Asymmetric effects of daytime and night-time warming on Northern Hemisphere vegetation

Time-lag and accumulation responses of vegetation growth to average and extreme precipitation and temperature events in China between 2001 and 2020

Climate change is often closely related to vegetation dynamics; time lag (Tlag) and accumulative effects (Tacc) are non-negligible phenomena when studying the interaction between climate and vegetation. But, amidst the escalating frequency of extreme climatic events, the quantification of temporal effects (Teffects) of such extremes on vegetation remains scarce. This research quantifies the Tlag and Tacc responses of China's vegetation to episodes of extreme temperature and precipitation since the early 2000s, utilizing daily meteorological data series. Overall, the precipitation in China has become wetter, and nighttime temperatures have risen significantly. The proportion of areas with Teffects ranged from 1.15 % to 15.95 %, and the correlation coefficient between the climate indices and the Normalized Difference Vegetation Index (NDVI) increased by 0.05 to 0.38 when considering the Teffects, compared to not considering it. The Tacc of vegetation had the strongest response (70.74-88.01 %) to extreme events among all the tested climate indices. Moreover, the Tacc of consecutive climate events had a greater impact on vegetation growth than individual climate event. The average Tacc for extreme temperature and extreme precipitation was 1.7-3.09 months and 2.17-3.25 months, respectively. Events like the over 95 % (R95p) and 99 % (R99p) percentile heavy precipitation and the maximum precipitation amount in one day (Rx1day) caused significant Teffects on NDVI. In addition, 90 % of grasslands exhibit Tacc, mainly contributed by the extreme precipitation indices (55.7 %), while the Teffects of forests were stronger than those of extreme temperature. Furthermore, NDVI was more affected by annual precipitation than by extreme precipitation, but the opposite was true for temperature. The results of this study highlight the importance of considering the Tlag and Tacc when predicting the effects of climate change on vegetation dynamics.

Mapping and analyzing the spatiotemporal dynamics of forest aboveground biomass in the ChangZhuTan urban agglomeration using a time series of Landsat images and meteorological data from 2010 to 2020

In the context of global warming, there is a substantial demand for accurate and cost-effective assessment and comprehensive understanding of forest above-ground biomass (AGB) dynamics. The timeliness and low cost of optical remote sensing data enable the mapping of large-scale forest AGB dynamics. However, mapping forest AGB with optical remote sensing data presents challenges primarily due to data uncertainty and the complex nature of the forest environment. Previous studies have demonstrated the potential of meteorological data in enhancing forest AGB mapping. To accurately capture the dynamics of forest AGB, we initially acquired Landsat datasets, digital elevation model (DEM), and meteorological datasets (temperature, humidity, and precipitation) from 2010 to 2020 in Changsha-Zhuzhou-Xiangtan urban agglomeration (CZT) located in Hunan Province, China. Spectral variables (SVs), including spectral bands and vegetation indices, were extracted from Landsat images, while meteorological variables (MVs) were derived from the monthly meteorological data using the Savitzky-Golay (S-G) filtering algorithm. Additionally, terrain variables (TVs) were also extracted from the DEM data. Three modelling models, multiple linear regression (MLR), K nearest neighbor (KNN) and random forest (RF), were developed for mapping the dynamics of forest AGB in CZT. The result revealed that MVs have the potential to improve forest AGB mapping. Integration of MVs into the models resulted in a significant reduction in root mean square error (RMSE) ranging from 32.85 % to 19.25 % compared to utilizing only SVs. However, minimal improvement was observed with the inclusion of TVs due to negligible topographic relief within the study area. An upward trend of forest AGB in CZT was observed during this period, which can be attributed to the effective implementation of government environmental protection policies. It is confirmed that the meteorological data has significant contribution to forest AGB mapping, thereby endorsing advancements in forest resource monitoring and management programs.

Warming suppresses grassland recovery in biomass but not in community composition after grazing exclusion in a Mongolian grassland

We conducted a 4-year temperature manipulation experiment in a Mongolian grassland to examine the effect of daytime and nighttime warming on grassland recovery after grazing exclusion. After constructing a livestock exclusion fence in the grassland, we established daytime and daytime-and-nighttime warming treatments within the fenced area by a combination of open-top chambers (OTC) and electric heaters. We measured the numbers of plants and aboveground biomass by species after recording percentage vegetation cover every summer for three warming treatments inside the fence-non-warming, daytime warming, and daytime-and-nighttime warming-and for the grassland outside of the fence. OTCs increased daytime temperature by about 2.0 °C, and heaters increased nighttime temperature by 0.9 °C during the growing period. Grazing exclusion had little effect on grassland biomass but reduced the abundance of poorly palatable species and modified plant community composition. Daytime warming decreased soil moisture and lowered aboveground biomass within the fenced grassland but had little effect on plant community composition. Nighttime warming lowered soil moisture further but its effects on grassland biomass and community composition were undetectable. We concluded that recovery of plant biomass in grasslands degraded by grazing would be lowered by future climate warming through soil drying. Because warming had little effect on the recovery of community composition, adverse effects of warming on grassland recovery might be offset by improving plant productivity through mitigation of soil drying by watering. Soil drying due to nighttime warming might have detectable effects on vegetation when warming persists for a long time.

Asymmetric Warming of Day and Night Benefits the Early Growth of Acer mono Seedlings More Than Symmetric Warming

Asymmetric warming refers to the difference between the increase in daytime maximum temperature and the increase in nighttime minimum temperature and has been documented in temperate regions. However, its impacts on seedling growth have been largely ignored. In this study, seedlings of a widely distributed tree species, Acer mono Maxim., were exposed to both symmetric warming (SW) and asymmetric warming scenarios (day warming [DW], night warming [NW] and diurnal asymmetric warming [DAW]). Compared to control, all warming scenarios were found to enhance belowground biomass. DW promoted the seedling growth, while NW reduced the stem biomass. DAW did not impact the total biomass relative to the control. Compared to SW, DAW advanced phenology, increased indole-3-acetic acid content and chlorophyll content, which enhanced total biomass and stored more NSC in the root. Future DAW would be not beneficial to the growth of A. mono seedlings by comparing with the control. This research encourages further exploration of tree growth experiments under asymmetric warming conditions, as most studies tend to underestimate the warming effects on plant growth by focusing on SW. Incorporating the responses of seedling physiology and growth to non-uniform diurnal warming into earth system models is crucial for more accurately predicting carbon and energy balances in a warmer world.

Long-term grazing changed the spatial distributions of dominant species in typical steppe of Inner Mongolia

Dominant species occupy a pivotal role in plant community, influencing the structure and function of the ecosystem. The spatial distributions of dominant species can react to the effect of different grazing intensities, thereby reflecting their tolerance and adaptive strategies toward grazing. In this study, geostatistical methods were mainly used to study the spatial distribution characteristics of Stipa krylovii Roshev. and Leymus chinensis (Trin.) Tzvel. species at two interval scales (quadrat size 5 m × 5 m, 10 m × 10 m) and two treatments (free grazing, FG, 1.66 sheep·ha- 1·a- 1; control, CK, 0 sheep·ha- 1·a- 1) in typical steppe of Inner Mongolia. A systematic sampling method was used in each 100 m × 100 m representative sample plots to obtain the height, coverage, and density of all species in the community. The results showed that grazing altered the concentrated distribution of S. krylovii and the spatial mosaic distribution pattern of S. krylovii and L. chinensis while having no effect on the spatial clumped distribution of L. chinensis. It also found that the spatial distributions of dominant species are primarily affected by structural factors, and random factors such as long-term grazing led to a transition of S. krylovii from a concentrated distribution to a small patchy random pattern should not be overlooked. Our findings suggest that long-term grazing alters the spatial distribution pattern of dominant species and that adaptive strategies may be the key for maintaining the dominant role of structural factors.

Natural variation in LONELY GUY-Like 1 regulates rice grain weight under warmer night conditions

Global nighttime temperatures are rising at twice the rate of daytime temperatures and pose a challenge for rice (Oryza sativa) production. High nighttime temperature (HNT) stress affects rice yield by reducing grain weight, size, and fertility. Although the genes associated with these yield parameters have been identified and characterized under normal temperatures, the genetic basis of grain weight regulation under HNT stress remains less explored. We examined the natural variation for rice single grain weight (SGW) under HNT stress imposed during grain development. A genome-wide association analysis identified several loci associated with grain weight under HNT stress. A locus, SGW1, specific to HNT conditions resolved to LONELY GUY-Like 1 (LOGL1), which encodes a putative cytokinin-activation enzyme. We demonstrated that LOGL1 contributes to allelic variation at SGW1. Accessions with lower LOGL1 transcript abundance had higher grain weight under HNT. This was supported by the higher grain weight of logl1-mutants relative to the wild type under HNT. Compared to logl1-mutants, LOGL1 over-expressers showed increased sensitivity to HNT. We showed that LOGL1 regulates the thiamin biosynthesis pathway, which is under circadian regulation, which in turn is likely perturbed by HNT stress. These findings provide a genetic source to enhance rice adaptation to warming night temperatures and improve our mechanistic understanding of HNT stress tolerance pathways.

Vegetation growth responses to climate change: A cross-scale analysis of biological memory and time lags using tree ring and satellite data

Vegetation growth is affected by past growth rates and climate variability. However, the impacts of vegetation growth carryover (VGC; biotic) and lagged climatic effects (LCE; abiotic) on tree stem radial growth may be decoupled from photosynthetic capacity, as higher photosynthesis does not always translate into greater growth. To assess the interaction of tree-species level VGC and LCE with ecosystem-scale photosynthetic processes, we utilized tree-ring width (TRW) data for three tree species: Castanopsis eyrei (CE), Castanea henryi (CH, Chinese chinquapin), and Liquidambar formosana (LF, Chinese sweet gum), along with satellite-based data on canopy greenness (EVI, enhanced vegetation index), leaf area index (LAI), and gross primary productivity (GPP). We used vector autoregressive models, impulse response functions, and forecast error variance decomposition to analyze the duration, intensity, and drivers of VGC and of LCE response to precipitation, temperature, and sunshine duration. The results showed that at the tree-species level, VGC in TRW was strongest in the first year, with an average 77% reduction in response intensity by the fourth year. VGC and LCE exhibited species-specific patterns; compared to CE and CH (diffuse-porous species), LF (ring-porous species) exhibited stronger VGC but weaker LCE. For photosynthetic capacity at the ecosystem scale (EVI, LAI, and GPP), VGC and LCE occurred within 96 days. Our study demonstrates that VGC effects play a dominant role in vegetation function and productivity, and that vegetation responses to previous growth states are decoupled from climatic variability. Additionally, we discovered the possibility for tree-ring growth to be decoupled from canopy condition. Investigating VGC and LCE of multiple indicators of vegetation growth at multiple scales has the potential to improve the accuracy of terrestrial global change models.

Automated generation of consistent annual maximum NDVI on coal bases with a new algorithm

Coal is one of the most important fossil energy sources and is ensuring global energy security. Annual maximum NDVI (Normalized Difference Vegetation Index) data is an important indicator for the research in balancing coal mining and vegetation conservation. However, the existing annual maximum NDVI data displayed lower values with temporally inconsistent and a noticeable mosaic line. Here we propose an algorithm for automatically generating the annual maximum NDVI of China's coal bases in Google Earth Engine called: Auto-NDVIcb. The accuracy of the Auto-NDVIcb algorithm has been verified with an average RMSE of 0.087 for the 14 coal bases from 2013 to 2022. Based on the proposed Auto-NDVIcb algorithm, an annual maximum NDVI dataset for all 14 coal bases in China from 2013 to 2022 was publicly released. This dataset can be fast and automatically updated online. Hence, the public dataset will continuously serve to monitor the vegetation change induced by coal mining, exploring the mechanism of vegetation degradation, and providing scientific data for developing vegetation protection policies in coal mines.

Spatial and temporal variation of net primary productivity of herbaceous marshes and its climatic drivers in China

Herbaceous marshes are widely distributed in China and are vital to regional ecological security and sustainable development. Vegetation net primary productivity (NPP) is a vital indicator of vegetation growth. Climatic change can significantly affect NPP, but variations in NPP of herbaceous marsh and their responses to climate change in China remain unclear. Using meteorological data and MODIS NPP data during 2000-2020, this study analyzed the spatial and temporal variations of NPP and their responses to climate change in Chinese herbaceous marshes. We found that the annual NPP of herbaceous marshes in China increased significantly at a rate of 3.34 g C/m2/a from 2000 to 2020, with an average value of 336.60 g C/m2. The increased annual total precipitation enhanced the national average NPP, whereas annual mean temperature had no significant effect on the national average NPP. Regionally, precipitation had a significant positive effect on the NPP in temperate semi-arid and arid and temperate semi-humid and humid marsh regions. For the first time, we discovered asymmetry effects of daytime and nighttime temperatures on NPP in herbaceous marshes of China. In temperate humid and semi-humid marsh regions, increased summer daytime temperature decreased the NPP while increased summer nighttime temperature increased the NPP. In the Tibetan Plateau, increased autumn daytime temperature, as well as summer daytime and nighttime temperatures could increase the NPP of herbaceous marshes. This study highlights the different influences of seasonal climate change on the NPP of herbaceous marshes in China and indicates that the differential effects of daytime and nighttime temperatures should be considering in simulating the NPP of herbaceous marshes in terrestrial ecosystem models, especially under the background of global asymmetric diurnal warming.

Ecological responses of squamate reptiles to nocturnal warming

Nocturnal temperatures are increasing at a pace exceeding diurnal temperatures in most parts of the world. The role of warmer nocturnal temperatures in animal ecology has received scant attention and most studies focus on diurnal or daily descriptors of thermal environments' temporal trends. Yet, available evidence from plant and insect studies suggests that organisms can exhibit contrasting physiological responses to diurnal and nocturnal warming. Limiting studies to diurnal trends can thus result in incomplete and misleading interpretations of the ability of species to cope with global warming. Although they are expected to be impacted by warmer nocturnal temperatures, insufficient data are available regarding the night-time ecology of vertebrate ectotherms. Here, we illustrate the complex effects of nocturnal warming on squamate reptiles, a keystone group of vertebrate ectotherms. Our review includes discussion of diurnal and nocturnal ectotherms, but we mainly focus on diurnal species for which nocturnal warming affects a period dedicated to physiological recovery, and thus may perturb activity patterns and energy balance. We first summarise the physical consequences of nocturnal warming on habitats used by squamate reptiles. Second, we describe how such changes can alter the energy balance of diurnal species. We illustrate this with empirical data from the asp viper (Vipera aspis) and common wall lizard (Podarcis muralis), two diurnal species found throughout western Europe. Third, we make use of a mechanistic approach based on an energy-balance model to draw general conclusions about the effects of nocturnal temperatures. Fourth, we examine how warmer nights may affect squamates over their lifetime, with potential consequences on individual fitness and population dynamics. We review quantitative evidence for such lifetime effects using recent data derived from a range of studies on the European common lizard (Zootoca vivipara). Finally, we consider the broader eco-evolutionary ramifications of nocturnal warming and highlight several research questions that require future attention. Our work emphasises the importance of considering the joint influence of diurnal and nocturnal warming on the responses of vertebrate ectotherms to climate warming.

Interannual Variations in Terrestrial Net Ecosystem Productivity and Climate Attribution in the Southern Hilly Region of China

The vegetation ecosystem in the southern hilly region of China (SHRC) plays a crucial role in the country's carbon reservoir. Clarifying the dynamics of net primary productivity (NPP) in this area and its response to climate factors in the context of climate change is important for national forest ecology, management, and carbon neutrality efforts. This study, based on remote sensing and meteorological data spanning the period 2001 to 2021, aims to unveil the spatiotemporal patterns of vegetation productivity and climate factors in the southern hilly region, explore interannual variation characteristics of vegetation productivity with altitude, and investigate the response characteristics of NPP to various climate factors. The results indicate that from 2001 to 2021, the annual average NPP in the southern hilly region had a significant increasing trend of 2.13 ± 0.78 g m-2 a-1. The trend of NPP varies significantly with altitude. Despite a general substantial upward trend in vegetation NPP, regions at lower elevations exhibit a faster rate of increase, suggesting a diminishing difference in the NPP of different elevation ranges. The overall rise in average temperature has positive implications for the southern hilly region, while the impact of precipitation on vegetation NPP demonstrates noticeable spatial heterogeneity. Regions in which vegetation NPP is significantly negatively correlated with precipitation are mainly concentrated in the southern areas of Guangdong, Fujian, and Jiangxi provinces. In contrast, other regions further away from the southeastern coast tend to exhibit a positive correlation. Over the past two decades, there has been an asymmetry in the diurnal temperature variation in the SHRC, with the nighttime warming rate being 1.8 times that of the daytime warming rate. The positive impact of daytime warming on NPP of vegetation is more pronounced than the impact of nighttime temperature changes. Understanding the spatiotemporal patterns of NPP in the SHRC and the characteristics of its response to climate factors contributes to enhancing our ability to protect and manage vegetation resources amidst the challenges of global climate change.

Impacts of climate change on fractional vegetation coverage of temperate grasslands in China from 1982 to 2015

The vegetation coverage of temperate grasslands in China has changed substantially due to climate change during the past decades, which significantly affects the function of grassland ecosystems. To appropriately carry out adaptive management and protect temperate grassland vegetation, it is important to understand the variations in fractional vegetation coverage (FVC) of China's temperate grasslands and how they are responding to climate change. Using the GIMMS NDVI and climatic datasets, this study explored the dynamics of FVC and their climatic drivers across the temperate grassland region of China during 1982∼2015. The results showed that the growing season mean FVC increased by 0.12% per year during 1982∼2015. The increases in precipitation and minimum temperature in the growing-season (especially in spring) could enhance the FVC of various vegetation types. In summer, the FVC of temperate steppe and desert steppe could drastically increase with increasing precipitation. In addition, this study found that the impacts of daytime and night-time warming on the FVC of temperate grasslands were asymmetric. Daytime warming can moderately increase FVC of temperate grasslands, while night-time warming could significantly increase it. Furthermore, the increase in summer daytime and night-time temperatures leads to a weak decrease and a moderate increase in FVC, respectively. This asymmetric effect was more evident for the temperate steppe and desert steppe in the central area. In autumn, the temperatures increase had significant positive impacts on the FVC of temperate meadows and steppes. This study highlights the differences in the impacts of climate change at different time scales on the FVC of grasslands with various vegetation types, and indicates that the asymmetric influences of daytime and night-time temperatures in different seasons on FVC must be included in calculating the vegetation coverage of China's temperate grasslands. The results could provide information for maintaining grassland ecosystem functions and managing environmental systems.

Regulation of biophysical drivers on carbon and water fluxes over a warm-temperate plantation in northern China

Plantations have great potential for carbon sequestration and play a vital role in the water cycle. However, it is challenging to accurately estimate the carbon and water fluxes of plantations, and the impact of biophysical drivers on the coupling of carbon and water fluxes is not well understood. Thus, we modified the phenology module of the Biome-BGC model and optimized the parameters with the aim of simulating the gross primary productivity (GPP), evapotranspiration (ET) and water use efficiency (WUE) of a warm-temperate plantation in northern China from 2009 to 2020. Photosynthetically active radiation (PAR) showed significant positive correlations on GPP and WUE during the first stage of the growing season (S1: from early April to late July). Active accumulated temperature (Taa) mainly controlled the changes in GPP and ET during the second stage (S2: between the end of July and early November). Throughout the growing season, soil water content dominated daily GPP and WUE, whereas Taa regulated ET. The optimized Biome-BGC model performed better than the original model in simulating GPP and ET. Compared with the values simulated by the original model, root mean square error decreased by 7.89 % and 15.97 % for the simulated GPP and ET, respectively, while the determination coefficient increased from 0.77 to 0.81 for simulated GPP and from 0.51 to 0.62 for simulated ET. The results of this study demonstrated that the optimized model more accurately assessed carbon sequestration and water consumption in plantations.

Declining coupling between vegetation and drought over the past three decades

Droughts have been implicated as the main driver behind recent vegetation die-off and are projected to drive greater mortality under future climate change. Understanding the coupling relationship between vegetation and drought has been of great global interest. Currently, the coupling relationship between vegetation and drought is mainly evaluated by correlation coefficients or regression slopes. However, the optimal drought timescale of vegetation response to drought, as a key indicator reflecting vegetation sensitivity to drought, has largely been ignored. Here, we apply the optimal drought timescale identification method to examine the change in coupling between vegetation and drought over the past three decades (1982-2015) with long-term satellite-derived Normalized Difference Vegetation Index and Standardized Precipitation-Evapotranspiration Index data. We find substantial increasing response of vegetation to drought timescales globally, and the correlation coefficient between vegetation and drought under optimal drought timescale overall declines between 1982 and 2015. This decrease in vegetation-drought coupling is mainly observed in regions with water deficit, although its initial correlation is relatively high. However, vegetation in water-surplus regions, with low coupling in earlier stages, is prone to show an increasing trend. The observed changes may be driven by the increasing trend of atmospheric CO2 . Our findings highlight more pressing drought risk in water-surplus regions than in water-deficit regions, which advances our understanding of the long-term vegetation-drought relationship and provides essential insights for mapping future vegetation sensitivity to drought under changing climate conditions.

Critical role of water conditions in the responses of autumn phenology of marsh wetlands to climate change on the Tibetan Plateau

The Tibetan Plateau, housing 20% of China's wetlands, plays a vital role in the regional carbon cycle. Examining the phenological dynamics of wetland vegetation in response to climate change is crucial for understanding its impact on the ecosystem. Despite this importance, the specific effects of climate change on wetland vegetation phenology in this region remain uncertain. In this study, we investigated the influence of climate change on the end of the growing season (EOS) of marsh wetland vegetation across the Tibetan Plateau, utilizing satellite-derived Normalized Difference Vegetation Index (NDVI) data and observational climate data. We observed that the regionally averaged EOS of marsh vegetation across the Tibetan Plateau was significantly (p < .05) delayed by 4.10 days/decade from 2001 to 2020. Warming preseason temperatures were found to be the primary driver behind the delay in the EOS of marsh vegetation, whereas preseason cumulative precipitation showed no significant impact. Interestingly, the responses of EOS to climate change varied spatially across the plateau, indicating a regulatory role for hydrological conditions in marsh phenology. In the humid and cold central regions, preseason daytime warming significantly delayed the EOS. However, areas with lower soil moisture exhibited a weaker or reversed delay effect, suggesting complex interplays between temperature, soil moisture, and EOS. Notably, in the arid southwestern regions of the plateau, increased preseason rainfall directly delayed the EOS, while higher daytime temperatures advanced it. Our results emphasize the critical role of hydrological conditions, specifically soil moisture, in shaping marsh EOS responses in different regions. Our findings underscore the need to incorporate hydrological factors into terrestrial ecosystem models, particularly in cold and dry regions, for accurate predictions of marsh vegetation phenological responses to climate change. This understanding is vital for informed conservation and management strategies in the face of current and future climate challenges.

Ecosystem functioning across the diel cycle in the Anthropocene

Given the marked differences in environmental conditions and active biota between daytime and nighttime, it is almost inevitable that ecosystem functioning will also differ. However, understanding of these differences has been hampered due to the challenges of conducting research at night. At the same time, many anthropogenic pressures are most forcefully exerted or have greatest effect during either daytime (e.g., high temperatures, disturbance) or nighttime (e.g., artificial lighting, nights warming faster than days). Here, we explore current understanding of diel (daily) variation in five key ecosystem functions and when during the diel cycle they primarily occur [predation (unclear), herbivory (nighttime), pollination (daytime), seed dispersal (unclear), carbon assimilation (daytime)] and how diel asymmetry in anthropogenic pressures impacts these functions.

Decoupling the response of vegetation dynamics to asymmetric warming over the Qinghai-Tibet plateau from 2001 to 2020

Global land surface air temperature data show that in the past 50 years, the rate of nighttime warming has been much faster than that of daytime, with the minimum daily temperature (Tmin) increasing about 40% faster than the maximum daily temperature (Tmax), resulting in a decreased diurnal temperature difference. The Qinghai-Tibet Plateau (QTP) is known as the "roof of the world", where temperatures have risen twice as fast as the global average warming rate in the last few decades. The factors affecting vegetation growth on the QTP are complex and still not fully understood to some extent. Previous studies paid less attention to the explanations of the complicated interactions and pathways between elements that influence vegetation growth, such as climate (especially asymmetric warming) and topography. In this study, we characterized the spatial and temporal trends of vegetation coverage and investigated the response of vegetation dynamics to asymmetric warming and topography in the QTP during 2001-2020 using trend analysis, partial correlation analysis, and partial least squares structural equation model (PLS-SEM) analysis. We found that from 2001 to 2020, the entire QTP demonstrated a greening trend in the growing season (April to October) at a rate of 0.0006/a (p < 0.05). The spatial distribution pattern of partial correlation between NDVI and Tmax differed from that of NDVI and Tmin. PLS-SEM results indicated that asymmetric warming (both Tmax and Tmin) had a consistent effect on vegetation development by directly promoting greening in the QTP, with NDVI values being more sensitive to Tmin, while topographic factors, especially elevation, mainly played an indirect role in influencing vegetation growth by affecting climate change. This study offers new insights into how vegetation responds to asymmetric warming and references for local ecological preservation.

Reversed asymmetric warming of sub-diurnal temperature over land during recent decades

In the latter half of the twentieth century, a significant climate phenomenon "diurnal asymmetric warming" emerged, wherein global land surface temperatures increased more rapidly during the night than during the day. However, recent episodes of global brightening and regional droughts and heatwaves have brought notable alterations to this asymmetric warming trend. Here, we re-evaluate sub-diurnal temperature patterns, revealing a substantial increase in the warming rates of daily maximum temperatures (Tmax), while daily minimum temperatures have remained relatively stable. This shift has resulted in a reversal of the diurnal warming trend, expanding the diurnal temperature range over recent decades. The intensified Tmax warming is attributed to a widespread reduction in cloud cover, which has led to increased solar irradiance at the surface. Our findings underscore the urgent need for enhanced scrutiny of recent temperature trends and their implications for the wider earth system.

Heterogeneous responses of wetland vegetation to climate change in the Amur River basin characterized by normalized difference vegetation index from 1982 to 2020

Climate change affects wetland vegetation dramatically in mid- and high- latitudes, especially in the Amur River basin (ARB), straddling three countries and distributing abundance wetlands. In this study, spatiotemporal changes in average normalized difference vegetation index (NDVI) of wetland during the annual growing season were examined in the ARB from 1982 to 2020, and the responses of wetland vegetation to climatic change (temperature and precipitation) in different countries, geographic gradients, and time periods were analyzed by correlation analysis. The NDVI of wetland in the ARB increased significantly (p < 0.01) at the rate of 0.023 per decade from 1982 to 2020, and the NDVI on the Russian side (0.03 per decade) increased faster than that on the Chinese side (0.02 per decade). The NDVI of wetland was significantly positively correlated with daily mean temperature (p < 0.05, r = 0.701) and negatively correlated with precipitation, although the correlation was not significant (p > 0.05, r = -0.12). However, the asymmetric effects of diurnal warming on wetland vegetation were weak in the ARB. Correlations between the NDVI of wetland and climatic factors were zonal in latitudinal and longitudinal directions, and 49°N and 130°E were the points for a shift between increasing and decreasing correlation coefficients, closely related to the climatic zone. Under climate warming scenarios, the NDVI of wetland is predicted to continue to increase until 2080. The findings of this study are expected to deepen the understanding on response of wetland ecosystem to global change and promote regional wetland ecological protection.

Fading regulation of diurnal temperature ranges on drought-induced growth loss for drought-tolerant tree species

Warming-induced droughts caused tree growth loss across the globe, leading to substantial carbon loss to the atmosphere. Drought-induced growth loss, however, can be regulated by changes in diurnal temperature ranges. Here, we investigated long term radial growth responses of 23 widespread distributed tree species from 2327 sites over the world and found that species' drought tolerances were significantly and positively correlated with diurnal temperature range-growth loss relationships for the period 1901-1940. Since 1940, this relationship has continued to fade, likely due to asymmetric day and night warming trends and the species' ability to deal with them. The alleviation of reduced diurnal temperature ranges on drought-induced growth loss was mainly found for drought resistant tree species. Overall, our results highlight the need to carefully consider diurnal temperature ranges and species-specific responses to daytime and nighttime warming to explore tree growth responses to current and future warmer and drier climates.

Vegetation-induced asymmetric diurnal land surface temperatures changes across global climate zones

Unprecedented global vegetation greening during past decades is well known to affect annual and seasonal land surface temperatures (LST). However, the impact of observed vegetation cover change on diurnal LST across global climatic zones is not well understood. Using global climatic time-series datasets, we investigated the long-term growing season daytime and nighttime LST changes globally and explored associated dominant contributors including vegetation and climate factors including air temperature, precipitation, and solar radiation. Results revealed asymmetric growing season mean daytime and nighttime LST warming (0.16 °C/10a and 0.30 °C/10a, respectively) globally from 2003 to 2020, as a result, the diurnal LST range (DLSTR) declined at 0.14 °C/10a. The sensitivity analysis indicated the LST response to changes in LAI, precipitation, and SSRD mainly concentrated during daytime instead of nighttime, however, which showed comparable sensitivities for air temperature. Combining the sensitivities results and the observed LAI and climate trends, we found rising air temperature contributes to 0.24 ± 0.11 °C/10a global daytime LST warming and 0.16 ± 0.07 °C/10a nighttime LST warming, turns to be the dominant contributor to the LST changes. Increased LAI cooled global daytime LST (-0.068 ± 0.096 °C/10a) while warmed nighttime LST (0.064 ± 0.046 °C/10a); hence LAI dominates declines in DLSTR trends (-0.12 ± 0.08 °C/10a), despite some day-night process variations across climate zones. In Boreal regions, reduced DLSTR was due to nighttime warming from LAI increases. In other climatic zones, daytime cooling, and DLSTR decline, was induced by increased LAI. Biophysically, the pathway from air temperature heats the surface through sensible heat and increased downward longwave radiation during day and night, while the pathway from LAI cools the surface by enhancing energy redistribution into latent heat rather than sensible heat during the daytime. These empirical findings of diverse asymmetric responses could help calibrate and improve biophysical models of diurnal surface temperature feedback in response to vegetation cover changes in different climate zones.

Climate trends and maize production nexus in Mississippi: empirical evidence from ARDL modelling

Climate change poses a significant threat to agriculture. However, climatic trends and their impact on Mississippi (MS) maize (Zea mays L.) are unknown. The objectives were to: (i) analyze trends in climatic variables (1970 to 2020) using Mann-Kendall and Sen slope method, (ii) quantify the impact of climate change on maize yield in short and long run using the auto-regressive distributive lag (ARDL) model, and (iii) categorize the critical months for maize-climate link using Pearson's correlation matrix. The climatic variables considered were maximum temperature (Tmax), minimum temperature (Tmin), diurnal temperature range (DTR), precipitation (PT), relative humidity (RH), and carbon emissions (CO2). The pre-analysis, post-analysis, and model robustness statistical tests were verified, and all conditions were met. A significant upward trend in Tmax (0.13 °C/decade), Tmin (0.27 °C/decade), and CO2 (5.1 units/decade), and a downward trend in DTR ( - 0.15 °C/decade) were noted. The PT and RH insignificantly increased by 4.32 mm and 0.11% per decade, respectively. The ARDL model explained 76.6% of the total variations in maize yield. Notably, the maize yield had a negative correlation with Tmax for June, and July, with PT in August, and with DTR for June, July, and August, whereas a positive correlation was noted with Tmin in June, July, and August. Overall, a unit change in Tmax reduced the maize yield by 7.39% and 26.33%, and a unit change in PT reduced it by 0.65% and 2.69% in the short and long run, respectively. However, a unit change in Tmin, and CO2 emissions increased maize yield by 20.68% and 0.63% in the long run with no short run effect. Overall, it is imperative to reassess the agronomic management strategies, developing and testing cultivars adaptable to the revealed climatic trend, with ability to withstand severe weather conditions in ensuring sustainable maize production.

Heavy grazing causes plant cluster fragmentation of sparse grasses

Cleistogenes songorica, as a clustered grass, is the main grassland flora of the Stipa breviflora desert grassland. Some studies have shown that the constructive species of S. breviflora (sparse cluster type) is prone to cluster fragmentation; however, research on C. songorica is relatively rare. Then will the C. songorica plant population (dense cluster type) also have cluster fragmentation under the influence of intense grazing? To answer this question, we used variance analysis and geo-statistical methods. The spatial distribution of C. songorica in S. breviflora desert steppe in Inner Mongolia was measured under four grazing intensities (no grazing, CK, 0 sheep·ha-1·half year-1; light grazing, LG, 0.93 sheep·ha-1·half year-1; moderate grazing, MG, 1.82 sheep·ha-1·half year-1; and heavy grazing, HG, 2.71 sheep·ha-1·half year-1) and four scales (10 cm × 10 cm, 20 cm × 20 cm, 25 cm × 25 cm, 50 cm × 50 cm). We then analyzed C. songorica whether fragmentation was present. The results showed that increased grazing intensity is associated with increased density and decreased height, coverage, and standing crop of C. songorica. The spatial distribution of C. songorica was affected by structural factors, and spatial heterogeneity decreased with increased spatial scale. With increased grazing intensity and spatial scale, the patch area of C. songorica gradually increased and tended toward band distribution. In summary, increased grazing intensity and spatial scale led to weakened heterogeneity of C. songorica spatial distribution and increased consistency.

Disentangling the effects of vapor pressure deficit on northern terrestrial vegetation productivity

The impact of atmospheric vapor pressure deficit (VPD) on plant photosynthesis has long been acknowledged, but large interactions with air temperature (T) and soil moisture (SM) still hinder a complete understanding of the influence of VPD on vegetation production across various climate zones. Here, we found a diverging response of productivity to VPD in the Northern Hemisphere by excluding interactive effects of VPD with T and SM. The interactions between VPD and T/SM not only offset the potential positive impact of warming on vegetation productivity but also amplifies the negative effect of soil drying. Notably, for high-latitude ecosystems, there occurs a pronounced shift in vegetation productivity's response to VPD during the growing season when VPD surpasses a threshold of 3.5 to 4.0 hectopascals. These results yield previously unknown insights into the role of VPD in terrestrial ecosystems and enhance our comprehension of the terrestrial carbon cycle's response to global warming.

Wetland vegetation cover changes and its response to climate changes across Heilongjiang-Amur River Basin

The Heilongjiang-Amur River Basin is one of the largest and most complex aquatic systems in Asia, comprising diverse wetland resources. The wetland vegetation in mid-high latitude areas has high natural value and is sensitive to climate changes. In this study, we investigated the wetland vegetation cover changes and associated responses to climate change in the Heilongjiang-Amur River Basin from 2000 to 2018 based on the growing season (May to September) climate and LAI data. Our results indicated that the wetland LAI increased at 0.014 m2·m-2/yr across Heilongjiang-Amur River Basin with the regional climate showed wetting and warming trends. On a regional scale, wetland vegetation in China and Russia had positive partial correlation with solar radiation and minimum air temperature, with precipitation showing a slight lag effect. In contrast, wetland vegetation in Mongolia had positive partial correlation with precipitation. These correlations were further investigated at different climate intervals. We found the precipitation is positively correlated with LAI in the warm regions while is negatively correlated with LAI in the wet regions, indicating an increase in precipitation is beneficial for the growth of wetland vegetation in heat sufficient areas, and when precipitation exceeds a certain threshold, it will hinder the growth of wetland vegetation. In the cold regions, we found solar radiation and minimum air temperature are positively correlated with LAI, suggesting SR and minimum air temperature instead of mean air temperature and maximum air temperature play more important roles in affecting the wetland vegetation growth in the heat limited areas. The LAI was found to be negatively correlated with maximum air temperature in the arid areas, indicating excessive temperature would inhibit the wetland vegetation growth when the water is limited. Our investigation can provide a scientific foundation for the trilateral region in wetland ecosystem protection and is beneficial for a more comprehensive understanding of the responses of wetlands in the middle and high latitudes to climate change.

The Seasonal Divergence in the Weakening Relationship between Interannual Temperature Changes and Northern Boreal Vegetation Activity

The response of boreal vegetation to global warming has shown a weakening trend over the last three decades. However, in previous studies, models of vegetation activity responses to temperature change have often only considered changes in the mean daily temperature (T_mean), with the diurnal temperature range (DTR) being neglected. The goal of this study was to evaluate the temporal trends of the relationships between two temperature factors (T_mean and DTR) and the vegetation activity across the boreal regions on both annual and seasonal timescales, by simultaneously employing satellite and climate datasets. We found that the interannual partial correlation between the growing season (GS) NDVI and T_mean (R_NDVI-Tmean) has shown a significant decreasing trend over the last 34 years. At the seasonal scale, the R_NDVI-Tmean showed a significant upward trend in the spring, while in the summer and autumn, the R_NDVI-Tmean exhibited a significant downward trend. The temporal trend characteristics of the partial correlation between the NDVI and DTR (R_NDVI-DTR), at both the GS and seasonal scales, were fully consistent with the R_NDVI-Tmean. The area with a significant decrease in the GS R_NDVI-Tmean and R_NDVI-DTR accounted for approximately 44.4% and 41.2% of the boreal region with the 17-year moving window, respectively. In stark contrast, the area exhibiting a significant increasing trend in the GS R_NDVI-Tmean and R_NDVI-DTR accounted for only approximately 22.3% and 25.8% of the boreal region with the 17-year moving window, respectively. With respect to the seasonal patterns of the R_NDVI-Tmean and R_NDVI-DTR, the area with a significant upward trend in the spring was greater than that with a significant downward trend. Nevertheless, more areas had a significant downward trend in the R_NDVI-Tmean and R_NDVI-DTR in summer and autumn than a significant upward trend. Overall, our research reveals a weakening trend in the impact of temperature on the vegetation activity in the boreal regions and contributes to a deeper understanding of the vegetation response to global warming.

Reassessment of growth-climate relations indicates the potential for decline across Eurasian boreal larch forests

Larch, a widely distributed tree in boreal Eurasia, is experiencing rapid warming across much of its distribution. A comprehensive assessment of growth on warming is needed to comprehend the potential impact of climate change. Most studies, relying on rigid calendar-based temperature series, have detected monotonic responses at the margins of boreal Eurasia, but not across the region. Here, we developed a method for constructing temporally flexible and physiologically relevant temperature series to reassess growth-temperature relations of larch across boreal Eurasia. Our method appears more effective in assessing the impact of warming on growth than previous methods. Our approach indicates widespread and spatially heterogeneous growth-temperature responses that are driven by local climate. Models quantifying these results project that the negative responses of growth to temperature will spread northward and upward throughout this century. If true, the risks of warming to boreal Eurasia could be more widespread than conveyed from previous works.

Asymmetric effects of daytime and nighttime warming on alpine treeline recruitment

Trees at their upper range limits are highly sensitive to climate change, and thus alpine treelines worldwide have changed their recruitment patterns in response to climate warming. However, previous studies focused only on daily mean temperature, neglecting the asymmetric influences of daytime and nighttime warming on recruitments in alpine treelines. Here, based on the compiled dataset of tree recruitment series from 172 alpine treelines across the Northern Hemisphere, we quantified and compared the different effects of daytime and nighttime warming on treeline recruitment using four indices of temperature sensitivity, and assessed the responses of treeline recruitment to warming-induced drought stress. Our analyses demonstrated that even in different environmental regions, both daytime and nighttime warming could significantly promote treeline recruitment, and however, treeline recruitment was much more sensitive to nighttime warming than to daytime warming, which could be attributable to the presence of drought stress. The increasing drought stress primarily driven by daytime warming rather than by nighttime warming would likely constrain the responses of treeline recruitment to daytime warming. Our findings provided compelling evidence that nighttime warming rather than daytime warming could play a primary role in promoting the recruitment in alpine treelines, which was related to the daytime warming-induced drought stress. Thus, daytime and nighttime warming should be considered separately to improve future projections of global change impacts across alpine ecosystems.

Long-Term Daytime Warming Rather Than Nighttime Warming Alters Soil Microbial Composition in a Semi-Arid Grassland

Climate warming has profoundly influenced community structure and ecosystem functions in the terrestrial biosphere. However, how asymmetric rising temperatures between daytime and nighttime affect soil microbial communities that predominantly regulate soil carbon (C) release remains unclear. As part of a decade-long warming manipulation experiment in a semi-arid grassland, we aimed to examine the effects of short- and long-term asymmetrically diurnal warming on soil microbial composition. Neither daytime nor nighttime warming affected soil microbial composition in the short term, whereas long-term daytime warming instead of nighttime warming decreased fungal abundance by 6.28% (p < 0.05) and the ratio of fungi to bacteria by 6.76% (p < 0.01), which could be caused by the elevated soil temperature, reduced soil moisture, and increased grass cover. In addition, soil respiration enhanced with the decreasing fungi-to-bacteria ratio, but was not correlated with microbial biomass C during the 10 years, indicating that microbial composition may be more important than biomass in modulating soil respiration. These observations highlight the crucial role of soil microbial composition in regulating grassland C release under long-term climate warming, which facilitates an accurate assessment of climate-C feedback in the terrestrial biosphere.

Global analysis of the correlation and propagation among meteorological, agricultural, surface water, and groundwater droughts

Groundwater drought monitoring relies on ground observation data, which cannot be used to reflect large-scale droughts in groundwater resources. The Gravity Recovery and Climate Experiment Satellite (GRACE) improved the situation and provided a new solution for groundwater drought research. However, the propagation relationship among global different drought types has not been fully explored. We employed CRU precipitation data, MERR2 reanalysis soil moisture data, GLDAS and GRACE data to calculate SPI (Standardized precipitation index), SSI (Standardized soil moisture index), SRI (Standardized runoff index), and GDI (Groundwater drought index), characterizing meteorological, agricultural, surface water and groundwater droughts, respectively. The Pearson correlation coefficient was adopted to study the propagation time of these four types of droughts. The results showed that the average propagation times for the different drought types are meteorological drought to surface water drought (3.5 months), meteorological drought to agricultural drought (5.7 months), agricultural drought to groundwater drought (12.97 months), surface water drought to groundwater drought (13.78 months), and meteorological drought to groundwater drought (14.47 months) from longest to shortest. (2) Climate conditions had a significant impact on the propagation time of different drought types. Low temperatures in cold climates resulted in the longest drought propagation time, while dry summer climates in temperate climates reduced drought propagation time. There were weaker propagation relationships in arid climates. In tropical climates, precipitation may not be the main driving factor for drought propagation. (3) Different land cover types show significant differences in the propagation of groundwater droughts, with forests having a longer propagation time from meteorological drought to agricultural drought or surface water drought than grassland and cropland, and forests having the shortest propagation time when meteorological drought, agricultural drought, and surface water drought is propagated to groundwater drought. Woody plants have deeper root systems than herbaceous plants and can draw up deeper groundwater. Forests have greater water storage capacity and weaker groundwater recharge than grasslands and croplands, resulting in forests being more resistant to agricultural and surface water droughts and less resistant to groundwater droughts during meteorological droughts. This study can help to clarify the propagation laws among different drought types and understand the internal mechanisms that affect the development of drought during the water cycle.

Evapotranspiration responses to CO2 and its driving mechanisms in four ecosystems based on CMIP6 simulations: Forest, shrub, farm and grass

Evapotranspiration (ET) is an essential process of the water cycle through which water is transferred from terrestrial ecosystems to atmosphere. However, in the climate context of increasing CO₂ concentration (also called as a CO₂-enriched climate), the variation of ET and its main drivers among different ecosystems remain unclear. This study analyzed the output data of the CMCC ESM2 model with a ridge regression method, and proposed the trends and drivers of ET in different ecosystems in a CO₂-enriched climate. In particular, the temporal - spatial characteristics of ET and its primary drivers for different periods and wetness levels were revealed. With the rising of CO₂ concentration, the atmospheric evapotranspiration demand increases, and the vegetation grows more luxuriantly. ET shows an overall upward trend, especially in the shrub ecosystems (7.41 mm decade^-1). Our results show that the thermal conditions are the main driving factors for humid forest and shrub ecosystems whereas relative humidity (RH) is the main driving factor for arid farm and grass ecosystems. In terms of the average contribution in all periods, surface solar radiation contributes 26% and 41% to ET variation in forest and shrub ecosystems, and RH contributes 49% and 32% to ET variation in farm and grass ecosystems, respectively. Notably, with the increase of wetness levels, the contribution of water conditions on ET becomes smaller, while that of thermal conditions becomes larger. Correlation analysis shows that LAI impacts on ET are regulated by environmental factors, which reflects the complexity of ET change mechanism. Overall, these findings further provide a reference for rational planning of ecosystems and efficient utilization of water resources.

Impacts of vegetation restoration on water resources and carbon sequestration in the mountainous area of Haihe River basin, China

The mountainous region of the Haihe River basin (MHRB) plays an important role in the water resource supply of its nearby mega-cities, including Beijing and Tianjin, and large areas of cropland. With the implementation of afforestation projects in recent decades, vegetation and carbon (C) uptake have greatly increased in the MHRB. In addition, the annual runoff has significantly declined, threatening regional water security. The trade-off relationship between water yield and C uptake in the MHRB remains unknown. This study employed a biogeochemical model (Biome-BGC) to simulate the natural vegetation dynamics and gross primary productivity (GPP) during 1982-2019 driven by climate forcing. A distributed hydrological model (geomorphology-based hydrological model, GBHM) was adopted to assess the impact of vegetation restoration on the hydrological processes. The results indicated that the leaf area index in the MHRB increased significantly (P < 0.01) during 1982-2019, which led to evapotranspiration increase and runoff (R) reduction. Under the influence of vegetation restoration, both the GPP and the water use efficiency (WUE) increased significantly in the MHRB during 2000-2019, however, the improvement of WUE decreased with the aridity index increasing. Our results showed that vegetation restoration can improve C sequestration efficiency in the MHRB and that the trade-off between water yield and C sequestration should be considered in planning ecological projects to achieve C neutrality.

Anthropogenic changes to the nighttime environment

How the relative impacts of anthropogenic pressures on the natural environment vary between different taxonomic groups, habitats, and geographic regions is increasingly well established. By contrast, the times of day at which those pressures are most forcefully exerted or have greatest influence are not well understood. The impact on the nighttime environment bears particular scrutiny, given that for practical reasons (e.g., researchers themselves belong to a diurnal species), most studies on the impacts of anthropogenic pressures are conducted during the daytime on organisms that are predominantly day active or in ways that do not differentiate between daytime and nighttime. In the present article, we synthesize the current state of knowledge of impacts of anthropogenic pressures on the nighttime environment, highlighting key findings and examples. The evidence available suggests that the nighttime environment is under intense stress across increasing areas of the world, especially from nighttime pollution, climate change, and overexploitation of resources.

Contrasting responses of peak vegetation growth to asymmetric warming: Evidences from FLUXNET and satellite observations

The peak growth of plant in summer is an important indicator of the capacity of terrestrial ecosystem productivity, and ongoing studies have shown its responses to climate warming as represented in the mean temperature. However, the impacts from the asymmetrical warming, that is, different rates in the changes of daytime (T_max ) and nighttime (T_min ) warming were mostly ignored. Using 60 flux sites (674 site-year in total) measurements and satellite observations from two independent satellite platforms (Global Inventory Monitoring and Modeling Studies [1982-2015]; MODIS [2000-2020]) over the Northern Hemisphere (≥30°N), here we show that the peak growth, as represented by both flux-based maximum primary productivity and the maximum greenness indices (maximum normalized difference vegetation index and enhanced vegetation index), responded oppositely to daytime and nighttime warming. T max - T min + (peak growth showed negative responses to T_max , but positive responses to T_min ) dominated in most ecosystems and climate types, especially in water-limited ecosystems, while T max + T min - (peak growth showed positive responses to T_max , but negative responses to T_min ) was primarily observed in high latitude regions. These contrasting responses could be explained by the strong association between asymmetric warming and water conditions, including soil moisture, evapotranspiration/potential evapotranspiration, and the vapor pressure deficit. Our results are therefore important to the understanding of the responses of peak growth to climate change, and consequently a better representation of asymmetrical warming in future ecosystem models by differentiating the contributions between daytime and nighttime warming.

Spatial and temporal variations of grassland vegetation on the Mongolian Plateau and its response to climate change

The Mongolian Plateau is an arid and semi-arid region with grassland as its main vegetation. It has a fragile ecosystem and is a sensitive area for global warming. The study is based on MODIS NDVI data and growth season meteorological data from 2000 to 2018, this study examined the spatial and temporal variation characteristics of grassland vegetation on the Mongolian Plateau during the growing season using trend analysis, partial correlation analysis, and residual analysis, and it explores the dual response of NDVI changes to climate and human activities. The study’s findings demonstrated that the growing season average NDVI of grassland vegetation on the plateau gradually increased from southwest to northeast during the growing season; the growing season average NDVI demonstrated a significant overall increase of 0.023/10a (p &lt; 0.05) from 2000 to 2018, with an increase rate of 0.030/10a in Inner Mongolia and 0.019/10a in Mongolia; the area showing a significant increase in NDVI during the growing season accounted for 91.36% of the entire study area. In Mongolian Plateau grasslands during the growing season of 2000–2018, precipitation and downward surface shortwave radiation grew significantly at rates of 34.83mm/10a and 0.57 W/m2/10a, respectively, while average air temperature decreased slightly at a rate of −0.018°C/10a. Changes in meteorological factors of grassland vegetation varied by region as well, with Inner Mongolia seeing higher rates of precipitation, lower rates of average air temperature, and lower rates of downward surface shortwave radiation than Mongolia. On the Mongolian Plateau, the NDVI of grassland vegetation in the growing season showed a significant positive correlation with precipitation (0.31) and a significant negative correlation with average air temperature (−0.09) and downward surface shortwave radiation (−0.19), indicating that increased in NDVI was driven by an increase in precipitation paired with a decrease in air temperature and a decrease in surface shortwave radiation. The overall increase in NDVI caused by human activity in the grasslands of the Mongolian Plateau was primarily positive, with around 18.37% of the region being beneficial. Climate change and human activity both affect NDVI variations in Mongolian Plateau grasslands, which are spatially heterogeneous. Moderate ecological engineering and agricultural production activities are crucial for vegetation recovery. This work is crucial to further understanding surface–atmosphere interactions in arid and semi-arid regions in the context of global climate change.

Short-term warming and N deposition alter the photosynthetic pigments trade-off in leaves of Leymus secalinus growing in different alpine grassland habitats on Qinghai-Tibetan plateau

Warming and N (nitrogen) deposition are the two main driving factors of global change. We examined the effects of increased N deposition (8 kg ha-1 year-1) and warming, as well as their combined effect on the leaf photosynthetic pigments of Leymus secalinus, which is one of the key alpine plants growing in different grassland habitats on Qinghai-Tibetan plateau. In 2014, the experiments were established in 12 plots (2×5m) of three types of habitats including alpine meadow (AM), alpine steppe (AS), and cultivated grassland (CG) with the following treatments: CK (control treatment), N (only N deposition), W (only warming), and W&N (warming combined with N deposition). Results showed that the effects of warming and N deposition on photosynthetic pigments of Leymus secalinus varied with different grassland habitat types. In three grassland types, warming led to no significant effects on the total chlorophyll content of L. secalinus, while N deposition alone only significantly enhanced total chlorophyll content in alpine meadow and cultivated grassland. N deposition combined with warming only significantly enhanced total chlorophyll content of L. secalinus in alpine steppe and cultivated grassland. Chla content plays an important role in determining the variation of total chlorophyll content. Chla/Chlb ratio of L. secalinus was more stable in alpine meadow compared with that of L. secalinus in the other two grassland types. Car/Chl ratio of L. secalinus was not prone to be affected by warming and N deposition in all grassland types. Leaf N content was obviously positively correlated with photosynthetic pigments, especially Chla content. Warming and N deposition all affected photosynthetic pigment dynamics and tended to increase Chla by enhancing its weight. Our results highlighted that both warming and N deposition as well as their combination can alter the trade-off of photosynthetic pigments through enhancing the Chla ratio in L. secalinus. In addition, growing habitats should be within consideration when studying alpine plants adaptation mechanism to global change in the future.

Saturation response of enhanced vegetation productivity attributes to intricate interactions

Evidence for the multifaceted responses of terrestrial ecosystems has been shown by the weakening of CO₂ fertilization-induced and warming-controlled productivity gains. The intricate relationship between vegetation productivity and various environmental controls still remains elusive spatially. Here several inherent preponderances make China a natural experimental setting to investigate the interaction and relative contributions of five drivers to gross primary productivity for the period from 1982 to 2018 (i.e., elevated atmospheric CO₂ concentrations, climate change, nutrient availability, anthropogenic land use change, and soil moisture) by coupling multiple long-term datasets. Despite a strikingly prominent enhancement of vegetation productivity in China, it exhibits similar saturation responses to the aforementioned environmental drivers (elevated CO₂ , climatic factors, and soil moisture). The CO₂ fertilization-dominated network explains the long-term variations in vegetation productivity in humid regions, but its effect is clearly attenuated or even absent in arid and alpine environments controlled by climate and soil moisture. Divergence in interactions also provides distinct evidence that water availability plays an essential role in limiting the potential effects of climate change and elevated CO₂ concentrations on vegetation productivity. Unprecedented industrialization and dramatic surface changes may have breached critical thresholds of terrestrial ecosystems under the diverse natural environment and thus forced a shift from a period dominated by CO₂ fertilization to a period with nonlinear interactions. These findings suggest that future benefits in terrestrial ecosystems are likely to be counteracted by uncertainties in the complicated network, implying an increasing reliance on human societies to combat potential risks. Our results therefore highlight the need to account for the intricate interactions globally and thus incorporate them into mitigation and adaptation policies.

Climate change enhanced the positive contribution of human activities to net ecosystem productivity from 1983 to 2018

Introduction

Accurate assessment of the net ecosystem productivity (NEP) is very important for understanding the global carbon balance. However, it remains unknown whether climate change (CC) promoted or weakened the impact of human activities (HA) on the NEP from 1983 to 2018.

Methods

Here, we quantified the contribution of CC and HA to the global NEP under six different scenarios based on a boosted regression tree model and sensitivity analysis over the last 40 years.

Results and discussion

The results show that (1) a total of 69% of the areas showed an upward trend in the NEP, with HA and CC controlled 36.33 and 32.79% of the NEP growth, respectively. The contribution of HA (HA_con) far exceeded that of CC by 6.4 times. (2) The CO2 concentration had the largest positive contribution (37%) to NEP and the largest influence area (32.5%). It made the most significant contribution to the NEP trend in the range of 435–440 ppm. In more than 50% of the areas, the main loss factor was solar radiation (SR) in any control area of the climate factors. (3) Interestingly, CC enhanced the positive HA_con to the NEP in 44% of the world, and in 25% of the area, the effect was greater than 50%. Our results shed light on the optimal range of each climatic factor for enhancing the NEP and emphasize the important role of CC in enhancing the positive HA_con to the NEP found in previous studies.

Uncertainty and sensitivity analysis of deep learning models for diurnal temperature range (DTR) forecasting over five Indian cities

In this article, the maximum and minimum daily temperature data for Indian cities were tested, together with the predicted diurnal temperature range (DTR) for monthly time horizons. RClimDex, a user interface for extreme computing indices, was used to advance the estimation because it allowed for statistical analysis and comparison of climatological elements such time series, means, extremes, and trends. During these 69 years, a more erratic DTR trend was seen in the research area. This study investigates the suitability of three deep neural networks for one-step-ahead DTR time series (DTRTS) forecasting, including recurrent neural network (RNN), long short-term memory (LSTM), gated recurrent unit (GRU), and auto-regressive integrated moving average exogenous (ARIMAX). To evaluate the effectiveness of models in the testing set, six statistical error indicators, including root mean square error (RMSE), mean absolute error (MAE), coefficient of correlation (R), percent bias (PBIAS), modified index of agreement (md), and relative index of agreement (rd), were chosen. The Wilson score approach was used to do a quantitative uncertainty analysis on the prediction error to forecast the outcome DTR. The findings show that the LSTM outperforms the other models in terms of its capacity to forget, remember, and update information. It is more accurate on datasets with longer sequences and displays noticeably more volatility throughout its gradient descent. The results of a sensitivity analysis on the LSTM model, which used RMSE values as an output and took into account different look-back periods, showed that the amount of history used to fit a time series forecast model had a direct impact on the model's performance. As a result, this model can be applied as a fresh, trustworthy deep learning method for DTRTS forecasting.

Contrasting temperature effects on the velocity of early- versus late-stage vegetation green-up in the Northern Hemisphere

Global vegetation greening has been widely confirmed in previous studies, yet the changes in the velocity of green-up in each month of green-up period (GUP) remains unclear. Here, we defined the velocity of vegetation green-up as V_NDVI (the monthly increase of Normalized Difference Vegetation Index [NDVI] during GUP) and further explored its response to climate change in middle-high-latitude Northern Hemisphere. We found that in early GUP, V_NDVI generally showed positive trends from 1982 to 2015, whereas in late GUP, it showed negative trends in most areas. Such contrasting trends were mainly due to a positive temperature effect on V_NDVI in early GUP, but this effect turned negative in late GUP. The increase of soil moisture also in part explained the accelerated vegetation green-up, especially in the arid and semi-arid ecosystems of inland areas. Our analyses also indicate that the first month of the GUP was the key stage impacting vegetation greenness in summer. Future warming may continuously speed up the early growth of vegetation, altering the seasonal trajectory of vegetation and its feedbacks to the Earth system.

Reduced diurnal temperature range mitigates drought impacts on larch tree growth in North China

Forests are facing climate changes such as warmer temperatures, accelerated snowmelt, increased drought, as well as changing diurnal temperature ranges (DTR) and cloud cover regimes. How tree growth is influenced by the changes in daily to monthly temperatures and its associations with droughts has been extensively investigated, however, few studies have focused on how changes in sub-daily temperatures i.e., DTR, influence tree growth during drought events. Here, we used a network of Larix principis-rupprechtii tree-ring data from 1989 to 2018, covering most of the distribution of planted larch across North China, to investigate how DTR, cloud cover and their interactions influence the relationship between drought stress and tree growth. DTR showed a negative correlation with larch growth in 95 % of sites (r_mean = -0.30, significant in 42 % of sites). Cloud cover was positively correlated with growth in 87 % of sites (r_mean = 0.13, significant in 5 % of sites). Enhanced tree growth was found at lower DTR in the absence of severe drought. Our findings highlight that in the absence of severe droughts, reduced DTR benefits tree growth, while increased cloud cover tended to benefit tree growth only during severe drought periods. Given how DTR influences drought impacts on tree growth, net tree growth was found to be larger in regions with smaller DTR.

Inter-annual variations of vegetation dynamics to climate change in Ordos, Inner Mongolia, China

To reveal the characteristics of climate change and the controlling factors for vegetation dynamics in the Ordos, Inner Mongolia, China, 34 years (1982–2015) of regional climate variables and vegetation dynamics were investigated. The results show that: Annual mean air temperature (TMP) significantly increased with a linear slope of 0.473°C/10yr. Annual precipitation (PRE) had a non-significant positive trend nearly 5 times lower than the trend of potential evapotranspiration (PET). The average Normalized Difference Vegetation Index (NDVI) computed for the region was found to show a significant positive trend (6.131×10⁻⁴/yr). However, all climate variables displayed non-significant correlations with NDVI at annual scale. The reduction of desert and the increase of grassland over the past decades were accountable for the increased NDVI. Principal components analysis revealed that the regional climate change can be characterized as changes in temperature, humidity and the availability of radiant energy. Based on principal components regression coefficients, NDVI was mostly sensitive to humidity component, followed by growing season warmth (WMI). Spatially, 93.1% of the pixels displayed positive trend and 61.8% of the pixels displayed significant change over the past decades. Both principal regression analysis and partial correlation analysis revealed that NDVI in eastern part of Ordos was sensitive to TMP, whereas, NDVI in southern and western areas of Ordos displayed the high sensitivity to combined effects of PRE and cloud coverage (CLD). Partial correlation analyses also revealed that TMX was a surrogate for aridity, TMN was a representative of humidity, and temperature variations below the threshold of 5°C (CDI) were less important than WMI. We conclude that regional climate change can be characterized by warming and increased aridity. The significant positive trend of regional NDVI and the non-significant correlations between NDVI and climate variables at annual scale suggests the hidden role of the human activities.

Responses of Forest Net Primary Productivity to Climatic Factors in China during 1982-2015

Forest ecosystems play an important role in the global carbon cycle. Clarifying the large-scale dynamics of net primary productivity (NPP) and its correlation with climatic factors is essential for national forest ecology and management. Hence, this study aimed to explore the effects of major climatic factors on the Carnegie−Ames−Stanford Approach (CASA) model-estimated NPP of the entire forest and all its corresponding vegetation types in China from 1982 to 2015. The spatiotemporal patterns of interannual variability of forest NPP were illustrated using linear regression and geographic information system (GIS) spatial analysis. The correlations between forest NPP and climatic factors were evaluated using partial correlation analysis and sliding correlation analysis. We found that over thirty years, the average annual NPP of the forests was 887 × 1012 g C/a, and the average annual NPP per unit area was 650.73 g C/m2/a. The interannual NPP of the entire forest and all its corresponding vegetation types significantly increased (p < 0.01). The increase in the NPP of evergreen broad-leaved forests was markedly substantial among forest types. From the spatial perspective, the NPP of the entire forest vegetation gradually increased from northwest to southeast. Over the years, the proportions of the entire forest and all its corresponding vegetation types with a considerable increase in NPP were higher than those with a significant decrease, indicating, generally, improvements in forest NPP. We also found climatic factors variably affected the NPP of forests over time considering that the rise in temperature and solar radiation improved the interannual forest NPP, and the decline in precipitation diminished the forest NPP. Such varying strength of the relationship between the interannual forest NPP and climatic factors also varied across many forest types. Understanding the spatiotemporal pattern of forest NPP and its varying responses to climatic change will improve our knowledge to manage forest ecosystems and maintain their sustainability under a changing environment.

Effect of Vegetation Carryover and Climate Variability on the Seasonal Growth of Vegetation in the Upper and Middle Reaches of the Yellow River Basin

Vegetation dynamics are often affected by climate variability, but the past state of vegetation has a non-negligible impact on current vegetation growth. However, seasonal differences in the effects of these drivers on vegetation growth remain unclear, particularly in ecologically fragile areas. We used the normalized difference vegetation index (NDVI), gross primary productivity (GPP), and leaf area index (LAI) to describe the vegetation dynamic in the upper and middle reaches of the Yellow River basin (YRB). Three active vegetation growing seasons (early, peak, and late) were defined based on phenological metrics. In light of three vegetation indicators and the climatic data, we identified the correlation between the inter-annual variation of vegetation growth in the three sub-seasons. Then, we quantified the contributions of climate variability and the vegetation growth carryover (VGC) effect on seasonal vegetation greening between 2000–2019. Results showed that both the vegetation coverage and productivity in the study area increased over a 20-year period. The VGC effect dominated vegetation growth during the three active growing seasons, and the effect increased from early to late growing season. Vegetation in drought regions was found to generally have a stronger vegetation carryover ability, implying that negative disturbances might have severer effects on vegetation in these areas. The concurrent seasonal precipitation was another positive driving factor of vegetation greening. However, sunshine duration, including its immediate and lagged impacts, had a negative effect on vegetation growth. In addition, the VGC effect can sustain into the second year. The VGC effect showed that initial ecological restoration and sustainable conservation would promote vegetation growth and increase vegetation productivity. This study provides a comprehensive perspective on understanding the climate–vegetation interactions on a seasonal scale, which helps to accurately predict future vegetation dynamics over time in ecologically fragile areas.

Varying Responses of Vegetation Greenness to the Diurnal Warming across the Global

The distribution of global warming has been varying both diurnally and seasonally. Little is known about the spatiotemporal variations in the relationships between vegetation greenness and day- and night-time warming during the last decades. We investigated the global inter- and intra-annual responses of vegetation greenness to the diurnal asymmetric warming during the period of 1982-2015, using the normalized different vegetation index (NDVI, a robust proxy for vegetation greenness) obtained from the NOAA/AVHRR NDVI GIMMS3g dataset and the monthly average daily maximum (T_max) and minimum temperature (T_min) obtained from the gridded Climate Research Unit, University of East Anglia. Several findings were obtained: (1) The strength of the relationship between vegetation greenness and the diurnal temperature varied on inter-annual and seasonal timescales, indicating generally weakening warming effects on the vegetation activity across the global. (2) The decline in vegetation response to T_max occurred mainly in the mid-latitudes of the world and in the high latitudes of the northern hemisphere, whereas the decline in the vegetation response to T_min primarily concentrated in low latitudes. The percentage of areas with a significantly negative trend in the partial correlation coefficient between vegetation greenness and diurnal temperature was greater than that of the areas showing the significant positive trend. (3) The trends in the correlation between vegetation greenness and diurnal warming showed a complex spatial pattern: the majority of the study areas had undergone a significant declining strength in the vegetation greenness response to T_max in all seasons and to T_min in seasons except autumn. These findings are expected to have important implications for studying the diurnal asymmetry warming and its effect on the terrestrial ecosystem.

Impact of recent climate change on corn, rice, and wheat in southeastern USA

Climate change and its impact on agriculture productivity vary among crops and regions. The southeastern United States (SE-US) is agro-ecologically diversified, economically dependent on agriculture, and mostly overlooked by agroclimatic researchers. The objective of this study was to compute the effect of climatic variables; daily maximum temperature (T_max), daily minimum temperature (T_min), and rainfall on the yield of major cereal crops i.e., corn (Zea mays L.), rice (Oryza sativa L.), and wheat (Triticum aestivum L.) in SE-US. A fixed-effect model (panel data approach) was used by applying the production function on panel data from 1980 to 2020 from 11 SE-US states. An asymmetrical warming pattern was observed, where nocturnal warming was 105.90%, 106.30%, and 32.14%, higher than the diurnal warming during corn, rice, and wheat growing seasons, respectively. Additionally, a shift in rainfall was noticed ranging from 19.2 to 37.2 mm over different growing seasons. Rainfall significantly reduced wheat yield, while, it had no effect on corn and rice yields. The T_max and T_min had no significant effect on wheat yield. A 1 °C rise in T_max significantly decreased corn (- 34%) and rice (- 8.30%) yield which was offset by a 1 °C increase in T_min increasing corn (47%) and rice (22.40%) yield. Conclusively, overall temperature change of 1 °C in the SE-US significantly improved corn yield by 13%, rice yield by 14.10%, and had no effect on wheat yield.

Assessment of climate change effects on vegetation and river hydrology in a semi-arid river basin

Climate change plays a key role in changing vegetation productivity dynamics, which ultimately affect the hydrological cycle of a watershed through evapotranspiration (ET). Trends and correlation analysis were conducted to investigate vegetation responses across the whole Upper Jhelum River Basin (UJRB) in the northeast of Pakistan using the normalized difference vegetation index (NDVI), climate variables, and river flow data at inter-annual/monthly scales between 1982 and 2015. The spatial variability in trends calculated with the Mann-Kendall (MK) trend test on NDVI and climate data was assessed considering five dominant land use/cover types. The inter-annual NDVI in four out of five vegetation types showed a consistent increase over the 34-year study period; the exception was for herbaceous vegetation (HV), which increased until the end of the 1990s and then decreased slightly in subsequent years. In spring, significant (p<0.05) increasing trends were found in the NDVI of all vegetation types. Minimum temperature (Tmin) showed a significant increase during spring, while maximum temperature (Tmax) decreased significantly during summer. Average annual increase in Tmin (1.54°C) was much higher than Tmax (0.37°C) over 34 years in the UJRB. Hence, Tmin appears to have an enhancing effect on vegetation productivity over the UJRB. A significant increase in NDVI, Tmin and Tmax during spring may have contributed to reductions in spring river flow by enhancing evapotranspiration observed in the watershed of UJRB. These findings provide valuable information to improve our knowledge and understanding about the interlinkages between vegetation, climate and river flow at a watershed scale.

Global and regional erosion of mammalian functional diversity across the diel cycle

Biodiversity is declining worldwide. When species are physically active (i.e., their diel niche) may influence their risk of becoming functionally extinct. It may also affect how species losses affect ecosystems. For 5033 terrestrial mammals, we predict future changes to diel global and local functional diversity through a gradient of progressive functional extinction scenarios of threatened species. Across scenarios, diurnal species were at greater risk of becoming functionally extinct than nocturnal, crepuscular, and cathemeral species, resulting in deep functional losses in global diurnal trait space. Redundancy (species with similar roles) will buffer global nocturnal functional diversity; however, across the land surface, losses will mostly occur among functionally dispersed species (species with distinct roles). Functional extinctions will constrict boundaries of cathemeral trait space as megaherbivores, and arboreal foragers are lost. Variation in the erosion of functional diversity across the daily cycle will likely profoundly affect the partitioning of ecosystem functioning between night and day.

Daytime warming triggers tree growth decline in the Northern Hemisphere

Global warming has been linked to declines in tree growth. However, it is unclear how the asymmetry in daytime and nighttime warming influences this response. Here, we use 2947 residual tree-ring width chronologies covering 32 species at 2493 sites, between 1901 and 2018, across the Northern Hemisphere, to analyze the effects of daytime and nighttime temperatures, precipitation, and drought stress on the radial growth of trees. We show that drought stress was primarily triggered by daytime rather than nighttime warming. The radial growth of trees was more sensitive to drought stress in warm regions than in cold regions, especially for angiosperms. Our study provides robust evidence that daytime warming is the primary driver of the observed declines in forest productivity related to drought stress and that daytime and nighttime warming should be considered separately when modelling forest-climate interactions and feedbacks in a future, warmer world.