Research on the spatial and temporal patterns of ozone concentration and population health effects in the Central Plains Urban Agglomeration from 2017 to 2020.

Fine particulate matter (PM2.5) and near-surface ozone (O3) are the main atmospheric pollutants in China. Long-term exposure to high ozone concentrations adversely affects human health. It is of great significance to systematically analyze the spatiotemporal evolution mechanism and health effects of ozone pollution. Based on the ozone data of 91 monitoring stations in the Central Plains Urban Agglomeration from 2017 to 2020, the research used Kriging method and spatial autocorrelation analysis to investigate the spatiotemporal variations of ozone concentration. Additionally, the study assessed the health effects of ozone on the population using the population exposure risk model and exposure-response relationship model. The results indicated that: (1) The number of premature deaths caused by ozone pollution in the warm season were 37,053 at 95% confidence interval (95% CI: 28,190-45,930) in 2017, 37,685 (95% CI: 28,669-46,713) in 2018, and 37,655 (95% CI: 28,647-46,676) in 2019. (2) The ozone concentration of the Central Plains urban agglomeration showed a decreasing trend throughout the year and during the warm season from 2017 to 2020, there are two peaks monthly, one is June, and the other is September. (3) In the warm season, the high-risk areas of population exposure to ozone in the Central Plains Urban Agglomeration were mainly concentrated in urban areas. In general, the population exposure risk of the south is lower than that of the north. The number of premature deaths attributed to ozone concentration during the warm season has decreased, but some southern cities such as Xinyang and Zhumadian have also seen an increase in premature deaths. China has achieved significant results in air pollution control, but in areas with high ozone concentrations and high population density, the health burden caused by air pollution remains heavy, and stricter air pollution control policies need to be implemented.

Mapping sedentary behaviour (MAPS-B) in winter and spring using wearable sensors, indoor positioning systems, and diaries in older adults who are pre-frail and frail: A feasibility longitudinal study.

Older adults who are frail are likely to be sedentary. Prior interventions to reduce sedentary time in older adults have not been effective as there is little research about the context of sedentary behaviour (posture, location, purpose, social environment). Moreover, there is limited evidence on feasible measures to assess context of sedentary behaviour in older adults. The aim of our study was to determine the feasibility of measuring context of sedentary behaviour in older adults with pre-frailty or frailty using a combination of objective and self-report measures. We defined "feasibility process" using recruitment (20 participants within two-months), retention (85%), and refusal (20%) rates and "feasibility resource" if the measures capture context and can be linked (e.g., sitting-kitchen-eating-alone) and are all participants willing to use the measures. Context was assessed using a wearable sensor to assess posture, a smart home monitoring system for location, and an electronic or hard-copy diary for purpose and social context over three days in winter and spring. We approached 80 potential individuals, and 58 expressed interest; of the 58 individuals, 37 did not enroll due to lack of interest or medical mistrust (64% refusal). We recruited 21 older adults (72±7.3 years, 13 females, 13 frail) within two months and experienced two dropouts due to medical mistrust or worsening health (90% retention). The wearable sensor, indoor positioning system, and electronic diary accurately captured one domain of context, but the hard copy was often not completed with enough detail, so it was challenging to link it to the other devices. Although not all participants were willing to use the wearable sensor, indoor positioning system, or electronic diary, we were able to triage the measures of those who did. The use of wearable sensors and electronic diaries may be a feasible method to assess context of sedentary behaviour, but more research is needed with device-based measures in diverse groups.

Brood indicators are an early warning signal of honey bee colony loss-a simulation-based study.

Honey bees (Apis mellifera) are exposed to multiple stressors such as pesticides, lack of forage, and diseases. It is therefore a long-standing aim to develop robust and meaningful indicators of bee vitality to assist beekeepers While established indicators often focus on expected colony winter mortality based on adult bee abundance and honey reserves at the beginning of the winter, it would be useful to have indicators that allow detection of stress effects earlier in the year to allow for adaptive management. We used the established honey bee simulation model BEEHAVE to explore the potential of different indicators such as population size, number of capped brood cells, flight activity, abundance of Varroa mites, honey stores and a brood-bee ratio. We implemented two types of stressors in our simulations: 1) parasite pressure, i.e. sub-optimal Varroa treatment by the beekeeper (hereafter referred as Biotic stress) and 2) temporal forage gaps in spring and autumn (hereafter referred as Environmental stress). Neither stressor type could be detected by bee abundance or honey reserves at the end of the first year. However, all response variables used in this study did reveal early warning signals during the course of the year. The most reliable and useful measures seem to be related to brood and the abundance of Varroa mites at the end of the year. However, while in the model we have full access to time series of variables from stressed and unstressed colonies, knowledge of these variables in the field is challenging. We discuss how our findings can nevertheless be used to develop practical early warning indicators. As a next step in the interactive development of such indicators we suggest empirical studies on the importance of the number of capped brood cells at certain times of the year on bee population vitality.

Assessment of environmental and spatial factors influencing the establishment of Anopheles gambiae larval habitats in the malaria endemic province of Woleu-Ntem, northern Gabon.

BACKGROUND: This study aimed to assess the spatial distribution of Anopheles mosquito larval habitats and the environmental factors associated with them, as a prerequisite for the implementation of larviciding. METHODS: The study was conducted in December 2021, during the transition period between the end of the short rainy season (September-November) and the short dry season (December-February). Physical, biological, and land cover data were integrated with entomological observations to collect Anopheles larvae in three major towns: Mitzic, Oyem, and Bitam, using the "dipping" method during the transition from rainy to dry season. The collected larvae were then reared in a field laboratory established for the study period. After the Anopheles mosquitoes had emerged, their species were identified using appropriate morphological taxonomic keys. To determine the influence of environmental factors on the breeding of Anopheles mosquitoes, multiple-factor analysis (MFA) and a binomial generalized linear model were used. RESULTS: According to the study, only 33.1% out of the 284 larval habitats examined were found to be positive for Anopheles larvae, which were primarily identified as belonging to the Anopheles gambiae complex. The findings of the research suggested that the presence of An. gambiae complex larvae in larval habitats was associated with various significant factors such as higher urbanization, the size and type of the larval habitats (pools and puddles), co-occurrence with Culex and Aedes larvae, hot spots in ambient temperature, moderate rainfall, and land use patterns. CONCLUSIONS: The results of this research mark the initiation of a focused vector control plan that aims to eradicate or lessen the larval habitats of An. gambiae mosquitoes in Gabon's Woleu Ntem province. This approach deals with the root causes of malaria transmission through larvae and is consistent with the World Health Organization's (WHO) worldwide objective to decrease malaria prevalence in regions where it is endemic.

Interim 2023/2024 Season Influenza Vaccine Effectiveness in Primary and Secondary Care in the United Kingdom.

BACKGROUND: We report 2023/2024 season interim influenza vaccine effectiveness for three studies, namely, primary care in Great Britain, hospital settings in Scotland and hospital settings in England. METHODS: A test negative design was used to estimate vaccine effectiveness. RESULTS: Estimated vaccine effectiveness against all influenzas ranged from 63% (95% confidence interval 46 to 75%) to 65% (41 to 79%) among children aged 2-17, from 36% (20 to 49%) to 55% (43 to 65%) among adults 18-64 and from 40% (29 to 50%) to 55% (32 to 70%) among adults aged 65 and over. CONCLUSIONS: During a period of co-circulation of influenza A(H1N1)pdm09 and A(H3N2) in the United Kingdom, evidence for effectiveness of the influenza vaccine in both children and adults was found.

Rotavirus trends and distribution of genotypes before and during COVID-19 pandemic era: Bangladesh, 2017-2021.

Rotavirus gastroenteritis is accountable for an estimated 128 500 deaths among children younger than 5 years worldwide, and the majority occur in low-income countries. Although the clinical trials of rotavirus vaccines in Bangladesh revealed a significant reduction of severe rotavirus disease by around 50%, the vaccines are not yet included in the routine immunization program. The present study was designed to provide data on rotavirus diarrhea with clinical profiles and genotypes before (2017-2019) and during the COVID-19 pandemic period (2020-2021). Fecal samples were collected from 2% of the diarrheal patients at icddr,b Dhaka hospital of all ages between January 2017 and December 2021 and were tested for VP6 rotavirus antigen using ELISA. The clinical manifestations such as fever, duration of diarrhea and hospitalization, number of stools, and dehydration and so on were collected from the surveillance database (n = 3127). Of the positive samples, 10% were randomly selected for genotyping using Sanger sequencing method. A total of 12 705 fecal samples were screened for rotavirus A antigen by enzyme immunoassay. Overall, 3369 (27%) were rotavirus antigen-positive, of whom children <2 years had the highest prevalence (88.6%). The risk of rotavirus A infection was 4.2 times higher in winter than in summer. Overall, G3P[8] was the most prominent genotype (45.3%), followed by G1P[8] (32.1%), G9P[8] (6.8%), and G2P[4] (6.1%). The other unusual combinations, such as G1P[4], G1P[6], G2P[6], G3P[4], G3P[6], and G9P[6], were also present. Genetic analysis on Bangladeshi strains revealed that the selection pressure (dN/dS) was estimated as <1. The number of hospital visits showed a 37% drop during the COVID-19 pandemic relative to the years before the pandemic. Conversely, there was a notable increase in the rate of rotavirus positivity during the pandemic (34%, p < 0.00) compared to the period before COVID-19 (23%). Among the various clinical symptoms, only the occurrence of watery stool significantly increased during the pandemic. The G2P[4] strain showed a sudden rise (19%) in 2020, which then declined in 2021. In the same year, G1P[8] was more prevalent than G3P[8] (40% vs. 38%, respectively). The remaining genotypes were negligible and did not exhibit much fluctuation. This study reveals that the rotavirus burden remained high during the COVID-19 prepandemic and pandemic in Bangladesh. Considering the lack of antigenic variations between the circulating and vaccine-targeted strains, integrating the vaccine into the national immunization program could reduce the prevalence of the disease, the number of hospitalizations, and the severity of cases.

Relationship between platelet-related parameters and new-onset atrial fibrillation after coronary bypass surgery.

OBJECTIVE: Inflammation plays a key role in the pathogenesis of postoperative atrial fibrillation after coronary artery bypass graft surgery. In this study, we aimed to investigate the changes in mean platelet volume and platelet values during the spring and autumn seasons in patients who underwent isolated coronary artery bypass graft surgery and the possible effect of these occurrences on postoperative atrial fibrillation. METHODS: Consecutive patients who underwent elective isolated coronary bypass surgery at our clinic in the spring and autumn months, between August 2020 and July 2022, were retrospectively included in this study. Variables were evaluated according to the spring and autumn seasons. Patients who did not develop in-hospital postoperative atrial fibrillation were identified as Group 1, and those who did constituted Group 2. RESULTS: A total of 622 patients were included in the study. The patients were divided into two groups: those who were operated on in the spring (n=277, median age=62 years, male gender ratio=77.3%) and those who were operated on in the autumn (n=345, median age=61 years, male gender ratio=81.4%). There was no statistically significant difference between the patients operated on in both seasons in terms of age, gender, hypertension rates, and the frequency of chronic obstructive pulmonary disease. In multivariate analysis, being over 70 years old (OR: 1.934, 95% confidence interval (CI) 1.489-2.995, p<0.001), having a left ventricular ejection fraction below 30% (OR: 1.550, 95%CI 1.190-2.236, p=0.012), and having chronic obstructive pulmonary disease (OR: 1.663, 95%CI 1.339-2.191, p<0.001) were found to be independent predictors in predicting the development of postoperative atrial fibrillation. CONCLUSION: In this study, we first demonstrated that mean platelet volume and platelet mass index values were higher in patients in the autumn months. Additionally, for the first time in the literature, we showed that there is a significant relationship between platelet mass index value and the development of postoperative atrial fibrillation in patients who underwent isolated coronary artery bypass graft.

A Novel Deep Learning Approach for Forecasting Myocardial Infarction Occurrences with Time Series Patient Data.

Myocardial Infarction (MI) commonly referred to as a heart attack, results from the abrupt obstruction of blood supply to a section of the heart muscle, leading to the deterioration or death of the affected tissue due to a lack of oxygen. MI, poses a significant public health concern worldwide, particularly affecting the citizens of the Chittagong Metropolitan Area. The challenges lie in both prevention and treatment, as the emergence of MI has inflicted considerable suffering among residents. Early warning systems are crucial for managing epidemics promptly, especially given the escalating disease burden in older populations and the complexities of assessing present and future demands. The primary objective of this study is to forecast MI incidence early using a deep learning model, predicting the prevalence of heart attacks in patients. Our approach involves a novel dataset collected from daily heart attack incidence Time Series Patient Data spanning January 1, 2020, to December 31, 2021, in the Chittagong Metropolitan Area. Initially, we applied various advanced models, including Autoregressive Integrated Moving Average (ARIMA), Error-Trend-Seasonal (ETS), Trigonometric seasonality, Box-Cox transformation, ARMA errors, Trend and Seasonal (TBATS), and Long Short Time Memory (LSTM). To enhance prediction accuracy, we propose a novel Myocardial Sequence Classification (MSC)-LSTM method tailored to forecast heart attack occurrences in patients using the newly collected data from the Chittagong Metropolitan Area. Comprehensive results comparisons reveal that the novel MSC-LSTM model outperforms other applied models in terms of performance, achieving a minimum Mean Percentage Error (MPE) score of 1.6477. This research aids in predicting the likely future course of heart attack occurrences, facilitating the development of thorough plans for future preventive measures. The forecasting of MI occurrences contributes to effective resource allocation, capacity planning, policy creation, budgeting, public awareness, research identification, quality improvement, and disaster preparedness.

Impact of persistently high sea surface temperatures on the rhizobiomes of Zostera marina in a Baltic Sea benthocosms.

Persistently high marine temperatures are escalating and threating marine biodiversity. The Baltic Sea, warming faster than other seas, is a good model to study the impact of increasing sea surface temperatures. Zostera marina, a key player in the Baltic ecosystem, faces susceptibility to disturbances, especially under chronic high temperatures. Despite the increasing number of studies on the impact of global warming on seagrasses, little attention has been paid to the role of the holobiont. Using an outdoor benthocosm to replicate near-natural conditions, this study explores the repercussions of persistent warming on the microbiome of Z. marina and its implications for holobiont function. Results show that both seasonal warming and chronic warming, impact Z. marina roots and sediment microbiome. Compared with roots, sediments demonstrate higher diversity and stability throughout the study, but temperature effects manifest earlier in both compartments, possibly linked to premature Z. marina die-offs under chronic warming. Shifts in microbial composition, such as an increase in organic matter-degrading and sulfur-related bacteria, accompany chronic warming. A higher ratio of sulfate-reducing bacteria compared to sulfide oxidizers was found in the warming treatment which may result in the collapse of the seagrasses, due to toxic levels of sulfide. Differentiating predicted pathways for warmest temperatures were related to sulfur and nitrogen cycles, suggest an increase of the microbial metabolism, and possible seagrass protection strategies through the production of isoprene. These structural and compositional variations in the associated microbiome offer early insights into the ecological status of seagrasses. Certain taxa/genes/pathways may serve as markers for specific stresses. Monitoring programs should integrate this aspect to identify early indicators of seagrass health. Understanding microbiome changes under stress is crucial for the use of potential probiotic taxa to mitigate climate change effects. Broader-scale examination of seagrass-microorganism interactions is needed to leverage knowledge on host-microbe interactions in seagrasses.

Why do avian responses to change in Arctic green-up vary?

Global climate change has altered the timing of seasonal events (i.e., phenology) for a diverse range of biota. Within and among species, however, the degree to which alterations in phenology match climate variability differ substantially. To better understand factors driving these differences, we evaluated variation in timing of nesting of eight Arctic-breeding shorebird species at 18 sites over a 23-year period. We used the Normalized Difference Vegetation Index as a proxy to determine the start of spring (SOS) growing season and quantified relationships between SOS and nest initiation dates as a measure of phenological responsiveness. Among species, we tested four life history traits (migration distance, seasonal timing of breeding, female body mass, expected female reproductive effort) as species-level predictors of responsiveness. For one species (Semipalmated Sandpiper), we also evaluated whether responsiveness varied across sites. Although no species in our study completely tracked annual variation in SOS, phenological responses were strongest for Western Sandpipers, Pectoral Sandpipers, and Red Phalaropes. Migration distance was the strongest additional predictor of responsiveness, with longer-distance migrant species generally tracking variation in SOS more closely than species that migrate shorter distances. Semipalmated Sandpipers are a widely distributed species, but adjustments in timing of nesting relative to variability in SOS did not vary across sites, suggesting that different breeding populations of this species were equally responsive to climate cues despite differing migration strategies. Our results unexpectedly show that long-distance migrants are more sensitive to local environmental conditions, which may help them to adapt to ongoing changes in climate.

Longitudinal assessment of extreme climate events in Kinnaur district, Himachal Pradesh, north-western Himalaya, India.

It is vital to keep an eye on changes in climatic extremes because they set the stage for current and potential future climate, which usually have a reasonable adverse impact on ecosystems and society. The present study examines the variability and trends in precipitation and temperature across seasons in the Kinnaur district, offering valuable insights into the complex dynamics of the Himalayan climate. Using Climatic Research Unit gridded Time Series (CRU TS) datasets from 1951 to 2021, the study analyzes the data to produce 28 climate indices based on India Meteorological Department (IMD) convention indices and Expert Team on Climate Change Detection and Indices (ETCCDI). Although there may be considerable variation in climate indices in terms of absolute values within different products, there is consensus in both long-term trends and inter-annual variability. Analysis shows that even within a small area, there is variability in the magnitude and direction of historic temperature trends. Initially, the data were subjected to rigorous quality control procedures, which involved identifying anomalies. Statistical analysis like trend analysis, employing Mann-Kendall test and Sen's slope estimator, reveal significant (p < 0.05) increase in consecutive dry days (CDD) at 0.03 days/year and decrease in consecutive wet days (CWD) at 0.02 days/year. Notably, the frequency of heavy precipitation occurrences showed an increasing trend. Changes in precipitation in the Western Himalaya are driven by a complex interplay of orographic effects, monsoonal dynamics, atmospheric circulation patterns, climate change, and localized factors such as topography, atmospheric circulation patterns, moisture sources, land-sea temperature contrasts, and anthropogenic influences. Moreover, in case of temperature indices, there is significant increasing trend observed. Temperature indices indicate a significant annual increase in warm nights (TN90p) at 0.06%/year and warm days (TX90p) at 0.11%/year. Extreme temperature events have been trending upward, with monthly daily maximum temperature (TXx) increasing by 1.5 °C yearly. This study enhances our comprehension of the global warming phenomenon and underscores the importance of acknowledging alterations in the water cycle and their repercussions on hydrologic resources, agriculture, and livelihoods in the cold desert of the northwestern Indian Himalaya.

Concentrations of Volatile Methyl Siloxanes in New York City Reflect Emissions from Personal Care and Industrial Use.

Volatile methyl siloxanes (VMS) are a group of organosilicon compounds of interest because of their potential health effects, their ability to form secondary organic aerosols, and their use as tracer compounds. VMS are emitted in the gas-phase from using consumer and personal care products, including deodorants, lotions, and hair conditioners. Because of this emission route, airborne concentrations are expected to increase with population density, although there are few studies in large urban centers. Here, we report summertime concentrations and daily variations of VMS congeners measured in New York City. Median concentrations of the 6 studied congeners, D3 (20 ng m-3), D4 (57 ng m-3), D5 (230 ng m-3), D6 (11 ng m-3), L5 (2.5 ng m-3), and L7 (1.3 ng m-3) are among the highest reported outdoor concentrations in the literature to date. Average congener ratios of D5:D4 and D5:D6 were consistent with previously reported emissions ratios, suggesting that concentrations were dominated by local emissions. Measured concentrations agree with previously published results from a Community Multiscale Air Quality model and support commonly accepted emissions rates for D4, D5, and D6 of 32.8, 135, and 6.1 mg per capita per day. Concentrations of D4, D5, D6, L5, and L7 and total VMS were significantly lower during the day than during the night, consistent with daytime oxidation reactivity. Concentrations of D3 did not show the same diurnal trend but exhibited a strong directional dependence, suggesting that it may be emitted by industrial point sources in the area rather than personal care product use. Concentrations of all congeners had large temporal variations but showed relatively weak relationships with wind speed, temperature, and mixing height.

Intra-decadal increase in globally-spread Magallana gigas in southern California estuaries.

Introduction and establishment of non-indigenous species (NIS) has been accelerated on a global scale by climate change. NIS Magallana gigas' (formerly Crassostrea gigas') global spread over the past several decades has been linked to warming waters, specifically during summer months, raising the specter of more spread due to predicted warming. We tracked changes in density and size distribution of M. gigas in two southern California, USA bays over the decade spanning 2010-2020 using randomly placed quadrats across multiple intertidal habitats (e.g., cobble, seawalls, riprap) and documented density increases by 2.2 to 32.8 times at 7 of the 8 sites surveyed across the two bays. These increases in density were coincident with 2-4° C increases in median monthly seawater temperature during summer months, consistent with global spread of M. gigas elsewhere. Size frequency distribution data, with all size classes represented across sites, suggest now-regular recruitment of M. gigas. Our data provide a baseline against which to compare future changes in density and abundance of a globally-spread NIS of significant concern.

Trends of Mansonia (Diptera, Culicidae, Mansoniini) in Porto Velho: Seasonal patterns and meteorological influences.

Entomological research is vital for shaping strategies to control mosquito vectors. Its significance also reaches into environmental management, aiming to prevent inconveniences caused by non-vector mosquitoes like the Mansonia Blanchard, 1901 mosquito. In this study, we carried out a five-year (2019-2023) monitoring of these mosquitoes at ten sites in Porto Velho, Rondônia, using SkeeterVac SV3100 automatic traps positioned between the two hydroelectric complexes on the Madeira River. Throughout this period, we sampled 153,125 mosquitoes, of which the Mansonia genus accounted for 54% of the total, indicating its prevalence in the region. ARIMA analysis revealed seasonal patterns of Mansonia spp., highlighting periods of peak density. Notably, a significant decreasing trend in local abundance was observed from July 2021 (25th epidemiological week) until the end of the study. Wind speed was observed to be the most relevant meteorological factor influencing the abundance of Mansonia spp. especially in the Joana D'Arc settlement, although additional investigation is needed to comprehensively analyze other local events and gain a deeper understanding of the ecological patterns of this genus in the Amazon region.

Extracting the winter wheat using the decision tree based on time series dual-polarization SAR feature and NDVI.

Winter wheat is one of the most important crops in the world. It is great significance to obtain the planting area of winter wheat timely and accurately for formulating agricultural policies. Due to the limited resolution of single SAR data and the susceptibility of single optical data to weather conditions, it is difficult to accurately obtain the planting area of winter wheat using only SAR or optical data. To solve the problem of low accuracy of winter wheat extraction only using optical or SAR images, a decision tree classification method combining time series SAR backscattering feature and NDVI (Normalized Difference Vegetation Index) was constructed in this paper. By synergy using of SAR and optical data can compensate for their respective shortcomings. First, winter wheat was distinguished from other vegetation by NDVI at the maturity stage, and then it was extracted by SAR backscattering feature. This approach facilitates the semi-automated extraction of winter wheat. Taking Yucheng City of Shandong Province as study area, 9 Sentinel-1 images and one Sentinel-2 image were taken as the data sources, and the spatial distribution of winter wheat in 2022 was obtained. The results indicate that the overall accuracy (OA) and kappa coefficient (Kappa) of the proposed method are 96.10% and 0.94, respectively. Compared with the supervised classification of multi-temporal composite pseudocolor image and single Sentinel-2 image using Support Vector Machine (SVM) classifier, the OA are improved by 10.69% and 5.66%, respectively. Compared with using only SAR feature for decision tree classification, the producer accuracy (PA) and user accuracy (UA) for extracting the winter wheat are improved by 3.08% and 8.25%, respectively. The method proposed in this paper is rapid and accurate, and provide a new technical method for extracting winter wheat.

All-you-can-eat buffet: A spider-specialized bat species (Myotis emarginatus) turns into a pest fly eater around cattle.

Determining the dietary spectrum of European insectivorous bats over time is the cornerstone of their conservation, as it will aid our understanding of foraging behavior plasticity in response to plummeting insect populations. Despite the global decline in insects, a restricted number of arthropod pest species thrive. Yet past research has overlooked the potential of European bats to suppress pests harmful to woodlands or livestock, in spite of their economic relevance. Here we investigated the diet composition, its breeding season variations and pest consumption of an insectivorous bat species (Myotis emarginatus), at the northern edge of its range (Wallonia, Belgium). We also explored the prey ecology to gain insight into the hunting strategies and foraging habitats of this bat species. We used DNA metabarcoding to amplify two COI markers within 195 bat droppings collected in June, July and August, thereby identifying 512 prey taxa predominated by Diptera, Araneae and Lepidoptera. Overall, in 97% of the samples we detected at least one of the 58 potential pest taxa, 41 of which targeting trees. The June samples were marked by a diet rich in orb-weaver spiders, in accordance with the archetypal diet of M. emarginatus bats. However, during the highly energy demanding July-August parturition and lactation period, roughly 55% of the dropping samples contained two cattle fly pests (Stomoxys calcitrans and Musca domestica). Moreover, among the 88 Diptera species preyed upon by M. emarginatus in July and August, these flies accounted for around 50% of the taxa occurrences. This plasticity-the switch from a spider-rich to a fly-rich diet-seems providential considering the dramatic ongoing drop in insect populations but this involves ensuring bat-friendly cattle farming. Our results revealed that bats widely consume pest entomofauna, thereby highlighting their potential role as allies of forest managers and farmers.

Land use change and coastal water darkening drive synchronous dynamics in phytoplankton and fish phenology on centennial timescales.

At high latitudes, the suitable window for timing reproductive events is particularly narrow, promoting tight synchrony between trophic levels. Climate change may disrupt this synchrony due to diverging responses to temperature between, for example, the early life stages of higher trophic levels and their food resources. Evidence for this is equivocal, and the role of compensatory mechanisms is poorly understood. Here, we show how a combination of ocean warming and coastal water darkening drive long-term changes in phytoplankton spring bloom timing in Lofoten Norway, and how spawning time of Northeast Arctic cod responds in synchrony. Spring bloom timing was derived from hydrographical observations dating back to 1936, while cod spawning time was estimated from weekly fisheries catch and roe landing data since 1877. Our results suggest that land use change and freshwater run-off causing coastal water darkening has gradually delayed the spring bloom up to the late 1980s after which ocean warming has caused it to advance. The cod appear to track phytoplankton dynamics by timing gonadal development and spawning to maximize overlap between offspring hatch date and predicted resource availability. This finding emphasises the importance of land-ocean coupling for coastal ecosystem functioning, and the potential for fish to adapt through phenotypic plasticity.

Future malaria environmental suitability in Africa is sensitive to hydrology.

Changes in climate shift the geographic locations that are suitable for malaria transmission because of the thermal constraints on vector Anopheles mosquitos and Plasmodium spp. malaria parasites and the lack of availability of surface water for vector breeding. Previous Africa-wide assessments have tended to solely represent surface water using precipitation, ignoring many important hydrological processes. Here, we applied a validated and weighted ensemble of global hydrological and climate models to estimate present and future areas of hydroclimatic suitability for malaria transmission. With explicit surface water representation, we predict a net decrease in areas suitable for malaria transmission from 2025 onward, greater sensitivity to future greenhouse gas emissions, and different, more complex, malaria transmission patterns. Areas of malaria transmission that are projected to change are smaller than those estimated by precipitation-based estimates but are associated with greater changes in transmission season lengths.

Endoparasitic helminth fauna and diet of Geophagus sveni (Pisces) in Upper Paraná River basin.

In freshwater ecosystems, parasite infection patterns are influenced by factors including spatial-temporal variations, host diet, and habitat. Fish often change diets, affecting their parasite communities. This study focused on non-native host fish Geophagus sveni, aiming to characterize diet and endoparasitic helminth fauna patterns in the invaded area, investigating spatial and seasonal possible differences of endoparasite infections and correlating with host diet, in São José dos Dourados River and Tietê River areas. The host fish were collected in these areas during the dry and rainy season using gillnets. The endoparasites were collected and preserved in alcohol and identified using taxonomic methods, and stomach contents were examined for diet analysis. Parasitism descriptors were calculated and evaluated spatially and seasonally by ANOVA and the Kruskal-Wallis tests. PERMANOVA assessed G. sveni diet differences, and RDA correlated the endohelminth abundance with the host diet. Two endoparasites were recorded: metacercariae of Austrodiplostomum compactum (Trematoda) and larvae and adults of Raphidascaris (Sprentascaris) lanfrediae (Nematoda). Spatial differences were observed for the mean abundance and prevalence of R. (S.) lanfrediae and A. compactum prevalence. Seasonal variations of parasitic descriptors occurred for the nematode in the Tietê River area. The detritus and aquatic insects were the most consumed items by G. sveni. Detritus consumption positively correlates with nematode abundance. The findings indicate that factors such as artificial channels and rainfall, which can influence resource availability, may affect the fish's diet and potentially influence the structure of its endoparasite community. The study emphasizes the importance of understanding trophic chain-transmitted parasites and calls for further research in Neotropical environments.

Predicting and reducing potential parasite infection between migratory livestock and resident Asiatic ibex of Pin valley, India.

Disease cross-transmission between wild and domestic ungulates can negatively impact livelihoods and wildlife conservation. In Pin valley, migratory sheep and goats share pastures seasonally with the resident Asiatic ibex (Capra sibirica), leading to potential disease cross-transmission. Focussing on gastro-intestinal nematodes (GINs) as determinants of health in ungulates, we hypothesized that infection on pastures would increase over summer from contamination by migrating livestock. Consequently, interventions in livestock that are well-timed should reduce infection pressure for ibex. Using a parasite life-cycle model, that predicts infective larval availability, we investigated GIN transmission dynamics and evaluated potential interventions. Migratory livestock were predicted to contribute most infective larvae onto shared pastures due to higher density and parasite levels, driving infections in both livestock and ibex. The model predicted a c.30-day antiparasitic intervention towards the end of the livestock's time in Pin would be most effective at reducing GINs in both hosts. Albeit with the caveats of not being able to provide evidence of interspecific parasite transmission due to the inability to identify parasite species, this case demonstrates the usefulness of our predictive model for investigating parasite transmission in landscapes where domestic and wild ungulates share pastures. Additionally, it suggests management options for further investigation.