Bioclimatic analysis and spatial distribution of fascioliasis causative agents by assessment of Lymnaeidae snails in northwestern provinces of Iran.

BACKGROUND: Snails of the Lymnaeidae family are the intermediate hosts of Fasciola species, the causative agents of fascioliasis. The purpose of this study was to determine the prevalence of Fasciola species in lymnaeid snails and to investigate the association of geoclimatic factors and Fasciola species distribution in northwestern provinces of Iran using geographical information system (GIS) data. METHODS: A total of 2000 lymnaeid snails were collected from 33 permanent and seasonal habitats in northwestern Iran during the period from June to November 2021. After identification by standard morphological keys, they were subjected to shedding and crushing methods. Different stages of Fasciola obtained from these snails were subjected to the ITS1 polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method for species identification. The associations of weather temperature, rainfall, humidity, evaporation, air pressure, wind speed, elevation, and land cover with the distribution of Fasciola species were investigated. Geographical and statistical analysis was performed using ArcMap and SPSS software, respectively, to determine factors related to Fasciola species distribution. RESULTS: Of the 2000 snails collected, 19 were infected with Fasciola hepatica (0.09%), six with F. gigantica (0.03%), and 13 with other trematodes. Among geoclimatic and environmental factors, mean humidity, maximum humidity, and wind speed were significantly higher in areas where F. hepatica was more common than F. gigantica. The altitude of F. hepatica-prevalent areas was generally lower than F. gigantica areas. No significant relationship was observed between other investigated geoclimatic factors and the distribution of infected snails. CONCLUSIONS: The present study showed the relationship of humidity and wind speed with the distribution of snails infected with F. hepatica or F. gigantica in the northwestern regions of Iran. In contrast to F. gigantica, F. hepatica was more prevalent in low-altitude areas. Further research is recommended to elucidate the relationship between geoclimatic factors and the presence of intermediate hosts of the two Fasciola species.

Tree diversity enhances predation by birds but not by arthropods across climate gradients.

Tree diversity can promote both predator abundance and diversity. However, whether this translates into increased predation and top-down control of herbivores across predator taxonomic groups and contrasting environmental conditions remains unresolved. We used a global network of tree diversity experiments (TreeDivNet) spread across three continents and three biomes to test the effects of tree species richness on predation across varying climatic conditions of temperature and precipitation. We recorded bird and arthropod predation attempts on plasticine caterpillars in monocultures and tree species mixtures. Both tree species richness and temperature increased predation by birds but not by arthropods. Furthermore, the effects of tree species richness on predation were consistent across the studied climatic gradient. Our findings provide evidence that tree diversity strengthens top-down control of insect herbivores by birds, underscoring the need to implement conservation strategies that safeguard tree diversity to sustain ecosystem services provided by natural enemies in forests.

Revealing climatic and groundwater impacts on the spatiotemporal variations in vegetation coverage in marine sedimentary basins of the North China Plain, China.

The North China Plain (NCP) is one of the three great plains in China and also serves as a vital region for grain, cotton, and oil production. Under the influence of regional hydrothermal changes, groundwater overexploitation, and seawater intrusion, the vegetation coverage is undergoing continuous alterations. However, a comprehensive assessment of impacts of precipitation, temperature, and groundwater on vegetation in marine sedimentary regions of the NCP is lacking. Heilonggang Basin (HB) is located in the low-lying plain area in the east of NCP, which is part of the NCP. In this study, the HB was chosen as a typical area of interest. We collected a series of data, including the Normalized Difference Vegetation Index (NDVI), precipitation, temperature, groundwater depth, and Total Dissolved Solids (TDS) from 2001 to 2020. Then the spatiotemporal variation in vegetation was analyzed, and the underlying driving mechanisms of vegetation variation were explored in this paper. The results show that NDVI experiences a rapid increase from 2001 to 2004, followed by stable fluctuations from 2004 to 2020. The vegetation in the HB has achieved an overall improvement in the past two decades, with 76% showing improvement, mainly in the central and eastern areas, and 24% exhibiting deterioration in other areas. From 2001 to 2020, NDVI correlates positively with precipitation, whereas its relationship with temperature fluctuates between positive and negative, and is not statistically significant. There is a threshold for the synergistic change of NDVI and groundwater depth. When the groundwater depth is lower than 3.8 m, NDVI increases sharply with groundwater depth. However, beyond this threshold, NDVI tends to stabilize and fluctuate. In the eastern coastal areas, NDVI exhibits a strong positive correlation with groundwater depth, influenced by the surface soil TDS controlled by groundwater depth. In the central regions, a strong negative correlation is observed, where NDVI is primarily impacted by soil moisture under the control of groundwater. In the west and south, a strong positive correlation exists, with NDVI primarily influenced by the intensity of groundwater exploitation. Thus, precipitation and groundwater are the primary driving forces behind the spatiotemporal variability of vegetation in the HB, while in contrast, the influence of temperature is uncertain. This study has elucidated the mechanism of vegetation response, providing a theoretical basis for mitigating adverse factors affecting vegetation growth and formulating rational water usage regulations in the NCP.

Variations in water economy traits in two Sphagnum species across their distribution boundaries.

PREMISE: We assessed changes in traits associated with water economy across climatic gradients in the ecologically similar peat mosses Sphagnum cuspidatum and Sphagnum lindbergii. These species have parapatric distributions in Europe and have similar niches in bogs. Sphagnum species of bogs are closely related, with a large degree of microhabitat niche overlap between many species that can be functionally very similar. Despite this, ecologically similar species do have different distributional ranges along climatic gradients that partly overlap. These gradients may favor particular Sphagnum traits, especially in relation to water economy, which can be hypothesized to drive species divergence by character displacement. METHODS: We investigated traits relevant for water economy of two parapatric bryophytes (Sphagnum cuspidatum and S. lindbergii) across the border of their distributional limits. We included both shoot traits and canopy traits, i.e., collective traits of the moss surface, quantified by photogrammetry. RESULTS: The two species are ecologically similar and occur at similar positions along the hydrological gradient in bogs. The biggest differences between the species were expressed in the variations of their canopy surfaces, particularly surface roughness and in the responses of important traits such as capitulum mass to climate. We did not find support for character displacement, because traits were not more dissimilar in sympatric than in allopatric populations. CONCLUSIONS: Our results suggest that parapatry within Sphagnum can be understood from just a few climatic variables and that climatic factors are stronger drivers than competition behind trait variation within these species of Sphagnum.

Analyzing vegetation health dynamics across seasons and regions through NDVI and climatic variables.

This study assesses the relationships between vegetation dynamics and climatic variations in Pakistan from 2000 to 2023. Employing high-resolution Landsat data for Normalized Difference Vegetation Index (NDVI) assessments, integrated with climate variables from CHIRPS and ERA5 datasets, our approach leverages Google Earth Engine (GEE) for efficient processing. It combines statistical methodologies, including linear regression, Mann-Kendall trend tests, Sen's slope estimator, partial correlation, and cross wavelet transform analyses. The findings highlight significant spatial and temporal variations in NDVI, with an annual increase averaging 0.00197 per year (p < 0.0001). This positive trend is coupled with an increase in precipitation by 0.4801 mm/year (p = 0.0016). In contrast, our analysis recorded a slight decrease in temperature (- 0.01011 °C/year, p < 0.05) and a reduction in solar radiation (- 0.27526 W/m2/year, p < 0.05). Notably, cross-wavelet transform analysis underscored significant coherence between NDVI and climatic factors, revealing periods of synchronized fluctuations and distinct lagged relationships. This analysis particularly highlighted precipitation as a primary driver of vegetation growth, illustrating its crucial impact across various Pakistani regions. Moreover, the analysis revealed distinct seasonal patterns, indicating that vegetation health is most responsive during the monsoon season, correlating strongly with peaks in seasonal precipitation. Our investigation has revealed Pakistan's complex association between vegetation health and climatic factors, which varies across different regions. Through cross-wavelet analysis, we have identified distinct coherence and phase relationships that highlight the critical influence of climatic drivers on vegetation patterns. These insights are crucial for developing regional climate adaptation strategies and informing sustainable agricultural and environmental management practices in the face of ongoing climatic changes.

Controls and relationships of soil organic carbon abundance and persistence vary across pedo-climatic regions.

One of the largest uncertainties in the terrestrial carbon cycle is the timing and magnitude of soil organic carbon (SOC) response to climate and vegetation change. This uncertainty prevents models from adequately capturing SOC dynamics and challenges the assessment of management and climate change effects on soils. Reducing these uncertainties requires simultaneous investigation of factors controlling the amount (SOC abundance) and duration (SOC persistence) of stored C. We present a global synthesis of SOC and radiocarbon profiles (nProfile = 597) to assess the timescales of SOC storage. We use a combination of statistical and depth-resolved compartment models to explore key factors controlling the relationships between SOC abundance and persistence across pedo-climatic regions and with soil depth. This allows us to better understand (i) how SOC abundance and persistence covary across pedo-climatic regions and (ii) how the depth dependence of SOC dynamics relates to climatic and mineralogical controls on SOC abundance and persistence. We show that SOC abundance and persistence are differently related; the controls on these relationships differ substantially between major pedo-climatic regions and soil depth. For example, large amounts of persistent SOC can reflect climatic constraints on soils (e.g., in tundra/polar regions) or mineral absorption, reflected in slower decomposition and vertical transport rates. In contrast, lower SOC abundance can be found with lower SOC persistence (e.g., in highly weathered tropical soils) or higher SOC persistence (e.g., in drier and less productive regions). We relate variable patterns of SOC abundance and persistence to differences in the processes constraining plant C input, microbial decomposition, vertical C transport and mineral SOC stabilization potential. This process-oriented grouping of SOC abundance and persistence provides a valuable benchmark for global C models, highlighting that pedo-climatic boundary conditions are crucial for predicting the effects of climate change and soil management on future C abundance and persistence.

Global evidence for joint effects of multiple natural and anthropogenic drivers on soil nitrogen cycling.

Global soil nitrogen (N) cycling remains poorly understood due to its complex driving mechanisms. Here, we present a comprehensive analysis of global soil δ15N, a stable isotopic signature indicative of the N input-output balance, using a machine-learning approach on 10,676 observations from 2670 sites. Our findings reveal prevalent joint effects of climatic conditions, plant N-use strategies, soil properties, and other natural and anthropogenic forcings on global soil δ15N. The joint effects of multiple drivers govern the latitudinal distribution of soil δ15N, with more rapid N cycling at lower latitudes than at higher latitudes. In contrast to previous climate-focused models, our data-driven model more accurately simulates spatial changes in global soil δ15N, highlighting the need to consider the joint effects of multiple drivers to estimate the Earth's N budget. These insights contribute to the reconciliation of discordances among empirical, theoretical, and modeling studies on soil N cycling, as well as sustainable N management.

The potential of durum wheat-chickpea intercropping to improve the soil available phosphorus status and biomass production in a subtropical climate.

The intercropping system is a promising approach to augmenting the soil nutrient status and promoting sustainable crop production. However, it is not known whether intercropping improves the soil phosphorus (P) status in alluvial soils with low P under subtropical climates. Over two growing seasons--2019-2020 and 2020-2021--two experimental fields were employed to explore the effect of durum wheat (Dw) and chickpea (Cp) cropping systems on the soil available P. A randomized complete block design was used in this experiment, with three blocks each divided into three plots. Each plot was used for one of the following three treatments with three replications: Dw monocrop (Dw-MC), Cp monocrop (Cp-MC), and Dw + Cp intercrop (CpDw-InC), with bulk soil (BS) used as a control. A reduction in the rhizosphere soil pH (-0.44 and -0.11 unit) was observed in the (Cp-MC) and (CpDw-InC) treatments over BS, occurring concomitantly with a significant increase in available P in the rhizosphere soil of around 28.45% for CpDw-InC and 24.9% for Cp-MC over BS. Conversely, the rhizosphere soil pH was significantly higher (+0.12 units) in the Dw-MC treatments. In addition, intercropping enhanced the soil microbial biomass P, with strong positive correlations observed between the biomass P and available P in the Cp-MC treatment, whereas this correlation was negative in the CpDw-InC and Dw-MC treatments. These findings suggested that Cp intercropped with Dw could be a viable approach in enhancing the available P through improved pH variation and biomass P when cultivated on alluvial soil under a subtropical climate.

Quantitative analysis of the impact of climate variability and human activities on grassland productivity of the Qilian Mountain National Park, China.

To quantitatively analyze the impact of climate variability and human activities on grassland productivity of China's Qilian Mountain National Park, this study used Carnegic-Ames-Stanford Approach model (CASA) and Integrated Vegetation model improved by the Comprehensive and Sequential Classification System (CSCS) to assess the trends of grassland NPP from 2000 to 2015, the residual trend analysis method was used to quantify the impact of human activities and climate change on the grassland based on the NPP changes. The actual grassland NPP accumulation mainly occurred in June, July and August (autumn); the actual NPP showed a fluctuating upward trend with an average increase of 2.2 g C·m-2 a-1, while the potential NPP increase of 1.6 g C·m-2 a-1 and human-induced NPP decreased of 0.5 g C·m-2 a-1. The annual temperature showed a fluctuating upward trend with an average increase of 0.1°C 10a-1, but annual precipitation showed a fluctuating upward trend with an average annual increase of 1.3 mm a-1 from 2000 to 2015. The area and NPP of grassland degradation caused by climate variability was significantly greater than that caused by human activities and mainly distributed in the northwest and central regions, but area and NPP of grassland restored caused by human activities was significantly greater than that caused by climate variability and mainly distributed in the southeast regions. In conclusion, grassland in Qilian Mountain National Park showed a trend of degradation based on distribution area, but showed a trend of restoration based on actual NPP. Climate variability was the main cause of grassland degradation in the northwestern region of study area, and restoration of grassland in the eastern region was the result of the combined effects of human activities and climate variability. Under global climate change, the establishment of Qilian Mountain National Park was of great significance to the grassland's protection and the grasslands ecological restoration that have been affected by humans.

Climate temperature and seasonal influences on the prevalence of temporomandibular disorders in South Korea.

This study aimed to explore seasonal variations in temporomandibular disorder (TMD) prevalence in South Korea, utilizing nationwide population-based big data. Data corresponding to the Korean Standard Classification of Diseases code of K07.6, which identifies TMD, were extracted from the Health Insurance Review and Assessment Service online platform for the period from 2010 to 2022. Additionally, we integrated these data with climate temperature records from the Korean Meteorological Administration. We subsequently conducted a statistical analysis of TMD patient data on a monthly and seasonal basis over the past 13 years to assess prevalence. Over the past 13 years, the number of TMD patients in Korea has steadily increased. The prevalence of TMD rose from 0.48% (224,708 out of a total population of 50,515,666) in 2010 to 0.94% (482,241 out of a total population of 51,439,038) in 2022, marking a 1.96-fold increase. Among children under 10 years of age, no significant differences were observed in TMD prevalence between boys and girls. However, a distinct female predominance emerged after the age of 10, with an average female-to-male ratio of 1.51:1. The peak prevalence of TMD occurred in individuals in their 20 s, followed by adolescents in their late 10 s. The majority of TMD patients were concentrated in Seoul and Gyeonggi province, with metropolitan areas accounting for 50% of the total patient count. Seasonally, TMD patient numbers showed no significant increase in winter compared with spring or summer. The temperature difference, defined as the absolute difference between the highest and lowest temperatures for each month, showed a positive correlation with TMD patient counts. A greater temperature difference was associated with higher patient counts. The strongest correlation between temperature differences and TMD patient numbers was observed in winter (r = 0.480, p < 0.01), followed by summer (r = 0.443, p < 0.01), and spring (r = 0.366, p < 0.05). Temperature differences demonstrated a significantly stronger correlation with the increase in the number of TMD patients than absolute climate temperatures. This aspect should be a key consideration when examining seasonal trends in TMD prevalence in South Korea.

Interpreting life-history traits, seasonal cycles, and coastal climate from an intertidal mussel species: Insights from 9000 years of synthesized stable isotope data.

Understanding past coastal variability is valuable for contextualizing modern changes in coastal settings, yet existing Holocene paleoceanographic records for the North American Pacific Coast commonly originate from offshore marine sediments and may not represent the dynamic coastal environment. A potential archive of eastern Pacific Coast environmental variability is the intertidal mussel species Mytilus californianus. Archaeologists have collected copious stable isotopic (δ18O and δ13C) data from M. californianus shells to study human history at California's Channel Islands. When analyzed together, these isotopic data provide windows into 9000 years of Holocene isotopic variability and M. californianus life history. Here we synthesize over 6000 δ18O and δ13C data points from 13 published studies to investigate M. californianus shell isotopic variability across ontogenetic, geographic, seasonal, and millennial scales. Our analyses show that M. californianus may grow and record environmental information more irregularly than expected due to the competing influences of calcification, ontogeny, metabolism, and habitat. Stable isotope profiles with five or more subsamples per shell recorded environmental information ranging from seasonal to millennial scales, depending on the number of shells analyzed and the resolution of isotopic subsampling. Individual shell profiles contained seasonal cycles and an accurate inferred annual temperature range of ~ 5°C, although ontogenetic growth reduction obscured seasonal signals as organisms aged. Collectively, the mussel shell record reflected millennial-scale climate variability and an overall 0.52‰ depletion in δ18Oshell from 8800 BP to the present. The archive also revealed local-scale oceanographic variability in the form of a warmer coastal mainland δ18Oshell signal (-0.32‰) compared to a cooler offshore islands δ18Oshell signal (0.33‰). While M. californianus is a promising coastal archive, we emphasize the need for high-resolution subsampling from multiple individuals to disentangle impacts of calcification, metabolism, ontogeny, and habitat and more accurately infer environmental and biological patterns recorded by an intertidal species.

Insights from modelling sixteen years of climatic and fumonisin patterns in maize in South Africa.

Mycotoxin contamination of agricultural commodities is a global public health problem that has remained elusive to various mitigation approaches, particularly in developing countries. Climate change and its impact exacerbates South Africa's vulnerability to mycotoxin contamination, and significantly threatens its's food systems, public health, and agro-economic development. Herein we analyse sixteen years (2005/2006-2020/2021) of annual national meteorological data on South Africa which reveals both systematic and erratic variability in critical climatic factors known to influence mycotoxin contamination in crops. Within the same study period, data on fumonisin (FB) monitoring show clear climate-dependent trends. The strongest positive warming trend is observed between 2018/2019 and 2019/2020 (0.51 °C/year), and a strong positive correlation is likewise established between FB contamination and temperature (r ranging from 0.6 to 0.9). Four machine learning models, viz support vector machines, eXtreme gradient boosting, random forest, and orthogonal partial least squares, are generalized on the historical data with suitable performance (RMSE as low as 0.00). All the adopted models are able to predict future FB contamination patterns with reasonable precision (R2 ranging from 0.34 to 1.00). The most important model feature for predicting average FB contamination (YA) is the historical pattern of average FB contamination in maize within the region (ΣFBs_avg). The two most significant features in modelling maximum FB contamination (YM) are minimum temperature from the CMIP6 data (Pro_tempMIN) and observed precipitation from the CRU data (O_prep). Our study provides strong evidence of the impact of climate change on FB in South Africa and reiterates the significance of machine learning modelling in predicting mycotoxin contamination in light of changing climatic conditions, which could facilitate early warnings and the adoption of relevant mitigation measures that could help in mycotoxin risk management and control.

Assessing eco-geographic influences on COVID-19 transmission: a global analysis.

COVID-19 has been massively transmitted for almost 3 years, and its multiple variants have caused serious health problems and an economic crisis. Our goal was to identify the influencing factors that reduce the threshold of disease transmission and to analyze the epidemiological patterns of COVID-19. This study served as an early assessment of the epidemiological characteristics of COVID-19 using the MaxEnt species distribution algorithm using the maximum entropy model. The transmission of COVID-19 was evaluated based on human factors and environmental variables, including climate, terrain and vegetation, along with COVID-19 daily confirmed case location data. The results of the SDM model indicate that population density was the major factor influencing the spread of COVID-19. Altitude, land cover and climatic factor showed low impact. We identified a set of practical, high-resolution, multi-factor-based maximum entropy ecological niche risk prediction systems to assess the transmission risk of the COVID-19 epidemic globally. This study provided a comprehensive analysis of various factors influencing the transmission of COVID-19, incorporating both human and environmental variables. These findings emphasize the role of different types of influencing variables in disease transmission, which could have implications for global health regulations and preparedness strategies for future outbreaks.

Merging adoption of natural climate solutions in agriculture with climatic and non-climatic risks within an (intra)gendered framework.

The extant research on climate variability shares significant theoretical contributions to vulnerability and risks. However, the literature mostly focuses on technical solutions to climate extremes which undermines efforts to identify and solve the dynamics within gender groups in using agricultural-based natural climate solutions (NCS) to address climatic and non-climatic risks. With this in mind, this study implements both quantitative and qualitative approaches including household surveys, key informant interviews, and focus group discussions to investigate the adoption of NCS within gender groups to address climatic and non-climatic risks in three selected communities (Katanga, Dakio, and Zonno) in the Bolgatanga East District of Upper East Region of Ghana. The Relative Importance Index (RII) was used to rank the key climatic and non-climatic risks confronting smallholder farmers in the district. Male and female smallholder farmers affirmed that there has been variation in the climate compared to their childhood. The results indicated climate change-induced erosion (RII = 0.268) as the highest climatic risk among male smallholder farmers. Increased bushfire (RII = 0.263) was the highest climatic risk affecting female smallholder farmers. The findings show that the high cost of farm inputs (RII = 0.505) is the highest non-climatic risk among the male smallholder farmers whereas inadequate credit facilities (RII = 0.295) affected most of the female smallholder farmers. In adapting to the climatic risks, both male and female smallholder farmers with no formal education plant early maturing crop varieties and cover crops on their farmland. Others engage in traditional non-farm activities such as weaving by using renewable materials with reduced ecological footprints to address non-climatic risks. The male and female smallholder farmers with post-secondary education typically resort to temporal migration during the dry season to work on non-farm jobs. Acknowledging the intra-gendered adoption of NCS among marginalized farming households; not only protects against maladaptation but also improves local-level resilience and climate risk management in Ghana.

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.

Prevalence and risk factors of gastrointestinal helminths infection in Brazilian horses: A retrospective study of a 12-year (2008-2019) diagnostic data.

Understanding gastrointestinal parasite distribution is crucial for effective control programs in horses. This study reports the prevalence of helminth infections in horses and selected risk factors (i.e., breed, age, climate, season) by analyzing 19,276 fecal samples from the Laboratory of Veterinary Clinical Parasitology, in Curitiba, Southern Brazil. The analyses were carried out from 2008 to 2019, coming from 153 stud farms located in 60 municipalities of nine Brazilian states. The parasite prevalence was 73.3%, with 72.1% present in the adult population and 80.6% in young horses. Strongyles were present in 100% horse farms. Strongyles had a prevalence of 72.1% with a mean FEC of 453.53 (+/- 717.6). Parascaris spp. had a prevalence of 5.8% and a FEC of 17.11 (+/- 149.2). The tropical wet/monsoon climate (Am) showed the lowest FEC for strongyles and Parascaris spp. when compared to the other climates. In the logistic regression analysis, young horses exhibited 4.6 times higher odds ratio (OR) (3.9-5.5) of Parascaris spp. and 1.2 (1.1-1.4) times higher OR of strongyles egg shedding when compared to adults (P < 0.001). Summer presented a higher risk for Parascaris spp. and Strongyles eggs when compared to the other seasons (P < 0.001). Mangalarga Marchador, Criollo, and Crossbred breeds were identified with higher OR of Parascaris spp. egg shedding than Thoroughbred. The extensive prevalence of strongyles across ages, seasons, breeds, and climates alerts for the risk of clinical manifestations in equines raised on pastures designing optimal health management and parasite control strategies worldwide.

Predicting the short and long term effects of food price inflation, armed conflicts, and climate variability on global acute malnutrition in Somalia.

BACKGROUND: Malnutrition poses a substantial challenge in Somalia, impacting approximately 1.8 million children. This critical issue is exacerbated by a multifaceted interplay of factors. Consequently, this study seeks to examine the long-term and short-term effects of armed conflicts, food price inflation, and climate variability on global acute malnutrition in Somalia. METHODS: The study utilized secondary data spanning from January 2015 to December 2022, sourced from relevant databases. Two distinct analytical approaches were employed to comprehensively investigate the dynamics of global acute malnutrition in Somalia. Firstly, dynamic autoregressive distributed lag (ARDL) simulations were applied, allowing for a nuanced understanding of the short and long-term effects of armed conflicts, food price inflation, and climate variability on malnutrition. Additionally, the study employed kernel-based regularized least squares, a sophisticated statistical technique, to further enhance the robustness of the findings. The analysis was conducted using STATA version 17. RESULTS: In the short run, armed conflicts and food price inflation exhibit positive associations with global acute malnutrition, particularly in conflict-prone areas and during inflationary periods. Moreover, climatic variables, specifically temperature and rainfall, demonstrate positive associations. It is important to note that temperature lacks a statistically significant relationship with global acute malnutrition in the short run. In the long run, armed conflicts and food price inflation maintain persistent impacts on global acute malnutrition, as confirmed by the dynamic ARDL simulations model. Furthermore, both temperature and rainfall continue to show positive associations with global acute malnutrition, but it is worth noting that temperature still exhibits a non-significant relationship. The results from kernel-based regularized least squares were consistent, further enhancing the robustness of the findings. CONCLUSIONS: Increased armed conflicts, food price inflation, temperature, and rainfall were associated with increased global acute malnutrition. Strategies such as stabilizing conflict-prone regions, diplomatic interventions, and peace-building initiatives are crucial, along with measures to control food price inflation. Implementing climate adaptation strategies is vital to counter temperature changes and fluctuating rainfall patterns, emphasizing the need for resilience-building. Policymakers and humanitarian organizations can leverage these insights to design targeted interventions, focusing on conflict resolution, food security, and climate resilience to enhance Somalia's overall nutritional well-being.

Rain, rain, go away, come again another day: do climate variations enhance the spread of COVID-19?

The spread of infectious diseases was further promoted due to busy cities, increased travel, and climate change, which led to outbreaks, epidemics, and even pandemics. The world experienced the severity of the 125 nm virus called the coronavirus disease 2019 (COVID-19), a pandemic declared by the World Health Organization (WHO) in 2019. Many investigations revealed a strong correlation between humidity and temperature relative to the kinetics of the virus's spread into the hosts. This study aimed to solve the riddle of the correlation between environmental factors and COVID-19 by applying RepOrting standards for Systematic Evidence Syntheses (ROSES) with the designed research question. Five temperature and humidity-related themes were deduced via the review processes, namely 1) The link between solar activity and pandemic outbreaks, 2) Regional area, 3) Climate and weather, 4) Relationship between temperature and humidity, and 5) the Governmental disinfection actions and guidelines. A significant relationship between solar activities and pandemic outbreaks was reported throughout the review of past studies. The grand solar minima (1450-1830) and solar minima (1975-2020) coincided with the global pandemic. Meanwhile, the cooler, lower humidity, and low wind movement environment reported higher severity of cases. Moreover, COVID-19 confirmed cases and death cases were higher in countries located within the Northern Hemisphere. The Blackbox of COVID-19 was revealed through the work conducted in this paper that the virus thrives in cooler and low-humidity environments, with emphasis on potential treatments and government measures relative to temperature and humidity. HIGHLIGHTS: • The coronavirus disease 2019 (COIVD-19) is spreading faster in low temperatures and humid area. • Weather and climate serve as environmental drivers in propagating COVID-19. • Solar radiation influences the spreading of COVID-19. • The correlation between weather and population as the factor in spreading of COVID-19.

One-third of Southern Ocean productivity is supported by dust deposition.

Natural iron fertilization of the Southern Ocean by windblown dust has been suggested to enhance biological productivity and modulate the climate1-3. Yet, this process has never been quantified across the Southern Ocean and at annual timescales4,5. Here we combined 11 years of nitrate observations from autonomous biogeochemical ocean profiling floats with a Southern Hemisphere dust simulation to empirically derive the relationship between dust-iron deposition and annual net community production (ANCP) in the iron-limited Southern Ocean. Using this relationship, we determined the biological response to dust-iron in the pelagic perennially ice-free Southern Ocean at present and during the last glacial maximum (LGM). We estimate that dust-iron now supports 33% ± 15% of Southern Ocean ANCP. During the LGM, when dust deposition was 5-40-fold higher than today, the contribution of dust to Southern Ocean ANCP was much greater, estimated at 64% ± 13%. We provide quantitative evidence of basin-wide dust-iron fertilization of the Southern Ocean and the potential magnitude of its impact on glacial-interglacial timescales, supporting the idea of the important role of dust in the global carbon cycle and climate6-8.

Climate of origin shapes variations in wood anatomical properties of 17 Picea species.

BACKGROUND: Variations in hydraulic conductivity may arise from species-specific differences in the anatomical structure and function of the xylem, reflecting a spectrum of plant strategies along a slow-fast resource economy continuum. Spruce (Picea spp.), a widely distributed and highly adaptable tree species, is crucial in preventing soil erosion and enabling climate regulation. However, a comprehensive understanding of the variability in anatomical traits of stems and their underlying drivers in the Picea genus is currently lacking especially in a common garden. RESULTS: We assessed 19 stem economic properties and hydraulic characteristics of 17 Picea species grown in a common garden in Tianshui, Gansu Province, China. Significant interspecific differences in growth and anatomical characteristics were observed among the species. Specifically, xylem hydraulic conductivity (Ks) and hydraulic diameter exhibited a significant negative correlation with the thickness to span ratio (TSR), cell wall ratio, and tracheid density and a significant positive correlation with fiber length, and size of the radial tracheid. PCA revealed that the first two axes accounted for 64.40% of the variance, with PC1 reflecting the trade-off between hydraulic efficiency and mechanical support and PC2 representing the trade-off between high embolism resistance and strong pit flexibility. Regression analysis and structural equation modelling further confirmed that tracheid size positively influenced Ks, whereas the traits DWT, D_r, and TSR have influenced Ks indirectly. All traits failed to show significant phylogenetic associations. Pearson's correlation analysis demonstrated strong correlations between most traits and longitude, with the notable influence of the mean temperature during the driest quarter, annual precipitation, precipitation during the wettest quarter, and aridity index. CONCLUSIONS: Our results showed that xylem anatomical traits demonstrated considerable variability across phylogenies, consistent with the pattern of parallel sympatric radiation evolution and global diversity in spruce. By integrating the anatomical structure of the stem xylem as well as environmental factors of origin and evolutionary relationships, our findings provide novel insights into the ecological adaptations of the Picea genus.