in

Incorporating river morphodynamics in the characterization of key ecological system units for conservation in the western Amazon


Abstract

This study presents a novel methodology for developing a conservation Blueprint in the western Amazon, focusing on the Marañón, Napo, and Ucayali basins. Our approach highlights the critical role of fluvial integrity in shaping ecological functions and biodiversity through floodplain reshaping, habitat interconnecting across forests, and the transport and distribution of sediments, nutrients, and minerals throughout the region. We introduced two ecological attributes, the Modern Morphodynamics Index (MOR) and the Suspended Sediment Index (SSI), which together provide an improved representation of the temporal dynamics and connectivity that rivers impart to the landscape, as well as their influence on biotic dynamics. Our methodology integrates quantification and classification of biotic (five taxa) and abiotic variables across spatially nested hierarchies to assess ecological conditions and human-induced pressure. The resulting Ecological System (ES) units prioritizes areas with high ecological condition scores (i.e., high integrity) and low anthropogenic impact, enabling the development of more targeted conservation strategies. Our findings underscore (1) the value of incorporating MOR and SSI, which identify regions characterized by high dynamism and substantial sediment and nutrient loads as major drivers of biotic patterns; and (2) the urgent need for expanded species diversity surveys to better understand spatiotemporal distribution patterns across these complex river systems. Overall, this comprehensive framework offers a robust foundation for informing conservation planning and infrastructure development, supporting the long-term sustainable management of these critical Amazonian ecosystems.

Similar content being viewed by others

The role of rivers in the origin and future of Amazonian biodiversity

Hydropower impacts on riverine biodiversity

Identifying controlling factors of delta morphology using a convolutional autoencoder

Data availability

Data is provided within the manuscript and supplementary information file.

References

  1. Jézéquel, C., Oberdorff, T., Tedesco, P. A. & Schmitt, L. Geomorphological diversity of rivers in the Amazon Basin. Geomorphology 400, 108078. https://doi.org/10.1016/j.geomorph.2021.108078 (2022).

    Google Scholar 

  2. Caldas, B. et al. Identifying the current and future status of freshwater connectivity corridors in the Amazon Basin. Conserv. Sci. Pract. 5(1), e12853. https://doi.org/10.1111/csp2.12853 (2023).

    Google Scholar 

  3. Oberdorff, T. et al. Unexpected fish diversity gradients in the Amazon basin. Sci. Adv. 5(9), eaav8681. https://doi.org/10.1126/sciadv.aav8681 (2019).

    Google Scholar 

  4. Rojas, T. V., Abad, J. D., Roque, W. R., Latrubesse, E. M. & Shan, J. Free and underfit-scavenger river dynamics dominate the large Amazonian Pacaya-Samiria wetland structure. Front. Environ. Sci. 11, 1082619. https://doi.org/10.3389/fenvs.2023.1082619 (2023).

    Google Scholar 

  5. Boschman, L. M. et al. Freshwater fish diversity in the western Amazon basin shaped by Andean uplift since the Late Cretaceous. Nat. Ecol. Evolut. https://doi.org/10.1038/s41559-023-02220-8 (2023).

    Google Scholar 

  6. Cassemiro, F. A. et al. Landscape dynamics and diversification of the megadiverse South American freshwater fish fauna. Proc. Natl. Acad. Sci. 120(2), e2211974120. https://doi.org/10.1073/pnas.2211974120 (2023).

    Google Scholar 

  7. Abell, R. et al. Freshwater ecoregions of the world: A new map of biogeographic units for freshwater biodiversity conservation. Bioscience 58(5), 403–414. https://doi.org/10.1641/B580507 (2008).

    Google Scholar 

  8. Groves, C. R., Hunter, M. L., Groves, C., Hunter, M., & Staff, N. C. Drafting a conservation blueprint: A practitioner’s guide to planning for biodiversity (Island Press, 2003).

  9. Junk, W. J., Bayley, P. B. and Sparks, R. E. The flood pulse concept in river-floodplain systems. In (ed Dodge, D. P.). Proceedings of the International Large River Symposium. Canadian Journal of Fisheries and Aquatic Sciences 106. 110–127 (Department of Fisheries and Oceans, 1989).

  10. Baker, J. C. A. et al. The changing Amazon hydrological cycle—Inferences from over 200 years of tree-ring oxygen isotope data. J. Geophys. Res. Biogeosci. 127, e2022JG006955. https://doi.org/10.1029/2022JG006955 (2022).

    Google Scholar 

  11. Melack, J. M. & Hess, L. L. Remote sensing of the distribution and extent of wetlands in the Amazon Basin. In Amazonian Floodplain Forests. Ecological Studies Vol. 210 (eds Junk, W. et al.) (Springer, 2010). https://doi.org/10.1007/978-90-481-8725-6_3.

    Google Scholar 

  12. Barthem, R. B. et al. Goliath catfish spawning in the far western Amazon confirmed by the distribution of mature adults, drifting larvae and migrating juveniles. Sci. Rep. 7, 41784 (2017).

    Google Scholar 

  13. Arantes, C. C. et al. Floodplain land cover affects biomass distribution of fish functional diversity in the Amazon River. Sci. Rep. 9(1), 16684. https://doi.org/10.1038/s41598-019-52243-0 (2019).

    Google Scholar 

  14. Anderson, E. P. et al. Fragmentation of Andes-to-Amazon connectivity by hydropower dams. Sci. Adv. 4(1), eaao1642. https://doi.org/10.1126/sciadv.aao1642 (2018).

    Google Scholar 

  15. Latrubesse, E. M. et al. Vulnerability of the biota in riverine and seasonally flooded habitats to damming of Amazonian rivers. Aquat. Conserv. Mar. Freshw. Ecosyst. 31(5), 1136–1149. https://doi.org/10.1002/aqc.3424 (2021).

    Google Scholar 

  16. Antunes, A. C. et al. AMAZONIA CAMTRAP: A data set of mammal, bird, and reptile species recorded with camera traps in the Amazon forest. https://doi.org/10.1002/ecy.3738 (2022).

  17. Miqueleiz, I. et al. Ecoregional distributions of the world’s freshwater vertebrate species. Sci. Data 12, 1286. https://doi.org/10.1038/s41597-025-05622-4 (2025).

    Google Scholar 

  18. Grill, G. et al. Mapping the world’s free-flowing rivers. Nature 569(7755), 215–221. https://doi.org/10.1038/s41586-019-1111-9 (2019).

    Google Scholar 

  19. Armijos, E. et al. Suspended sediment dynamics in the Amazon River of Peru. J. South Am. Earth Sci. 44, 75–84. https://doi.org/10.1016/j.jsames.2012.09.002 (2013).

    Google Scholar 

  20. Constantine, J. A., Dunne, T., Ahmed, J., Legleiter, C. & Lazarus, E. D. Sediment supply as a driver of river meandering and floodplain evolution in the Amazon Basin. Nat. Geosci. 7(12), 899–903. https://doi.org/10.1038/ngeo2282 (2014).

    Google Scholar 

  21. Castello, L. et al. The vulnerability of Amazon freshwater ecosystems. Conserv. Lett. https://doi.org/10.1111/conl.12008 (2013).

    Google Scholar 

  22. Marin, F. R. et al. Protecting the Amazon forest and reducing global warming via agricultural intensification. Nat. Sustain. 5(12), 1018–1026. https://doi.org/10.1038/s41893-022-00968-8 (2022).

    Google Scholar 

  23. Boulton, C. A., Lenton, T. M. & Boers, N. Pronounced loss of Amazon rainforest resilience since the early 2000s. Nat. Clim. Chang. 12(3), 271–278. https://doi.org/10.1038/s41558-022-01287-8 (2022).

    Google Scholar 

  24. Sonter, L. J. et al. Mining drives extensive deforestation in the Brazilian Amazon. Nat. Commun. 8(1), 1013. https://doi.org/10.1038/s41467-017-00557-w (2017).

    Google Scholar 

  25. Abad, J., Rojas, T., Anampa, L. y Chicchón, H. Minería Ilegal en Áreas Clave para la Biodiversidad y zonas prioritarias para la conservación en la Amazonía Peruana. Conservación Amazónica – ACCA. Accessed November 12, 2025, https://acca.org.pe/wp-content/uploads/2025/08/Mineria-ilegal-en-zonas-prioritarias-para-la-conservacion-en-la-Amazonia-peruana.pdf (2025a).

  26. Feng, X. et al. How deregulation, drought and increasing fire impact Amazonian biodiversity. Nature 597(7877), 516–521. https://doi.org/10.1038/s41586-021-03876-7 (2021).

    Google Scholar 

  27. Arellano, P., Tansey, K., Balzter, H. & Boyd, D. S. Detecting the effects of hydrocarbon pollution in the Amazon forest using hyperspectral satellite images. Environ. Pollut. 205, 225–239. https://doi.org/10.1016/j.envpol.2015.05.041 (2015).

    Google Scholar 

  28. Rosell-Melé, A. et al. Oil pollution in soils and sediments from the Northern Peruvian Amazon. The Science of the total environment. 610–611. 1010–1019. https://doi.org/10.1016/j.scitotenv.2017.07.208 (2017).

  29. Valverde, H., Abad, J. D., Guerrero, L., Estrada, Y. & Frias, C. Hydrogeomorphic characterization of the Huallaga River for the Peruvian Amazon Waterway. J. Waterway Port Coastal Ocean Eng. https://doi.org/10.1061/JWPED5.WWENG-2021 (2024).

    Google Scholar 

  30. Chicchon, H. & Abad, J. D. Peruvian Amazon Waterway, river dynamics and shallow zones. J. Waterw. Port Coast. Ocean Eng. ASCE 151, 5. https://doi.org/10.1061/JWPED5.WWENG-2237 (2025).

    Google Scholar 

  31. Ward, J. V. The four-dimensional nature of lotic ecosystems. J. N. Am. Benthol. Soc. 8(1), 2–8 (1989).

    Google Scholar 

  32. Poff, N. L. et al. The natural flow regime: A paradigm for river conservation and restoration. Bioscience 47(11), 769–784. https://doi.org/10.2307/1313099 (1997).

    Google Scholar 

  33. FISRWG Stream Corridor Restoration: Principles, Processes, and Practices. By the Federal Interagency Stream Restoration Working Group (FISRWG)(15 Federal agencies of the US gov’t). GPO Item No.0120-A; SuDocs No. A 57.6/2:EN 3/PT.653. ISBN-0-934213-59-3 (1998).

  34. Tockner, K., Pusch, M., Borchardt, D. & Lorang, M. S. Multiple stressors in coupled river-floodplain ecosystems. Freshw. Biol. 55(s1), 135–151. https://doi.org/10.1111/j.1365-2427.2009.02371.x (2010).

    Google Scholar 

  35. Carvajal-Quintero, J. D. et al. Damming fragments species’ ranges and heightens extinction risk. Conserv. Lett. 10(6), 708–716. https://doi.org/10.1111/conl.12336 (2017).

    Google Scholar 

  36. Latrubesse, E. M. et al. Damming the rivers of the Amazon basin. Nature 546(7658), 363–369. https://doi.org/10.1038/nature22333 (2017).

    Google Scholar 

  37. Flecker, A. S. et al. Reducing adverse impacts of Amazon hydropower expansion. Science 375(6582), 753–760. https://doi.org/10.1126/science.abj4017 (2022).

    Google Scholar 

  38. Abad, J. D. et al. River geomorphology and fish diversity around the Manseriche Gorge, the last Andean crossing is in peril. Water Resour. Res. 60(11), 37322. https://doi.org/10.1029/2024WR037322 (2024).

    Google Scholar 

  39. Jézéquel, C. et al. A database of freshwater fish species of the Amazon Basin. Sci. Data 7(1), 96. https://doi.org/10.1038/s41597-020-0436-4 (2020).

    Google Scholar 

  40. Margules, C. & Pressey, R. Systematic conservation planning. Nature 405, 243–253. https://doi.org/10.1038/35012251 (2000).

    Google Scholar 

  41. Pressey, R. L. & Bottrill, M. C. Opportunism, threats, and the evolution of systematic conservation planning. Conserv. Biol. 22, 1340–1345. https://doi.org/10.1111/j.1523-1739.2008.01032.x (2008).

    Google Scholar 

  42. Linke, S., Turak, E. & Nel, J. Freshwater conservation planning: The case for systematic approaches. Freshw. Biol. 56, 6–20. https://doi.org/10.1111/j.1365-2427.2010.02456.x (2011).

    Google Scholar 

  43. Reside, A. E., Butt, N. & Adams, V. M. Adapting systematic conservation planning for climate change. Biodivers. Conserv. 27, 1–29. https://doi.org/10.1007/s10531-017-1442-5 (2018).

    Google Scholar 

  44. Adams, V. M. et al. Implementation strategies for systematic conservation planning. Ambio 48, 139–152. https://doi.org/10.1007/s13280-018-1067-2 (2019).

    Google Scholar 

  45. Tellez, P., Petry, P., Walshurger, T., Higgins, J. & Apse, C. Portafolio de Conservacion De Agua Dulce Para La Cuenca Del Rio Magdalena – Cauca. The Nature Conservancy and CorMagdalena, Bogota, Colombia. 199 (2012).

  46. Petry, P. et al. A conservation assessment of the Rio Tapajós, Brazil. The Nature Conservancy. 23 (2018).

  47. The Nature Conservancy Brasil. Resumo executivo: Plano de conservação para a bacia do rio Araguaia [Executive summary]. The Nature Conservancy Brasil. https://www.tnc.org.br/content/dam/tnc/nature/en/documents/brasil/Resumo_Executivo_português.pdf (2024).

  48. Rodríguez-Iturbe, I., Muneepeerakul, R., Bertuzzo, E., Levin, S. A. & Rinaldo, A. River networks as ecological corridors: A complex systems perspective for integrating hydrologic, geomorphologic, and ecologic dynamics. Water Resour. Res. 45, W01413 (2009).

    Google Scholar 

  49. Grabowski, R. C., Surian, N. & Gurnell, A. M. Characterizing geomorphological change to support sustainable river restoration and management. WIREs Water 1(5), 483–512 (2014).

    Google Scholar 

  50. Espinoza Villar, R. et al. The integration of field measurements and satellite observations to determine river solid loads in poorly monitored basins. J. Hydrol. https://doi.org/10.1016/j.jhydrol.2012.04.024 (2012).

    Google Scholar 

  51. Puhakka, M., Kalliola, R., Rajasilta, M. & Salo, J. River types, site evolution and successional vegetation patterns in Peruvian Amazonia. J. Biogeogr. 19(6), 651–665. https://doi.org/10.2307/2845707 (1992).

    Google Scholar 

  52. Kalliola R. J., Puhakka M. & Danjoy W. Amazonía peruana: Vegetación húmeda tropical en el llano subandino. Jyvaskyla: Proyecto Amazonía Universidad de Turku|ONERN (1993).

  53. Greenberg, E. & Ganti, V. The pace of global river meandering influenced by fluvial sediment supply. Earth Planet. Sci. Lett. 634, 118674. https://doi.org/10.1016/j.epsl.2024.118674 (2024).

    Google Scholar 

  54. Abad, J. D. et al. Morphodynamics of anabranching structures in the Peruvian Amazon River. Earth Surf. Processes Landf. 50(1), e6020. https://doi.org/10.1002/esp.6020 (2025).

    Google Scholar 

  55. Hortal, J., Jimenez-Valverde, J., Gomez, J. F., Lobo, J. M. & Baselga, A. Historical bias in biodiversity inventories affects the observed environmental niche of the species. Oikos 117, 847–858. https://doi.org/10.1111/j.0030-1299.2008.16434.x (2008).

    Google Scholar 

  56. Meyer, C., Kreft, H., Guralnick, R. & Jetz, W. Global priorities for an effective information basis of biodiversity distributions. Nat. Commun. 6, 8221. https://doi.org/10.1038/ncomms9221 (2015).

    Google Scholar 

  57. Araújo, M. B. & Guisan, A. Five (Or so) challenges for species distribution modelling. J. Biogeogr. 33(10), 1677–1688 (2006).

    Google Scholar 

  58. Tedesco, P. A. et al. A global database on freshwater fish species occurrence in drainage basins. Sci. Data 4, 170141. https://doi.org/10.1038/sdata.2017.141 (2017).

    Google Scholar 

  59. Petry, P., & Sotomayor, L. Mapping Freshwater Ecological Systems with Nested Watersheds in South America. The Nature Conservancy (2009).

  60. Bogotá-Gregory, J. D. et al. Biogeochemical water type influences community composition, species richness, and biomass in megadiverse Amazonian fish assemblages. Sci. Rep. https://doi.org/10.1038/s41598-020-72349-0 (2020).

    Google Scholar 

  61. Higgins, J. V., Bryer, M. T., Khoury, M. L. & Fitzhugh, T. W. A freshwater classification approach for biodiversity conservation planning. Conserv. Biol. 19(2), 432–445 (2005).

    Google Scholar 

  62. Frias, C. E. et al. Planform evolution of two anabranching structures in the Upper Amazon River. Water Resour. Res. https://doi.org/10.1002/2014WR015836 (2015).

    Google Scholar 

  63. Latrubesse, E. Patterns of anabranching channels: The ultimate end-member adjustment of mega rivers. Geomorphology 101(1–2), 130–145. https://doi.org/10.1016/j.geomorph.2008.05.035 (2008).

    Google Scholar 

  64. Abad, J. D. et al. Hydrogeomorphology of asymmetric meandering channels: Experiments and field evidence. Water Resour. Res. 59, e2022WR033904. https://doi.org/10.1029/2022wr033904 (2023).

    Google Scholar 

  65. Guerrero, L. et al. Hydrogeomorphology of the origin of the Amazon River, the confluence between the Marañón and Ucayali rivers. Earth Surf. Process. Landf. https://doi.org/10.1002/esp.5949 (2024).

    Google Scholar 

  66. Dominguez-Ruben, L., Abad, J., Gutierrez, R. & Szupiany, N. Meander statistics toolbox (MStaT): A toolbox for geometry characterization of bends in meandering streams. SoftwareX. https://doi.org/10.1016/j.softx.2021.100674 (2021).

    Google Scholar 

  67. Li, Z. et al. High-resolution modeling of meander cutoffs: Laboratory and field scales. Front. Earth Sci. https://doi.org/10.3389/feart.2023.1208782 (2023).

    Google Scholar 

  68. Heiner, M., Higgins, J., Li, X. & Baker, B. Identifying freshwater conservation priorities in the Upper Yangtze River Basin. Freshw. Biol. 56(1), 89–105. https://doi.org/10.1111/j.1365-2427.2010.02466.x (2011).

    Google Scholar 

  69. Khoury, M., Higgins, J. & Weitzell, R. A freshwater conservation assessment of the Upper Mississippi River basin using a coarse-and fine-filter approach. Freshw. Biol. 56(1), 162–179. https://doi.org/10.1111/j.1365-2427.2010.02468.x (2011).

    Google Scholar 

  70. QGIS Development Team. QGIS Geographic Information System (Version 3.34). Open Source Geospatial Foundation Project. https://qgis.org (2024).

  71. Gorelick, N. et al. Google earth engine: Planetary-scale geospatial analysis for everyone. Remote Sens. Environ. 202, 18–27. https://doi.org/10.1016/j.rse.2017.06.031 (2017).

    Google Scholar 

  72. Lehner, B. & Grill, G. Global river hydrography and network routing: baseline data and new approaches to study the world’s large river systems. Hydrol. Process. 27(15), 2171–2186 (2013).

    Google Scholar 

  73. Japan Aerospace Exploration Agency (JAXA) ALOS PALSAR Digital Elevation Model (DEM), 12.5 m/30 m resolution. Alaska Satellite Facility, University of Alaska Fairbanks (2006–2011).

  74. Masanobu, S. et al. New global forest/non-forest maps from ALOS PALSAR data (2007–2010). Remote Sens. Environ. 155(13–31), 2014. https://doi.org/10.1016/j.rse.2014.04.014 (2014).

    Google Scholar 

  75. Abatzoglou, J. et al. TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015. Sci. Data 5, 170191. https://doi.org/10.1038/sdata.2017.191 (2018).

    Google Scholar 

  76. Alcárcel-Gutiérrez, F. A., Gómez Tapias, J., Montes Ramírez, N. E. & Almanza-Meléndez, M. F. Geological map of South America in google earth. J. Maps https://doi.org/10.1080/17445647.2023.2185167 (2023).

    Google Scholar 

  77. Gumbricht, T. et al. An expert system model for mapping tropical wetlands and peatlands reveals South America as the largest contributor. Glob. Change Biol. 25, 156. https://doi.org/10.1111/gcb.13689 (2017).

    Google Scholar 

  78. Hansen, M. C. et al. High-Resolution global maps of 21st-century forest cover change. Science 342, 850–853. https://doi.org/10.1126/science.1244693 (2013).

    Google Scholar 

  79. Zanaga, D. et al. ESA WorldCover 10m 2021 v200. https://doi.org/10.5281/zenodo.7254221 (2022).

  80. Smith, M. P., Schiff, R. Olivero, A. & MacBroom J. The active river Área: A conservation framework for protecting rivers and streams. Boston: TNC. (Report by The Nature Conservancy) (2008).

  81. Abad, J. D. et al. Planform dynamics and cut-off processes in the lower Ucayali River, Peruvian Amazon. Water 14(19), 3059. https://doi.org/10.3390/w14193059 (2022).

    Google Scholar 

  82. U.S. Geological Survey Landsat 5, 7 and 8 imageries. Obtained from the U.S. Geological Survey (2023).

  83. European Space Agency (ESA). Sentinel-2 imagery. Obtained from Copernicus Open Access Hub (2023).

  84. Santos, D. A., Martinez, J. M., Harmel, T., Borges, H. D. & Roig, H. Evaluation of SENTINEL-2/MSI imagery products LEVEL-2A obtained by three different atmospheric corrections for monitoring suspended sediments concentration in Madeira River, Brazil. In 2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS) 207–212 (IEEE, 2020). 10.5194/isprs-archives-XLII-3-W12-2020-243-2020.

  85. Breiman, L. Classification and Regression Trees 1st edn. (Routledge, 1984). https://doi.org/10.1201/9781315139470.

    Google Scholar 

  86. Gardner, J. et al. Human activities change suspended sediment concentration along rivers. Environ. Res. Lett. 18(6), 064032. https://doi.org/10.1088/1748-9326/acd8d8 (2023).

    Google Scholar 

  87. Lehner, B., Verdin, K. & Jarvis, A. New global hydrography derived from spaceborne elevation data. EOS Trans. Am. Geophys. Union 89(10), 93–94. https://doi.org/10.1029/2008EO100001 (2008).

    Google Scholar 

  88. Pekel, J., Cottam, A., Gorelick, N. & Belward, A. S. High-resolution mapping of global surface water and its long-term changes. Nature 540, 418–422. https://doi.org/10.1038/nature20584 (2016).

    Google Scholar 

Download references

Acknowledgements

The authors thank all participants from the technical workshops held in Lima and Iquitos (Peru), including the communities of Padre Cocha and San Joaquin de Omagua (Loreto, Peru) for sharing local knowledge. Thanks also to Hernan Chicchon and Jesus Marin-Diaz for assisting on the estimation of the MOR index.

Funding

This project was funded by the Freshwater Amazon Program by The Nature Conservancy under Contract PERU 138/2023 with RED YAKU.

Author information

Authors and Affiliations

Authors

Contributions

Conceptualization, PP, JDA, LDR, AC, TVR, RLM; methods and materials, LDR, ETR, TVR, JDA, and PP; formal analysis, LDR, PP, ETR, TVR; data curation, LDR, TVR, and ETR; interpretation and discussion, LDR, TVR, PP, RLM, JDA; writing—original draft preparation, LDR, TVR and JDA; review and editing, AC, PP, RLM, and ETR; visualization, LDR, TVR, and ETR; supervision, JDA, AC; project administration, JDA, TVR and AC; funding acquisition, AC, JDA, TVR. All authors have read and agreed to the published version of the manuscript.

Corresponding authors

Correspondence to
A. Cardenas or J. D. Abad.

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.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary Material 1

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

Cite this article

Dominguez-Ruben, L., Rojas, T.V., Petry, P. et al. Incorporating river morphodynamics in the characterization of key ecological system units for conservation in the western Amazon.
Sci Rep (2026). https://doi.org/10.1038/s41598-026-36942-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41598-026-36942-z


Source: Ecology - nature.com

Biodiversity implications of land-intensive carbon dioxide removal

Ferula sinkiangensis (新疆阿魏, xin jiang a wei)

Back to Top