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Climate change can significantly alter phytoplankton growth and proliferation, which would counteract restoration efforts to control algal blooms. However, the knowledge is limited about the quantitative evaluation of the causal effect of algal biomass resurgence in large shallow lakes where there is no significant improvement after long term lake restoration. Here, a bucket process-based phytoplankton dynamic model is developed to quantify the contributions of climate change and nutrients concentration changes to phytoplankton biomass resurgence after 2014 in hypereutrophic Lake Taihu, China. Compared to 2008-2014, the mean water temperature (WT) and the mean phosphate are higher, the mean photosynthetically active radiation (PAR), the mean total suspended solids (TSS), and the mean dissolved inorganic nitrogen (DIN) are lower, during 2015-2020. Their contribution to algal biomass resurgence during 2015-2020 is WT (+58.7 %), PAR (-2.6 %), TSS (+23.2 %), DIN (-22.1 %) and phosphate (+42.7 %), respectively. Climate change (WT, PAR, and TSS), which contributed +64.9 % to the phytoplankton biomass resurgence, underscores the urgent need to continuously take more effective measures to reduce nutrient emissions to offset the effects of climate change in Lake Taihu and in other eutrophic lakes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationship that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The impact of drought on terrestrial ecosystems is increasing, and the spatiotemporal heterogeneity of drought changes exacerbates the difficulty of determining ecosystem responses, especially in arid regions far from oceans. Tree rings have been widely used to understand how forest ecosystems respond to drought. However, the link between local hydroclimate variations related to tree rings and large-scale climate changes is not clear in the Qilian Mountains. Here, we used the tree ring width index to analyze the trend of Picea crassifolia growth and its relationship with climate in the middle Qilian Mountains. The results showed that the radial growth trend of Picea crassifolia is synchronized in the middle Qilian Mountains by calculating the Gleichläufigkeit index (GLK). Our analyses indicated that tree radial growth is positively correlated with drought during the growing season. Tree growth responds stably to drought (scPDSI and SPEI) and precipitation but unstably to temperature during 1950-2019. We further traced the meteorological factors that cause regional drought changes associated with radial growth. An increased total precipitation and decreased evaporation contribute to drought alleviation, favoring an increased tree radial growth. The increased total precipitation is mainly due to increased large-scale precipitation, which is related to water vapor transport changes. This study attempts to explore the influence of large-scale meteorology on regional drought change and its related tree radial growth response, which helps us to better understand the changes in forest ecosystems under climate change., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Fractional vegetation cover (FVC) has changed significantly under various disturbances over northern China in recent decades. This research examines the dynamics of FVC and how it is affected by climate and human activity during the period of 1990-2018 in northern China. The effects of climate change (i.e., temperature, precipitation, solar radiation, and soil moisture) and human activity (socioeconomic data and land use) on vegetation coverage change in northern China from 1990 to 2018 were quantified using the Sen + Mann-Kendall test, partial correlation analysis, and structural equation modelling (SEM) methods. The findings of this research indicate the following: (1) From 1990 to 2018, the overall trend in FVC in northern China was increased. The areas with obvious increases were mainly situated on the northern slope of Tianshan Mountains, Xinjiang, the Loess Plateau, the Northeast China Plain, and the Sanjiang Plain, while the areas with distinct degradation were located in the Inner Mongolia Plateau, the Changbai Mountain and the eastern part of north China. (2) In the past 29 years, the FVC in northern China has been mainly affected by precipitation and soil moisture. (3) Based on structural equation modelling, we discovered that certain variables impacted the main factors influencing the amount of FVC in northern China. Human activity has had a larger impact on FVC than climate change. Our findings can accelerate the comprehension of vegetation dynamics and their underlying mechanisms and provide a theoretical basis for regional ecological environmental protection., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Heatwaves have been intensified worldwide due to climate change, posing great health risks, especially to elderly populations. However, in China, limited studies have employed the heat index to decipher the spatiotemporal trends of heatwaves and their impacts on the elderly population. By comparing the three heatwave definitions, this study aimed to evaluate the long-term spatiotemporal variations in heatwaves from 1964 to 2022 across China using the Excess Heat Factor (EHF). We took advantage of high-resolution reanalysis temperature data on the Google Earth Engine (GEE) platform to efficiently calculate the heatwaves. Our results revealed that the frequency and duration of heatwaves increased significantly in approximately 77 % of China's total area, with South China experiencing the most frequent and prolonged heatwaves. Conversely, in most areas, no significant trend was discerned in the growth of the maximum and average heatwave intensities. The total number of elderly people affected by heatwaves surged from approximately 11.96 million in 2001 to over 30.31 million in 2020, with an estimated additional 1.12 million older adults exposed to heatwaves annually across the nation (R 2  = 0.60, p < 0.05). The population factor exhibited largest effect on the exposure of heatwaves, followed by climate effects and combined factors, with the corresponding explanatory power about 42.84 %, 34.85 % and 22.31 %, respectively. These individuals predominantly resided in the Northeast China, Southwest China, and South China. We also found geographical variations in heatwave exposure along elevations and land use types. These insights underscore the pressing necessity for formulating strategic interventions to mitigate the health threats presented by mounting heatwave exposure, especially for susceptible groups like the elderly in China., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

By utilizing the mediation effect model and the spatial Durbin model, this research investigates the influence that environmental restrictions have had on marine pollution in 38 coastal prefecture-level cities from the years 2000-2018. In order to gain a comprehensive understanding of the effect that environmental legislation has on contamination in offshore regions as well as its primary goal, the research takes a variety of different approaches into consideration. Following are the findings from the study; Firstly, pollution levels in coastal marine areas tend to rise at first and then fall when environmental laws are enacted, illustrating a non-linear pattern known as an inverted "U" shape. In order to improve the maritime environment through environmental legislation, it is crucial to support new green technologies. There is a "U" shaped linkage amongst environmental legislation and development of environmentally friendly technologies. Spatial spillover effects may allow for the regulation of coastal city environments to affect marine pollution in neighboring areas. Secondly, there is also an inverted "U" pattern visible in the impact trajectory of this effect. According to the results of this research, it is crucial to set up a strict and factually sound regulatory framework in the field of marine environmental governance. It is also suggested that local context be taken into account while crafting environmental regulating regulations. Also, it's crucial to promote development, dissemination, and use of green technology by completely capitalizing on the innovation's conduction effect. Thirdly, promoting cooperation efforts among areas to avoid and control such pollution is essential, and the transfer and management of offshore pollution between regions must be a top priority., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Inc.)

Flash droughts characterized by rapid onset and intensification are expected to be a new normal under climate change and potentially affect vegetation photosynthesis and terrestrial carbon sink. However, the effects of flash drought on vegetation photosynthesis and their potential dominant driving factors remain uncertain. Here, we quantify the susceptibility and response magnitude of vegetation photosynthesis to flash drought across different ecosystems (i.e., forest, shrubland, grassland, and cropland) in China based on reanalysis and satellite observations. By employing the extreme gradient boosting model, we also identify the dominant factors that influence these flash drought-photosynthesis relationships. We show that over 51.46 % of ecosystems across China are susceptible to flash drought, and grasslands are substantially suppressed, as reflected in both sensitivity and response magnitude (with median gross primary productivity anomalies of -0.13). We further demonstrate that background climate differences (e.g., mean annual temperature and aridity) predominantly regulate the response variation in forest and shrubland, with hotter/colder or drier ecosystems being more severely suppressed by flash drought. However, in grasslands and croplands, the differential vegetation responses are attributed to the intensity of abnormal hydro-meteorological conditions during flash drought (e.g., vapor pressure deficit (VPD) and temperature anomalies). The effects of flash droughts intensify with increasing VPD and nonmonotonically relate to temperature, with colder or hotter temperatures leading to more severe vegetation loss. Our results identify the vulnerable ecological regions under flash drought and enable a better understanding of vegetation photosynthesis response to climate extremes, which may be useful for developing effective management strategies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Diatoms and dinoflagellates are two typical functional groups of phytoplankton, playing important roles in ecosystem processes and biogeochemical cycles. Changes in diatoms and dinoflagellates are thought to be one of the possible mechanisms for the increase in harmful algal blooms (HABs), due to changing hydrological conditions associated with climate change and human activities. However, little is known about their ability to adapt to changing ocean environments, thus making it difficult to know whether and how they are adapting. By analyzing a 44-year monitoring dataset in the central Bohai Sea during 1978-2021, we found that the abundance ratio of diatoms to dinoflagellates showed a decreasing trend seasonally and ecologically, indicating that the phytoplankton community underwent distinct successional processes from diatom dominance to diatom-dinoflagellate co-dominance. These processes exhibited varying responses to temperature, nutrient concentrations and ratios, and their interactions, of which temperature primarily drove the seasonal succession whereas nutrients were responsible for the ecological succession. Specifically, diatoms showed a preference for lower temperatures and higher DIP concentrations, and were able to tolerate lower DIN at lower temperatures. In contrast, dinoflagellates tended to prevail at conditions of warming and high N/P ratios. These different traits of diatoms and dinoflagellates reflected the fact that warming as a result of rising temperature and eutrophication as a consequence of nutrient input would favor dinoflagellates over diatoms. Moreover, the increasing dominance of dinoflagellates indicated that dinoflagellate blooms were likely to become more frequent and intense in the central Bohai Sea., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Corn is the third most cultivated food crop in the world, and climate change has important effects on corn production and food security. China is the top user of chemical fertilizer in the world, and analyzing how to effectively manage fertilizer application in such a developing country with resource constraints is crucial. We present empirical evidence from China to demonstrate the nonlinear impact of temperature on fertilizer usage in corn production based on a panel dataset that shows 2297 corn-growing counties during 1998-2016. Our findings indicate that fertilizer usage barely changes with increasing temperatures that are below 28 °C; however, exposure to temperatures above 28 °C leads to a sharp increase in fertilizer use. The increase in temperatures in the sample period implies that fertilizer usage per hectare for corn increased by 1.5 kg. Summer corn fertilizer application in the Yellow-Huai River Valley is more sensitive to warming than in the North region. Moreover, nitrogen, phosphorus, and potassium fertilizers have different temperature thresholds of 32 °C, 20 °C, and 20 °C, respectively, that cause significant changes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Drought and floods seriously affect agriculture across the world. It is of great importance to lower down the agricultural vulnerability to disasters to build climate-resilient agriculture. The paper aims to investigate the spatio-temporal changes of agricultural vulnerability to drought and floods in the world in the period 2003-2019. Research results show that (1) the agricultural vulnerability to drought and floods is at a low level across the globe owning to the dual effects of decreasing exposure and increasing adaptability; (2) the northern parts of United States, northeastern parts of China, and the border between Russia and Kazakhstan are identified as most vulnerable areas to drought and floods; and (3) spatio-temporal mismatch of precipitation is the main factor to cause floods and drought while better adaption is beneficial to minimize the adverse effects of disasters. Based on analysis on the drivers and spatial patterns of drought and floods risk in all dimensions, tailored measures and policies are put forwards to make adaptive strategies of agriculture to climate change., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Grasslands are one of the most important terrestrial biomes, supporting a wide range of ecological functions and services. Grassland degradation due to overgrazing is a severe issue worldwide, especially in developing regions. However, observations from multiple sources have shown that temperate grasslands in China have significantly increased during the past two decades. It remains controversial what factors have driven the vegetation restoration in this region. In this study, we combined remote-sensing images and field survey datasets to quantify the contributions of different factors to vegetation restoration in six temperate grasslands in northern China. Across the six grasslands, the Normalized Difference Vegetation Index (NDVI) increased by 0.003-0.0319 year -1 . The average contributions of grazing exclusion and climate change to the NDVI increase were 49.23 % and 50.77 %, respectively. Precipitation change was the primary climate factor driving vegetation restoration, contributing 50.76 % to the NDVI variance. By contrast, climate warming tended to slow vegetation restoration, and atmospheric CO 2 concentration change contributed little to the NDVI increase in the temperate grasslands. These results emphasize the significant contributions of both climate change and human management to grassland vegetation restoration., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

The response of vegetation to climate change and human activities has attracted considerable attention. However, quantitative studies on the effects of climate change and human activities on dryland vegetation in different seasons remain unclear. This study investigated the impacts of precipitation, temperature, soil water storage (SWS) (top [0-7 cm], shallow [7-28 cm], and middle [28-100 cm] layers), vapor pressure deficit (VPD), and afforestation on vegetation as well as their relative contribution rates during the rainy season ([RS], June to September), dry season ([DS], November to April), transition season ([TS], May and October), and all year period (AY) in China's drylands from 2001 to 2020 using the first-difference method. Areas with precipitation and SWS showing significant positive correlation with dryland vegetation (p < 0.05) were found to be larger in RS than in DS and TS, and the positive effect of SWS increased with soil depth in the 0-28 cm interval. Increasing VPD induced a significant negative effect on vgetation during RS but it was not predominant in DS and TS. Afforestation showed an extremely significant positive correlated with dryland vegetation across >60 % of China's dryland areas (p < 0.01), but this improvement was found to be limited to regions with the highest afforestation area. Moreover, dryland vegetation dynamics were driven by afforestation in all seasons, with contribution rates of 64.23 %-71.46 %. The effects of SWS and VPD on vegetation driven by precipitation and temperature exceeded the direct effects of precipitation and temperature. Among climatic factors, VPD showed a major regulating effect on dryland vegetation at the top and shallow soil layers in almost all seasons, whereas the relative contribution rate of SWS increased with soil layer. The findings can provide a scientific reference for the sustainable development and protection of drylands under global warming., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

The economic impacts of climate-induced heat stress on pig farming have not been sufficiently investigated, despite the significant threat it poses to the industry. In this study, we coupled consecutive years of county-scale meteorological data with operational-level economic data to estimate the impact of climate-induced heat stress on the productivity of the Chinese pig industry using a stochastic frontier production function model. Based on model results, we projected the impact of heat stress on pig production in 2030 and 2050 with and without technological advances. Results showed that heat stress has a significant negative impact on pig production, with southern regions being more affected. However, considering technological advances, losses will decrease by 21 % and 52 %, respectively, compared with the scenario without technological advances. Simultaneously, we calculated the costs of climate change mitigation and adaptation and found that increasing production inputs to reduce production losses from heat stress costs one-fifth of forgoing production losses. Therefore, we recommend a positive climate change response strategy., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier B.V.)

Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Over-exploitation of groundwater due to intensive irrigation and anticipated climate change pose severe threats to the water and food security worldwide, particularly in the North China Plain (NCP). Limited irrigation has been recognized as an effective way to improve crop water productivity and slow the rapid decline of groundwater levels. Whether optimized limited irrigation strategies could achieve a balance between groundwater pumping and grain production in the NCP under future climate change deserves further study. In this study, an improved Soil and Water Assessment Tool (SWAT) model was used to simulate climate change impacts on shallow groundwater levels and crop production under limited irrigation strategies to suggest optimal irrigation management practices under future climate conditions in the NCP. The simulations of eleven limited irrigation strategies for winter wheat with targeted irrigations at different growth stages and with irrigated or rainfed summer maize were compared with future business-as-usual management. Climate change impacts showed that mean wheat (maize) yield under adequate irrigation was expected to increase by 13.2% (4.9%) during the middle time period (2041-2070) and by 11.2% (4.6%) during the late time period (2071-2100) under three SSPs compared to the historical period (1971-2000). Mean decline rate of shallow groundwater level slowed by approximately 1 m a -1 during the entire future period (2041-2100) under three SSPs with a greater reduction for SSP5-8.5. The average contribution rate of future climate toward the balance of shallow groundwater pumping and replenishment was 62.9%. Based on the simulated crop yields and decline rate of shallow groundwater level under the future climate, the most appropriate limited irrigation was achieved by applying irrigation during the jointing stage of wheat with rainfed maize, which could achieve the groundwater recovery and sustainable food production., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Climate change has impacted the distribution and abundance of numerous plant and animal species during the last century. Orchidaceae is one of the largest yet most threatened families of flowering plants. However, how the geographical distribution of orchids will respond to climate change is largely unknown. Habenaria and Calanthe are among the largest terrestrial orchid genera in China and around the world. In this paper, we modeled the potential distribution of eight Habenaria species and ten Calanthe species in China under the near-current period (1970-2000) and the future period (2081-2100) to test the following two hypotheses: 1) narrow-ranged species are more vulnerable to climate change than wide-ranged species; 2) niche overlap between species is positively correlated with their phylogenetic relatedness. Our results showed that most Habenaria species will expand their ranges, although the climatic space at the southern edge will be lost for most Habenaria species. In contrast, most Calanthe species will shrink their ranges dramatically. Contrasting range changes between Habenaria and Calanthe species may be explained by their differences in climate-adaptive traits such as underground storage organs and evergreen/deciduous habits. Habenaria species are predicted to generally shift northwards and to higher elevations in the future, while Calanthe species are predicted to shift westwards and to higher elevations. The mean niche overlap among Calanthe species was higher than that of Habenaria species. No significant relationship between niche overlap and phylogenetic distance was detected for both Habenaria and Calanthe species. Species range changes in the future was also not correlated with their near current range sizes for both Habenaria and Calanthe. The results of this study suggest that the current conservation status of both Habenaria and Calanthe species should be adjusted. Our study highlights the importance of considering climate-adaptive traits in understanding the responses of orchid taxa to future climate change., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

To detect potential impacts of climate change on the distribution of common echinoderm species in the Yellow Sea (YS) and East China Sea (ECS), species distribution models (SDMs) were applied. Ensemble SDMs were constructed and were in good model performance for six of the eight selected common echinoderm species. Under future climate scenarios, the brittle stars Ophiopholis mirabilis, Amphioplus depressus and the sea cucumber Protankyra bidentata were projected to expand in the southwestern areas of the YS, the ECS, and the coastal areas of the YS and ECS, respectively; the brittle stars Stegophiura sladeni, Amphiura digitula and Amphiura vadicola will likely contract their ranges in the south distribution areas and expand in the north, showing a northward movement trend. Temperature was the most important environmental variable influencing the distribution of the latter three echinoderms. Our findings will improve our understanding of the impacts of climate change on marine species distributions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Combining the comprehensive effects of temperature and humidity, this study applies a heat stress index to project future population exposure to high temperature and related health-risks over China under different climate change scenarios. Results show that the number of high temperature days, population exposure and their related health-risks will increase significantly in the future compared to the reference period (1985-2014), which is mainly caused by the change of >T99p (the wet bulb globe temperature >99th percentile derived from the reference period). The population effect is absolutely dominant in influencing the decrease in exposure to T90-95p (the wet bulb globe temperature is in the range of (90th, 95th]) and T95-99p (the wet bulb globe temperature is in the range of (95th, 99th]), and the climate effect is the most prominent contributor to the upsurge in exposure to > T99p in most areas. An additional 0.1 billion person-days increase in population exposure to T90-95p, T95-99p and >T99p in a given year is associated with the number of deaths by 1002 (95% CI: 570-1434), 2926 (95% CI: 1783-4069) and 2635 (95% CI: 1345-3925), respectively. Compared with the reference period, total exposure to high temperature under the SSP2-4.5 (SSP5-8.5) scenario will increase to 1.92 (2.01) times in the near-term (2021-2050) and 2.16 (2.35) times in the long-term (2071-2100), which will increase the number of people at heat risk by 1.2266 (95% CI: 0.6341-1.8192) [1.3575 (95% CI: 0.6926-2.0223)] and 1.5885 (95% CI: 0.7869-2.3902) [1.8901 (95% CI:0.9230-2.8572)] million, respectively. Significant geographic variations exist in the changes of exposure and related health-risks. The change is greatest in the southwest and south, whereas it is relatively small in the northeast and north. The findings provide several theoretical references for climate change adaptation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Forests influence climate through both the biochemical and biophysical processes, and the impacts of the latter on local climate may be much larger than the former. However, the biophysical effects of afforestation in arid regions have received little attention compared with afforestation in the tropic, temperate and boreal zones. In this study, we combined in situ eddy covariance flux measurements from a neighboring pairs of forested and background desert sites with the decomposed temperature metric (DTM) method to characterize the impacts of arid forests on surface temperature (T s ). A clear-sky, one-dimensional planetary boundary layer (PBL) model was used to estimate the impacts of afforestation on state of regional climate. We showed that despite absorbing more net radiation (35.4 W m -2 ) the riparian forests tended to cool T s (-1.28 °C) on annual basis, but with a significant seasonality. Specifically, afforestation may lead to a net cooling effect from March to September and a slightly warming effect in other months. The DTM method revealed that evapotranspiration played a dominant role in cooling surface temperature, while surface albedo (α) and incoming longwave radiation (L↓) acted together to increase forest surface temperature. From June to September, a shallower, cooler and wetter boundary layer was developed over the forest due to high plant transpiration. In other months, the PBL was slightly deeper and warmer over the forest than that over the desert. Therefore, the riparian forests were important in moderating warming trends in arid regions., Competing Interests: Declaration of competing interest We declared that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work. All authors have agreed the submits of this paper to your Journal. We declared that we will not submit this paper to another Journal until we hear from you., (Copyright © 2022. Published by Elsevier B.V.)

Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Leaf phenology is one of the most reliable indicators of global warming in temperate regions because it is highly sensitive to temperatures. Temperature sensitivity (S T ) is defined as the values of changed days of leaf flushing date (LUD) per degree increase in temperatures. Climate warming substantially advanced LUD in the temperate region, but its effect on S T of LUD is still not clear. We used spring phenological records of 12 woody plants in eastern China in the years of 1983-2014 to explore temporal and spatial changes of LUD and S T . Furthermore, we compared the difference of S T and preseason temperatures in two periods (1983-1997 and 2000-2014), and explored the main factors regulating S T . The results showed that the average LUD significantly advanced (-2.7 days per decade). The mean LUD over the period 1983-2014 was in day of the year (DOY) 87 ± 7 across sites and species for the early leaf flushing species (EFS), and mean DOY 102 ± 5 for the late leaf flushing species (LFS). LUD was earlier in low latitude than that in high latitude. S T of Armeniaca vulgaris was the most sensitive to temperature across all sites (-3.66 d °C -1 ), while Firmiana simplex was the most insensitive (-2.37 d °C -1 ). LUD of EFS was more sensitive to temperature warming than that of LFS. At the same site, LUD of EFS would advance more obviously than that of LFS under global warming. For all species, S T decreased significantly with shorter preseason length and warmer temperatures at the preseason end. Our results had demonstrated a strong relationship between S T and the preseason length (mean temperature at the preseason end)., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Quantifying the contributions of climate change (CC) and human activities (HA) to vegetation change is crucial for making a sustainable vegetation restoration scheme. However, the effects of extreme climate and time-lag and -accumulation effects on vegetation are often ignored, thus underestimating the impact of CC on vegetation change. In this study, the spatiotemporal variation of fractional vegetation cover (FVC) from 2000 to 2019 in northern China (NC) as well as the time-lag and -accumulation effects of 15 monthly climatic indices, including extreme indices, on the FVC, were analyzed. Subsequently, a modified residual analysis considering the influence of extreme climate and time-lag and -accumulation effects was proposed and used to attribute the change in the FVC contributed by CC and HA. Given the multicollinearity of climatic variables, partial least squares regression was used to construct the multiple linear regression between climatic indices and the FVC. The results show that: (1) the annual FVC significantly increased at a rate of 0.0268/10a from 2000 to 2019 in all vegetated areas of NC. Spatially, the annual FVC increased in most vegetated areas (∼81.6 %) of NC, and the increase was significant in ∼54.6 % of the areas; (2) except for the temperature duration (DTR), climatic indices had no significant time-lag effects but significant time-accumulation effects on the FVC change. The DTR had both significant time-lag and -accumulation effects on the FVC change. Except for potential evapotranspiration and DTR, the main temporal effects of climatic indices on the FVC were a 0-month lag and 1-2-month accumulation; and (3) the contributions of CC and HA to FVC change were 0.0081/10a and 0.0187/10a in NC, respectively, accounting for 30.2 % and 69.8 %, respectively. HA dominated the increase in the FVC in most provinces of NC, except for the Qinghai and Neimenggu provinces., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier B.V.)

Average climatic events describe the occurrence of weather or climate at an average value, whereas extreme events are defined as events that exceed the upper or lower threshold value of statistical or observational average climatic events. This study investigated the impacts of both average climate change (ACC) (i.e., average precipitation, temperature, and potential evapotranspiration [PET]) and extreme climate change (ECC) (i.e., five precipitation and five temperature extremes) on dryland vegetation based on the Normalized Difference Vegetation Index (NDVI). The spatial divergences of ACC and ECC in affecting changes in NDVI over drylands were determined using the geographical detector model. In this study, the growth of vegetation in 40.29 % of global drylands was driven by average precipitation and this dominant effect also occurred in all the plant species, particularly shrubs. However, the sensitivity of grassland to average precipitation exceeded that of most of the woody vegetation. The average temperature and PET controlled 28.64 % and 31.07 % of the changes in NDVI, respectively. Precipitation extremes (except for consecutive dry days and consecutive wet days) and warm temperature extremes (WTE) had positive influences on dryland vegetation, and the effect of WTE on NDVI exceeded that of the remaining temperature extremes. Temperature extremes exerted more significant effects than precipitation extremes for changes in the grassland NDVI. In contrast, the variations in shrub NDVI were primarily dominated by precipitation extremes. We also found that the impacts of parts of average and extreme climatic factors on vegetation had changed over time. Furthermore, temperature extremes had far exceeded the average temperature in affecting vegetation growth at the spatial scale, and this action gradually intensified from 1982 to 2015. The influences of all precipitation extremes were weaker than those of the average precipitation. Those can offer scientific references for ecosystem protection in drylands., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

The climate aridity since the mid-20th century has raised concerns about water resources on the Chinese Loess Plateau (CLP). A lack of extended observation-like precipitation records for the eastern CLP (ECLP) means that it remains unclear whether or not the current arid state of the CLP is unprecedented, and the spatial-temporal characteristics of hydroclimatic variability across the CLP over past centuries are not well understood. Here we present a regional hydrological-year precipitation reconstruction for the Heichashan Mountains, which successfully captures hydroclimate changes on the ECLP since 1773 CE. The reconstruction explains 48.72 % of the observed variance for 1957-2019 CE and reveals a wetting trend since the early 2000s and shows 2014-2020 CE to have been the second wettest period over the past 248 years. 1910-1932 CE was the longest and driest period over the past centuries. Furthermore, the 19th century was relatively wet, whereas the 20th century was dry. We demonstrate that droughts tend to occur in warm periods. Combining our new reconstruction with previously published hydroclimatic reconstructions, we find that hydroclimate has changed synchronously on the ECLP and the western CLP (WCLP) for most of the past two centuries. Some regional differences do exist, for example in the 1890s-1920s, when aridity gradually intensified across the ECLP, no similar drying is evident in records for the WCLP, although the 1920s megadrought occurred in both the ECLP and WCLP. Another difference is in the onset of the 20th-century aridity, which began in the 1950s on the ECLP, around 20 years later than it began on the WCLP. In addition to the known influences of the Asian Summer Monsoon and related large-scale circulations, this work highlights a major finding that the 1920s megadrought may be related to a regime shift in Northern Hemisphere temperature., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Climate change has become increasingly severe, threatening ecosystem stability and, in particular, biodiversity. As a typical indicator of ecosystem evolution, vegetation growth is inevitably affected by climate change, and therefore has a great potential to provide valuable information for addressing such ecosystem problems. However, the impacts of climate change on vegetation growth, especially the spatial and temporal distribution of vegetation, are still lacking of comprehensive exposition. To this end, this review systematically reveals the influences of climate change on vegetation dynamics in both time and space by dynamical modeling the interactions of meteorological elements and vegetation growth. Moreover, we characterize the long-term evolution trend of vegetation growth under climate change in some typical regions based on data analysis. This work is expected to lay a necessary foundation for systematically revealing the coupling effect of climate change on the ecosystem., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

The heatwave frequency and intensity have significantly changed as the climate warms and human activities increase, which poses a potential risk to human society. However, the impact factors that determine the change of heatwave events remain unclear. Here, we estimated the heatwave events based on data from 2474 in-suit gauges during 1960-2018 at daily scale in China. Besides, we explored possible drivers and their contributions to the change of heatwave based on correlation analysis, multiple linear regression (MLR), and random forest (RF) in different subregions of China. The results show that the temporal changes of all heatwave metrics exhibit significant differences between the period 1960-1984 and the period 1985-2019. Spatially, the heatwave frequency and duration significant increase in the southern China (S), eastern arid region (EA), northeastern China (NE), Qinghai-Tibet region (QT) and western arid and semi-arid region (WAS). The occurrence of the first heatwave event in a year tends to be earlier in S, NE, EA, WAS, and QT than before. Based on the regression modelling and RF, human activities play an important role in heatwave intensity in all subregions of China. For heatwave frequency, urbanization generate a dominant influence in NE, EA, and QT, with relative contributions (RC) ranging from 32.8 % to 38.9 %. Long-term climate change exerts the dominant influence in C, N, and S. Moreover, the first day of the yearly heatwave event (HWT) in NE is significantly influenced by climate change, with RC of 33.9 % for temperature variation (TEM). Our findings could provide critical information for understanding the causes of heatwave across different regions of China in the context of rapid urbanization and climate change., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Background: As climate change, compound hot extremes (CHEs), daytime and nighttime persistent hot extremes, are projected to become much more frequent and intense, which may pose a serious threat to human health. However, evidence on the impact of CHEs on injury is rare., Methods: We collected injury death data and daily meteorological data from six Chinese provinces during 2013-2018. A time-stratified case-crossover design with two-stage analytic approach was applied to assess the associations of CHEs with injury mortality by intention, mechanism, age and gender. Using the projected daily temperatures of five General Circulation Models (GCMs), we projected the frequency of CHEs and CHEs-attributable mortality burden of injury under three Representative Concentration Pathway (RCP) scenarios., Results: CHEs were significantly associated with increased injury mortality risk (RR = 1.14, 95%CI: 1.09-1.19), with strong effects on unintentional injuries (RR = 1.16, 95%CI:1.11,1.22) and intentional injuries (RR = 1.11, 95%CI:0.99,1.25). Female (RR = 1.21,95%CI: 1.13-1.29) and the elderly (RR = 1.30, 95%CI: 1.22-1.39) were more susceptible to CHEs. Both the frequency and injury mortality burden of CHEs showed a steep rising trend under RCP8.5 scenario, with a 7.37-fold and 8.22-fold increase respectively, by the end of the century, especially in southern, eastern, central and northwestern China., Conclusion: CHEs were associated with increased injury mortality risk, and the CHEs-attributable injury mortality burden was projected to aggravate substantially in the future as global warming. It is urgent to develop targeted adaptation policies to alleviate the health burden of CHEs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Unprecedented pulses of extreme precipitation due to climate change are causing significant stresses and impacts on regional and even global ecosystems. However, the relationship of vegetation response to this disturbance is unclear, such as phase characteristics, extent, timing, and degree. We summarize the nexus between vegetation resistance, recovery, and resilience under three stages of extreme precipitation pulses: duration, lagging, and post-disturbance, and then construct a pragmatic scheme to quantify and validate this complex relationship based on precipitation and Normalized Difference Vegetation Index (NDVI) data for the Qilian Mountains Nature Reserve (QMNR) from 2000 to 2020. The results show that the four extreme precipitation pulses were spring 2010 (118.98 mm), summer 2007 (312.25 mm), autumn 2010 (109.74 mm), and winter 2018 (6.84 mm). Extreme precipitations had a significant effect on vegetation in at least 98.5 % of the area, and there was also a two-month time lag effect. Specifically, the percentage of negative vegetation resistance in the face of four seasons of extreme precipitation pulses was 18.3 %, 2.0 %, 15.4 %, and 21.7 %, respectively, compared to negative recovery rates of 4.8 %, 11.9 %, 17.8 % and 10.2 % respectively, resilience was even more severe, with 20.1 %, 10.9 %, 16.1 % and 16.3 % of vegetation failing to rebound to normal levels within two months. The negative resistance, negative recovery, and weak resilience of vegetation under short-term extreme precipitation pulses are approximately 4.8, 3.7, and 5.3 times more fierce than long-term vegetation degradation. A total of 62 % of the four seasonal areas of severe negative resistance, severe negative recovery, and weak resilience were located in areas of moderate and significant steepness, which confirms that extreme precipitation pulses cause serious degradation of vegetation. Response of vegetation under extreme precipitation pulses is perceived, quantified, and validated in this study, which is essential for addressing climate change., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Distinguishing the respective roles of climate change and anthropogenic activities can provide crucial information for sustainable management of the environment. Here, using the residual trend method (RESTREND), which measures the residue of the actual and potential trends of vegetation, we quantified the relative contributions of human activities (e.g., ecological restoration, overgrazing, and urbanization) and climate change (the warmer and wetter trend) to vegetation dynamics in China during 1988-2018 based on multiple vegetation indices, including the vegetation optical depth (Ku-VOD, C-VOD), normalized difference vegetation index (NDVI), and gross primary productivity (GPP). The results showed that the VOD, NDVI, and GPP exhibited overall increasing trends during 1988-2018. Human activities contributed >70% to the increases in NDVI and GPP in China, whereas a counterbalanced contribution of human activities and climate change was identified for the VOD dynamics (51% vs. 49%). Regions with high contributions from human activities to NDVI, GPP, and VOD were located in northeastern, southern, central, and northwestern China. In northern China, the positive impacts of human activities on NDVI (78%) and BEPS-GPP (83%) were greater than those of climate change. In contrast, human activities contributed 96% to the decrease in Ku-VOD over the same period. Before 2000, climate change promoted increases in GPP and NDVI in most regions of southern China. The increasing rates of GPP and NDVI accelerated after 2000 due to afforestation. However, human activities like overgrazing and urbanization have led to decreases in Ku-VOD in northern and southwestern China, and in C-VOD in northeastern, eastern, central, southwestern, and southern China. In all, the relative roles of climate and human factors varied in different regions when NDVI, GPP, or VOD were individually considered. Our results highlighted that the regional-scale vegetation conditions should be taken into full account to achieve sustainable management of ecosystems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Net ecosystem productivity (NEP) is an important index that indicates the carbon sequestration capacity of forest ecosystems. However, the effect of climate change on the spatiotemporal variability in NEP is still unclear. Using the Integrated Terrestrial Ecosystem Carbon-budget (InTEC) model, this study takes the typical subtropical forests in the Zhejiang Province, China as an example, simulated the spatiotemporal patterns of forest NEP from 1979 to 2079 based on historically observed climate data (1979-2015) and data from three representative concentration pathway (RCP) scenarios (RCP2.6, RCP4.5, and RCP8.5) provided by the Coupled Model Intercomparison Project 5 (CMIP5). We analyzed the responses of NEP at different forest age classes to the variation in meteorological factors. The NEP of Zhejiang's forests decreased from 1979 to 1985 and then increased from 1985 to 2015, with an annual increase rate of 9.66 g C·m -2 ·yr -1 and a cumulative NEP of 364.99 Tg·C. Forest NEP decreased from 2016 to 2079; however, the cumulative NEP continued to increase. The simulated cumulative NEP under the RCP2.6, RCP4.5, and RCP8.5 scenarios was 750 Tg·C, 866 Tg·C, and 958 Tg·C, respectively, at the end of 2079. Partial correlation analysis between forest NEP at different age stages and meteorological factors showed that temperature is the key climatic factor that affects the carbon sequestration capacity of juvenile forests (1979-1999), while precipitation is the key climatic factor that affects middle-aged forests (2000-2015) and mature forests (2016-2079). Adopting appropriate management strategies for forests, such as selective cutting of different ages, is critical for the subtropical forests to adapt to climate change and maintain their high carbon sink capacity., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Changes in extreme events have received increasing attention in the context of climate change. Extreme changes in wet and dry events due to changes in meteorological elements, such as the spatial and temporal redistribution of precipitation and temperature increases, are extreme weather events that have attracted much attention in recent years. In contrast, there is a relative lack of research on extreme compound events that focuses on a transition between wet and dry spells in adjacent months. This paper provides maps of the frequency, duration, and severity of national-scale dry wet abrupt alternation (DWAA) events for 1980-1999 and 2000-2019, aiming to obtain information regarding events in the hotspot areas of DWAA in China during the past four decades in order to analyze their change patterns. This paper performs station-based standardized precipitation evapotranspiration index (SPEI) calculations to characterize local wet and dry spells based on meteorological observations provided by the China Meteorological Administration (CMA) since 1980 with regional analyses based on seven geographic divisions of China. Our finding explicitly discloses the "more-less-more" DWAA variation pattern from North to South China. Additionally, the changes in frequency, duration, and severity in the different regions are revealed. The frequency, duration, and severity of DW increased from 5.08 to 6.74, 17.71 to 24.62, and 12.51 to 17.01, respectively, an increase of 32.53%, 39.04% and 36.01%, while the corresponding WD only increased by 9.45%, 15.22% and 13.51%. In addition, events with a higher severity of DWAA are prone to appear in most regions due to the increasing interval between heavy rainfall and the increase in precipitation under global warming., Competing Interests: Declaration of competing interest The authors declare that they have no conflicts of interest to this work., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Soybean is an important oil crop in China, and the national focus of soybean production is in Northeast China. In order to achieve high-stable yield, it is crucial to acknowledge the impacts of mean climate and extreme climate indices on soybean yield and yield components. In this study, based on the weather data from 61 counties from 1981 to 2017 in Northeast China, we assessed the impacts of mean climate and extreme climate indices on soybean observed yield and simulated yield. Mean climate include effective growing degree days (GDD 10 ), precipitation (Pre), and solar radiation (SR); extreme climate indices include the number of cool days during seed-filling period (C 15 ), the number of cool days during 15 days before anthesis (C 17 ), the number of hot days (H 30 ), maximum amount of 5 Day accumulated precipitation (P5), and consecutive dry days (CDD)). We used the DSSAT-CROPGRO-Soybean model to identify the main yield components for soybean. The results showed that observed soybean yield reduced by 3.57% due to the collective changes in the eight study climate indices. Increases in GDD 10 , decreases in Pre, and decreases in SR caused a 3.96%, -3.89%, and - 0.48% change in soybean yield, respectively. Decreases in C 15 and C 17 led to a 5.36% increase in soybean yield; increases in H 30 , P5, and CDD caused a 5.75%, 0.30%, and 1.14% reduction in soybean yield, respectively. By comparing the response of observed and simulated soybean yield to climate indices (excluding P5) in the DSSAT-CROPGRO-Soybean model, we identified the key yield components for soybean as the number of pods and seed weight. The negative impacts on the number of pods and seed weight were mainly attributed to changes in Pre and H30 from anthesis to podding and during seed-filling period. Our results could be used to assist the local soybean community adapt to climate change., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Variation in the physical and chemical environment driven by climate change poses severe threats to the world cultural heritage. Assessing climate risk of cultural heritage is significant to their protection, especially for countries such as China which has a long history and a large amount of cultural heritage. In the study, we employ the risk assessment framework proposed by the Intergovernmental Panel on Climate Change (IPCC) to assess quantitatively the long-term precipitation-related climate risk of cultural heritage at the provincial level in China. The cultural heritage is divided into 5 categories based on material and cultural characteristics: ancient culture sites, ancient tombs, ancient architectural structures, cave temples and stone carvings, and the modern and contemporary historic sites; and the future climate is projected to 2099 under the RCP-4.5 scenario. The results show that the risk of 5 categories of heritage varies considerably. The overall risk of the ancient culture sites and ancient tombs is significantly higher than that of the other 3 categories of heritage due to the vulnerable materials and old age. Spatially, the central regions of China face the highest overall climate risk due to the high hazard and exposure, followed by the eastern regions and the western regions. There are small regional differences in the risk of the ancient tombs while significant regional differences in the risk of the ancient architectural structures. To mitigate the climate risk of cultural heritage, the study highlights the key regions and the corresponding categories of heritage as well as strategies for prioritizing cultural heritage protection., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Annual gross primary productivity (AGPP) serves as the basis for forming biomass and carbon sinks. Analysing the effects of ecosystem types on AGPP spatial variations would be beneficial for clarifying the spatial variability in AGPP, which would serve ecological management practices such as ensuring regional food security. Based on published eddy covariance measurements in China, we collected AGPP data from 128 ecosystems and analysed the effects of ecosystem types on the spatial variations in AGPP to reveal the AGPP spatial variability and its influencing factors over terrestrial ecosystems of China. The results showed that AGPP significantly differed among ecosystem types and vegetation regions, with the lowest AGPP appearing in grasslands, while different ecosystem types had comparable AGPP within the same vegetation region. The AGPP of all ecosystem types showed a decreasing latitudinal trend but slight longitudinal and altitudinal trends. Mean annual air temperature (MAT) and mean annual precipitation (MAP) were found to affect the spatial variations in AGPP over most ecosystem types, while other factors played little role. The mean annual leaf area index (LAI) and the maximum leaf area index (MLAI) were also found to affect the spatial variations in AGPP over most ecosystem types. Factors influencing the AGPP spatial variations differed among ecosystem types, but all included climatic and biotic factors. Therefore, climate inducing spatial distribution of ecosystem types and the non-zonal water supply made AGPP values and factors affecting the spatial variations in AGPP differ among ecosystem types, while different ecosystem types within the same vegetation region had comparable AGPP values. The spatial variation in AGPP over terrestrial ecosystems of China resulted from the integrated effects of climatic and biotic factors. Our study provided data support for improving the understanding of global AGPP spatial variability., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

The altitudinal changes of plant phenology in response to climate change remain poorly understood in subtropical mountain areas. Using the satellite phenology and climate dataset (temperature, precipitation and solar radiation) from 2001 to 2016 in southwest China, we analyzed the spatiotemporal changes of climate and phenological characteristics of the growing season length (LOS), start of the growing season (SOS) and end of the growing season (EOS) for the deciduous broadleaf forest (DBF). Results show that LOS was shortened by 25 and 15.2 days/km rise in elevation, respectively, using two regression methods based on "Hopkins' bioclimatic law" (expressing LOS as a function of altitude, latitude and longitude) and altitudinal mean annual LOS. The majority of the shortened LOS towards high elevations was attributed to the postponed SOS and the advanced EOS as the elevation is higher and lower than 2.2-2.3 km, respectively. The recent climate warming has significantly prolonged LOS in the entire DBF area. This increase in LOS differs with altitude due to altitudinal heterogeneity of climate change. In the cold high mountain environment, changes of phenological parameters are more sensitive to climate warming, characterized by a significantly advanced SOS, postponed EOS and prolonged LOS driven by spring and autumn warming. In the warm environment of the low elevation areas, changes of phenological parameters are relatively smaller even though the temperature rise is greater than that in the cold high mountains. Furthermore, winter wetting can significantly weaken the advanced SOS and prolonged LOS at lower elevations in the warm south, but winter drying and declining solar radiation in spring can enhance the advanced SOS and prolonged LOS at the extremely high elevations in the cold north. These results highlight the critical need to include altitudinal heterogeneity when assessing phenological changes from remote sensing platforms., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Near-surface air temperature is an important indicator of climate change and extreme events. ERA5-Land reanalysis products feature finer spatial and temporal resolutions, and have been widely adopted in global climate-related research. However, the performance of ERA5-Land air temperature data in coastal urban agglomerations has received little attention. In this study, a comprehensive evaluation is conducted in the Guangdong-Hong Kong-Macau Greater Bay Area (GBA) using the observations of 1080 automatic weather stations in 2018 as reference. Generally, ERA5-Land underestimates temperature (an average bias of 0.90 °C), and performs better at low temperatures than at high temperatures. At the station level, it is observed that the correlation shows a strong positive linear relationship with the distance to the coastline in summer, and that the bias increases with increasing altitude throughout the year. With respect to different land cover types, data accuracy over urban and built-up lands is the lowest. The spatial pattern of ERA5-Land is generally consistent with that of stations but relatively poor in urban areas. In addition, ERA5-Land properly captures daily and monthly variations, as well as intraday temperature fluctuations. These conclusions provide a reference for the implementation of ERA5-Land in coastal urban agglomerations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

The increasing uncertainty related to disaster risk under climate change brings about new challenges for sustainable urban management. The emergence of the urban resilience concept can improve the ability and extent to which cities can absorb and resolve risks, providing insight into the sustainable development of cities and regions. Yet, to date, the impact of climate change on regional urban resilience is not well understood. This paper measures the changes in urban resilience of the Beijing-Tianjin-Hebei (BTH) region from 1998 to 2019, and then explores the contribution of climate influencing factors such as temperature, precipitation and wind speed to urban resilience using econometric models. Results demonstrate the following: (1) Urban resilience shows a large spatial heterogeneity in the BTH region. Overall, Beijing and Tianjin have better and more stable resilience than Hebei Province. (2) Regarding the static impact of climate change on urban resilience, a 1 unit increase in Ln temperature and Ln precipitation will respectively increase Ln resilience by 1.01 units and 0.54 units, indicating that it has a significant positive impact on urban resilience. Each 1 unit increase in Ln wind speed will decrease resilience by 1.65 units, representing a significant negative effect. (3) Regarding the dynamic impact of climate change on urban resilience, a positive 1 unit impact of climatic factors indicates that an increase in temperature will first increase and then decrease urban resilience, and an increase in precipitation and wind speed will initially support improvement in urban resilience. Based on these findings, this article offers policy recommendations to improve urban resilience., Competing Interests: Declaration of competing interest The authors declare that there is no conflict of interests regarding the publication of the article., (Copyright © 2022. Published by Elsevier B.V.)

Irrigation substantially alters land surface temperature (LST) in different regions of the world. Studies have recently focused on quantifying irrigation-induced LST change based on remote sensing technology due to its high spatiotemporal resolution. However, the biophysical mechanisms of irrigation on LST remains poorly understood. Here we first investigated the impact of irrigation on LST during 2003-2012 over the North China Plain (NCP), which is one of the most intensively irrigated areas around the word. We then attributed the mechanisms underlying LST change between adjacent irrigated and non-irrigated croplands based on two surface energy balance-based methods: the Decomposed Temperature Metric (DTM) method and the intrinsic biophysical mechanism (IBM) method. The results indicate that at annual scale, irrigation produce an overall cooling effect over the NCP, with the mean observed LST change of -0.098 K, calculated LST change of -0.096 K for DTM method and -0.165 K for IBM method, respectively. Furthermore, the agreement between the annual observed and calculated LST difference indicate that DTM is a more robust method than IBM in quantifying irrigation-induced LST change over the NCP. The attribution method DTM reveals that components of albedo and emissivity has an average cooling effect of -0.012 K and -0.005 K, respectively, while incoming radiation lead to a weak warming effect of +0.01 K. The enhanced turbulent fluxes of latent heat flux dominate the cooling effect (-0.174 K on average), further offsets the sensible heat flux warming effect (+0.085 K). Another attribution method IBM demonstrates that the annual cooling effect of irrigation is mostly induced by changes in aerodynamic resistance (-0.175 K), whereas the biophysical contributions of albedo (-0.0005 K) and Bowen ratio (+0.001 K) have a negligible impact on LST. This study provides a useful reference for assessing local climate impact of irrigation when implementing environmental protection projects., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier B.V.)

Terrestrial evapotranspiration (ET) refers to a key process in the hydrological cycle by which water is transferred from the Earth's surface to lower atmosphere. With spatiotemporal variations, ET plays a crucial role in the global ecosystem and affects vegetation distribution and productivity, climate, and water resources. China features a complex, diverse natural environment, leading to high spatiotemporal heterogeneity in ET and climatic variables. However, past and future ET trends in China remain largely unexplored. Thus, by using MOD16 products and meteorological datasets, this study examined the spatiotemporal variations of ET in China from 2000 to 2019 and analyzed what is behind changes, and explored future ET trends. Climate variation in China from 2000 to 2019 was statistically significant and had a remarkable impact on ET. Average annual ET increased at a rate of 5.3746 mm yr -1 (P < 0.01) during the study period. The main drivers of the trend are increasing precipitation and wind speed. The increase in ET can also be explained to some extent by increasing temperature, decreasing sunshine duration and relative humidity. The zonation results show that the increase in temperature, wind speed, and precipitation and the decrease in relative humidity had large and positive effects on ET growth, and the decrease in sunshine duration had either promoting or inhibiting effects in different agricultural regions. Pixel-based variations in ET exhibited an overall increasing trend and obvious spatial volatility. The Hurst exponent indicates that the future trend of ET in China is characterized by significant anti-persistence, with widely distributed areas expected to experience a decline in ET. These findings improve the understanding of the role of climate variability in hydrological processes, and the ET variability in question will ultimately affect the climate system., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Extreme temperature and precipitation indices have important implications for the crop growing season. Whether a coupled regional model with carbon-nitrogen cycling (CN) and vegetation dynamics (DV) can better represent these indices during the growing season compared with a model without these modules remains unknown. This study evaluates the performance of extreme indices in three wheat planting regions (including northeast spring wheat, north winter wheat and south winter wheat regions) over China in the period of 1990-2009 using the Regional Climate Model (RegCM) coupled with the Community Land Model (CLM), which include CN and DV. The results show that relative to the RegCM-CLM, both the RegCM-CLM-CN and RegCM-CLM-CN-DV perform better in simulating summer days (SU), consecutive dry days (CDD), consecutive wet days (CWD), and the interannual variability in all the extreme indices in the three regions but produce larger biases on frost days (FD). The trends of extreme indices in the high-impact risk region of wheat are also better captured by the RegCM-CLM with CN or CN-DV compared with the model without these modules. In the northeast spring wheat and southern winter wheat regions, the greater cold bias of mean daily minimum temperature between RegCM-CLM-CN-DV and RegCM-CLM is consistent with the leaf area index (LAI) difference, which may increase evaporative cooling and thus increasing FD biases. Overestimation of the LAI may have a weaker effect than the surface albedo on the mean daily maximum temperature, leading to decreased SU biases in RegCM-CLM-CN-DV relative to RegCM-CLM., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Vegetation phenology is a sensitive indicator of climate change and vegetation growth. In the present study, two phenological phases with respect to vegetation growth at the initial and mature stages, namely, the start of the season (SOS) and the peak of the season (POS), were estimated from a satellite-derived normalized difference vegetation index (NDVI) dataset over a long-term period of 32 years (1983 to 2014) and used to explore their responses to atmospheric variables, including air temperature, precipitation, solar radiation, wind speed and soil moisture. First, the forward feature selection method was used to determine whether each independent variable was linear or nonlinear to the SOS and POS. In addition, a generalized additive model (GAM) was used to analyze the correlation between the phenological phases and each independent variable at different temporal scales. The results show that soil moisture and precipitation are linearly correlated with the SOS, whereas the other variables are nonlinearly correlated. Meanwhile, soil moisture, wind speed and solar radiation are found to be nonlinearly correlated with the POS. However, air temperature and precipitation reveal a significant negative correlation with the POS. Furthermore, it was concluded that the aforementioned independent variables from the previous year could contribute to approximately 63%-85% of the SOS variations in the present year, whereas the atmospheric variables from April to June could contribute to approximately 70%-85% of the POS variations in the same year. Finally, the SOS and POS predicted by the GAM exhibit significant agreement with those derived from the satellite NDVI dataset, with the root mean square error of approximately 3 to 5 days., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Amphibians are particularly vulnerable to climate changes that are expected to cause habitat fragmentation and loss and, ultimately, local extirpations. However, little is known about how the interaction between climate change and fragmentation may impede the ability of amphibians to adapt to climate change. Here, we used the iconic mountain frog Quasipaa boulengeri as an indicator species to extrapolate climate-driven shifts in its habitat availability and connectivity in central and southern China according to the minimum and maximum representative concentration pathways. The models projected an average habitat loss of 36%-71% and the in situ and ex situ climate-change refugia to be 29%-64% and 5%-18% of the present-day suitable habitats, respectively. An increase in habitat fragmentation was reflected in a 51% decrease in core patch size, a 9% increase in the mean least-cost path (LCP) length, and a 19% increase in the cost-weighted distance. These climate-driven shifts varied spatially around the Sichuan Basin, with those in the southeast of the Basin being the most pronounced habitat and connectivity losses and those along the Basin being relatively optimistic. The effectiveness of refugia may only be maintained through a narrow passageway along the southern Sichuan Basin because of the presence of LCPs over time. Our results emphasize the need to understand how climate change and connectivity will jointly affect the distribution of mountain amphibians and to accordingly adopt conservation strategies. Further, our findings highlight the importance of identifying and preserving climate-change refugia and habitat connectivity for species persistence and conservation planning., Competing Interests: Declaration of competing interest We declare that we have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Determining appropriate farming management practices to adapt to climate change with lower environmental costs is important for sustainable agricultural production. In this study, a long-term experiment (1985-2019) was conducted under different management practices combining fertilization rate (no, low and high N fertilizer, N 0 , N 1 and N 2 ), straw additions (no, low and high addition, S 0 , S 1 and S 2 ) with conservation tillage (no-tillage, NT) in the North China Plain (NCP). The Denitrification-Decomposition (DNDC) model was firstly evaluated using the experimental data, and then applied to simulate the changes of crop yields, soil organic carbon (SOC), and N 2 O emissions under different management practices combined with climate change scenarios, under low and high emission scenarios of societal development pathways (SSP245 and SSP585, respectively) with climate projections from 2031 to 2100. Under the low emission scenario (SSP245), wheat yields were the highest with the NT-N 1 -S 2 treatment (a 23% increase relative to the baseline (1981-2010)). For maize yields, the NT-N 1 -S 1 treatment increased 46% relative to baseline under the SSP585, whereas, the yields increased less in all treatments under SSP245-2040s. The SOC was predicted to increase by 6-60% by 2100 under SSP245. Straw addition and tillage were the main factors influencing SOC. N fertilizer was the most important driver for wheat and maize yields, however, N 2 O emissions from soil increased with increased application of N fertilizer. Therefore, the no-tillage method under low N fertilizer and high straw addition (NT-N 1 -S 2 ) is recommended to promote crop yields and substantially increase SOC under SSP245 and SSP585. Conservation agriculture practices can potentially offset crop yield reductions, increase soil quality, and reduce greenhouse gas emissions in the NCP, and ensure crop production to meet the growing demand for food under future climate change., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

In this study, the climate change, tsunami and biodiversity for 336 km coastline endangered at the South China Sea was investigated with the review for the past, current and prediction models for the future. The hydraulic study of the coastal area was conducted using a well-established 2D numerical model suite Delft3D. The study revealed that the generated earthquakes at the convergence zone in the last century are small (M w 7.3), the possibility that a megathrust earthquake event in the SCS basin occurs in the future. The study area comprises a narrow strip of vegetation notably dominated by Casuarina equisetifolia with other coastal plants. Mangrove forests are found along the coastline and estuaries that are overlaid with marine alluvial soils. The current paper is the first comprehensive study of the South China Sea, and the findings increase the awareness among the public to understand the risk associated with environmental pollution., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Ecosystems in the arid/humid transition zone (AHTZ) of northern China are highly sensitive to climate change and human activities. Accurately assessing the impact of climate change on these ecosystems is important for effectively reducing the risks faced by them under future climate change. In this study, the leaf area index during the selected growing season (LAI GS ) was used as an indicator for vegetation activity. After comparison different potential indicators, the growing season temperature (T GS ) was used to indicate temperature, and the growing season aridity index (AI GS ), which considers the regional water budget, was used to indicate moisture rather than precipitation, which is used more commonly. Correlation analysis and residual trends were used to study the influence of climatic and non-climatic factors on vegetation activity in the AHTZ from 1982 to 2016. The results for regions where LAI GS increased significantly (0.037/10 yr, 53.58% of the study area), the regions where LAI GS dominated by non-climatic factors (18.40%) was larger than areas dominated by climatic factors (9.61%). However, most (25.57%) of the regions in the selected study area were mainly driven by both climatic and non-climatic factors. In about half (49.73%) of the climate-affected regions, significant changes in LAI GS were driven jointly by T GS and AI GS . These regions were mainly in the northern and western Loess Plateau. The regions where changes were driven mainly by AI GS , and those where changes were driven mainly by T GS , each accounted for nearly a quarter of climate-affected regions (24.87% and 25.40%, respectively). The former regions were on the western Songliao Plain, the northern North China Plain, and the northern Loess Plateau, and the latter regions were in the northern Greater Khingan Mountains, on the southern North China Plain, in the western mountains of North China, and on the southern Loess Plateau., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Climate change is projected to affect the hydrological cycles in China, while the effects are expected to vary spatiotemporally. Understanding the variations in water security conditions and their sensitivity to climatic variables is crucial for assessing regional ecosystem responses to climate change. In the present study, we estimated the water yield capacity, an important indicator of water security in North China (NC), at a spatial resolution of 1 km during the last two decades based on the Budyko framework and quantified the sensitivity of water yield change to climate change among different vegetation types. The results showed that the performances of the Budyko framework were reliable both at the pixel scale and across large watersheds. The annual water yield in North China was estimated to be 7.61 ± 2.67 ∗ 10 10  m 3 /yr, with an average mean water yield (MWY) of 49.51 ± 17.49 mm/yr. The spatial pattern of mean water yield change (MWYC) exhibited high heterogeneity; 46% of the study region was dominated by an increasing trend, while 9.84% was statistically significant (P < 0.05). Compared with temperature, the water yield capacity was more sensitive to precipitation variation. A consistent trend of variation was found in cropland between water yield and precipitation, while negative sensitivity coefficients were found in natural vegetation types. The variation in sensitivity coefficients (Swyp) in natural vegetation showed that in regions with a decrease in precipitation, the variation in water yield capacity also decreased, while in regions with an increase in precipitation from 0 to 8 mm/yr, the water yield capacity first decreased and then increased with precipitation. Our findings suggest that grass and shrubs would be more beneficial to regional water security in North China's revegetation, while afforestation would provide protection for the regional environment from extreme rainfall events., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

The rising temperatures, increased evaporation, and altered precipitation patterns associated with global warming pose threats to aquatic ecosystems, especially the salinization of lake water and changes in the terrestrial carbon budget. We studied a series of samples of catchment soils, surface sediments, and sediment cores from 51 lakes and reservoirs covering an extensive climatic range in northeastern China. Measurements included salinity indices (electrical conductivity and pH) and other physicochemical parameters, including magnetic properties and color (chroma). The results indicate that the occurrence of salt minerals and the salinity of the lake sediments are dominated by the arid climatic conditions of the region. This enabled us to develop climatic transfer functions between salinity, precipitation and evaporation, with potential applications in paleoclimatic research. As carbonates are the dominant salts in most of the studied lakes and reservoirs, past salinity variations are likely reflected by changes in HCO 3 - and CO 3 -carbonate interactions to climate change. Our findings emphasize the important role of alkaline lakes in carbon burial and carbon neutralization, in the context of ongoing global warming.2- concentrations, which provides the opportunity to study the response of water-CO 2 -carbonate interactions to climate change. Our findings emphasize the important role of alkaline lakes in carbon burial and carbon neutralization, in the context of ongoing global warming., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Southwest China is an important biodiversity hotspot in the world and is controlled by the Pacific and Indian Ocean monsoon in the east and west part respectively. However, how abiotic and biotic factors affect the response of vegetation to climate change in different monsoon regions is still not clear. Here we used the annual change rate of growing-season normalized difference vegetation index (NDVI trend) during 1982-2015 to explore the vulnerability of vegetation (forests and shrubs) activity to climate change in southwest China. We examined NDVI trend in relation to: 1) climate change trends, i.e. annual change rate of water and energy availability, indicated by the Palmer Drought Index (PDSI) and potential evapotranspiration (PET), respectively; 2) climatic condition, i.e. mean PDSI and PET during 1982-2015; 3) vegetation height; 4) biome type; 5) monsoon region. The results showed that NDVI generally increased in the Pacific monsoon region, especially in the southern areas, probably because the vegetation under more productive climate were more resistant to climate change, and also because decreased temperature lead to lower evapotranspiration which alleviated the slight drought trend in this region. In contrast, NDVI generally decreased in the Indian Ocean monsoon region which showed more pronounced drought trend, especially in the tall subalpine and tropical forests of Southeast Tibetan Mountains, which supports the "hydraulic limitation hypothesis" that vegetation height interacted with climate change in affecting vegetation vulnerability. Our analysis highlighted the critical roles of different monsoon systems, climate condition and vegetation height in affecting ecosystem vulnerability. We suggest that the (sub)tropical forests in the Pacific monsoon region may have act as an important carbon sink during the past decades, while the tall forests in Southeast Tibetan mountains (a biodiversity center with high carbon stock) are highly vulnerable to climate change and should have priority in ecosystem protection., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Vegetation is highly sensitive to climate changes in arid regions. The relationship between vegetation and climate changes can be effectively characterized by vegetation phenology. However, few studies have examined the vegetation phenology and productivity changes in arid Central Asia (ACA). The vegetation phenological information of ACA was extracted using MODIS NDVI (Normalized Difference Vegetation Index) data, and the dynamics of vegetation phenological changes under spatiotemporal variations were quantitatively assessed. Moreover, the impacts of climate change on vegetation phenology and net primary productivity were analyzed by combining meteorological data with that of MODIS NPP (Net Primary Productivity) during the same period. The results demonstrated that the start of the season (SOS) of vegetation in the study was concentrated from mid-February to mid-April, while the end of the season (EOS) was concentrated from early October to mid-December. The length of growing season (LOS) ranged from 6 to 10 months. The SOS of vegetation was gradually postponed at a rate of 0.16 d·year -1 . The EOS advanced at a rate of 0.69 d·year -1 . The LOS was gradually shortened at a rate of 0.89 d·year -1 . For each per 1000 m increase in elevation, the SOS of vegetation was postponed by 12.40 d; the EOS advanced by 0.40 d, and the LOS was shortened by 11.70 d. For the impacts of climate changes on vegetation phenology and NPP, the SOS of vegetation phenology negatively correlated with temperature but positively correlated with precipitation and NPP. The EOS and LOS positively correlated with temperature but negatively with precipitation and NPP. Results indicated that the SOS was not moved ahead but was delayed, while the EOS advanced rather than being postponed under climate change. These results can offer new insights on the phenological response to climate change in arid regions and on non-systematic changes in phenology under global warming., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

In China, an unambiguous greening trend was observed over the last three decades. The feedback induced by vegetation growth can affect regional climate. Here, we investigated how vegetation feeds back to land surface temperature (LST) in temperature zones and land-use types in China using 18-years (2001-2018) of Moderate Resolution Imaging Spectroradiometer (MODIS) LST and Normalized Difference Vegetation Index (NDVI) data. We first showed that vegetation feedback was significantly negative (p < 0.1, t-test) in most parts of China. Specifically, we discovered a downtrend of vegetation feedback from the coldest temperature zone to the hottest temperature zone. Moreover, vegetation feedback and thermal condition showed an inverse relationship among temperature zones. The inverse relationship clarified that vegetation growth can cool most parts of China during climate change. In the end, we showed the pattern of vegetation feedback among land-use types. Due to the expansion of grassland, vegetation feedback may temporarily positive. Suitable vegetation coverage in urban land, banning deforestation, and cultivating land reasonably can decrease the local temperature by inducing negative vegetation feedback., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)