14 citations as recorded by crossref.

1. Soil resilience to degradation in Poland by 2050 under climate and land use change J. Coblinski et al. https://doi.org/10.1016/j.catena.2025.109463
2. Soil compaction alleviation by deep non-inversion tillage and crop yield responses in no tilled soils of the Pampas region of Argentina. A meta-analysis G. Peralta et al. https://doi.org/10.1016/j.still.2021.105022
3. A dataset of inventory plots and biomass estimates from the Chaco dry forest M. Weixelbaumer et al. https://doi.org/10.1186/s13595-026-01327-9
4. Putting the Ecosystem Services idea at work: Applications on impact assessment and territorial planning L. Staiano et al. https://doi.org/10.1016/j.envdev.2020.100570
5. Deforestation and current management practices reduce soil organic carbon in the semi-arid Chaco, Argentina P. Baldassini & J. Paruelo https://doi.org/10.1016/j.agsy.2019.102749
6. Relationship between degradation and the structural-functional complexity of subtropical xerophytic forests in the Argentine Wet Chaco E. Arnesi et al. https://doi.org/10.1016/j.foreco.2024.121957
7. Spatial patterns of nutrients balance of major crops in Argentina J. Koritschoner et al. https://doi.org/10.1016/j.scitotenv.2022.159863
8. Soil Carbon, Nitrogen and Phosphorus Contents along a Gradient of Agricultural Intensity in the Kilombero Valley, Tanzania J. Livsey et al. https://doi.org/10.3390/land9040121
9. Relationships between land-use intensity, woody species diversity, and carbon storage in an arid woodland ecosystem A. Magnano et al. https://doi.org/10.1016/j.foreco.2022.120747
10. Carbon-scaled nitrous oxide emissions better reflect the impacts of land use changes than raw nitrous oxide emissions in the Dry Chaco region J. Chalco Vera & M. Acreche https://doi.org/10.1016/j.agee.2024.109128
11. How may deforestation rates and political instruments affect land use patterns and Carbon emissions in the semi-arid Chaco, Argentina? P. Baldassini et al. https://doi.org/10.1016/j.landusepol.2020.104985
12. SOC content of global Mollisols at a 30 m spatial resolution from 1984 to 2021 generated by the novel ML-CNN prediction model X. Meng et al. https://doi.org/10.1016/j.rse.2023.113911
13. Environment quality, sowing date, and genotype determine soybean yields in the Argentinean Gran Chaco A. Madias et al. https://doi.org/10.1016/j.eja.2020.126217
14. High-resolution soil organic carbon mapping at the field scale in Southern Belgium (Wallonia) Y. Zhou et al. https://doi.org/10.1016/j.geoderma.2022.115929