Global distribution pattern in characteristics of gross primary productivity response to soil water availability

Funding Information: The study is supported by the National Key Research and Development Program of China (No. 2022YFB3903300 ), the Second Tibetan Plateau Scientific Expedition and Research Program (STEP) \u201C Dynamic monitoring and simulation of water cycle in Asian water tower area \u201D (No. 2019QZKK0206 ), and the Youth Innovation Funding of the National Space Science Center, Chinese Academy of Sciences. This work used eddy covariance data acquired and shared by the FLUXNET community, including these networks: AmeriFlux, AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet-Canada, GreenGrass, ICOS, KoFlux, LBA, NECC, OzFlux-TERN, TCOS-Siberia, and USCCC. The FLUXNET eddy covariance data processing and harmonization was carried out by the ICOS Ecosystem Thematic Center, AmeriFlux Management Project and Fluxdata project of FLUXNET, with the support of CDIAC, and the OzFlux, ChinaFlux and AsiaFlux offices. Publisher Copyright: © 2025 The Author(s). Published by Elsevier B.V.Understanding how carbon assimilation rates respond to water availability is crucial for diagnosing global carbon and water cycles. This study aims to investigate characteristics and drivers of gross primary productivity (GPP) responses to soil water availability using three parameters from a light-use-efficiency (LUE) model: WI, kW and αW, representing the inflection point, slope and lag effect of GPP response to soil water availability changes, respectively. We followed a hybrid modeling approach coupling an artificial neural network with the LUE model to derive model parameters and examine intricate relationships between these parameters and features characterizing climate, vegetation, nutrient deposition, soil properties and elevation across 196 eddy covariance sites. Relationships between the LUE model parameters and observed ecosystem properties were analyzed using partial dependence plots and Shapley additive explanation dependence plots. Our results revealed significant statistical differences in parameters across plant functional types. Specifically, forests exhibited lower inflection points, responding more steeply and immediately to water availability changes, contrasting with smoother and lagged responses from open shrubs. Vegetation seasonality, represented by variability of enhanced vegetation index (EVI) and seasonal EVI, was the most influential noncategorical factor, followed by soil properties. Notably, the relationships were predominantly nonlinear. Additionally, older forest ecosystems generally showed lower vulnerability while responding more steeply to relative soil water availability changes than younger forests. While aridity was less influential on parameter variability than anticipated, aridity seasonality was a primary driver for the inflection point. High temperatures and substantial diurnal and annual temperature ranges were linked to pronounced lag effects. Despite these findings, challenges remain regarding model accuracy on annual scales, parameter uncertainties and interactions between features. Overall, this study underscores the spatial heterogeneity of GPP responses to soil water availability and highlights the importance of considering variability in model parameters and GPP sensitivities across space and time.publishersversionpublishe

Simulation of Pseudostellaria heterophylla distribution in China: assessing habitat suitability and bioactive component abundance under future climate change scenariosplant components

BackgroundPseudostellaria heterophylla is used in traditional Chinese medicine, so ensuring an adequate supply of plant material with high levels of bioactive components is important.MethodsUsing an optimized maximum entropy niche model and assays of bioactive components from cultivation samples, this study started from the plant’s natural distribution area and estimated correlations of ecological factors with not only abundance of the plant but also abundance of polysaccharides and heterophyllin B. These correlations were combined with the spatial analysis function in ArcGIS to generate maps of the suitability of different habitats in China for cultivating P. heterophylla under current climate conditions and different models of climate change.ResultsThe following ecological factors emerged as particularly important for habitat suitability: precipitation of driest month and driest quarter, annual precipitation, annual mean temperature, temperature seasonality, and mean temperature of coldest quarter, contributing to a cumulative total of 87%. Under current climate conditions, optimum habitats of P. heterophylla were mainly distributed in the southwestern region (Guizhou) and eastern regions (Anhui, Zhejiang, Fujian, Jiangsu) of China, and only 0.197×106 km2 of these areas were optimum habitat. In future climate change scenarios, the optimal habitat area of P. heterophylla exhibited an increase across different time periods under the SSP5-8.5 climate scenario. By the 2090s, distribution area of high heterophyllin B content under SSP5-8.5 climate scenarios will increase significantly, distribution area of high polysaccharide content had little change under all three climate scenarios (SSP 1-2.6, 2-4.5, 5-8.5). The center of mass of suitable habitat migrates southwestward under scenario SSP 1-2.6 and SSP 2-4.5, while it migrates northward under scenario SSP 5-8.5. Under the three climate scenarios, the center of mass of suitable habitat migrated consistently with that of high polysaccharide content but differed from that of high heterophyllin B content.ConclusionThese findings provide a crucial foundation for cultivating P. heterophylla with superior medicinal properties, developing adaptive management strategies to enhance conservation efforts, and ensuring sustainable utilization in the face of global climate change

Heterologous booster vaccination enhances antibody responses to SARS-CoV-2 by improving Tfh function and increasing B-cell clonotype SHM frequency

Heterologous prime-boost has broken the protective immune response bottleneck of the COVID-19 vaccines. however, the underlying mechanisms have not been fully elucidated. Here, we investigated antibody responses and explored the response of germinal center (GC) to priming with inactivated vaccines and boosting with heterologous adenoviral-vectored vaccines or homologous inactivated vaccines in mice. Antibody responses were dramatically enhanced by both boosting regimens. Heterologous immunization induced more robust GC activation, characterized by increased Tfh cell populations and enhanced helper function. Additionally, increased B-cell activation and antibody production were observed in a heterologous regimen. Libra-seq was used to compare the differences of S1-, S2- and NTD-specific B cells between homologous and heterologous vaccination, respectively. S2-specific CD19+ B cells presented increased somatic hypermutations (SHMs), which were mainly enriched in plasma cells. Moreover, a heterologous booster dose promoted the clonal expansion of B cells specific to S2 and NTD regions. In conclusion, the functional role of Tfh and B cells following SARS-CoV-2 heterologous vaccination may be important for modulating antibody responses. These findings provide new insights for the development of SARS-CoV-2 vaccines that induce more robust antibody response

Effect of symbiotic fungi-Armillaria gallica on the yield of Gastrodia elata Bl. and insight into the response of soil microbial community

Armillaria members play important roles in the nutrient supply and growth modulation of Gastrodia elata Bl., and they will undergo severe competition with native soil organisms before colonization and become symbiotic with G. elata. Unraveling the response of soil microbial organisms to symbiotic fungi will open up new avenues to illustrate the biological mechanisms driving G. elata’s benefit from Armillaria. For this purpose, Armillaria strains from four main G. elata production areas in China were collected, identified, and co-planted with G. elata in Guizhou Province. The result of the phylogenetic tree indicated that the four Armillaria strains shared the shortest clade with Armillaria gallica. The yields of G. elata were compared to uncover the potential role of these A. gallica strains. Soil microbial DNA was extracted and sequenced using Illumina sequencing of 16S and ITS rRNA gene amplicons to decipher the changes of soil bacterial and fungal communities arising from A. gallica strains. The yield of G. elata symbiosis with the YN strain (A. gallica collected from Yunnan) was four times higher than that of the GZ strain (A. gallica collected from Guizhou) and nearly two times higher than that of the AH and SX strains (A. gallica collected from Shanxi and Anhui). We found that the GZ strain induced changes in the bacterial community, while the YN strain mainly caused changes in the fungal community. Similar patterns were identified in non-metric multidimensional scaling analysis, in which the GZ strain greatly separated from others in bacterial structure, while the YN strain caused significant separation from other strains in fungal structure. This current study revealed the assembly and response of the soil microbial community to A. gallica strains and suggested that exotic strains of A. gallica might be helpful in improving the yield of G. elata by inducing changes in the soil fungal community

Genome-wide association analysis identifies 30 new susceptibility loci for schizophrenia

We conducted a genome-wide association study (GWAS) with replication in 36,180 Chinese individuals and performed further transancestry meta-analyses with data from the Psychiatry Genomics Consortium (PGC2). Approximately 95% of the genome-wide significant (GWS) index alleles (or their proxies) from the PGC2 study were overrepresented in Chinese schizophrenia cases, including ∼50% that achieved nominal significance and ∼75% that continued to be GWS in the transancestry analysis. The Chinese-only analysis identified seven GWS loci; three of these also were GWS in the transancestry analyses, which identified 109 GWS loci, thus yielding a total of 113 GWS loci (30 novel) in at least one of these analyses. We observed improvements in the fine-mapping resolution at many susceptibility loci. Our results provide several lines of evidence supporting candidate genes at many loci and highlight some pathways for further research. Together, our findings provide novel insight into the genetic architecture and biological etiology of schizophrenia