Two sub-annual timescales and coupling modes for terrestrial water and carbon cycles.

To bridge the knowledge gap between (a) our (instantaneous-to-seasonal-scale) process understanding of plants and water and (b) our projections of long-term coupled feedbacks between the terrestrial water and carbon cycles, we must uncover what the dominant dynamics are linking fluxes of water and carbon. This study uses the simplest empirical dynamical systems models-two-dimensional linear models-and observation-based data from satellites, eddy covariance towers, weather stations, and machine-learning-derived products to determine the dominant sub-annual timescales coupling carbon uptake and (normalized) evaporation fluxes. We find two dominant modes across the Contiguous United States: (1) a negative correlation timescale on the order of a few days during which landscapes dry after precipitation and plants increase their carbon uptake through photosynthetic upregulation. (2) A slow, seasonal-scale positive covariation through which landscape drying leads to decreased growth and carbon uptake. The slow (positively correlated) process dominates the joint distribution of local water and carbon variables, leading to similar behaviors across space, biomes, and climate regions. We propose that vegetation cover/leaf area variables link this behavior across space, leading to strong emergent spatial patterns of water/carbon coupling in the mean. The spatial pattern of local temporal dynamics-positively sloped tangent lines to a convex long-term mean-state curve-is surprisingly strong, and can serve as a benchmark for coupled Earth System Models. We show that many such models do not represent this emergent mean-state pattern, and hypothesize that this may be due to lack of water-carbon feedbacks at daily scales.

The relationship between CXCR6+CD8+T cells and clinicopathological parameters in patients with primary biliary cholangitis.

BACKGROUND: CXCR6+CD8+T cells have been implicated in the pathogenesis of various liver and autoimmune diseases. However, their involvement in primary biliary cholangitis (PBC) has not been elucidated. METHODS: We used immunohistochemistry and flow cytometry to quantify CXCR6+CD8+T cells in hepatic tissue and peripheral blood samples obtained from CXCR6+CD8+T cells obtained from PBC patients. Then, we performed comprehensive statistical analyses to access the correlation between the abundance of these cells and clinical as well as pathological data across different stages of PBC. RESULTS: Our research revealed that CXCR6+ cell frequencies in CD3+CD8+T cells from PBC patients significantly exceeded that of healthy controls (HCs) (2.24 vs. 0.61%, p < 0.01). A similar pattern emerged for hepatic CXCR6+CD8+T cell counts, which were notably higher in the PBC cohort compared to HCs. Our cohort consisted of 118 PBC patients, categorized into 62 early-stage (E-PBC) and 56 late-stage (L-PBC) cases. Notably, significant disparities existed between these groups in terms of liver enzyme and lipid profile levels (p < 0.05), with no notable differences observed in gender, age, blood counts, cholesterol levels, or autoantibodies (p > 0.05). Intriguingly, the quantity of hepatic CXCR6+CD8+T cells per high power field (HPF) was significantly elevated in both E-PBC and L-PBC patients as opposed to normal liver samples, indicating a substantial increase in these cells across all stages of PBC (p = 0.000). Spearman's rank correlation analysis showed a positive correlation between CXCR6+CD8+T cell counts and serum levels of Alkaline Phosphatase (AKP) and Gamma-Glutamyl Transferase (GGT), ANA, IgG and IgM, while revealing a negligible correlation with Alanine Aminotransferase (ALT) and Aspartate Aminotransferase (AST). Subsequent findings indicated significant variances in CXCR6+ cell numbers not only among different PBC stages but also across various degrees of inflammation and fibrosis (p ≤ 0.007). In a follow-up study post-Ursodeoxycholic Acid (UDCA) treatment, stark differences were identified in biochemical and immunohistochemical profiles between responder (31 patients) and non-responder (33 patients) groups (p < 0.05). A Wilcoxon rank-sum test further demonstrated a significant difference in the level of hepatic CXCR6+CD8+T cells between these two response groups (p = 0.002). CONCLUSION: CXCR6+CD8+T cells play a vital role in the pathogenesis of PBC, exhibiting correlations with the extent of inflammation, staging of liver fibrosis, and response to pharmacological interventions in PBC patients.

AppleQSM: Geometry-Based 3D Characterization of Apple Tree Architecture in Orchards.

The architecture of apple trees plays a pivotal role in shaping their growth and fruit-bearing potential, forming the foundation for precision apple management. Traditionally, 2D imaging technologies were employed to delineate the architectural traits of apple trees, but their accuracy was hampered by occlusion and perspective ambiguities. This study aimed to surmount these constraints by devising a 3D geometry-based processing pipeline for apple tree structure segmentation and architectural trait characterization, utilizing point clouds collected by a terrestrial laser scanner (TLS). The pipeline consisted of four modules: (a) data preprocessing module, (b) tree instance segmentation module, (c) tree structure segmentation module, and (d) architectural trait extraction module. The developed pipeline was used to analyze 84 trees of two representative apple cultivars, characterizing architectural traits such as tree height, trunk diameter, branch count, branch diameter, and branch angle. Experimental results indicated that the established pipeline attained an R2 of 0.92 and 0.83, and a mean absolute error (MAE) of 6.1 cm and 4.71 mm for tree height and trunk diameter at the tree level, respectively. Additionally, at the branch level, it achieved an R2 of 0.77 and 0.69, and a MAE of 6.86 mm and 7.48° for branch diameter and angle, respectively. The accurate measurement of these architectural traits can enable precision management in high-density apple orchards and bolster phenotyping endeavors in breeding programs. Moreover, bottlenecks of 3D tree characterization in general were comprehensively analyzed to reveal future development.

Constraining long-term model predictions for woody growth using tropical tree rings.

The strength and persistence of the tropical carbon sink hinges on the long-term responses of woody growth to climatic variations and increasing CO2 . However, the sensitivity of tropical woody growth to these environmental changes is poorly understood, leading to large uncertainties in growth predictions. Here, we used tree ring records from a Southeast Asian tropical forest to constrain ED2.2-hydro, a terrestrial biosphere model with explicit vegetation demography. Specifically, we assessed individual-level woody growth responses to historical climate variability and increases in atmospheric CO2 (Ca ). When forced with historical Ca , ED2.2-hydro reproduced the magnitude of increases in intercellular CO2 concentration (a major determinant of photosynthesis) estimated from tree ring carbon isotope records. In contrast, simulated growth trends were considerably larger than those obtained from tree rings, suggesting that woody biomass production efficiency (WBPE = woody biomass production:gross primary productivity) was overestimated by the model. The estimated WBPE decline under increasing Ca based on model-data discrepancy was comparable to or stronger than (depending on tree species and size) the observed WBPE changes from a multi-year mature-forest CO2 fertilization experiment. In addition, we found that ED2.2-hydro generally overestimated climatic sensitivity of woody growth, especially for late-successional plant functional types. The model-data discrepancy in growth sensitivity to climate was likely caused by underestimating WBPE in hot and dry years due to commonly used model assumptions on carbon use efficiency and allocation. To our knowledge, this is the first study to constrain model predictions of individual tree-level growth sensitivity to Ca and climate against tropical tree-ring data. Our results suggest that improving model processes related to WBPE is crucial to obtain better predictions of tropical forest responses to droughts and increasing Ca . More accurate parameterization of WBPE will likely reduce the stimulation of woody growth by Ca rise predicted by biosphere models.