Nutritional Resilience of Crops under Intense Climate Fluctuations: An Active and Dynamic Adaptation Strategy

Classical plant nutritional diagnosis assumes that environmental fluctuations throughout the crop's phenological cycle occur within predictable limits. Traditional methods (sufficiency ranges, DRIS, and CND) establish fixed mineral targets because they assume moderate and historical instability of the growing medium. This approach maintains its operational validity as long as the environment does not suffer abrupt disruptions.However, the current scenario of intense climate change highlights the limitations of this classic method. Extreme fluctuations continuously alter the metabolic demand for nutrients, generating two effects that invalidate static references: (i) identical tissue concentrations may reflect distinct physiological states depending on the environmental context; and (ii) different genotypes subjected to the same management present different tissue concentrations due to the active reconfiguration of the ionome, modulated by the genotype × environment interaction. Consequently, diagnoses anchored in fixed references demand a new interpretative understanding when the biological target is dynamic.In this context, natural forest ecosystems play a pivotal role, acting as a carbon sink by storing carbon in plant tissue and soil. They can also be a source of C to the atmosphere when this natural forest is replaced by crops or pastures. As for planted forests, their use is controversial, being considered both an instrument to promote carbon sequestration and a form of biodiversity loss by replacing native vegetation. Mixed systems, which involve forests and livestock or crops, on the other hand, can be a tool for more sustainable agriculture from the point of view of GHG emissions.We invite contributions that treat the ionome as a dynamic system to measure, partition, and predict reconfiguration capacity. We accept field and controlled studies (with more than one stressor), descriptions, and predictive models at physiological, molecular, and ecological scales. Specific themes include, but are not limited to: - Ionic responses to drought, heat, and combined stress- High-throughput phenotyping and remote sensing; nutrient sound diagnosis- Machine learning for plant nutrition- Genotype-environment (G×E) interactions affecting nutritional resilience. We accept all types of articles, including Original Research, Methods, Reviews, Mini-Reviews, Perspectives, and Opinions. Topic editors: Luciano Kayser Vargas, Renato De Mello Prado, Dilier Olivera Viciedo Source: https://www.frontiersin.org/research-topics/84903/nutritional-resilience-of-crops-under-intense-climate-fluctuations-an-active-and-dynamic-adaptation-strategy