Geographic Patterns Research Articles

Beyond the regional average: Drivers of geographical rainfall variability during East Africa's short rains

AbstractThe East African “short rains” from October–December (OND) are crucial for the region's cultural and agricultural landscape. Traditional climate studies have often treated these rains as a single mode, representing the average rainfall across the region. This approach, however, fails to capture the complex geographical variations in seasonal rainfall. In our study, we analyse 4200 reforecasts from a seasonal prediction system spanning 1981–2022, identifying distinct clusters that represent different geographical patterns of the short rains. We explore the influence of tropical sea‐surface temperature patterns, upper‐level tropospheric flow, and low‐level moisture fluxes on these clusters. A key revelation of our research is the limited predictability of certain geographical rainfall structures based on large‐scale climatic drivers. This finding highlights a gap in current forecasting methodologies, emphasising the necessity for further research to understand and predict these intricate patterns. Our study illuminates the complexities of regional rainfall variability in East Africa, underlining the importance of continued investigation to improve climate resilience strategies in the region.

The role of species interactions in shaping the geographic pattern of ungulate abundance across African savannah

Macroecologists traditionally emphasized the role of environmental variables for predicting species distribution and abundance at large scale. While biotic factors have been increasingly recognized as important at macroecological scales, producing valuable biotic variables remains challenging and rarely tested. Capitalizing on the wealth of population density estimates available for African savannah ungulates, here we modeled species average population density at 100 × 100 km as a function of both environmental variables and proxies of biotic interactions (competition and predation) and estimated their relative contribution. We fitted a linear mixed effect model on 1043 population density estimates for 63 species of ungulates using Bayesian inference and estimated the percentage of total variance explained by environmental, anthropogenic, and biotic interactions variables. Environmental and anthropogenic variables were the main drivers of ungulate population density, with NDVI, Distance to permanent water bodies and Human population density showing the highest contribution to the variance. Nonetheless, biotic interactions altogether contributed to a quarter of the variance explained, with predation and competition having a negative effect on species density. Despite the limitations of modelling biotic interactions in macroecological studies, proxies of biotic interactions can enhance our understanding of biological patterns at broad spatial scales, uncovering novel predictors as well as enhancing the predictive power of large-scale models.

The Potential Habitat Response of Cyclobalanopsis gilva to Climate Change.

Cyclobalanopsis gilva, a valuable timber species in China, holds significant importance for understanding the constraints imposed by climate change on the dynamic geographic distribution of tree species. This study utilized the MaxEnt maximum entropy model to reconstruct the migratory dynamics of C. gilva geographical distribution since the Last Glacial Maximum. The objective was to comprehend the restrictive mechanisms of environmental factors on its potential geographical distribution, aiming to provide insights for mid-to-long-term afforestation planning of C. gilva. The optimized MaxEnt model exhibited a significantly high predictive accuracy, with an average AUC value of 0.949 ± 0.004 for the modern suitable habitat model of C. gilva. The total suitable habitat area for C. gilva in contemporary times was 143.05 × 104 km2, with a highly suitable habitat area of 3.14 × 104 km2. The contemporary suitable habitat was primarily located in the southeastern regions of China, while the highly suitable habitat was concentrated in eastern Fujian and central-eastern Taiwan. Bioclimatic variables such as mean diurnal range (Bio2), min temperature of coldest month (Bio6), precipitation of driest quarter (Bio17), and precipitation of driest month (Bio14) predominantly influenced the modern geographic distribution pattern of C. gilva, with temperature factors playing a leading role. With global climate warming, there is a risk of fragmentation or even loss of suitable habitat for C. gilva by 2050 and 2090. Therefore, the findings of this study can significantly contribute to initiating a habitat conservation campaign for this species.

Geographic patterns and climatic drivers of phylogenetic structure of liverworts along a long elevational gradient in the central Himalaya

AbstractFor clades originating in warm climates, the tropical niche conservatism hypothesis predicts that current biological assemblages in colder or drier climates are expected to have lower phylogenetic diversity, and species in colder or drier climates are expected to be more closely related to each other (i.e., higher phylogenetic clustering). Liverworts are one of the oldest clades of extant land plants. They originated about 500 Ma during a warm (“greenhouse”) period and experienced multiple major cycles of warm and cold periods. Here, I test the tropical niche conservatism hypothesis using liverwort assemblages distributed along an elevational gradient crossing about 5000 m of elevation in the central Himalaya. I found that, in general, phylogenetic diversity and dispersion decrease with increasing elevation and thus with decreasing temperature, which is consistent with the tropical niche conservatism hypothesis. Phylogenetic diversity decreases with elevation monotonically, but phylogenetic dispersion decreases with elevation in a triphasic (zig‐zag) pattern, which is generally consistent with the triphasic pattern found in angiosperms and polypod ferns along the same elevational gradient. Temperature‐related variables explained approximately the same amount of the variation in phylogenetic diversity and dispersion as did precipitation‐related variables, although mean annual temperature explained 9%−15% more variation than did annual precipitation. Climate extreme variables explained approximately the same amount of variation in phylogenetic diversity and dispersion as did climate seasonality variables.

The Phylogenetic Structure Patterns of Angiosperm Species and Their Determinants in East Eurasia

ABSTRACTAimThe Kunming‐Montreal Global Biodiversity Framework requires that evolutionary histories of species should be considered in conservation planning. The phylogenetic structure of species assemblages quantifies species evolutionary histories and increasingly becomes an endeavour for ecologists. Understanding the geographic patterns of phylogenetic structure of species assemblages and their drivers can provide a fundamental reference for conservation planning. Although several theoretical hypotheses based on the effects of contemporary environment, historical climate change and evolutionary niche conservatism had been widely discussed in previous studies, the relative contributions of these hypotheses on phylogenetic structure of angiosperms, especially herbaceous species, remain debated.LocationEast Eurasia.Major Taxa StudiedAngiosperms.MethodsWe compiled distributions of 43,023 angiosperm species in east Eurasia at spatial resolution (100 × 100 km2). Using this newly compiled database and a species‐level phylogeny, we estimated the phylogenetic structure patterns for species with different growth forms. We explored the relationships of these patterns with contemporary environment and historical climate change to test predictions of the tropical niche conservatism hypothesis (TCH) and to compare the contribution of different hypotheses using generalised linear models and hierarchical partitioning.ResultsWe found that phylogenetic structure of angiosperms displayed significant latitudinal gradients. Notably, phylogenetic structure patterns and their drivers differed between woody and herbaceous species. Actual evapotranspiration was the best predictor of phylogenetic structure patterns for all and herbaceous species, while the mean temperature of the coldest quarter was the best predictor for woody species. The effect of historical climate change on phylogenetic structure patterns was weak.Main ConclusionsOur results suggest that the TCH only explains the phylogenetic structure pattern of woody species, not herbaceous species. Moreover, contemporary climate influences the phylogenetic structure of angiosperms in east Eurasian by affecting herbaceous and woody species differently.

Changes in Substance Use Diagnoses in the Great Plains during the COVID-19 Pandemic.

As drug overdose mortality rises in the United States, healthcare visits present critical opportunities to mitigate this trend. This study examines changes in healthcare visits for substance use disorders (SUDs) and remission prior to and during the COVID-19 pandemic in the Great Plains, with a focus on identifying the characteristics of those served. Data were analyzed from 109,671 patient visits (mode = one visit per patient), encompassing diverse demographics, including sex, age, race, ethnicity, and geographic location. Visits analyzed included those for Alcohol Use Disorder (AUD), Opioid Use Disorder (OUD), or Stimulant Use Disorder (StUD) and those in remission of these disorders between March 2019 and March 2021. Patient demographic information and geographic factors, like rurality and Medicaid expansion status, were considered, and logistic regression was utilized. Visits were primarily by White (70.83%) and Native American (21.39%) patients, non-Hispanic (91.70%) patients, and males (54.16%). Various demographic, geographic, and temporal trends were observed. Findings indicated that males were more likely to receive an AUD diagnosis, while females were more likely to receive an OUD or StUD diagnosis. Metropolitan-residing patients were more likely to receive an AUD diagnosis, while non-metropolitan patients were more likely to receive an OUD diagnosis. Remission odds increased for StUD during the pandemic but decreased for AUD and OUD. These findings illuminate the demographic and geographic patterns of SUD-related healthcare visits, suggesting critical touchpoints for intervention. The results emphasize the urgent need for targeted healthcare strategies, especially in rural and underserved areas, to address persistent health disparities.

Analysis of the Genetic Variation and Geographic Distribution Patterns of Xanthomonas citri pv. citri Strains in Citrus Production in Burkina Faso.

It is essential to have a thorough knowledge of the genetic variation among different strains of Xanthomonas citri pv. citri, which is responsible for causing citrus bacterial canker. This understanding is important for studying disease characteristics, population structure, and evolution and ultimately for developing sustainable methods of control. A total of 48 strains obtained from citrus production areas in Burkina Faso in 2012, 2020, and 2021 were subjected to Polymerase Chain reaction (PCR) tests using specific primers. The aim was to examine the distribution of type 3 effectors and determine the geographical origins of the strains. The examination of the distribution of type 3 non-transcription-activator-like effectors (TALEs) revealed a broader range of strains obtained in 2020 and 2021 than in 2012. However, all the strains possessed a shared set of three genes, specifically, XopE2, XopN, and AvrBs2. Furthermore, all examined effectors were observed in the Bobo-Dioulasso region. Regarding the characterization of TALEs, two profiles containing two to three TALEs were discovered. Profile 1, consisting of two TALEs, was found in 37 X. citri pv. citri strains, whereas Profile 2, comprising three TALEs, was detected in 11 strains. Among the three TALEs (A, B, and C) that were identified, TALEs B and C were present in all the strains. The correlation matrix indicated a positive association between the type 3 effector content of strains and the duration of their isolation. Principal component analysis revealed a limited organization of the strains under investigation. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Geographic Gradients in Species Interactions: From Latitudinal Patterns to Ecological Mechanisms

The idea that species interactions are more ecologically and evolutionarily important toward lower latitudes underpins seminal theories in ecology and evolution. Recent global studies have found the predicted latitudinal gradients in interactions, particularly predation. However, latitudinal patterns alone do not reveal why interactions vary geographically and so do not provide strong predictions in space (e.g., for specific ecosystems) or time (e.g., forecasting responses to global change). Here, I review theory to identify a clearer, mechanistic, and testable framework for predicting geographic variation in the importance of species interactions. I review competing metrics of importance, proximate mechanisms that can increase interaction importance, and environmental gradients that could generate predictable geographic patterns (climate extremes and stability, warmth, productivity, and biodiversity). Strong empirical tests are accumulating thanks to the rise of global experiments and datasets; renewed focus on testing why interactions vary spatially will help move the field from identifying latitudinal patterns to understanding broader mechanisms.

Across a phylogeographic break in the Qinling Mountains-Huaihe River Line: Quaternary evolutionary history of a medicinal and edible homologous plant (Allium macrostemon) in China

Biogeographic barriers to gene flow are central to studies of plant phylogeography. There are many physical and geographic barriers in China, but few studies have used molecular ecological evidence to investigate the natural geographic isolation barrier of the Qinling Mountains-Huaihe River Line (QHL). Allium macrostemon is a precious Chinese perennial herb belonging to the Amaryllidaceae family. It is used as a food and medicine, with a variety of health and healing properties. Five SSR markers, three chloroplast DNA (cpDNA) markers (psbA-trnH, rps16 and trnL-F), one nuclear ribosomal DNA (nrDNA) marker (ITS), and simplified genome GBS sequencing were used to analyse the genetic diversity and structure of A. macrostemon. Combining SSR, cpDNA, nrDNA ITS data and GBS analysis results, we divided A. macrostemon populations into northern and southern groups, with the southern group further divided into southwestern and central-southeastern groups. Niche simulation results reveal that the distribution area of A. macrostemon will reach its maximum in the future. These data indicate that the regional separation of A. macrostemon has been maintained by the combined influence of a geographical barrier and Quaternary climate, and that the back-and-forth fluctuations of QHL and Quaternary climate have played an important role in this process. QHL acts as a north-south dividing line in phylogeography and population genetic structure, promoting physical geographic isolation. This study provides a theoretical basis for the conservation, development, and utilization of A. macrostemon resources. It further provides a reference for understanding the systematic geographical pattern of the large-scale spatial distribution of plants in China and enriches our understanding of Quaternary plant evolution in areas with complex terrain.

Population genetic diversity and environmental adaptation of Tamarix hispida in the Tarim Basin, arid Northwestern China.

Arid ecosystems, characterized by severe water scarcity, play a crucial role in preserving Earth's biodiversity and resources. The Tarim Basin in Northwestern China, a typical arid region isolated by the Tianshan Mountains and expansive deserts, provides a special study area for investigating how plant response and adaptation to such environments. Tamarix hispida, a species well adapted to saline-alkaline and drought conditions, dominates in the saline-alkali lands of the Tarim Basin. This study aims to examine the genetic diversity and environmental adaptation of T. hispida in the Tarim Basin. Genomic SNPs for a total of 160 individuals from 17 populations were generated using dd-RAD sequencing approach. Population genetic structure and genetic diversity were analyzed by methods including ADMIXTURE, PCA, and phylogenetic tree. Environmental association analysis (EAA) was performed using LFMM and RDA analyses. The results revealed two major genetic lineages with geographical substitution patterns from west to east, indicating significant gene flow and hybridization. Environmental factors such as Precipitation Seasonality (bio15) and Topsoil Sand Fraction (T_SAND) significantly shaped allele frequencies, supporting the species' genetic adaptability. Several genes associated with environmental adaptation were identified and annotated, highlighting physiological and metabolic processes crucial for survival in arid conditions. The study highlights the role of geographical isolation and environmental factors in shaping genetic structure and adaptive evolution. The identified adaptive genes related to stress tolerance emphasize the species' resilience and highlight the importance of specific physiological and metabolic pathways.

Phenotypic diversity and population structure of Pecan (Carya illinoinensis) collections reveals geographic patterns

Pecan (Carya illinoinensis) is an economically important nut crop known for its genetic diversity and adaptability to various climates. Understanding the growth variability, phenological traits, and population structure of pecan populations is crucial for breeding programs and conservation. In this study, plant growth and phenological traits were evaluated over three consecutive seasons (2015–2017) for 550 genotypes from 26 provenances. Significant variations in plant height, stem diameter, and budbreak were observed among provenances, with Southern provenances exhibiting faster growth and earlier budbreak compared to Northern provenances. Population structure analysis using SNP markers revealed eight distinct subpopulations, reflecting genetic differentiation among provenances. Notably, Southern Mexico collections formed two separate clusters, while Western collections, such as 'Allen 3', 'Allen 4', and 'Riverside', were distinguished from others. 'Burkett' and 'Apache' were grouped together due to their shared maternal parentage. Principal component analysis and phylogenetic tree analysis further supported subpopulation differentiation. Genetic differentiation among the 26 populations was evident, with six clusters highly in agreement with the subpopulations identified by STRUCTURE and fastSTRUCTURE. Principal components analysis (PCA) revealed distinct groups, corresponding to subpopulations identified by genetic analysis. Discriminant analysis of PCA (DAPC) based on provenance origin further supported the genetic structure, with clear separation of provenances into distinct clusters. These findings provide valuable insights into the genetic diversity and growth patterns of pecan populations. Understanding the genetic basis of phenological traits and population structure is essential for selecting superior cultivars adapted to diverse environments. The identified subpopulations can guide breeding efforts to develop resilient rootstocks and contribute to the sustainable management of pecan genetic resources. Overall, this study enhances our understanding of pecan genetic diversity and informs conservation and breeding strategies for the long-term viability of pecan cultivation.

Census Tract-Level Social Vulnerability and Gonorrhea Rates in Central Ohio: Results From the STD Surveillance Network, 2020-2021.

Gonorrhea remains a significant burden in central Ohio, particularly in socially disadvantaged communities. This study evaluates gonorrhea case rates and changes from 2020 to 2021, focusing on geographic patterns associated with social vulnerability. We analyzed gonorrhea case data from the Columbus STD Surveillance Network for 2020 and 2021. Cases were linked to census tracts and categorized into low (0-0.66) or high (0.67-1.0) vulnerability groups based on the Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry Social Vulnerability Index (SVI). We mapped gonorrhea case rates per 100,000 population, stratified by SVI group, and compared changes using Jenks natural breaks to determine cutpoints. High case rates were defined as ≥605 (2020) and ≥532 (2021). A change in case rates was defined as <154 (decrease/no change) or ≥154 (increase). Demographic factors were summarized for both years. In 2020 and 2021, nearly half of high-SVI tracts had high gonorrhea rates, compared with about 4% to 7% of low-SVI tracts. Median rates in high-SVI tracts were approximately 5 times higher than in low-SVI tracts, with rates of 546 and 598 per 100,000 in 2020 and 2021, compared with 98 and 104 per 100,000, respectively. Gonorrhea rates increased in 23 (9%) of low-SVI tracts and 37 (25%) of high-SVI tracts. Demographic characteristics remained consistent between the 2 years. Gonorrhea rates increased in central Ohio between 2020 and 2021, with higher burdens in high-SVI census tracts. Understanding the dynamics of social vulnerability at the community level is crucial for targeting limited STD resources effectively.

Spatial non-equilibrium and distribution dynamic evolution of the development level of national physical fitness in China's provinces.

Physical health is fundamental to a country's socio-economic advancement. An in-depth exploration of the spatial distribution and dynamic evolution of national physical fitness across China is crucial for enhancing the country's overall physical health. This study aims to provide valuable insights into the geographical and temporal patterns of physical fitness, informing strategies for national physical fitness improvement. Employing data from China's national physical fitness monitoring of 31 provinces, cities, and districts for the years 2005, 2010, and 2015, this study utilizes the Gini coefficient, its decomposition, and nonparametric density estimation methods. These techniques are applied to analyze the spatial disparities and temporal trends in national physical fitness levels among different demographics, including the overall population, males, females, and urban and rural residents. The study reveals that the regional disparity in China's national physical fitness initially narrowed and then expanded across the general population, females, and in both urban and rural areas, while consistently increasing among males. In terms of geographical distribution, the East, Middle, and West regions show significant heterogeneity, with the East-West gap being the most pronounced (Gini coefficients of 0.0249, 0.0230, 0.0263). The contribution rate of regional gaps was highest (54.40% -64.69%), followed by regional disparities (24.78% -27.15%), and the contribution of hypervariable density difference was the smallest (10.53% -19.75%). Despite a slight improvement in overall national physical fitness, the absolute regional disparities have further widened. Provinces with lower levels of national physical fitness demonstrate a 'club convergence' trend, indicating regional clustering of similar fitness levels. Additionally, a 'catch-up effect' is evident in rural areas, particularly in provinces with historically lower levels of national physical fitness. These findings suggest the need for region-specific public health strategies to address the growing disparities in national physical fitness across China.

Probabilistic seismic hazard analysis for the Dominican Republic

The Dominican Republic experiences moderate to high seismic hazard mostly caused by oblique convergence at the Caribbean/North American plate boundary that manifests as subduction zones, less-pronounced subduction-like trenches with thrust faulting, long strike-slip faults parallel to the plate boundary, and onshore deformation. Historical earthquakes have damaged the Dominican Republic’s large cities and those in neighboring Haiti, once requiring relocation. Given this, the Dominican Republic joined the “Training and Communication for Earthquake Risk Assessment” (TREQ) project funded by the United States Agency for International Development, which aimed to increase earthquake risk assessment capacity in Latin American cities. The TREQ project was the basis for developing an openly available probabilistic seismic hazard model for the Dominican Republic. The input model was developed from two main datasets: a homogenized earthquake catalog and an active faults database that combines results of recent local projects with a global database. The seismic source characterization used these to constrain source geometries and occurrence rates for active shallow crustal earthquakes, subduction interfaces and subduction-like thrusts, and intraslab earthquakes. Shallow crustal earthquakes, including those on subduction-like thrusts, are modeled by smoothed seismicity and fault sources, the latter using pre-defined geometries that permit multi-fault ruptures. Seismicity on the Puerto Rico Trench subduction interface is modeled as a fault source, while intraslab sources use pre-defined gridded ruptures inside the intraslab volume. The source characterization applies epistemic uncertainties to modeling assumptions affecting occurrence rates and maximum magnitudes. The ground motion characterization used residual analyses from past regional projects as a basis, updating some components with more recent ground motion models. Computed hazard results reinforce those from recent studies in terms of geographical hazard patterns and levels. For 475-year return periods, peak ground acceleration (PGA) in Santiago de los Caballeros reaches 0.50 g, controlled by the Septentrional Fault, while all tectonic region types contribute to the PGA 0.31 g computed for Santo Domingo.

Investigating the impact of fuel price shocks on bicycle sharing usage in Budapest

The creation of sustainable urban communities is contingent upon the establishment of a sustainable, efficient, and fast transportation system. Bicycle sharing systems (BSS) are one of the most sustainable and inclusive ways of transportation in cities. An important question is how to increase BSS ridership and whether it can effectively replace cars in cities, hence contributing to achieving the 11th Sustainable Development Goal and creating sustainable urban communities. This paper aims to contribute to this stream of research by investigating the effect of fuel prices on BSS ridership. We exploit a natural experiment from Budapest, Hungary, where fuel prices were capped between November 15, 2021, and December 6, 2022. Once the price cap was suddenly eliminated, fuel prices increased by around one-third immediately leading to a very substantial and rarely observable one-time price increase. The difference-in-difference regression results indicate a 2–6% increase in BSS ridership after the elimination of the fuel price cap. The geographical pattern of the change shows that BSS usage mainly increased in the outer part of the city; however, some areas observed a decline. The regression results are also reinforced by survey findings. Understanding these dynamics is crucial for effective urban planning and transportation policymaking.

Effects of the interaction between Linnean and Darwinian shortfalls on diversification gradients

It is now widely recognized that broad-scale patterns in species richness, particularly the Latitudinal Diversity Gradients (LDGs), are driven by complex interactions among ecological, evolutionary, and historical processes. However, even if it is now possible to better evaluate evolutionary explanations for LDGs based on speciation and diversification rates estimated from phylogenies, a subtle interaction between such estimates and the geographic structure of the Linnean shortfall, forming the Latitudinal Taxonomy Gradient (LTG), was recently recognized. Here, we expand on previous simulation results and show that a relatively small geographical bias in the Linnean shortfall, adding less than 20% of new species phylogenetically correlated with previously described ones in the southern (richer) region, would be enough to change the patterns in diversification rates, based on different methods (tip rates DR and GeoSSE). Further investigations of the magnitude of LTG and new empirical modeling of problems in species delimitation are thus necessary to evaluate the robustness of the estimates of the diversification gradients to biased knowledge and taxonomic uncertainty, allowing a better understanding of the evolutionary dynamics underlying LDGs. Geographical patterns in the Linnean shortfall, creating Latitudinal Taxonomy Gradients (LTGs), may jeopardize robust estimates of diversification gradients and our understanding of processes underlying diversity patterns. Simulations show that a relatively small geographic bias in the Linnean shortfall, adding new undiscovered species phylogenetically close to the known ones, is sufficient to invert patterns in diversification rates estimated by two distinct methods. A more comprehensive assessment of the magnitude of diversification gradients in respect to the LTGs is necessary to evaluate the robustness of our understanding of LDGs. Empirical modeling of species delimitation quality and simulations adding small branches in the phylogenies, mitigating simultaneously both Linnean and Darwinian shortfalls, may provide more consistent evidence for drivers of LDGs accounting for taxonomic uncertainty.

SDG: A global large-scale airport perception disparity cognition modeling method based on deep learning and geographic knowledge

Global airport perception levels vary due to natural geographical factors and economic development disparities. Understanding these differences is crucial for assessing regional airport development and its correlation with geographical patterns. However, there are limited methods available to effectively comprehend these disparities. To address this issue, this paper proposes a Salience, Disturbance, and Geographic-knowledge (SDG) approach for the cognitive analysis of global large-scale airport perception differences. Salience is assessed using a two-class deep learning model to evaluate the prominence of known airports. Disturbance is evaluated using an object detection model to measure background interference in large-scale airport perception. Geographic-knowledge analysis considers the correlation between regional airports and their surrounding geographic environment. The results rank perception difficulties for 17 regions worldwide, with Tajikistan exhibiting the highest difficulty at 0.922, while the Jiangsu–Zhejiang–Shanghai region in China has the lowest at 0.102. We also performed correlation analyses to validate the effectiveness of our model. To our knowledge, this paper pioneers the cognitive analysis of target perception difficulty differences across multiple global regions.

Ten years of oil pollution detection in the Eastern Mediterranean shipping lanes opposite the Egyptian coast using remote sensing techniques

The Eastern Mediterranean region, a vital conduit for global maritime trade, faces significant environmental challenges due to marine pollution, particularly from oil spills. This is the first study covering the long period of comprehensive monitoring of oil pollution using the full mission of Sentinel-1 Synthetic Aperture Radar (SAR) data in the Mediterranean Sea, so this research aims to detect and analyze comprehensively the occurrence of oil spills in the Eastern Mediterranean over a decade (2014–2023). This study focuses on identifying geographical distribution patterns, proximity to shorelines, frequency across maritime zones, and potential sources of these spills, especially around major ports and maritime routes. This study utilizes SAR data from the Sentinel-1 satellite. The methodology included automated detection algorithms within the Sentinel application platform (SNAP) and integration with GIS mapping to study oil spill patterns and characteristics. Over 1000 Sentinel-1 scenes were investigated in the northern Mediterranean waters off the coast of Egypt, to detect and analyze 355 oil spill events with a total impacted area of more than 6000 km2. The analysis of temporal spill distribution reveals significant fluctuations from year to year. Within the entire timeline of the study, 2017 had the largest spatial areas covering one thousand square kilometers. In contrast, the single largest spill recorded during the study period occurred in 2020, covering 198.73 square kilometers. The results identified a non-uniform distribution of oil spills and primarily exhibiting elongated patterns aligned with the navigation routes. The distinct increase of oil spill incidents was within the Exclusive Economic Zone (EEZ), obviously drifted to the coastline and around major ports. The study emphasizes the critical role of remote sensing technologies in addressing environmental challenges caused by the maritime transport sector, advocating for enhanced monitoring and regulatory enforcement to protect marine ecosystems and support sustainable naval activities. The findings highlight the urgent need for targeted continuous monitoring and rapid response strategies in high-traffic maritime areas, particularly around the EEZ and major ports.

Sexual color ornamentation, microhabitat choice, and thermal physiology in the common wall lizard (Podarcis muralis).

Common wall lizards (Podarcis muralis) in Italy show a striking variation in body coloration across the landscape, with highly exaggerated black and green colors in hot and dry climates and brown and white colors in cool and wet climates. Males are more intensely colored than females, and previous work has suggested that the maintenance of variation in coloration across the landscape reflects climatic effects on the strength of male-male competition, and through this sexual selection. However climatic effects on the intensity of male-male competition would need to be exceptionally strong to fully explain the geographic patterns of color variation. Thus, additional processes may contribute to the maintenance of color variation. Here we test the hypothesis that selection for green and black ornamentation in the context of male-male competition is opposed by selection against ornamentation because the genes involved in the regulation of coloration have pleiotropic effects on thermal physiology, such that ornamentation is selected against in cool climates. Field observations revealed no association between body coloration and microhabitat use or field active body temperatures. Consistent with these field data, lizards at the extreme ends of the phenotypic distribution for body coloration did not show any differences in critical minimum temperature, preferred body temperature, temperature-dependent metabolic rate, or evaporative water loss when tested in the laboratory. Combined, these results provide no evidence that genes that underlie sexual ornamentation are selected against in cool climate because of pleiotropic effects on thermal biology.

Geographical Patterns in Mortality Impacts Due To Heatwaves of Different Characteristics in Spanish Cities.

The impact of heatwaves (HWs) on human health is a topic of growing interest due to the global magnification of these phenomena and their substantial socio-economic impacts. As for other countries of Southern Europe, Spain is a region highly affected by heat and its increase under climate change. This is observed in the mean values and the increasing incidence of extreme weather events and associated mortality. Despite the vast knowledge on this topic, it remains unclear whether specific types and characteristics of HW are particularly harmful to the population and whether this shows a regional interdependency. The present study provides a comprehensive analysis of the relationship between HW characteristics and mortality in 12 Spanish cities. We used separated time series analysis in each city applying a quasi-Poisson regression model and distributed lag linear and non-linear models. Results show an increase in the mortality risk under HW conditions in the cities with a lower HW frequency. However, this increase exhibits remarkable differences across the cities under study not showing any general pattern in the HW characteristics-mortality association. This relationship is shown to be complex and strongly dependent on the local properties of each city pointing out the crucial need to examine and understand on a local scale the HW characteristics and the HW-mortality relationship for an efficient design and implementation of prevention measures.