The study compares neutral genetic diversity and adaptive differentiation between old-growth and recently planted Norway spruce (Picea abies) stands in northern Sweden, finding similar overall genetic diversity but stronger local adaptation signals in natural forests. Planted stands exhibit weaker adaptive variation and higher vulnerability to future climate change, underscoring the need to conserve adaptive genetic variation in forest management.

The study used Arabidopsis thaliana mutants with low (vtc2, vtc4) and high (vtc2/OE-VTC2) ascorbate levels to examine how ascorbate concentration affects gene expression and cellular homeostasis. Transcriptomic analysis revealed that altered ascorbate levels modulate defense and stress pathways, and that TAA1/TAR2‑mediated auxin biosynthesis is required for coping with elevated ascorbate in a light‑dependent manner.

The study applied non‑stationary generalized Pareto distributions, rooted in extreme value theory, to estimate how the risk of low yields for major crops changes over time under climate change. Analyses of global (1961‑2022) and Japanese (1948/1958‑2020) yield datasets revealed increasing low‑yield risk for most crops and regions, with only Japanese wheat showing a mitigating trend, and simulation tests confirmed the models' general accuracy, which depends on dataset size.

The study shows that the SnRK1 catalytic subunit KIN10 directs tissue-specific growth‑defense programs in Arabidopsis thaliana by reshaping transcriptomes. kin10 knockout mutants exhibit altered root transcription, reduced root growth, and weakened defense against Pseudomonas syringae, whereas KIN10 overexpression activates shoot defense pathways, increasing ROS and salicylic acid signaling at the cost of growth.

The study combined long‑read whole‑genome assembly, multi‑omics profiling (DNA methylation, mRNA, ribosome‑associated transcripts, tRNA abundance, and protein levels) in two Arabidopsis thaliana accessions to evaluate how genomic information propagates through the Central Dogma. Codon usage in gene sequences emerged as the strongest predictor of both mRNA and protein abundance, while methylation, tRNA levels, and ribosome‑associated transcripts contributed little additional information under stable conditions.

The study presents the first thermal performance curve for the duckweed Wolffia globosa, identifying an optimal constant growth temperature of ~32 °C and showing that projected mean temperature increases under a high‑emissions scenario would not significantly affect growth under constant conditions. However, simulated heat‑wave temperature fluctuations markedly reduce growth rates due to increased frond mortality, suggesting that while W. globosa can recover quickly, extreme temperature variability may limit its productivity.

The study performed a comprehensive computational analysis of the Arabidopsis thaliana proteome, classifying 48,359 proteins by melting temperature (Tm) and melting temperature index (TI) and linking thermal stability to amino acid composition, molecular mass, and codon usage. Machine‑learning and evolutionary analyses revealed that higher molecular mass and specific codon pairs correlate with higher Tm, and that gene duplication has driven the evolution of high‑Tm proteins, suggesting a genomic basis for stress resilience.