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

Climate change-induced pan-financial market and the contagion of systemic financial risks are becoming important issues in the financial sector. The paper measures the temperature difference in terms of the degree and direction of deviation of the actual temperature relative to the average temperature of the same historical period. Based on the high-dimensional time-series variable LASSO-VAR-DY framework, we construct a pan-financial market volatility correlation network consisting of 112 Chinese listed companies in banking, insurance, securities, real estate, traditional energy, and new energy, use eigenvector centrality to measure the systematic risk of each firm, and then empirically test the effect of temperature difference on systematic risk under pan-financial market scenario. The results of the study show that (ⅰ) There is a significant difference among the systemic risk of financial sectors such as banking, insurance, and securities in the financial market pan-financial market scenario and the systemic risk when the financial market pan-financial market is not taken into account;(ⅱ) Higher temperature significantly exacerbates systemic financial risk, while colder temperature significantly mitigates systemic risk, but both have an asymmetric effect on systemic risk, and there is sectoral heterogeneity.(ⅲ) From the dynamic evolutionary characteristics, there are significant differences in the response of systemic financial risk to positive and negative temperature shocks;(iv) The results of the systemic risk variance decomposition indicate that the temperature change contributes more to the variance of systemic risk in the banking and securities sectors in pan-financial market;(ⅴ) The contagion source of financial systemic risk shows an obvious path of leaping and changing characteristics, and the contagion source of systemic risk (source of impact) shows the evolution law of "bank → real estate → new energy → temperature difference," which means that the temperature difference has become the contagion source of systemic financial risk. This study provides a reference for preventing and resolving systemic risks under pan-financial market scenario and provides a basis for improving the current macroprudential regulatory framework., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Jia, Du. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

This paper investigates the relationship between extreme temperature and online complaints to local government officials. We show that the number of complaints significantly increases by 11.1% on extremely hot days relative to the benchmark temperature. Such effect is most pronounced on the day of extreme weather conditions and muted immediately after the extreme weather day. Among all the complaint areas, we find that 28.6% of the increase in complaints on hot days is related to public service, 42.8% to urban construction, 21.4% to noise, and 7.2% to safety. Moreover, we reveal that the primary motivators of increased complaints on hot days are not likely to be psychological factors; instead, the complaints are more likely to be associated with inadequate provision of public facilities to cope with extreme weather and inadequate management of other environmental disamenities caused by extreme temperature. [ABSTRACT FROM AUTHOR]

Concurrent compound dry and hot events (CDHEs) amplified more damange on the ecosystems and human society than individual extremes. Under climate change, compound dry and hot events become more frequent on a global scale. This paper proposes a mathematical method to quantitatively attribute changes of CDHEs to changes of precipitation, change in temperature and change in the dependence between precipitation and temperature. The attribution is achieved by formulating the total differential equation of the return period of CDHEs among Meta-gaussian model. A case study of China is devised based on monthly precipitation and temperature data during the period from 1921 to 2020 for 80 major river basins. It is found that temperature is the main driving factor of increases in CDHEs for 49 major river basins in China, except for the upper and middle reaches of the Yangtze River. In West China, precipitation changes drove the increase in CDHEs in 18 river basins (23%), particularly in parts of North Xinjiang, Qinghai and Gansu. On the other hand, dependence between precipitation and temperature dominated changes of CDHEs in 13 river basins (16%) of China with other factors, including parts of South China, East China and Northwestern China. Furthermore, changes in both the mean and spread of precipitation and temperature can also contribute to changes in CDHEs. [ABSTRACT FROM AUTHOR]

Understanding runoff dynamics is vital for effective water management in climate-affected areas. This study focuses on the Dayekou basin in China's Qilian Mountains, known for their high climate variability. Using 25 years of data (1994–2018) on river runoff, precipitation, and temperature, statistical methods were applied to explore the annual variations and climate change impacts on these parameters. Results reveal a significant variability in the river runoff (132.27 to 225.03 mm), precipitation (340.19 to 433.29 mm), and average temperature (1.38 to 2.08 °C) over the period. Decadal rising rates average 17 mm for runoff, 17 mm for precipitation, and 0.25 °C for temperature, with the peak precipitation and runoff occurring in 1998–2000, 2008, and 2016. The annual runoff distribution also exhibited a unimodal pattern, peaking at 39.68 mm in July. The cumulative runoff during low periods constituted only 13.84% of the annual total, concentrated in the second half of the year, particularly during the June-October flood season. The correlation analysis underscored a strong relationship between river runoff and precipitation (correlation coefficient > 0.80), while the temperature correlation was weaker (correlation coefficient < 0.80). This 25-year analysis provides valuable insights into runoff variation, elucidating the interconnected effects of temperature and precipitation in the Dayekou basin, with substantial implications for sustainable development amid climate challenges. [ABSTRACT FROM AUTHOR]

Historical records truthfully document human life and activities associated with climate and environmental changes. Based on the official historical records for the years 1–1911 Common Era (i.e., a period of 1911 years), we examine how the 408 epidemic events, occurring in 282 years, are related to solar activity, geographical locations, seasons, and natural disasters of anomalous temperature and irregular precipitation, in China. The epidemics occur more frequently during the low solar activity period. The inland area and area north to the climate boundary of Qinling–Huaihe Line along 35° geographic latitude, in particular, suffer epidemics more often during low solar activity periods. In fact, 45% or more epidemics occurred in summer, while less than 9% occurred in winter. The infection is highly related to social distancing, and therefore the epidemics also occur likely in areas with high-density population or heavy traffic. Statistical tests further demonstrate that natural disasters owing to anomalous temperature and irregular precipitation act as mediators which significantly cause the epidemics in ancient China. [ABSTRACT FROM AUTHOR]