@misc{WangZhuCaoetal., author = {Wang, Guan and Zhu, Zihong and Cao, Jianhua and Zhu, Tongbin and Zhou, Jinxing and M{\"u}ller, Christoph and Li, Junran and Freese, Dirk and Le Roux, Xavier}, title = {Agricultural cultivation duration affects soil inorganic N turnover and supply capacity : Evidence in subtropical karst regions}, series = {Agriculture, Ecosystems \& Environment}, volume = {381}, journal = {Agriculture, Ecosystems \& Environment}, publisher = {Elsevier BV}, issn = {0167-8809}, doi = {10.1016/j.agee.2024.109462}, abstract = {The conversion of indigenous woodlands to agricultural lands has significantly altered nitrogen (N) cycling, impacting both ecosystem productivity and environmental health locally and globally. The relationship between cultivation duration and soil N availability and the mechanisms that drive these changes, however, remain unclear. In this study, we aimed to investigate how the duration of agricultural reclamation influences soil N cycling in the karst landscapes of southwestern China. We selected economic crops that have been cultivated for 1, 5, 15, and 30 years and conducted a regional survey using 15N labeling and molecular biology techniques to assess the effects of cultivation duration on soil N cycling. Our results show that short-term reclamation (< 5 years) caused minimal changes in soil N dynamics, with little effect on the net production rates of NH4+ and NO3-. However, as cultivation duration increased, we observed progressive declines in mineralization, nitrification, and microbial immobilization rates of NH4+ and NO3-. This led to a substantial reduction in soil inorganic N availability (-39 \% for NH4+ and -70 \% for NO3-) and a significant increase in the mean residence time of NH4+ and NO3-, indicating a slower N turnover. Long-term reclamation (30 years) resulted in the most pronounced effects, reducing the soil's capacity to supply inorganic N by impairing soil organic matter input, degrading soil structure, and lowering soil pH. Key soil variables such as soil organic carbon content, pH, total N, and soil aggregate stability explained over 80 \% of the variance in N turnover rates. Overall, our findings suggest that while shortterm reclamation has little impact, long-term agricultural practices significantly impair soil N cycling and availability. Sustainable agricultural practices that enhance soil organic matter content and promote soil aggregate stability could help preserve soil health and maintain productivity in karst and similar regions worldwide.}, language = {en} } @misc{NoiaJuniorRuaneAthanasiadisetal., author = {N{\´o}ia-J{\´u}nior, Rog{\´e}rio de S. and Ruane, Alex C. and Athanasiadis, Ioannis N. and Ewert, Frank and Harrison, Matthew Tom and J{\"a}germeyr, Jonas and Martre, Pierre and M{\"u}ller, Christoph and Palosuo, Taru and Salmer{\´o}n, Montserrat and Webber, Heidi and Maccarthy, Dilys Sefakor and Asseng, Senthold}, title = {Crop models for future food systems}, series = {One earth}, volume = {8}, journal = {One earth}, number = {10}, publisher = {Elsevier BV}, address = {Amsterdam}, issn = {2590-3322}, doi = {10.1016/j.oneear.2025.101487}, pages = {1 -- 7}, abstract = {Global food systems face intensifying pressure from climate change, resource scarcity, and rising demand, making their transformation toward resilience and sustainability urgent. Process-based crop growth models (CMs) are critical for understanding cropping system dynamics and supporting decisions from crop breeding to adaptive management across diverse environments. Yet, current CMs struggle to capture extreme events, novel production systems, and rapidly evolving data streams, limiting their ability to inform robust and timely decisions. Here, we outline CM structure, identify key knowledge gaps, and propose six priorities for next-generation CMs: (1) expand applications to extremes and to diverse systems; (2) support climate-resilient breeding; (3) integrate with machine learning for better inputs and forecasts; (4) link with standardized sensor and database networks; (5) promote modular, open-source architectures; and (6) build capacity in under-resourced regions. These priorities will substantially enhance CM robustness, comparability, and usability, reinforcing their role in guiding sustainable food system transformation.}, language = {en} }