Annual Temperature Research Articles

Modeling the Current and Future Distribution of Indianthus virgatus (Roxb.) Suksathan & Borchs.: AMonotypic Plant Endemic to the Western Ghats-Sri Lanka Biodiversity Hotspot.

Species distribution modeling (SDM) is an essential tool in ecology and conservation for predicting species distributions based on species presence/absence data and environmental variables. The present study aimed to understand the distribution pattern and habitat suitability of Indianthus virgatus under current and future climate change scenarios (2050 and 2070) using MaxEnt (3.4.4) and Wallace Ecological Modeling (v2.1.2) tools. The study also intended to identify key environmental predictors of I. virgatus' distribution. Species occurrence data were collected from various sources, including herbarium (online and physical), field surveys, and online databases, yielding 105 unique locations in the Western Ghats (WG) of India and Sri Lanka. We used 19 bioclimatic variables and elevation data sourced from WorldClim for modeling. The MaxEnt and Wallace models showed excellent performance in predicting the distribution of I. virgatus, with area under the curve values of 0.958 (± 0.002) and 0.93, respectively. In MaxEnt modeling, Temperature Seasonality (bio4) was the most significant environmental parameter, followed by the Precipitation of the Coldest Quarter (bio19). In contrast, the Annual Mean Temperature (bio1), Temperature Seasonality (bio4), and Annual Precipitation (bio12) were among the key contributors in Wallace EcoMod. Both the models predicted relatively lesser areas in the species' distribution range as highly suitable habitats (HSH) in India and Sri Lanka. We found divergent trends in predicting I. virgatus distributions using MaxEnt and Wallace EcoMod, particularly for future projections. Nevertheless, both models predicted significant habitat loss under future climate change scenarios, especially under RCP85, with varying degrees of suitability across India and Sri Lanka. Overall, our findings on expected habitat loss under future climate change scenarios highlight the importance of conserving I. virgatus, which has already been declared critically endangered (CR) in Sri Lanka.

The Streamflow Response to Multi‐Day Warm Anomaly Events: Sensitivity to Future Warming and Spatiotemporal Variability by Event Magnitude

AbstractPersistent warm temperature anomalies can drive streamflow in regions where snow and glacier melt are important constituents of streamflow. However, the spatiotemporal variability of the streamflow response depends on both the magnitude of the forcing temperature anomalies and the nature of the underlying hydrological system. Here we ask: when, where, and for what magnitude of temperature anomalies will the streamflow response change most rapidly under warming? We use observed streamflow and temperature for 868 basins across Canada to quantify the streamflow response during warm temperature anomalies and how such responses vary in space, time, and by anomaly magnitude. We first identify two temporal modes of the streamflow response, one in autumn and one in spring, the relative strength of which varies by climate. We then use sinusoidal approximations of seasonal temperature cycles to characterize the sensitivity of such modes to changes in annual temperature. At individual basins, we find that relative to moderate warm events, the streamflow response to more extreme warm events is more sensitive to changes in mean annual temperatures, and this sensitivity is greatest in the coastal, southern, and central regions of Canada. Our results have implications for how the hydrological impacts of extreme events, such as heatwaves, will change in space and time under future climate change.

Assessment of Hydrometeorological Impacts of Climate Change on Water Bodies in Northern Kazakhstan

This article examines the impact of climate change on the hydrometeorological indicators of some lakes and reservoirs in the Akmola and North Kazakhstan regions. Two meteorological variables’ annual and seasonal trends at three weather stations in 1986–2023 were analyzed. The non-parametric Mann–Kendall and Sen’s slope methods were used to determine the presence of a positive or negative trend in weather data and their statistical significance. Hydrometric indicators were studied using the ArcGIS 10.8 program from 1995 to 2023. The results indicate an increasing average spring air temperature, with an annual rise of 0.08–0.09 °C. A significant trend in increasing average annual precipitation was observed in Saumalkol, with a rise of 4.7 mm per year. In contrast, no significant trends were found in the annual and seasonal precipitation data for Sergeyevka. It was also found that the area of Lake Saumalkol increased by 1.6% due to a rise in annual precipitation. In contrast, the area of Lake Kopa decreased by 6.04% because of an increase in the annual average temperature.

The species diversity and phylogenetic structure patterns of desert plant communities in the Turpan-Hami region, Xinjiang

Desert plant communities play a crucial role in enhancing desert ecosystem productivity and stability but are highly susceptible to environmental changes owing to their limited resilience and resistance to disturbances, making it essential to understand the factors influencing their diversity patterns and community structure, particularly under the threat of climate change and intensifying droughts. This study focused on the Turpan-Hami desert region, a typical desert ecosystem in which diversity patterns and community structures remain unclear. We established 101 sampling sites ranging from elevations of -134 to 2056m and recorded community information, including species composition, height, coverage, and density, using the sample plot method. The diversity patterns were analyzed using regression analysis, and the phylogenetic structure was assessed. Additionally, Canonical Correspondence Analysis, Mantel tests, and General Linear Models were used to identify the key factors affecting community structure. Our results demonstrated that the species richness and phylogenetic diversity of plant communities exhibited a monotonic increase with elevation, and the phylogenetic structure exhibited low clustering and high dispersion along the elevational gradient. The annual mean temperature emerged as the most significant factor influencing diversity patterns, with soil nutrients, such as total potassium and available phosphorus, also affecting the spatial distribution of diversity. Notably, no significant correlations were found between community phylogenetic structure and abiotic factors, highlighting the complex interactions that drive diversity in the Turpan-Hami region. This study offers valuable insights into the mechanisms shaping desert plant community diversity and is essential for biodiversity conservation efforts in fragile desert ecosystems amid climate change.

Modeling spatiotemporal distribution of yellow rust wheat pathogen using machine learning algorithms: Insights from environmental assessment

The yellow rust pathogen (Puccinia striiformis Westend) poses a significant threat to wheat production in the world, necessitating a comprehensive understanding of its spatiotemporal distribution and the influence of climatic factors. In this study, we employed an ensemble of four prominent machine learning algorithms to assess the impact of various environmental and remote sensing variables on the spread of yellow rust at a national scale. Our analysis incorporated 55 climatic parameters, including monthly temperature, precipitation, solar radiation, and wind speed. The results demonstrated that the RF algorithm yielded robust predictions, with a Receiver Operator Characteristic (ROC) of 0.916 and True Skill Statistic (TSS) of 0.748. Furthermore, the study identified key influencing variables for wheat disease modeling, such as annual precipitation, temperature seasonality, and isothermality. Projections based on the model indicate a potential decrease in disease spread by 2050 in specific regions. The findings underscore the efficacy of ensemble modeling in predicting the spatiotemporal distribution of yellow rust on a large scale, offering valuable insights for the development of robust agricultural management strategies in the face of evolving climate conditions.

Influence of climate on soil viral communities in Australia on a regional scale

AbstractViruses play a crucial role in regulating microbial communities and ecosystem functioning. However, the biogeographic patterns of viruses and their responses to climate factors remain underexplored. In this study, we performed viral size fraction metagenomes on 108 samples collected along a 2600 km transect across Australia, encompassing distinct climate conditions. A total of 14,531 viral operational taxonomic units were identified. Climate factors had a greater influence than edaphic and biotic factors on driving the alpha diversity of viral communities. The strongest relationship was observed between mean annual temperature and the diversity of viral communities. Moreover, climate factors, particularly aridity index, were the primary drivers of viral community structure. Overall, these findings underscore the pivotal role of climate factors in shaping viral communities and have implications for understanding how climate change influences soil viral ecology.

Temperature governs the community assembly of root-associated ectomycorrhizal fungi in alpine forests on the Qinghai-Tibetan Plateau

Unraveling the assembly processes of ectomycorrhizal (ECM) fungal communities in changing environments is crucial for forecasting the impacts of climate change on forests. However, the assembly processes and key drivers of root-associated ECM fungal communities in alpine coniferous forests remain poorly understood. To address this knowledge gap, we conducted sampling in 65 monodominant alpine coniferous forests, which encompass 11 plant species belonging to three genera (Abies, Pinus, and Picea) within the Pinaceae family, all located on the Qinghai-Tibetan Plateau. We employed a combination of null model and multivariate analyses to elucidate the drivers and assembly processes of ECM fungal communities. Our results revealed significant variation in the composition and diversity of root-associated ECM fungal communities among Abies, Pinus, and Picea, indicating specific preferences for ECM fungi among Pinaceae genera. Importantly, mean annual temperature (MAT) emerged as the primary driver of these variations and regulated the assembly processes within the community of root-associated ECM fungi. As MAT temperature, the α-diversity of these fungi significantly decreased, suggesting that increased temperature may reduce the species diversity of root-associated ECM fungi in alpine forests. Furthermore, stochastic processes, such as dispersal limitation and drift, became more influential as MAT increased. Conversely, the role of deterministic processes, particularly heterogeneous selection, in shaping the ECM fungal community assembly weakened with increasing MAT. This study provides novel theoretical insights into the processes of ECM fungal community assembly in alpine forests, emphasizing the pivotal role of temperature in regulating the assembly processes and compositional dynamics of root-associated ECM fungal communities in these unique environments.

No Future Growth Enhancement Expected at the Northern Edge for European Beech due to Continued Water Limitation.

With ongoing global warming, increasing water deficits promote physiological stress on forest ecosystems with negative impacts on tree growth, vitality, and survival. How individual tree species will react to increased drought stress is therefore a key research question to address for carbon accounting and the development of climate change mitigation strategies. Recent tree-ring studies have shown that trees at higher latitudes will benefit from warmer temperatures, yet this is likely highly species-dependent and less well-known for more temperate tree species. Using a unique pan-European tree-ring network of 26,430 European beech (Fagus sylvatica L.) trees from 2118 sites, we applied a linear mixed-effects modeling framework to (i) explain variation in climate-dependent growth and (ii) project growth for the near future (2021-2050) across the entire distribution of beech. We modeled the spatial pattern of radial growth responses to annually varying climate as a function of mean climate conditions (mean annual temperature, mean annual climatic water balance, and continentality). Over the calibration period (1952-2011), the model yielded high regional explanatory power (R2 = 0.38-0.72). Considering a moderate climate change scenario (CMIP6 SSP2-4.5), beech growth is projected to decrease in the future across most of its distribution range. In particular, projected growth decreases by 12%-18% (interquartile range) in northwestern Central Europe and by 11%-21% in the Mediterranean region. In contrast, climate-driven growth increases are limited to around 13% of the current occurrence, where the historical mean annual temperature was below ~6°C. More specifically, the model predicts a 3%-24% growth increase in the high-elevation clusters of the Alps and Carpathian Arc. Notably, we find little potential for future growth increases (-10 to +2%) at the poleward leading edge in southern Scandinavia. Because in this region beech growth is found to be primarily water-limited, a northward shift in its distributional range will be constrained by water availability.

Increased offspring size and reduced gestation length in an ectothermic vertebrate under a worst-case climate change scenario

As global temperatures continue to rise, understanding the impacts of warming environments has become increasingly important. Temperature is especially relevant for ectothermic organisms which depend upon consistent and predictable annual temperature cycles for reproduction and development. However, additional research is required in this area to elucidate the potential impacts of climate change on future generations. To understand how projected increases in environmental temperatures may impact reproductive outcomes within natural populations of ectothermic vertebrates, we manipulated minimum ambient temperatures during gestation in Red-sided garter snakes (Thamnophis sirtalis parietalis). Wild snakes were collected in the Interlake region of Manitoba, Canada during their spring mating season and allowed to mate in controlled conditions. For the duration of gestation, mated females were placed into one of two ambient thermal conditions: temperatures emulating those found in the species’ natural habitat or temperatures with a consistent 5 °C increase to match end-of-century climate change projections. We recorded observations for each litter and all neonates resulting from controlled mating trials. We observed no difference in litter sizes or birth rates between thermal conditions. However, we observed a significant reduction in gestation length and significant increase to neonate body mass and body condition associated with increased ambient temperatures. These results suggest that increased minimum temperatures during gestation may confer reproductive benefits for the northern populations of this species even under the most extreme current modeled warming predictions. We discuss the broader implications of this effect, including possible negative ecological outcomes.

Mycorrhizal types determined the response of yield of woody bioenergy crops to environmental factors.

Meeting the demand for energy solely through fossil fuels has posed challenges. To mitigate the risk of energy shortage, woody bioenergy crops as a renewable energy feedstock have been the subject of many researchers. Also, mycorrhizas play an important role in crop productivity and inevitably affect the biomass yield of woody bioenergy crops. Based on a global synthesis of biomass yield of woody bioenergy crops, a framework for identifying and comparing bioenergy crop biomass in response to mycorrhizal type was developed. Our results found that the biomass yield of woody bioenergy crops in descending order was ectomycorrhizas (ECM) crops (10.2 ton DM ha-1year-1) > arbuscular mycorrhizas (AM)+ECM crops (8.8 ton DM ha-1year-1) > AM crops (8.0 ton DM ha-1year-1). In addition, our analysis revealed that the climate had the strongest effect on biomass yield in AM and ECM crops, whereas geography exerted the most significant influence on biomass yield in AM+ECM crops. Furthermore, there were differences in the biomass yield response of different mycorrhizal and plant types to geographic (latitude and elevation) and climatic factors (mean annual temperature (MAT) and mean annual precipitation (MAP)). When cultivating AM crops, we can focus more on temperature conditions-warmer locations, whereas for ECM crops, selecting regions with higher precipitation levels is advantageous. This study revealed the relationship between mycorrhizae and bioenergy crops. It provides data and theoretical support to rationalize differences in different woody bioenergy crops and their different responses to global change and increased production of bioenergy crops.

Contrasting foliar nitrogen nutrition of coexisting temperate and boreal trees across a modest temperature cline

The temperate-boreal forest ecotone represents a transition zone from temperate to boreal forest where nitrogen (N) is frequently limiting tree growth, which is highly sensitive to climate change. However, the spatial patterns and potential drivers of plant N nutrition and soil N availability remain poorly understood. To address this, we conducted a field investigation along a temperate-boreal forest ecotone in northeastern China, characterized by a modest mean annual temperature gradient (∼1°C) within the range of current climate warming. Our goal was to evaluate the spatial variation in foliar N nutrition and soil N availability, and the potential driving factors for Mongolian oak (Quercus mongolica) and Dahurian larch (Larix gmelinii), the dominant trees of the local temperate and adjacent boreal forests, respectively. Our results revealed no significant spatial trend in topsoil N availability across the sampling transect. Overall, foliar N concentration was significantly higher, but foliar δ15N was lower, for Mongolian oak than Dahurian larch. More important, foliar N concentration for Mongolian oak increased significantly toward the boreal forest, driven by lower mean annual temperatures and mean annual precipitation, with no significant trend observed for Dahurian larch. Additionally, foliar Δδ15N (foliar δ15N−soil δ15N) decreased significantly for Mongolian oak as it approached the boreal forest, while it increased significantly for Dahurian larch toward the temperate forest. Furthermore, the foliar N concentration, δ15N, and Δδ15N for Dahurian larch were all higher with an increasing basal area proportion of Mongolian oak. Our findings reveal contrasting patterns of foliar N nutrition between co-occurring temperate and boreal trees across a temperate-boreal forest ecotone which experiences a modest climatic gradient. These results underscore the importance of incorporating interspecific interactions to enhance our understanding of future N cycling in southern boreal forests in the context of climate warming.

Miocene evolution of vegetation, climate, and elevation in the Wulan Basin of northeast Tibetan Plateau based on a CRACLE analysis of palynological assemblages

The uplift of the Tibetan Plateau (TP) during the Cenozoic has played a pivotal role in shaping global climate and vegetation evolution, however, understanding the uplift history of its various tectonic blocks remains complex. In this paper, we analyze palynological samples from the Miocene Xiayoushashan and Shangyoushashan formations in the Wulan Basin to explore the relationship between climate change and TP uplift. The analysis identified four distinct pollen zones: Zone I (18–15.3 Ma) characterized by Artemisia-Lycopodium-Aster-Polygonaceae; Zone II (15.3–12.7 Ma) dominated by Pinus-Picea-Aster-Artemisia; Zone III (12.7–11.7 Ma) featuring Lycopodium-Picea-Pinus-Polygonaceae; Zone IV (11.7–8.7 Ma) characterized by Picea-Chenopodiaceae-Lycopodium-Artemisia. Results indicate that the whole study interval was dominated by shrubs and grasses, interspersed with conifers and broad-leaved trees, exhibiting an altitudinally zonal pattern. Using the Coexistence Likelihood Estimation (CRACLE) method, we estimate a mean annual temperature (MAT) ranging from 6.0 to 14.7 °C and a mean annual precipitation (MAP) between 919.1 and 1612.4 mm during Miocene times. While minor climatic fluctuations occurred, the region experienced a cool-temperate and sub-humid climate significantly warmer and more humid conditions compared to the present. Based on MAT differences, the paleoelevation of the Wulan Basin during the Miocene was estimated to be c. 1655–2025 m, suggesting an uplift of c. 1275–1645 m since that time. These findings corroborate previous suggestions that the northeastern TP had not reached its current elevation prior to the Late Miocene.

Exploring the integration of InSAR data into climate‐driven creep models to assess slow‐moving landslide dynamics

AbstractThe deformation behavior of slow‐moving large landslides is often governed by rainfall characteristics. Based on observational data such as precipitation, deformation measurement, and pore water pressure measurements in the slip zone, in many cases a strong correlation between strong rainfall events, a time‐delayed increase of pore water pressures in the slip zone, and, simultaneously to this, an increase of the deformation rate of the landslide can be found. Based on such detailed data, calculation models, which couples the relation between rainfall characteristics and the development of pore water pressures in the slip zone on one hand and the deformation behavior of the slope on the other, can be developed and be used for a better understanding and a prediction of deformation behavior of such slow‐moving landslides. Climate change issues will lead to a change in rainfall frequency and magnitude and annual temperature distribution characteristics in several regions worldwide, which will also lead to changes in the deformation behavior of such large landslides. In this contribution, satellite‐based interferometric synthetic aperture radar (InSAR) data are discussed to be used as source for deformation measurements as bases for prediction models describing the rainfall‐triggered deformation behavior of slow‐moving landslides.

Spatial and temporal distribution patterns of ants (Hymenoptera: Formicidae) in Gobi Desert ecosystems, Northwest China

Ants (Hymenoptera: Formicidae) represent the most critical arthropod community in desert ecosystems, where interactions among vegetation, soil, and climate dictate ant assemblages. Nonetheless, our understanding of how various factors influence desert ant assemblages across different spatial and temporal scales remains limited. Therefore, this study aims to analyse the temporal and spatial distribution patterns of desert ants and to determine the effects of precipitation and temperature variations on ant assemblages. To achieve this, we continuously monitored the monthly dynamics of ants at 72 uniform 8m × 8m grid points in the Gobi Desert ecosystem of Northwest China from 2015 to 2020 using pitfall traps. The results indicated that Messor desertus and Cataglyphis aenescens were the dominant ant species, with significant annual and monthly variations in the number of individuals captured from 2015 to 2020. In 2020, monthly captures of M. desertus exhibited a bimodal pattern, peaking in November, whereas those of C. aenescens exhibited a unimodal pattern, peaking in June. Annual data revealed that population size was significantly positively correlated spatially at a distance of 24 meters. Semi-variance analysis and Moran’s I indicated that structural factors predominantly controlled the ant assemblages at a small scale from 2015 to 2020. Annual catches of desert ants tended to decrease with increasing annual precipitation, while an opposite trend was rising average annual temperatures. In conclusion, variations in annual and monthly precipitation and temperature influenced the temporal response patterns of desert ants, thereby altering their spatial assemblages.

Климатические изменения годового стока рек Северного Приохотоморья

The aim of this study was to assess the climatic changes in the annual river runoff of the Northern Okhotsk Sea region within the Magadan region. In the present work the analyzed series end with data for 2019. Observation series of river runoff at eight hydrological stations were used in this work. By the method of hydrological analogy, these series were brought to a multiyear period by restoring year-on-year values. Thus, the series of annual runoff for 1958–2019 were analyzed. The research method was the analysis of runoff time series for the presence of homogeneity in the mean (Student’s criterion), as well as spectral analysis. Comparison of mean long-term values of runoff layers for two periods (1958–2000 and 2001–2019) showed that the “norm” increased by 5–37%. It should be noted that these changes are not random according to the Student’s criterion with significance level of 5%. The presence of a trend in long-term water availability fluctuations is also evidenced by the time course of the dynamic mean annual runoff. Analysis of the runoff series, mean annual air temperature and total annual precipitation made it possible to conclude that annual runoff increase is caused by climatic changes, mainly by an increase in precipitation. It is possible that runoff increase is also due to the thawing of ice in the permafrost strata. But you should pay attention to the fact that with climate warming, moisture losses for evapotranspiration increase, primarily due to the growth of trees and shrubs. Moreover, this effect is more noticeable in large catchments. A 6-year cyclicity was revealed in the long-term fluctuations of annual runoff. These fluctuations are most likely a non-stationary complex Markov process. The results of this work will be useful for hydrological calculations, long-term and ultra-long-term runoff forecasts, and studying the river – sea ecosystems. Further hydrological studies should be carried out with the obligatory study of evapotranspiration in various landscape conditions.

Formation and evolution of thermokarst landslides in the Qinghai-Tibet Plateau, China

Thermokarst landslide (TL) activity in the Qinghai-Tibet Plateau (QTP) is intensifying due to climate warming-induced permafrost degradation. However, the mechanisms driving landslide formation and evolution remain poorly understood. This study investigates the spatial distribution, annual frequency, and monthly dynamics of TLs along the Qinghai-Tibet engineering corridor (QTEC), in conjunction with in-situ temperature and rainfall observations, to elucidate the interplay between warming, permafrost degradation, and landslide activity. Through the analysis of high-resolution satellite imagery and field surveys, we identified 1298 landslides along the QTEC between 2016 and 2022, with an additional 386 landslides recorded in a typical landslide-prone sub-area. In 2016, 621 new active-layer detachments (ALDs) were identified, 1.3 times the total historical record. This surge aligned with unprecedented mean annual and August temperatures. The ALDs emerged primarily between late August and early September, coinciding with maximum thaw depth. From 2016 to 2022, 97.8 % of these ALDs evolved into retrogressive thaw slumps (RTSs), identified as active landslides. Landslides typically occur in alpine meadows at moderate altitudes and on gentle northward slopes. The thick ice layer near the permafrost table serves as the material basis for ALD occurrence. Abnormally high temperature significantly increased the active layer thickness (ALT), resulting in melting of the ice layer and formation of a thawed interlayer, which was the direct causing factor for ALD. By altering the local material, micro-topography, and thermal conditions, ALD activity significantly increases RTS susceptibility. Understanding the mechanisms of ALD formation and evolution into RTS provides a theoretical foundation for infrastructure development and disaster mitigation in extreme environments.

Modernization of small-sized drying plant for searching optimal modes with thermovision control

The climatic features of the Murmansk region (low average annual temperature; insignificant number of sunny days) do not contribute to the effective use of natural methods of drying aquatic organisms and determine the use of artificial dehydration methods using appropriate equipment. The capabilities of ship fish processing complexes are limited; highly productive coastal fish processing plants are required to supply the population with fish products. The development and testing of new drying modes has been carried out using a small-sized drying unit UPOR-M2. In the course of the study, a drying unit modernization project has been developed, equipment has been selected (thermal imaging system; damper and fan control modules), the system has been modernized and a number of experiments has been conducted to determine the effectiveness of the work performed. The modernization of the drying unit has made it possible to increase the accuracy of the data obtained by 25 % (temperature), 20 % (relative humidity), 18 % (weight), to implement remote control of the processes and to ensure reliable operation of the drying system. Further research of different drying modes for aquatic organisms should include upgrading the air supply control system and improving communication equipment.

Study of the feature of the temperature regime of the Mykolaiv and region in the context of the issue of climate change

Climate change is one of the most important and acute environmental problems of our time. It includes a complex of changes, such as rising ambient temperatures, changes in precipitation patterns, rising sea levels, and more frequent extreme weather events. According to the Intergovernmental Panel on Climate Change (IPCC), the average global temperature has risen by about 1.1°C since the late nineteenth century. Projections point to a possible increase of 1.5°C by the middle of this century unless significant measures are taken to reduce greenhouse gas emissions. On the basis of the above, the paper analyzes trends in changes in atmospheric air temperature on the territory of risky agriculture in the South of Ukraine in the Mykolaiv region.The purpose of the study: to determine and substantiate the regularities of changes in the temperature regime of Mykolaiv and Mykolaiv region in the context of climate change.Research results. The values of temperature characteristics for the year and season in Mykolaiv and Mykolaiv region during 1991−2023 are analyzed. In Mykolaiv, about 60-67 days with a negative average daily air temperature and about 32 days with a negative maximum daily air temperature are recorded. The duration of the period with a negative minimum air temperature can be an average of 93 days per year: 64 in winter, 16 in spring and 14 in autumn. At the same time, on a large territory of the Mykolaiv region, autumn is warmer than spring. The average seasonal air temperature is 10.6°C, the average maximum temperature is 15.4°C, and the average minimum temperature is 6.4°C. In the Northern Black Sea region, both maximum and minimum temperatures in autumn are higher than in spring. The dynamics of changes in average annual temperatures in the city of Mykolaiv in the period from 1980 to 2023 are analyzed. A stable linear trend towards a gradual increase in average annual temperatures has been determined. The warmest year for this observation period is 2023, the coldest are 1985 and 1987. It is determined that the rate of increase in average temperature is 0.61°C for every ten years. Maximum temperatures are increasing at a rate of 0.0884°C per year and minimum temperatures are decreasing at a rate of 0.0136°C per year. Every year, the average annual temperature increases by approximately 0.021°С. The largest number of days accompanied by heat stress (up to 90%) is observed in July – August. Thus, changes in air temperature indicate a significant change in the temperature regime of the entire climate system of the region, and the consequences of climate change may be predominantly negative and will intensify in the future.

EFFECTS OF THE CLIMATE GRADIENT ONF THE WOOD DENSITY OF Cedrela odorata L. IN THE NEOTROPICAL REGION

Understanding wood properties is crucial for optimizing its technological potential, enhancing both the effectiveness of use and product quality. Among these properties, density is regarded as one of the most significant. Numerous studies have documented the relationship between wood density and climate. However, the influence of climatic factors on the density variation of native species remains largely unexplored. Cedrela odorata L., a species traditionally logged in Brazil and widely distributed across the Neotropical region, requires further analysis to understand its potential response to varying climate patterns, thereby informing its management. This study aimed to determine the relationship between the basic density of Cedrela odorata L. and the climatic conditions in the Neotropical region. A comprehensive database was compiled from published scientific literature. Statistical analyses were conducted using Generalized Linear Models (GLM), with the best models selected based on the corrected Akaike Information Criterion (AICc). The presence of spatial patterns was assessed using Moran’s Index to verify spatial autocorrelation. The study identified significant relationships between the wood density of C. odorata and variables such as mean annual temperature and annual precipitation. The findings indicate a strong interaction between the climatic variables analyzed and the basic density of Cedrela odorata L. wood, with density being more sensitive to mean annual temperature.

Thermal regime of peatlands in Western Siberia near the southern border of the permafrost

Relevance. The permafrost degradation under the effect of global warming. It determines the necessity for a predictive assessment of permafrost stability to minimize disturbances to engineering installations in the permafrost zone. Aim. To assess the stability of frozen peatlands in the southern part of the zone of insular distribution of permafrost. Objects. Soils of flat-mound and high-mound palsa mires, which preserve permafrost on the southern border of the insular permafrost zone. Methods. Measurements of the temperature of peat and mineral soil in geocryological boreholes from 0 to 10 m deep using the SAM-N automatic monitoring surveillance network; determination of surface temperature from thermal channels of MODIS satellite images from 2000 to 2022; analysis of meteorological indices and determination of air temperature trends for predictive assessment of permafrost stability; calculation of indicator values of permafrost state, such as freezing degree-days and thawing degree-days, frost index, freezing and thawing N-factors. Results. Numerous features of unstable permafrost have been observed. In particular, the mean annual temperature of the surface layer was positive in all studied boreholes (+0.8...+1.3°C), and the temperature at the depth of zero amplitudes (10 m) is close to the melting point (with the predominance of temperatures in the range of –0.2...–0.3°C). Besides, a layer of soil that does not freeze throughout the year (non-merging permafrost) was identified. The thawing degree-days and frost number values correspond to areas with unfrozen soils. Positive trends in air temperature, Earth's surface temperature, and snow depth were observed. For 2000–2022, surface air temperature increased by 0.76°C/10 years on average. The land surface temperature increased in summer by an average of 0.42°C/10 years. If the positive trend in surface air temperatures continues, frozen peatlands in the southern part of the permafrost zone will completely melt in 50–70 years.