Seasonal Activity Research Articles

Local and Regional Diurnal Variability of Aerosol Properties Retrieved by DSCOVR/EPIC UV Algorithm

AbstractThe hour‐to‐hour variability of 388 nm aerosol optical depth (AOD) and single scattering albedo (SSA) derived from near UV observations by the Earth Polychromatic Imaging Camera (EPIC) on the Deep Space Climate Observatory has been evaluated at multiple locations around the world. AOD retrievals by the EPIC near UV algorithm (EPICAERUV) have been compared to ground based AOD measurements at 16 Aerosol Robotic Network (AERONET) stations representative of the most commonly observed aerosol types over geographic regions in three continents. Obtained results show that, in general, the EPICAERUV algorithm reproduces closely the hour‐to‐hour AOD variability reported by AERONET ground‐truth observations. Although most sites in the analysis show high correlation between the AOD hourly measurements by the ground‐based and space‐borne measuring techniques. Best algorithm performance is observed in the presence of carbonaceous and desert dust aerosols. The diurnal cycle of the retrieved SSA product was also analyzed. Although, a direct comparison of hourly EPICAERUV retrievals to equivalent ground‐based observations was not possible, the satellite result shows that diurnal SSA variability as large as 0.05 can be observed mostly associated with carbonaceous aerosols. EPICAERUV observed diurnal cycle of retrieved AOD on a regional basis was examined for the unusually active seasons of aerosol production of Saharan desert dust aerosols in 2020, and during the 2023 Canadian wildfires. Results presented in this study confirm the EPIC near UV aerosol product is well suited for observing diurnal variability of aerosols and, therefore, it is an important resource for climate and air quality studies.

Forbs, graminoids, and lepidopterans: breadth and seasonal variation in the diet of the New Mexico jumping mouse (Zapus luteus)

Abstract The New Mexico Jumping Mouse (Zapus luteus) is a federally endangered granivore active for only 3 to 5 months annually. Knowledge of diet can help guide habitat recovery and yet despite calls for restoration of its riparian habitat, the diet of Z. luteus remains largely unknown. To date, only 8 plant species have been described in the diet—whereas insectivory, mycophagy, and dietary shifts have only been hypothesized. In the late summer, Z. luteus rapidly accumulates fat for a 9-month hibernation and restoration may fail if seasonal variation in the diet is overlooked. We used DNA metabarcoding on fecal DNA (n = 165) to resolve dietary taxa within multiple trophic levels of the diet and investigate monthly patterns of consumption. Seldom studied in metabarcoding frameworks, we also investigated exogenous contamination in Sherman live-capture traps. Potential contamination among feces, pelage, and trap surfaces was detectable but low (median = 0% to 2%), with fecal communities distinct from exogenous sources. The diet of Z. luteus was varied and most frequently (frequency of occurrence) of graminoids, forbs, lepidopterans, dipterids, and false-truffles. For plant foods, dietary diversity increased throughout their season of activity, shifting from sedges and woody vegetation in the early season (June to July) to forbs and grasses in the late season (August to September). Insect consumption was consistently detected throughout the season, whereas mycophagy was more frequently detected in August, when hypogeous fungi are typically more abundant. The breadth of dietary taxa suggests plasticity in resource use, potentially accommodating diverse patterns of seed availability throughout their active period. Shifts in plant consumption may reflect a dietary adaptation to the phenological patterns of their plant communities, a synchrony that might benefit both pre- and post-hibernation survival. Our work substantially improves our understanding of the diet of Z. luteus (241 dietary taxa) and will be useful for guiding habitat recovery. It also offers scalable methods to further investigate the diet under disturbance contexts (e.g., grazing, wildfire, drought).

Seasonal Photosynthetic Activity in the Crown Compartments of European Ash (Fraxinus excelsior)

Leaves facing different directions (north, south, east, and west) receive differing levels of illumination, resulting in spatial differences in photosynthesis PN in the crowns of mature trees. We measured diurnal trends in PN for a semi-solitary European ash (Fraxinus excelsior) over spring, summer, and autumn and compared these data with leaf biometric traits and leaf area distribution. The highest light-saturated PN (PNmax) was to the south and west, and the lowest to the north. Likewise, intrinsic water use efficiency, defined as the ratio (PN/gS) of photosynthetic rate (PN) and stomatal conductance (gS), was also lowest to the north. The thickest leaves were found on the northern face and the thinnest in the south, suggesting differences in leaf anatomy may have contributed to differences in PN. The greatest leaf area was recorded in the southern crown quadrant, which contributed more than 50% of the tree’s accumulated PN. Our research emphasises the importance of choosing representative leaves for gas exchange measurements. In-depth studies into the spatial distribution of leaves and their traits will be necessary for accurate upscaling of leaf-level photosynthesis to whole tree and canopy levels.

Seasonal prediction of tropical cyclones activity in the North Indian Ocean during post‐monsoon months

AbstractThe frequency and power dissipation index (PDI) of tropical cyclones (TCs) in the North Indian Ocean (NIO) has dramatically grown over the last 10 years, according to our analysis utilizing the European Centre for Medium Range Weather Forecasts reanalysis version‐5 (ERA5) dataset and the India Meteorological Department (IMD) best track data over the period 1982–2021. Our findings indicate that the recent increase in the post‐monsoon TC PDI over NIO is caused by a reduction in wind shear and an increase in convective available potential energy over the Bay of Bengal. The importance of improving our understanding and developing more accurate predictions of the TCs activity has increased as TCs become more frequent and intense owing to the effects of global warming. This study therefore develops TC prediction models for frequency and PDI over NIO for various lead times that vary from 2 to 8 months in addition to the trend analysis employing the ERA5 and IMD best track data. The potential predictors used in proposed model are surface temperature (2 m temperature over land and sea surface temperature over oceanic regions), vertical wind shear, winds (zonal, meridional), geopotential height and temperature at different pressure levels during January–August. The developed models are remarkably accurate (skill is ~94%) in forecasting TCs frequency and PDI. The proposed models outperform the best performing models that are already in use for long‐range TC activity prediction. With a lead‐time as long as up to 8 months, this effort is the first to investigate the possibility of forecasting the frequency and PDI of post‐monsoon TC activity over the NIO with good accuracy. Therefore, the developed models show an operational potential for seasonal TC activity forecast over the NIO.

Evaluation of Absconding Rate, Foraging and Defensive Behaviour in <i>Apis mellifera monticola</i>

Honey bee colonies display a wide range of behavioural variations based on their genetic origin and environmental factors. It is crucial to evaluate the absconding, foraging, and defensive behaviour of different honey bee races to lay the groundwork for future selection and improvement in Ethiopia. For this study, we kept 90 colonies of Apis mellifera monticolla, with 30 colonies/ agroecology, in improved box hives. These colonies were similar in terms of the resources contained in the hive. During the active seasons of September to December 2021 and April to June 2022, an assessment of the foraging activity, defensive behaviour, and absconding rate was done. The study revealed that colonies of A.m.monticola exhibited an average response time of 53.29 sec to disturbances, indicating their defensive behaviour. Additionally, these colonies demonstrated a willingness to pursue intruders for distances of up to 182.42 m. These colonies were excellent foragers, beginning their activities at 8:13 a.m. and returning to the hive by 10:04 p.m. Moreover, A.m. monticolla showed an absconding rate ranging from 1.90 to 4.28% when faced with disruptions. To ensure optimal colony health and productivity, it is advisable to conduct further research on the selection of high-performing colonies.

Comparison of Air Pollutants during the Two COVID-19 Lockdown Periods in Winter 2019 and Spring 2022 in Shanghai, China

During the winter of 2019, the global outbreak of COVID-19 prompted extensive research on urban air pollution under lockdown measures. However, these studies predominantly focused on winter conditions, thereby limiting investigations into changes in urban air pollutants during other seasons that were also subject to lockdown restrictions. Shanghai, China, has undergone two COVID-19 lockdown periods in two seasons: winter 2019 and spring 2022. The seasonal variations and human activities were represented by meteorological factors and nighttime light brightness in this paper, respectively. The reduction in human-related emissions during the two lockdown periods was estimated based on the targets outlined in China’s Air Pollution Prevention and Control Action Plan. The results showed significant reductions in NO2 and PM particles during the two lockdown periods, both accompanied by a notable increase in O3 concentration. In comparison to the winter lockdown, there was an approximate 40% decrease in the NO2 and PM2.5 concentrations in the spring, while the O3 concentration exhibited an increase of 48.81%. Furthermore, due to shifting wind patterns during the two lockdowns from winter to spring, the high-pollution core areas shifted 20–25 km southeastward in the spring. The PM particles and NO2 concentrations exhibited a considerable impact from human activities, whereas the O3 concentration was affected mostly by seasonal change and interactions among air pollutants. Compared to the corresponding non-lockdown condition, the concentration of CO decreased during the winter lockdown; however, it increased during the spring lockdown. The different change in CO concentration during the two lockdown periods was found to have a lower effect on the O3 concentration than that caused by changes in meteorological factors and nitrogen oxide (NO, NO2) concentrations. In summary, the impact of COVID-19 lockdown periods on urban air pollutants was more pronounced in spring compared to winter, and the interactions among air pollutants also underwent alterations.

Mosquitoes in urban green spaces and cemeteries in northern Spain

BackgroundMosquitoes inhabiting urban green spaces and cemeteries in Europe represent a crucial facet of public health concern and contribute to the ecological balance. As urbanization intensifies, these areas increasingly serve as vital habitats for various mosquito species, fostering breeding grounds and increasing the risk of disease transmission.MethodsA study was conducted in the three main cities (inland, coastal, and estuarine) of the Basque Country, northern Spain, to investigate the species composition, abundance, dynamic populations, larval habitats, and host preferences of mosquitoes in urban green spaces and cemeteries. CDC traps and dipping were used to collect mosquitoes for 2 years (2019–2020).ResultsA total of 21 mosquito species were identified, with Culex pipiens s.l. being the most abundant and widespread. The three ecological forms of Cx. pipiens were found, and Cx. pipiens pipiens was the most common in both green areas and cemeteries. Morphological identification together with molecular tools identified 65 COI sequences with high homology. The highest species richness was found in the inland city, followed by the coastal city and the estuarine city. Mosquito abundance was significantly higher in green areas compared to cemeteries and in the coastal and estuarine cities compared to the inland city. The investigation of larval breeding sites highlighted the dominance of Cx. pipiens s.l., particularly in semi-artificial ponds, diverse water-holding containers (tyres and buckets) and drainage systems in green areas; in cemeteries, most of the larvae were found in flowerpots and funerary urns. Seasonal activity exhibited variable peaks in mosquito abundance in the different cities, with a notable increase in July or August. Additionally, blood meal analysis revealed that Cx. pipiens s.l. fed on several common urban avian species.ConclusionsStudies on mosquitoes are essential to understand their role in disease transmission and to design targeted and sustainable management strategies to mitigate the associated risks.Graphical

Seasonal activity patterns of a Kalahari mammal community: Trade-offs between environmental heat load and predation pressure.

Mammals in arid zones have to trade off thermal stress, predation pressure, and time spent foraging in a complex thermal landscape. We quantified the relationship between the environmental heat load and activity of a mammal community in the hot, arid Kalahari Desert. We deployed miniature black globe thermometers within the existing Snapshot Safari camera trap grid on Tswalu Kalahari Reserve, South Africa. Using the camera traps to record species' activity throughout the 24-h cycle, we quantified changes in the activity patterns of mammal species in relation to heat loads in their local environment. We compared the heat load during which species were active between two sites with differing predator guilds, one where lion (Panthera leo) biomass dominated the carnivore guild and the other where lions were absent. In the presence of lion, prey species were generally active under significantly higher heat loads, especially during the hot and dry spring. We suggest that increased foraging under high heat loads highlights the need to meet nutritional requirements while avoiding nocturnal activity when predatory pressures are high. Such a trade-off may become increasingly costly under the hotter and drier conditions predicted to become more prevalent as a result of climate change within the arid and semi-arid regions of southern Africa.

Effectiveness of Malaise trap and sweep net sampling in sawfly research (Hymenoptera: Symphyta)

Malaise traps and sweep nets are commonly used to study sawfly faunas, seasonality and communities. Here we analyse a large dataset obtained with these methods in Slovakia and Hungary over the last two and a half decades. The dataset included collections from twenty-one sites, each covering the entire growing season, eleven of which were obtained with the Malaise trap and ten with the sweep net. We conclude that both methods are suitable for faunistic studies of sawflies (Hymenoptera, Symphyta), although they may lead to certain biased results for some Symphyta groups. Special attention should be paid to Siricidae, Orussidae, Xiphidriidae and Cimbicidae, which were only weakly recorded with both methods. Argidae, Blennocampinae, Dolerinae and Tenthredininae were underrepresented in the Malaise trap samples and Allantinae in the sweep net samples. Both methods gave equally good results in measuring species richness in an one-year study. Ideally, they should be used together as they complement each other well. The net method has a great advantage in determining the exact population density. In contrast, the Malaise trap collections were often heavily dominated by only a few species, with males being preferentially trapped. Use of Malasie trap should be preferred for the study of seasonal flight activity.

Baltic Sea coastal sediment-bound eukaryotes have increased year-round activities under predicted climate change related warming.

Climate change related warming is a serious environmental problem attributed to anthropogenic activities, causing ocean water temperatures to rise in the coastal marine ecosystem since the last century. This particularly affects benthic microbial communities, which are crucial for biogeochemical cycles. While bacterial communities have received considerable scientific attention, the benthic eukaryotic community response to climate change remains relatively overlooked. In this study, sediments were sampled from a heated (average 5°C increase over the whole year for over 50 years) and a control (contemporary conditions) Baltic Sea bay during four different seasons across a year. RNA transcript counts were then used to investigate eukaryotic community changes under long-term warming. The composition of active species in the heated and control bay sediment eukaryotic communities differed, which was mainly attributed to salinity and temperature. The family level RNA transcript alpha diversity in the heated bay was higher during May but lower in November, compared with the control bay, suggesting altered seasonal activity patterns and dynamics. In addition, structures of the active eukaryotic communities varied between the two bays during the same season. Hence, this study revealed that long-term warming can change seasonality in eukaryotic diversity patterns. Relative abundances and transcript expression comparisons between bays suggested that some taxa that now have lower mRNA transcripts numbers could be favored by future warming. Furthermore, long-term warming can lead to a more active metabolism in these communities throughout the year, such as higher transcript numbers associated with diatom energy production and protein synthesis in the heated bay during winter. In all, these data can help predict how future global warming will affect the ecology and metabolism of eukaryotic community in coastal sediments.

Streamflow response to catastrophic windthrow and forest recovery in subalpine spruce forest

Windstorms account for about half of forest disturbances in Europe and are considered as drivers of natural regeneration of plant species, accompanied by significant changes in hydrological and soil moisture conditions. Our study aims to identify the effects of deforestation caused by catastrophic windthrow on streamflow characteristics in conjunction with meteorological and soil moisture data. The research was conducted in the headwater catchment (34.4 km2), in the Western Tatra Mountains, Poland. Streamflow characteristics such as average, high, and low flows, coefficient of variability, as well as flashiness of the streamflow (Richard-Baker Flashiness Index) and drought frequency (Standardised Streamflow Index) were calculated in the pre-event (2007–2013) and post-event (2013–2020) periods. The analysis was carried out for calendar months, seasons of the year, as well as for the growing and non-growing seasons. Wavelet Analysis was applied to track the changes in streamflow time series in relation to meteorological conditions (precipitation, air temperature) and remotely sensed soil wetness in the root zone. Principal Components Analysis was applied in order to identify the major drivers of the observed variability. The results revealed increasing low (+14%), average (+8%), and maximum monthly flows (16%) in the post-event period. The most significant increase in low flows (+47%, p<0.1) occurred during snowmelt. The increase in average (+31%, p<0.1) and high flows (+90%, p<0.05) occurred during mid-winter thaws. The frequency of hydrological droughts decreased by up to 36% in the post-event period, despite similar climatic conditions. The flashiness of streamflow increased during mid-winter thaws and rainfall events. The short-scale periodicity in streamflow increased in the post-event period. The results revealed the presence of 3-month periodicity in the root zone soil wetness associated with long-term soil water storage, which decreased after the catastrophic windthrow. Streamflow in the post-event period became strongly coupled with precipitation and root zone soil wetness at short period bands (∼3–16 days) in hydrologically active season. Short-scale correlation between precipitation and streamflow was decreasing with the gradual succession of vegetation.

Mixing-layer-height-referenced ozone vertical distribution in the lower troposphere of Chinese megacities: stratification, classification, and meteorological and photochemical mechanisms

Abstract. Traditional tropospheric ozone (O3) climatology uses a simple average substantially smoothed stratification structure in individual O3 profiles, limiting our ability to properly describe and understand how O3 is vertically distributed at the interface between the mixing layer (ML) and free troposphere (FT). In this study, we collected 1897 ozonesonde profiles from two Chinese megacities (Beijing and Hong Kong) over the period 2000–2022 to investigate the climatological vertical heterogeneity of the lower-tropospheric O3 distribution with a mixing-layer-height-referenced (h-referenced) vertical coordinate system. The mixing-layer height (h) was first estimated following an integral method that integrates the information of temperature, humidity, and cloud. After that, a so-called h-referenced vertical distribution of O3 was determined by averaging all individual profiles expressed as a function of z/h rather than z (where z is altitude). We found that the vertical stratification of O3 is distributed heterogeneously in the lower troposphere, with stronger vertical gradients at the surface layer and ML–FT interface. There are low vertical autocorrelations of O3 between the ML and FT but high autocorrelations within each of the two atmospheric compartments. These results suggest that the ML–FT interface acts as a geophysical “barrier” separating air masses of distinct O3 loadings. This barrier effect varies with season and city, with an ML–FT detrainment barrier in summer (autumn) and an FT–ML entrainment barrier in other seasons in Beijing (Hong Kong). Based on a Student's t test, daily h-referenced O3 profiles were further classified into three typical patterns: MLO3-dominated, FTO3-dominated, and uniform distribution. Although the FTO3-dominated pattern occurs most frequently during the whole study period (69 % and 54 % of days in Beijing and Hong Kong, respectively), the MLO3-dominated pattern prevails in the photochemically active season, accounting for 47 % of summer days in Beijing and 54 % of autumn days in Hong Kong. These occurrences of the MLO3-dominated pattern are significantly more frequent than in previously reported results at northern mid-latitudes, indicating intensive photochemical MLO3 production under the high-emission background of a Chinese megacity. From a FTO3-dominated to MLO3-dominated pattern, the O3 precursor CH2O (NO2) experiences a substantial increase (decrease) in Beijing but a slight change in Hong Kong. Vertically, the increment of CH2O is larger in the upper ML, and the decrement of NO2 is larger in the lower ML. Such vertical changes in O3 precursors push O3 production sensitivity away from the VOC-limited regime and facilitate high-efficiency production of O3 via photochemical reactions, particularly in the upper ML of Beijing.

Regionalization of the Onset and Offset of the Rainy Season in Senegal Using Kohonen Self-Organizing Maps

This study explores the spatiotemporal variability of the onset, end, and duration of the rainy season in Senegal. These phenological parameters, crucial for agricultural planning in West Africa, exhibit high interannual and spatial variability linked to precipitation. The objective is to detect and spatially classify these indices across Senegal using different approaches. Daily precipitation data and ERA5 reanalyses from 1981 to 2018 were utilized. The employed method enables the detection of key dates. Subsequently, the Kohonen algorithm spatially classifies these indices on topological maps. The results indicate a meridional gradient of the onset, progressively later from the southeast to the northwest, whereas the end follows a north–south gradient. The duration varies from 45 days in the north to 150 days in the south. The use of self-organizing maps allows for classifying the onset, end, and duration of the season into four zones for the onset and end, and three zones for the duration of the season. They highlight the interannual irregularity of transitions, with both early and late years. The dynamic analysis underscores the complex influence of atmospheric circulation fields, notably emphasizing the importance of low-level monsoon flux. These findings have tangible implications for improving seasonal forecasts and agricultural activity planning in Senegal. They provide information on the onset, end, and duration classes for each specific zone, which can be valuable for planning crops adapted to each region.

How well do multi-fire danger rating indices represent China forest fire variations across multi-time scales?

To better support wildfire predictions and risk assessment, multiple fire danger rating indices (FDRIs) have been developed but their credibility in China remains obscure. Compared with the satellite fire observations, 13 FDRIs are evaluated for the historical (2003–2021) forest fire frequency in China from four different time scales: active seasons, trends, interannual variations (IAVs) and discrimination of fire/non-fire days (DFDs). Most FDRIs effectively capture the double active seasons over Southwest China and the dominant active season over Northeast and South China but fail over the other regions. FDRIs with cloud cover perform better in capturing climatological fire seasonality. All FDRIs fail to reproduce the significant decreasing trend of forest fires speculatively due to local fire management and discordant changes in meteorological elements. Most FDRIs have the advantages of the IAVs and DFDs over Southwest China but exhibit deficiencies over the other regions. FDRIs incorporating wind speed perform best in representing both IAVs and DFDs, indicating the indispensable effect of surface wind on the interannual/daily variation of fire danger. This study provides a credible reference for utilizing FDRIs in China, as well as offers insights for developing better regional FDRIs to represent different time-scale variations.

Spatial and temporal assessment of snake encounters in urban Delhi, India

Delhi, the capital city of India is, highly urbanized and surrounded by remnant forest, farms, ridges, and other green areas experience regular snake encounters in and around residential, institutional, and industrial areas. A total of 41 months of sampling from January 2019 to May 2022 was conducted wherein we, studied the snake assemblage in Delhi to determine the species composition, encounter frequency, seasonal activity patterns, and probable encounter sites in an urban setup. We documented 372 individuals belonging to 15 species from seven families out of 23 species found in Delhi. Snakes were found inside forests, public parks, homes, drain networks, streets, office buildings, and even in school-college buildings. The most recorded species being Ptyas mucosa (37.37%, n = 139), Naja naja (19.62%, n = 73), and Lycodon aulicus (13.44%, n = 50). The highest numbers of incidents were reported in the month of July (22.04%, n = 82) and August (19.89%, n = 74) during the peak monsoon season, for identifying high encounter sites, we used a geostatistical modeling tool, Ordinary kriging to identify places having more snake occurrences. We further used a statistical spatial method called average nearest neighbor distance to detect the pattern distribution of snake species. Spatial interpolation done through Ordinary kriging highlighted two areas having concentrated snake encounters. The results of the average nearest neighbor distance analysis showed three species having clustered and two species having dispersed distribution. The incidence of snake encounters was found to be highly seasonal and appeared to be associated mainly with monthly rainfall, temperature, and humidity. The findings of this study on snakes’ distribution patterns provide valuable insights into the conservation of these species. Understanding their habitat preferences and spatial distribution is crucial for the implementation of effective conservation strategies.

Influence of spatial and seasonal asymmetries on long-range tropical cyclone prediction in the western North Pacific

The seasonal predictability of tropical cyclones (TC) in the western North Pacific (WNP) reported in previous studies are mainly based under the general consideration that the WNP is homogeneous in terms of its spatial and temporal characteristics. Here we present evidence that the western (Domain 1) and eastern (Domain 2) parts of the WNP exhibit spatial and seasonal asymmetric response to large-scale environments (e.g., asymmetrical sea surface temperature anomalies distribution) leading to distinct spatial and seasonal TC variability in the said domains. Exploring such asymmetries, we propose an alternative approach on the long-range predictability of TC genesis frequency in the WNP during its active TC season (i.e., June-November, JJASON) by separately predicting the TC genesis frequency in two domains (i.e., Domains 1 and 2) in two distinct seasons (i.e., June-August and September-October), respectively. Using a number of climate indices as predictors in different lead times, our regression-based models present its best significant seasonal predictability of TC genesis frequency during JJASON (i.e., r = 0.80, p < 0.01) that essentially captures the spatial and seasonal asymmetry in the WNP. It is expected that this study provides valuable insights on the long-range and more localized TC prediction in support of disaster risk reduction in the WNP region.

The use of environmental data in descriptive and predictive models of vector-borne disease in North America.

Vector-borne disease incidence and burden are on the rise. Weather events and climate patterns are known to influence vector populations and disease distribution and incidence. Changes in weather trends and climatic factors can shift seasonal vector activity and host behavior, thus altering pathogen distribution and introducing diseases to new geographic regions. With the upward trend in global temperature, changes in the incidence and distribution of disease vectors possibly linked to climate change have been documented. Forecasting and modeling efforts are valuable for incorporating climate into predicting changes in vector and vector-borne disease distribution. These predictions serve to optimize disease outbreak preparedness and response. The purpose of this scoping review was to describe the use of climate data in vector-borne disease prediction in North America between 2000 and 2022. The most investigated diseases were West Nile virus infection, Lyme disease, and dengue. The uneven geographical distribution of publications could suggest regional differences in the availability of surveillance data required for vector-borne disease predictions and forecasts across the United States, Canada, and Mexico. Studies incorporated environmental data from ground-based sources, satellite data, previously existing data, and field-collected data. While environmental data such as meteorological and topographic factors were well-represented, further research is warranted to ascertain if relationships with less common variables, such as oceanographic characteristics and drought, hold among various vector populations and throughout wider geographical areas. This review provides a catalogue of recently used climatic data that can inform future assessments of the value of such data in vector-borne disease models.

Molecular and haematological investigations on Anaplasma ovis infection in goats in Ahvaz, Iran: Insights into infection rate, haemolytic effect and breed influences.

Anaplasma ovis (A. ovis) is the predominant causative agent of anaplasmosis in goats and sheep in most tropical and subtropical regions of the world. However, there is considerable variation in reported infection rates, breed susceptibility, and controversial findings regarding the haemolytic effects of A. ovis infection in goats. Thus, we investigated the molecular and haematological aspects of A. ovis infection in goats from Ahvaz city. One hundred and fifty apparently healthy goats (74 blacks and 76 Najdi goats) were randomly sampled from six flocks in the Ahvaz suburb during ticks' activity season. Haematological evaluation, smear microscopic (SM) examination and PCR assay were performed to assess A. ovis infection. Additionally, the percentage of parasitemia was determined from blood smears. SM examination revealed that 25.7% of the goats displayed erythrocyte Anaplasma-like inclusion bodies. PCR analysis indicated that 54% of the goats were positive for A. ovis infection (44.6% of blacks and 63.2% of Najdi goats). No significant difference in haematological values was observed between healthy and infected goats based on PCR testing. However, a significant difference in haematological indices was observed between the group with parasitemia level of 0.01-0.02% (SM and PCR positive) compared to the healthy goats (SM and PCR negative), particularly concerning Hb, PCV and RBC count (p < 0.01). When the parasitemia exceeds 0.01%, A. ovis infection may disrupt haematological parameters in infected goats. The high prevalence of A. ovis infection (54%) among the studied goats underscores the importance of giving special attention to implementing necessary measures for disease control in the Ahvaz suburb.

Spatial Scales of Kinetic Energy in the Arctic Ocean

AbstractDespite the importance of the Arctic Ocean for the large‐scale circulation and climate, there is still a knowledge gap in our understanding of the spatial characteristics of the Arctic Ocean circulation, especially for the mesoscale. This paper investigates the spatial characteristics of the Arctic Ocean circulation using a simulation with 1 km horizontal resolution. We revealed that there are two peaks in the kinetic energy (KE) spectral density at the 400 m depth, one at the gyre scale of the Arctic Circumpolar Boundary Current (centered at 1,700–2,000 km), and the other associated with the mesoscale (at about 60 km). However, at the 70 m depth, the boundary currents tend to mask the spectrum peak associated with the mesoscale. The KE spectrum exhibits a power‐law scaling typical for ocean eddies. We found that about 80% (50%) of the KE is on scales smaller than 100 km (30 km). The maximum KE content is in the 10–20 km scale band in most of the eddy‐rich regions of the abyssal ocean. The seasonality of the KE spectrum and KE content inside the Arctic Ocean follow the seasonality of eddy activity and baroclinicity, with low values in spring and maxima in late summer to autumn, and the seasonal variation is stronger at the 70 m depth than the 400 m depth. The strong concentration of KE on the very small spatial scales warrants future studies on energy transfer between scales in the Arctic Ocean.

Evidence on the exposure Index’s substitution effect in assessing brook pollution risk in urban–rural fringe

Brooks are significant ecological sources and migration channels of material flow as well as energy flow in urban–rural fringes. Despite their significance, the absence of monitoring data poses challenges in assessing brook pollution risk. Taking Muli Brook as an example, a spatiotemporal variability of water quality was revealed through sample collection and water chemistry analysis. We reveal spatiotemporal variability of pollution and then developed an Exposure Index (EPI), verifying its substitution effect in assessing brook pollution risk. Our findings demonstrate a downward trend in pollution from 2020 to 2022, with exceptions in dissolved oxygen (DO) and pH. Notably, more severe pollution is observed during spring and summer, influenced by seasonal production activities and extreme weather events. Despite the diminishing disparity near urban areas, the cumulative influence of upstream pollutants outweighs that of surrounding human activities. Stronger associations between pollution risks and water area EPI were observed, compared to those of construction land and farm land. In conclusion, EPI emerges as a valuable tool for assessing brook pollution risks in urban–rural fringes, offering precise insights into brook habitat characteristics, especially in the absence of consistent monitoring data.