Título : Disentangling the connections between management, soil health, and crop productivity at field and regional scales
Autor(es) : Rubio, Valentina
Fecha de publicación : 1-ago-2023
Tipo de publicación: Tesis de doctorado
Versión: Publicado
Supervisor(es) : Harold van Es
Publicado por: Cornell
Areas del conocimiento : Ciencias Naturales y Exactas
Ciencias de la Tierra y relacionadas con el Medio Ambiente
Ciencias Agrícolas
Agricultura, Silvicultura y Pesca
Agricultura
Ciencias del Suelo
Otros descriptores : Salud del suelo
Soil Health
Crop productivity
Digital Soil Mapping
Resumen : The expansion of agriculture and unsustainable management strategies have resulted in severe soil depletion, compromising soil functionality, and the ecosystem services it provides. Understanding the drivers of Soil Health (SH) is crucial for developing effective strategies and promoting sustainable management. This research presents the results of four interrelated projects conducted in Uruguay, and New York State, USA. The projects aim to enhance our understanding of SH drivers at different scales and their connection with anthropogenic management and crop productivity. The research highlights the negative impacts of replacing natural grassland with annually cultivated areas, and underscores the benefits of various conservation practices. It provides a comprehensive set of reference values for evaluating SH indicators in the Pampas region. The study also demonstrates the critical influence of soil organic carbon degradation on cereal productivity losses under annual crop rotations and its relationship with a broader set of SH indicators. To understand the driving force of management in SH, a methodological framework based on the critical zone approach is presented. It proposes using aboveground biomass inputs, which account for 50% of SH variations, as an indicator for potential agronomic management effects on SH. Management scenarios for the Pampas region are evaluated to showcase the applicability of this approach in assessing sustainable management practices. Furthermore, high-resolution spatial data, machine learning models, and digital soil mapping techniques are employed to develop SH prediction models and maps, as well as identify the main drivers of SH at a regional scale in New York State, USA. Overall, the findings emphasize the complexity of SH drivers and the need for comprehensive assessments that consider context-specific conditions, which includes an understanding of management effects on biomass fluxes within a land use system and region. Overall, this research contributes to advancing our knowledge of the complex interplay between inherent soil properties and human activities on SH and provides insights into the design of management strategies that promote sustainable soil management.
URI / Handle: https://hdl.handle.net/20.500.12381/4025
DOI: https://doi.org/10.7298/0xzg-2f70
Financiadores: Agencia Nacional de Investigación e Innovación
Programa Fulbright
Identificador ANII: POS_FUL_2019_1_1008446
Nivel de Acceso: Acceso abierto
Licencia CC: Reconocimiento 4.0 Internacional. (CC BY)
Aparece en las colecciones: Publicaciones de ANII

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