Cold Months Research Articles

GIS Tips & Tricks ‐ Mapping the Aurora Borealis

November in Alaska ushers in dark, cold winter nights, but it also marks the peak season for aurora viewing. As we embrace the magic of the northern lights and cozy up for the colder months, it’s the perfect time to map this celestial wonder. Last year during the holidays, we crafted a wonderful snowy basemap to showcase Anchorage’s cross-country ski trails. To continue on with our winter theme, we???ll first start by recreating the custom basemap. This month, Shira Ellenson, from the Dewberry-Alaska office, returns to the Tips & Tricks column to bring the aurora borealis to our mapping community in a step-by-step workflow for the winter season.

Complex assessment of ambient particulate matter in a small settlement with coal-handling port

Relevance. Russian coal exports have been steadily increasing in recent years, and Far Eastern ports, originally not adapted to dusty cargoes, have switched to coal operations. Unoptimized coal handling leads to increased content of coal-containing particles in the air and to various environmental problems. Aim. To analyze the concentration of particulate matter in the air and the chemical composition of particles on the surface of conifer needles in the Posyet settlement (Primorsky Krai, Russia), where a large coal terminal operates. Materials and methods. The chemical composition was studied on the surface of conifer needles by X-ray fluorescence and in washout of conifer needle samples using Raman spectroscopy and energy dispersive analysis. Concentrations of particles with the diameter of 2.5 and 10 μm (PM2.5 and PM10, respectively) were measured using automatic monitoring stations. Results and conclusions. Chemical composition was dominated by mineral particles (calcite, silicates, etc.). However, the presence of coal particles (up to 8.3%) and metal particles was also observed. Mean concentrations of PM2.5 and PM10 were within the Russian and international health standards, but close to their upper limits. Concentrations of both measured particle fractions were highest during the winter months (as well as in March, which is traditionally a cold month in the Far East), followed by a gradual decrease. The study obtained new data on the annual variations of concentrations of PM2.5 and PM10, as well as on the basic composition of particles from the surface of woody vegetation (needles) as an indicator of the state of air pollution in this settlement.

Habitat suitability and relative abundance of wild boars in the east‐central Tianshan Mountains, China

AbstractAs wild boar populations and their distribution ranges increase, human–wild boar conflicts have become increasingly prevalent in numerous regions across the globe. These conflicts have a profound impact on human livelihoods, resulting in significant economic losses. Understanding the habitat requirements and relative abundance of wild boars is crucial prior to implementing any conservation measures. However, studies on wild boar habitat and population in the central and eastern regions of the Tianshan Mountains in China are lacking. We assessed the activity patterns and relative abundance of wild boars in these areas and evaluated habitat suitability using a combination of camera trapping, line transects, species distribution modeling (maximum entropy model), and hierarchical abundance modeling (Bayesian N‐mixture model). We used 311 infrared cameras and 280 field‐based line transects to cover approximately 31,000 km² from September 2022 to May 2023 in the east‐central Tianshan Mountains. We used 240 wild boar distribution locations and 13 environmental predictors in the development of species distribution models. We also used species counts and associated environmental predictors in the N‐mixture model to estimate the relative abundance of wild boar. Wild boars were most active during crepuscular hours (1800), and relatively active in the diurnal period compared to the nocturnal period. The probability of wild boar occurrence increased with higher normalized difference vegetation index (NDVI), the minimum temperature of the coldest month, and annual temperatures below 39°C. Boars were most likely to be found in closed deciduous‐coniferous forests. The relative abundance of wild boars was positively affected by NDVI and negatively affected by the minimum temperature of the coldest month and temperature annual range. Based on our results, we suggest areas of management priority. In particular, extensive and intact habitat with substantial wild boar populations, such as the Banfanggou, the South Mountain of Urumqi, and the Hutubi, should be prioritized for long‐term wild boar population monitoring and management so the adverse impacts of increasing wild boar populations in the study region can be minimized.

The Spatiotemporal Dynamics of Temperature Variability Across Mts. Qinling: A Comparative Study from 1971 to 2022

Analyzing the spatiotemporal patterns of atmospheric temperature in sensitive areas is critically important for understanding the broader implications of global climate change, which remains a prominent topic in geosciences. It also plays a crucial role in advancing sustainable development. This study utilized daily minimum, maximum, and mean temperature data from twelve meteorological stations across the South and North Mts. Qinling (Qinling Mountains). Employing trend analysis, the Mann–Kendall mutation test, and Morlet wavelet analysis, we explored the predominant temperature trends and characteristics from 1971 to 2022. Our findings revealed consistent inter-annual warming trends in both regions, with more rapid temperature increases in the North compared to the South. Notably, significant shifts occurred in 2003 for both mean and minimum temperatures in the North, while the maximum and minimum temperature values were recorded in the 2010s and 1980s, respectively. Both regions exhibited a primary temperature fluctuation cycle of 28 years. Seasonally, the strongest warming effects appeared in spring, with the weakest in autumn, and moderate effects in winter and summer, indicating that spring contributes most significantly to regional warming. Monthly analysis showed positive temperature trends across all months, with higher rates in the North. The weakening temperature boundary effect of the Mts. Qinling suggested a weakening North–South division, particularly highlighted by the northward shift of the 1 °C isotherm curve for the coldest month, moving away from the previously observed 0 °C isotherm. This northward shift highlights the differential warming rates between the northern and southern regions. Overall, the analysis confirms a robust warming trend, with notable fluctuations in January’s temperatures since 1998, suggesting the Mts. Qinling’s emerging role as a climatic divider in the Chinese Mainland. This introduces new challenges for regional ecosystems, agricultural production, and water resource management, highlighting the pressing need to advance regional sustainable development in the face of climate change.

Effects of ensemble-forecasted key environmental factors on the distribution, active constituents, and transcription regulation in Ligusticum chuanxiong Hort.

Ligusticum chuanxiong Hort., with over 2000 years of medicinal use and cultivation history, is extensively used in clinical settings for treating heart disease, headache, dysmenorrhea, and amenorrhea. Constructing the geographic distribution pattern of L. chuanxiong and identifying the environmental factors limiting its range, as well as clarifying the effects of key environmental factors on the content of major active constituents and transcription regulation, could provide a scientific foundation for the conservation and effective management of this valuable medicinal resource. The results reveal that the predominant environmental factors influencing the distribution were the minimum temperature of the coldest month (Bio6) and solar radiation (Srad), with cumulative account for 87.46% of the importance. Correlation analysis further reveals significant negative correlations between Bio6 and the content of major active constituents in L. chuanxiong, with Srad exhibiting a negative correlation with these constituents. The gene differential expression analysis indicated that the expression levels of some genes associated with growth and active constituent biosynthesis pathways, such as RPT2_13888, UVR8_16871, CLPB3_3155, and 4CLL5_116, varied significantly among locations influenced by differing key environmental factors. Consequently, alterations in the environment were found to influence the gene expression levels within these pathways, resulting in variations in the content of active constituents. These findings contribute to an enhanced understanding of how environmental factors impact the distribution and quality of medicinal plants and offer a theoretical reference for the introduction, cultivation, quality improvement, resource utilization and management of L. chuanxiong. © 2024 Society of Chemical Industry.

Climate and management changes over 40 years drove more stress‐tolerant and less ruderal weed communities in vineyards

AbstractSpontaneous plant communities have undergone considerable constraints due to human‐mediated changes. Understanding how plant communities are shifting in response to land management and climate changes is necessary to predict future ecosystem functioning and improve the resilience of managed ecosystems, such as agroecosystems. Using Mediterranean weed communities as models of managed plant communities in a climate change hotspot, we quantified the extent to which they have shifted from the 1980s to the 2020s in response to climate and management changes in vineyards. The weed communities of the same 40 vineyards in the Montpellier region were surveyed using the same protocol in spring, summer, and autumn, for two years, with a 40‐year interval (1978–1979 vs. 2020–2021). In four decades, the annual range of temperatures (i.e., the difference between the warmest month's and the coldest month's mean temperatures) increased by 1.2°C and the summer temperatures by 2°C. Weed management diversified over time with the adoption of mowing that replaced the chemical weeding of interrows. Chemical weeding is now mostly limited to the area under the row. Current weed communities were 41% more abundant, 24% more diverse, and with a less even distribution of abundance across species than the 1980s communities at the vineyard level. Modern communities were composed of more annual species (57% of annual species in the 1980s vs. 80% in the 2020s) with lower community‐weighted seed mass and were composed of fewer C4 species. They had higher community‐weighted specific leaf area, higher leaf dry matter content, and lower leaf area than the 1980s weed communities. At the community level, the onset of flowering was earlier and the duration of flowering was longer in the 2020s. Climate change induced more stress‐tolerant communities in the 2020s while the diversification of weed management practices favored less ruderal communities. This study shows that plant communities are shifting in response to climate change and that land management is a strong lever for action to model more diverse and eventually more desirable weed communities in the future.

Numerical Estimation of Potable Water Production for Single-Slope Solar Stills in the Caspian Region

This study provides a detailed numerical assessment of the productivity of single-slope solar stills across key cities in the Caspian region, including Aktau, Atyrau, Astrakhan, Makhachkala, Baku, Tehran, and Turkmenbashi. Employing a mathematical model based on heat balance equations and the Fourth Order Runge–Kutta method, we simulated the distillation process under various climatic conditions. The results reveal that productivity is significantly influenced by geographic location and local meteorological conditions. Tehran demonstrated the highest productivity across all seasons, with values of 1.75 × 103 kg/(m2·year) and an efficiency of 0.53, due to its optimal solar irradiation and ambient temperature. In contrast, Atyrau and Makhachkala exhibited lower productivity, particularly in colder months, highlighting the effect of ambient temperature on solar still efficiency. The analysis identified the optimal water depth at 2 cm and insulation thickness between 4 and 9 cm for enhancing productivity in continental climates like Aktau. Additionally, the lowest cost of distilled water was USD 0.024 per kilogram in Baku. These findings align with the existing literature, validating the numerical model’s accuracy. Future research will explore integrating solar stills with other renewable and fossil fuel-based technologies.

Evaluation of the relationships between physico-chemical parameters and the abundance of Vibrio spp. in blue crabs (Callinectes sapidus) and seawater from the Maryland Coastal Bays.

Fluctuations in water quality characteristics influence the productivity of blue crabs (Callinectes sapidus), and the risk of human exposure to pathogenic Vibrio species. Thus, this study assessed the prevalence of total and pathogenic/clinical markers of Vibrio parahaemolyticus and Vibrio vulnificus in blue crabs and seawater from the Maryland Coastal Bays (MCBs) and the correlation between Vibrio levels and physicochemical parameters. Three to five crabs and 1 L of seawater were collected monthly for 3 years (May 2018 to December 2020) from six sites within the MCBs. Hemolymph and crab tissue were extracted and pooled for each site. Extracted hemolymph, crab tissue, and seawater were analyzed for V. parahaemolyticus and V. vulnificus using the Most Probable Number (MPN) and real-time PCR methods. A one-way Analysis of Variance (ANOVA), correlations, and linear models were used to analyze the data. Akaike Information Criterion (AICc) was evaluated to determine the model that provides the best fit to the data relating to Vibrio concentrations and environmental factors. Results suggested that environmental factors could influence the growth of Vibrio spp. Both V. parahaemolyticus and V. vulnificus were more prevalent during the warmer months than colder months. Vibrio was more prevalent in crab samples compared to seawater. Vibrio vulnificus concentrations in seawater and hemolymph were positively correlated with temperature (p = 0.0143 seawater) and pH (p = 0.006 hemolymph). A negative correlation was observed between the concentration of V. vulnificus in whole crab (tissue) and dissolved oxygen level (p = 0.0256). The concentration of V. parahaemolyticus in seawater was positively correlated with temperature (p = 0.009) and negatively correlated with dissolved oxygen (p = 0.012). These results provide current information on the spatial and temporal distributions of Vibrio spp. in the MCBs that are useful for implementing more efficient processing and handling procedures of seafood products.

Enhancing building energy efficiency: Numerical analysis of a hybrid thermoelectric ventilation system and earth-air heat exchange with photovoltaic-thermoelectric power integration for heating and cooling loads

The lack of studies on hybrid systems combining thermoelectric ventilation (TEV) and earth-air heat exchangers with a photovoltaic-thermoelectric generator (PV-TEG) as the power supply for the hybrid system is addressed in this research. This study aims to investigate the effectiveness and performance of such a combined system in providing the required thermal load of a building. To simulate the performance of TEV and PV-TEG systems, energy conservation equations for various components of the system were formulated for the quasi-state mode. The performance of the earth-air heat exchanger system was evaluated using the effectiveness-number of transfer units method. The resulting set of algebraic equations was then solved using a MATLAB code. Results indicated significant preheating (5.41–15.03 °C) and precooling (0.7–10.22 °C) effects during the daily hours of 15-February and 15-July, respectively. Additionally, the TEG component effectively reduced PV temperatures by 3.54 °C–16.99 °C in 15-February and 3.99 °C–21.54 °C in 15-July. The system also demonstrated a high monthly useful thermal energy output (1215–1584 kWh) in the cold months (December to March), contrasting with higher monthly useful thermal exergy (712–763 kWh) in the summer months. Furthermore, increasing the number of TEGs from 10 to 50 resulted in significant improvements in the yearly average energy and exergy proficiency indexes (PIya,en and PIya,ex) by 164.97 % and 459.82 %, respectively. The supply air mass flow rate and the length and depth of the earth-air duct were identified as the second and third most influential parameters affecting these indexes. Moreover, the system at CPV concentration ratio of 3 provided the highest PIya,en and PIya,ex of 1.512 and 14.65, respectively.

How to alleviate seasonal limitations on water quality in farmland ditches? The importance of plant selection and configuration

In subtropical monsoon climate regions, traditional plants in constructed wetlands such as farmland ditches underperform in cold months, detracting from both purification capacity and esthetic appeal. To alleviate this weakness, this study introduced Phalaris arundinacea, a species with strong adaptability and cold tolerance, into a plant community dominated by Phragmites australis, constructing an ingenious composite plant community for year‐round water quality restoration and enhancement of attractiveness. First, laboratory simulations revealed significant seasonal differences in the removal rates of ammonia nitrogen (NH3‐N), total nitrogen (TN), and total phosphorus (TP) by the P. arundinacea community and P. australis community under different pollutant loads. Phragmites australis showed superior NH3‐N and TN removal capabilities from May to October, whereas P. arundinacea excelled in the rest of the months throughout the year. For TP removal, P. australis outperformed P. arundinacea from July to October, while P. arundinacea was more effective from January to May. We then verified this in rear farmland ditches, where P. australis were strategically partial substituted with P. arundinacea (Partial Replacement Treatment [PRT]), and compared it with unchanged farmland ditches (Control Treatment). We found that PRT enhanced decontamination efficiency over the year, especially significantly improving the water quality during colder months. Hence, this study advocates a novel strategy for effective annual decontamination and maintenance of wetlands such as farmland ditches, highlighting the importance of seasonally adaptive plant communities for water restoration. This transformative approach dramatically advances the field of wetland management, insisting on the important role of cold‐resistant species for year‐round ecosystem service optimization.

Air pollution by BTEX and the related health risks due to the tobacco smoke, a systematic review

BTEX is a group of hazardous chemical compounds that include benzene, toluene, ethylbenzene, and xylene. The indoor concentration of BTEX is mostly influenced by tobacco smoking, the region within the house, and seasonal variations. This systematic review analyzed studies on BTEX concentrations in indoor air, using data from Google Scholar, Science Direct, and Springer from 2010 to 2020, and performed statistical analysis with R after thorough data extraction and evaluation. Duplicate studies were removed, and disagreements during the article selection process were resolved by a third reviewer. Out of the 1351 articles obtained from the keyword search, only 13 were eventually selected for this study. The most abundant compound found in houses among BTEX was toluene, with a concentration of 13.80±16.50 µg/m3. The results indicated that the concentration of ƩBTEX in houses where smoking occurred was lower than in houses where no smoking occurred (18.52 vs. 27.66 µg/m3); However, the concentration of benzene in smoking houses was higher than in non-smoking houses (7.17±9.42 vs. 2.65±3.77 µg/m3, unpaired Wilcoxon test: p>0.05). The concentration of BTEX in houses was substantially lower than that in cafes (21.10±31.10 vs. 15,100±9740 µg/m3, unpaired Wilcoxon test: p<0.05). The urban region had the most significant accumulation of all BTEXs, with the industrial and rural sectors following suit. The findings indicated that the average concentration of BTEX in warm months (such as spring and summer) were higher than in cold months (such as fall and winter) within houses (28.50±44.30 vs. 8.60±7.77 µg/m3, unpaired Wilcoxon test: p>0.05). The findings indicated that the Cancer Risk (CR) associated with houses (3.11×10-6) and cafes (3.54×10-3) exceeded the permissible threshold. Moreover, the waterpipe cafes that utilized fruit-flavored tobacco had the greatest CR (4.98×10-3). Furthermore, the presence of smoking, regional factors, and seasonal variations did not result in an increase in the hazard quotient (HQ) in houses beyond the acceptable thresholds. Finally, smoking, seasonal variations, and region had critical impact on indoor BTEX concentrations, and they could increase the risk of carcinogenic potential in the indoor environments.

MITIGATING THE URBAN HEAT ISLAND EFFECT: The Thermal Performance of Shade-Tree Planting in Downtown Los Angeles

The intensifying urban heat island (UHI) effect presents a growing challenge for urban environments, yet there is a lack of comprehensive strategies that account for how multiple factors influence tree-cooling effectiveness throughout the year. While most studies focus on the effects of individual factors, such as tree shading or transpiration, over specific time periods, fewer studies address the combined impact of various factors—such as seasonal variations, building shading, transpiration rates, tree placement, and spacing—on tree cooling across different seasons. This study fills this gap by investigating the thermal environment in downtown Los Angeles through ENVI-met simulations. A novel tree-planting strategy was developed to enhance cooling performance by adjusting tree positions based on these key factors. The results show that the new strategy reduces Universal Thermal Climate Index (UTCI) temperatures by 2.2 °C on the hottest day, 0.97 °C on the coldest day, and 1.52 °C annually. The study also evaluates the negative cooling effects in colder months, demonstrating that, in cities with climates similar to Los Angeles, the benefits of tree cooling in hot weather outweigh the drawbacks during winter. These findings provide a new method for optimizing tree placement in urban planning, contributing to more effective UHI mitigation strategies.

Exergy based yearly performance analysis of a poly-generation system for a small-town application

The current study conducts a comprehensive year-round exergy analysis of an integrated system centered around a reversible solid oxide cell (RSOC), aimed at fulfilling the power and fresh water requirements of a small town, equivalent to 2.7 MW and 2000 m³/day, respectively. The integrated system encompasses four subsystems: the solar field, RSOC, organic Rankine cycle coupled with ejector cooling (ORC), and zero liquid discharge multi-effect desalination (MED-ZLD). The proposed system is analyzed using MATLAB. The annual exergy efficiency for each subsystem is examined, yielding average values of 11.9 %, 48.11 %, and 56.22 % for the solar field, ORC cycle, and MED-ZLD, respectively. Notably, the exergy efficiency of the Rankine cycle is higher in colder months compared to warmer ones. This phenomenon is attributed to the cycle's greater heat generation relative to the cooling it produces during the cold season. The RSOC exhibits noteworthy average exergy efficiencies of 93 % in electrolysis mode, 69.87 % in fuel cell mode, and an overall average exergy efficiency of 79.62 % throughout the year. The average exergy efficiency of the overall system is evaluated throughout the day, nighst, and the entire operational period. The results are values of 10.74 %, 34.31 %, and 23.34 %, respectively. This discrepancy is due to the primary energy supply source, which is solar energy during the day and input hydrogen during the night. The highest exergy efficiency is observed in December, while the lowest is in June. Furthermore, the study examines the distribution of exergy destruction and identifies cycles with significant impacts by analyzing the exergy destruction ratio across various months. The solar field is the primary contributor to daytime exergy destruction, peaking at 94.9 %. At night, the MED-SET cycle leads in exergy destruction, followed closely by the RSOC cycle operating as a fuel cell. The research also delves into exploring key contributors to exergy destruction in various cycles, shedding light on crucial insights into the intricate dynamics of the integrated system's performance.

Application of machine learning and deep learning techniques in modeling the associations between air pollution and meteorological parameters in urban areas of tehran metropolis.

Tehran, the most crowded city in Iran, suffers from severe air pollution, particularly during the cold months. This research endeavored to examine the statistical relationships between criteria air pollutants (CO, NO2, SO2, O3, PM10, and PM2.5) and meteorological elements (temperature, rainfall, wind speed, relative humidity, air pressure, sunshine hours, solar radiation, and cloudiness), as well as assess and compare the efficacy of six different algorithms (multiple linear regression (MLR), generalized additive model (GAM), classification and regression trees (CART), random forest (RF), gradient boosting machine (GBM), and deep learning (DL)) in modeling pollutants and climatic factors responsible for variations in Tehran's air pollution levels from 2001 to 2021 using R 4.3.2 software. The results of this study showed that O3 was strongly affected by weather conditions, while other pollutants were mainly influenced by each other than by meteorological parameters and more extensive research is required to pinpoint the precise impact of human activity on these pollutant levels in Tehran. Also based on the predictive model performance evaluation and concerning the principle of parsimony, in half of the cases, the MLR outperformed other models, despite its seeming simplicity and principal assumptions dependence. In other situations, the GAM was a good substitute.

Clustering Anomalous Circulations and Their Implications on the Prediction of Minimum 2-m Air Temperature over Northeastern China during Winter

Abstract The ERA5 reanalysis during cold months (November–March) of 1979–2020 was used for determining four cluster centroids through the k-means for classifying regional anomalies of the daily geopotential height at 500 hPa (H500) over northeastern China. Empirical orthogonal function (EOF) was used to reduce dimensionality. Four clusters were linked to the EOF patterns with clear meteorological meanings, which are associated with the evolution of ridges and troughs over northeastern China. Those systems relate to warm and cold advections at 850 hPa. In each H500 cluster, the advection is the major contributor leading to temperature changes at 850 hPa, which significantly relates to the changes and anomalies of daily minimum air temperature at 2 m (T2min). Furthermore, the jet activities over Asia relate to more or less occurrence of specific H500 clusters in jet phases. This is because anomalous westerlies are generally in favor of positive anomalies of the vorticity tendency at 500 hPa. For the reforecasts during 2004–19 in the Chinese Meteorology Administration (CMA) S2S model, the hit rates above 50% for all the H500 clusters are within 9.5 days, which are in between those for the first two and the last two clusters. The correct prediction of H500 anomalies improves the T2min prediction up to 12 days, compared with 8 days for the incorrect one. The good prediction of the jet activities leads to a more accurate prediction of H500 anomalies. Therefore, improvement of the model prediction of jet activities and H500 anomalies will lead to better prediction of winter weather near the ground over northeastern China.

A Chart Review for Epidemiology and Outcome of Fungal Bloodstream Infections Among Neonates in a Tertiary Care Hospital at North India

Background and Aims The risk of fungal bloodstream infection (BSI) and accompanying mortality in neonates varies widely in between centres depending on the region, the population characteristics and the risk factors. Methods This chart review of neonatal cases with fungal BSI admitted in a tertiary care teaching hospital in North India aimed to comprehensively investigate the epidemiology, profile of fungal species (and their susceptibility to various antifungal agents), risk factors, clinical profile and outcomes in these neonates. The study spanned over a one-year period, from September 2022 to August 2023, included all symptomatic neonates with positive blood cultures for fungal pathogen. Results Over one year, 24 out of 1,174 neonates at risk were diagnosed with fungal BSI, with a cumulative risk of 2.0 per 100 neonates. A peak in cases occurred in February. Candida pelliculosa was the predominant species (75% of isolates), while Candida albicans constituted 4.2%. Most isolates were sensitive to fluconazole, except for some fluconazole-resistant Candida pelliculosa (5.5%) and Candida tropicalis (25.0%), which remained susceptible to amphotericin-B and voriconazole. Around 60% of neonates were preterm, 40% had very low birth weight and 37% were small for gestational age. Nearly all had received prior broad-spectrum antibiotics, with 92% receiving prolonged courses over five days. Respiratory support, including intubation and mechanical ventilation, was used in 83% before onset of fungal sepsis. Intriguingly, all neonates had some invasive device in place for more than seven days. Mortality rate of 25% was observed, with preterm birth and gastrointestinal anomalies contributing to adverse outcomes. Conclusions This study confirms the ongoing shift in trend from albicans to non-albicans Candida infections in our region as well. A seasonal peak of fungal sepsis noted in the month of February hinted at potential seasonal variation or lapses in infection control practices during colder months. The analysis of trends in fungal BSI might hold a significance within neonatal intensive care units (NICUs) for the prompt detection of outbreaks. Simultaneously, understanding and analysing risk factors associated with fungal BSI are essential for targeted prevention.

Modeling of ecological niches of Barbary Partridge (Alectoris barbara) under conditions of bioclimatic variability in the Fes-Meknes region (Morocco)

Abstract The Barbary Partridge (Alectoris barbara) is a bird species belonging to the Phasianidae family and is endemic to North Africa, including Morocco. Effective conservation of this species requires a thorough understanding and accurate assessment of the environmental factors that influence reproductive parameters. In this study, we used the species distribution models (SDM) to study the geographical distribution of the Barbary Partridge in Morocco. These models are tools that allow us to study the effects of climate change on the spatial distribution of species, they are based on the Maxent (maximum entropy) algorithm. These models are based on environmental and biological data and can predict the probability of a species’ occurrence in a given geographic area. They can also predict how climatic and environmental conditions will change over time and how these changes will affect the species’ distribution. The results obtained revealed that the environmental factors that have a significant influence on the distribution area of Barbary Partridge under Moroccan conditions are: annual precipitation (Bio12) with a contribution rate of 23.3%; precipitation of the driest quarter (Bio17) at 19.9%; altitude at 9.9%; minimum temperature of the coldest month (Bio 6) at 7.6%; precipitation of the driest month (Bio14) at 7.2%; and mean temperature of the wettest quarter (Bio8) at 4.4%. This information can be used to assist in long-term conservation planning by identifying areas that may become more or less suitable for the species.

Understanding how winter conditions in the North Atlantic affect the physiology and behaviour of Atlantic Salmon in sea-cages

In recent years there have been a number of instances where declines in water temperature are suspected to have contributed to winter mortalities at salmon cage-sites in Atlantic Canada. In addition, it is expected that temperature variability due to more intense and frequent winter storms will increase with climate change, and this may further threaten Atlantic salmon health and welfare in sea-cages. To better understand cage-site conditions and aspects of salmon behaviour and physiology during the winter, we fitted Atlantic salmon in commercial size sea-cages in Newfoundland (Canada) for two consecutive years with internal and external data storage tags (DSTs) that recorded depth, temperature, heart rate (fH) and 3D-acceleration (swimming activity). Tags were surgically attached / implanted in late October / early November when water temperatures were 8–10 °C, and the DSTs were collected at the time of harvest. Although tag retrieval was limited due to some early mortality, challenges due to Covid-19 and with fish identification during harvest, the data collected for both years were comparable.Water temperature decreased at a rate of 0.35–0.57 °C week−1 from October / November to March, and the coolest average weekly temperature experienced by the fish was 1.10 °C in early March of both years. Average fH decreased with temperature starting in the fall, and the fish primarily occupied the upper 5 m of the cage for the duration of this study, despite the fact that temperatures were generally homogeneous with depth. Nonetheless, vertical migrations to deeper depths were observed during some periods (e.g., at night during the coldest months), and thus, the average depth of the fish was greater during these times.These data reveal that temperatures in sea-cages in Newfoundland remain below 5 °C for ~5 months and are below 2 °C for ~1.5 months. Thus, understanding how cold temperatures affect various aspects of salmon biology, and monitoring these fish during this period, is critical to the sustainability and future of this industry.

Comparison of GARP and MaxEnt in Modeling Current and Future Geographic Distribution of Ceracris nigricornis Walker (Acrididae, Orthoptera) in China.

Ceracris nigricornis Walker is an insect of the Acrididae, which can harm bamboo, rice, corn, sorghum and other crops, and can cause serious economic losses. In this study, based on 234 occurrence sites of C. nigricornis obtained from the Global Biodiversity Information Facility and literature, and data of three future climate scenarios presented by CMIP6, two niche models (GARP, MaxEnt) were used to predict the suitable area of C. nigricornis in China. The result shows that the main environmental factors affecting the distribution of C. nigricornis are min temperature of coldest month (bio6), mean temperature of coldest quarter (bio11), precipitation of driest month (bio14) and precipitation of wettest quarter (bio16). From the result of MaxEnt model, it can be seen that the suitable area of C. nigricornis in China is 128.91 × 104 km2 under current scenario. It will decrease by 3.19% in the 2050s and then increase by 12.04% in the 2090s under the SSP1-2.6 scenario, increase by 5.79% in the 2050s and then decrease by 7.53% in the 2090s under the SSP2-4.5 scenario, and increase by 33.03% in 2050s and then decrease by 23.31% in the 2090s under SSP5-8.5 scenario. From the result of GARP model, it can be seen that the suitable area of C. nigricornis in China is 166.09 × 104 km2 under current scenario. It will increase by 8.41% in 2050s and then continue to increase by 6.11% in 2090s under SSP1-2.6 scenario, increase by 23.84% in the 2050s and then decrease by 0.88% in the 2090s under the SSP2-4.5 scenario, and increase by 34.37% in 2050s and then decrease by 1.75% in 2090s under SSP5-8.5 scenario. The boundaries of suitable areas will expand to the north and southwest of China under future climate change scenarios, specially in Sichuan, Chongqing and Yunnan. Local forestry authorities should strengthen the monitoring of bamboo forests to prevent the damage caused by the introduction of C. nigricornis.

Venturing Into the Unknown: The Importance of Variable Selection When Modelling Alien Species Under Non‐Analogue Climatic Conditions

ABSTRACTSpecies distribution models (SDMs) are widely used to address species' responses to bioclimatic conditions in the fields of ecology, biogeography and conservation. Among studies that have addressed reasons for model prediction variability, the impact of climatic variable selection has received limited attention and is rarely assessed in sensitivity analyses. Here, we tested the assumption that this aspect of model design is a major source of uncertainty, especially when projections are made to non‐analogue climates. As a study system, we used 142 alien plant species introduced to the sub‐Antarctic islands. Based on global occurrence data, we fitted SDMs as functions of seven bioclimatic variable sets that only differed in the identity of two temperature variables. Moreover, we calculated the overlap between the island's climatic conditions and the niches the species have realised outside of the islands. Despite comparable internal evaluation metrics, projections of these models were in sharp contrast with each other, with some models predicting the sub‐Antarctic islands' climate to be almost ubiquitously suitable to most species and others unsuitable to almost all species. In particular, the mean temperature of the warmest month led to strong underpredictions of the SDMs, while its replacement by the mean temperature of the coldest month led to massive overpredictions. Partitioning the variance in projections demonstrated that predictor identity was its most important source, followed by island and species identity. The size of area projected to be suitable was also related to the overlap in predictor values realised in the global range of species (outside of the islands) and on the islands. Our findings emphasise the importance of bioclimatic variable selection in SDMs, especially when making projections to non‐analogue climates. Such extrapolations are often required, especially when using SDMs to assess invasion risk under both current and future climates.