rank correlation methods. 4th, 2d impression edn, viii, 202 pages : illustrations ; 24 cmGriffin, (1975).

  38. Sen, P. K. Estimates of the regression coefficient based on kendall’s Tau. J. Am. Stat. Assoc. 63, 1379–1389. https://doi.org/10.2307/2285891 (1968).

    Google Scholar 

  39. Xu, W., Hou, Y., Hung, Y. S. & Zou, Y. A comparative analysis of spearman’s Rho and kendall’s Tau in normal and contaminated normal models. Sig. Process. 93, 261–276. https://doi.org/10.1016/j.sigpro.2012.08.005 (2013).

    Google Scholar 

  40. Kruskal, W. H. & Wallis, W. A. Use of ranks in One-Criterion variance analysis. J. Am. Stat. Assoc. 47, 583–621 (1952).

    Google Scholar 

  41. Masoudi, M., Asrari, E., Younesfard, A. R. & Haghighi, A. T. Spatial and statistical analysis of climate change in the middle east: A study of precipitation and temperature variability using NOAA weather data and Geostatistical methods. Earth Syst. Environ. https://doi.org/10.1007/s41748-025-00802-z (2025).

    Google Scholar 

  42. Barnard, D. M., Barnard, H. R. & Molotch, N. P. Topoclimate effects on growing season length and montane conifer growth in complex terrain. Environ. Res. Lett. 12, 064003 (2017).

    Google Scholar 

  43. Tomaszewska, M. A., Nguyen, L. H. & Henebry, G. M. Land surface phenology in the Highland pastures of montane central asia: interactions with snow cover seasonality and terrain characteristics. Remote Sens. Environ. 240, 111675. https://doi.org/10.1016/j.rse.2020.111675 (2020).

    Google Scholar 

  44. Mozaffarian, V. Flora of Chahar and Bakhtiari 1 edn (Isfahan- Memar khane Baghnazar, 2017).

  45. Pordel, F., Ebrahimi, A. & Azizi, Z. Evaluating spatio-temporal phytomass changes using vegetation index derived from Landsat 8 (Case study: Mrajan rangeland, Boroujen). Rangeland 11, 166–178 (2017).

    Google Scholar 

  46. Thompson, J. A. & Paull, D. J. Assessing Spatial and Temporal patterns in land surface phenology for the Australian alps (2000–2014). Remote Sens. Environ. 199, 1–13. https://doi.org/10.1016/j.rse.2017.06.032 (2017).

    Google Scholar 

  47. Ipcc Climate Change 2022: Impacts, Adaptation and Vulnerability. Chapter 10: Asia (IPCC, 2022).

  48. Pan, Y. et al. Climate-driven land surface phenology advance is overestimated due to ignoring land cover changes. Environ. Res. Lett. 18, 044045. https://doi.org/10.1088/1748-9326/acca34 (2023).

    Google Scholar 

  49. Mohammadian, A., borujeni, E. A., Ebrahimi, A., Tahmasebi, Naghipour, A. A. & p. & The combined effect of fire period and grazing intensity on plant species diversity indices in the semi-steppe rangeland of Chaharmahal and Bakhtiari Province. Iran. J. Range Desert Res. 21, 84–97 (2020).

    Google Scholar 

  50. Omidipour, R., Tahmasebi, P., Ebrahimi, A. & Nadaf, M. Investigating the effect of animal grazing management on composition and Spatial diversity indices (Case study: Broujen Rangelands, Charmahal and Bakhtiari). Integr. Watershed Manage. J. 1, 63–79 (2021).

    Google Scholar 

  51. Heidari Ghahfarrokhi, Z., Ebrahimi, A., Pordanjani, H. A., Asadi, E. & Shirmardi, H. A. Effects of livestock grazing on vegetation and soil properties in rangelands: A case study of Farsan – Chaharmahal Va Bakhtiari Province. Joournal Rangeland 17 (2024).

  52. Qader, S. H., Priyatikanto, R., Khwarahm, N. & Tatem, A. Characterising the land surface phenology of middle Eastern countries using moderate resolution Landsat data. (2022).

  53. Khormizi, H. Z., Malamiri, H. R. G., Kalantari, Z. & Ferreira, C. S. S. Trend of changes in phenological components of iran’s vegetation using satellite observations. Remote Sens. 15, 1–21. https://doi.org/10.3390/rs15184468 (2023).

    Google Scholar 

  54. Vogel, J. Drivers of phenological changes in Southern Europe. Int. J. Biometeorol. 66, 1903–1914. https://doi.org/10.1007/s00484-022-02331-0 (2022).

    Google Scholar 

  55. Mirgol, B. et al. Interplay among recent trends in climate Extremes, vegetation Phenology, and crop production in the Southern mediterranean region. Int. J. Climatol. 45, e8768. https://doi.org/10.1002/joc.8768 (2025).

    Google Scholar 

  56. Wipf, S., Stoeckli, V. & Bebi, P. Winter climate change in alpine tundra: plant responses to changes in snow depth and snowmelt timing. Clim. Change. 94, 105–121. https://doi.org/10.1007/s10584-009-9546-x (2009).

    Google Scholar 

  57. An, S., Zhang, X. & Ren, S. Spatial difference between temperature and snowfall driven spring phenology of alpine grassland land surface based on Process-Based modeling on the Qinghai–Tibet plateau. Remote Sens. 14, 1273 (2022).

    Google Scholar 

  58. Liu, Y., Zhou, W., Gao, S., Ma, X. & Yan, K. Phenological responses to snow seasonality in the Qilian mountains is a function of both elevation and vegetation types. Remote Sens. 14, 3629 (2022).

    Google Scholar 

  59. Garonna, I. et al. Shifting relative importance of Climatic constraints on land surface phenology. Environ. Res. Lett. 13, 024025. https://doi.org/10.1088/1748-9326/aaa17b (2018).

    Google Scholar 

  60. Zhumanova, M., Wrage-Mönnig, N. & Jurasinski, G. Long-term vegetation change in the Western Tien-Shan mountain pastures, central Asia, driven by a combination of changing precipitation patterns and grazing pressure. Sci. Total Environ. 781, 146720. https://doi.org/10.1016/j.scitotenv.2021.146720 (2021).

    Google Scholar 

  61. Dronova, I. & Taddeo, S. Remote sensing of phenology: towards the comprehensive indicators of plant community dynamics from species to regional scales. J. Ecol. 110, 1460–1484. https://doi.org/10.1111/1365-2745.13897 (2022).

    Google Scholar 

  62. Iwanycki Ahlstrand, N., Primack, R. B. & Tøttrup, A. P. A comparison of herbarium and citizen science phenology datasets for detecting response of flowering time to climate change in Denmark. Int. J. Biometeorol. 66, 849–862. https://doi.org/10.1007/s00484-022-02238-w (2022).

    Google Scholar 

  63. Eyshi Rezaei, E., Siebert, S. & Ewert, F. Climate and management interaction cause diverse crop phenology trends. Agric. For. Meteorol. 233, 55–70. https://doi.org/10.1016/j.agrformet.2016.11.003 (2017).

    Google Scholar 

  64. Park, D. S., Newman, E. A. & Breckheimer, I. K. Scale gaps in landscape phenology: challenges and opportunities. Trends Ecol. Evol. 36, 709–721. https://doi.org/10.1016/j.tree.2021.04.008 (2021).

    Google Scholar 

Download references

Acknowledgements

We would like to thank the Department of Natural Resources of Iran, the Global Ecology Unit at CREAF-CSIC-UAB, Barcelona, and the Center for Global Change and Earth Observations at Michigan State University.

Funding

The authors received no financial support for the research, authorship, and publication of this article.

Author information

Authors and Affiliations

  1. Department of Natural Resources, Isfahan University of Technology, Isfahan, 8415683111, Iran

    Fatemeh Pordel, Reza Jafari, Mostafa Tarkesh Esfahani & Mohsen Ahmadi

  2. Department of Geography, Environment, and Spatial Sciences, Michigan State University, East Lansing, MI, 48824, USA

    Geoffrey M. Henebry

  3. Center for Global Change and Earth Observations, Michigan State University, East Lansing, MI, 48823, USA

    Geoffrey M. Henebry

  4. Faculty of Natural Resources and Earth Sciences, Shahrekord University, Chaharmahal va Bakhtiari, Iran

    Ataollah Ebrahimi

  5. Global Ecology Unit CREAF-CSIC-UAB, CSIC, Barcelona, Spain

    Fatemeh Pordel, Adrià Descals & Josep Penuelas

  6. CREAF, Cerdanyola del Vallès, Barcelona, Spain

    Adrià Descals & Josep Penuelas

Authors
  1. Fatemeh Pordel
    View author publications

    Search author on:PubMed Google Scholar

  2. Reza Jafari
    View author publications

    Search author on:PubMed Google Scholar

  3. Mostafa Tarkesh Esfahani
    View author publications

    Search author on:PubMed Google Scholar

  4. Mohsen Ahmadi
    View author publications

    Search author on:PubMed Google Scholar

  5. Geoffrey M. Henebry
    View author publications

    Search author on:PubMed Google Scholar

  6. Ataollah Ebrahimi
    View author publications

    Search author on:PubMed Google Scholar

  7. Adrià Descals
    View author publications

    Search author on:PubMed Google Scholar

  8. Josep Penuelas
    View author publications

    Search author on:PubMed Google Scholar

Contributions

A: Fatemeh Pordel: Data curation, methodology, writing original draft, software analysis, data validationA: Reza Jafari: Writing, reviewing and editingA: Mostafa Tarkesh Esfahani: ModellingA: Mohsen Ahmadi: ModellingB.C: Geoffrey M. Henebry: Writing, reviewing and editingD: Ataollah Ebrahimi : ModellingE.F: Adrià Descals: ModellingE.F: Josep Penuelas: Writing, reviewing and editing All authors reviewed the manuscript.

Corresponding author

Correspondence to Reza Jafari.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

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

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pordel, F., Jafari, R., Esfahani, M.T. et al. Land surface phenometrics and their responses to climatic variables in the semi-arid rangelands of the central Zagros mountains. Sci Rep (2026). https://doi.org/10.1038/s41598-026-38652-y

Download citation

  • Received: 24 July 2025

  • Accepted: 30 January 2026

  • Published: 09 February 2026

  • DOI: https://doi.org/10.1038/s41598-026-38652-y

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Keywords

  • Rangeland phenology
  • MODIS NDVI
  • Phenological metrics
  • LSP trend
Download PDF

Advertisement

Explore content

  • Research articles
  • News & Comment
  • Collections
  • Subjects
  • Follow us on Facebook
  • Follow us on X
  • Sign up for alerts
  • RSS feed

About the journal

  • About Scientific Reports
  • Contact
  • Journal policies
  • Guide to referees
  • Calls for Papers
  • Editor's Choice
  • Journal highlights
  • Open Access Fees and Funding

Publish with us

  • For authors
  • Language editing services
  • Open access funding
  • Submit manuscript

Search

Advanced search

Quick links

  • Explore articles by subject
  • Find a job
  • Guide to authors
  • Editorial policies

Scientific Reports (Sci Rep)

ISSN 2045-2322 (online)

nature.com sitemap

About Nature Portfolio

  • About us
  • Press releases
  • Press office
  • Contact us

Discover content

  • Journals A-Z
  • Articles by subject
  • protocols.io
  • Nature Index

Publishing policies

  • Nature portfolio policies
  • Open access

Author & Researcher services

  • Reprints & permissions
  • Research data
  • Language editing
  • Scientific editing
  • Nature Masterclasses
  • Research Solutions

Libraries & institutions

  • Librarian service & tools
  • Librarian portal
  • Open research
  • Recommend to library

Advertising & partnerships

  • Advertising
  • Partnerships & Services
  • Media kits
  • Branded content

Professional development

  • Nature Awards
  • Nature Careers
  • Nature Conferences

Regional websites

  • Nature Africa
  • Nature China
  • Nature India
  • Nature Japan
  • Nature Middle East
  • Privacy Policy
  • Use of cookies
  • Legal notice
  • Accessibility statement
  • Terms & Conditions
  • Your US state privacy rights
Springer Nature

© 2026 Springer Nature Limited

Nature Briefing Anthropocene

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

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