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• 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]

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]

• 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] 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]

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]

• 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]

• 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]

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]

Climate extremes are expected to increase in frequency and intensity as a consequence of anthropogenic climate change attributed to the rise of atmospheric concentrations of greenhouse gases (GHGs). However, studies on the impacts of climate extremes on terrestrial ecosystems are limited. Here, we experimentally imposed extreme drought and a heat wave (∼60-year recurrence) to investigate their effects on GHGs fluxes of a semiarid grassland in China. We estimated a 16% and 38% percent reduction in net ecosystem CO 2 uptake caused by the heat wave and drought respectively, but via different mechanisms. Drought reduced gross ecosystem productively (GEP) and to a lower extent ecosystem respiration (ER). By contrast, the simulated heat wave suppressed only GEP while ER remained stable. The climate extremes also created a legacy effect on GEP and NEE lasting until the end of the growing season, whereas ER recovered immediately. Although CH 4 and N 2 O fluxes were unaffected by the heat wave, drought promoted CH 4 uptake and suppressed N 2 O emission during the treatment period. The effect of drought on GHGs fluxes generally overwhelmed that of the heat wave treatment, and there were no interactive effects of these two types of climate extremes. Our results showed that responses of ecosystem GHGs exchange to climate extremes are strongly regulated by soil moisture status. In conclusion, future amplification of climate extremes could decrease the sink for GHGs, especially CO 2 , in this semiarid grasslands. [ABSTRACT FROM AUTHOR]

Soil microbes play a crucial role in myriad ecological processes in terrestrial ecosystem. With increasing nitrogen (N) loading, phosphorus (P) may become more limiting for soil microbes and these processes. However, it remains unclear to what extent P addition impacts soil microbial communities and respiration at global scale, especially under different N loadings. Therefore, we used a global meta-analysis to examine the effects of phosphorus addition on soil microbes based on 2293 paired observations from 129 studies in the world. Overall, P addition increased significantly total as well as fungal, bacterial, and actinomycete (ACT) phospholipid fatty acids (PLFAs), together with Gram+ bacteria (G+) and Gram- bacteria (G-) abundance regardless of N input or not. The increments were more pronounced under higher P addition rate or places with higher mean annual temperature or mean annual precipitation. Moreover, the fungi: bacteria ratio significantly decreased along elevational gradients. Furthermore, higher P addition frequency tended to have significantly more ACT PLFAs, as well as higher G+:G-, but significantly lower fungi: bacteria ratio (F:B). However, the responses of P addition on bacterial PLFAs and F:B were larger in forest than grassland, and cropland and varied with P fertilizer forms. In addition, the responses of soil organic carbon (SOC) contents was positively correlated with those of microbial biomass carbon (MBC) and bacterial PLFAs, and all these three parameters, in addition to fungal PLFAs, correlated positively with the response of soil respiration (Rs). Our results suggest that phosphorus addition had globally positive effects on soil microbes with different N loadings, and the positive effects of soil microbial abundance tended to promote heterotrophic respiration (Rh) and Rs. These results deepen our understanding of soil microbial community structure and function dynamics under increasing P deposition. They also provide extensive evidences and bases for parameterization of soil carbon cycling models incorporating microbial responses under global climate change. • We found phosphorus addition had globally positive effects on soil microbes. • The soil microbial biomass positively correlated with phosphorus addition rate, mean annual temperature (MAT) and mean annual precipitation (MAP). • The responses of soil microbes varied with P addition forms and ecosystem types. • The positive effects of soil microbes tended to promote Rs and Rh. [ABSTRACT FROM AUTHOR]

Abstract: Gross primary productivity (GPP) is a key component of land–atmospheric carbon exchange. Reliable calculation of regional/global GPP is crucial for understanding the response of terrestrial ecosystems to climate change and human activity. In recent years, many light use efficiency (LUE) models driven by remote sensing data have been developed for calculating GPP at various spatial and temporal scales. However, some studies show that GPP calculated by LUE models was biased by different degrees depending on sky clearness conditions. In this study, a two-leaf light use efficiency (TL-LUE) model is developed based on the MOD17 algorithm to improve the calculation of GPP. This TL-LUE model separates the canopy into sunlit and shaded leaf groups and calculates GPP separately for them with different maximum light use efficiencies. Different algorithms are developed to calculate the absorbed photosynthetically active radiation for these two groups. GPP measured at 6 typical ecosystems in China was used to calibrate and validate the model. The results show that with the calibration using tower measurements of GPP, the MOD17 algorithm was able to capture the variations of measured GPP in different seasons and sites. But it tends to understate and overestimate GPP under the conditions of low and high sky clearness, respectively. The new TL-LUE model outperforms the MOD17 algorithm in reproducing measured GPP at daily and 8-day scales, especially at forest sites. The calibrated LUE of shaded leaves is 2.5–3.8 times larger than that of sunlit leaves. The newly developed TL-LUE model shows lower sensitivity to sky conditions than the MOD17 algorithm. This study demonstrates the potential of the TL-LUE model in improving GPP calculation due to proper description of differences in the LUE of sunlit and shaded leaves and in the transfer of direct and diffuse light beams within the canopy. [Copyright &y& Elsevier]

Understanding the responses of soil C mineralization to climate change is critical for evaluating soil C cycling in future climatic scenarios. Here, we took advantage of a multifactor experiment to investigate the individual and combined effects of experimental warming and increased precipitation on soil C mineralization and C and N natural abundances at two soil depths (0-10 and 10-20 cm) in a semiarid Inner Mongolian grassland since April 2005. For each soil sample, we calculated potentially mineralizable organic C ( C) from cumulative CO-C evolved as indicators for labile organic C. The experimental warming significantly decreased soil C mineralization and C at the 10-20-cm depth ( P < 0.05). Increased precipitation, however, significantly increased soil pH, NO-N content, soil C mineralization, and C at the 0-10-cm depth and moisture and NO-N content at the 10-20-cm depth (all P < 0.05), while significantly decreased exchangeable NH-N content and C natural abundances at the two depths (both P < 0.05). There were significant warming and increased precipitation interactions on soil C mineralization and C, indicating that multifactor interactions should be taken into account in future climatic scenarios. Significantly negative correlations were found between soil C mineralization, C, and C natural abundances across the treatments (both P < 0.05), implying more plant-derived C input into the soils under increased precipitation. Overall, our results showed that experimental warming and increased precipitation exerted different influences on soil C mineralization, which may have significant implications for C cycling in response to climate change in semiarid and arid regions. [ABSTRACT FROM AUTHOR]