36 citations as recorded by crossref.

1. The use of biogeochemical models to evaluate mitigation of greenhouse gas emissions from managed grasslands R. Sándor et al. 10.1016/j.scitotenv.2018.06.020
2. A model-data fusion approach to analyse carbon dynamics in managed grasslands V. Myrgiotis et al. 10.1016/j.agsy.2020.102907
3. CM2Mc-LPJmL v1.0: biophysical coupling of a process-based dynamic vegetation model with managed land to a general circulation model M. Drüke et al. 10.5194/gmd-14-4117-2021
4. The role of cover crops for cropland soil carbon, nitrogen leaching, and agricultural yields – a global simulation study with LPJmL (V. 5.0-tillage-cc) V. Porwollik et al. 10.5194/bg-19-957-2022
5. Dynamics of soil organic carbon in the steppes of Russia and Kazakhstan under past and future climate and land use S. Rolinski et al. 10.1007/s10113-021-01799-7
6. Implementing the nitrogen cycle into the dynamic global vegetation, hydrology, and crop growth model LPJmL (version 5.0) W. von Bloh et al. 10.5194/gmd-11-2789-2018
7. ATTILA 4.0: Lagrangian advective and convective transport of passive tracers within the ECHAM5/MESSy (2.53.0) chemistry–climate model S. Brinkop & P. Jöckel 10.5194/gmd-12-1991-2019
8. Water Use in Global Livestock Production—Opportunities and Constraints for Increasing Water Productivity J. Heinke et al. 10.1029/2019WR026995
9. Confronting an individual-based simulation model with empirical community patterns of grasslands F. Taubert et al. 10.1371/journal.pone.0236546
10. Two decades of Earth system modeling with an emphasis on Model for Interdisciplinary Research on Climate (MIROC) M. Kawamiya et al. 10.1186/s40645-020-00369-5
11. From planetary to regional boundaries for agricultural nitrogen pollution L. Schulte-Uebbing et al. 10.1038/s41586-022-05158-2
12. Connecting competitor, stress-tolerator and ruderal (CSR) theory and Lund Potsdam Jena managed Land 5 (LPJmL 5) to assess the role of environmental conditions, management and functional diversity for grassland ecosystem functions S. Wirth et al. 10.5194/bg-21-381-2024
13. Biomes of the world under climate change scenarios: increasing aridity and higher temperatures lead to significant shifts in natural vegetation C. Bonannella et al. 10.7717/peerj.15593
14. Tackling unresolved questions in forest ecology: The past and future role of simulation models I. Maréchaux et al. 10.1002/ece3.7391
15. Coordinating AgMIP data and models across global and regional scales for 1.5°C and 2.0°C assessments C. Rosenzweig et al. 10.1098/rsta.2016.0455
16. MIROC-INTEG-LAND version 1: a global biogeochemical land surface model with human water management, crop growth, and land-use change T. Yokohata et al. 10.5194/gmd-13-4713-2020
17. Global cotton production under climate change – Implications for yield and water consumption Y. Jans et al. 10.5194/hess-25-2027-2021
18. The carbon budget of the managed grasslands of Great Britain – informed by earth observations V. Myrgiotis et al. 10.5194/bg-19-4147-2022
19. Do details matter? Disentangling the processes related to plant species interactions in two grassland models of different complexity S. Wirth et al. 10.1016/j.ecolmodel.2021.109737
20. Predicting methane emissions, animal-environmental metrics and carbon footprint from Brahman (Bos indicus) breeding herd systems based on long-term research on grazing of neotropical savanna and Brachiaria decumbens pastures C. Ramírez-Restrepo et al. 10.1016/j.agsy.2020.102892
21. Land-use conversions from managed grasslands to croplands in Uruguay increase medium-term net carbon emissions to the atmosphere J. Castaño-Sánchez et al. 10.1080/1747423X.2021.1933227
22. Differential responses of native and managed prairie pastures to environmental variability and management practices R. Bajgain et al. 10.1016/j.agrformet.2020.108137
23. Grazing and aridity reduce perennial grass abundance in semi-arid rangelands – Insights from a trait-based dynamic vegetation model M. Pfeiffer et al. 10.1016/j.ecolmodel.2018.12.013
24. Inferring management and predicting sub-field scale C dynamics in UK grasslands using biogeochemical modelling and satellite-derived leaf area data V. Myrgiotis et al. 10.1016/j.agrformet.2021.108466
25. Modelling the role of livestock grazing in C and N cycling in grasslands with LPJmL5.0-grazing J. Heinke et al. 10.5194/gmd-16-2455-2023
26. Dynamic simulation of management events for assessing impacts of climate change on pre-alpine grassland productivity K. Petersen et al. 10.1016/j.eja.2021.126306
27. Wetter environment and increased grazing reduced the area burned in northern Eurasia from 2002 to 2016 W. Hao et al. 10.5194/bg-18-2559-2021
28. DynaGraM: A process-based model to simulate multi-species plant community dynamics in managed grasslands T. Moulin et al. 10.1016/j.ecolmodel.2020.109345
29. Multi-model assessment identifies livestock grazing as a major contributor to variation in European Union land and water footprints D. Vanham et al. 10.1038/s43016-023-00797-8
30. Feed balances for ruminant livestock: gridded estimates for data−constrained regions S. Fraval et al. 10.1016/j.animal.2024.101199
31. Global trends in grassland carrying capacity and relative stocking density of livestock J. Piipponen et al. 10.1111/gcb.16174
32. The role of species traits for grassland productivity F. Taubert et al. 10.1002/ecs2.3205
33. Impact of mowing frequency and temperature on the production of temperate grasslands: explanations received by an individual‐based model J. Schmid et al. 10.1111/oik.09108
34. The importance of management information and soil moisture representation for simulating tillage effects on N<sub>2</sub>O emissions in LPJmL5.0-tillage F. Lutz et al. 10.5194/gmd-13-3905-2020
35. How Much Complexity Is Required for Modelling Grassland Production at Regional Scales? I. Vogeler et al. 10.3390/land12020327
36. Livestock and human use of land: Productivity trends and dietary choices as drivers of future land and carbon dynamics I. Weindl et al. 10.1016/j.gloplacha.2017.10.002