EGUsphere EGUsphere EGUsphere EGUsphere Copernicus Publications Göttingen, Germany 10.5194/egusphere-2026-296 Absence of nitrogen threshold effect on soil respiration leads to an underestimation of global soil carbon sequestration in model Wang Daju 1 9 16 Yang Ruowen 2 16 Cai Lei https://orcid.org/0000-0002-9794-407X 2 16 Gentine Pierre 3 4 Terrer César 5 Niu Shuli https://orcid.org/0000-0002-2394-2864 6 7 Migliavacca Mirco https://orcid.org/0000-0003-3546-8407 8 Yuan Wenping 9 10 Tateno Ryunosuke 11 Xiao Junlan 1 Peñuelas Josep https://orcid.org/0000-0002-7215-0150 12 13 Tang Caixian 14 Fu Yongshuo H. https://orcid.org/0000-0002-9761-5292 15 Shi Weiyu 1 Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing, 400700, China Department of Atmospheric Sciences, Yunnan University, Kunming, 650000, China Department of Earth and Environmental Engineering, Columbia University, New York, 10027, USA Center for Learning the Earth with Artificial Intelligence and Physics (LEAP), Columbia University, 10027, New York, USA Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, 02139, USA Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 101408, China European Commission, Joint Research Centre (JRC), Ispra, 21027, Italy School of Atmospheric Sciences, Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle, Sun Yat-sen University, Zhuhai, 519000, China Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China Field Science Education and Research Center, Kyoto University, Kyoto, 113-8656, Japan CREAF, Cerdanyola del Vallès, Catalonia, 08290, Spain CSIC, Global Ecology Unit, CREAF-CSIC-UAB, Cerdanyola del Vallès, 08290, Spain La Trobe Institute for Sustainable Agriculture and Food, Department of Animal, Plant & Soil Sciences, Bundoora, VIC, 3083, Australia College of Water Sciences, Beijing Normal University, Beijing, 100875, China These authors contributed equally to this work. 03 02 2026 2026 1 25 Copyright: © 2026 Daju Wang et al. 2026 This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/ This article is available from https://egusphere.copernicus.org/preprints/2026/egusphere-2026-296/ The full text article is available as a PDF file from https://egusphere.copernicus.org/preprints/2026/egusphere-2026-296/egusphere-2026-296.pdf

Soil respiration (<em>Rs</em>), a key component of the global carbon cycle, plays a pivotal role in regulating atmospheric CO<sub>2</sub> concentrations and climate. Yet, the global responses of <em>Rs</em> and its components, including heterotrophic respiration (<em>Rh</em>) and autotrophic respiration (<em>Ra</em>) to varying levels of nitrogen (N) deposition remain poorly understood. By synthesizing global data from 931 paired observations of 226 experimental sites, this study indicated that <em>Rs </em>responses generally decline with increasing N inputs: low to moderate additions exert negligible or slightly positive effects, while higher additions consistently suppress <em>Rs</em>, mainly through reductions in <em>Rh</em>. Based on an N addition threshold (N<sub>th</sub>) that indicates whether <em>Rs</em> increases or decreases, we incorporated this response pattern into the Community Land Model version 5 (CLM5). We demonstrate that ignoring N's variable impacts may cause <em>Rs</em> to be overestimated or soil carbon sequestration to be underestimated by up to 20 %. Our results provide a robust global assessment of <em>Rs</em>-N relationships and demonstrate the importance of representing N-induced reductions in soil respiration in Earth system models, to improve predictions of terrestrial carbon-climate feedbacks.