Annual Temperature Research Articles

Weather-related changes in the dehydration of respiratory droplets on surfaces bolster bacterial endurance

HypothesisThe study shows for the first time a fivefold difference in the survivability of the bacterium Pseudomonas Aeruginosa (PA) in a realistic respiratory fluid droplet on fomites undergoing drying at different environmental conditions. For instance, in 2023, the annual average outdoor relative humidity (RH) and temperature in London (UK) is 71 % and 11 °C, whereas in New Delhi (India), it is 45 % and 26 °C, showing that disease spread from fomites could have a demographic dependence. Respiratory fluid droplet ejections containing pathogens on inanimate surfaces are crucial in disease spread, especially in nosocomial settings. However, the interplay between evaporation dynamics, internal fluid flow and precipitation and their collective influence on the distribution and survivability of pathogens at different environmental conditions are less known. ExperimentsShadowgraphy imaging is employed to study evaporation, and optical microscopy imaging is used for precipitation dynamics. Micro-particle image velocimetry (MicroPIV) measurements reveal the internal flow dynamics. Confocal imaging of fluorescently labelled PA elucidates the bacterial distribution within the deposits. FindingsThe study finds that the evaporation rate is drastically impeded during drying at elevated solutal concentrations, particularly at high RH and low temperature conditions. MicroPIV shows reduced internal flow under high RH and low temperature (low evaporation rate) conditions. Evaporation rate influences crystal growth, with delayed efflorescence and extending crystallization times. PA forms denser peripheral arrangements under high evaporation rates and shows a fivefold increase in survivability under low evaporation rates. These findings highlight the critical impact of environmental conditions on pathogen persistence and disease spread from inanimate surfaces.

Accelerated aging tests of large-diameter GFRP bars in alkaline environment

Fiber reinforced polymer (FRP) bars have become increasingly popular, while the studies on durability of FRP bars are primarily on small-diameter FRP bars. This study investigated the tensile strength retention in glass FRP (GFRP) bars of different diameters (13 mm and 25 mm) after immersion in an alkaline solution (pH=12.6) at various temperatures (20 °C, 40 °C and 60 °C) for 1, 2, 3, and 6 months. The results reveal that the degradation of GFRP bars was slow at 20 °C, accelerated but not pronounced at 40 °C and considerable at 60 °C. Particularly, the 13 mm diameter GFRP bars exhibited a more significant reduction in tensile strength, with a decrease of 20.12 % after 6 months, while the 25 mm diameter bars only decreased by 13.23 %. Results reveal that, importantly, degradation of GFRP bars is primarily attributed to the diffusion of the moisture and alkalis, which disrupts the bond between the fibers and the matrix, causing interface damage. Finally, based on the Arrhenius theory, it is predicted that the tensile strength retention of 13 mm and 25 mm diameter GFRP bars will be 66.4 % and 79.8 %, respectively, after 50 years of exposure at an average annual temperature of 35 °C. The important finding that the small-diameter FRP bars are more vulnerable to the alkaline exposure than larger diameter bars suggests that the current studies on durability of FRP bars are conservative to be referred in practice.

Analysis of Landscape Pattern Evolution and Impact Factors in the Mainstream Basin of the Tarim River from 1980 to 2020

The mainstream basin of the Tarim River serves as a vital ecological security barrier that prevents the merging and expansion of deserts and an important strategic corridor directly linking Qinghai and Xinjiang. With society’s development and climate change, ecological issues such as river interruption, vegetation degradation, and land desertification in the basin have notably intensified, and the ecological security is facing a critical test. Exploring the characteristics of landscape changes and their driving factors within the basin is crucial in improving the ecological environment system’s management. Based on land use data from 1980 to 2020, this study analyzed the characteristics of the spatiotemporal changes and pattern evolution of the landscape through a landscape transfer matrix and landscape pattern indices. It further revealed the impact factors of the landscape pattern through canonical correspondence analysis. The results showed that (1) in 1980–2020, the areas of desert, forest, farmland, and settlement landscapes increased, while the area of grassland landscape decreased, and the water landscape showed an “increasing–decreasing–recovery” pattern. The landscape transition types mainly included the transition from grassland to desert; mutual transitions among farmland, grassland, and forests; mutual transitions between water and grassland; and the transition from farmland to settlements. (2) The overall landscape pattern demonstrated increased fragmentation, shape complexity, and evenness with decreased aggregation. Furthermore, different landscapes exhibited distinct characteristics of landscape pattern changes; for instance, grassland landscape showed severe fragmentation, while desert landscape displayed the strongest dominance. (3) The landscape pattern was a result of the combined impact of natural and human factors, with the soil thickness (SOT), road density (ROD), annual actual evapotranspiration (AAE), population density (POD), and mean annual temperature (MAT) exhibiting significant influences. Specifically, the settlement and farmland landscapes were mainly influenced by the mean annual relative humidity (MAH), POD, GDP density (GDP), and distance to artificial water (DAW); the forest, grassland, and water landscapes were mainly influenced by the SOT, soil organic matter content (SOM), AAE, ROD, elevation (ELE), MAT, slope (SLP), and distance to natural water (DNW); and the desert landscape was mainly influenced by the DAW, DNW, SLP, AAE, SOT, SOM, and ROD. These findings can provide a scientific reference for landscape management and restoration, as well as sustainable social and economic development, in the mainstream basin of the Tarim River.

MaxEnt-Based Potential Distribution Mapping and Range Shift under Future Climatic Scenarios for an Alpine Bamboo Thamnocalamus spathiflorus in Northwestern Himalayas

Thamnocalamus spathiflorus is a shrubby woody bamboo invigorating at the alpine and sub-alpine region of the northwestern Himalayas. The present investigation was conducted to map the potential distribution of Th. spathiflorus in the western Himalayas for current and future climate scenario using Ecological Niche Modelling (ENM). In total, 125 geo-coordinates were collected for the species presence from Himachal Pradesh (HP) and Uttarakhand (UK) states of India and modelled to predict the current distribution using the Maximum Entropy (MaxEnt) model, along with 13 bioclimatic variables selected after multi-collinearity test. Model output was supported with a significant value of the Area Under the “Receiver Operating Characteristics” Curve (AUC = 0.975 ± 0.019), and other confusion matrix-derived accuracy measures. The variables, namely precipitation seasonality (Bio 15), precipitation (Prec), annual temperature range (Bio 7), and altitude (Alt) showed highest level of percentage contribution (72.2%) and permutation importance (60.9%) in predicting the habitat suitability of Th. spathiflorus. The actual (1 km2 buffer zone) and predicted estimates of species cover were ~136 km2 and ~982 km2, respectively. The predicted range was extended from Chamba (HP) in the north to Pithoragarh (UK) in southeast, which further protracted to Nepal. Furthermore, the distribution modelling under future climate change scenarios (RCP 8.5) for year 2050 and 2070 showed an eastern centroidal shift with slight decline of the species area by ~16 km2 and ~46 km2, respectively. This investigation employed the Model for Interdisciplinary Research on Climate (MIROC6)–shared socio-economics pathways (SSP245) for cross-validation purposes. The model was used to determine the habitat suitability and potential distribution of Th. spathiflorus in relation to the current distribution and RCP 8.5 future scenarios for the years 2021–2040 and 2061–2080, respectively. It showed a significant decline in the distribution area of the species between year 2030 and 2070. Overall, this is the pioneer study revealing the eco-distribution prediction modelling of this important high-altitude bamboo species.

Land use and temperature shape the beta diversity of soil nematodes across the Mollisol zone in northeast China

Understanding soil biodiversity response to land use change is crucial for predicting and preserving soil ecological functions and health under anthropogenic influence. Yet, the overall effect of land use changes and climate conditions on belowground biodiversity remains insufficiently explored at large scales. Here, we studied the effect of conversion from natural soils to agricultural soils on soil nematode diversity and community assembly across the Mollisol zone in northeast China. We found that nematode alpha diversity decreased in agricultural soils, and nematode alpha diversity did not exhibit a regular change with latitudinal variation. For beta diversity, we found that nematode community structures were significantly affected by land use change. Furthermore, climatic factors and geographic distance significantly impacted the beta diversity of soil nematodes, but not the alpha diversity. Mean annual temperature was a primary climatic determinant of soil nematode communities, while the effect of mean annual precipitation on soil nematode beta diversity was only observed in agricultural soils. Stochastic processes dominated soil nematode community assembly, but agricultural soils increased the importance of deterministic processes compared to natural soils. There is no any expected variation in soil nematode alpha diversity along the Mollisol zone. Our findings highlight the crucial role of temperature in driving soil nematode communities.

Data driven forest fire susceptibility mapping in Bangladesh

Forests are essential natural resources that serve to facilitate economic activity while also providing an essential impact on climate regulation and the carbon cycle. In the Chittagong hill tracts, forest fires significantly contribute to the eradication of forests and the depletion of biodiversity. As a result, addressing the forest fire hazard is crucial for mitigating its potential negative effects. By implementing machine learning (ML) and deep learning (DL) algorithms, the primary aim of this research is to determine which areas within the CHT are most prone to forest fires. Artificial Neural Network (ANN), Classification and Regression Trees (CART), Categorical Boosting (Catboost), Convolutional Neural Network (CNN), Deep Neural Network (DNN), Gradient Boosting Decision Tree (GBDT), Random Forest (RF), Support Vector Machine (SVM), eXtreme Gradient Boosting (XGboost) are among these algorithms. This research investigates 267 past forest fire incidents while incorporating fifteen predictive parameters for forest fires. The utmost accuracy is demonstrated by the Catboost model, which has an AUC value of 0.83. Applied models the Bandarbon and Rangamati regions of the Chittagong hill tracts have been thoroughly analyzed and discovered to be extremely and moderately vulnerable to forest fires due to their intricate physical and social characteristics. The Catboost model indicates that 67.38% of the total regions and 0.59% of the regions in Chittagoong hill tracts are classified as moderate and high susceptible zones, respectively. The results of this study present the models utilized in the present analysis exhibit a high level of effectiveness. Furthermore, the findings indicated that the NDVI and annual temperature had the most influence. The application of both ML and DL approaches in the Chittagong hill tracts for the first time resulted in models that exhibited excellent accuracy and precision, combining perfectly with the actual conditions on the ground. This study will undeniably assist the local government in implementing efficient governance and preservation strategies for the sustainable maintenance of forest resources, while enhancing the well-being of individuals living in and around the forest. Forest fire susceptibility assessment can be utilized in various locations worldwide that include significant natural and human-induced characteristics.

Impacts of Climate Change on the Distribution of Suitable Habitats and Ecological Niche for Trollius Wildflowers in Ili River Valley, Tacheng, Altay Prefecture.

Xinjiang in China is distinguished by its distinctive regional landscape and high ecological sensitivity. Trollius wildflowers represent a unique and iconic element of the mountain flower landscape in Xinjiang. However, their populations are predominantly distributed in mountainous areas, making them susceptible to climate change. Despite this, the impacts of climate change on the distribution of suitable habitats and ecological niche differentiation for Trollius wildflowers have rarely been quantified. Consequently, simulations were conducted using the R-optimized MaxEnt model to predict the suitable habitat distribution of Trollius wildflowers. This was based on the occurrence data and environmental variables for the four species of Trollius (T. altaicus, T. asiaticus, T. dschungaricus, and T. lilacinus) that exist in the study area. The simulation was conducted over a period of time, beginning with the past glacial period and extending to the present, and then to the future (2050s, 2070s, and 2090s) under multiple scenarios (SSP1-2.6, SSP3-7.0, SSP5-8.5). The simulation of suitable habitats enabled the measurement of the ecological niche breadth and differentiation. The results demonstrate that the model predictions are precisely accurate, with AUC values exceeding 0.9. Annual mean temperature (Bio1), isothermality (Bio3), and precipitation in the warmest quarter (Bio18) are the dominant climate variables, in addition to vegetation, elevation, and soil factors. The proportion of suitable habitats for Trollius wildflowers varies considerably over time, from 0.14% to 70.97%. The majority of habitat loss or gain occurs at the edges of mountains, while stable habitats are concentrated in the core of the mountains. The gravity center of suitable habitats also shifts with spatial transfer, with the shifts mainly occurring in a northeasterly-southwesterly direction. The SSP1-2.6 scenario results in the sustained maintenance of habitats, whereas the SSP3-7.0 and SSP5-8.5 scenarios present challenges to the conservation of habitats. The threshold of ecological niche breadth for Trollius wildflowers is subject to fluctuations, while the ecological niche differentiation also varies. The study aims to examine the evolution of the habitat and ecological niche of Trollius wildflowers in Xinjiang under climate change. The findings will provide theoretical support for delineating the conservation area, clarify the scope of mountain flower tourism development and protection of mountain flower resources, and promote the sustainable development of ecotourism and effective utilization of territorial space in Xinjiang.

Wpływ działalności antropogenicznej w dorzeczu górnego Dunaju na reżim temperatury wody Dunaju w Bratysławie

The man activity in the basin affects the water temperature in the increasingly higher levels (construction of water reservoirs, construction of thermal and nuclear power plants or drainage of waste water to streams). In this paper, we focused our attention on the evaluation of the impact of anthropogenic activity to increase the thermal load of the Danube River for the period 1926–2020 at the Bratislava (Slovakia) station. In the first part, the long-term trends of a series of monthly and annual water temperatures in the Danube (period 1931–2020) are identified. In the second part, the dependence of the range of daily water temperature values is analysed at the temperature of the atmosphere in Vienna. The impact of an increase in the temperature of the Danube water due to human activity was tried to identify for lower, average, and higher flows (for Danube discharge at Bratislava water gauge 1500 m3s-1, 2000 m3s-1, and 3000 m3s-1) by comparing two periods: 1932–1961, and 1991–2020. As the effect of water heating in the river stream is most noticeable during low flow (dry) periods and high air temperatures, only daily water and air temperature data from the warm months between May and September were used in the calculations. At monthly flow rates of 1500 m3s-1, the water temperature was, on average, 0.5°C higher during the period of 1991–2020 than it was during the period of 1932–1960. This growth could be attributed to human activities in the Danube basin above Bratislava (warming of water in the built tanks, the wastewater flow to the Danube flow, etc.)

How Climate Warming Influences the Phenology of Grapholita molesta (Busck, 1916) (Lepidoptera: Tortricidae) in China: Insight from Long-Term Historical Data.

Grapholita molesta (Busck, 1916), a significant pest affecting various fruits such as pears, apples, peaches, etc., is highly adaptable to changing temperatures. However, the phenological response mechanism of this pest to climate warming remains unclear. To address this issue, we collected population dynamics data of G. molesta in China over the years along with corresponding climate data. We analyzed five phenological indexes: the first, end, and peak occurrence dates of contemporary adults as well as the first and peak occurrence dates of overwintering adults in China. Results revealed an upward trend in the annual average temperature and average temperature of the four seasons in regions infested by G. molesta in eastern, northeastern, northwestern, northern, and southwestern China from 1980 to 2020. Notably, the population peak date of overwintering adults in northeastern and eastern China significantly advanced along with the first occurrence date and the population peak date of overwintering adults in northern China. Additionally, the population peak date of contemporary adults in northwestern China significantly advanced. However, the end occurrence date of contemporary adults in northern China was significantly delayed, as was the first occurrence date of overwintering adults in northwestern China. Furthermore, our study demonstrated spatial heterogeneity in the phenological response of G. molesta to climate warming across China. This study elucidates the phenological response of G. molesta to climate warming, offering valuable insights for predicting future pest infestations and informing adaptive pest management strategies in fruit tree cultivation.

Unraveling boreal forest composition and drivers across scales in eastern Siberia

The Siberian boreal forest is the largest continuous forest region on Earth and plays a crucial role in regulating global climate. However, the distribution and environmental processes behind this ecosystem are still not well understood. Here, we first develop Sentinel-2-based classified maps to show forest-type distribution in five regions along a southwest-northeast transect in eastern Siberia. Then, we constrain the environmental factors of the forest-type distribution based on a multivariate analysis of bioclimatic variables, topography, and ground-surface temperatur at the local and regional scales. Furthermore, we identify potential versus realized forest-type niches and their applicability to other sites. Our results show that mean annual temperature and mean summer and winter temperatures are the most influential predictors of forest-type distribution. Furthermore, we show that topography, specifically slope, provides an additional but smaller impact at the local scale. We find that the filling of climatic environmental niches by forest types decreases with geographic distance, but that the filling of topographic niches varies from one site to another. Our findings suggest that boreal forests in eastern Siberia are driven by current climate and topographical factors, but that there remains a portion of the variability that cannot be fully accounted for by these factors alone. While we hypothesize that this unexplained variance may be linked to legacies of the Late Glacial, further evidence is needed to substantiate this claim. Such results are crucial to understanding and predicting the response of boreal forests to ongoing climate change and rising temperatures.

Integrated nitrogen fertilizer management for improving wheat yield and the efficiency of water and nitrogen fertilizer use

Improving resource use efficiency through optimized nitrogen (N) management is the key to increasing crop productivity, but it remains unclear whether integrated N management practices could better improve wheat yield and the use of N and water. Here we investigated the effects of individual and integrated N management practices on wheat production in different soil-climatic conditions, and constructed the relationship between the soil-climate factors and N application rate on wheat yield. Results showed that individual N management practice (optimized N application rate only) reduced wheat yield by 2.4 %, increased N use efficiency (NUE) by 45 %, and decreased water use efficiency (WUE) by 2.2 %; however, integrated N management practice (integrating optimized N rate with irrigation, tillage, manure, or straw return) increased yield and NUE on average by 5.4 % and 55 % respectively, without reducing WUE. In different soil-climate conditions, individual N management practice decreased wheat yield from 1.1 % to 5.0 %; however, integrated N management practice increased yield by 8.5 %, 6.4 %, and 5.8 % in soil organic carbon (SOC) ≥ 10 g kg−1, mean annual precipitation ≤ 400 mm, and 10 °C < mean annual temperature ≤ 15 °C, respectively. Mixed-effects model showed that the integrated N management practice had a higher yield by better exploiting the yield-enhancing benefits of SOC. Facing the complex production environment of the future, applying integrated N management practice will be a key alternative for improving grain production and resource use efficiency.

Оценка частоты возникновения засухи в Файзабадском районе (Таджикистан) в зависимости от метеорологических условий

The results of the analysis of the manifestation of drought in the Faizabad region based on calculations of the standardized precipitation and evapotranspiration index (SPEI) are presented. It has been established that there is no definite pattern in the occurrence of drought, even for a long period. By comparing the number and duration of droughts in the Fayzabad district with the climatic characteristics of the Fayzabad district, a close dependence of drought on the average annual temperature and precipitation has been established.

Predicting Ocean Current Temperature Off the East Coast of America with XGBoost and Random Forest Algorithms Using Rstudio

This research investigates the comparative predictive efficacy of two leading machine learning methodologies, specifically the XGBoost and Random Forest models, in estimating ocean temperature dynamics in the TS Gulf Stream and Labrador Current regions along the east coast of North America. Using annual temperature datasets and relevant oceanographic parameters, the data is carefully processed, cleaned and sorted into training and test subsets via the RStudio Platform. The performance evaluation model is carried out using predetermined machine learning assessment criteria, including Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Mean Squared Error (MSE), and R-squared. The results show the superiority of the XGBoost model compared to Random Forest in terms of prediction accuracy and minimizing prediction errors. The XGBoost model shows lower MSE values and higher R-squared values than the Random Forest model, indicating its better capacity in explaining data variations. XGBoost consistently provides more accurate predictions and shows higher sensitivity in identifying important factors influencing ocean temperature fluctuations than Random Forest. This research significantly improves understanding and prognostic capabilities regarding ocean temperature dynamics in the TS Gulf Stream and Labrador Current regions. Empirical evidence underlines the efficacy of the XGBoost model in predicting ocean temperatures in the studied region. Continuous model evaluation and parameter refinement for both methodologies is critical to establishing standards for optimal prediction performance. The findings of this research have implications for the fields of oceanography and climate science, and offer potential pathways to comprehensively understand and mitigate the impacts of climate change on marine ecosystems.

The Influence of Climate Change on the Distribution of Hibiscus mutabilis in China: MaxEnt Model-Based Prediction.

Our study utilized 374 geographical distribution records of H. mutabilis and 19 bioclimatic factors, employing the MaxEnt model and the Geographic Information System (ArcGIS). The key environmental variables influencing the suitable distribution areas of H. mutabilis were analyzed through the comprehensive contribution rate, permutation importance, and Pearson correlation coefficient. Based on this analysis, the contemporary and future suitable distribution areas and their extents were predicted. The results indicate that the key limiting factor affecting the suitable distribution areas of H. mutabilis is the precipitation of the driest month (bio14), with secondary factors being annual precipitation (bio12), annual mean temperature (bio1), and annual temperature range (bio7). Under contemporary climate conditions, the total suitable area for H. mutabilis is approximately 2,076,600 km2, primarily concentrated in the tropical and subtropical regions of southeastern China. Under low-to-medium-emission scenarios (SSP1-2.6, SSP2-4.5), the total suitable area of H. mutabilis shows a trend of first decreasing and then increasing compared to the current scenario. In contrast, under high-emission scenarios (SSP5-8.5), it exhibits a trend of first increasing and then decreasing. The spatial pattern changes indicate that the retention rate of suitable areas for H. mutabilis ranges from 95.28% to 99.28%, with the distribution centers primarily located in Hunan and Guizhou provinces, showing an overall migration trend towards the west and north. These findings suggest that H. mutabilis possesses a certain level of adaptability to climate change. However, it is crucial to consider regional drought and sudden drought events in practical cultivation and introduction processes. The results of our study provide a scientific basis for the rational cultivation management, conservation, and utilization of germplasm resources of H. mutabilis.

Projecting the response of carbon sink potential to land use/land cover change in ecologically fragile regions

Introduction: The carbon storage service of ecosystems in ecologically fragile areas is highly sensitive to regional land use/land cover (LULC) changes. Predicting changes in regional carbon storage under different LULC scenarios is crucial for land use management decisions and exploring carbon sink potential. This study focuses on the Luan River Basin, a typical ecologically fragile area, to analyze the impact of LULC changes on carbon storage.Methods: The PLUS-InVEST model was employed to simulate LULC patterns for the year 2030 under three scenarios: natural development, cropland protection and urban development, and ecological protection. The model projected the future carbon sink potential of the basin under these scenarios.Results: From 2000 to 2020, carbon storage showed a trend of decrease followed by an increase. By 2030, compared to 2020, carbon storage is projected to increase by 16.97% under the ecological protection scenario and decrease by 22.14% under the cropland protection and urban development scenario. The increase in carbon storage was primarily due to the conversion of cropland and grassland to forestland, while the decrease was mainly associated with the conversion of forestland to grassland and cropland, and the transformation of grassland to cropland and construction land. In the potential LULC scenarios of 2030, certain regions within the basin exhibited unstable carbon sink potential, strongly influenced by LULC changes. These areas were predominantly characterized by artificially cultivated forests, shrubs, and agricultural land. Implementing appropriate forest management measures and optimizing agricultural land management practices are essential to enhance carbon sink potential in these regions. Population density, annual average temperature, and DEM (Digital Elevation Model) were the dominant factors driving the spatial variation of carbon sink potential in the Luan River Basin.Discussion: The research results provide a theoretical basis for rational planning of land use and the enhancement of carbon sink potential in ecologically fragile regions.

Interrelationships and Environmental Influences of Photosynthetic Capacity and Hydraulic Conductivity in Desert Species Populus pruinosa

An improved understanding of the mechanisms underlying plant adaptation to habitat heterogeneity can be achieved by clarifying the climate-driving factors of the hydraulic and photosynthetic traits of different populations. With a focus on Populus pruinosa Schrenk, which is the predominant tree species in the desert riparian forests of the Tarim Basin, Xinjiang, this study investigated the hydraulic and photosynthetic trait relationships and their interactions with environmental factors in 11 P. pruinosa populations using a Pearson correlation analysis, plant trait networks, a redundancy analysis, and a least squares linear regression analysis. The results showed that the degree of variation in the hydraulic traits was higher than that in the photosynthetic traits. The net photosynthetic rate (Pn) showed a significantly positive correlation with leaf-specific conductivity (Kl) and the Huber value (Hv). The Hv exhibited a significantly positive correlation with the water-use efficiency and Kl, and the branch–leaf mass ratio significantly affected the hydraulic traits. The groundwater depth (GD) in natural P. pruinosa forest habitats ranged from 3.4 to 7.9 m. With an increase in the annual average temperature, the hydraulic conductivity of the xylem significantly increased; with an increase in GD, Pn and Kl significantly decreased. The temperature annual range, temperature seasonality (standard deviation), min temperature of the coldest month, and GD were significantly correlated with the diameter and average path length of the overall trait network parameters, and these environmental factors affected the coordination of the functional traits of P. pruinosa.

Climatic and biogeographic factors show contrasted effects on continental and volcanic ISARs

Abstract Aim The study of islands biotas is fundamental to understand biodiversity patterns and process, both on evolutionary and ecological time scales. This study explores the influence of biogeographic and climatic factors on island species–area relationships (ISARs) in volcanic and continental islands, aiming to detect differences in slopes and intercepts between these island origins. Methods Data from 5049 vegetation plots on 58 Central Mediterranean Sea islands were collected from various sources. Islands were categorized as volcanic or continental based on their geological origin. area, isolation, maximum elevation, eccentricity, mean annual temperature and annual precipitation were calculated for each island. By using a moving window, we created groups of islands, and ISARs were fitted to each group using the Arrhenius power functions. Linear models and a permutation test were employed to examine how ISAR model parameters varied with the above-mentioned variables. Results While ISAR intercept values did not differ between island origins, volcanic islands showed higher ISAR slopes than continental islands. Whereas increasing island isolation and mean annual temperature increased ISAR intercepts on continental islands groups, it decreased on volcanic ones. Increasing annual precipitation decreased ISAR intercept on continental islands groups and increased on volcanic islands groups. Increasing island isolation, eccentricity and mean annual temperature increased the ISAR slope on volcanic islands groups while increasing annual precipitation decreased it. Increasing maximum elevation increased ISAR slope on continental islands groups. Main conclusions Our study provides evidence about the importance of island geological origin in determining the observed ISAR patterns. Biogeographic and climatic factors are pivotal in shaping species richness patterns on islands, exerting varying influences on both volcanic and continental islands.

Bimodalność i długoterminowe trendy wartości ekstremalnych temperatury powietrza

Histograms of air temperature with a bimodal shape are commonly observed in many regions of the world. In this study, we investigate the causes of bimodality in the histograms of daily temperature series (minimum, average, and maximum) for selected climatological stations in Slovakia. Our findings suggest that in the Central European region, the bimodal shape of air temperature histograms is mainly due to the latent heat of freezing, as the surface of snow and ice and the air are thermally coupled. The asymmetry in the air temperature histograms is due to the lower mass heat capacity of ice compared to water and air. The energy-intensive latent heat of conversion of ice to water (and vice versa) results in the more frequent occurrence of ground-layer air temperatures around the freezing point, leading to the formation of the observed local maximum. This has far-reaching implications, such as the calculation of the annual mean air temperature at climatological stations. When calculating the average air temperature, negative temperatures should be given less weight than positive temperatures. Temperatures around 0-6°C should be given higher weight. This may also explain why Arctic regions are experiencing more significant warming than equatorial regions. In the second part of this paper, we analyze the long-term trends of selected temperature indices for the climatological station at Hurbanovo (Slovakia) from 1871 to 2020. Our results indicate statistically significant changes in all temperature indices, with indices related to cold temperatures increasing more significantly than those associated with high temperatures. Finally, study examines theoretical probability distributions to estimate T-year temperatures for temperature indices at the Hurbanovo climate station in Slovakia. The analysis includes three time periods (1901–1960, 1961–2020, and 1991–2020) and reveals significant changes in temperature indices at the Hurbanovo station. The 100-year temperature of TN,min was –35.75°C in 1901–1960, –28.69°C in 1961–2020, and –26.52°C in 1991–2020. The 100-year temperature of TX,max was 39.4°C in 1901–1960 and 39.63°C in 1961–2020. TN,min showed the most significant changes, with the 100-year temperature increasing by up to 7.06°C in 1961–2020 and up to 9.23°C in 1991–2020.

Evaluation of weather and environmental factors and their association with cutaneous melanoma incidence: A national ecological study

BackgroundCutaneous melanoma (CM) is a significant contributor to skin cancer-related mortality globally and in Canada. Despite the well-established link between ultraviolet (UV) radiation exposure and skin cancer risk, there remains a gap in population-level interventions and persistent misconceptions about sun exposure and impact of environment on individual behavior. ObjectiveThe current study provides an ecological analysis using latest available data (2011-2017) to define geographic/environmental contributors to the CM landscape in Canada. MethodsUtilizing Canadian Cancer Registry (CCR) and Canadian Urban Environmental Health Research Consortium (CANUE) data, we analyzed 39,605 CM cases occurring in Canada from 2011-2017. Environmental data, including UV radiation, greenspace (NDVI), temperature, heat events, and precipitation was used to evaluate the effect of environment on CM incidence rates across Forward Sortation Area (FSA) postal codes. ResultsFSAs with increased CM incidence were associated with higher annual average temperature, snowfall, heat events, NDVI, and vitamin D-weighted UV exposure. Conversely, factors associated with decreased incidence included an increased annual highest temperature, rain precipitation, and a longer duration of heat events. LimitationsThis study is subject to ecological bias and findings should be interpreted with caution ConclusionThis study further substantiates associations between specific environmental factors and CM incidence.

Tree species distributions in the United States and Canada under climate from 20,000 years ago to year 2100

Current locations of species may not be suited to future climate, resulting in ranges that shift to higher latitudes, with potential for range expansion or contraction in extent. To identify potential shifts in distributions of 119 tree species centered in the United States and Canada, I modeled species occurrences under current climate and then predicted to past (20, 10, and 6 thousand years ago) and future climates (six projections during 2071–2100 for North American warming of 4.3 °C to 8.8 °C), with a singular focus on the climate space of tree species, or bioclimatic envelope models. Mean accuracies of withheld samples for models, based on climate of 1900 to 1990, were 0.97, with an average of 6.2 variables per model; annual temperature and temperature of the warmest quarter generally were the most important variables. Based on model predictions under past and future climate, centers of species distributions shifted an average of 565 km latitudinally since climate 20,000 years ago and 440 km to 1065 km shifts were expected in response to end-of-century climates. Overall, 64 tree species may gain more area than lose area that matches current climate space under future climate, whereas 36 species may lose potential climate space, with relative stability for 19 species. Canada and the mountainous western U.S., and National Forests in the mountainous western U.S., were likely to gain climate space appropriate for these species, particularly species of the eastern U.S. Conversely, greatest number of species were predicted to be lost from most of the eastern half of the U.S.; National Forests in the southeastern U.S., particularly in Alabama, Mississippi, and Texas, may lose 25 to 50 of these tree species. Isolation of potential dynamics for tree species already native to northern North America demonstrated that a large pool of diverse species from the southeastern U.S. was predicted to have suitable climate space in Canada and the western U.S. It may be beneficial for managers to become familiar with tree species south or east of their regions, particularly climate-tolerant pine and oak species, to determine which ones are desirable to manage for the future.