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Dryness stress can limit vegetation growth and is often characterized by low soil moisture (SM) and high atmospheric water demand (vapor pressure deficit, VPD). However, the relative role of SM and VPD in limiting ecosystem production remains debated and is difficult to disentangle, as SM and VPD are coupled through land-atmosphere interactions, hindering the ability to predict ecosystem responses to dryness. Here, we combine satellite observations of solar-induced fluorescence with estimates of SM and VPD and show that SM is the dominant driver of dryness stress on ecosystem production across more than 70% of vegetated land areas with valid data. Moreover, after accounting for SM-VPD coupling, VPD effects on ecosystem production are much smaller across large areas. We also find that SM stress is strongest in semi-arid ecosystems. Our results clarify a longstanding question and open new avenues for improving models to allow a better management of drought risk. Dryness stresses vegetation and can lead to declines in productivity, increased emission of carbon, and plant mortality, but the drivers of this stress remain unclear. Here the authors show that soil moisture plays a dominant role relative to atmospheric water demand over most global land vegetated areas.

As a region susceptible to the impacts of climate change, evaluating the temporal and spatial variations in ecological environment quality (EEQ) and potential influencing factors is crucial for ensuring the ecological security of the Tibetan Plateau. This study utilized the Google Earth Engine (GEE) platform to construct a Remote Sensing-based Ecological Index (RSEI) and examined the temporal and spatial dynamics of the Tibetan Plateau’s EEQ from 2000 to 2022. The findings revealed that the RSEI of the Tibetan Plateau predominantly exhibited a slight degradation trend from 2000 to 2022, with a multi-year average of 0.404. Utilizing SHAP (Shapley Additive Explanation) to interpret XGBoost (eXtreme Gradient Boosting), the study identified that natural factors as the primary influencers on the RSEI of the Tibetan Plateau, with temperature, soil moisture, and precipitation variables exhibiting higher SHAP values, indicating their substantial contributions. The interaction between temperature and precipitation showed a positive effect on RSEI, with the SHAP interaction value increasing with rising precipitation. The methodology and results of this study could provide insights for a comprehensive understanding and monitoring of the dynamic evolution of EEQ on the Tibetan Plateau amidst the context of climate change.

The biophysical effects of forests on climate have been extensively studied with climate models. However, models cannot accurately reproduce local climate effects due to their coarse spatial resolution and uncertainties, and field observations are valuable but often insufficient due to their limited coverage. Here we present new evidence acquired from global satellite data to analyse the biophysical effects of forests on local climate. Results show that tropical forests have a strong cooling effect throughout the year; temperate forests show moderate cooling in summer and moderate warming in winter with net cooling annually; and boreal forests have strong warming in winter and moderate cooling in summer with net warming annually. The spatiotemporal cooling or warming effects are mainly driven by the two competing biophysical effects, evapotranspiration and albedo, which in turn are strongly influenced by rainfall and snow. Implications of our satellite-based study could be useful for informing local forestry policies. Local climatic effects of forests remain poorly understood due to the coarse spatial resolution of models and field observations. Here, the authors use global satellite data to analyse the spatiotemporal cooling or warming effects of tropical, temperate and boreal forests on climate.

Changes in vegetation activity are driven by multiple natural and anthropogenic factors, which can be reflected by Normalized Difference Vegetation Index (NDVI) derived from satellites. In this paper, NDVI trends from 1982 to 2012 are first estimated by the Theil–Sen median slope method to explore their spatial and temporal patterns. Then, the impact of climate variables and human activity on the observed NDVI trends is analyzed. Our results show that on average, NDVI increased by 0.46 × 10−3 per year from 1982 to 2012 globally with decadal variations. For most regions of the world, a greening (increasing)–browning (decreasing)–greening (G-B-G) trend is observed over the periods 1982–2004, 1995–2004, and 2005–2012, respectively. A positive partial correlation of NDVI and temperature is observed in the first period but it decreases and occasionally becomes negative in the following periods, especially in the Humid Temperate and Dry Domain Regions. This suggests a weakened effect of temperature on vegetation growth. Precipitation, on the other hand, is found to have a positive impact on the NDVI trend. This effect becomes stronger in the third period of 1995–2004, especially in the Dry Domain Region. Anthropogenic effects and human activities, derived here from the Human Footprint Dataset and the associated Human Influence Index (HII), have varied impacts on the magnitude (absolute value) of the NDVI trends across continents. Significant positive effects are found in Asia, Africa, and Europe, suggesting that intensive human activity could accelerate the change in NDVI and vegetation. A more accurate attribution of vegetation change to specific climatic and anthropogenic factors is instrumental to understand vegetation dynamics and requires further research.

Mega-urban agglomerations are strategic core areas for national economic development and the main regions of new urbanization. They also have important roles in shifting the global economic center of gravity to China. However, the development of mega-urban agglomerations has triggered the interactive coercion between resources and the eco-envi- ronment. The interactive coupled effects between urbanization and the eco-environment in mega-urban agglomerations represent frontier and high-priority research topics in the field of Earth system science over the next decade. In this paper, we carried out systematic theo- retical analysis of the interactive coupling mechanisms and coercing effects between ur- banization and the eco-environment in mega-urban agglomerations. In detail, we analyzed the nonlinear-coupled relationships and the coupling characteristics between natural and human elements in mega-urban agglomerations. We also investigated the interactive coercion intensities between internal and external elements, and the mechanisms and patterns of local couplings and telecouplings in mega-urban agglomeration systems, which are affected by key internal and external control elements. In addition, we proposed the interactive coupling theory on urbanization and the eco-environment in mega-urban agglomerations. Furthermore we established a spatiotemporal dynamic coupling model with multi-element, multi-scale, multi-scenario, multi-module and multi-agent integrations, which can be used to develop an intelligent decision support system for sustainable development of mega-urban agglomera- tions. In general, our research may provide theoretical guidance and method support to solve problems related to mega-urban agglomerations and maintain their sustainable development.

Summary Grain weight is the most important component of rice yield and is mainly determined by grain size, which is generally controlled by quantitative trait loci (QTLs). Although numerous QTLs that regulate grain weight have been identified, the genetic network that controls grain size remains unclear. Herein, we report the cloning and functional analysis of a dominant QTL, grain length and width 2 (GLW2), which positively regulates grain weight by simultaneously increasing grain length and width. The GLW2 locus encodes OsGRF4 (growth‐regulating factor 4) and is regulated by the microRNA miR396c in vivo. The mutation in OsGRF4 perturbs the OsmiR396 target regulation of OsGRF4, generating a larger grain size and enhanced grain yield. We also demonstrate that OsGIF1 (GRF‐interacting factors 1) directly interacts with OsGRF4, and increasing its expression improves grain size. Our results suggest that the miR396c‐OsGRF4‐OsGIF1 regulatory module plays an important role in grain size determination and holds implications for rice yield improvement.

Keratoconus (KC) is an irreversible blinding eye disease; therefore, early screening of KC suspects (KCS) is crucial for protecting patients’ quality of life. Scheimpflug imaging is a commonly used screening device in clinical practice. We aimed to evaluate the diagnostic ability of a Scheimpflug imaging device (Scansys) for KC and KCS and compared it with other Scheimpflug-based devices (Pentacam and Corvis ST). This prospective case-control study included 107 normal eyes, 72 KCS, and 57 KC. Scansys screening index Keratoconus probability (KCP) showed excellent performance in diagnosing KC at a cutoff value of 16.4 (area under the receiver operating characteristic [AUROC] = 1.000), with 100% sensitivity and 98.11% specificity. KCP had a better KCS diagnostic ability at a cutoff value of 8.9 (AUROC = 0.813) than Corvis biomechanical index (CBI, AUROC = 0.764), reaching 67.61% sensitivity and 85.85% specificity. Pentacam screening index Belin/Ambrósio enhanced ectasia display deviation (BAD-D) showed the best performance with 92.96% sensitivity and 89.62% specificity at a cutoff value of 1.525 (AUROC = 0.970) in diagnosing KCS. Scansys provides accurate KCP parameters in diagnosing KC; however, the efficiency of diagnosing KCS should be further optimized.

The Tibetan grassland social-ecological systems are widely held to be highly vulnerable to climate change. We aim to investigate livelihood adaptation strategies of herder households and the types of local institutions that shaped those adaptation strategies. We examined the barriers and opportunities for strengthening adaptive capacity of local herder communities. We designed and implemented a household survey in the herder communities of northern Tibet. The survey results showed that migratory grazing has become less feasible. Storage, diversification, and market exchange have become the dominant adaptation strategies. The adaptation strategies of local herders have been reshaped by local institutional change. Local governmental and market institutions played the dominant roles in reshaping climate adaptation strategies. Although the present livelihood adaption strategies related to sedentary grazing have improved productivity and profitability of the herding livelihood, they have led to continuous deterioration of pastures. The local grazing system has become more and more dependent on artificial feeding and inputs from outside the grazing system. Purchasing forage has become one of the dominant adaptation strategies of local herder households. Multilevel regression modeling of this adaptation behavior showed that explanatory variables related to climate variability, household capital, and local institutional arrangements had statistically significant relationships with the adoption of this adaptation strategy. The results implies that building household capital and promoting the coordination among local governmental, market, and communal institutions are critical for strengthening adaptive capacity of the Tibetan herder communities.

Fitness cost is a common phenomenon in rice blast disease-resistance breeding. MiR396 is a highly conserved microRNA (miRNA) family targeting Growth Regulating Factor ( OsGRF ) genes. Mutation at the target site of miR396 in certain OsGRF gene or blocking miR396 expression leads to increased grain yield. Here we demonstrated that fitness cost can be trade-off in miR396- OsGRF s module via balancing growth and immunity against the blast fungus. The accumulation of miR396 isoforms was significantly increased in a susceptible accession, but fluctuated in a resistant accession upon infection of Magnaporthe oryzae . The transgenic lines over-expressing different miR396 isoforms were highly susceptible to M. oryzae . In contrast, overexpressing target mimicry of miR396 to block its function led to enhanced resistance to M. oryzae in addition to improved yield traits. Moreover, transgenic plants overexpressing OsGRF6 , OsGRF7 , OsGRF8 , and OsGRF9 exhibited enhanced resistance to M. oryzae , but showed different alteration of growth. While overexpression of OsGRF7 led to defects in growth, overexpression of OsGRF6 , OsGRF8 , and OsGRF9 resulted in better or no significant change of yield traits. Collectively, our results indicate that miR396 negatively regulates rice blast disease- resistance via suppressing multiple OsGRF s, which in turn differentially control growth and yield. Therefore, miR396- OsGRFs could be a potential module to demolish fitness cost in rice blast disease-resistance breeding.

Rhizoctonia solani is a major fungal pathogen of rice ( Oryza sativa L. ) that causes great yield losses in all rice-growing regions of the world. Here we report the draft genome sequence of the rice sheath blight disease pathogen, R. solani AG1 IA, assembled using next-generation Illumina Genome Analyser sequencing technologies. The genome encodes a large and diverse set of secreted proteins, enzymes of primary and secondary metabolism, carbohydrate-active enzymes, and transporters, which probably reflect an exclusive necrotrophic lifestyle. We find few repetitive elements, a closer relationship to Agaricomycotina among Basidiomycetes, and expand protein domains and families. Among the 25 candidate pathogen effectors identified according to their functionality and evolution, we validate 3 that trigger crop defence responses; hence we reveal the exclusive expression patterns of the pathogenic determinants during host infection. The rice sheath blight pathogen, Rhizoctonia solani, is an important fungal pathogen that can devastate rice and maize crops. Zheng and colleagues sequence and assemble the R. solani AG1 IA genome—the first to be sequenced from the Rhizoctonia genus—using Illumina sequencing technology.