Search

The relationship between plant aboveground biomass and diversity typically follows a unimodal pattern, showing a positive correlation in resource‐poor habitats and a negative correlation in resource‐rich environments. Precipitation is a crucial resource for both plant biomass and diversity in terrestrial ecosystems. However, the impact of precipitation changes on the relationship between plant biomass and diversity remains unclear. We conduct a water addition field experiment in a semiarid grassland and identify a unimodal relationship between plant biomass and species richness under ambient conditions. Water addition delays the declining phase of this unimodal curve and shift it upward compared to ambient conditions. Our meta‐analysis of water addition experiments conducted across major biomes worldwide (grassland, shrubland, desert, and forest) supports this finding, while water reduction does not alter the biomass–diversity relationship. Water addition increases biomass in all climate but only increases species richness in arid and semiarid climate. Similarly, water reduction decreases biomass in all climate but only reduces species richness in arid and semiarid climate. Species richness in dry subhumid and humid climate does not change significantly. Furthermore, our field experiment shows that water addition increases plant diversity while decreasing soil inorganic nitrogen levels. The increase in one resource, such as water, leads to the scarcity of another, such as nutrient, thus postponing the declining phase of the plant biomass–diversity relationship typically observed in resource‐rich habitats. Our research contributes to predicting the plant biomass–diversity relationship under changing precipitation conditions and highlights the complex interplay between water availability, nutrient level, and plant diversity. [ABSTRACT FROM AUTHOR]

Crossing certain aridity thresholds in global drylands can lead to abrupt decays of ecosystem attributes such as plant productivity, potentially causing land degradation and desertification. It is largely unknown, however, whether these thresholds can be altered by other key global change drivers known to affect the water-use efficiency and productivity of vegetation, such as elevated CO2 and nitrogen (N). Using >5000 empirical measurements of plant biomass, we showed that crossing an aridity (1–precipitation/potential evapotranspiration) threshold of ∼0.50, which marks the transition from dry sub-humid to semi-arid climates, led to abrupt declines in aboveground biomass (AGB) and progressive increases in root:shoot ratios, thus importantly affecting carbon stocks and their distribution. N addition significantly increased AGB and delayed the emergence of its aridity threshold from 0.49 to 0.55 (P  < 0.05). By coupling remote sensing estimates of leaf area index with simulations from multiple models, we found that CO2 enrichment did not alter the observed aridity threshold. By 2100, and under the RCP 8.5 scenario, we forecast a 0.3% net increase in the global land area exceeding the aridity threshold detected under a scenario that includes N deposition, in comparison to a 2.9% net increase if the N effect is not considered. Our study thus indicates that N addition could mitigate to a great extent the negative impact of increasing aridity on plant biomass in drylands. These findings are critical for improving forecasts of abrupt vegetation changes in response to ongoing global environmental change. [ABSTRACT FROM AUTHOR]

Understanding the process of dryland degradation is crucial to combating desertification and maintaining land sustainability. To identify important indicators of dryland degradation, we conducted a field survey of 46 drylands spanning an aridity gradient across the Tibetan Plateau. Our random forest model suggested that soil sand content was the most important predictor of variation in soil fertility (carbon, nitrogen, and phosphorus). Most soil fertility showed a nonlinear and abrupt decline with increasing soil sand content, and displayed three sequential thresholds. First, soil organic carbon sharply decreased beyond a soil sand content threshold of 47%. Second, exceeding a subsequent threshold of 70%, the total nitrogen and light fraction carbon declined dramatically with increasing soil sand content. Finally, soil heavy fraction carbon, inorganic carbon, and total carbon were drastically reduced when the soil sand content exceeded 80%. The three soil fertility thresholds along the gradient of the soil sand content indicated a sequence of dryland degradation phases. Our findings provide an approach for detecting the severity of dryland degradation and suggest vulnerable areas of degradation on the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

Deadly humid heat conditions exceeding human thermoregulatory capacity have been reported; however, whether and where the deadly humid heat events occur consecutively across the land surface are largely unknown. We calculate the maximum consecutive days of deadly humid heat, defined as daily maximum wet‐bulb temperature (TWmax) ≥35°C, for observations of 9,278 meteorological stations and for simulations of 14 global climate models. We further define short and long deadly humid heatwaves as a period of 3–4 and ≥5 consecutive days with daily TWmax ≥35°C, respectively. Our analyses show that six stations in some subtropical regions have experienced deadly humid heat with daily TWmax ≥35°C, but only occurs in individual days. Deadly humid heatwaves increase exponentially as the global mean temperature rising. When limiting global warming within 1.5°C, long deadly humid heatwaves will not occur across the land surface, and short deadly humid heatwaves will only emerge in some drylands but not in humid areas. Under 2°C warming, 0.09% of the global land, 0.42% of the human population, and 0.56% of the global centres of crop diversity are projected to be exposed to long deadly humid heatwaves. Meanwhile, 18% of the deadly humid heatwaves lasting ≥3 consecutive days will occur in humid areas; the fractions are projected to rapidly increase in humid areas as temperature rising further. At the end of the century, the percentage of land areas and human population exposed to deadly humid heatwaves lasting ≥3 consecutive days are expected to be 76‐times higher than that under 1.5°C warming level. Our finding suggests that keeping global warming within 1.5°C will significantly constrain the emergence of prolonged deadly humid heatwaves and thus reduce the risk of the human population especially outdoor agricultural workers. [ABSTRACT FROM AUTHOR]

The microbial priming effect—the decomposition of soil organic carbon (SOC) induced by plant inputs—has long been considered an important driver of SOC dynamics, yet we have limited understanding about the direction, intensity, and drivers of priming across ecosystem types and biomes. This gap hinders our ability to predict how shifts in litter inputs under global change can affect climate feedbacks. Here, we synthesized 18,919 observations of CO2 effluxes in 802 soils across the globe to test the relative effects (i.e., log response ratio [RR]) of litter additions on native SOC decomposition and identified the dominant environmental drivers in natural ecosystems and agricultural lands. Globally, litter additions enhanced native SOC decomposition (RR = 0.35, 95% CI: 0.32–0.38), with greater priming effects occurring with decreasing latitude and more in agricultural soils (RR = 0.43) than in uncultivated soils (RR = 0.28). In natural ecosystems, soil pH and microbial community composition (e.g., bacteria: fungi ratio) were the best predictors of priming, with greater effects occurring in acidic, bacteria‐dominated sandy soils. In contrast, the substrate properties of plant litter and soils were the most important drivers of priming in agricultural systems since soils with high C:N ratios and those receiving large inputs of low‐quality litter had the highest priming effects. Collectively, our results suggest that, though different factors may control priming effects, the ubiquitous nature of priming means that alterations of litter quality and quantity owing to global changes will likely have consequences for global C cycling and climate forcing. [ABSTRACT FROM AUTHOR]

Accurate long-term temperature and precipitation estimates at high spatial and temporal resolutions are vital for a wide variety of climatological studies. We have produced a new, publicly available, daily, gridded maximum temperature, minimum temperature, and precipitation dataset for China with a high spatial resolution of 1 km that covers a long-term period (1961 to 2019). It has been named the HRLT, and the dataset is publicly available at 10.1594/PANGAEA.941329 (Qin and Zhang, 2022). In this study, the daily gridded data were interpolated using comprehensive statistical analyses, which included machine learning methods, the generalized additive model, and thin plate splines. It was based on the 0.5 ∘ × 0.5 ∘ gridded dataset from the China Meteorological Administration, together with covariates for elevation, aspect, slope, topographic wetness index, latitude, and longitude. The accuracy of the HRLT daily dataset was assessed using observation data from meteorological stations across China. The maximum and minimum temperature estimates were more accurate than the precipitation estimates. For maximum temperature, the mean absolute error (MAE), root mean square error (RMSE), Pearson's correlation coefficient (Cor), coefficient of determination after adjustment (R2), and Nash–Sutcliffe modeling efficiency (NSE) were 1.07 ∘ C, 1.62 ∘ C, 0.99, 0.98, and 0.98, respectively. For minimum temperature, the MAE, RMSE, Cor, R2 , and NSE were 1.08 ∘ C, 1.53 ∘ C, 0.99, 0.99, and 0.99, respectively. For precipitation, the MAE, RMSE, Cor, R2 , and NSE were 1.30 mm, 4.78 mm, 0.84, 0.71, and 0.70, respectively. The accuracy of the HRLT was compared to those of three other existing datasets, and its accuracy was either greater than the others, especially for precipitation, or comparable in accuracy, but with higher spatial resolution or over a longer time period. In summary, the HRLT dataset, which has a high spatial resolution, covers a longer period of time and has reliable accuracy. [ABSTRACT FROM AUTHOR]

Soil microbial communities regulate soil carbon feedbacks to climate warming through microbial respiration (i.e., metabolic rate). A thorough understanding of the responses of composition, biomass, and metabolic rate of soil microbial community to warming is crucial to predict soil carbon stocks in a future warmer climate. Therefore, we conducted a field manipulative experiment in a semiarid grassland on the Loess Plateau of China to evaluate the responses of the soil microbial community to increased temperature from April 2015 to December 2017. Soil temperature was 2.0°C higher relative to the ambient when open‐top chambers (OTCs) were used. Warming did not affect microbial biomass or the composition of microbial functional groups. However, warming significantly decreased microbial respiration, directly resulting from soil pH decrease driven by the comediation of aboveground biomass increase, inorganic nitrogen increase, and moisture decrease. These findings highlight that the soil microbial community structure of semiarid grasslands resisted the short‐term warming by 2°C, although its metabolic rate declined. [ABSTRACT FROM AUTHOR]

Understanding whether soil microbial respiration adapts to the ambient thermal climate with an enhanced or compensatory response, hence potentially stimulating or slowing down soil carbon losses with warming, is key to accurately forecast and model climate change impacts on the global carbon cycle. Despite the interest in this topic and the plethora of recent studies in natural ecosystems, it has been seldom explored in croplands. Using two recently published independent datasets of soil microbial metabolic quotient (MMQ; microbial respiration rate per unit biomass) and carbon use efficiency (CUE; partitioning of C to microbial growth vs. respiration), we find a compensatory thermal adaptive response for MMQ in global croplands. That is, mean annual temperature (MAT) has a negative effect on MMQ. However, this compensatory thermal adaptation is only half or less of that found in previous studies for noncultivated ecosystems. In contrast to the negative MMQ‐MAT pattern, microbial CUE increases with MAT across global croplands. By incorporating this positive CUE‐MAT relationship (greater C partitioning into microbial growth rather than respiration with increasing temperature) into a microbial‐explicit soil organic carbon model, we successfully predict the thermal compensation of MMQ observed in croplands. Our model‐data integration and database cross‐validation suggest that a warmer climate may select for microbial communities with higher CUE, providing a plausible mechanism for their compensatory metabolic response. By helping to identify appropriate representations of microbial physiological processes in soil biogeochemical models, our work will help build confidence in model projections of cropland C dynamics under a changing climate. Key Points: Soil microbial respiration rates adapt to ambient temperature with a compensatory response in global croplandsThe compensatory thermal adaptive capacity of soil microorganisms is lower in croplands than in natural ecosystemsA warmer climate may select for microbial communities with higher carbon use efficiency in cropland soils [ABSTRACT FROM AUTHOR]

The degree to which climate warming will stimulate soil organic carbon (SOC) losses via heterotrophic respiration remains uncertain, in part because different or even opposite microbial physiology and temperature relationships have been proposed in SOC models. We incorporated competing microbial carbon use efficiency (CUE)–mean annual temperature (MAT) and enzyme kinetic–MAT relationships into SOC models, and compared the simulated mass‐specific soil heterotrophic respiration rates with multiple published datasets of measured respiration. The measured data included 110 dryland soils globally distributed and two continental to global‐scale cross‐biome datasets. Model–data comparisons suggested that a positive CUE–MAT relationship best predicts the measured mass‐specific soil heterotrophic respiration rates in soils distributed globally. These results are robust when considering models of increasing complexity and competing mechanisms driving soil heterotrophic respiration–MAT relationships (e.g., carbon substrate availability). Our findings suggest that a warmer climate selects for microbial communities with higher CUE, as opposed to the often hypothesized reductions in CUE by warming based on soil laboratory assays. Our results help to build the impetus for, and confidence in, including microbial mechanisms in soil biogeochemical models used to forecast changes in global soil carbon stocks in response to warming. [ABSTRACT FROM AUTHOR]

In 1999, the Grain for Green Project was implemented by the Chinese government. Since then, the vegetation of Zuli River Basin, a semi-arid river basin of the Chinese Loess Plateau, has been greatly changed. Clearly understanding the impact of natural and artificial factors on vegetation change is important for policy making and ecosystem management. In this study, spatio-temporal variations in vegetation cover in Chinese Zuli River Basin during 1999–2016 were investigated using Landsat normalized difference vegetation index (NDVI) data. Analyses of several indicators, including changes in NDVI in different slopes and land use changes and the relationships between climatic factors and NDVI change, were presented to quantitatively evaluate the effects of agriculture, climate, and policy on NDVI change. The NDVI in the Zuli River Basin increased during the study period, and the main contributors to this change were forest in 1999–2011, cropland, abandoned farmland, and grassland in 2009–2016, and land with slopes ≤ 15°. Land with slope > 15°, where the "Project" was implemented, slightly contributed to the increase in regional NDVI. In 1999–2011, the project (−98.16%) combined with climate change (−68.18%) showed negative effects on the increase in NDVI in the Zuli River Basin, but agriculture (22.28%) played a positive role in increasing this index. In 2009–2016 and 1999–2016, the project (38.45% and 35.25%, respectively), the project combined with climate change (49.83% and 46.30%, respectively), agriculture (18.61% and 23.30%, respectively), promoted increases in NDVI in the basin. [ABSTRACT FROM AUTHOR]

Past vegetation and climatic conditions are known to influence current biodiversity patterns. However, whether their legacy effects affect the provision of multiple ecosystem functions, that is, multifunctionality, remains largely unknown. Here we analyzed soil nutrient stocks and their transformation rates in 236 drylands from six continents to evaluate the associations between current levels of multifunctionality and legacy effects of the Last Glacial Maximum (LGM) desert biome distribution and climate. We found that past desert distribution and temperature legacy, defined as increasing temperature from LGM, were negatively correlated with contemporary multifunctionality even after accounting for predictors such as current climate, soil texture, plant species richness, and site topography. Ecosystems that have been deserts since the LGM had up to 30% lower contemporary multifunctionality compared with those that were nondeserts during the LGM. In addition, ecosystems that experienced higher warming rates since the LGM had lower contemporary multifunctionality than those suffering lower warming rates, with a ~9% reduction per extra degree Celsius. Past desert distribution and temperature legacies had direct negative effects, while temperature legacy also had indirect (via soil sand content) negative effects on multifunctionality. Our results indicate that past biome and climatic conditions have left a strong "functionality debt" in global drylands. They also suggest that ongoing warming and expansion of desert areas may leave a strong fingerprint in the future functioning of dryland ecosystems worldwide that needs to be considered when establishing management actions aiming to combat land degradation and desertification. [ABSTRACT FROM AUTHOR]

Understanding under which climate and soil conditions the plant productivity–precipitation relationship is linear or nonlinear is useful for accurately predicting the response of ecosystem function to global environmental change. Using long-term (2000–2016) net primary productivity (NPP)–precipitation datasets derived from satellite observations, we identify > 5600 pixels in the North Hemisphere landmass that fit either linear or nonlinear temporal NPP–precipitation relationships. Differences in climate (precipitation, radiation, ratio of actual to potential evapotranspiration, temperature) and soil factors (nitrogen, phosphorous, organic carbon, field capacity) between the linear and nonlinear types are evaluated. Our analysis shows that both linear and nonlinear types exhibit similar interannual precipitation variabilities and occurrences of extreme precipitation. Permutational multivariate analysis of variance suggests that linear and nonlinear types differ significantly regarding to radiation, ratio of actual to potential evapotranspiration, and soil factors. The nonlinear type possesses lower radiation and/or less soil nutrients than the linear type, thereby suggesting that nonlinear type features higher degree of limitation from resources other than precipitation. This study suggests several factors limiting the responses of plant productivity to changes in precipitation, thus causing nonlinear NPP–precipitation pattern. Precipitation manipulation and modeling experiments should combine with changes in other climate and soil factors to better predict the response of plant productivity under future climate. [ABSTRACT FROM AUTHOR]

Responses of soil respiration (R s ) to increasing nitrogen (N) deposition and warming will have far-reaching influences on global carbon (C) cycling. However, the seasonal (growing and non-growing seasons) difference of R s responses to warming and N deposition has rarely been investigated. We conducted a field manipulative experiment in a semi-arid alfalfa-pasture of northwest China to evaluate the response of R s to nitrogen addition and warming from March 2014 to March 2016. Open-top chambers were used to elevate temperature and N was enriched at a rate of 4.42 g m − 2 yr − 1 with NH 4 NO 3 . Results showed that (1) N addition increased R s by 14% over the two-year period; and (2) warming stimulated R s by 15% in the non-growing season, while inhibited it by 5% in the growing season, which can be explained by decreased plant coverage and soil water. The main effect of N addition did not change with time, but that of warming changed with time, with the stronger inhibition observed in the dry year. When N addition and warming were combined, an antagonistic effect was observed in the growing season, whereas a synergism was observed in the non-growing season. Overall, warming and N addition did not affect the Q10 values over the two-year period, but these treatments significantly increased the Q10 values in the growing season compared with the control treatment. In comparison, combined warming and nitrogen addition significantly reduced the Q10 values compared with the single factor treatment. These results suggest that the negative indirect effect of warming-induced water stress overrides the positive direct effect of warming on R s . Our results also imply the necessity of considering the different R s responses in the growing and non-growing seasons to climate change to accurately evaluate the carbon cycle in the arid and semi-arid regions. [ABSTRACT FROM AUTHOR]

Many uncertainties exist in our quest to understand and predict how terrestrial ecosystems will respond to climate change. A particularly challenging issue is how increases in extreme precipitation regimes, which are characterized by larger but fewer individual precipitation events, will impact ecosystems. Based on a wide-ranging review of empirical studies of both hydrological and ecological processes, Knapp et al. (2008) generated a suite of hypotheses positing how these processes would respond to an increase in extreme precipitation regimes and, from this, concluded that mesic ecosystems would be more detrimentally impacted than xeric ones. In this study we present the first thorough test of these hypotheses by examining how forest, shrubland, grassland and desert ecosystems of the Tibetan Plateau, having very different vegetation and climate characteristics, respond to more extreme rainfall regimes. We accomplished this by using a simulation model (Biome-BGC) to examine the integrated behavior of these ecosystems based on the simultaneous responses and interactions of 10 hydrological and ecological processes: runoff, canopy evaporation, soil evaporation, soil water storage, transpiration, net primary productivity, soil respiration, net ecosystem exchange, nitrogen [N] mineralization, and N leaching. We ran forty-year simulations (1986–2008) where we manipulated mean growing season precipitation to create more extreme intra-annual precipitation regimes characterized by lower precipitation frequencies, longer dry periods, and larger individual (daily) precipitation events. When compared to ambient conditions, our simulations showed that increases in extreme rainfall regimes (1) impacted all hydrological processes in mesic ecosystems, resulting in a reduction of soil mineral N due to increased leaching; and (2) enhanced plant growth in xeric ecosystems, leading to larger and denser canopies and higher light interception. The responses of hydrological processes tended to follow Knapp et al.’s hypotheses more so than ecological responses. Overall, responses of mesic ecosystems closely followed the hypotheses but xeric ecosystems were highly variable and only weakly consistent with them. Our findings provide new insights as to how more extreme rainfall regimes may potentially affect the functioning of terrestrial ecosystems. [ABSTRACT FROM AUTHOR]

Trend and variability of China's summer precipitation during 1955-2008 are examined. The results show that (1) summer precipitation has significantly increased in South China and significantly decreased in North China, while there are no significant trends in the West and China overall; (2) interannual variability is greatly intensified all over China with more wet and dry extreme years in the second bin (1977-2008) than in the first bin (1955-1976). Covariability between China's summer precipitation and the Pacific sea surface temperature ( SST) is analysed using singular value decomposition ( SVD) technique. The first mode of SVD displays an El Niño-Southern Oscillation ( ENSO)-like SST pattern, the associated precipitation shows negative anomalies in North China; the second mode exhibits SST fluctuations in the western and central Pacific that corresponding to positive anomalies in South China. In addition, cooling over the mid-lower reaches of Yangtze River basin (i.e. South-central China) might also contribute to decreased (increased) summer precipitation in North (South) China. The percentages of variance of summer precipitation and SST explained by each mode suggest that the increased variability of the second SVD mode in the second bin is consistent with intensified variability of China's summer precipitation in the same period. © 2013 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Human activities are critical factors influencing ecosystem sustainability. However, knowledge on regarding the mechanisms underlying the response of vegetation dynamics to human activities remains limited. To detect the driving factors and their individual contribution to the grassland vegetation dynamics in China's Loess Plateau, a structural equation model (SEM) and a principal component regression model were built. The SEM showed that population change and urbanization, temperature and humidity, and agriculture and economy accounted for 62.5%, 31.2%, and 7.7%, respectively, of the overall impact directly affecting grassland vegetation dynamics. Furthermore, the principal component regression model demonstrated that the effects of the urbanization rate on the grassland above-ground biomass exceeded those of the other factors. The agriculture population had the maximum negative effect on grassland area. The higher the urbanization rate means the higher the number of residents migrates from rural to urban areas. Following this argument, the disturbances of human activities to grassland vegetation were expected to gradually decrease in rural areas, where the vast majority of the Loess Plateau is located. The migration of rural residents to urban areas promoted the increase in biomass and areas of grassland vegetation. Our findings suggest that the effect of urbanization should be considered when assessing vegetation change. [ABSTRACT FROM AUTHOR]

Pasture-crop rotation has been considered as an efficient agronomical practice to improve soil and water conservation, develop livestock production, and promote food security. However, the characteristics of soil water restoration and performances of crop yield and water use efficiency (WUE) after conversion of long-term leguminous pasture into croplands still remain unclear. A field experiment was conducted in China's Loess Plateau to investigate soil water restoration and wheat yields in crop rotation with Italian ryegrass (Festuca perennis Lam.) and winter wheat (Triticum aestivum L.) converted from three 9-year-old leguminous pastures, viz. milk vetch (Astragalus adsurgens Pall.), alfalfa (Medicago sativa L.) and bush clover (Lespedeza davurica S.), and unplanted control (fallow). Soil water in the alfalfa treatment gradually recovered from up to down compared to the fallow treatment (control) during cultivation phase. After one year of rotation, the recovery levels of soil water in the three pasture-crop rotation systems at 0–500 cm soil depth were 97.1%, 95.5% and 94.2%, respectively, compared to the fallow treatment. The legume treatments significantly enhanced the crop yield (35.6%−64.5%), aboveground biomass (28.7%−59.4%) and WUE (60%−68.3%) of winter wheat compared with fallow. These results imply that the concerns about soil desiccation from long-term alfalfa was resolvable after long-term alfalfa converted into cropland in the rainfed farming area of Loess Plateau. The results also suggest that legume pasture-crop rotation can facilitate achieving a sustainable development of rainfed farming. • Soil water could be recovered after conversion of long-term leguminous pasture into cropland. • Fastest soil water restoration happened in alfalfa-crop rotation system with a top-down recovery pattern. • Legume pasture-crop rotation significantly increase wheat aboveground biomass and yield. [ABSTRACT FROM AUTHOR]

Abstract China initiated the "Grain for Green Project" in 1999 to mitigate soil erosion. The vegetation cover of the Chinese Loess Plateau, one of the most erosive regions in the world, has been greatly increased. However, studies on quantitatively investigating the climate change and human activities on vegetation coverage change were rare. In this study, spatio-temporal changes in vegetation coverage were investigated using MODIS normalized difference vegetation index (NDVI) data over 2000–2016. And a new method was introduced using Net Primary Productivity (NPP) model and relationship between NPP and NDVI to quantitatively and spatially distinguish the NDVI affected by climate change and human activities. Results showed that mean NDVI value over 2009–2016 were 14.46% greater than that over 2000–2007. In order to quantify the contribution of climate change and human activities to vegetation change, an NPP model suitable for the grassland of the Chinese Loess Plateau was identified using biomass observations from field survey and literature. The NDVI affected by climate change (NDVI climate) was estimated by the NPP model and the relationship between NPP and NDVI. And the NDVI affected by human activities (NDVI human) was calculated by actual NDVI minus NDVI climate. Comparison of the two stages showed that human activities and climate change contributed 42.35% and 57.65% respectively to the ΔNDVI on grassland in the Loess Plateau. After analysis of numerous NDVI human related factors, the slopes restored by the "Grain for Green Project" was considered the main influence factor of human activities. Graphical abstract Unlabelled Image Highlights • Novel method was developed to distinguish climate change and human activities. • Human activities contributed 42.35% to the vegetation change. • Climate change contributed 57.65% to the vegetation change. • The "Grain for Green Project" was the main human influence on vegetation. [ABSTRACT FROM AUTHOR]

Ridge-furrow mulching can reduce soil evaporation and conserve rainfall, thereby increasing crop yield and water use efficiency (WUE) in dryland cropping systems. In this study, we collected 837 observations from 50 published papers and used meta-analysis to investigate whether ridge-furrow and mulching practices are equally effective on maize yield, WUE and evapotranspiration (ET) across a range of precipitation and temperature gradients and soil types in China. Five practices were included: (i) straw mulch on flat plots (SMF), (ii) straw mulch on ridge-furrow plots (SMR), (iii) plastic mulch on flat plots (PMF), (iv) plastic mulch on ridge-furrow plots (PMR), and (v) flat plots without mulch, which was used as a control (CK). The meta-analysis showed that both straw mulch and plastic mulch significantly increased maize yields and WUE (except for SMR), and that plastic mulch was more effective than straw mulch in increasing yields, particularly in cold and dry environments. PMR has the highest yields and is more effective in clay loam than in silt loam soils. Straw mulch, but particularly plastic mulch, increased the soil moisture compared to the CK, while plastic mulch increased soil temperature, mainly in spring. However, the positive effect of plastic mulch on maize yield diminished with increasing mean growing-season temperature and precipitation, reaching zero (similar to the CK of no mulch and flat plots) when the growing-season precipitation was greater than 770 mm and the mean growing-season air temperature exceeded 24 °C. The small benefit of straw mulch (on average about 12%) was similar across the precipitation and temperature gradients, including when the benefits of plastic mulch reached zero. While our analysis has shown the benefits of ridge-furrow plastic mulch on yield and water-use efficiency, it has also highlighted the limitations of the benefits. The results provide a guide to the regions where plastic-film mulch and ridge-furrow planting are likely to improve maize yields and regions where the benefits are likely to be limited. [ABSTRACT FROM AUTHOR]

Lagged precipitation effect explains a large proportion of annual aboveground net primary productivity in some dryland ecosystems. Using satellite-derived plant productivity and precipitation datasets in the Northern Hemisphere drylands during 2000–2018, we identify 1111 pixels mainly located in the Tibetan Plateau, the western US, and Kazakhstan where productivities are significantly correlated with previous-year precipitation (hereafter, the lagged type). Differences in climatic and edaphic factors between the lagged and unlagged (pixels where productivities are not correlated with previous-year precipitation) types are evaluated. Permutational multivariate analysis of variance shows that the two types differ significantly regarding six climatic and edaphic factors. Compared to unlagged type, water availability, soil organic carbon, total nitrogen, field capacity, silt content and radiation are more sensitive to changes in precipitation in lagged type. Water availability is the most important factor for distinguishing the two types, followed by soil organic carbon, total nitrogen, field capacity, soil texture, and radiation. Our study suggests that the altered sensitivities of several climatic and edaphic factors to precipitation collectively affect the lagged effect of precipitation on productivity in drylands. Unlabelled Image • Climatic-edaphic factors differ significantly between lagged and unlagged drylands. • Lagged drylands were characterized by high sensitivity of water availability, SOC and nitrogen content to precipitation. • Water availability is the most important factor controlling lagged precipitation effect. [ABSTRACT FROM AUTHOR]

Precipitation is known to have legacy effects on plant diversity and production of many terrestrial ecosystems. Precipitation regimes are expected to become more variable with increasing extreme precipitation events. However, how previous-year precipitation regimes affect the current-year aboveground biomass (AGB) remains largely unknown. Here we measured long-term (2004–2017) AGB in a semi-arid grassland of the Chinese Loess Plateau to evaluate the impact of previous-year precipitation amount on current-year AGB. Furthermore, to assess the response of current-year AGB to previous-year precipitation regimes, we conducted a field manipulation experiment that included three precipitation regimes during 2014–2017: (i) ambient precipitation, (ii) monthly added four 5 mm rain events, and (iii) monthly added one 20 mm event. Both the long-term (2004–2017) observations under ambient precipitation and short-term (2014–2017) measurements under manipulative treatments showed significant positive effects of previous-year precipitation on current-year AGB. Our path analysis suggested that previous-year precipitation frequency had negative effects on the current-year density and mean height of grass (Leymus secalinus) while had positive effects on forb (Artemisia capillaris). The forb had much smaller height and AGB (65% and 53% less, respectively) than the grass. Consequently, the AGB reduced in the weekly small events treatment, causing the sensitivity of AGB to precipitation to decrease. Therefore, our findings indicated that the impacts of precipitation regimes on plant community dynamics should be taken into consideration while assessing the precipitation legacy effect on ecosystem production. Unlabelled Image • Current-year aboveground biomass (AGB) increased linearly with previous-year precipitation. • Precipitation frequency negatively affects the sensitivity of AGB to precipitation. • Previous-year precipitation amount increases the current-year grass density. • Previous-year precipitation frequency increases the current-year forb density. [ABSTRACT FROM AUTHOR]

The northern hemisphere has experienced regional cooling, especially during the global warming hiatus (1998-2012) due to ocean energy redistribution. However, the lack of studies about the natural cooling effects hampers our understanding of vegetation responses to climate change. Using 15,125 ground phenological time series at 3,620 sites since the 1950s and 31-year satellite greenness observations (1982-2012) covering the warming hiatus period, we show a stronger response of leaf onset date (LOD) to natural cooling than to warming, i.e. the delay of LOD caused by 1°C cooling is larger than the advance of LOD with 1°C warming. This might be because cooling leads to larger chilling accumulation and heating requirements for leaf onset, but this non-symmetric LOD response is partially offset by warming-related drying. Moreover, spring greening magnitude, in terms of satellite-based greenness and productivity, is more sensitive to LOD changes in the warming area than in the cooling. These results highlight the importance of considering non-symmetric responses of spring greening to warming and cooling when predicting vegetation-climate feedbacks., (© The Author(s) 2023. Published by Oxford University Press on behalf of National Academy of Sciences.)