Publications of Markus Reichstein

Ascenso, G.; Giuliani, M.; Pérez-Aracil, J.; Salcedo-Sanz, S.; Bertini, C.; Bonetti, P.; Camps-Valls, G.; Fernández Torres, M. Á.; Ficchì, A.; Linscheid, N. et al.; Merlo, M.; Palcic, G.; Reichstein, M.; Restelli, M.; Toreti, A.; Walt, E.; Castelletti, A.: The maturation of AI in drought science: A review of trends, pitfalls, and priorities. Water Resources Research 62 (4), e2025WR041828 (2026)

Hanggara, B. B.; El-Madany, T. S.; Carrara, A.; Moreno, G.; Gonzalez-Cascon, R.; Burchard-Levine, V.; Martin, P.; Metzger, S.; Hildebrandt, A.; Reichstein, M. et al.; Lee, S.-C.: Non‐abrupt vegetation changes due to altered nutrient balance make complex scale‐dependent warming and cooling effects. Global Change Biology 32 (3), e70782 (2026)

Ruiz-Vásquez, M.; O, S.; Brenning, A.; Reichstein, M.; Balsamo, G.; Orth, R.: Land surface information from satellites boost near-surface temperature forecast skill. Communications Earth & Environment 7, 245 (2026)

Luo, H.; Bastos, A.; Reichstein, M.; Duveiller, G.; Kretzschmar, J.; Quaas, J.: Hydroclimate shapes photosynthetic sensitivity to cloud cover across global terrestrial ecosystems. Nature Communications 17, 1646 (2026)

Jin, Z.; Liu, L.; Yang, Q.; Jia, X.; Tao, S.; Guo, Y.; Ghosh, R.; Wang, S.; Zhu, Q.; Jung, M. et al.; Guan, K.; Kumar, V.; Reichstein, M.; Fang, J.; Luo, Y.: Knowledge-guided machine learning for global change ecology research. Global Change Biology 32 (2), e70742 (2026)

Li, N.; Sippel, S.; Linscheid, N.; Mahecha, M. D.; Reichstein, M.; Bastos, A.: Quantifying the time of emergence of the anthropogenic signal in the global land carbon sink. Biogeosciences 23 (2), pp. 767 - 792 (2026)

Eigenbrod, F.; Alexander, P.; Apfel, N.; Athanasiadis, I.; Berger, T.; Bullock, J.; Duveiller, G.; Equihua, J.; Menezes, I.; Moreira, R. et al.; Paudel, D.; Sitokonstantinou, V.; Reichstein, M.; Willcock, S.; Woodman, T.: Causal machine learning methods for understanding land use and land cover change. Landscape Ecology 41, 25 (2026)

Li, W.; Duveiller, G.; Gans, F.; Smits, J.; Kraemer, G.; Frank, D.; Mahecha, M. D.; Weber, U.; Migliavacca, M.; Ceglar, A. et al.; Keenan, T. F.; Reichstein, M.: Globally synchronized changes in the biosphere, atmosphere, and society identified using public data. One Earth 9 (1), 101559 (2026)

Zhang, J.; Yu, K.; Reichstein, M.; Xu, L.; Wright, I. J.; Migliavacca, M.; Gomarasca, U.; Laughlin, D. C.; Cen, X.; Liu, C. et al.; He, H.; He, N.: Trait space and compactness: A new perspective on explaining variations in primary productivity. Ecology 107 (1), e70278 (2026)

Tautenhahn, S.; Jung, M.; Rzanny, M.; Mäder, P.; Reichstein, M.; Ahrens, B.; Bebber, A.; Boho, D.; Chytrý, M.; Dengler, J. et al.; Jansen, F.; Katal, N.; Midolo, G.; Tichý, L.; Walther, S.; Weber, U.; Wittich, H. C.; Wäldchen, J.: Urbanization signatures on climate and soils uncovered by crowd-sensed plants. Nature Cities 3, 126–135 (2026)

ElGhawi, R.; Reimers, C.; Schnur, R.; Reichstein, M.; Körner, M.; Carvalhais, N.; Winkler, A. J.: Hybrid‐modeling of land‐atmosphere fluxes using integrated machine learning in the ICON‐ESM modeling framework. Journal of Advances in Modeling Earth Systems 17 (12), e2025MS005102 (2025)

Wang, Lijun, L.; Shi, L.; Reimers, C.; Wang, Y.; He, L.; Wang, Y.; Reichstein, M.; Jiang, S.: A self-supervised deep learning model for enhanced generalization in soil moisture prediction. Journal of Hydrology 662 (Part B), 133974 (2025)

Tiggeloven, T.; Pfeiffer, S.; Matano, A.; van den Homberg, M.; Thalheimer, L.; Reichstein, M.; Torresan, S.: The role of artificial intelligence for early warning systems: Status, applicability, guardrails, and ways forward. iScience 28 (11), 113689 (2025)

Chen, D.; Roy, D. P.; Zhu, Z.; McVicar, T. R.; Sheffield, J.; Atkinson, P. M.; AghaKouchak, A.; Blaschke, T.; Borrelli, P.; Dorigo, W. et al.; Fensholt, R.; Gorelick, N.; Guanter, L.; Hubacek, K.; McCabe, M. F.; Miralles, D. G.; Rammig, A.; Reichstein, M.; Rignot, E.; Rogers, B. M.; Tyukavina, A.; Veraverbeke, S.; Zarco-Tejada, P. J.; Berthier, E.: Comment: A call for integrated and cooperative global sharing of China’s Earth observation data. Nature Geoscience 18, pp. 1071 - 1073 (2025)

Paulus, S.; Migliavacca, M.; Reichstein, M.; Orth, R.; Lee, S.-C.; Carrara, A.; Hildebrandt, A.; Nelson, J. A.: Insights into water vapor uptake by dry soils using a global eddy covariance observation network. Global Change Biology 31 (10), e70547 (2025)

Yu, X.; Orth, R.; Reichstein, M.; Reimers, C.; Gomarasca, U.; Migliavacca, M.; Papale, D.; Bahn, M.; Bastos, A.: Widespread but divergent drought legacy effects on gross primary productivity across biomes. Global Change Biology 31 (10), e7054 (2025)

Nguyen, N. B.; Migliavacca, M.; Bassiouni, M.; Baldocchi, D. D.; Gherardi, L. A.; Green, J. K.; Papale, D.; Reichstein, M.; Cohrs, K.-H.; Cescatti, A. et al.; Nguyen, T. D.; Nguyen, H. H.; Nguyen, Q. M.; Keenan, T. F.: Widespread underestimation of rain-induced soil carbon emissions from global drylands. Nature Geoscience 18, pp. 869 - 876 (2025)

Kraft, B.; Nelson, J. A.; Walther, S.; Gans, F.; Weber, U.; Duveiller, G.; Reichstein, M.; Zhang, W.; Rußwurm, M.; Tuia, D. et al.; Körner, M.; Hamdi, Z. M.; Jung, M.: On the added value of sequential deep learning for the upscaling of evapotranspiration. Biogeosciences 22 (12), pp. 3965 - 3987 (2025)

Migliavacca, M.; Grassi, G.; Bastos, A.; Ceccherini, G.; Ciais, P.; Janssens-Maenhout, G.; Lugato, E.; Mahecha, M. D.; Novick, K. A.; Peñuelas, J. et al.; Pilli, R.; Reichstein, M.; Avitabile, V.; Beck, P. S. A.; Barredo, J. I.; Forzieri, G.; Herold, M.; Korosuo, A.; Mansuy, N.; Mubareka, S.; Orth, R.; Rougieux, P.; Cescatti, A.: Securing the forest carbon sink for the European Union's climate ambition. Nature 643 (8074), pp. 1203 - 1213 (2025)

Kariyathan, T.; Bastos, A.; Reichstein, M.; Peters, W.; Marshall, J.: Limitations in the use of atmospheric CO₂ observations to directly infer changes in the length of the biospheric carbon uptake period. Atmospheric Chemistry and Physics 25 (14), pp. 7863 - 7878 (2025)