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The ongoing effects of climate change have exacerbated two significant challenges to global populations: the transmission of foodborne pathogens and antimicrobial resistance (AMR) through the food chain. Using the latest available scientific information this review explores how climate-related factors such as rainfall, floods, storms, hurricanes, cyclones, dust, temperature and humidity impact the spread of the foodborne pathogens Salmonella, E. coli, Campylobacter, Vibrio, Listeria, and Staphylococcus aureus. We explore the complex dynamics between environmental changes and the heightened risk of foodborne diseases, analysing the contribution of wildlife, insects and contaminated environments in the proliferation of AMR and climate change. This review paper combines a thorough analysis of current literature with a discussion on findings from a wide variety of studies to provide a comprehensive overview of how climatic factors contribute to the survival, persistence and transmission of bacterial pathogens in the food chain. In addition, we discuss the necessity for effective mitigation strategies and policies. By providing insights into the interrelationships between climate change and food safety, this review hopes to inform future research and policy development to promote safer and more sustainable food systems and further integration within the One Health approach.

This research explores the effects of High Tide alerts on hotel prices in Venice, a city that is vulnerable to the impacts of extreme climate events due to its fragile ecosystem and a long history of floods in the city center. By analyzing and combining price data from Booking.com with publicly available information on tides and weather, this study uses regression discontinuity design to test for changes in hotel prices when tide levels reach a critical threshold. The results offer insights into the sensitivity of hotel prices to weather alerts and provide valuable information on the potential impact of climate change on Venice's tourism-driven economy, with implications for the cost–benefit analysis of activating protective barriers for lagoon protection. [ABSTRACT FROM AUTHOR]

[Significance] The proposal of a carbonate factory and its classification study are of great significance for promoting the development of carbonate sedimentology. However, the current classification scheme is not sufficient to cover all carbonate sediments, so it is urgent to clarify different carbonate factories at the level of mechanism and process. [Progress] The carbon used by traditional carbonate factories mainly comes from atmospheric and oceanic inorganic carbon pools, whereas certain marine and continental carbonate factories mainly fix carbon from exogenous carbon pools, so the two are fundamentally different. The latter is often highly significant for tracing deep water environments and climate events. [Conclusions and prospects] As an example, this study takes hydrocarbon seep carbonate, and formally puts forward the concept of a cold seep carbonate factory. In addition, its sedimentary characteristics, biological composition and biogeochemical processes are summarized, and an example is discussed to address its geological significance. The type of carbonate factory based on an exogenous carbon pool deserves much attention. [ABSTRACT FROM AUTHOR]

The Late Pleistocene to the Holocene is a time interval that covers the climate transition from a cold to a warm interglacial regime. In the Baltic region, many studies have focused on estimating environmental responses to climatic forcing using palynological and stratigraphic proxies of glacial and periglacial settings. Herein we describe the mixed lacustrine-aeolian succession of the Zervynos-2 section (south-eastern Lithuania), located in the north-eastern part of the European Sand Belt. The succession and the sedimentation styles were characterized by granulometric parameters, structural features, dolomite/calcite ratio, and paleobotanical macro-remains. Our analyses revealed that the Zervynos-2 paleolake formed on the sandur (outwash) plain during the final stage of the Pleistocene. The onset of lake sedimentation was caused by sudden submergence of a sandbody-constrained paleovalley. Carbonate ratios and macro-remains from the lower gyttja material showed the presence of substantial millennial-scale oscillations, which suggests a delayed response to the isotopically derived paleotemperatures. The transition to the fast sand sedimentation started approximately in the Middle Holocene and is interpreted here as being caused by warming and drying of the climate in the Baltic region. The upper Holocene portion of the section represents the transition to exclusively aeolian sedimentation with lower accumulation rates that are likely related to a long-term cooling trend. The obtained results support the conjecture that there is a direct but delayed positive correlation between dolomite and calcite ratios in lake sediments and the climatic signal in the Greenland GISP2 record.

Climate change forecasts indicate that the frequency and intensity of extreme climate events will increase in the future; these changes will have important effects on ecosystem stability and function. An important arid region of the world, Central Asia has ecosystems that are extremely vulnerable to extreme weather events. However, few studies have investigated the resistance and resilience of this region's ecosystems to extreme weather events. In this study, first, the extreme drought/wet threshold was calculated based on the 113-year (1901–2013) standardized precipitation–evapotranspiration index (SPEI); second, moderate resolution imaging spectroradiometer (MODIS) remote sensing data were applied to calculate ecosystem water use efficiency (WUE) and quantify ecosystem resistance and resilience after different extreme climate events; and finally, differences in the changes of various ecosystem types before and after climate events were assessed. The results showed the following: (1) The average SPEI was 0.073, and the thresholds of extreme wetness and drought were 0.91 and −0.67, respectively. Central Asia experienced extreme wet periods in 2002 and 2003 and a drought period in 2008. (2) Suitable wetness levels can increase the resistance of an ecosystem; however, continuous wetness reduces ecosystem resistance, as does drought. Wet areas had strong resilience after wet events, and arid areas had strong resilience after drought events. (3) During both wet and drought years, the transition between shrubland and grassland caused changes in ecosystem resistance and resilience. These findings are important for understanding the impact of future climate change on ecosystem stability. [ABSTRACT FROM AUTHOR]

This paper presents a quantitative framework to optimise embedded footing performance subjected to extreme historical climate events with respect to the uncertainties associated with site-specific soil and climatic parameters. The proposed framework is developed based on partially saturated soil mechanics principles in conjunction with a multi-objective optimisation algorithm called Non-dominated Sorting Genetic Algorithm (NSGA-II) to develop a robust optimised design procedure. The proposed method was applied to two semi-arid climate sites, Riverside and Victorville, both situated in California, United States. The results show that the proposed method generally improves the embedded footing design compared to conventional methods in terms of cost and performance. Based on the findings, under the extreme climate conditions, the proposed method estimates the average soil degree of saturation within the footing influence zone between 52% and 95%, with a mean value of 63.1% for the Victorville site, and 57% and 90% with a mean value of 81.6% for the site in Riverside. It is also found that the optimal design from the proposed method shows a lower total construction cost, 44% and 19%, for the Victorville and Riverside sites, respectively, compared to the ones designed by the conventional methods. [ABSTRACT FROM AUTHOR]

Highlights: What are the main findings? The abundance of most of fish stocks in the Beibu Gulf continued to decline over the last 15 years. What is the implication of the main finding? Environmental variations caused by climate events can episodically enhance the abundance of certain fish stocks. Warming may be the reason of northward shifts in distribution of most fishes. Improving prediction of ecological responses to climate variability requires understanding how local fish population dynamics are impacted by climate events. The present study was conducted in the Beibu Gulf of the northwestern South China Sea where the fisheries are characterized by high ecological and commercial value. We evaluated the relationship between major commercial fish population dynamics (abundance and distribution) and climate periods, using survey data from 2006–2020. The analysis using random forest and GAM models show that climate events are not the best predictors for the variations of fish abundance, because abundance of most fish stocks decreases significantly with the year, and the increasing fishing pressure over time can better explain the overall downward trend in fishery stocks. However, environmental variables that correlate significantly with interannual variation in ONI may impact fish abundance in short terms. Our research suggests that climate events leading to higher surface seawater salinity in winter favors pelagic fishes by improving habitat availability, and higher near-surface chlorophyll-α concentration during La Niña events provides better food condition for overwintering fish. In addition, there is no clear evidence that climatic events have a significant impact on gravity center of fish distribution, whereas climate change has caused most fishes to move to cooler coastal waters in the north. [ABSTRACT FROM AUTHOR]

Populations are subjected to climatic uncertainties, the predictions of which are major challenges for the scientific community. This study analyzes indigenous climate event prediction and adaptation based on indigenous knowledge in North Benin. A sample of 80 holders of indigenous knowledge of prediction of climate events was selected using snowball sampling in the district of Gogonou. Data were collected during semi-structured interviews with the indigenous knowledge holders. Data included the profile of the knowledge holders, climate events and their prediction signs, and the planned responses in the face of climate events. Data were analyzed using discourse analysis and descriptive statistics. The results showed that the holders of indigenous knowledge of prediction of climate events are agropastoralists and some of their wives. They are over 60 years old and rooted in traditional religion. Climate events predicted were floods, pockets of drought, early cessation of rains, and invasion of fields by caterpillars. These climate events are predicted from animal, vegetable, and nature behaviors. The responses developed in the face of climate events are mainly the relocation of fields to firm land, the use of drought-tolerant varieties, the relocation of planting periods, and the planning of the suspension of children's schooling for spreading and planting operations. These findings demonstrate the necessity for policymakers to consider the value of indigenous knowledge to reduce the e􀀀ects of climate change. [ABSTRACT FROM AUTHOR]

Machine learning (ML) and in particular deep learning (DL) methods push state-of-the-art solutions for many hard problems, for example, image classification, speech recognition, or time series forecasting. In the domain of climate science, ML and DL are known to be effective for identifying causally linked modes of climate variability as key to understand the climate system and to improve the predictive skills of forecast systems. To attribute climate events in a data-driven way, we need sufficient training data, which is often limited for real-world measurements. The data science community provides standard data sets for many applications. As a new data set, we introduce a consistent and comprehensive collection of climate indices typically used to describe Earth System dynamics. Therefore, we use 1000-year control simulations from Earth System Models. The data set is provided as an open-source framework that can be extended and customized to individual needs. It allows users to develop new ML methodologies and to compare results to existing methods and models as benchmark. For example, we use the data set to predict rainfall in the African Sahel region and El Niño Southern Oscillation with various ML models. Our aim is to build a bridge between the data science community and researchers and practitioners from the domain of climate science to jointly improve our understanding of the climate system. [ABSTRACT FROM AUTHOR]

The Late Pleistocene to the Holocene is a time interval that covers the climate transition from a cold to a warm interglacial regime. In the Baltic region, many studies have focused on estimating environmental responses to climatic forcing using palynological and stratigraphic proxies of glacial and periglacial settings. Herein we describe the mixed lacustrine-aeolian succession of the Zervynos-2 section (south-eastern Lithuania), located in the north-eastern part of the European Sand Belt. The succession and the sedimentation styles were characterized by granulometric parameters, structural features, dolomite/calcite ratio, and paleobotanical macro-remains. Our analyses revealed that the Zervynos-2 paleolake formed on the sandur (outwash) plain during the final stage of the Pleistocene. The onset of lake sedimentation was caused by sudden submergence of a sandbody-constrained paleovalley. Carbonate ratios and macro-remains from the lower gyttja material showed the presence of substantial millennial-scale oscillations, which suggests a delayed response to the isotopically derived paleotemperatures. The transition to the fast sand sedimentation started approximately in the Middle Holocene and is interpreted here as being caused by warming and drying of the climate in the Baltic region. The upper Holocene portion of the section represents the transition to exclusively aeolian sedimentation with lower accumulation rates that are likely related to a long-term cooling trend. The obtained results support the conjecture that there is a direct but delayed positive correlation between dolomite and calcite ratios in lake sediments and the climatic signal in the Greenland GISP2 record. [ABSTRACT FROM AUTHOR]

Machine learning (ML) and in particular deep learning (DL) methods push state-of-the-art solutions for many hard problems, for example, image classification, speech recognition, or time series forecasting. In the domain of climate science, ML and DL are known to be effective for identifying causally linked modes of climate variability as key to understand the climate system and to improve the predictive skills of forecast systems. To attribute climate events in a data-driven way, we need sufficient training data, which is often limited for real-world measurements. The data science community provides standard data sets for many applications. As a new data set, we introduce a consistent and comprehensive collection of climate indices typically used to describe Earth System dynamics. Therefore, we use 1000-year control simulations from Earth System Models. The data set is provided as an open-source framework that can be extended and customized to individual needs. It allows users to develop new ML methodologies and to compare results to existing methods and models as benchmark. For example, we use the data set to predict rainfall in the African Sahel region and El Niño Southern Oscillation with various ML models. Our aim is to build a bridge between the data science community and researchers and practitioners from the domain of climate science to jointly improve our understanding of the climate system.

Climate change forecasts indicate that the frequency and intensity of extreme climate events will increase in the future; these changes will have important effects on ecosystem stability and function. An important arid region of the world, Central Asia has ecosystems that are extremely vulnerable to extreme weather events. However, few studies have investigated the resistance and resilience of this region’s ecosystems to extreme weather events. In this study, first, the extreme drought/wet threshold was calculated based on the 113-year (1901–2013) standardized precipitation–evapotranspiration index (SPEI); second, moderate resolution imaging spectroradiometer (MODIS) remote sensing data were applied to calculate ecosystem water use efficiency (WUE) and quantify ecosystem resistance and resilience after different extreme climate events; and finally, differences in the changes of various ecosystem types before and after climate events were assessed. The results showed the following: (1) The average SPEI was 0.073, and the thresholds of extreme wetness and drought were 0.91 and −0.67, respectively. Central Asia experienced extreme wet periods in 2002 and 2003 and a drought period in 2008. (2) Suitable wetness levels can increase the resistance of an ecosystem; however, continuous wetness reduces ecosystem resistance, as does drought. Wet areas had strong resilience after wet events, and arid areas had strong resilience after drought events. (3) During both wet and drought years, the transition between shrubland and grassland caused changes in ecosystem resistance and resilience. These findings are important for understanding the impact of future climate change on ecosystem stability.

Improving prediction of ecological responses to climate variability requires understanding how local fish population dynamics are impacted by climate events. The present study was conducted in the Beibu Gulf of the northwestern South China Sea where the fisheries are characterized by high ecological and commercial value. We evaluated the relationship between major commercial fish population dynamics (abundance and distribution) and climate periods, using survey data from 2006–2020. The analysis using random forest and GAM models show that climate events are not the best predictors for the variations of fish abundance, because abundance of most fish stocks decreases significantly with the year, and the increasing fishing pressure over time can better explain the overall downward trend in fishery stocks. However, environmental variables that correlate significantly with interannual variation in ONI may impact fish abundance in short terms. Our research suggests that climate events leading to higher surface seawater salinity in winter favors pelagic fishes by improving habitat availability, and higher near-surface chlorophyll-α concentration during La Niña events provides better food condition for overwintering fish. In addition, there is no clear evidence that climatic events have a significant impact on gravity center of fish distribution, whereas climate change has caused most fishes to move to cooler coastal waters in the north.

The study examines the relationship between sudden- and gradual-onset climate events and migration, hypothesizing that this relationship is mediated by the adaptive capacity of affected individuals. We use survey data from regions of Cambodia, Nicaragua, Peru, Uganda, and Vietnam that were affected by both types of events with representative samples of non-migrant residents and referral samples of migrants. Although some patterns are country-specific, the general findings indicate that less educated and lower-income people are less likely to migrate after exposure to sudden-onset climate events compared to their counterparts with higher levels of education and economic resources. These results caution against sweeping predictions that future climate-related events will be accompanied by widespread migration. [ABSTRACT FROM AUTHOR]

Urban informal settlements have, over the years, been centres of conflicting development debates, yet, for people with low socio-economic status, these are areas of opportunities. However, the "peripheral" nature of these locations has far-reaching implications on how people in these areas participate in decision-making processes that affect them. Lately, the effects of climate-related events have also added another layer of socio-economic, political, and environmental challenge to the dynamics of life in the marginal areas of the urban setting. The purpose of this paper is to critically examine how people in marginal informal settlements of Lilongwe City respond to climate-related events and interact with the wider ecosystem of development stakeholders. The major thesis of the paper is that while critical policymakers ignore these peripheral voices in the provision of basic services, an enhanced support to these informal settlements can prove positive if efforts are harnessed to mitigate the effects of climate-related events and urban marginality and amplify marginal voices to change social policies for the good of all. This paper uses the case of Lilongwe City where three informal settlements of Mtandire, Kaliyeka, and Kawale form part of the study. [ABSTRACT FROM AUTHOR]

Abstract Aim Our study evaluated the effects of extreme weather events and environmental conditions on the trophic groups of copepods (herbivores and omnivores) in the upper Paraná River floodplain. Methods The zooplankton were collected and Copepods and Rotifers were analyzed in nine environments of the upper Paraná River floodplain during 2000 and 2010, during which time the La Niña (drought) and El Niño (flood) climatic events occurred, respectively. Results The results suggest that in periods of extreme drought productivity-related variables act as determining forces on abundance of copepod trophic groups due to the contraction of aquatic ecosystems. Although the abundance of trophic groups is associated with system productivity, the responses between them differ, since herbivore abundance was associated with chlorophyll-a and total phosphorus and omnivores with rotifer abundance. In extreme flood (El Niño), no significant relationship was found between environmental variables and any trophic group. Conclusions In general, it is believed that in periods of extreme drought the variables associated with productivity act as determining forces on the abundance of trophic groups of copepods due to the contraction of aquatic ecosystems. According to the results found, it is suggested that other works be carried out with a greater number of extreme events to corroborate our results and, and also to extrapolate to other aquatic communities.

Rivers are critical ecosystems for protecting and harboring high biodiversity. Tropical rivers particularly are unique for facing extreme climatic events under the current accelerated disruption from human activities. The Bobos-Nautla river basin is exposed to climatic events and disturbances from anthropogenic impacts that stress aquatic organisms. We assessed the health condition of this river system using a non-conventional biomonitor, Corydalus sp., with a set of early-warning biomarkers including lipid peroxidation levels (LPO) and antioxidant activity, superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx), and the neurotransmitter acetylcholinesterase (AChE) considering their spatial and temporal variations. Biomarkers and water quality parameters were analyzed, and the integrated biomarker response (IBR) was assessed as a stress index. Biomarkers showed no significant spatial differences; however, a high-stress period during the rainy season was detected, evidenced by the highest LPO levels; this period is related to the leaching of allochthonous materials from agricultural and urban zones. The peak IBR value during the rainy season confirmed the seasonality of biomarkers. A slight increase in IBR was recorded in lowlands, seemingly associated with agricultural land and human settlements. A principal component analysis showed nutrient enrichment during the rainy season and depletion during the cold-dry season, together with a peak activity of antioxidant enzymes. These results highlight the importance of climatic events such as the rainy season on the health condition of Corydalus sp., which is highly sensitive to the complex mixtures of pollutants that enter the waterbody during extreme climatic events, promoting oxidative stress. Our results also showed the ability of Corydalus sp. to recover and return to a basal level. [ABSTRACT FROM AUTHOR]

This study employs the event study method on the daily closing prices of 385 listed firms in Turkey from December 2020 to December 2022 to examine the market reactions to two significant climate-related events: the Glasgow Climate Pact (GCP) and the Sharm el-Sheikh Implementation Plan (SSIP). The GCP event triggered predominantly adverse market reactions, with significant and negative abnormal returns observed before and after the event and an adverse event day return. Conversely, the SSIP event generated a mixed market response, characterized by significant negative abnormal returns before the event and significant positive abnormal returns after the event. Additionally, the energy sector firms have been vulnerable to the SSIP, given their declining returns, while other sectors experienced significant positive returns. The cross-sectional regression analysis highlights the impact of firm-level characteristics on abnormal returns. For the GCP event, firm leverage, firm size, book-to-market ratio, and past returns exhibit significant associations with abnormal returns during different periods. Similarly, for the SSIP event, firm size, book-to-market ratio, past returns, and past volatility demonstrate significant relationships with abnormal returns. The findings suggest that firms should align their strategies with climate goals and capitalize on emerging clean energy and sustainability opportunities to maintain share prices. Investors must carefully evaluate climate-related events’ impact and consider firm-level characteristics when making investment decisions. This study contributes to understanding market reactions to climate events and provides insights for firms and investors in navigating the evolving landscape of climate change. [ABSTRACT FROM AUTHOR]

During the last glacial–interglacial transition, there were multiple intense climatic events such as the Bølling–Allerød warming and Younger Dryas cooling. These events show abrupt and rapid climatic changes. In this study, the climate events and cycles during this interval are examined through wavelet analysis of Arctic and Antarctic ice-core 18O and tropical marine 14C records. The results show that periods of ~1383–1402, ~1029–1043, ~726–736, ~441–497 and ~202–247 years are dominant in the Arctic region, whereas periods of ~1480, ~765, ~518, ~311, and ~207 years are prominent in the Antarctic TALDICE. In addition, cycles of ~1019, ~515, and ~209 years are distinct in the tropical region. Among these variations, the de Vries cycle of ~202–209 years, correlated with variations in solar activity, was detected globally. In particular, this cycle shows a strong signal in the Antarctic between about 13,000 and 10,500 yr before present (BP). In contrast, the Eddy cycle of ~1019–1043 years was prominent in Greenland and the tropical region, but was not detected in the Antarctic TALDICE records. Instead, these records showed that the Heinrich cycle of ~1480 year was very strong and significant throughout the last glacial–interglacial interval.

This study applied an untargeted–targeted (UT) fingerprinting approach, based on comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC×GC-TOF MS), to assess the effects of rainfall and temperature (both seasonal and elevational) on the tea metabolome. By this strategy, the same compound found in multiple samples need only to be identified once, since chromatograms and mass spectral features are aligned in the data analysis process. Primary and specialized metabolites of leaves from two Chinese provinces, Yunnan (pu′erh) and Fujian (oolong), and a farm in South Carolina (USA, black tea) were studied. UT fingerprinting provided insight into plant metabolism activation/inhibition, taste and trigeminal sensations, and antioxidant properties, not easily attained by other analytical approaches. For example, pu′erh and oolong contained higher relative amounts of amino acids, organic acids, and sugars. Conversely, black tea contained less of all targeted compounds except fructose and glucose, which were more similar to oolong tea. Findings revealed compounds statistically different between spring (pre-monsoon) and summer (monsoon) in pu′erh and oolong teas as well as compounds that exhibited the greatest variability due to seasonal and elevational differences. The UT fingerprinting approach offered unique insights into how differences in growing conditions and commercial processing affect the nutritional benefits and sensory characteristics of tea beverages.

Using a Climate Resilience Screening Index (CRSI) that was developed to represent resilience to acute weather events at multiple scales for the United States, nine regions of the United States are compared for resilience for these types of natural hazards. The comparison examines the domains, indicators, and metrics of CRSI addressing environmental, economic, and societal aspects of resilience to acute climate events at county scales. The index was applied at the county scale and aggregated to represent select regions of the United States. Comparisons showed higher levels of resilience in the Northeast and West, including Alaska, (>4.0) while counties in the South Atlantic and South-Central regions exhibited lower resilience (0.60), and above national median scores for society, built environment and natural environment domains which enhances their resilience scores. South Atlantic and South-Central regions of the US are characterized by higher risk scores (>0.31) accompanied by lower levels of governance (

Abstract: Saroma Lake is the southernmost lagoon exhibiting seasonal sea ice coverage in the Northern hemisphere and one of the most important aquaculture areas for Japanese scallops (Mizuhopecten yessoensis). Under conditions of adequate food and appropriate temperature, scallops grow well from the time of ice melting in April to harvesting starting in July. However, over the past decade, Saroma Lake frequently has not been completely covered by ice in winter, and the production of Japanese scallops has shown significant changes. Therefore, this study integrated data from satellite remote sensing, buoys, and in situ observations with climatic events [the winter East Asian Monsoon (EAM) and El Niño/La Niña–Southern Oscillation events] to investigate the impact of ice coverage variations on scallop growth in Saroma Lake between 2007 and 2015. Daily ice conditions were detected using Moderate Resolution Imaging Spectroradiometer false colour images and an unsupervised classification method. The results indicated that EAM strongly influenced the ice coverage variation in Saroma Lake through their effects on temperature during winter. Ice coverage variations show a strong correlation with water temperature and spring phytoplankton blooms, which are the two most important environmental factors for scallop growth. In addition, extreme climate events could cause water temperature anomalies (as in 2015) which are unfavourable for scallop growth. Monitoring ice conditions should be considered when developing plans and management strategies for scallop aquaculture in Saroma Lake. [ABSTRACT FROM AUTHOR]

The scarcity of well-dated, highly temporally resolved, paleoclimate records since the last glacial maximum (LGM) in Northeast China limits our understanding of past climatic variations and the prediction of future hydrological changes in the context of anthropogenic global warming. A high-resolution n -alkane record covering the past ∼25 kyr was retrieved from Lake Tuofengling, a hydrologically closed crater lake in the central Great Khingan Mountains. The sediments contained a suite of mid- and long-chain n -alkanes with a strong odd-to even-carbon number predominance. The relative proportion of mid-to long-chain n -alkane homologues (P aq) was proposed to evaluate the input of submerged/floating plants into lake sediments relative to that from emergent/terrestrial plants, which could be a useful indicator of lake level in lacustrine settings. The P aq proxy demonstrated that lake level increased stably from the shallowest level during the LGM to a maximum depth at 7.5–3.0 cal ka BP, with a minor decreasing trend during the late Holocene. The asynchronous changes in effective moisture in the East Asian summer monsoon (EASM) region since the LGM might be directly or indirectly mediated by the shift in the rainfall belt, the position and intensity of the Western Pacific Subtropical High and Okhotsk High at different timescales. Our study provides new insights into climatic evolution in Northeast China, where the main climate pattern may not always be similar to the typical EASM pattern. • Changes in lake level reconstructed using Paq ratio since LGM. • Younger Dryas was characterized by relatively humid conditions in Northeast China. • Pacific Ocean was the main regulator of hydroclimatic pattern in the EASM region. [ABSTRACT FROM AUTHOR]

A review of the entire Neogene climate in Europeis a useful tool for climate researchers, synthesizingpresent day knowledge on a variety of past warmer climatemodes thus facilitating the debate regarding possiblefuture climate scenarios in the Old Continent. This workcentres on the European scenario, debating possible futureprojections and describing the Miocene and Plioceneclimate in the Old Continent. With present evidences ofa global warming scenario, it is highly important that welook at past climatic events in order to better predict futureclimate changes impact in biodiversity. The review presentedhere synthesizes the literature regarding climate,faunal and floral evolution for the European Neogene, andaims to help palaeoclimatic researchers and climatologiststo characterize some of the boundary conditions for modellingpossible analogous of IPPC climate scenarios. If thefuture climate projections come to be true, it is shown thatthe Pliocene, and particularly the Mid Piacenzian WarmPeriod, should be considered as the best analogue for theimpact of a warming climate in Europe.