Northeast Institute of Geography and Agroecology

Plant architecture, including plant height, tiller number, and leaf angle, is a critical determinant of rice yield. However, few genes have been identified that simultaneously regulate these traits and hold breeding value. We have previously shown that OsWRKY53 regulates the plant height and leaf angle via BR signalling. Here, we establish OsWRKY53 as a novel negative regulator of tillering in rice. The oswrky53 mutant exhibits a semi-dwarf stature coupled with increased tiller number, representing a promising agronomic combination. Genetic and molecular analyses reveal that OsWRKY53 acts as a direct transcriptional activator of OsTB1, thereby suppressing tiller formation. In addition, we found OsWRKY53 physically interacts with OsGT1, and their cooperative action synergistically enhances OsTB1 expression and suppresses tiller number. Intriguingly, the oswrky53 mutant exhibits reduced sensitivity to Strigolactone (SL) and increased SL contents. We further demonstrate that SL promotes degradation of OsWRKY53, and D53 interacts with and stabilises the OsWRKY53. Simultaneously, OsWRKY53 negatively regulates SL biosynthesis, enabling OsWRKY53 to function as a fine-tuning regulator in the SL signalling pathway. Furthermore, OsGT1 exhibits subspecies-specific regulation, with indica accessions carrying the OsGT1581T allele showing significantly enhanced tillering capacity compared to japonica varieties. These findings collectively reveal the mechanism by which OsWRKY53 regulates the formation of tillers in rice, providing new genetic targets for semi-dwarf and high-tillering rice breeding.

Accurate crop classification is critical for optimizing agricultural resource use and informing production decisions. Deep learning, with its robust feature extraction ability, has become a prevalent technique for remote sensing-based crop classification. However, agricultural landscape complexity poses three key challenges: background noise interference, class confusion from inter-crop spectral similarity, and blurred small-area crop boundaries due to class imbalance. This paper proposes FCR-TransUNet, a TransUNet-based enhanced model integrating three modules: Feature Enhancement Module (FEM) for noise filtering, Class-Attention (CAExperimental results on the Youyi Farm and barley datasets validate the superiority of the proposed model. On the Youyi Farm dataset, FCR-TransUNet achieves an MIoU of 92.2%, representing an improvement of 1.8% over SAM2-UNet and 2.9% over the baseline TransUNet. On the barley dataset, it yields an MIoU of 89.9%. Ablation studies further verify the effectiveness of each designed module. To comprehensively evaluate the classification performance of FCR-TransUNet across the full crop growth cycle, experiments were conducted using remote sensing images from May, July, and August, respectively. The results demonstrate that FCR-TransUNet exhibits strong stability and adaptability at different crop growth stages, providing a reliable solution for precision agriculture and intelligent agricultural production.

Abstract Rivers are increasingly fragmented and degraded, yet the European Union Nature Restoration Regulation calls for restoring at least 25,000 kilometres of free-flowing rivers by 2030. Translating this ambition into effective implementation remains challenging because restoration priorities differ across ecological, social, economic, and governance contexts. Here, we synthesize expert knowledge from 45 countries through a structured, multi-step prioritization process to identify research priorities for restoring free-flowing rivers in Europe. We identified 27 priorities and analysed how expert background and spatial context influenced their ranking. Restoration priorities differed systematically depending on whether experts emphasized ecological integrity, community engagement, economic considerations, or governance capacity, revealing clear patterns in how disciplinary and professional perspectives shape implementation pathways. This demonstrates that restoration strategies cannot be universal but must be adapted to local and regional political, institutional, and ecological conditions. Building on these findings, we propose a structured prioritisation framework that links barrier removal, connectivity restoration, governance mechanisms, and policy instruments to context-specific needs. Together, our results provide an empirically grounded and implementation-oriented roadmap to support European Union Member States in delivering ambitious river restoration targets in a context-sensitive and socially robust manner.

Shifts in tree water sources are important for understanding the spatiotemporal dynamics of ecosystem water fluxes. However, our understanding of tree water uptake remains limited, constraining reliable predictions of local and global hydrological processes under ongoing climate change. The isotopic composition of water (δ2H and δ18O) is a powerful tracer of the Earth’s water cycle, as isotopic differences among water reservoirs, together with mixing and fractionation processes, allow water movements to be traced across the hydraulic continuum.This study aims to characterize the tree water sources of Scots pine (Pinus sylvestris L.) in a Mediterranean forest (Pyrenees, NE Spain) during the 2024 growing season. To do so, the isotopic composition of water in several ecohydrological compartments was measured. Precipitation, soil water pools at multiple depths (10, 20, 30, 40, and 60 cm), and xylem water from four individuals were sampled biweekly. Bulk soil water was extracted using cryogenic vacuum distillation, whereas xylem water was obtained using a flow-rotor centrifuge (cavitron). The cavitron enables access to mobile xylem water (e.g., sap) and is not affected by the well-known methodological artifacts associated with cryogenic extraction. Bayesian isotope mixing models were applied to quantify the relative contributions of distinct water pools to xylem water and their temporal evolution. Dynamics of total water uptake were estimated from transpiration data.Our results show that Scots pine predominantly relied on shallow soil water (10 cm) during most of the growing season, with xylem water closely reflecting the isotopic signature of recent precipitation. A decoupling between the isotopic signature of precipitation and xylem water emerged as seasonal drying progressed. Under dry conditions, tree water uptake was low, and tree water sources shifted towards deeper soil layers (40-60 cm). Overall, these patterns indicate a strong coupling between rainfall inputs and tree water use during periods of high transpiration demand, suggesting that the contribution of deeper soil water reserves represent only a very small fraction of tree total water use during a growing season. These findings underscore the ecological importance of shallow soil water and recent precipitation in sustaining forest function and highlight the role of vegetation water use in regulating atmospheric water fluxes.