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1.
PLoS One ; 19(3): e0299363, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38478477

RESUMO

Global, spatially interpolated climate datasets such as WorldClim and CHELSA, widely used in research, are based on station data, which are rare in tropical mountains. However, such biodiversity hotspots are of high ecological interest and require accurate data. Therefore, the quality of such gridded datasets needs to be assessed. This poses a kind of dilemma, as proving the reliability of these potentially weakly modelled data is usually not possible due to the lack of stations. Using a unique climate dataset with 170 stations, mainly from the montane and alpine zones of sixteen mountains in Tanzania including Kilimanjaro, we show that the accuracy of such datasets is very poor. Not only is the maximum amount of mean annual precipitation drastically underestimated (partly more than 50%), but also the elevation of the precipitation maximum deviates up to 850m. Our results show that, at least in tropical regions, they should be used with greater caution than before.


Assuntos
Clima , Tempo (Meteorologia) , Temperatura , Reprodutibilidade dos Testes , Tanzânia , Clima Tropical
2.
Water Sci Technol ; 89(5): 1312-1324, 2024 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-38483500

RESUMO

Wastewater treatment plants (WWTPs) are under increasing pressure to enhance resource efficiency and reduce emissions into water bodies. The separation of urine within the catchment area may be an alternative to mitigate the need for costly expansions of central WWTPs. While previous investigations assumed a spatially uniform implementation of urine separation across the catchment area, the present study focuses on an adapted stochastic wastewater generation model, which allows the simulation of various wastewater streams (e.g., urine) on a household level. This enables the non-uniform separation of urine across a catchment area. The model is part of a holistic modelling framework to determine the influence of targeted urine separation in catchments on the operation and emissions of central WWTPs, which will be briefly introduced. The wastewater generation model is validated through an extensive sampling and measurement series. Results based on observed and simulated wastewater quantity and quality for a catchment area of 366 residents for two dry weather days indicate the suitability of the model for wastewater generation and transport modelling. Based on this, four scenarios for urine separation were defined. The results indicate a potential influence of spatial distribution on the peaks of total nitrogen and total phosphorus.


Assuntos
Nitrogênio , Águas Residuárias , Simulação por Computador , Fósforo , Tempo (Meteorologia)
3.
PLoS One ; 19(3): e0299463, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38457430

RESUMO

The study of nocturnal bird migration brings observational challenges because of reduced visibility and observability of birds at night. Remote sensing tools, especially radars, have long been the preferred choice of scientists to study nocturnal migrations. A major downside of these remote sensing tools is the lack of species-level information. With technological advances in recent decades and with improved accessibility and affordability of acoustic tools, sound recordings have steeply increased in popularity. In Europe, there is no exhaustive qualitative and quantitative evaluation of the content of such acoustic databases and therefore the value for migration science and migration-related applications, such as bird collision hazard assessments, is mostly unknown. In the present work we compared migration schedules estimated from citizen science data with quantitative temporal occurrence of species in four years of acoustic recordings. Furthermore, we contrasted acoustic recordings with citizen science observations and weather radar data from one spring and one autumn season to assess the qualitative and quantitative yield of acoustic recordings for migration-related research and applications. Migration intensity estimated from weather radar data correlated best at low levels with acoustic records including all species in spring while in autumn passerine species showed stronger correlation than the entire species composition. Our findings identify a minor number of species whose call records may be eligible for applications derived from acoustics. Especially the highly vocal species Song thrush and Redwing showed relatively good correlations with radar and citizen science migration schedules. Most long-distance passerine migrants and many other migrants were not captured by acoustics and an estimated seasonal average of about 50% of nocturnally migrating passerine populations remained undetected. Overall, the ability of acoustic records to act as a proxy of overall migration dynamics is highly dependent on the migration period and species involved.


Assuntos
Ciência do Cidadão , Radar , Migração Animal , Tempo (Meteorologia) , Estações do Ano
4.
Malar J ; 23(1): 78, 2024 Mar 15.
Artigo em Inglês | MEDLINE | ID: mdl-38491345

RESUMO

BACKGROUND: Vegetation health (VH) is a powerful characteristic for forecasting malaria incidence in regions where the disease is prevalent. This study aims to determine how vegetation health affects the prevalence of malaria and create seasonal weather forecasts using NOAA/AVHRR environmental satellite data that can be substituted for malaria epidemic forecasts. METHODS: Weekly advanced very high-resolution radiometer (AVHRR) data were retrieved from the NOAA satellite website from 2009 to 2021. The monthly number of malaria cases was collected from the Ministry of Health of Benin from 2009 to 2021 and matched with AVHRR data. Pearson correlation was calculated to investigate the impact of vegetation health on malaria transmission. Ordinary least squares (OLS), support vector machine (SVM) and principal component regression (PCR) were applied to forecast the monthly number of cases of malaria in Northern Benin. A random sample of proposed models was used to assess accuracy and bias. RESULTS: Estimates place the annual percentage rise in malaria cases at 9.07% over 2009-2021 period. Moisture (VCI) for weeks 19-21 predicts 75% of the number of malaria cases in the month of the start of high mosquito activities. Soil temperature (TCI) and vegetation health index (VHI) predicted one month earlier than the start of mosquito activities through transmission, 78% of monthly malaria incidence. CONCLUSIONS: SVM model D is more effective than OLS model A in the prediction of malaria incidence in Northern Benin. These models are a very useful tool for stakeholders looking to lessen the impact of malaria in Benin.


Assuntos
Malária , Mosquitos Vetores , Animais , Humanos , Benin/epidemiologia , Malária/epidemiologia , Tempo (Meteorologia) , África Ocidental/epidemiologia
5.
Proc Natl Acad Sci U S A ; 121(13): e2309969121, 2024 Mar 26.
Artigo em Inglês | MEDLINE | ID: mdl-38498708

RESUMO

In this study, we model and predict rice yields by integrating molecular marker variation, varietal productivity, and climate, focusing on the Southern U.S. rice-growing region. This region spans the states of Arkansas, Louisiana, Texas, Mississippi, and Missouri and accounts for 85% of total U.S. rice production. By digitizing and combining four decades of county-level variety acreage data (1970 to 2015) with varietal information from genotyping-by-sequencing data, we estimate annual historical county-level allele frequencies. These allele frequencies are used together with county-level weather and yield data to develop ten machine learning models for yield prediction. A two-layer meta-learner ensemble model that combines all ten methods is externally evaluated against observations from historical Uniform Regional Rice Nursery trials (1980 to 2018) conducted in the same states. Finally, the ensemble model is used with forecasted weather from the Coupled Model Intercomparison Project across the 110 rice-growing counties to predict production in the coming decades for Composite Variety Groups assembled based on year of release, breeding program, and several breeding trends. Results indicate positive effects over time of public breeding on rice resilience to future climates, and potential reasons are discussed.


Assuntos
Oryza , Oryza/genética , Mudança Climática , Melhoramento Vegetal , Clima , Tempo (Meteorologia)
6.
J Safety Res ; 88: 336-343, 2024 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-38485376

RESUMO

INTRODUCTION: Continuing flight into adverse weather remains a significant problem in general aviation (GA) safety. A variety of experiential, cognitive, and motivational factors have been suggested as explanations. Previous research has shown that adverse weather accidents occur further into planned flights than other types of accident, suggesting that previous investment of time and effort might be a contributing factor. The aim of this study was to experimentally determine the effect of prior commitment on general aviation pilots' decision-making and risk-taking in simulated VFR flights. METHOD: Thirty-six licensed pilots 'flew' two simulated flights designed to simulate an encounter with deteriorating coastal weather and a developing extensive cloud base underneath the aircraft as it crossed a mountain range. After making a decision to continue or discontinue the flight, pilots completed a range of risk perception, risk taking, and situational awareness measures. RESULTS: Visual flight rules were violated in 42% of the flights. Prior commitment, in terms of distance already flown, led to an increased tendency to continue the flight into adverse weather in the coastal 'scud running' scenario. Continuing pilots perceived the risks differently and showed greater risk tolerance than others. These 'bolder' pilots also tended to be more active and better qualified than the others. CONCLUSIONS: There are undoubtedly multiple factors underlying any individual decision to continue or discontinue a flight. The willingness to tolerate a higher level of risk seems to be one such factor. This willingness can increase with time invested in the flight and also seems to be related to individual flight qualifications and experience. PRACTICAL APPLICATIONS: All pilots might benefit from carefully structured simulator sessions designed to safely teach practical risk management strategies with clear and immediate feedback.


Assuntos
Acidentes Aeronáuticos , Aviação , Humanos , Acidentes Aeronáuticos/prevenção & controle , Tomada de Decisões , Tempo (Meteorologia) , Aeronaves
7.
Behav Processes ; 216: 105014, 2024 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-38461866

RESUMO

Dogs are used for oil detection to support spill remediation and conservation, but little is known about the effects of weathering and aging of oil odorants on dogs' ability to generalize and discriminate unweathered oil from aged/weathered tar ball oil. Three dogs were trained to detect unweathered oil odorant using a three-alternative choice procedure and automated olfactometers. We evaluated dogs' ability to discriminate unweathered target oil from four different weathered/tar ball samples. All three dogs successfully discriminated the unweathered target oil from the four nontarget weathered oils with an accuracy of 96%, 97%, and 100%. After the oil discrimination test, dogs' ability to discriminate unweathered target oil from novel natural odorants on a beach (plastic bottle lid, bird feathers, and rocks) was tested in a novel discrimination test yielding an accuracy of 95%, 100%, and 100%. These data suggest dogs are successful in discriminating unweathered oil from weathered oil with explicit training.


Assuntos
Óleos , Cães Trabalhadores , Animais , Cães , Odorantes , Tempo (Meteorologia)
8.
Sci Rep ; 14(1): 6622, 2024 03 19.
Artigo em Inglês | MEDLINE | ID: mdl-38503812

RESUMO

Increasing urbanization coupled with spatial expansion and numerical increase of New World vulture populations has engendered a rise in human-vulture conflict, creating a need for effective tools to mitigate vulture-related damage. Visual frightening devices that mimic the presence of human or other predators can be employed in human-vulture conflict scenarios to increase perceived risk by the pest species, thereby eliciting an antipredator behavioral response, such as fleeing. One visual frightening device, inflatable scarecrows, recently proved effective at reducing passerine attendance at feral swine feeders, but their effectiveness when directed at other species and conflict scenarios has varied. Our primary objective was to evaluate an inflatable deterrent for reducing the number of black (Coragyps atratus) and turkey vultures (Cathartes aura) present (hereafter abundance) at 13 human-vulture conflict sites throughout the southeastern United States. We predicted that vulture abundance would be substantially reduced when inflatable deterrents were deployed. Because we suspected other factors might also influence vulture site abundance, we also examined the exploratory variables of weather, site size (area), and vulture tolerance to human approach in relation to vulture site abundance using a model selection approach. Black vulture site abundance was more pervasive than turkey vultures, occurring at all sites and accounting for 85% of daily vulture counts (10.78 ± 0.52 vultures/site/day) whereas turkey vultures were only present at 62% of sites (2.12 ± 0.21). Across all sites, inflatable scarecrows were effective at reducing vulture abundance by 82% during the seventeen-day treatment period when deterrents were deployed (3.50 ± 0.20), but only a 48% reduction during the twenty-one-day post-treatment phase (15.34 ± 1.39) was observed. Site size and weather did not influence tool effectiveness. Human tolerance at sites, as determined by vulture flight initiation distance, was influential, with tool effectiveness being reduced at sites where local human tolerance was high. We recommend inflatable scarecrows as a tool to reduce vulture-wildlife conflict to private property and recreation at sites where the conflict is spatially restricted (e.g., parking lot or recreation area), conducive to scarecrow deployment (e.g., flat stable surfaces), and where vulture site human tolerance is low to moderate.


Assuntos
Animais Selvagens , Falconiformes , Humanos , Animais , Suínos , Sudeste dos Estados Unidos , Tempo (Meteorologia)
9.
Nat Plants ; 10(3): 367-373, 2024 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-38459130

RESUMO

High interannual variation in seed production in perennial plants can be synchronized at subcontinental scales with wide consequences for ecosystem functioning, but how such synchrony is generated is unclear1-3. We investigated the factors contributing to masting synchrony in European beech (Fagus sylvatica), which extends to a geographic range of 2,000 km. Maximizing masting synchrony via spatial weather coordination, known as the Moran effect, requires a simultaneous response to weather conditions across distant populations. A celestial cue that occurs simultaneously across the entire hemisphere is the longest day (the summer solstice). We show that European beech abruptly opens its temperature-sensing window on the solstice, and hence widely separated populations all start responding to weather signals in the same week. This celestial 'starting gun' generates ecological events with high spatial synchrony across the continent.


Assuntos
Ecossistema , Fagus , Estações do Ano , Tempo (Meteorologia) , Sementes/fisiologia , Fagus/fisiologia
10.
PLoS One ; 19(3): e0300229, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38502675

RESUMO

Accurate short-term load forecasting is of great significance in improving the dispatching efficiency of power grids, ensuring the safe and reliable operation of power grids, and guiding power systems to formulate reasonable production plans and reduce waste of resources. However, the traditional short-term load forecasting method has limited nonlinear mapping ability and weak generalization ability to unknown data, and it is prone to the loss of time series information, further suggesting that its forecasting accuracy can still be improved. This study presents a short-term power load forecasting method based on Bagging-stochastic configuration networks (SCNs). First, the missing values in the original data are filled with the average values. Second, the influencing factors, such as the weather- and week-type data, are coded. Then, combined with the data of influencing factors after coding, the Bagging-SCNs integration algorithm is used to predict the short-term load. Finally, by taking the daily load data of Quanzhou City, Zhejiang Province as an example, the program of the abovementioned method is compiled in Python language and then compared with the long short-term memory neural network algorithm and the single-SCNs algorithm. Simulation results show that the proposed method for medium- and short-term load forecasting has a high forecasting accuracy and a significant effect on improving the accuracy of load forecasting.


Assuntos
Algoritmos , Redes Neurais de Computação , Tempo (Meteorologia) , Previsões , Simulação por Computador
11.
Vet Parasitol Reg Stud Reports ; 49: 101005, 2024 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-38462306

RESUMO

Flystrike remains an important animal health issue on New Zealand sheep farms. To date no useful predictive tool to assist farmers to develop control options has been available. The aim of this study was to use National Institute of Water and Atmospheric Research (NIWA) virtual climate station data in New Zealand to develop a weather-based model to accurately predict the presence of Lucilia spp. on sheep farms throughout New Zealand. Three LuciTrap® baited fly traps were positioned on each of eight sheep farms throughout New Zealand (5 in the North Island and 3 in the South Island). The traps were put out for both the 2018-2019 and 2019-2020 seasons. They were emptied each week and the flies morphologically identified; with the counts of Lucilia cuprina and L. sericata combined as Lucilia spp. The count data for Lucilia spp. for each week of trapping was transformed into a binary outcome and a generalised linear mixed effects models fitted to the data, with farm as a random effect. The dependent variable was Lucilia spp. flies caught, yes or no, and the independent variables were mean weekly climate variables from the nearest NIWA virtual climate station to that farm. The model was trained on the 2018-2019 catch data and tested on the 2019-2020 catch data. A cut point was identified which maximised the model's ability to correctly predict whether Lucilia spp. were present or not for the 2019-2020 catch data, and the sensitivity, specificity, accuracy, and area under the curve (AUC) of the model calculated. The final model included just 3 significant variables, mean weekly 10 cm soil temperature, mean weekly soil moisture index, and mean weekly wind speed at 10 m. Mean weekly 10 cm soil temperature accounted for 64.7% of the variance explained by the model, mean weekly soil moisture index 34.7% and mean weekly wind speed at 10 m only 0.6%. The results showed that the predictive model had a sensitivity of 0.93 (95% CI = 0.80-0.98) and a specificity of 0.75 (95% CI = 0.62-0.85), using a cut point for the probability of Lucilia spp. being present on farm = 0.383. This model provides New Zealand farmers with a tool which will allow them to know when Lucilia spp. flies will likely be present and thus more accurately plan their interventions to prevent flystrike.


Assuntos
Dípteros , Miíase , Animais , Ovinos , Fazendas , Nova Zelândia/epidemiologia , Tempo (Meteorologia) , Miíase/veterinária , Calliphoridae , Solo
12.
BMC Public Health ; 24(1): 633, 2024 Feb 28.
Artigo em Inglês | MEDLINE | ID: mdl-38419007

RESUMO

BACKGROUND: Dermatitis caused by insects and mites, diagnosed as papular urticaria or scabies, is a common skin disease. However, there is still a lack of studies about the effects of weather and air pollution on outpatient visits for this disease. This study aims to explore the impacts of meteorological and environmental factors on daily visits of dermatitis outpatients. METHODS: Analyses are conducted on a total of 43,101 outpatient visiting records during the years 2015-2020 from the largest dermatology specialist hospital in Guangzhou, China. Hierarchical cluster models based on Pearson correlation between risk factors are utilized to select regression variables. Linear regression models are fitted to identify the statistically significant associations between the risk factors and daily visits, taking into account the short-term effects of temperatures. Permutation importance is adopted to evaluate the predictive ability of these factors. RESULTS: Short-term temperatures have positive associations with daily visits and exhibit strong predictive abilities. In terms of total outpatients, the one-day lagged temperature not only has a significant impact on daily visits, but also has the highest median value of permutation importance. This conclusion is robust across most subgroups except for subgroups of summer and scabies, wherein the three-day lagged temperature has a negative effect. By contrast, air pollution has insignificant associations with daily visits and exhibits weak predictive abilities. Moreover, weekdays, holidays and trends have significant impacts on daily visits, but with weak predictive abilities. CONCLUSIONS: Our study suggests that short-term temperatures have positive associations with daily visits and exhibit strong predictive abilities. Nevertheless, air pollution has insignificant associations with daily visits and exhibits weak predictive abilities. The results of this study provide a reference for local authorities to formulate intervention measures and establish an environment-based disease early warning system.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Dermatite , Ácaros , Escabiose , Humanos , Animais , Poluentes Atmosféricos/análise , Pacientes Ambulatoriais , Poluição do Ar/efeitos adversos , Poluição do Ar/análise , Tempo (Meteorologia) , China/epidemiologia , Insetos , Material Particulado/análise
13.
Environ Sci Technol ; 58(8): 3812-3822, 2024 Feb 27.
Artigo em Inglês | MEDLINE | ID: mdl-38358300

RESUMO

Fog harvesting is considered a promising freshwater collection strategy for overcoming water scarcity, because of its environmental friendliness and strong sustainability. Typically, fogging occurs briefly at night and in the early morning in most arid and semiarid regions. However, studies on water collection from short-term fog are scarce. Herein, we developed a patterned surface with highly hydrophilic interconnected microchannels on a superhydrophobic surface to improve droplet convergence driven by the Young-Laplace pressure difference. With a rationally designed surface structure, the optimized water collection rate from mild fog could reach up to 67.31 g m-2 h-1 (6.731 mg cm-2 h-1) in 6 h; this value was over 130% higher than that observed on the pristine surface. The patterned surface with interconnected microchannels significantly shortened the startup time, which was counted from the fog contact to the first droplet falling from the fog-harvesting surface. The patterned surface was also facilely prepared via a controllable strategy combining laser ablation and chemical vapor deposition. The results obtained in outdoor environments indicate that the rationally designed surface has the potential for short-term fog harvesting. This work can be considered as a meaningful attempt to address the practical issues encountered in fog-harvesting research.


Assuntos
Água Doce , Água , Gases , Pressão , Tempo (Meteorologia) , Interações Hidrofóbicas e Hidrofílicas
14.
JAMA ; 331(8): 696-697, 2024 02 27.
Artigo em Inglês | MEDLINE | ID: mdl-38315469

RESUMO

This JAMA Insights in the Climate Change and Health series discusses the increase in extreme weather events caused by climate change and how these events bring about increased migration due to effects on water availability, food access, and rates of endemic diseases.


Assuntos
Mudança Climática , Emigração e Imigração , Iniquidades em Saúde , México , Saúde Pública , Tempo (Meteorologia) , Estados Unidos
15.
Bioresour Technol ; 396: 130419, 2024 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-38325610

RESUMO

Effects of short hydraulic retention time (HRT) in wet weather and long HRT in dry weather on sludge properties, microbial community, and metabolomic of anammox granular system were studied. Results showed under equal nitrogen loading rate (0.4 kg N/(m3 · d)) conditions, an HRT of 4.41 h was beneficial for total nitrogen removal efficiency (78.9 %). The shorter the HRT, the lower the particle density (1.01±0.34 g/cm3), the lower the settling performance (1.18±0.28 cm/s), and the worse the biomass retention (1.04±0.18 g/L), but the higher the mechanical strength (85.22 Pa). Properly decreasing HRT could increase the permeability of anammox granules, ensuring their activity. Metabolomics analysis indicated that the activity of anaerobic ammonium oxidizing bacteria was promoted by stimulating the metabolic pathways of amino acids and glycerophospholipids. In summary, this research clarified the effect of wet/dry weather on anammox granular system and provided theoretical guidance for the application in engineering.


Assuntos
Compostos de Amônio , Oxidação Anaeróbia da Amônia , Reatores Biológicos/microbiologia , Esgotos/microbiologia , Compostos de Amônio/metabolismo , Bactérias Anaeróbias/metabolismo , Tempo (Meteorologia) , Nitrogênio/metabolismo , Oxirredução , Anaerobiose
16.
Water Sci Technol ; 89(4): 841-858, 2024 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-38423604

RESUMO

The most important information required to successfully issue a flood warning is the quantitative precipitation forecasts (QPFs). This is important to run subsequent rainfall-runoff simulations. A rainfall-runoff simulation derives its accuracy mainly from the accuracy of the input QPFs. The dynamically based global numerical weather prediction models (NWPMs) are strong candidate sources of QPFs. A main problem is the real-time selection of which NWPM should be used to provide the QPFs for flood warning simulations. This paper develops an automated technique to solve this problem. The technique performs real-time comparisons with measured rainfall fields using a novel 'tolerant' hydrologic approach. The 'tolerant' approach performs the comparison on the basin scale and allows for timing shifts in the forecasts. This is because QPFs can be good but only a few hours early or late. Two events are used for illustration, and the proposed real-time application in flood warning is presented. The developed technique, employing the tolerant approach, could eliminate the effects of the timing shifts and, accordingly, succeeded to select the QPFs to be used. A Python package was developed for automation. The developed technique is expected to also be useful for offline assessments of historical performances of NWPMs.


Assuntos
Inundações , Chuva , Tempo (Meteorologia) , Simulação por Computador , Hidrologia
17.
Spat Spatiotemporal Epidemiol ; 48: 100635, 2024 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-38355259

RESUMO

The transmission growth rate of infectious diseases, particularly COVID-19, has forced governments to take immediate control decisions. Previous studies have shown that human mobility, weather condition, and vaccination are potential factors influencing virus transmission. This study investigates the contribution of weather conditions, namely temperature and precipitation, human mobility, and vaccination to coronavirus transmission. Three machine learning models: random forest (RF), XGBoost, and neural networks, are applied to predict the confirmed cases based on three aforementioned variables. All models' prediction are evaluated via spatial and temporal analysis. The spatial analysis observes the model performance over countries on certain times. The temporal analysis looks at the model prediction of each country during the specified period. The models' prediction results effectively indicate the transmission trend. The RF model performs best with a coefficient of determination of up to 89%. Meanwhile, all models confirm that vaccination is most significantly associated with COVID-19 cases.


Assuntos
COVID-19 , Humanos , COVID-19/epidemiologia , COVID-19/prevenção & controle , Tempo (Meteorologia) , Temperatura , Aprendizado de Máquina , Vacinação
18.
Environ Geochem Health ; 46(3): 87, 2024 Feb 17.
Artigo em Inglês | MEDLINE | ID: mdl-38367090

RESUMO

The ecotoxic effect of Zn species arising from the weathering of the marmatite-like sphalerite ((Fe, Zn)S) in Allium cepa systems was herein evaluated in calcareous soils and connected with its sulfide oxidation mechanism to determine the chemical speciation responsible of this outcome. Mineralogical analyses (X-ray diffraction patterns, Raman spectroscopy, scanning electron microscopy and atomic force microscopy), chemical study of leachates (total Fe, Zn, Cd, oxidation-reduction potential, pH, sulfates and total alkalinity) and electrochemical assessments (chronoamperometry, chronopotentiometry, cyclic voltammetry, and electrochemical impedance spectroscopy) were carried out using (Fe, Zn)S samples to elucidate interfacial mechanisms simulating calcareous soil conditions. Results indicate the formation of polysulfides (Sn2-), elemental sulfur (S0), siderite (FeCO3)-like, hematite (Fe2O3)-like with sorbed CO32- species, gunningite (ZnSO4·H2O)-like phase and smithsonite (ZnCO3)-like compounds in altered surface under calcareous conditions. However, the generation of gunningite (ZnSO4·H2O)-like phase was predominant bulk-solution system. Quantification of damage rates ranges from 75 to 90% of bulb cells under non-carbonated conditions after 15-30 days, while 50-75% of damage level is determined under neutral-alkaline carbonated conditions. Damage ratios are 70.08 and 30.26 at the highest level, respectively. These findings revealed lower ecotoxic damage due to ZnCO3-like precipitation, indicating the effect of carbonates on Zn compounds during vegetable up-taking (exposure). Other environmental suggestions of the (Fe, Zn)S weathering and ecotoxic effects under calcareous soil conditions are discussed.


Assuntos
Cebolas , Poluentes do Solo , Compostos de Zinco , Solo/química , Sulfetos/química , Tempo (Meteorologia) , Poluentes do Solo/análise
19.
Proc Biol Sci ; 291(2017): 20232016, 2024 Feb 28.
Artigo em Inglês | MEDLINE | ID: mdl-38378152

RESUMO

Migratory species trade-off long-distance movement with survival and reproduction, but the spatio-temporal scales at which these decisions occur are relatively unknown. Technological and statistical advances allow fine-scale study of animal decision-making, improving our understanding of possible causes and therefore conservation management. We quantified effects of reproductive preparation during spring migration on subsequent breeding outcomes, breeding outcomes on autumn migration characteristics and autumn migration characteristics on subsequent parental survival in Greenland white-fronted geese (Anser albifrons flavirostris). These are long-distance migratory birds with an approximately 50% population decline from 1999 to 2022. We deployed GPS-acceleration devices on adult females to quantify up to 5 years of individual decision-making throughout the annual cycle. Weather and habitat-use affected time spent feeding and overall dynamic body acceleration (i.e. energy expenditure) during spring and autumn. Geese that expended less energy and fed longer during spring were more likely to successfully reproduce. Geese with offspring expended more energy and fed for less time during autumn, potentially representing adverse fitness consequences of breeding. These behavioural comparisons among Greenland white-fronted geese improve our understanding of fitness trade-offs underlying abundance. We provide a reproducible framework for full annual cycle modelling using location and behaviour data, applicable to similarly studied migratory animals.


Assuntos
Migração Animal , Gansos , Feminino , Animais , Estações do Ano , Tempo (Meteorologia) , Reprodução
20.
Environ Pollut ; 345: 123526, 2024 Mar 15.
Artigo em Inglês | MEDLINE | ID: mdl-38355085

RESUMO

Understanding the role of meteorology in determining air pollutant concentrations is an important goal for better comprehension of air pollution dispersion and fate. It requires estimating the strength of the causal associations between all the relevant meteorological variables and the pollutant concentrations. Unfortunately, many of the meteorological variables are not routinely observed. Furthermore, the common analysis methods cannot establish causality. Here we use the output of a numerical weather prediction model as a proxy for real meteorological data, and study the causal relationships between a large suite of its meteorological variables, including some rarely observed ones, and the corresponding nitrogen dioxide (NO2) concentrations at multiple observation locations. Time-lagged convergent cross mapping analysis is used to ascertain causality and its strength, and the Pearson and Spearman correlations are used to study the direction of the associations. The solar radiation, temperature lapse rate, boundary layer height, horizontal wind speed and wind shear were found to be causally associated with the NO2 concentrations, with mean time lags of their maximal impact at -3, -1, -2 and -3 hours, respectively. The nature of the association with the vertical wind speed was found to be uncertain and region-dependent. No causal association was found with relative humidity, temperature and precipitation.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Poluentes Atmosféricos/análise , Dióxido de Nitrogênio/análise , Meteorologia , Tempo (Meteorologia) , Poluição do Ar/análise , Monitoramento Ambiental/métodos , Material Particulado/análise , China , Conceitos Meteorológicos
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