Climatic Zones Research Articles

Analysis of informativeness of features of classification of dangerous weather events based on radar observation results

One of the crucial factors affecting the safety and regularity of state and civil aviation flights is the meteorological situation. The European territory of Russia is most characterized by dangerous meteorological phenomena associated with cumulonimbus clouds: shower, thunderstorms, hail, accompanied by high atmospheric turbulence. Currently, meteorological radar stations are an indispensable source of information about the weather situation for air transport. The criteria for the classification of meteorological phenomena used in modern radar stations are formed for each event separately and are based on knowledge only about the altitude distribution of radar reflectivity and air temperature, despite the fact that radar data assess the wind characteristics of the atmosphere. It is shown that optimization of the classification criteria for the mentioned meteorological phenomena should be realized by generalization of the criteria and their construction in accordance with the theory of statistical hypothesis distinction, as well as by additional use of information on atmospheric turbulence. Based on the analysis of radar signals reflected from the meteorological events of shower, thunderstorm, and hail, probability distributions of reflectivity and specific dissipation rate of turbulent energy were obtained. Statistical analysis of probability distribution densities was carried out for: the maximum value of reflectivity Zmax, its dependence on height H(Zmax), as well as the maximum specific dissipation rate of turbulent energy EDRmax and the value H(EDRmax). The classification criterion based on the maximum probability functional was chosen to determine the structure of classification algorithms and decision rules. At the same time under the acceptable confidence is accepted the value of the probability of correct classification not lower than 0.8. For the accepted criterion the decision thresholds are constructed and the complete matrices of classification probabilities are calculated. The results of calculations showed that the worst informativeness in the classification of dangerous meteorological events of cumulonimbus cloudiness have parameters H(Zmax), H(EDRmax). Parameters Zmax, EDRmax have greater separating ability, but even for them the confidence of classification is unacceptable. In the article to increase the confidence of classification the joint use of features in the form of multivariate probability distribution densities of information parameters was applied. The best results are achieved when three p(Zmax,H(Zmax),EDRmax) and four p(Zmax,H(Zmax),EDRmax,H(EDRmax)) features are used. In the probability matrices for these cases, the maximum and acceptable at 0.8 level of probabilities of correct classification are achieved. Thus, the expansion of the feature space due to atmospheric turbulence is justified in the problem under consideration. These results will be refined with increasing observation time and will vary for different climatic zones. In general, the decision thresholds for classifying dangerous meteorological events of cumulonimbus cloudiness should be adaptive.

The Cooling Effect of Plant Configuration on Urban Parks Green Space in Temperate Continental Climate Zones

The Cooling Effect of Plant Configuration on Urban Parks Green Space in Temperate Continental Climate Zones

Interpretable machine learning on large samples for supporting runoff estimation in ungauged basins

The distribution of flowmeter data and basin characteristic information exhibits substantial disparities, with most flow observations being recorded at a limited number of well-monitored locations. The perennial challenge of achieving reliable and robust hydrological modeling in ungauged catchments through regionalization has persisted. The increasing availability of large-scale hydrological datasets, coupled with recent advancements in machine learning techniques, offers new opportunities to explore patterns of association between basin attributes and hydrological parameters to enhance streamflow predictions. A novel parameter cross-regional transfer approach based on interpretable machine learning (XGBoost) is proposed to accurately predict runoff processes in ungauged regions by leveraging well-trained models across numerous basins within climate zones. We validate the effectiveness of this framework across 5,764 basins in a large sample dataset (Caravan), employing Nash-Sutcliffe Efficiency (NSE), RMSE and bias to assess performance. And a comparison is made with deep transfer learning based on LSTM and Transformer. Results indicate that the proposed method achieves NSE values exceeding 0.2 for 75 % of the ungauged basins, demonstrating superior performance and more stable accuracy compared to pure deep learning models, owing to its incorporation of physical constraints. Furthermore, the response of parameters to basin attributes within different climatic zones in the large-sample context is elucidated through SHAP values, enriching the understanding of hydrological features through data-driven inverse inference. These findings underscore the capability of interpretable machine learning to leverage hydro-physical regularities extracted from abundant basin features, thereby enhancing the accuracy of runoff predictions in ungauged regions.

Bio-curvilinear shading device for cooling load reduction in office buildings assessed by a novel energy simulation framework

Excessive heat accumulation is one of the main challenges in office buildings with curtain wall systems. This challenge requires a staggering amount of cooling energy, especially in desert and temperate climate zones. Hence, an effective and practical shading device is necessary to address this issue using a bio-inspired strategy to reduce cooling energy consumption and enhance sustainability. This study uses a Bio-Curvilinear Shading Device (Bio-CSD) to improve cooling energy efficiency, cost-effectiveness and CO2 reduction in the desert and temperate climate zones in Iraq. To alleviate overheating issues, we designed a Bio-CSD and a modified Bio-Curvilinear Shading Device (mBio-CSD) from a cactus, namely the Ogonchu plant (Pilosocereus chrysostele). Fifty-one scenarios were investigated to examine the prevalence of three distinct office building typologies: linear [T1], concentric [T2], and courtyard [T3]. The Bio-CSD and the mBio-CSD were simulated using a novel energy simulation framework for curvilinear shading devices using IDA Indoor Climate and Energy (ICE) software v4.8. Our findings revealed that the Bio-CSD outperforms a Rectilinear Shading Device (RSD) under identical conditions with the same surface area. The Bio-CSD allows maximum cooling energy savings of 31 %, 24 %, and 22 % and 23 %, 19 %, and 16 % for the three office building typologies (T1, T2 and T3) in temperate and desert climate zones, respectively. Our Bio-CSD can be a cost-effective and eco-friendly solution to mitigate overheating issues while ensuring more natural light penetration during winter, with reduced material use and lower costs.

Population genetic structure of Culex tritaeniorhynchus in different types of climatic zones in China

BackgroundCulex tritaeniorhynchus is widely distributed in China, from Hainan Island in the south to Heilongjiang in the north, covering tropical, subtropical, and temperate climate zones. Culex tritaeniorhynchus carries 19 types of arboviruses. It is the main vector of the Japanese encephalitis virus (JEV), posing a serious threat to human health. Understanding the effects of environmental factors on Culex tritaeniorhynchus can provide important insights into its population structure or isolation patterns, which is currently unclear.ResultsIn total, 138 COI haplotypes were detected in the 552 amplified sequences, and the haplotype diversity (Hd) value increased from temperate (0.534) to tropical (0.979) regions. The haplotype phylogeny analysis revealed that the haplotypes were divided into two high-support evolutionary branches. Temperate populations were predominantly distributed in evolutionary branch II, showing some genetic isolation from tropical/subtropical populations and less gene flow between groups. The neutral test results of HNQH (Qionghai) and HNHK(Haikou) populations were negative (P < 0.05), indicating many low-frequency mutations in the populations and that the populations might be in the process of expansion. Moreover, Wolbachia infection was detected only in SDJN (Jining) (2.24%), and all Wolbachia genotypes belonged to supergroup B. To understand the influence of environmental factors on mosquito-borne viruses, we examined the prevalence of Culex tritaeniorhynchus infection in three ecological environments in Shandong Province. We discovered that the incidence of JEV infection was notably greater in Culex tritaeniorhynchus from lotus ponds compared to those from irrigation canal regions. In this study, the overall JEV infection rate was 15.27 per 1000, suggesting the current risk of Japanese encephalitis outbreaks in Shandong Province.ConclusionsTropical and subtropical populations of Culex tritaeniorhynchus showed higher genetic diversity and those climatic conditions provide great advantages for the establishment and expansion of Culex tritaeniorhynchus. There are differences in JEV infection rates in wild populations of Culex tritaeniorhynchus under different ecological conditions. Our results suggest a complex interplay of genetic differentiation, population structure, and environmental factors in shaping the dynamics of Culex tritaeniorhynchus. The low prevalence of Wolbachia in wild populations may reflect the recent presence of Wolbachia invasion in Culex tritaeniorhynchus.

Limited drought tolerance in the neotropical seasonally dry forest plants impairs future species richness.

Neotropical seasonal dry forest (NSDF) is one of the most threatened ecosystems according to global climate change predictions. Nonetheless, few studies have evaluated the global climate change impacts on diversity patterns of NSDF plants. The lack of whole biome-scale approaches restricts our understanding of global climate change consequences in the high beta-diverse NSDF. We analysed the impact of global climate change on species distribution ranges, species richness, and assemblage composition (beta diversity) for 1,178 NSDF species. We used five representative plant families (in terms of abundance, dominance, and endemism) within the NSDF: Cactaceae, Capparaceae, Fabaceae, Malvaceae, and Zygophyllaceae. We reconstructed potential species distributions in the present and future (2040-2080), considering an intermediate Shared Socioeconomic Pathway and two dispersal ability assumptions on the taxa. Using a resource use scores index, we related climate-induced range contractions with species' water stress tolerance. Even under a favourable dispersal scenario, species distribution and richness showed future significant declines across those sites where mean temperature and precipitation seasonality are expected to increase. Further, changes in species range distribution in the future correlated positively with potential use of resources in Fabaceae. Results suggest that biotic heterogenization will likely be the short-term outcome at biome scale under dispersal limitations. Nonetheless, by 2080, the prevailing effect under both dispersal assumptions will be homogenization, even within floristic nuclei. This information is critical for further defining new areas worth protecting and future planning of mitigation actions for both species and the whole biome.

Droughts and heatwaves in the West African monsoon system

AbstractHeatwaves and droughts increasingly impact public health and societal system in a world subject to global warming. Several studies reported these phenomena all around the world, but there is a dearth of research specifically in West Africa. This study fills that gap by comparing heatwave/heat stress and drought occurrence in three climate zones (Guinea, Sudan and Sahel) of West Africa from 1981 to 2020. The analysis focuses on the comparison of station and gridded datasets. The Cumulative Excess Heat (CumHeat) and the Universal Thermal Climate Index (UTCI) are considered for heatwaves. For drought, the Standardized Precipitation (Evapotranspiration) Index SPI (SPEI) are used at 3‐, 6‐ and 12‐month scales. Both heatwave and drought characteristics are investigated as well as their co‐occurrence (D‐HW). The investigation reveals a good correlation between station and gridded datasets for drought indices. While station data records fewer and less intense heatwave, gridded data indicates longer‐lasting heat extremes. The study also demonstrates a strong agreement between the UTCI computed from the Rayman model and ERA5‐HEAT dataset, despite timing discrepancies, especially along the Guinea coast. The Sahel region is found to endure higher heat stress levels, with increasing intensity of heatwaves over time. Notably, the study uncovers an increasing frequency of compound D‐HW in all zones, especially the Sudan and Sahel zones, offering new insights into the climatic challenges faced by West Africa. These findings emphasize the critical need for improved planning and early warning systems (EWS) to mitigate the impacts of these climate extremes ecosystems and human health.

A Systematic Review of the Most Recent Concepts in Kinetic Shading Systems with a Focus on Biomimetics: A Motion/Deformation Analysis

In the context of sustainability and ambitious goals for reducing CO2 emissions, modifying transparency in architecture becomes a crucial tool for managing energy flow into buildings. Kinetic shading systems (KSSs) regulate light and heat entry into a room, thereby reducing energy consumption and CO2 emissions and improving daylight comfort. Recent advancements in KSSs have led to a significant increase in published papers since early 2022. This paper systematically reviews recent technological innovations in KSSs and presents the mechanical principles utilized in these systems. Given the kinetic/mechanical nature of all case studies examined, a categorization based on ‘type of motion and deformation’ was used, ranging from the simplest to the most complex solutions. In the context of kinetic systems, the motion category addresses the displacement (translation, rotation, or both) of rigid façade elements, while deformation describes the transformation that changes the shape of these elements. The data are presented in tabular form, including details about building type, climate zone, research type, evaluation, and before and after values. Additionally, some reviewed systems’ authors drew inspiration from nature, employing biomimetic methods to design KSSs. Despite considerable growth, these solutions still represent only 21% of all analyzed shading system cases. This topic is extensively discussed, considering tropical and nastic plant movements towards this paper’s conclusion. The PRISMA protocol was used to review, screen, select, and retrieve all cited papers. This review covers the most recent publications from 2022 to April 2024, recorded in the WoS and Scopus databases, and includes 66 papers.

Assessment of relationship between sea surface temperature (SST) changes and precipitation types in Nigeria from 2000 to 2022

This study investigated the circulation patterns associated with rainfall variations across Nigeria’s different climatic zones (2000–2022). Data was acquired from MERRA2, gridded ERSST5 provided by the NOAA, and observation data records obtained from the Climatic Research Unit (CRU). Principal Component Analysis (PCA) was employed to compare different precipitation types, while the Multinomial Logistic Regression Model was employed to examine the influence of SSTa on precipitation presenting regression coefficients with a significance level set at p < 0.05. Five distint standard precipitation index (SPI) classes: very dry, dry, normal, wet and very wet were categorised using prcipitation data. Analysis was done in R-studio and involved data preparation, model training, and evaluation, with emphasis on interpreting the coefficients to discern the impact of SST anomalies on precipitation for each specified level. The results show that TOP, AVP, LSP, and CNP varied: spatially, the northern region received low moisture budget from the Atlantic Ocean while the temporal distribution of precipitation across different climatic zones indicate high variability in precipitation across these zones. The mean SSTa in the WAf region were predominantly positive (0.5 and 1). The lowest (highest) global SST values were prevalent during the DJF (JJA) season(s) whereas, the monthly distribution of SSTa for the WAf region reveal neutral (2000–2016) and El Niño (2016–2022) episodes. The analysis of NIF values indicates a varied but generally stronger relationship between WAf SST anomalies and precipitation types compared to nino3.4 SST versus precipitation types. As a signal for prediction of seasonal and spatial distribution of precipitation across Nigeria’s different climatic zones, this outcome can support planning for food security, water and biodiversity conservation, and climate change adaptation and mitigation.

Drought and Wildfire Trends in Native Forests of South-Central Chile in the 21st Century

Over the last decades, Chile has experienced a long-term drought with significant consequences for water availability, forest productivity, and soil degradation, ultimately dramatically increasing the surface of burned area. Here, we quantify the Palmer Drought Severity Index (PDSI) to ascertain the extent of “moisture deficiency” across the central-southern region of Chile from 2000 to 2023 to assess the drought’s relationship with the frequency of wildfires focusing on the impact of native forests. Our methodology quantifies the PDSI from the burned area data using MODIS MCD64A1 satellite imagery, validated by in situ wildfire occurrence records. The findings indicate that 85.2% of fires occurred under moderate to severe drought conditions. We identified 407,561 ha showing varying degrees of degradation due to wildfires, highlighting the critical areas for targeted conservation efforts. A significant increase in both the frequency of wildfires and the extent of the affected area in native forests was observed with the intensification of drought conditions in the 21st century within mesic to humid Mediterranean climatic zones where drought explains up to 41% of the variability in the burned area (r2 = 0.41; p &lt; 0.05). This study highlights the relationship between drought conditions and wildfire frequency, showing the paramount need to adopt comprehensive wildfire mitigation management in native forests.

DISPERAL OF THE LILIACEAE REPRESENTATIVES IN RELATION TO THE STRUCTURE OF THEIR REPRODUCTIVE ORGANS

The Liliaceae family is a terminal one in the order Liliales sensu APG IV (2016) and consists of 15 genera with more than 700 species. The family’s geographical range covers most of the Northern hemisphere and extends through several natural zones, from forest tundra (Gagea species) to tropical forests (Tricyrtis imeldae Guthnick), within three continents, i. e. Eurasia, North America and Africa. Most Liliaceous genera occur both in Eurasia and North America. Representatives of Liliaceae develop coenocarpous fleshly indehiscent berries or dry dehiscent capsules. In most cases, multi-seeded berries themselves are a diaspore, whereas in the case of capsules, the seeds are normally a diaspora. The capsules play a vital role in seed dispersal. Structural adaptations of fruits allowed representatives of Liliaceae to spread into the territories that make up the modern range of the family.The aim of the study is to determine the principal patterns of fruit development for the representatives of Liliaceae with different types of dissemination. The study is based on the investigation of morphological and anatomical structure of fruits which is related to geography, ecology and biology of the Liliaceae taxa dissemination.The study has revealed that the wind is the most typical and widespread agent of dissemination for the investigated representatives of Liliaceae. The specialized capsules responsible for anemochory, i.e. auto-anemochory and anemochionochory (mainly in representatives of the ground cover of deciduous forests in temperate and subtropical climatic zones of the Holarctic Kingdom), are characteristic of representatives of the Lilioideae subfamily. Unlike the capsules supporting the anemochory, which actively participate in dissemination, the primary function of capsules of baromyrmecochorous representatives of Liliaceae is seed production rather than their dispersal, which is reflected in the anatomical structure of the capsules, with numerous intercellular spaces in the pericarp and almost complete lack of its lignification. The endozoochory of fleshly berries of Liliaceae is effective for dispersal by long-distance transport, primarily by birds. Supposedly, the ornitochory prevents dispersal among a large number of ecosystems, which is echoed in the ranges of Clintonia, Prosartes and Streptopus genera, representatives of the ground cover of coniferous and broadleaf forests of the Holarctic Kingdom.

Pursuit and escape drive fine-scale movement variation during migration in a temperate alpine ungulate

Climate change reduces snowpack, advances snowmelt phenology, drives summer warming, alters growing season precipitation regimes, and consequently modifies vegetation phenology in mountain systems. Elevational migrants track spatial variation in seasonal plant growth by moving between ranges at different elevations during spring, so climate-driven vegetation change may disrupt historic benefits of migration. Elevational migrants can furthermore cope with short-term environmental variability by undertaking brief vertical movements to refugia when sudden adverse conditions arise. We uncover drivers of fine-scale vertical movement variation during upland migration in an endangered alpine specialist, Sierra Nevada bighorn sheep (Ovis canadensis sierrae) using a 20-year study of GPS collar data collected from 311 unique individuals. We used integrated step-selection analysis to determine factors that promote vertical movements and drive selection of destinations following vertical movements. Our results reveal that relatively high temperatures consistently drive uphill movements, while precipitation likely drives downhill movements. Furthermore, bighorn select destinations at their peak annual biomass and maximal time since snowmelt. These results indicate that although Sierra Nevada bighorn sheep seek out foraging opportunities related to landscape phenology, they compensate for short-term environmental stressors by undertaking brief up- and downslope vertical movements. Migrants may therefore be impacted by future warming and increased storm frequency or intensity, with shifts in annual migration timing, and fine-scale vertical movement responses to environmental variability.

Evaluation of static and dynamic PV-Integrated shading systems for office spaces in Australia

The paper summarizes a comprehensive analysis to determine the energy and cost benefits of static and dynamic photovoltaic (PV)-integrated shading devices when applied to windows of office spaces located in different climate zones across Australia. The evaluated dynamic shading systems consist of rotating overhangs placed above the windows and operated to minimize the annual energy demands of office spaces. For the first time, the study determines through optimization-based controls the best angle settings for the rotating overhangs on hourly, daily, or monthly basis to minimize the energy consumption of office spaces in Australia. The analysis results indicate that both optimally designed static and optimally operated dynamic PV-integrated overhangs have substantial potential to reduce the annual energy needs of office spaces for all Australian climates with annual energy savings ranging from 45% to over 100% depending on the building orientation, window size, glazing type, and overhang depth. This high energy benefits are attributed to the multi-function capability of the PV-integrated shading systems to minimize cooling and space thermal loads while maximizing on-site electricity generation. Unlike the case of static shading devices, it is found that dynamic PV-integrated overhangs allow office spaces to reach net-zero energy operation for certain climate zones in Australia.

Detection of functional diversity gradients and their geoclimatic filters is sensitive to data types (occurrence vs. abundance) and spatial scales (sites vs. regions)

Functional diversity (FD) reflects within- and between-site variation of species traits (α- and β-FD, respectively). Understanding how much data types (occurrence-based vs. abundance-weighted) and spatial scales (sites vs. regions) change FD and ultimately interfere with the detection of underlying geoclimatic filters is still debated. To contribute to this debate, we explored the occurrence of 1690 species in 690 sites, abundances of 1198 species in 343 sites, and seven functional traits of the Atlantic Forest woody flora in South America. All FD indices were sensitive and dependent on the data type at both scales, with occurrence particularly increasing α richness and dispersion (occurrence > abundance in 80% of the sites) while abundance increased β total, β replacement, and α evenness (abundance > occurrence in 60% of the sites). Furthermore, detecting the effect of geoclimatic filters depended on the data type and was scale-dependent. At the site scale, precipitation seasonality and soil depth had weak effects on α- and β-FD (max. R2 = 0.11). However, regional-scale patterns of α richness, dispersion, and evenness strongly mirrored the variation in precipitation seasonality, soil depth, forest stability over the last 120 kyr, and cation exchange capacity (correlations > 0.80), suggesting that geoclimatic filters manifest stronger effects at the regional scale. Also, the role of edaphic gradients expands the idea of biogeographical filters beyond climate. Our findings caution functional biogeographic studies to consider the effect of data type and spatial scale before designing and reaching ecological conclusions about the complex nature of FD.

Effectiveness of artificial reefs in enhancing phytoplankton community dynamics: A meta-analysis

Artificial reefs (ARs) are widespread globally and play a positive role in enhancing fish communities and restoring habitat. However, the effect of ARs on phytoplankton, which are fundamental to the marine food chain, remains inconclusive. Conducting a literature review and meta-analysis, this study investigates how ARs influence phytoplankton community dynamics by comparing the biomass, density, and diversity of phytoplankton between ARs and natural water bodies across varying deployment durations, constituent materials, and climatic zones. The study findings suggest that, overall, ARs enhance the biomass, density, and diversity of phytoplankton communities, with no significant differences observed compared to natural water bodies. The enhancement effect of ARs on phytoplankton communities becomes progressively more pronounced with increasing deployment time, with the overall status of phytoplankton communities being optimal when artificial reefs are deployed for 5 years or longer. Concrete and stone ARs can significantly enhance the biomass and diversity of phytoplankton, respectively. The effect of ARs on phytoplankton diversity is unrelated to climatic zones. However, deploying ARs in temperate waters significantly enhances phytoplankton biomass, while in tropical waters, it significantly reduces phytoplankton density. The research findings provide practical implications for the formulation of artificial reef construction strategies tailored to the characteristics of different aquatic ecosystems, emphasizing the need for long-term deployment and appropriate material selection. This study offers a theoretical basis for optimizing AR design and deployment to achieve maximum ecological benefits.

Applicability assessment and climate zoning of using air-side economizers for data center cooling in China

The application effect of air-side economizer is closely related to outdoor air temperature, humidity and cleanliness, leading to significant variations in different regions. In this paper the key factors affecting the applicability of air-side economizers were analyzed in terms of energy-saving potential and corrosion risk, and their assessment criteria were screened out. Then the K-mean cluster analysis was performed on zoning indicators from assessment criteria, and two zoning results were obtained, both of which could divide the country into eight climate zones. To determine a more reasonable zoning result, the consistency between available hours with different counting methods and energy-saving potential, as well as the effect of humidification energy consumption on energy-saving potential was discussed through energy consumption analysis. We conclude that the humidification method has a significant impact on the energy consumption and zoning results of the air-side economizer. When adopting isenthalpic humidification, it is more appropriate to assess the energy-saving potential of the air-side economizer by the annual available hours with DBTout ≤ 27 °C and DPTout ≤ 15 °C. Additionally, the zoning result obtained with this and pollutant concentration indicators is more reasonable. In the zoning results, Zone I is most suitable for applying air-side economizers due to its large energy-saving potential and low corrosion risk, but only includes Lhasa. However, Zone VII and Zone VIII are deemed to have high corrosion risk, resulting in higher costs for risk control in these areas, which comprise Taiyuan, Urumqi, Xi’an, Zhengzhou, Tianjin, Jinan and Shijiazhuang.

Enhancing the estimation of direct normal irradiance for six climate zones through machine learning models

The evaluation of solar radiation is essential for large-scale solar energy systems, as assessing economic feasibility early on depends on accurate solar radiation data. Accurate sensors are needed to characterize the solar resource. Due to a scarcity of solar radiation data, numerical models are commonly used to estimate solar radiation components using meteorological variables that are simple or cheap to measure. In recent years, the use of machine learning (ML) algorithms has gained significant popularity in the estimation of solar radiation components. In this study it is proposed a post-processing approach using the separation model outcomes as input variables to estimate the diffuse fraction. Three ML models are employed (XGBoost, Random Forest, and Multilayer Perceptron) to boost the accuracy in terms of three statistical indicators: nRMSE, nMBE, and R2. The employed technique takes a distinctive approach by using reference stations to train the machine learning models and, afterward, make the assessment at the site under study. The results show an improvement in terms of precision of individual separation model outcomes. Thus, the proposed methodology may serve as a reliable approach for estimating solar radiation components in cases where historical data for a specific place of interest is not accessible.

Tropical and montane Apis cerana show distinct dance-distance calibration curves.

Social bees have evolved sophisticated communication systems to recruit nestmates to newly found food sources. As foraging ranges can vary from a few hundred meters to several kilometers depending on the environment or season, populations of social bee species living in different climate zones likely show specific adaptations in their recruitment communication. Accordingly, studies in the western honey bee, Apis mellifera, demonstrated that temperate populations exhibit shallower dance-calibration curves compared with tropical populations. Here, we report the first comparison of calibration curves for three Indian Apis cerana lineages: the tropical Apis indica, and the two montane Himalayan populations Apis cerana cerana (Himachal Pradesh) and Apis cerana kashmirensis (Jammu and Kashmir). We found that the colonies of the two montane A. cerana populations show dance-distance calibration curves with significantly shallower slopes than those of the tropical A. indica. Next, we transferred A. c. cerana colonies to Bangalore (∼ 2600 km away) to obtain calibration curves in the same location as A. indica. The common garden experiment confirmed this difference in slopes, implying that the lineages exhibit genetically fixed differences in dance-distance coding. However, the slopes of the calibration curves of the transferred A. c. cerana colonies were also significantly higher than those of the colonies tested in their original habitat, indicating an important effect of the environment. The differences in dance-distance coding between temperate and tropical A. cerana lineages resemble those described for Apis mellifera, suggesting that populations of both species independently evolved similar adaptations.

Unraveling the genomic landscape of Campylorhynchus wrens along western Ecuador's precipitation gradient: Insights into hybridization, isolation by distance, and isolation by the environment.

Environmental gradients have the potential to influence genetic differentiation among populations ultimately leading to allopatric speciation. However, environmental gradients can also facilitate hybridization between closely related taxa. We investigated a putative hybrid zone in western Ecuador, involving two polytypic wren species (Aves: Troglodytidae), Campylorhynchus zonatus and C. fasciatus. Our study addressed two primary questions: (1) Is there evidence of population structure and genetic admixture between these taxa in western Ecuador? and (2) What are the relative contributions of isolation by distance and isolation by the environment to the observed genetic differentiation along the environmental gradient in this region? We analyzed 4409 single-nucleotide polymorphisms (SNPs) from 112 blood samples sequenced using ddRadSeq and a de novo assembly. The optimum number of genetic clusters ranged from 2 to 4, aligning with geographic origins, known phylogenetics, and physical or ecological constraints. We observed notable transitions in admixture proportions along the environmental gradient in western Ecuador between C. z. brevirostris and the northern and southern genetic clusters of C. f. pallescens. Genetic differentiation between the two C. f. pallescens populations could be attributed to an unreported potential physical barrier in central western Ecuador, where the proximity of the Andes to the coastline restricts lowland habitats, limiting dispersal and gene flow, especially among dry-habitat specialists. The observed admixture in C. f. pallescens suggests that this subspecies may be a hybrid between C. z. brevirostris and C. fasciatus, with varying degrees of admixture in western Ecuador and northwestern Peru. We found evidence of isolation by distance, while isolation by the environment was less pronounced but still significant for annual mean precipitation and precipitation seasonality. This study enhances our understanding of avian population genomics in tropical regions.

The impact of urban configuration types on urban heat islands, air pollution, CO2 emissions, and mortality in Europe: a data science approach

The world is becoming increasingly urbanised. As cities around the world continue to grow, it is important for urban planners and policy makers to understand how different urban configuration patterns affect the environment and human health. However, previous studies have provided mixed findings. We aimed to identify European urban configuration types, on the basis of the local climate zones categories and street design variables from Open Street Map, and evaluate their association with motorised traffic flows, surface urban heat island (SUHI) intensities, tropospheric NO2, CO2 per person emissions, and age-standardised mortality. We considered 946 European cities from 31 countries for the analysis defined in the 2018 Urban Audit database, of which 919 European cities were analysed. Data were collected at a 250 m × 250 m grid cell resolution. We divided all cities into five concentric rings based on the Burgess concentric urban planning model and calculated the mean values of all variables for each ring. First, to identify distinct urban configuration types, we applied the Uniform Manifold Approximation and Projection for Dimension Reduction method, followed by the k-means clustering algorithm. Next, statistical differences in exposures (including SUHI) and mortality between the resulting urban configuration types were evaluated using a Kruskal-Wallis test followed by a post-hoc Dunn's test. We identified four distinct urban configuration types characterising European cities: compact high density (n=246), open low-rise medium density (n=245), open low-rise low density (n=261), and green low density (n=167). Compact high density cities were a small size, had high population densities, and a low availability of natural areas. In contrast, green low density cities were a large size, had low population densities, and a high availability of natural areas and cycleways. The open low-rise medium and low density cities were a small to medium size with medium to low population densities and low to moderate availability of green areas. Motorised traffic flows and NO2 exposure were significantly higher in compact high density and open low-rise medium density cities when compared with green low density and open low-rise low density cities. Additionally, green low density cities had a significantly lower SUHI effect compared with all other urban configuration types. Per person CO2 emissions were significantly lower in compact high density cities compared with green low density cities. Lastly, green low density cities had significantly lower mortality rates when compared with all other urban configuration types. Our findings indicate that, although the compact city model is more sustainable, European compact cities still face challenges related to poor environmental quality and health. Our results have notable implications for urban and transport planning policies in Europe and contribute to the ongoing discussion on which city models can bring the greatest benefits for the environment, climate, and health. Spanish Ministry of Science and Innovation, State Research Agency, Generalitat de Catalunya, Centro de Investigación Biomédica en red Epidemiología y Salud Pública, and Urban Burden of Disease Estimation for Policy Making as a Horizon Europe project.