Global Climatic Factors Research Articles

Characterizing the local and global climatic factors associated with vegetation dynamics in the karst region of southwest China

Understanding the relationship between vegetation and climatic drivers is essential for assessing terrestrial ecosystem patterns and managing future vegetation dynamics. This study examines the effects of local climatic factors and remote large-scale ocean–atmosphere circulations from the Pacific, Atlantic, and Arctic Oceans, as well as the East Asian and Indian summer monsoons, on the spatiotemporal variability of the Normalized Difference Vegetation Index (NDVI) in the karst region of southwest China (KRSC) using Mann-Kendall test, Sen’s slope, cross-correlation, and wavelet analysis. We observed a significant increase in NDVI over karst and non-karst regions from 1981 to 2019, with a notable abrupt shift from 2001 onwards, underscoring the importance of understanding the underlying drivers. The significant correlation and coherence of surface air (TMP) and soil temperatures (ST) with NDVI, especially when analyzed using wavelet methods, indicate their crucial role in vegetation dynamics. Additionally, the broad coherence patterns of AMO and WHWP with NDVI at annual and decadal cycles suggest that ocean–atmosphere interactions also play a significant part. At interannual periodicities, most large-scale indices displayed significant coherence with NDVI. These findings highlight the complexity of NDVI variability, which is better explained by the integration of multiple local and global factors rather than by single variables. The integrated local–global drivers, particularly TMP-ST-AMO-NP-WHWP and PCP-SM-AMO-NP-WHWP with mean coherence of 0.90 and 0.89, respectively, showed the highest mean coherence, emphasizing the need for a multifaceted approach in understanding vegetation changes rather than a single local variable or atmospheric circulation index. These findings have significant implications for policymakers, aiding in better planning and policy formulations considering climate change and atmospheric variability.

Integration of Air Conditioning Systems in Intelligent Buildings to Increase Efficiency

Heating, ventilation, air conditioning, and cooling, collectively known as HVAC, account for more than 40% of the electricity consumed in buildings. Global climatic factors, referring to comfort and factors related to health, dictate that there is an increasing need for the application of HVAC/R systems. Therefore, it is increasingly compelling to investigate various approaches to enhance the effectiveness of air treatment systems. The automation of buildings has facilitated the integration of air treatment systems with “other existing” systems that can impact the indoor climatic conditions, such as automated windows and curtains, etc. In order to achieve this, it is essential to employ calculation techniques for air handling systems and for the heat transfer between buildings and the external environment. By integrating these systems, it becomes possible to maintain a comfortable environment while actively minimizing the electricity consumption of the heat pump. This article focuses on the integration of air conditioning systems in intelligent buildings to enhance efficiency.

Assessment of extreme precipitation events in Brazil during 2023: Insights from CHIRPS and rain gauge data

This study conducts a comprehensive analysis of extreme precipitation events that occurred during the year 2023 in Brazil, aiming to provide valuable insights into climate risks and support decision-making related to disaster prevention. Leveraging data from the Climate Hazard Infrared Precipitation with Stations (CHIRPS) and complementing it with observational data from the network gauges of the National Center for Monitoring and Alerts of Natural Disasters (Cemaden), the research focuses on assessing indices derived from rainfall data, notably days with precipitation exceeding 50 mm, and juxtaposes these events against historical averages from 1992 to 2022 to discern anomalies. Data are aggregated at the municipal level, considering the maximum value within each municipal domain. The results highlight the influence of the El Niño phenomenon in the Southern region of Brazil, especially in Rio Grande do Sul, underscoring the importance of considering global and local climatic factors in impact assessment. Additionally, specific analyses are presented for municipalities such as Petrópolis (RJ), Manaus (AM), and São Sebastião (SP), revealing trends and anomalies that warrant attention for adaptation measures and disaster risk reduction. The study concludes that 2023 served as an illustrative year for climate projections, emphasizing the urgency to advance mitigation actions and reduce greenhouse gas emissions to address future climate challenges.

Drivers of soil microbial and detritivore activity across global grasslands

Covering approximately 40% of land surfaces, grasslands provide critical ecosystem services that rely on soil organisms. However, the global determinants of soil biodiversity and functioning remain underexplored. In this study, we investigate the drivers of soil microbial and detritivore activity in grasslands across a wide range of climatic conditions on five continents. We apply standardized treatments of nutrient addition and herbivore reduction, allowing us to disentangle the regional and local drivers of soil organism activity. We use structural equation modeling to assess the direct and indirect effects of local and regional drivers on soil biological activities. Microbial and detritivore activities are positively correlated across global grasslands. These correlations are shaped more by global climatic factors than by local treatments, with annual precipitation and soil water content explaining the majority of the variation. Nutrient addition tends to reduce microbial activity by enhancing plant growth, while herbivore reduction typically increases microbial and detritivore activity through increased soil moisture. Our findings emphasize soil moisture as a key driver of soil biological activity, highlighting the potential impacts of climate change, altered grazing pressure, and eutrophication on nutrient cycling and decomposition within grassland ecosystems.

Supervised Methods for Modeling Spatiotemporal Glacier Variations by Quantification of the Area and Terminus of Mountain Glaciers Using Remote Sensing

Glaciers are important indictors of climate change as changes in glaciers physical features such as their area is in response to measurable evidence of fluctuating climate factors such as temperature, precipitation, and CO2. Although a general retreat of mountain glacier systems has been identified in relation to centennial trends toward warmer temperatures, there is the potential to extract a great deal more information regarding regional variations in climate from the mapping of the time history of the terminus position or surface area of the glaciers. The remote nature of glaciers renders direct measurement impractical on anything other than a local scale. Considering the sheer number of mountain glaciers around the globe, ground measurements of terminus position are only available for a small percentage of glaciers and ground measurements of glacier area are rare. In this project, changes in the terminal point and area of Franz Josef and Gorner glaciers were quantified in response to climate factors using satellite imagery taken by Landsat at regular intervals. Two supervised learning methods including a parametric method (multiple regression) and a nonparametric method (generalized additive model) were implemented to identify climate factors that impact glacier changes. Local temperature, CO2, and precipitation were identified as significant factors for predicting changes in both Franz Josef and Gorner glaciers. Spatiotemporal quantification of glacier change is an essential task to model glacier variations in response to global and local climate factors. This work provided valuable insights on quantification of surface area of glaciers using satellite imagery with potential implementation of a generic approach.

Growth dynamic and climate signals on abandoned plantation of Pinus elliottii in Southern Brazil: A dendrochronological contribution

Pinus plantation forestry in South America has expanded quickly and assumed a significant portion of land use, including in urban arborization. This invasive alien genus changes the plant community, resulting in a loss of biodiversity, and environmental issues that require public policy actions. Here, we applied dendrochronology to assess ecological growth dynamics and micro and macro scale climate effects on an abandoned Pinus elliottii trees in urban forest fragments, and provide insights into the management for public policies. We constructed a robust 41-year (1978 – 2019) chronology that showed r = 0.63, rbar = 0.47, and EPS = 0.92 with an average annual growth rate of 7.10 mm/year. Modeling tree growth of diameter, height and volume of P. elliottii based on tree-ring analysis, we assessed the average diameter without bark (42.37 cm) and height (19 m). The growth rates in the early years evidence pioneer behavior, representing rapid sexual maturity. The volume growth model indicates an average individual volume of 1.23 m³ , with maximum productivity at 16 years when the current annual volume increment peaks. This age corresponds to a diameter of 32 cm, which would be an appropriate minimum logging diameter to wood destined for a sawmill. Volumetric increment rates highlight the potential trade-in forestry sector and application in public policies that aim to control and manage P. elliotti. We evidence significant climatic signals, but with moderate influence on the variability of growth. For the local climatic variables, there was a positive influence of warm and humid summer and late spring, during the previous and current growth seasons. Furthermore, considering global climatic factors, there was only a positive influence of the Annual Southern Oscillation Index for June, representing a positive correlation for dry and cold early winter, influenced by La Niña events. This work provides an understanding of the biological growth of P. elliotti in urban forest fragments and opens a perspective to assist public policies in managing the invasion of Pinus spp. linked to the forest trade.

A dataset of zooplankton occurrence, abundance, and biomass in the Far East seas and adjacent Pacific Ocean waters.

Planktonic animals drifting or floating in the sea have small body sizes and weights from hundreds to thousands of milligrams, and are primarily the food for other zooplankton and macrofauna: fish, cephalopods, seabirds and marine mammals, and also the larval pool of many benthic invertebrates. This paper describes a unique dataset of zooplankton collected from 1984 to 2013 in the North Pacific (the Bering Sea, Sea of Okhotsk, Sea of Japan and adjacent Pacific Ocean waters), one of the most productive and economically important regions of the world's oceans using a Juday net made of kapron sieve No. 49 (0.168 mm mesh) with a 0.1 m2 opening. The information in this dataset has already been used to quantify the inventory of marine biological resources and assess the waters of the Russian Far Eastern seas and adjacent Pacific Ocean. In 2016, five tabular reference books were printed in Russian in limited numbers containing the species composition, occurrence (number and percentage of samples), abundance and biomass (in individuals per cubic meter, milligrams per cubic meter) of zooplankton in the surveyed area. The data are grouped by species, developmental stages, size fractions (animal length of 0.6-1.2 mm "fine/small," 1.2-3.2 mm "medium" and >3.2 mm "large"), standard regions (their total area is more than 6 million km2 ), vertical layers of water, light and dark time of the day, four seasons of the year and multiyear periods, in which there were considerable changes in the biota of the region caused by global climate and oceanographic factors. This information has recently been verified, corrected, translated into English, transformed from text to digital format, and supplemented by GIS with maps of the standard regions by which data were aggregated using morphometric parameters (volume of water in cubic kilometers in the region, in its epipelagic 0-200 m, and upper epipelagic 0-50 m water layers, occupied area in square kilometers, longitude and latitude of their centroids in decimal degrees) to increase their availability to the scientific community worldwide. The data enable the evaluation of the total plankton stock of the Russian Far Eastern seas in the North Pacific (in trillions of specimens and thousands of tons), recalculate the volumetric characteristics of density into areal characteristics (in billions of specimens per square kilometer or tons per square kilometer), and, using previously published tables on calorific value and chemical composition of zooplankton, obtain their energy characteristics. Such data are crucial for the proper management of marine resources, aquaculture development, nature conservation, and the assessment of the anthropogenic impact on nature. The presented metadata provide a detailed description of how this unique dataset was created, sources and volume of gathered information, its benefits and drawbacks, some results on the quantitative inventory of marine biological resources and assessment of waters in the North Pacific, and future prospects for the use of this type of dataset in applied and fundamental research. There are no copyright restrictions on the data; please cite this data paper when the data are used in publications.

Current distribution of two species of Chinese macaques (Macaca arctoides and Macaca thibetana) and the possible influence of climate change on future distribution

Predicting the spatial distribution of species and suitable areas under global climate change could provide a reference for species conservation and long-term management strategies. Macaca thibetana and Macaca arctoides are two endangered species of Chinese macaques. However, limited information is available on their distribution, and their habitat needs lack proper assessment due to complicated taxonomy and less research attention. In recent years, scholars widely used the maximum entropy (MaxEnt) model to predict the impact of global climate and certain environmental factors on species distribution. Therefore, we used the MaxEnt model to predict the spatiotemporal distribution of both macaque species under six climate change scenarios using occurrence and high-resolution ecological data. We identified climatic factors, elevation, and land cover that shape their distribution range and determined shifts in their habitat range. The results demonstrated that temperature range, annual precipitation, forest land cover, and temperature seasonality, including the precipitation of the driest month are the main factors affecting their distribution. Currently, M. thibetana is mainly concentrated in central, eastern, southern, and southwestern China, and M. arctoides is mainly concentrated in three provinces (Yunnan, Guangxi, and Guangdong) in southern China. The MaxEnt model predicted that the suitable habitat for both species will increase with increased greenhouse emission scenarios. We also found that with the further increase in greenhouse emissions M. thibetana is expected to migrate to western China, and M. arctoides is expected to migrate to western or eastern China. This reinterpretation of the distribution of M. thibetana and M. arctoides in China, and predicted potential suitable habitat and possible migration direction, may provide new insights into the future conservation and management of these two species.

Differences in climate-growth relationships between two tree species that co-occur in a seasonally dry tropical forest in Northeastern Brazil

Seasonally dry tropical forests are an important global climate regulator and represent one of main drivers of carbon sink dynamics. However, projections of climate change suggest future productivity losses and negative impacts on forest functioning. Understanding the interaction between climate variability and tree growth responses between species with different growth strategies represents a crucial challenge to forecast ecosystem functioning in the future. Here we used tree ring chronology to evaluate changes in growth and climate sensitivity of two tropical tree species that co-occur in a seasonally dry tropical forest in Brazil: Cedrela odorata and Ceiba glaziovii. Using Pearson correlations and linear regressions we explored how growth variability is correlated with local (precipitation, temperature) and global (ocean temperature and El Niño Southern Oscillation - ENSO) climatic factors. Tree growth was closely related with precipitation in C. odorata (r = 0.59) and C. glaziovii (0.24). Differences were found at monthly level, which C. odorata showing greater sensitivity in the beginning of rainy season. The South Atlantic Temperature was positively correlated with C. odorata, while ENSO was negatively correlated. Our results showed a dominant effect of precipitation on tree growth and suggest that are different growth strategies among species, which C. odorata being the most sensitive to drought and C. glaziovii more adapted with parenchyma in trunk. Therefore, C. odorata is probably more vulnerable to the deleterious effects of future climate change than C. glaziovii. Our findings highlight the importance of understanding the climate sensitivity of different seasonally dry tropical forest species, which is critical to predicting carbon dynamics in tropical regions. These also reveal that differences in sensitivity must be considered when prioritizing conservation measures for seasonally dry tropical forests.

Қазақстан Республикасында халықты сапалы ауыз сумен қамтамасыз етудің құқықтық аспектілері

The proposed article examines the legal issues of providing the population with high-quality drinking water.The importance of providing the population with drinking water and the need for legal influence on it is also considered. Today, there is a problem of water shortage all over the world due to changes in the global climate or other factors. From the point of view of natural law, humanity has equal rights to quality water and no one should be given an advantage over others. After all, the health of the population and social status directly depend on high-quality drinking water. Undoubtedly, water not only satisfies the natural needs of a person, but also affects his health.the main goal of the city is the theoretical legal study of providing the population with high-quality drinking water, bringing proposals for improving domestic legislation and practice. The main part of the article analyzes the historical legal aspects of providing the population with high-quality drinking water, presenting mechanisms for improvement in the conditions of the Republic of Kazakhstan, taking into account the current regulatory situation. In the final part, the authors propose effective ways to improve the quality of drinking water supply to the population in the conditions of the Republic of Kazakhstan.

Survey and identification of coinfecting Botryosphaeriales causing stem canker diseases of Eucalyptus camaldulensis in Ethiopia

Eucalyptus is the most widely planted forest tree species in the world. In Ethiopia, pathogenic fungi pose an increasing threat to Eucalyptus species. Due to limited research, there is insufficient information on the associated diseases and pathogens. This study investigated Eucalyptus diseases, the extent of their damage, and the causal fungal pathogens. A Eucalyptus disease survey was conducted in the Eucalyptus forestry areas of Ethiopia during the growth years 2019/20 and 2020/21. Disease assessment and sampling were carried out in eighteen plantations at nine locations. E. camaldulensis was the most dominant species planted in the surveyed areas. The field study shows a high incidence and severity of canker diseases. Diseased stem and branch samples were collected, cultured on malt extract agar media and studied. The results of morphological and ITS sequence analysis confirmed that the fungal species Neofusicoccum parvum, Lasiodiplodia theobromae, and Aplosporella hesperidica caused the observed canker symptoms. This is the first report of Lasiodiplodia theobromae and Aplosporella hesperidica causing diseases in Eucalyptus plants in Ethiopia. Changes in global climate and environmental factors, such as altitude, are believed to have a strong impact on the susceptibility of Eucalyptus plants to diseases. Strict quarantine practices and continuous monitoring of pathogenic and endophytic fungal species associated with Eucalyptus trees are issues to be prioritized to effectively control and manage the disease.

Climate-informed monthly runoff prediction model using machine learning and feature importance analysis

Accurate runoff prediction can provide a reliable decision-making basis for flood and drought disaster prevention and scientific allocation of water resources. Selecting appropriate predictors is an effective way to improve the accuracy of runoff prediction. However, the runoff process is influenced by numerous local and global hydrometeorological factors, and there is still no universal approach about the selection of suitable predictors from these factors. To address this problem, we proposed a runoff prediction model by combining machine learning (ML) and feature importance analysis (FIA-ML). Specifically, take the monthly runoff prediction of Yingluoxia, China as an example, the FIA-ML model uses mutual information (MI) and feature importance ranking method based on random forest (RF) to screen suitable predictors, from 130 global climate factors and several local hydrometeorological information, as the input of ML models, namely the hybrid kernel support vector machine (HKSVM), extreme learning machine (ELM), generalized regression neural network (GRNN), and multiple linear regression (MLR). An improved particle swarm optimization (IPSO) is used to estimate model parameters of ML. The results indicated that the performance of the FIA-ML is better than widely-used long short-term memory neural network (LSTM) and seasonal autoregressive integrated moving average (SARIMA). Particularly, the Nash-Sutcliffe Efficiency coefficients of the FIA-ML models with HKSVM and ELM were both greater than 0.9. More importantly, the FIA-ML models can explicitly explain which physical factors have significant impacts on runoff, thus strengthening the physical meaning of the runoff prediction model.

A combined microbial and biogeochemical dataset from high-latitude ecosystems with respect to methane cycle

High latitudes are experiencing intense ecosystem changes with climate warming. The underlying methane (CH4) cycling dynamics remain unresolved, despite its crucial climatic feedback. Atmospheric CH4 emissions are heterogeneous, resulting from local geochemical drivers, global climatic factors, and microbial production/consumption balance. Holistic studies are mandatory to capture CH4 cycling complexity. Here, we report a large set of integrated microbial and biogeochemical data from 387 samples, using a concerted sampling strategy and experimental protocols. The study followed international standards to ensure inter-comparisons of data amongst three high-latitude regions: Alaska, Siberia, and Patagonia. The dataset encompasses different representative environmental features (e.g. lake, wetland, tundra, forest soil) of these high-latitude sites and their respective heterogeneity (e.g. characteristic microtopographic patterns). The data included physicochemical parameters, greenhouse gas concentrations and emissions, organic matter characterization, trace elements and nutrients, isotopes, microbial quantification and composition. This dataset addresses the need for a robust physicochemical framework to conduct and contextualize future research on the interactions between climate change, biogeochemical cycles and microbial communities at high-latitudes.

Co-effects of global climatic dynamics and local climatic factors on scrub typhus in mainland China based on a nine-year time-frequency analysis

BackgroundScrub Typhus (ST) is a rickettsial disease caused by Orientia tsutsugamushi. The number of ST cases has been increasing in China during the past decades, which attracts great concerns of the public health. MethodsWe obtained monthly documented ST cases greater than 54 cases in 434 counties of China during 2012–2020. Spatiotemporal wavelet analysis was conducted to identify the ST clusters with similar pattern of the temporal variation and explore the association between ST variation and El Niño and La Niña events. Wavelet coherency analysis and partial wavelet coherency analysis was employed to further explore the co-effects of global and local climatic factors on ST. ResultsWavelet cluster analysis detected seven clusters in China, three of which are mainly distributed in Eastern China, while the other four clusters are located in the Southern China. Among the seven clusters, summer and autumn-winter peak of ST are the two main outbreak periods; while stable and fluctuated periodic feature of ST series was found at 12-month and 4-(or 6-) month according to the wavelet power spectra. Similarly, the three-character bands were also found in the associations between ST and El Niño and La Niña events, among which the 12-month period band showed weakest climate-ST association and the other two bands owned stronger association, indicating that the global climate dynamics may have short-term effects on the ST variations. Meanwhile, 12-month period band with strong association was found between the four local climatic factors (precipitation, pressure, relative humidity and temperature) and the ST variations. Further, partial wavelet coherency analysis suggested that global climatic dynamics dominate annual ST variations, while local climatic factors dominate the small periods. ConclusionThe ST variations are not directly attributable to the change in large-scale climate. The existence of these plausible climatic determinants stimulates the interests for more insights into the epidemiology of ST, which is important for devising prevention and early warning strategies.

Mercury deposition in the western tropical South Atlantic during the last 70 ka

Mercury is released via natural and anthropogenic sources. Atmospheric deposition via dry and wet deposition is the main source of mercury to the continents and oceans. In the oceans, organic matter is the primary driver of mercury accumulation in marine sediments. Previous studies reported that mercury is sensitive to past climate changes and that global and regional climatic factors can control its environmental dynamics. Here, we used sediment core M125–95-3 collected at the western tropical South Atlantic to investigate mercury deposition and accumulation changes in the marine realm over the last 70 ka. Our records show higher concentration during the glacial period than in the interglacial period due to increased atmospheric dust. On millennial-scale events, the increased residence time of North Atlantic Deep Water enhanced the regenerative scavenging of mercury, which reduced mercury concentration in M125–95-3 core. In addition, the dilution effect might have reduced the mercury concentration further during Heinrich stadials due to increased terrigenous input via the São Francisco River. Altogether, the results suggest a strong influence of deep ocean circulation on the deposition and accumulation of mercury in marine sediments in the western tropical South Atlantic on millennial timescales, highlighting long-term oceanic processes that act on the geochemical cycle of mercury.

Oligocene moisture variations as evidenced by an aeolian dust sequence in Inner Mongolia, China

The aridification of Central Asia since the Eocene has widespread evidence, but climate-controlled environmental reorganizations during the Oligocene remain ambiguous. We employed environmental magnetic, mineralogical and geochemical methods on a latest Eocene to late Oligocene terrestrial sequence in Inner Mongolia, China, to examine how global climatic trends and regional factors influenced the evolution of moisture and weathering in the region. Highlighting the climatic influence, our weathering and rainfall proxy data document the drawdown of atmospheric CO2 and global cooling during the early Oligocene semi-arid phase, which culminated in the Early Oligocene Aridification Event at 31 Ma. Moreover, for the first time in the terrestrial eastern Central Asian setting, we provide geochemical and geophysical evidence for a second major Oligocene aridification event nearly synchronous to the mid-Oligocene Glacial Maximum at around 28 Ma. These aridification events were interrupted by periods of increased rainfall and weathering and can be associated with the terminations of glacial events seen in marine oxygen isotope records.

Multi-proxy records of paleoclimatic changes in sediment core ST2 from the southern Zhejiang-Fujian muddy coastal area since 1650 yr BP

Sediment core ‘ST2’ collected from southern Zhejiang-Fujian muddy coastal area (ZFMA) was analyzed for grain size, bulk elemental composition (TOC and TN), stable carbon isotopes (δ13C), and lignin-derived phenols. The C/N ratios (6.2–10.1) and δ13C values (−21.7‰ to −23.0‰) demonstrated the predominance of marine organic matter. This was supported by a three end-member mixing model generated based on N/C ratio, δ13C, and Ʌ (total lignin in mg/100 mg of TOC). The results showed that marine and soil-derived organic matter accounted for 68.0% and 29.7%, respectively, of the total organic matter. The syringyl/vanillyl (S/V; 0.32 to 1.07) and cinnamyl/vanillyl (C/V; 0.13 to 0.91) ratios, together with the estimated range of lignin phenol vegetation index (LPVI) from 22.39 to 1451.91, indicated the predominance of non-woody angiosperms. The high vanillic acid/vanillin and syringic acid/syringaldehyde ratios suggested that the sediments were degraded prior to deposition. Our results showed that the variation of soil-derived organic matter along the core was affected by the East Asian monsoons, suggesting an anti-phase relationship between East Asian Winter Monsoon and East Asian Summer Monsoon. On the other hand, the temperature variations affected the abundance and type of vegetation. In addition, the variation of soil-derived organic matter showed remarkable consistency with other climate factors, such as solar irradiance, El Niño Southern Oscillation, North Atlantic Oscillation and North Atlantic ice drift. Meanwhile, the coherency relationship between the soil-derived organic matter and paleotyphoon activity indicates a possible linkage with paleotyphoon activity. Thus, the southern ZFMA was affected by both regional and global climatic factors, as well as extreme events-typhoon activity.

Peat palaeorecords from the arid Caspian Lowland in Russia: Environmental and anthropogenic effects during the second half of the Holocene

The current study presents new palaeoecological records from arid areas in the western sector of the Caspian Lowland, covering the second half of the Holocene . Environmental alterations, driven by global climatic factors and regional features initiated by the Caspian Sea, were identified based on palynological and sedimentological changes in two mires . The study revealed that the wetlands in the south and northwest of the Caspian Lowland have different origins and sources of water supply because they are associated with the priority influence of the Caspian Sea (i.e. Arkida mire) or the dynamics of winter-cyclonic precipitation (i.e. Zelmen mire). Therefore, the humidification episodes in the peatlands under consideration were rarely synchronous. In the south of the Caspian Lowland adjacent to the Caucasus, the climate was milder, steppe vegetation predominated, and the most favourable intervals were at about 4.1–3.8, 3.4–2.8, 2.3–2.9 and after 1.5 cal ka BP. Apparently, the moisturising influence of the Caspian Sea was decisive there, even during the strengthening of the high-pressure zone in Siberia , resulting in a decreased role of westerlies and dryness in other regions. The northeast of the Caspian Lowland was distinguished by longer arid episodes and a more significant contribution of semi-desert vegetation. An increase in moisture and steppe predominance detected there at intervals of 6.7, 3.8, 2.8–2.4, and several shorter ones after 1.4 cal ka BP is associated with warm and humid winters that coincided with a weak Siberian High and North Atlantic warming combined with Caspian transgression. Wetlands in arid areas were vulnerable to intensive human activity over thousands of years and were involved in year-round grazing cycles, even during dry periods. Peculiarities of paleoecological records reflect the burning and forced grazing on the mire under aridification , evident signs of overgrazing, and the use of swamp herbs for building purposes. • Holocene moisture in the arid Caspian lowland was influenced by the Caspian Sea and westerlies. • Influence in the Caspian transgression was decisive even in the strengthening of the Siberian High. • Peat records reflect different episodes of aridification in the south and northwest. • Wetlands in arid areas were used by human activity in the past.

Climate-growth relations of congeneric tree species vary across a tropical vegetation gradient in Brazil

Seasonally dry tropical forests are an important global climatic regulator, a main driver of the global carbon sink dynamics and are predicted to suffer future reductions in their productivity due to climate change. Yet, little is known about how interannual climate variability affects tree growth and how climate-growth responses vary across rainfall gradients in these forests. Here we evaluate changes in climate sensitivity of tree growth along an environmental gradient of seasonally dry tropical vegetation types (evergreen forest – savannah – dry forest) in Northeastern Brazil, using congeneric species of two common neotropical genera: Aspidosperma and Handroanthus. We built tree-ring width chronologies for each species × forest type combinations and explored how growth variability correlated with local (precipitation, temperature) and global (the El Niño Southern Oscillation - ENSO) climatic factors. We also assessed how growth sensitivity to climate and the presence of growth deviations varied along the gradient. Precipitation stimulates tree growth and was the main growth-influencing factor across vegetation types. Trees in the dry forest site showed highest growth sensitivity to interannual variation in precipitation. Temperature and ENSO phenomena correlated negatively with growth and sensitivity to both climatic factors were similar across sites. Negative growth deviations were present and found mostly in the dry-forest species. Our results reveal a dominant effect of precipitation on tree growth in seasonally dry tropical forests and suggest that along the gradient, dry forests are the most sensitivity to drought. These forests may therefore be the most vulnerable to the deleterious effects of future climatic changes. These results highlight the importance of understanding the climatic sensitivity of different tropical forests. This understanding is key to predict the carbon dynamics in tropical regions, and sensitivity differences should be considered when prioritizing conservation measures of seasonally dry topical forests.

Ramification of Global and Local Climatic Variability on Resurgent Cases of Dengue in Delhi, India

It has become evident that the global climate is changing rapidly over the past few decades. The variation and change in the global climatic factors have a notable impact on the local climate of a region. The changing climate is widely regarded as one of the most serious global health threats of the 21st century. Among various kinds of diseases, the most vulnerable to these changes are vector-borne diseases. In the Indian context, particularly Delhi city is the most vulnerable to dengue, a kind of vector-borne disease having its highest impact. We sought to identify and explore the correlation and influence of the global climatic phenomena and local climatic factors with the reported number of dengue cases in Delhi. The temporal expansions of reported dengue cases in Delhi have a variation from its first major outbreak in the city during the year 1996 to 2015. A statistical tool like Pearson Product Moment Correlation (PPMC) is used in this study to establish the interrelationship and the level of impact and local climatic variation on dengue. An exceptional negative correlation value of r = -0.82 between the monsoon index and the dengue incidences was reported during the positive years and also maintains a very high positive correlation with other global climatic indices. The study here finds that there is a strong correlation of climatic variation which further influences the epidemiology of dengue in Delhi.