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Attention mechanisms have significantly boosted the performance of video classification neural networks thanks to the utilization of perspective contexts. However, the current research on video attention generally focuses on adopting a specific aspect of contexts (e.g., channel, spatial/temporal, or global context) to refine the features and neglects their underlying correlation when computing attentions. This leads to incomplete context utilization and hence bears the weakness of limited performance improvement. To tackle the problem, this paper proposes an efficient attention-in-attention (AIA) method for element-wise feature refinement, which investigates the feasibility of inserting the channel context into the spatio-temporal attention learning module, referred to as CinST, and also its reverse variant, referred to as STinC. Specifically, we instantiate the video feature contexts as dynamics aggregated along a specific axis with global average and max pooling operations. The workflow of an AIA module is that the first attention block uses one kind of context information to guide the gating weights calculation of the second attention that targets at the other context. Moreover, all the computational operations in attention units act on the pooled dimension, which results in quite few computational cost increase (< 0.02%). To verify our method, we densely integrate it into two classical video network backbones and conduct extensive experiments on several standard video classification benchmarks. The source code of our AIA is available at https://github.com/haoyanbin918/Attention-in-Attention. [ABSTRACT FROM AUTHOR]

In recent years, vision Transformers and MLPs have demonstrated remarkable performance in image understanding tasks. However, their inherently dense computational operators, such as self-attention and token-mixing layers, pose significant challenges when applied to spatio-temporal video data. To address this gap, we propose PosMLP-Video, a lightweight yet powerful MLP-like backbone for video recognition. Instead of dense operators, we use efficient relative positional encoding to build pairwise token relations, leveraging small-sized parameterized relative position biases to obtain each relation score. Specifically, to enable spatio-temporal modeling, we extend the image PosMLP’s positional gating unit to temporal, spatial, and spatio-temporal variants, namely PoTGU, PoSGU, and PoSTGU, respectively. These gating units can be feasibly combined into three types of spatio-temporal factorized positional MLP blocks, which not only decrease model complexity but also maintain good performance. Additionally, we enrich relative positional relationships by using channel grouping. Experimental results on three video-related tasks demonstrate that PosMLP-Video achieves competitive speed-accuracy trade-offs compared to the previous state-of-the-art models. In particular, PosMLP-Video pre-trained on ImageNet1K achieves 59.0%/70.3% top-1 accuracy on Something-Something V1/V2 and 82.1% top-1 accuracy on Kinetics-400 while requiring much fewer parameters and FLOPs than other models. The code is released at https://github.com/zhouds1918/PosMLP_Video. [ABSTRACT FROM AUTHOR]

Efficient action recognition aims to classify a video clip into a specific action category with a low computational cost. It is challenging since the integrated spatial-temporal calculation (e. g., 3D convolution) introduces intensive operations and increases complexity. This paper explores the feasibility of the integration of channel splitting and filter decoupling for efficient architecture design and feature refinement by proposing a novel spatio-temporal collaborative (STC) module. STC splits the video feature channels into two groups and separately learns spatio-temporal representations in parallel with decoupled convolutional operators. Particularly, STC consists of two computation-efficient blocks, i.e., $\text {S}_{\mathrm{ T}}$ and $\text {T}_{\mathrm{ S}}$ , where they extract either spatial (${S}_{\cdot }$) or temporal (${T}_{\cdot }$) features and further refine their features with either temporal ($\cdot _{T}$) or spatial ($\cdot _{S}$) contexts globally. The spatial/temporal context refers to information dynamics aggregated from temporal/spatial axis. To thoroughly examine our method’s performance in video action recognition tasks, we conduct extensive experiments using five video benchmark datasets requiring temporal reasoning. Experimental results show that the proposed STC networks achieve a competitive trade-off between model efficiency and effectiveness. [ABSTRACT FROM AUTHOR]

• Precipitation was repackaged to simulate 4-level of precipitation variability. • Extra-extreme precipitation variability scenario potentially reduced N 2 O emissions. • Effects of precipitation variability on N 2 O fluxes had high interannual variations. • Soil, microbes, functional genes, and plants explained 61% variation in N 2 O fluxes. High temporal precipitation variability, characterized by less frequent but larger-magnitude precipitation events, is increasing. However, how precipitation variability affects N 2 O emissions and the underlying mechanisms remain unclear, especially at multiple-year scales. We conducted a 3-year manipulative experiment in which the same long-term mean growing season precipitation total was repackaged into events of inversely varying magnitude and frequency to simulate four levels of precipitation variability (extra-extreme, extreme, medium, and normal) in a semiarid grassland. Cumulative N 2 O emissions was the smallest under the extra-extreme precipitation variability scenario (6 very large rainfall events), 26% less than emission under the other three treatments (10, 16, and 24 rainfall events) over the three growing seasons. However, this difference was almost entirely due to three sampling events in the third year. Plant community (biomass and biodiversity), soil abiotic properties (water, dissolved organic carbon and pH), soil microbial biomass (carbon, nitrogen and the ratio), and soil functional genes (archaeal and bacterial amoA, nirS, nirK, narG , and nosZ) explained 61% of the variation in N 2 O emissions in response to the precipitation variability. Structural equation modelling indicated that the precipitation variability had direct positive effects, and indirect negative effects via soil abiotic properties, on soil functional genes that ultimately had positive effects on N 2 O emissions. The reduction in N 2 O emission in the extra-extreme precipitation variability scenario in the third year was due to low levels of soil water content, soil pH, aboveground biomass, and microbial biomass carbon simultaneously. Our results suggest that at the multi-year timescale, semiarid grasslands may have negative feedbacks to future precipitation regimes with higher variability. [Display omitted] [ABSTRACT FROM AUTHOR]

Sentiment analysis is an important topic concerning identification of feelings, attitudes, emotions and opinions from text. To automate such analysis, a large amount of example text needs to be manually annotated for model training. This is laborious and expensive, but the cross-domain technique is a key solution to reducing the cost by reusing annotated reviews across domains. However, its success largely relies on the learning of a robust common representation space across domains. In the recent years, significant effort has been invested to improve the cross-domain representation learning by designing increasingly more complex and elaborate model inputs and architectures. We support that it is not necessary to increase design complexity as this inevitably consumes more time in model training. Instead, we propose to explore the word polarity and occurrence information through a simple mapping and encode such information more accurately whilst managing lower computational costs. The proposed approach is unique and takes advantage of the stochastic embedding technique to tackle cross-domain sentiment alignment. Its effectiveness is benchmarked with over ten data tasks constructed from two review corpora and it is compared against ten classical and state-of-the-art methods. [ABSTRACT FROM AUTHOR]

• Seasonal timing strongly regulates the response of N 2 O emissions to extreme droughts. • Early drought affected N 2 O emission with high interannual variability. • Middle drought consistently suppressed N 2 O emissions. • Late drought had little effect on N 2 O fluxes. Terrestrial ecosystems are important sources of nitrous oxide (N 2 O), a powerful greenhouse gas which can be strongly impacted by increasing droughts in association with climate change. However, detailed information on whether and how drought timing regulates N 2 O fluxes is still lacking. Here, we conducted a 3-year field experiment on a semiarid grassland in which extreme drought was imposed in either early-, mid-, or late-growing seasons repeatedly from 2014 to 2016. We found that early drought affected N 2 O emission with high interannual variability (increased, decreased and unchanged N 2 O emission in 2014, 2015, and 2016, respectively), coincident with changes in inorganic nitrogen (SIN), dissolve organic carbon (DOC), microbial biomass carbon (MBC), and soil functional genes (bacterial amoA , nirK , nirS , and nosZ). However, middle drought consistently suppressed N 2 O emissions due to simultaneous decreases in MBC, DOC and the abundances of archaeal amoA , nirK , and narG genes , causing the largest reduction in N 2 O emissions across the three years. In contrast, late drought had little effect on N 2 O fluxes, even though DOC and SIN decreased and the abundance of nirK , nirS , and nosZ increased. As a result, soil organic C and mineral N availability and functional gene abundances were not always robust factors for predicting N 2 O emissions under droughts across all treatments, except for abundance of AOA and nosZ. Our results highlight the vital role of seasonal timing in regulating the response of N 2 O emissions to extreme droughts. [ABSTRACT FROM AUTHOR]

Rising ambient temperature is expected to increase incidence of bacillary dysentery (BD), but few studies have compared the temperature-BD effects of different age groups and cities in China, especially in a multi-city setting. We used city-specific data including BD cases and meteorological variables to determine the relationship between BD incidence and temperature at provincial level. Weekly BD disease surveillance data and meteorological variables were collected in all 16 prefecture-level cities in Anhui Province of China. Firstly, city-specific weekly mean temperature-BD incidence associations were estimated with Distributed Lag Nonlinear Model (DLNM). Secondly, city-specific estimates were pooled at province-level through multivariate meta-analysis. Also, we conducted subgroup analyses for ages (children <5 years old and population of other ages) and urbanization of cities (high and low level), respectively. In Anhui, BD morbidity risk increased with increasing weekly mean temperature. Relative risks (RR) at the 90th percentile (27.5 °C) versus the 50th percentile (17 °C) of weekly mean temperature were 1.42 (95% confidence interval (CI): 1.16, 1.75) and 2.02 (95% CI: 1.76, 2.32) for children <5 and population of other ages, respectively. The relative risk of high temperature on other ages group was higher than that of children under five years old (p = 0.006). Children under 5 in high urbanized cities appeared to be more vulnerable to the effects of ambient high temperature (RR: 1.56, 95% CI: 1.20, 1.92) than in low urbanized cities (RR: 1.01, 95% CI: 0.70, 1.46), the difference between two intervals was statistically significant (p = 0.044). This study suggests that high temperatures may be an important trigger of BD incidence, and especially lead to a substantial burden of BD for high urbanized cities in Anhui Province of China. Unlabelled Image • High weekly mean temperature increased risks of bacillary dysentery (BD) in Anhui. • Urbanization level modified associations between high temperature and BD incidence. • For children <5, effect of high temperature on BD increased in high urbanized cities. [ABSTRACT FROM AUTHOR]

Highlights • Grazing interacted extreme drought timing to regulate steppe ecosystem CO 2 exchange. • Extreme drought reduced CO 2 uptake in a fenced steppe regardless of seasonal timing. • Early-season drought caused largest declines in CO 2 uptake in a grazed steppe. Abstract Climate models predict a substantial increase in the frequency of extreme drought, suggesting subsequent impacts on the carbon (C) and water cycles. Although many studies have investigated the impacts of extreme drought on ecosystem functioning, it remains unknown how the timing of extreme drought within a growing season may affect carbon and water cycling. Here we conducted a 3-year field experiment to investigate the influence of seasonal drought timing on ecosystem carbon and water exchange by excluding rainfall (for consecutive 30 days) during three periods of the growing season (May–June, July–August and August–September) in fenced and grazed sites of a semiarid temperate steppe in Inner Mongolia, China. In the fenced steppe, extreme drought reduced growing-season net CO 2 uptake regardless of drought timing, while in the grazed steppe, early-growing season drought caused relatively larger reductions to net CO 2 uptake than drought imposed later in the season. The effect of extreme drought on evapotranspiration (ET) was similar to that of CO 2 exchange at the fenced site, with consistent reductions of seasonally-integrated ET for all treatments compared with the ambient condition. In contrast, at the grazed site, the response of ET to extreme drought was more variable, possibly due to the absence of litter and greater bare ground. Surprisingly, both gross and net carbon uptake declined with increasing ET at the grazed site, while the fenced site showed the positive water-carbon linkage typically seen in semiarid ecosystems. The different responses of CO 2 and water exchanges for the fenced and grazed sites were regulated predominately by soil temperature and soil water content. Together, our results show that drought timing within the growing season can significantly alter drought impacts on ecosystem water and CO 2 exchanges, and that grazing management may further mediate the response. [ABSTRACT FROM AUTHOR]

• N 2 O flux is sensitive and insensitive to drought and heat wave, respectively. • Soil water content is a first-order predictor of seasonal variation of N 2 O flux. • Inter-annual variations of N 2 O flux are impacted by precipitation distribution. • Archaeal amoA and nirK mainly regulates climate extremes effects on N 2 O flux. Nitrous oxide (N 2 O), the third most important greenhouse gas, contributes to the increasing frequency and severity of climate extremes. Disentangling feedbacks of climate extremes on terrestrial N 2 O emission is important for forecasting future climate changes. Here, we experimentally imposed extreme drought and heat wave events during three years in a semiarid grassland to investigate the responses of N 2 O flux. We identified that N 2 O flux suppression during droughts was mediated by soil water content (SWC), microbial biomass carbon (MBC), soil inorganic nitrogen (SIN) and dissolved organic carbon (DOC) contents, and the abundance of archaeal amoA, nirK, and narG. However, bacterial amoA, nirS, and nosZ remained stable. Upon rewetting following droughts, the SWC, SIN, DOC, archaeal amoA, nirK, narG, and resultant N 2 O fluxes recovered to the magnitude of the ambient control. In contrast, heat waves alone or in combination with drought did not impact N 2 O fluxes or the underlying physical, chemical and microbial states. Stepwise multiple linear regression suggested that SWC, DOC, and MBC were the key factors regulating immediate responses of N 2 O flux to climate extremes while the major factors regulating seasonal mean N 2 O flux in response to climate extremes were archaeal amoA abundance, nirK abundance, and MBC. Our results suggest that N 2 O fluxes were sensitive to droughts but insensitive to heat waves. Soil moisture induced changes in substrate availability, and the community size of total and functional microorganisms in soil jointly regulated N 2 O responses to climate extremes. The relative importance of regulating factors shifted at different timescales. [ABSTRACT FROM AUTHOR]

Increasing heavy rainfalls can strongly affect ecosystem nitrogen (N) cycling processes and thereby alter soil N fluxes and pools. However, the effects of heavy rainfalls on soil N fluxes and pools are poorly understood, particularly with regards to high rainfall timing under field conditions. We conducted a 3-year (2014–2016) manipulative experiment in which heavy rainfall was imposed in middle (plant peak growing stage) or late (plant senescent growth stage) growing season in a semiarid grassland of Inner Mongolia, China to explore the responses of N 2 O fluxes and soil total N contents and the underlying microbial mechanisms. Mid-season heavy rainfall promoted soil N 2 O emissions by 65% on average across the three years, attributable mainly to increases in denitrifying nirK and nirS abundances induced large denitrification at higher soil water contents. However, archaeal and bacterial amoA and narG genes did not change significantly due probably to counteracting effects of increased soil water content (positive) and soil pH (negative). Mid-season heavy rainfall led to 17% reduction in soil total N by the end of the last year of the study (2016), partly due to the enhanced accumulated N 2 O emissions over the three years. In contrast, late-season heavy rainfall did not change N 2 O emissions and soil total N contents even though soil water content, soil pH and nirK and nirS abundance were significantly increased, perhaps due to limitation by low temperature. Timing of the heavy rainfall events during the plant growing season strongly influenced their impacts on soil N fluxes and pools and heavy rainfalls in the peak stage of plant growth may potentially cause a positive feedback to global warming and exacerbate N limitation in terrestrial ecosystems. • N 2 O flux and soil total N responses to heavy rainfall depended on seasonal timing. • Mid-season heavy rainfall increased N 2 O flux by 65% due to higher denitrification. • Enhanced N 2 O emissions coincided with 17% of reduction in soil total N. • Late-season heavy rainfall did not change N 2 O emissions and soil total N contents. [ABSTRACT FROM AUTHOR]

Highlights: [•] DNDC modeling qualified effects of altered precipitation patterns on fenced and grazed steppe. [•] Ecologically effective rainfall controls ecosystem CO2 sink/source functions. [•] Altered rainfall patterns had no significant effect on CO2 fluxes and plant productivity. [Copyright &y& Elsevier]

Abstract: We used an eddy covariance technique to measure evapotranspiration and carbon flux over two very different growing seasons for a typical steppe on the Inner Mongolia Plateau, China. The rainfall during the 2004 growing season (344.7mm) was close to the annual average (350.43mm). In contrast, precipitation during the 2005 growing season was significantly lower than average (only 126mm). The wet 2004 growing season had a higher peak evapotranspiration (4mmday−1) than did the dry 2005 growing season (3.3mmday−1). In 2004, latent heat flux was mainly a consumption resource for net radiation, accounting for ∼46% of net radiation. However, sensible heat flux dominated the energy budget over the whole growing season in 2005, accounting for 60% of net radiation. The evaporative rate (LE/R n) dropped by a factor of four from the non-soil stress to soil water limiting conditions. Maximum half-hourly CO2 uptake was −0.68mgm−2 s−1 and maximum ecosystem exchange was 4.3gCO2 m−2 day−1 in 2004. The 2005 drought growing stage had a maximum CO2 exchange value of only −0.22mgm−2 s−1 and a continuous positive integrated-daily CO2 flux over the entire growing season, i.e. the ecosystem became a net carbon source. Soil respiration was temperature dependent when the soil was under non-limiting soil moisture conditions, but this response declined with soil water stress. Water availability and a high vapor pressure deficit severely limited carbon fixing of this ecosystem; thus, during the growing season, the capacity to fix CO2 was closely related to both timing and frequency of rainfall events. [Copyright &y& Elsevier]

Abstract: In this study, we conducted eddy covariance (EC) measurements of water vapor exchange over a typical steppe in a semi-arid area of the Inner Mongolia Plateau, China. Measurement sites were located within a 25-year-old enclosure with a relatively low leaf area index (∼1.5m2 m−2) and dominated by Leymus chinensis. Energy balance closure was (H +LE)=17.09+0.69×(Rn− G) (W/m2; r 2 =0.95, n =6596). Precipitation during the two growing seasons of the study period was similar to the long-term average. The peak evapotranspiration in 2004 was 4mmd−1, and 3.5mmd−1 in 2003. The maximum latent heat flux was higher than the sensible heat flux, and the sensible heat flux dominated the energy budget at midday during the entire growing season in 2003; latent heat flux was the main consumption component for net radiation during the 2004 growing season. During periods of frozen soil in 2003 and 2004, the sensible heat flux was the primary consumption component for net radiation. The soil heat flux component was similar in 2003 and 2004. The decoupling coefficient (between 0.5 and 0.1) indicates that evapotranspiration was strongly controlled by saturation water vapor pressure deficit (VPD) in this grassland. The results of this research suggest that energy exchange and evapotranspiration were controlled by the phenology of the vegetation and soil water content. In addition, the amount and frequency of rainfall significantly affect energy exchange and evapotranspiration upon the Inner Mongolia plateau. [Copyright &y& Elsevier]

Aim: Species–area relationships (SAR) are widely utilized for estimating the species richness and its spatial turnover across various scales. Despite the prevalent characterization of SAR using the power law in many microbial community studies, its efficacy remains unvalidated. This study aims to characterize the microbial SAR and its mechanisms in alpine grassland soils on the Qinghai‐Tibet Plateau (QTP). Location: Qinghai‐Tibet Plateau, China. Time Period: August 2014. Major Taxa Studied: Soil bacteria. Methods: Soil samples were collected from five alpine grassland sites on the QTP. Employing a nested sampling strategy at each site, soil samples were collected in plot sizes ranging from 0.5 × 0.5 m2 to 2048 × 2048 m2. Soil bacterial communities were analysed by sequencing 16S ribosomal RNA gene amplicons using an Illumina MiSeq. Results: The bacterial SAR exhibited a logarithmic power law (R2: 0.952–0.999), outperforming the power law (R2: 0.701–0.852). Consequently, the most widely adopted power law led to an overestimation of species richness by up to 15.07% in areas >256 × 256 m2, and the regional maximum theoretical richness based on Chao1 by up to 9.88%. Mechanistically, the passive sampling hypothesis was refuted through the rarefied species richness analysis, and the disproportionate effect hypothesis was rejected based on analyses of the effective numbers of species number conversions for the probability of interspecific encounters (SPIE). Notably, Pearson and multiple linear regression analyses indicated that the spatial turnover of bacterial richness was determined by the environmental heterogeneity (R2: 0.855–0.999), rather or better than environmental variables themselves, supporting the 'environment heterogeneity hypothesis'. Main Conclusions: Soil bacterial SAR in alpine grasslands exhibited a logarithmic power relationship. Spatial turnover was primarily governed by the environmental heterogeneity. In contrast, the traditional power law leads to an overestimation of soil bacterial diversity at the regional scale. [ABSTRACT FROM AUTHOR]

• Structural stable state triggers a change in functional stable state. • Long-term ungrazed steppe had an abrupt transition in plant functional type and followed a shift in ecosystem function. • Moderate grazed activity no abrupt transitions for stable states. Theoretical models suggest that ecosystems can be found in one of several possible alternative stable states, and a shift in structural stable state (SSS) can trigger a change in functional stable state (FSS). But we still lack the empirical evidence to confirm these states and transitions, and to inform the rates of change. Here, a 30-yr dataset from long-term ungrazed and grazed temperate grasslands was analyzed to determine whether abrupt transitions of SSS and FSS can occur. We found that the long-term ungrazed grassland experienced abrupt transitions in the dominant plant functional type (shift in SSS) that was followed by a transition between carbon sink and source 1–2 year later (shift in FSS). A directional shift in precipitation and temperature accounted for 40% of the variation in the SSS transition, while the SSS transition explained 20% of the variation in the FSS transition. In contrast, no abrupt transitions for SSS and FSS were observed in the long-term moderately grazed grassland. These findings provide important insight into the interacting effects of climate change and livestock grazing on ecosystem transitions in temperate grasslands. Moderate utilization of production in ecosystems that have co-evolved with herbivores can offset structural and functional transitions induced by climate change. [ABSTRACT FROM AUTHOR]

[Display omitted] • Severely altered precipitation regime induced NO 3 – and DOC redistribution between soil layers in the alpine meadow. • Topsoil microorganisms are more sensitive to severe changes in precipitation regime in the alpine meadow. • The main edaphic regulators of microbial communities are heterogeneous in soil layers in the alpine meadow. • Microbes at different soil layers have divergent modes of regulating GHG fluxes in the alpine meadow. How soil microbial communities regulate greenhouse gas (GHG) emissions as precipitation events are "repackaged" from many small events to a few larger events has received significant attention. Previous studies have quantified the net fluxes of GHG across the soil/atmosphere interface; however, they have not investigated GHG fluxes in soil profiles under altered precipitation regimes. This study investigated the joint regulation of topsoil and subsoil microorganisms on GHG emissions under changes in precipitation regime in an alpine meadow. Severely altered precipitation regimes have led to changes in NO 3 –, DOC, and soil moisture among different soil layers, which can be attributed to a combination of substrate migration and changes in carbon and nitrogen mineralization rates. Topsoil microorganisms exhibit high sensitivity to severe changes in the precipitation regime, which can affect their biomass, microbial composition, and metabolic activities. In contrast, the activity of subsoil microorganisms remains relatively stable. This was likely due to the heterogeneity of dominant regulators across soil layers. Under the severely altered precipitation regime, carbon dioxide (CO 2) emissions significantly decreased by approximately 11.08%. This decrease was primarily due to a reduction in microbial respiration in the topsoil. The decrease in both topsoil and subsoil methane (CH 4) uptake likely caused the inhibition of the CH 4 sink from the surface (by approximately 11.60%). While a 1.75-fold increase in nitrous oxide (N 2 O) emissions under the severe changes in the precipitation regime might be primarily related to the increase in subsoil N 2 O emissions caused by the increasing abundance of subsoil denitrifiers, as well as the addition of subsoil nitrate content and soil moisture. This study revealed the divergent modes of microbial communities at different soil layers regulating GHG fluxes, which could guide the improvement of ecological models predicting GHG emissions in response to altered precipitation regimes. [ABSTRACT FROM AUTHOR]

In alpine meadows, plants and soil microbes typically engage in competition for nitrogen (N) under N-deficient conditions. However, the acquisition and distribution of N among soil microbes and plants under alpine meadow degradation and climate warming induced by global climate change are still uncharacterized. In this study, we isotope labeled inorganic (NH4+-15N, NO3−-15N) and organic (glycine-15N) N in both degraded and non-degraded plots by using open-top chambers (OTC) to mimic increasing air temperatures. After 6 h, the 15N contents in soil microbes and plants were measured to investigate the effects of degradation and rising air temperature on N allocations in the ecosystems studied. Results showed that alpine meadow degradation significantly reduced soil microbial N accumulation by 52% compared to those in non-degraded plots. In non-degraded plots, warming significantly lowered the organic N levels of soil microbes by 49%, whereas in degraded ones, it reduced both NH4+-15N and NO3−-15N recovery by 80% and 45% on average but increased glycine-15N recovery by 653%. Meanwhile, warming decreased the plant recovery of NH4+-15N and NO3−-15N by 75% and 45% but increased the recovery of glycine-15N by 45% in non-degraded plots. Conversely, in degraded plots, warming markedly lowered NH4+-15N recovery by 40% but increased glycine-15N recovery by 114%. Warming mitigates the effects of alpine meadow degradation on nitrogen allocation among soil microbes and plants. In unwarmed plots, degradation significantly elevated the total 15N recovery ratio of soil microbes to plants by 60%. However, in warmed plots, the impact of degradation on this ratio was reduced. The responses of the 15N recovery ratio of soil microbes and plants to rising temperatures were closely related to alpine meadow quality. In non-degraded areas, warming enhanced the recovery ratio for NH4+-15N by 165% but reduced it for glycine-15N by 66%. Conversely, in degraded plots, warming decreased the recovery ratio for NH4+-15N by 66% but increased it for glycine-15N by 232%. This indicates that warming can increase carbon limitation for soil microbes in degraded alpine meadows, and the restoration of degraded alpine meadows should prioritize restoring carbon accumulation. [ABSTRACT FROM AUTHOR]

The alpine grassland on the Qinghai-Tibet Plateau covers an area of about 1/3 of China's total grassland area and plays a crucial role in regulating grassland ecological functions. Both environmental changes and irrational use of the grassland can result in severe grassland degradation in some areas of the Qinghai-Tibet Plateau. However, the magnitude and patterns of the physical and anthropogenic factors in driving grassland variation over northern Tibet remain debatable, and the interactive influences among those factors are still unclear. In this study, we employed a geographical detector model to quantify the primary and interactive impacts of both the physical factors (precipitation, temperature, sunshine duration, soil type, elevation, slope, and aspect) and the anthropogenic factors (population density, road density, residential density, grazing density, per capita GDP, and land use type) on vegetation variation from 2000 to 2015 in northern Tibet. Our results show that the vegetation index in northern Tibet significantly decreased from 2000 to 2015. Overall, the stability of vegetation types was sorted as follows: the alpine scrub > the alpine steppe > the alpine meadow. The physical factors, rather than the anthropogenic factors, have been the primary driving factors for vegetation dynamics in northern Tibet. Specifically, meteorological factors best explained the alpine meadow and alpine steppe variation. Precipitation was the key factor that influenced the alpine meadow variation, whereas temperature was the key factor that contributed to the alpine steppe variation. The anthropogenic factors, such as population density, grazing density and per capita GDP, influenced the alpine scrub variation most. The influence of population density is highly similar to that of grazing density, which may provide convenient access to simplify the study of the anthropogenic activities in the Tibet plateau. The interactions between the driving factors had larger effects on vegetation than any single factor. In the alpine meadow, the interaction between precipitation and temperature can explain 44.6% of the vegetation variation. In the alpine scrub, the interaction between temperature and GDP was the highest, accounting for 27.5% of vegetation variation. For the alpine steppe, the interaction between soil type and population density can explain 29.4% of the vegetation variation. The highest value of vegetation degradation occurred in the range of 448–469 mm rainfall in the alpine meadow, 0.61–1.23 people/km2 in the alpine scrub and –0.83–0.15 °C in the alpine steppe, respectively. These findings could contribute to a better understanding of degradation prevention and sustainable development of the alpine grassland ecosystem in northern Tibet. [ABSTRACT FROM AUTHOR]

[Display omitted] Structural information of grassland changes on the Tibetan Plateau is essential for understanding alterations in critical ecosystem functioning and their underlying drivers that may reflect environmental changes. However, such information at the regional scale is still lacking due to methodological limitations. Beyond remote sensing indicators only recognizing vegetation productivity, we utilized multivariate data fusion and deep learning to characterize formation-based plant community structure in alpine grasslands at the regional scale of the Tibetan Plateau for the first time and compared it with the earlier version of Vegetation Map of China for historical changes. Over the past 40 years, we revealed that (1) the proportion of alpine meadows in alpine grasslands increased from 50% to 69%, well-reflecting the warming and wetting trend; (2) dominances of Kobresia pygmaea and Stipa purpurea formations in alpine meadows and steppes were strengthened to 76% and 92%, respectively; (3) the climate factor mainly drove the distribution of Stipa purpurea formation, but not the recent distribution of Kobresia pygmaea formation that was likely shaped by human activities. Therefore, the underlying mechanisms of grassland changes over the past 40 years were considered to be formation dependent. Overall, the first exploration for structural information of plant community changes in this study not only provides a new perspective to understand drivers of grassland changes and their spatial heterogeneity at the regional scale of the Tibetan Plateau, but also innovates large-scale vegetation study paradigm. [ABSTRACT FROM AUTHOR]

• Dynamic scene graph is adaptive to different questions. • Word-level co-attention mechanism to refine node features and edge features. • Dynamic scene graph is beneficial to the logistic reasoning. • The proposed method experimentally outperforms the best results on the GQA dataset. In visual question answering task, it is vital to learn the semantic interactions between the question and target objects in the input image. Existing scene graph-based methods generally extract global features from the image and then perform feature fusion with the question representation. However, the scene graph constructed by these methods only obtains the abstract semantic features from the image, but does not consider the influence of the positional words and semantic information in question. In this paper, we propose a Question-aware Dynamic Scene Graph (QDSG) method. Firstly, we adopt a scene graph of the initial state based on the local attribute features of the image target. Then we design a dynamic scene graph adaptive to different questions based on the initial scene graph, which is used a word-level co-attention mechanism to refine node features and edge features. Finally, iterative reasoning is performed on the refined scene graph and the correct answer is predicted by using the graph attention network model. The proposed method is sufficient to learn the semantic local features to generate the interactive scene graph between the image and question, which is beneficial to the logistic reasoning depending on the adaptive graph refinement. The proposed method outperforms the comparative performance when compared with state-of-the-art models on the GQA dataset and its semantic and structural type datasets. [ABSTRACT FROM AUTHOR]

Cueing facilitates retention and transfer of multimedia learning. From the perspective of cognitive load theory (CLT), cueing has a positive effect on learning outcomes because of the reduction in total cognitive load and avoidance of cognitive overload. However, this has not been systematically evaluated. Moreover, what remains ambiguous is the direct relationship between the cue-related cognitive load and learning outcomes. A meta-analysis and two subsequent meta-regression analyses were conducted to explore these issues. Subjective total cognitive load (SCL) and scores on a retention test and transfer test were selected as dependent variables. Through a systematic literature search, 32 eligible articles encompassing 3,597 participants were included in the SCL-related meta-analysis. Among them, 25 articles containing 2,910 participants were included in the retention-related meta-analysis and the following retention-related meta-regression, while there were 29 articles containing 3,204 participants included in the transfer-related meta-analysis and the transfer-related meta-regression. The meta-analysis revealed a statistically significant cueing effect on subjective ratings of cognitive load (d = −0.11, 95% CI = [−0.19, −0.02], p < 0.05), retention performance (d = 0.27, 95% CI = [0.08, 0.46], p < 0.01), and transfer performance (d = 0.34, 95% CI = [0.12, 0.56], p < 0.01). The subsequent meta-regression analyses showed that dSCL for cueing significantly predicted dretention for cueing (β = −0.70, 95% CI = [−1.02, −0.38], p < 0.001), as well as dtransfer for cueing (β = −0.60, 95% CI = [−0.92, −0.28], p < 0.001). Thus in line with CLT, adding cues in multimedia materials can indeed reduce SCL and promote learning outcomes, and the more SCL is reduced by cues, the better retention and transfer of multimedia learning. [ABSTRACT FROM AUTHOR]

Urolithiasis was a global disease and it was more common in southern China. This study looked into the association between daily temperature and urolithiasis hospital admissions in Ganzhou, a large prefecture-level city in southern China. In Ganzhou City from 2016 to 2019, a total of 60,881 hospitalized cases for urolithiasis from 69 hospitals and meteorological data were gathered. The effect of high ambient temperature on urolithiasis hospital admissions was estimated using a distributed lag nonlinear model. Stratified analysis was done to examine sex differences. The study found that in Ganzhou of China, the exposure–response curves approximated a "J" shape which across genders were basically similar. The maximum lag effect occurred on the second day after high temperatures for males but on the third day for females. Compared to the 10 °C reference temperature and considering the cumulative lag effect of 10 days, the relative risks of the daily mean temperature at the 95th percentile on the total, male, and female hospital admissions for urolithiasis were 2.026 (95% CI: 1.628, 2.521), 2.041 (95% CI: 1.603, 2.598), and 2.030 (95% CI: 1.552, 2.655), respectively, but the relative risks between sex were not statistically significant (p = 0.977). Urolithiasis morbidity risk in China could be exacerbated by high temperatures. The effect of high temperature on urolithiasis was similar across genders. [ABSTRACT FROM AUTHOR]

Background: With an increasing incidence of obesity, the relationship between obesity and body image has become a hot research topic worldwide. From high school to university, young people experience changes in their social environment. University students have a high incidence of eating disorders and insufficient physical activity. The purpose of this study was to explore the relationship between body dissatisfaction, insufficient physical activity, and disordered eating behaviors among university students in southern China.Methods: In total, 1296 university students aged 18-23 years were recruited for this study. The participants completed anthropometric measurements, the Physical Activity Rating scale-3 (PARS-3), and the Chinese-Dutch Eating Behavior Questionnaire (C-DEBQ). The ideal weight and silhouette were reported by university students using a questionnaire.Results: Compared with men, young women had a higher level of body dissatisfaction. For men, body mass index (BMI; β = 0.76, P <  0.01), physical activity score (β = - 0.11, P <  0.01), and restrained eating score (β = 0.10, P <  0.01) were the significant factors predictive of body dissatisfaction. For women, BMI (β = 0.57, P <  0.01), muscle mass (β = 0.12, P <  0.01), physical activity score (β = - 0.11, P <  0.01), and restrained eating score (β = 0.09, P <  0.01) were the significant factors predictive of body dissatisfaction.Conclusions: University students with high body dissatisfaction had lower physical activity scores and higher restrained eating scores. The data presented here highlight the impact of university students' body dissatisfaction on physical activity deficiency and disordered eating behaviors in China. [ABSTRACT FROM AUTHOR]

The grassland in the Hindu Kush Himalayan (HKH) region is one of the largest and most biodiverse mountain grassland types in the world, and its ecosystem service functions have profound impacts on the sustainable development of the HKH region. Monitoring the spatiotemporal distribution of grassland aboveground biomass (AGB) accurately and quantifying its response to climate change are indispensable sources of information for sustainably managing grassland ecosystems in the HKH region. In this study, a pure vegetation index model (PVIM) was applied to estimate the long-term dynamics of grassland AGB in the HKH region during 2000–2018. We further quantified the response of grassland AGB to climate change (temperature and precipitation) by partial correlation and variance partitioning analyses and then compared their differences with elevation. Our results demonstrated that the grassland AGB predicted by the PVIM had a good linear relationship with the ground sampling data. The grassland AGB distribution pattern showed a decreasing trend from east to west across the HKH region except in the southern Himalayas. From 2000 to 2018, the mean AGB of the HKH region increased at a rate of 1.57 g/(m2·yr) and ranged from 252.9 (2000) to 307.8 g/m2 (2018). AGB had a positive correlation with precipitation in more than 80% of the grassland, and temperature was positively correlated with AGB in approximately half of the region. The change in grassland AGB was more responsive to the cumulative effect of annual precipitation, while it was more sensitive to the change in temperature in the growing season; in addition, the influence of climate varied at different elevations. Moreover, compared with that of temperature, the contribution of precipitation to grassland AGB change was greater in approximately 60% of the grassland, but the differences in the contribution for each climate factor were small between the two temporal scales at elevations over 2000 m. An accurate assessment of the temporal and spatial distributions of grassland AGB and the quantification of its response to climate change are of great significance for grassland management and sustainable development in the HKH region. [ABSTRACT FROM AUTHOR]

Extreme climatic events are likely to intensify under climate change and can have different effects on ecosystems depending on their timing and magnitude. Understanding how productivity responds to extreme precipitation patterns requires assessing stability and vulnerability during critical growing periods at the plant community level. In this study, we experimentally imposed two contrasting types of extreme precipitation patterns, including extreme drought (excluding all rainfall for 30 consecutive days) during early-, mid-, and late-stages of the growing season, and heavy rainfall (adding 14.1 mm of rainfall every day for 20 consecutive days) during mid- and late-stages of the growing season over four years (2013–2016) in a steppe community in Inner Mongolia, China. We found that extreme drought and heavy rainfall had no effect on community aboveground net primary productivity (ANPP), species richness, and dominance at any stage of the growing season. Community stability in response to extreme drought was mainly driven by compensation among species and the stability of dominant species, while the compensatory effect among species and functional groups, and the stability of dominant species contributed to the community stability in response to heavy rainfall. Overall, our findings indicate that the responses of the ecosystem to intra-seasonal contrasting extreme precipitation patterns can be driven by similar stability mechanisms and suggest that semiarid temperate steppe communities may have strong initial resistance to more frequent extreme climatic events in the future. [ABSTRACT FROM AUTHOR]

Numerical research on natural convection heat transfer in Toco Toucans beak is carried out in this work to determine the optimal direction for their geometric evolution. The isothermal contours, streamlines, and Nusselt number are obtained. The results show that the entrainment effect near the distal region is stronger than that at the proximal region, leading to the accumulation of the thermal boundary layer near the proximal region. The air flowing upward from the mandible accumulates thermal energy at the lower beak teeth, which increases the air velocity at the maxilla. This process improves the adverse effects of preheating on the air and enhances maxillary heat transfer. Based on the analysis of the flow and temperature fields, it is determined that rounding beak surface is necessary to achieve a more uniform Nusselt number distribution in the direction of gravity. Subsequent research revealed that rounding the beak surface increased the average Nusselt number by 0.5%, indicating that the current shape is very close to the optimal cross-sectional profile. The heat transfer mechanism of the beak was quantitatively elucidated, providing a reference for the study of the beaks of other species in ecology. • Abstract the heat transfer structure of a toucan's beak into a numerical model for natural convection. • Quantitatively describes the flow conditions of the boundary layer around the beak. • The beak of Toco toucans is anticipated to evolve toward a more rounded shape. [ABSTRACT FROM AUTHOR]

This study used the time series data of Ganzhou city to explore the individual and interaction effects of temperature and humidity on COPD death, and identify vulnerable subgroups of the population. We collected daily COPD mortality and meteorological data in Ganzhou from 2016 to 2019. The nonlinear distribution lag model was used to examine the associations and interaction between daily mean temperature and humidity and COPD mortality. For the total population, male and 65 years old or above, the relative risk (RR) for COPD mortality could be significant at extremely low temperature (3.3 ℃), reaching 1.799 (95% confidence interval [CI]: 1.216, 2.662), 1.894 (95% CI: 1.164, 3.084) and 1.779 (95% CI:1.185, 2.670). Also, at extremely low humidity (47.8%), the risk reached 1.888 (95% CI: 1.217, 2.930), 1.837 (95% CI: 1.066, 3.165) and 2.166 (95% CI: 1.375, 3.414). The cumulative COPD death risk for females was 3.524 (95% CI: 1.340, 9.267) at high temperature (30.7 ℃), 1.953(95% CI: 1.036, 3.683) at low humidity (47.8%) and 1.726 (95% CI: 1.048, 2.845) at high humidity (96.7%). For the total COPD deaths and subgroups, the interaction effects between daily temperature and humidity were not significant (p > 0.05). Both extremely low temperature and low humidity increased the risk of COPD death in Ganzhou city, especially for males and people over 65 years old. Females were more sensitive to extremely high temperature and humidity. Patients with COPD should pay attention to self-protection under extreme temperature and humidity weather conditions. [ABSTRACT FROM AUTHOR]

Objective: To investigate the relationship between the aspartate aminotransferase to alanine aminotransferase ratio (AAR) and the prognosis of IgA nephropathy (IgAN).Clinical, pathological and follow-up data of 271 patients with IgAN from January 1, 2013, to July 31, 2023, were collected. A 50% decrease in estimated glomerular filtration rate (eGFR) or end-stage renal disease (ESRD) was used as renal composite end point events. A receiver operating characteristic (ROC) curve was plotted to predict the composite end point events by AAR. The optimal cutoff value of 1.24 was determined, and patients were allocated to high AAR and low AAR groups. Kaplan‒Meier (K‒M) curves and Cox proportional hazard models were used to evaluate the predictive effect of AAR on renal composite end point events.After a mean follow-up of 29 months, 39 patients achieved renal composite end point events. Among them, 9 and 30 patients in the low and high AAR groups achieved renal composite end point events, respectively, with a significant difference (P < 0.001). After adjustment for confounding factors, AAR was found to be an independent prognostic factor for renal composite end point events (HR = 3.283, 95% CI: 1.489–7.238, P = 0.003). Kaplan‒Meier analysis showed that high AAR was associated with achieving renal composite end point events in patients with IgAN. Moreover, the clinical features in the high AAR group were more severe. Further subgroup analysis showed that high AAR had a better predictive effect in patients with more severe clinicopathological manifestations.AAR is an independent prognostic factor in patients with IgAN.Methods: To investigate the relationship between the aspartate aminotransferase to alanine aminotransferase ratio (AAR) and the prognosis of IgA nephropathy (IgAN).Clinical, pathological and follow-up data of 271 patients with IgAN from January 1, 2013, to July 31, 2023, were collected. A 50% decrease in estimated glomerular filtration rate (eGFR) or end-stage renal disease (ESRD) was used as renal composite end point events. A receiver operating characteristic (ROC) curve was plotted to predict the composite end point events by AAR. The optimal cutoff value of 1.24 was determined, and patients were allocated to high AAR and low AAR groups. Kaplan‒Meier (K‒M) curves and Cox proportional hazard models were used to evaluate the predictive effect of AAR on renal composite end point events.After a mean follow-up of 29 months, 39 patients achieved renal composite end point events. Among them, 9 and 30 patients in the low and high AAR groups achieved renal composite end point events, respectively, with a significant difference (P < 0.001). After adjustment for confounding factors, AAR was found to be an independent prognostic factor for renal composite end point events (HR = 3.283, 95% CI: 1.489–7.238, P = 0.003). Kaplan‒Meier analysis showed that high AAR was associated with achieving renal composite end point events in patients with IgAN. Moreover, the clinical features in the high AAR group were more severe. Further subgroup analysis showed that high AAR had a better predictive effect in patients with more severe clinicopathological manifestations.AAR is an independent prognostic factor in patients with IgAN.Results: To investigate the relationship between the aspartate aminotransferase to alanine aminotransferase ratio (AAR) and the prognosis of IgA nephropathy (IgAN).Clinical, pathological and follow-up data of 271 patients with IgAN from January 1, 2013, to July 31, 2023, were collected. A 50% decrease in estimated glomerular filtration rate (eGFR) or end-stage renal disease (ESRD) was used as renal composite end point events. A receiver operating characteristic (ROC) curve was plotted to predict the composite end point events by AAR. The optimal cutoff value of 1.24 was determined, and patients were allocated to high AAR and low AAR groups. Kaplan‒Meier (K‒M) curves and Cox proportional hazard models were used to evaluate the predictive effect of AAR on renal composite end point events.After a mean follow-up of 29 months, 39 patients achieved renal composite end point events. Among them, 9 and 30 patients in the low and high AAR groups achieved renal composite end point events, respectively, with a significant difference (P < 0.001). After adjustment for confounding factors, AAR was found to be an independent prognostic factor for renal composite end point events (HR = 3.283, 95% CI: 1.489–7.238, P = 0.003). Kaplan‒Meier analysis showed that high AAR was associated with achieving renal composite end point events in patients with IgAN. Moreover, the clinical features in the high AAR group were more severe. Further subgroup analysis showed that high AAR had a better predictive effect in patients with more severe clinicopathological manifestations.AAR is an independent prognostic factor in patients with IgAN.Conclusion: To investigate the relationship between the aspartate aminotransferase to alanine aminotransferase ratio (AAR) and the prognosis of IgA nephropathy (IgAN).Clinical, pathological and follow-up data of 271 patients with IgAN from January 1, 2013, to July 31, 2023, were collected. A 50% decrease in estimated glomerular filtration rate (eGFR) or end-stage renal disease (ESRD) was used as renal composite end point events. A receiver operating characteristic (ROC) curve was plotted to predict the composite end point events by AAR. The optimal cutoff value of 1.24 was determined, and patients were allocated to high AAR and low AAR groups. Kaplan‒Meier (K‒M) curves and Cox proportional hazard models were used to evaluate the predictive effect of AAR on renal composite end point events.After a mean follow-up of 29 months, 39 patients achieved renal composite end point events. Among them, 9 and 30 patients in the low and high AAR groups achieved renal composite end point events, respectively, with a significant difference (P < 0.001). After adjustment for confounding factors, AAR was found to be an independent prognostic factor for renal composite end point events (HR = 3.283, 95% CI: 1.489–7.238, P = 0.003). Kaplan‒Meier analysis showed that high AAR was associated with achieving renal composite end point events in patients with IgAN. Moreover, the clinical features in the high AAR group were more severe. Further subgroup analysis showed that high AAR had a better predictive effect in patients with more severe clinicopathological manifestations.AAR is an independent prognostic factor in patients with IgAN. [ABSTRACT FROM AUTHOR]

The plant productivity and species richness (P-SR) relationship has been a central topic in ecology for decades. It is increasingly recognized that climate resources (CR, temperature and precipitation) might affect the P-SR relationship as (1) the response of plant productivity and species richness to CR are different; (2) plant-plant interactions change along the CR gradient. However, little is known about how these effects mediate the shape and strength of the P-SR relationship from local-site to regional scales. Here, we proposed a cross-scale framework to disentangle the climatic control over the P-SR relationship in grasslands using the HerbDivNet dataset, which covers 28 natural grasslands in 19 countries and 6 continents with wide precipitation and temperature gradients. Our results showed that, at the local-site scale, a humped-back P-SR relationship is common at sites under poor and rich CR conditions, whereas both the shape and strength of the P-SR relationship strongly vary among sites under moderate CR condition. However, at the regional scale, the humped-back P-SR relationship is only observed under poor CR condition. We suggested that the asynchronous responses of productivity and species richness to increasing CR is an abiotic driver of the inconsistent P-SR relationships along the climatic gradient in addition to the changing plant-plant interactions suggested by the stress-gradient hypothesis. These findings help to reconcile the long-standing debate over the P-SR relationship and highlight the importance of CR conditions in developing or comparing grassland ecosystem theories and management at small scales. • Climate effects cause inconsistent P-SR relationships from local to regional scales. • Asynchronous response of P and SR to CR is an abiotic driver of P-SR relationship. • Unimodal P-SR relationship at regional scale only exists with poor CR. • None unimodal P-SR relationships at site scale are mostly observed with moderate CR. • Shape and strength of P-SR relationship strongly vary among sites with moderate CR. [ABSTRACT FROM AUTHOR]

Poplar 741 [ Populus alba × ( P. davidiana + P. simonii) × P. tomentosa] leaves were rooted within 8 days when cultured on 1/2 MS medium. The subcellular localization of endogenous indole-3-acetic acid (IAA) in the rhizogenesis was investigated, using an immunocytochemical approach. The results of IAA subcellular localization revealed organelle-specific distribution. Three days after root induction, IAA in vascular cambium cells of the basal region of the petiole was distributed mainly in the plasma membrane, endoplasmic reticulum (ER), and nucleus, with a lesser amount in the cytoplasm. In phloem of the basal region of the petiole, IAA was detected in the plasma membrane and ER of the companion cell and in the plasma membrane of the sieve element. In xylem of the basal region of the petiole, no IAA gold particles were labeled. In mesophyll cells IAA was distributed in the chloroplast starch grains before root induction, and the amount in the chloroplast starch grains increased after 3 days after root induction. This suggests that the plasma membrane and nucleus of cambium cells may be the target sites where IAA performs its physiological activities during poplar leaf rhizogenesis. IAA polar transport from lamina mesophyll to the basal region of the petiole during rhizogenesis is mediated by phloem. The starch grains of mesophyll chloroplasts appeared to accumulate IAA and may be a source of IAA during poplar leaf rhizogenesis. Novel and direct evidence regarding the function of IAA during rhizogenesis is provided in this study. [ABSTRACT FROM AUTHOR]

Against a backdrop of rising temperature, large portions of the western United States are experiencing fewer, larger and less frequent precipitation events. How such temporal 'repackaging' of precipitation alters the magnitude and timing of seasonal maximum gross primary productivity (GPPmax) remains unknown. Addressing this knowledge gap is critical, since changes to GPPmax magnitude and timing can impact a range of ecosystem services and management decisions.Here we used a field‐based precipitation manipulation experiment in a semi‐arid mixed annual/perennial bunchgrass ecosystem with mean annual precipitation ~384 mm to investigate how temporal repackaging of a fixed total seasonal precipitation amount impacts seasonal GPPmax and its timing.We found that temporal repackaging of precipitation profoundly influenced the seasonal timing of GPPmax. Many/small precipitation events advanced the seasonal timing of GPPmax by ~13 days in comparison with climatic normal precipitation. Conversely, few/large events led to deeper soil water infiltration, which delayed the timing of GPPmax by up to 16 days in comparison with climatic normal precipitation, and altered end‐of‐season community composition by increasing the diversity of shallow‐rooted annual plants. While GPPmax magnitude did not differ across precipitation treatments, it was positively correlated with the abundance and biomass of deeper‐rooted perennial bunchgrasses. The sensitivity of plant growth, biomass accumulation and plant life histories to the timing and magnitude of precipitation events and the resulting temporal patterns of soil moisture regulated ecosystem responses to altered precipitation patterns.Our results highlight the sensitivity of semi‐arid grassland ecosystem to the temporal repackaging of precipitation. We find that already‐observed and model‐forecasted shifts toward few/large precipitation events could drive significant delays in the timing of peak productivity for this ecosystem. Adaptive land management frameworks should consider these findings since shifts in peak ecosystem productivity would have major implications for multiple land user communities. Additional research is needed to better understand the role of climate, community composition and soil properties in mediating variability in the seasonal timing of maximum ecosystem productivity. A free Plain Language Summary can be found within the Supporting Information of this article. [ABSTRACT FROM AUTHOR]

• Causality models were applied to discover ecosystem causal networks. • Growing season temperature dominated changes in ecosystem structure and function. • Only weak causal links existed between ecosystem structure and function. • Relative causality-driven intensities were identified. The understanding of the interplay between the environment, ecosystem structure, and function is crucial for effectively managing ecosystems in the face of climate change and environmental disturbances. Numerous observations and simulation experiments relying on correlation analysis have yielded the conclusion that environmental factors can directly or indirectly affect ecosystem community structure and function. However, the limitations of traditional ecological approaches lie in their inadequate control over confounding factors, thus hindering our comprehensive understanding of the true causal relationships. Our study aims to address these limitations and obtain a more accurate picture of causality about environment, ecosystem structure and function within a long-term time series data of an ecosystem. Here, utilizing a 31-year dataset of typical temperate grassland ecosystems, we developed an advanced causal discovery model and further enhanced it to effectively identify the causal network within the ecosystem, while also quantifying the intensity of causal pathways connecting the environment, ecosystem structure, and function. We found that the primary driver for changes in ecosystem structure and function was the temperature during the growing season, with soil water content being the secondary factor. However, there was only a weak causal relationship between ecosystem structure and gross primary productivity (GPP), which was mediated by eurytopic xerophyte plants. These findings challenge the conventional notion that precipitation is a key driver of changes in ecosystem carbon fluxes, highlighting the importance of plant-available water in regulating ecosystem structure and function. Our results suggest that the effects of global warming and severe droughts on plant growth and carbon sequestration capacity necessitate significant attention and further mitigation measures in arid and semi-arid regions. [ABSTRACT FROM AUTHOR]

• Droughts increased CH 4 uptake in a wet year in the semiarid grassland. • Magnitude and pathways of drought effects on CH 4 uptake depend on seasonal timing. • Positive effects of early drought on CH 4 uptake were the least. • Plant composition regulated CH 4 uptake in response to droughts. Increasingly frequent and severe droughts are occurring in multiple seasons of a year in many dryland ecosystems, with unknown impacts on the role of drylands in cycling of methane (CH 4), a potent greenhouse gas. In particular, there is limited understanding of how drought occurring at different times within the growing season regulates biological CH 4 uptake, and how these responses are mediated by plant community composition. Here, we quantify how drought timing and plant community composition regulate CH 4 uptake in a semiarid grassland. We employ a field experiment in which droughts were imposed in early, middle, or late growing season in three different communities (two graminoids, two shrubs and their mixture), respectively. All three droughts increased CH 4 uptake, but the effect size and pathway varied with seasonal timing. Early and middle drought increased CH 4 uptake through increasing both soil pomA abundance and diffusivity resulting from reduced soil water content (SWC), while late drought increased CH 4 uptake only by reducing SWC. Overall, early drought had the least positive effects on CH 4 uptake because it excluded the least precipitation and therefore had smaller impacts on SWC. Besides, plant composition did not affect CH 4 uptake under normal environment but regulated CH 4 uptake in response to droughts due to different response of plant composition to droughts. Early and middle drought had larger positive effects on CH 4 uptake in shrub communities than the other two communities, consistent with larger reductions in SWC and larger increases in pomA abundance, respectively. In contrast, late drought had consistent effects on CH 4 uptake across three communities. Our results suggest that the magnitude and pathways of extreme drought effects on CH 4 uptake are strongly co-regulated by seasonal timing and plant composition. [ABSTRACT FROM AUTHOR]

This study characterized the effect of green manures (February orchid, hairy vetch, rattail fescue and a no-green-manure control) and the termination method (flail or disk) on nutrient contents, enzyme activities, microbial biomass, microbial community structure of rhizosphere soil and vegetative growth of walnut tree. All three selected green manures significantly enhanced the water content, organic C, total N and available P. The rattail fescue significantly decreased the mineral N. Total organic C, total N, mineral N and available P were significantly greater under flail than under disk. Hairy vetch and February orchid significantly improved levels of soil β-glucosidase, N-acetyl-glucosaminidase and acid phosphatase activity, whereas rattail fescue improved only β-glucosidase activity. All of the green manures significantly decreased phenoloxidase activity. β-glucosidase, N-acetyl-glucosaminidase and acid phosphatase activities were significantly greater under flail relative to disk. The termination method had no significant effect on phenoloxidase activity. The different types of green manures and termination methods significantly altered the soil microbial biomass and microbial community structure. The green-manure treatments were characterized by a significantly greater abundance of Gram-positive (Gram +) bacteria, total bacteria and saprophytic fungi compared to the control. Hairy vetch significantly decreased the abundance of arbuscular mycorrhizal fungi (AMF) while February orchid and rattail fescue increased their abundance compared to the no-green-manure treatment. The abundance rates of Gram+ bacteria, actinomycetes, saprophytic fungi and AMF were significantly greater in soils under flail than under disk. In terms of vegetative growth of walnut tree, hairy vetch showed the greatest positive effects. The growth of walnut tree was significantly greater under flail relative to disk. Our results indicate that green-manure application benefits the rhizosphere soil micro-ecology, rhizosphere soil nutrient contents and tree growth. Overall, the hairy vetch and flail combined treatment is recommended for walnut orchards in northern China. [ABSTRACT FROM AUTHOR]

Sustainable development goals (SDGs) emphasize a holistic achievement instead of cherry-picking a few. However, no assessment has quantitatively considered the evenness among all 17 goals. Here, we propose a systematic method, which first integrates both the evenness and the overall status of all goals, to distinguish the ideal development pathways from the uneven ones and then revisit the development trajectory in China from 2000 to 2015. Our results suggest that, despite the remarkable progress, a bottleneck has occurred in China since 2013 due to the stagnant developments in some SDGs. However, many far-reaching policies in China have been targeting these deficiencies since then, providing a perspective on how a country approaches sustainable development by promoting evenness among all SDGs. Our results also indicate that regions with the slowest progress are the developed provinces, owing to the persistent uneven status of all goals. Our study demonstrates the importance of adopting evenness in assessing and guiding sustainable development. [ABSTRACT FROM AUTHOR]

Droughts and heat waves are increasing in magnitude and frequency, altering the carbon cycle. However, understanding of the underlying response mechanisms remains poor, especially for the combination (hot drought). We conducted a 4‐year field experiment to examine both individual and interactive effects of drought and heat wave on carbon cycling of a semiarid grassland across individual, functional group, community and ecosystem levels. Drought did not change below‐ground biomass (BGB) or above‐ground biomass (AGB) due to compensation effects between grass and non‐grass functional groups. However, consistently decreased BGB under heat waves limited such compensation effects, resulting in reduced AGB. Ecosystem CO2 fluxes were suppressed by droughts, attributed to stomatal closure‐induced reductions in leaf photosynthesis and decreased AGB of grasses, while CO2 fluxes were little affected by heat waves. Overall the hot drought produced the lowest leaf photosynthesis, AGB and ecosystem CO2 fluxes although the interactions between heat wave and drought were usually not significant. Our results highlight that the functional group compensatory effects that maintain community‐level AGB rely on feedback of root system responses, and that plant adjustments at the individual level, together with shifts in composition at the functional group level, co‐regulate ecosystem carbon sink strength under climate extremes. • It is indispensable to explore the mechanisms and impacts of climate extremes on the carbon cycle given they are increasing in magnitude and frequency.• Aboveground biomass responses to climate extremes rely on the functional group compensatory effects and feedbacks of root system responses.• Plant physiological adjustments and shifts in community composition co‐regulate ecosystem CO2 fluxes under climate extremes. [ABSTRACT FROM AUTHOR]

• Temperate and alpine grasslands were weak carbon sinks. • Elevated water consistently increased carbon fluxes in temperate and alpine grasslands. • Increased temperature reduced carbon fluxes in temperate grasslands and increased carbon fluxes in alpine grasslands. Temperate grassland (TG) and alpine grassland (AG) are two distinct grassland types with different climatic backgrounds and adaptation patterns. Little is known about the universal and divergent responses of TGs and AGs to climate change, particularly with regard to the carbon (C) fluxes. The large-scale responses of the C fluxes in different grasslands to climate change remain unclear, with only a few comparative studies of distinct responses of the C fluxes in TGs and AGs to climate change hinders our understanding of this subject. In this study, we conducted a large-scale transect study across the Mongolian, Loess, and Tibetan Plateaus in China to reveal the similarities and differences in the responses of the C fluxes in TGs and AGs to climate change. We used C flux data measured by eddy covariance from ChinaFLUX and published literature, covering the period from 2003 to 2020. The results showed that TGs and AGs in China were weak C sinks. Net ecosystem productivity in TGs and AGs exhibited opposite trends with increasing latitude, longitude, and altitude. Elevated water (mean annual precipitation and soil water content) consistently increased the C fluxes. Conversely, increased temperature (mean annual temperature and mean annual soil temperature) reduced the C fluxes in TGs and increased the C fluxes in AGs. The water factors promoted the C fluxes in both TGs and AGs by improving the leaf area indices. Conversely, the temperature factors had a strong direct, negative effect on the C fluxes in TGs and a weak direct, positive effect on the C fluxes in AGs, emphasizing the divergent patterns of the C fluxes in TGs and AGs and their responses to climate change. Overall, this study enhances our knowledge on C sinks and various grassland hydrothermal sensitivities. [ABSTRACT FROM AUTHOR]

The peptide obtained from walnut protein enzymatic hydrolysate had high ACE inhibitory activity. Through centrifugation, ultrafiltration, gel chromatography and high performance liquid chromatography (HPLC), the walnut oligo-peptide, which was denoted as P4-c with high ACE inhibitory activity was obtained. Three novel ACE inhibitory peptides, GVVPHN, EHSLDPLK and KTLLNFGPN, were identified from P4-c by high-resolution ion mobility mass spectrometry (IM-MS). The three novel ACE inhibitory peptides possessed good ACE inhibitory activity and the fraction GVVPHN had high ACE inhibitory activity with 27.3 µmol L−1 of IC50. The molar percentage of hydrophobic amino acids in the peptide GVVPHN was 50% while the hydrophobic amino acid contents of EHSLDPLK and KTLLNFGPN were 37.5% and 44.4%, respectively, which indicates ACE inhibitory activities were hydrophobicity of amino acid-dependent. [ABSTRACT FROM AUTHOR]

Nitrous oxide (N2O) emissions from soil contribute to global warming and are in turn substantially affected by climate change. However, climate change impacts on N2O production across terrestrial ecosystems remain poorly understood. Here, we synthesized 46 published studies of N2O fluxes and relevant soil functional genes (SFGs, that is, archaeal amoA, bacterial amoA, nosZ, narG, nirK and nirS) to assess their responses to increased temperature, increased or decreased precipitation amounts, and prolonged drought (no change in total precipitation but increase in precipitation intervals) in terrestrial ecosystem (i.e. grasslands, forests, shrublands, tundra and croplands). Across the data set, temperature increased N2O emissions by 33%. However, the effects were highly variable across biomes, with strongest temperature responses in shrublands, variable responses in forests and negative responses in tundra. The warming methods employed also influenced the effects of temperature on N2O emissions (most effectively induced by open‐top chambers). Whole‐day or whole‐year warming treatment significantly enhanced N2O emissions, but daytime, nighttime or short‐season warming did not have significant effects. Regardless of biome, treatment method and season, increased precipitation promoted N2O emission by an average of 55%, while decreased precipitation suppressed N2O emission by 31%, predominantly driven by changes in soil moisture. The effect size of precipitation changes on nirS and nosZ showed a U‐shape relationship with soil moisture; further insight into biotic mechanisms underlying N2O emission response to climate change remain limited by data availability, underlying a need for studies that report SFG. Our findings indicate that climate change substantially affects N2O emission and highlights the urgent need to incorporate this strong feedback into most climate models for convincing projection of future climate change. [ABSTRACT FROM AUTHOR]

Plant roots play a crucial role in acquiring available nutrients and regulating microbial decomposition, leading to faster nutrient cycling in the rhizosphere than in bulk soil. With increasing nitrogen (N) loading, rhizosphere processes may become more crucial than bulk soil processes for accurately predicting nutrient cycling process changes. However, it remains unclear how the rhizosphere and bulk soil extracellular enzyme activities (EEAs) respond to N addition on a global scale. Therefore, we used a global meta-analysis to examine the effects of N addition on EEAs involved in carbon (C), N, and phosphorus (P) acquisition in paired rhizosphere and bulk soils, based on 1992 observations from 40 studies. Overall, N addition significantly increased β-xylosidase (BXYL) activity by 17.0% in bulk soil, together with urease (URE) activity in both the rhizosphere (25.3%) and bulk soil (33.6%). In addition, N addition marginally significantly decreased phenol oxidase (PHEO) activity in the rhizosphere (−18.4%), as well as peroxidase (PERO) activity in both the rhizosphere (−12.6%) and bulk soil (−13.6%). The reductions may be caused by fungi: bacteria ratio and Gram+ bacteria: Gram− bacteria ratio (F: B and G+: G−, respectively) reductions. We also found that EEAs (e.g., acid/alkaline phosphatase (AP) and PHEO) did not always have a simple linear relationship with higher N addition rate and duration. Additionally, the responses of β-1,4-N-acetyl-glucosaminnidase (NAG) and PHEO significantly increased with increase in mean annual temperature (MAT), whereas those of microbial biomass carbon (MBC) and microbial biomass nitrogen (MBN) significantly decreased with increase in mean annual precipitation (MAP). Moreover, the responses of PHEO and PERO significantly decreased along altitudinal gradients. Furthermore, we found that the N sensitivity of rhizosphere C-acquisition (BG, PHEO, and PERO) and P-acquisition (AP) enzyme activities was significantly lower than that of bulk soil, but no significant difference was noted in N-acquisition enzyme activities except for the NAG which exhibited marginal significant differences between the rhizosphere and bulk soil. Our results suggest that EEAs in the rhizosphere and bulk soil have different response patterns, and these differences might mainly be caused by soil nutrient availability and microbial attributes. These results deepen our understanding of rhizosphere and bulk soil nutrient cycling processes under increasing N loading. They also provide extensive evidence and a basis for the parameterization of global nutrient cycling models that incorporate rhizosphere responses to climate change. • Response pattern of extracellular enzyme activities (EEAs) in the rhizosphere and bulk soil to nitrogen (N) addition on a global scale. • EEAs (e.g., AP and PHEO) did not always have a simple linear relationship with higher N addition. • N sensitivity of rhizosphere C-acquisition (BG, PHEO, and PERO) and P-acquisition (AP) EEAs was significantly lower than that of bulk soil. • N sensitivity of rhizosphere N-acquisition EEAs (LAP and URE) showed insignificant difference compared to that of bulk soil. • N sensitivity of NAG activity showed marginal significance between the rhizosphere and bulk soil. [ABSTRACT FROM AUTHOR]

• Dominant factor for the IAVs of ET varied among the four grassland ecosystems. • Net radiation dominated the IAV of ET at the alpine marsh meadow. • Water availability mainly regulated the IAVs of ET for relatively arid sites. • Environmental responses of surface conductance varied across the grasslands. Understanding the long-term variation in evapotranspiration (ET) for the spatially distributed grasslands is crucial for the accurate prediction of ET response to climate change. In this study, we analyzed the interannual variability (IAV) of ET and its responses to environmental conditions at four grassland ecosystems across a wide range of climatic and biome conditions based on the long-term (9–11 years) eddy-covariance measurements. The four ecosystems encompassed the most prevalent grassland vegetations in China, containing a typical temperate steppe, an alpine meadow-steppe, an alpine shrubland meadow, and an alpine marsh meadow. The IAVs of annual ET at the typical temperate steppe and the alpine meadow-steppe were primarily affected by either change in precipitation (P) or relative humidity (RH). Leaf area index (LAI) was the dominant factor controlling the IAVs of annual and growing-season ET at the alpine shrubland meadow, and the IAV of LAI was significantly correlated with P variation. As to the alpine marsh meadow, net radiation turned to be the dominant factor for the IAV of annual ET, additionally with significant effects from water supply condition (P and RH) on the IAV of growing-season ET. Similar environmental responses were also found for the IAVs of mean surface conductance (g s) across the sites. Specifically, annual and growing-season mean g s significantly increased with increases in LAI at the alpine shrubland meadow, and appeared to be more sensitive to changes in water availability and VPD at the typical temperate steppe and the alpine meadow-steppe. Significant linear relationships were also observed among the IAVs of mean Priestley-Taylor coefficient (α = ET/ET eq , where ET eq is the equilibrium evaporation), decoupling coefficient (Ω), and g s on both the annual and growing-season basis in this study. Moreover, the variabilities of annual mean g s , Ω , and α further demonstrated the energy-limited conditions at the alpine marsh meadow, and the overall water-limited conditions at the other three grasslands. This study reveals the divergent environmental responses of long-term ET variations over grassland ecosystems, and contributes to the comprehensive understanding on the ET process and modeling efforts as well. [ABSTRACT FROM AUTHOR]

Summary: Heavy rainfall events are expected to increase in frequency and severity in the future. However, their effects on natural ecosystems are largely unknown, in particular with different seasonal timing of the events and recurrence over multiple years.We conducted a 4 yr manipulative experiment to explore grassland response to heavy rainfall imposed in either the middle of, or late in, the growing season in Inner Mongolia, China. We measured hierarchical responses at individual, community and ecosystem levels.Surprisingly, above‐ground biomass remained stable in the face of heavy rainfall, regardless of seasonal timing, whereas heavy rainfall late in the growing season had consistent negative impacts on below‐ground and total biomass. However, such negative biomass effects were not significant for heavy rainfall in the middle of the growing season. By contrast, heavy rainfall in the middle of the growing season had greater positive effects on ecosystem CO2 exchanges, mainly reflected in the latter 2 yr of the 4 yr experiment. This two‐stage response of CO2 fluxes was regulated by increased community‐level leaf area and leaf‐level photosynthesis and interannual variability of natural precipitation.Overall, our study demonstrates that ecosystem impacts of heavy rainfall events crucially depend on the seasonal timing and multiannual recurrence. Plant physiological and morphological adjustment appeared to improve the capacity of the ecosystem to respond positively to heavy rainfall. [ABSTRACT FROM AUTHOR]

• We focus on reducing the endpoint errors for 3D-HPE. • We construct a deeper human structure-aware network in cascading manner. • Geometric relationships are implicitly considered in the proposed network. • Experiments on the most popular dataset demonstrate its superiority. Existing 3D human pose estimation (3D-HPE) methods focus on reducing the overall joint error, resulting in endpoints and bone lengths with large errors. To address this issue, we propose a human structure-aware network, which is capable of recovering 3D joint locations from given 2D joint detections. We cascade a refinement network with a basic network in a residual learning manner, meanwhile fuse the features from 2D and 3D coordinates by a residual connection. Specifically, our refinement network employs a dual-channel structure, in which the symmetrical endpoints are divided into two parts and refined separately. Such a structure is able to avoid the mutual interference of joints with large errors to promise reliable 3D features. Experimental results on the Human3.6M dataset demonstrate that our network reduces the errors of both endpoints and bone lengths compared with existing state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

• Warming significantly increased the soil extractable organic N contents. • Degradation significantly decreased the soil extractable organic C and N contents. • Degradation significantly decreased soil methanotrophic activity. • Warming and degradation had no interactive effects on methanotrophic activity. • Active methanotrophic communities in meadow soils were dominated by Methylosinus. The Tibetan alpine meadow ecosystem is an important part of the Eurasian grasslands and is experiencing intense warming at approximately three times the global warming rate and rapid degradation. However, little is known about the effect of warming and degradation and their interactions on ecosystem functions like soil carbon (C) and nitrogen (N) pools and methane (CH 4) uptake in this region. Here, we selected a long-term simulated warming site in a Tibetan alpine meadow with different degradation levels. After 4 years of warming, we analyzed soil total C (TC) and total N (TN) contents, extractable organic C (EOC) and extractable organic N (EON) contents as well as methanotrophic activity, abundance and community structure. Soil EOC and EON contents were measured through hot water extraction, whereas methanotrophic activity was measured along a gradient of CH 4 concentrations in laboratory incubations. Michaelis–Menten kinetics analysis [maximal rate of velocity (V max) and half-saturation constant (K m)] was used to quantify changes in methanotrophic activity among the treatments. Active methanotrophic communities in the natural soils were measured via DNA-based stable isotope probing (SIP). The results showed that warming significantly increased soil EON contents, whereas degradation significantly decreased soil TC and TN contents, and EOC and EON contents. Methanotrophic activity was significantly lower at different levels of degradation but no significant effects were observed under warming. Changes in soil methanotrophic abundance among the treatments followed the same trend, but warming and degradation had no interactive effects on methanotrophic activity and abundance. Active methanotrophic communities in the natural meadow soils were dominated by Methylosinus (a Type II methanotroph). In conclusion, our results indicate that soil C and N pools and CH 4 oxidation capability were influenced more strongly by degradation than warming. However, warming may have an additional effect on the stability of these important ecosystem processes, regardless of degradation in this region. [ABSTRACT FROM AUTHOR]

Aims: Long-duration drought can alter ecosystem plant species composition with subsequent effects on carbon cycling. We conducted a rainfall manipulation field experiment to address the question: how does drought-induced vegetation change, specifically shrub encroachment into grasslands, regulate impacts of subsequent drought on soil CO2 efflux (Rs) and its components (autotrophic and heterotrophic, Ra and Rh)? Methods: We conducted a two-year experiment in Inner Mongolia plateau, China, using constructed steppe communities including graminoids, shrubs and their mixture (graminoid + shrub) to test the effects of extreme-duration drought (60-yr return time) on Rs, Rh and Ra. Results: Our results indicated that extreme-duration drought reduced net primary production, with subsequent effects on Rs, Rh and Ra in all three vegetation communities. There was a larger relative decline in Ra (35–54%) than Rs (30–37%) and Rh (28–35%). Interestingly, we found Rs in graminoids is higher than in shrubs under extreme drought. Meanwhile, Rh declines were largest in the shrub community. Although Ra and Rh both decreased rapidly during drought treatment, Rh recovered quickly after the drought, while Ra did not, limiting the Rs recovery. Conclusions: This study suggests that plant species composition regulates several aspects of soil CO2 efflux response to climate extremes. This regulation may be limited by above- and below-ground net primary production depending on soil water availability. The results of this experiment address a critical knowledge gap in the relationship between soil respiration and plant species composition. With shrub encroachment into grasslands, total soil respiration is reduced and can partly offset the effect of reduction in productivity under drought stress. [ABSTRACT FROM AUTHOR]

Biological nitrogen fixation, conducted by soil diazotrophs, is the primary nitrogen source for natural grasslands. However, the diazotrophs in grassland soils are still far from fully investigated. Particularly, their regional-scale distribution patterns have never been systematically examined. Here, soils (0–5 cm) were sampled from 54 grasslands on the Tibetan Plateau to examine the diazotroph abundance, diversity, and community composition, as well as their distribution patterns and driving factors. The diazotroph abundance was expressed as nifH gene copies, measured using real-time PCR. The diversity and community composition of diazotrophs were analyzed through MiSeq sequencing of nifH genes. The results showed that Cyanobacteria (47.94%) and Proteobacteria (45.20%) dominated the soil diazotroph communities. Most Cyanobacteria were classified as Nostocales which are main components of biological crusts. Rhizobiales, most of which were identified as potential symbiotic diazotrophs, were also abundant in approximately half of the soil samples. The soil diazotroph abundance, diversity, and community composition followed the distribution patterns in line with mean annual precipitation. Moreover, they also showed significant correlations with prokaryotic abundance, plant biomass, vegetation cover, soil pH values, and soil nutrient contents. Among these environmental factors, the soil moisture, organic carbon, available phosphorus, and inorganic nitrogen contents could be the main drivers of diazotroph distribution due to their strong correlations with diazotroph indices. These findings suggest that autotrophic and symbiotic diazotrophs are the predominant nitrogen fixers in Tibetan grassland soils, and highlight the key roles of water and nutrient availability in determining the soil diazotroph distribution on the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

Abstract: Given the important contributions of semiarid region to global land carbon cycle, accurate modeling of the interannual variability (IAV) of terrestrial gross primary productivity (GPP) is important but remains challenging. By decomposing GPP into leaf area index (LAI) and photosynthesis per leaf area (i.e., GPP_leaf), we investigated the IAV of GPP and the mechanisms responsible in a temperate grassland of northwestern China. We further assessed six ecosystem models for their capabilities in reproducing the observed IAV of GPP in a temperate grassland from 2004 to 2011 in China. We observed that the responses to LAI and GPP_leaf to soil water significantly contributed to IAV of GPP at the grassland ecosystem. Two of six models with prescribed LAI simulated of the observed IAV of GPP quite well, but still underestimated the variance of GPP_leaf, therefore the variance of GPP. In comparison, simulated pattern by the other four models with prognostic LAI differed significantly from the observed IAV of GPP. Only some models with prognostic LAI can capture the observed sharp decline of GPP in drought years. Further analysis indicated that accurately representing the responses of GPP_leaf and leaf stomatal conductance to soil moisture are critical for the models to reproduce the observed IAV of GPP_leaf. Our framework also identified that the contributions of LAI and GPP_leaf to the observed IAV of GPP were relatively independent. We conclude that our framework of decomposing GPP into LAI and GPP_leaf has a significant potential for facilitating future model intercomparison, benchmarking and optimization should be adopted for future data‐model comparisons. [ABSTRACT FROM AUTHOR]