Plant Stress Biology in a Warming World: Synergies in Abiotic and Biotic Adaptation

Plants encounter environmental stress as combinations of fluctuating abiotic and biotic factors rather than as isolated perturbations. This reality challenges the traditional pathway-centred model of stress biology, in which tolerance is inferred from a limited set of genes, hormones or metabolites measured under one controlled treatment. This critical narrative review examines how genomics, transcriptomics, proteomics, metabolomics, ionomics, epigenomics, phenomics, microbiome profiling and single-cell approaches can be integrated to reconstruct stress adaptation as a dynamic, context-dependent network. Literature published from 2000 to 30 June 2026 was considered, together with earlier foundational work where conceptually necessary. The synthesis emphasises three conclusions. First, stress combinations generate emergent molecular states that cannot be predicted reliably by adding single-stress responses; stress identity, sequence, intensity, developmental stage, tissue, cell type, genotype and microbiome context jointly shape the observed state. Second, the principal value of multi-omics is not the accumulation of parallel data layers but the ability to test cross-layer relationships while recognising temporal lags and discordance between transcripts, proteins, metabolites and phenotypes. Third, translation to crop resilience remains limited because many studies use small, controlled-environment experiments, bulk tissues and correlation-based integration without independent perturbational or field validation. Network methods, latent-factor models and supervised integration improve feature prioritisation, but each can amplify batch effects, overfitting or confounding when sample size is small relative to molecular dimensionality. Single-cell and single-nucleus approaches, high-throughput phenotyping and plant-microbiome measurements offer routes to recover spatial and ecological context, yet they also introduce new sampling and harmonisation problems. The review therefore argues for a shift from descriptive multi-omics towards matched-sample, time-resolved, perturbation-aware and field-connected experimental designs. Such designs are more likely to identify stress-response modules that remain predictive across genotypes and environments and to distinguish robust adaptation mechanisms from context-specific molecular signatures.