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1.
Braz. j. biol ; 84: e259259, 2024. tab, graf
Artigo em Inglês | LILACS, VETINDEX | ID: biblio-1364517

RESUMO

Rice is a widely consumed staple food for a large part of the world's human population. Approximately 90% of the world's rice is grown in Asian continent and constitutes a staple food for 2.7 billion people worldwide. Bacterial leaf blight (BLB) caused by Xanthomonas oryzae pv. oryzae is one of the devastating diseases of rice. A field experiment was conducted during the year 2016 and 2017 to investigate the influence of different meteorological parameters on BLB development as well as the computation of a predictive model to forecast the disease well ahead of its appearance in the field. The seasonal dataset of disease incidence and environmental factors was used to assess five rice varieties/ cultivars (Basmati-2000, KSK-434, KSK-133, Super Basmati, and IRRI-9). The accumulated effect of two year environmental data; maximum and minimum temperature, relative humidity, wind speed, and rainfall, was studied and correlated with disease incidence. Average temperature (maximum & minimum) showed a negative significant correlation with BLB disease and all other variables; relative humidity, rainfall, and wind speed had a positive correlation with BLB disease development on individual varieties. Stepwise regression analysis was performed to indicate potentially useful predictor variables and to rule out incompetent parameters. Environmental data from the growing seasons of July to October 2016 and 2017 revealed that, with the exception of the lowest temperature, all environmental factors contributed to disease development throughout the cropping season. A disease prediction multiple regression model was developed based on two-year data (Y = 214.3-3.691 Max T-0.508 Min T + 0.767 RH + 2.521 RF + 5.740 WS), which explained 95% variability. This disease prediction model will not only help farmers in early detection and timely management of bacterial leaf blight disease of rice but may also help reduce input costs and improve product quality and quantity. The model will be both farmer and environmentally friendly.


O arroz é um alimento básico amplamente consumido por grande parte da população humana mundial. Aproximadamente 90% do arroz do mundo é cultivado no continente asiático e constitui um alimento básico para 2,7 bilhões de pessoas em todo o mundo. O crestamento bacteriano das folhas (BLB) causado por Xanthomonas oryzae pv. oryzae é uma das doenças devastadoras do arroz. Um experimento de campo foi realizado durante os anos de 2016 e 2017 para investigar a influência de diferentes parâmetros meteorológicos no desenvolvimento do BLB, bem como o cálculo de um modelo preditivo para prever a doença bem antes de seu aparecimento em campo. O conjunto de dados sazonais de incidência de doenças e fatores ambientais foi usado para avaliar cinco variedades/cultivares de arroz (Basmati-2000, KSK-434, KSK-133, Super Basmati e IRRI-9). O efeito acumulado de dados ambientais de dois anos; temperatura máxima e mínima, umidade relativa do ar, velocidade do vento e precipitação pluviométrica foram estudados e correlacionados com a incidência da doença. A temperatura média (máxima e mínima) apresentou correlação significativa negativa com a doença BLB e todas as outras variáveis; umidade relativa, precipitação e velocidade do vento tiveram uma correlação positiva com o desenvolvimento da doença BLB em variedades individuais. A análise de regressão stepwise foi realizada para indicar variáveis preditoras potencialmente úteis e para descartar parâmetros incompetentes. Os dados ambientais das safras de julho a outubro de 2016 e 2017 revelaram que, com exceção da temperatura mais baixa, todos os fatores ambientais contribuíram para o desenvolvimento da doença ao longo da safra. Um modelo de regressão múltipla de previsão de doença foi desenvolvido com base em dados de dois anos (Y = 214,3-3,691 Max T-0,508 Min T + 0,767 RH + 2,521 RF + 5,740 WS), que explicou 95% de variabilidade. Este modelo de previsão de doenças não só ajudará os agricultores na detecção precoce e gestão atempada da doença bacteriana das folhas do arroz, mas também pode ajudar a reduzir os custos de insumos e melhorar a qualidade e a quantidade do produto. O modelo será agricultor e ambientalmente amigável.


Assuntos
Oryza , Temperatura , Pragas da Agricultura , Umidade
2.
J Environ Manage ; 330: 117147, 2023 Mar 15.
Artigo em Inglês | MEDLINE | ID: mdl-36610192

RESUMO

Soil carbon (SC) heterogeneity in mountain ecosystems is ascertained by a complex interdependency of topography, climate, edaphic features, and biotic elements, which may incite uncertainties in regional SC estimation. However, quantitative evaluations of the interplay between SC and these determinants as well as underlying possible link networks, are uncommon. Using the data set of SC along with soil properties at 0-10 and 10-20 cm depths from 135 plots under three coniferous forests, we aimed to ascertain SC heterogeneity and to elucidate how these interactions affect the SC storage, operating data-driven models (Least Absolute Shrinkage and Selection Operator [LASSO] regression and structural equation modeling [SEM]) to identify the dominant explanatory factors affecting the distribution of SC in Kashmir Himalayan forests. Average SC stocks at 0-10 cm and 10-20 cm depth intervals range from 32.41 Mg ha-1 in sub-alpine (SA) forest to 48.50 Mg ha-1 in mixed conifer (MC) forest. The findings show that SC declines significantly from 0 - 10 cm to 10-20 cm strata, consistent with other soil physico-chemical determinants other than bulk density. SEM renders better model fit (0-10 cm: R2 = 0.61; 10-20cm: R2 = 0.46) with lesser uncertainties compared to LASSO (0-10 cm: R2 = 0.55; 10-20cm: R2 = 0.37). Soil properties and topography play a key role in modulating SC stocks, with total nitrogen (TN), soil moisture (SM), and elevation being principal drivers with contrasting effects on SC storage, while climate and vegetation parameters are of lesser influence. The relative effect of majority of explanatory drivers reduces with depth while that of temperature increases. Our analyses indicate that shifts in floristic composition could have long-lasting implications on soil structure and C storage, providing valuable data for C sink management.


Assuntos
Ecossistema , Solo , Análise de Classes Latentes , Solo/química , Carbono/análise , Sequestro de Carbono , Florestas , Aprendizado de Máquina , China
3.
Am J Bot ; 2023 Jan 17.
Artigo em Inglês | MEDLINE | ID: mdl-36648370

RESUMO

Lineage-specific traits determine how plants interact with their surrounding environment. As different species may find similar phenotypic solutions through evolution to tolerate, persist in, and invade environments with certain characteristics, some traits may become more common in certain types of habitats. These general patterns of geographical trait distribution point towards the existence of some rules in how plants diversify in space over time. Trait-environment correlation analyses are ways to discover general rules in plant biogeography by quantifying to what extent unrelated lineages have similar evolutionary responses to a given type of habitat. In this synthesis, I give a short historical overview on trait-environment correlation analyses, from some key observations from classic naturalists to modern approaches using trait evolution models, large phylogenies, and massive datasets of traits and distributions. I discuss some limitations of modern approaches, including the need for more realistic models, the lack of data from tropical areas, and the necessary focus on trait scoring that goes beyond macro-morphology. Overcoming these limitations will allow the field to explore new questions related to trait lability and niche evolution and to better set apart rules and exceptions in how plants diversify in space over time. This article is protected by copyright. All rights reserved.

4.
Sci Total Environ ; : 160505, 2022 Dec 02.
Artigo em Inglês | MEDLINE | ID: mdl-36470391

RESUMO

The increased availability of environmental data with depth deriving from remote-sensing-based datasets permits more comprehensive modelling of the distribution of marine ecosystems in space and time. This research tests the potential of such objective modelling of marine ecosystems in four dimensions, spatial and temporal, to provide projections of how climate change may affect biodiversity, including aquaculture. This approach could be replicated for any regional seas. The Bohai Sea, Yellow Sea, and East China Sea (BYECS) are marginal seas in the Northwest Pacific bounded by China, Korea, and Japan. Despite providing important ecological and economic services, their ecological conditions and ecosystems distribution have not yet been systematically mapped. This analysis used 13 marine environmental variables, measured on a three-dimensional and monthly basis during 1993-2019, to classify and map the BYECS region by k-means clustering using cosine similarity as distance function. There were 13 distinct areas identified that fit the definition of "ecosystems" that is, enduring regions demarcated by environmental characteristics. Of these 13 ecosystems, the Yellow Sea Cold Water (YSCW) Ecosystem is significant in relation to seasonal species composition and the newly developing deep-sea salmon caging aquaculture in the region. Projections of the potential size of this water mass under various climate-change scenarios based on analysis using the Non-Parametric Probabilistic Ecological Niche (NPPEN) model show that its volume may decrease 31 %-66 % in the future. Such a decrease would have impacts on the seasonal species' abundances in the BYECS marginal sea region and threaten the deep-sea cold-water salmon farming.

5.
Iran J Parasitol ; 17(3): 306-316, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36466033

RESUMO

Background: Cystic echinococcosis (CE) is one of the most important parasitic infections in subgroup seven common neglected diseases of humans and animals. It is in the list of 18 neglected tropical diseases of the WHO. We aimed to analyze the situation of the disease in Iran using Geographical Information System (GIS) and satellite data analysis. Methods: The data obtained from the Ministry of Health and Medical Education, Tehran, Iran and other related centers from 2009 to 2018 were analyzed using GIS. Then, the spatial distribution maps of the disease were generated, and the hot spots of the disease in Iran were determined using spatial analysis of ArcGIS10.5 software. Geographically weighted regression (GWR) analysis in ArcGIS10.5 was used to correlate the variables affecting the disease including temperature, relative humidity, normalized different vegetation index (NDVI) and incidence of hydatidosis. Data analysis was performed by Linear regression analysis and SPSS 21 software using descriptive statistics and chi-square test. Results: Zanjan, Khorasan Razavi, North Khorasan, Chaharmahal Bakhtiari, Hamedan, Semnan, and Ardabil provinces were the hot spots of CE. The results of geographical weighted regression analysis showed that in Khorasan Razavi, North Khorasan, Chaharmahal Bakhtiari, Hamedan, Semnan, Ardabil, Zanjan, Qazvin, and Ilam provinces, the highest correlation between temperature, humidity, vegetation density and the incidence of hydatidosis was observed (P<0.001). Conclusion: The use of maps could provide reliable estimates of at-risk populations. Climatic factors of temperature, humidity, NDVI had a greater impact on the probability of hydatidosis. These factors can be an indicator used to predict the presence of disease. Environmental and climatic factors were associated with echinococcosis.

6.
Artigo em Inglês | MEDLINE | ID: mdl-36497652

RESUMO

The study sought to review the works of literature on agent-based modeling and the influence of climatic and environmental factors on disease outbreak, transmission, and surveillance. Thus, drawing the influence of environmental variables such as vegetation index, households, mosquito habitats, breeding sites, and climatic variables including precipitation or rainfall, temperature, wind speed, and relative humidity on dengue disease modeling using the agent-based model in an African context and globally was the aim of the study. A search strategy was developed and used to search for relevant articles from four databases, namely, PubMed, Scopus, Research4Life, and Google Scholar. Inclusion criteria were developed, and 20 articles met the criteria and have been included in the review. From the reviewed works of literature, the study observed that climatic and environmental factors may influence the arbovirus disease outbreak, transmission, and surveillance. Thus, there is a call for further research on the area. To benefit from arbovirus modeling, it is crucial to consider the influence of climatic and environmental factors, especially in Africa, where there are limited studies exploring this phenomenon.


Assuntos
Dengue , Animais , Umidade , Tempo (Meteorologia) , Temperatura , Vento
7.
Dis Aquat Organ ; 152: 115-125, 2022 Dec 15.
Artigo em Inglês | MEDLINE | ID: mdl-36519683

RESUMO

Infectious diseases are one of the main threats to biodiversity. The fungus Batrachochytrium dendrobatidis (Bd) is associated with several amphibian losses around the globe, and environmental conditions may dictate the success of pathogen spread. The Brazilian Amazon has been considered climatically unsuitable for chytrid fungus, but additional information on Bd dynamics in this ecoregion is still lacking. We sampled 462 amphibians (449 anurans, 4 caudatans and 9 caecilians), representing 57 species from the Brazilian Amazon, and quantified Bd infections using qPCR. We tested whether abiotic variables predicted the risk of Bd infections, and tested for relationships between biotic variables and Bd. Finally, we experimentally tested the effects of Bd strains CLFT 156 and CLFT 102 (from the southern and northern Atlantic Forest, respectively) on Atelopus manauensis. We detected higher Bd prevalence than those previously reported for the Brazilian Amazon, and positive individuals in all 3 orders of amphibians sampled. Both biotic and abiotic predictors were related to prevalence, and no variable explained infection load. Moreover, we detected higher Bd prevalence in forested than open areas, while the host's reproductive biology was not a factor. We detected higher mortality in the experimental group infected with CLFT 156, probably because this strain was isolated from a region characterized by discrepant climatic conditions (latitudinally more distant) when compared with the host's sampling site in Amazon. The lowland Brazilian Amazon is still underexplored and future studies targeting all amphibian orders are essential to better understand Bd infection dynamics in this region.


Assuntos
Quitridiomicetos , Micoses , Animais , Anfíbios/microbiologia , Anuros/microbiologia , Biodiversidade , Micoses/epidemiologia , Micoses/veterinária , Micoses/microbiologia
8.
Waste Manag Res ; : 734242X221142223, 2022 Dec 21.
Artigo em Inglês | MEDLINE | ID: mdl-36544368

RESUMO

Eco-efficiency assessment of municipal solid waste (MSW) suppliers is a useful tool in the transition to a circular economy. Furthermore, it provides evidence of the economic and environmental performance of municipalities that can be used for decision-making and/or elaboration of regulatory policies. In this study, eco-efficiency scores were computed for a sample of 140 Chilean municipalities in the provision of MSW services. In doing so, the stochastic semi-parametric envelopment of data method was applied. It is a novel technique which overcomes the limitations of parametric (stochastic frontier analysis) and non-parametric (data envelopment analysis) methods previously employed to evaluate the eco-efficiency of MSW services. The average eco-efficiency of the 140 assessed municipalities was 0.332 which indicates that they could save 66.8% of their operational costs and recycling the same amount of waste. Moreover, 61.4% of the evaluated municipalities presented an eco-efficiency score which was lower than 0.4, whereas the other municipalities (38.6% of the sample) exhibited an eco-efficiency which raged between 0.4 and 0.80. Hence, none of the municipalities assessed was identified as eco-efficient which, implies that there is room for all municipalities to reduce operational costs in the management of MSW. Population density, tourism and location of the municipality were identified as factors influencing the eco-efficiency of the municipalities in MSW management.

9.
Artigo em Inglês | MEDLINE | ID: mdl-36402879

RESUMO

Macrobenthic invertebrate communities serve as markers of anthropogenic stress in freshwater ecosystems. In this study, 17 sampling sites were selected from two Nile river subbranches (El-Rayah El-Behery and El-Rayah El-Nassery) and subjected to different anthropogenic influences to explore the ecological environment and characteristics of macrobenthos communities. Macrobenthos were studied using taxonomic diversity and biological trait analysis to investigate how human activity and variation in water quality affect their structure and function. A total of 37 taxa represented by 43,389 individuals were recognized. The communities are composed chiefly of Oligochaeta and aquatic insects. Multivariate statistical analyses found that the most influential environmental variables in the structural and functional community were sodium, dissolved oxygen, silicate, pH, calcium, and cadmium. At high levels of pollution, notably sewage and industrial pollution in the northern part of El-Rayah El-Behery, characteristics such as larger body size, detritus feeders, burrowers, and high tolerance to pollution predominated, whereas at low levels of pollution, features such as small body sizes, scraper and predator feeders, intolerant and fairly tolerant of pollution, and climber and swimmer mobility are predominant. The results confirm our prediction that the distribution of macroinvertebrate traits varies spatially in response to environmental changes. The diversity-based method distinguished impacted sewage and industrial sites from thermal effluent sites, while the trait-based approach illustrated an apparent variance between the ecological status of contaminated regions. Therefore, the biological features should be employed in addition to structural aspects for assessing the biodiversity of macroinvertebrate communities under environmental stressors.

10.
Water Res ; 226: 119310, 2022 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-36369683

RESUMO

Heavy metal(loid)s (HMs) have been consistently entering the food chain, imposing great harm on environment and public health. However, previous studies on the spatial dynamics and transport mechanism of HMs have been profoundly limited by the field sampling issues, such as the uneven observations of individual carriers and their spatial mismatch, especially over large-scale catchments with complex environment. In this study, a novel methodological framework for mapping HMs at catchment scale was proposed and applied, combining a species distribution model (SDM) with physical environment and human variables. Based on the field observations, we ecologicalized HMs in different carriers as different species. This enabled the proposed framework to model the 'enrichment area' of individual HMs in the geographic space (termed as the HM 'habitat') and identify their 'hotspots' (peak value points) within the catchment. Results showed the output maps of HM habitats from secondary carriers (soil, sediment, and wet deposition) well agreed with the influence of industry contaminants, hydraulic sorting, and precipitation washout process respectively, indicating the potential of SDM in modeling the spatial distributions of the HM. The derived maps of HMs from secondary carriers, along with the human and environmental variables were then input as explanatory variables in SDM to predict the spatial patterns of the final HM accumulation in river water, which was observed to have largely improved the prediction quality. These results confirmed the value of our framework to leverage SDMs from ecology perspective to study HM contamination transport at catchment scale, offering new insights not only to map the spatial HM habitats but also help locate the HM transport chains among different carriers.


Assuntos
Metais Pesados , Poluentes do Solo , Humanos , Poluentes do Solo/análise , Monitoramento Ambiental/métodos , Medição de Risco , Metais Pesados/análise , Solo , China
11.
Insects ; 13(11)2022 Nov 15.
Artigo em Inglês | MEDLINE | ID: mdl-36421955

RESUMO

The Hessian fly, Mayetiola destructor (Say) (Diptera: Cecidomyiidae), is a destructive wheat pest worldwide and an important alien species in China. Based on 258 distribution records and nine environmental factors of the Hessian fly, we predicted the potential distribution area in China under three current and future (2050s and 2070s) climate change scenarios (RCP2.6, RCP4.5, and RCP8.5) via the optimized MaxEnt model. Under the current climate conditions, the suitable distribution areas of the Hessian fly in China were 25-48° N, 81-123° E, and the total highly suitable distribution area is approximately 9.63 × 105 km2, accounting for 9.99% of the total national area. The highly suitable areas are mainly located in northern Xinjiang and central and eastern China. With the rising global temperatures, except for the high-suitable areas under the RCP8.5 scenario, most potential geographic distribution areas would expand in the future. The minimum temperature in February (tmin-2), precipitation in March (prec-3), maximum temperature in November (tmax-11), and precipitation seasonality (bio-15) are important factors that affect the potential geographic distribution of the Hessian fly. This study provides an important reference and empirical basis for management of the Hessian fly in the future.

12.
J Med Entomol ; 59(6): 1936-1946, 2022 Nov 16.
Artigo em Inglês | MEDLINE | ID: mdl-36189969

RESUMO

Exposure to mosquito-borne diseases is influenced by landscape patterns and microclimates associated with land cover. These influences can be particularly strong in heterogeneous urban landscapes where human populations are concentrated. We investigated how land cover and climate influenced abundances of Ae. albopictus (Skuse) (Diptera: Culicidae) and Cx. quinquefasciatus (Say) (Diptera: Culicidae) in Norman, Oklahoma (United States). From June-October 2019 and May-October 2020 we sampled mosquitoes along an urban-rural gradient using CO2 baited BG Sentinel traps. Microclimate sensors at these sites measured temperature and humidity. We mapped environmental variables using satellite images from Landsat, Sentinel-2, and VIIRS, and the CHIRPS rainfall dataset. We also obtained meteorological data from the closest weather station. We compared statistical models of mosquito abundance based on microclimate, satellite, weather station, and land cover data. Mosquitoes were more abundant on trap days with higher temperature and relative humidity. Rainfall 2 wk prior to the trap day negatively affected mosquito abundances. Impervious surface cover was positively associated with Cx. quinquefasciatus and tree cover was negatively associated with Ae. albopictus. Among the data sources, models based on satellite variables and land cover data had the best fits for Ae. albopictus (R2 = 0.7) and Cx. quinquefasciatus (R2 = 0.51). Models based on weather station or microclimate data had weaker fits (R2 between 0.09 and 0.17) but were improved by adding land cover variables (R2 between 0.44 and 0.61). These results demonstrate the potential for using satellite remote sensing for mosquito habitat analyses in urban areas.


Assuntos
Aedes , Culex , Humanos , Animais , Mosquitos Vetores , Ecossistema , Vetores de Doenças
13.
Ecol Lett ; 25(12): 2739-2752, 2022 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-36269686

RESUMO

Species' responses to broad-scale environmental or spatial gradients are typically unimodal. Current models of species' responses along gradients tend to be overly simplistic (e.g., linear, quadratic or Gaussian GLMs), or are suitably flexible (e.g., splines, GAMs) but lack direct ecologically interpretable parameters. We describe a parametric framework for species-environment non-linear modelling ('senlm'). The framework has two components: (i) a non-linear parametric mathematical function to model the mean species response along a gradient that allows asymmetry, flattening/peakedness or bimodality; and (ii) a statistical error distribution tailored for ecological data types, allowing intrinsic mean-variance relationships and zero-inflation. We demonstrate the utility of this model framework, highlighting the flexibility of a range of possible mean functions and a broad range of potential error distributions, in analyses of fish species' abundances along a depth gradient, and how they change over time and at different latitudes.


Assuntos
Meio Ambiente , Dinâmica não Linear , Animais , Análise Espacial , Peixes
14.
Waste Manag Res ; : 734242X221122514, 2022 Oct 05.
Artigo em Inglês | MEDLINE | ID: mdl-36196845

RESUMO

Improving eco-efficiency in the provision of municipal solid waste plays an important role for a sustainable economy. Eco-efficiency of municipal solid waste service providers (MSWSPs) has been generally assessed using the conventional data envelopment analysis (DEA) method. However, this approach is sensitive to data noise and has no statistical properties. To overcome these limitations, in this paper, we adopt the double-bootstrap DEA model to derive robust eco-efficiency scores. This nonparametric method allows conducting statistical inference to explore environmental factors affecting the eco-efficiency of MSWSPs. The empirical approach focused on a sample of 298 MSWSPs in Chile, a middle-income country whose policies for promoting waste recycling are incipient. The results indicated that based on the bias-corrected eco-efficiency scores, the potential saving in costs and unsorted waste could be up to 37.8% on average to generate the same level of output (recycled waste). The findings showed that dealing with data noise and uncertainly is of great importance when conducting benchmarking analysis. The region where the municipality is located, tourism, population density and waste per capita are environmental variables that significantly influenced eco-efficiency of Chilean MSWSPs. Several policy implications are discussed based on the findings of this study.

15.
Biology (Basel) ; 11(9)2022 Sep 09.
Artigo em Inglês | MEDLINE | ID: mdl-36138814

RESUMO

Algae are the naturally produced food for fish in any aquatic ecosystem and an indicator of a productive pond. However, excess abundance of harmful algae can have detrimental effects on fish health. In this study, the algal communities of 30 coastal homestead fish ponds were investigated to identify the diversity, assemblage and controlling environmental variables of harmful algae from a tropical coastal area. The findings showed that 81 of the 89 genera of identified algae were harmful, with the majority of them being in the classes of Cyanophyceae (50.81%), Chlorophyceae (23.75%), Bacillariophyceae (9.5%), and Euglenophyceae (8.47%). Microcystis spp. alone contributed 28.24% to the total abundance of harmful algae. Significant differences (p < 0.05) in algal abundance were found among the ponds with the highest abundance (470 ± 141.74 × 103 cells L-1) at pond (S25) near agricultural fields and the lowest abundance (109.33 ± 46.91 × 103 cells L-1) at pond (S14) which was lacking sufficient sunlight and nutrients. Diversity indices, e.g., dominance (D), evenness (J'), richness (d) and Shannon diversity index (H') ranged from 0.17 to 0.44, 0.23 to 0.6, 0.35 to 2.23 and 0.7 to 1.79, respectively, indicating a moderate range of diversity and community stability. Community composition analysis showed the assemblage was dominated by Cyanophyceae, Chlorophyceae and Bacillariophyceae, whereas, multivariate cluster analyses (CA) identified 11 major clusters. To identify the factors controlling their distribution or community assemblages, eight environmental variables (temperature, pH, dissolved oxygen (DO), salinity, transparency, nitrates, phosphates and sulphate) were measured. ANOVA analysis showed that the variables significantly differed (p < 0.05) among the ponds, and canonical correspondence analysis (CCA) demonstrated that DO, nitrates, phosphates, sulphates, salinity and transparency have the most impact on the abundance of algal genera. In addition, analyses with Pearson's correlation coefficient showed that the abundance of total algae, diversity and community were mainly governed by phosphates and sulphates. These results can be used to identify and control these toxic algal groups in the local aquaculture sector.

16.
Animals (Basel) ; 12(18)2022 Sep 08.
Artigo em Inglês | MEDLINE | ID: mdl-36139197

RESUMO

Accurate descriptions of home ranges can provide important information for understanding animal ecology and behavior and contribute to the formulation of conservation strategies. We used the grid cell method and kernel density estimation (KDE) to estimate the home range size of golden snub-nosed monkeys (Rhinopithecus roxellana) in Tangjiahe National Nature Reserve. We also used Moran's eigenvector maps analysis and variation partitioning to test the influence of environmental variables on home range use. The seasonal home range size was 15.4 km2 in spring, 11.6 km2 in summer, 13.7 km2 in autumn, and 15.6 km2 in winter, based on the grid cell method. The seasonal core area of 50% KDE was 9.86 km2 in spring, 5.58 km2 in summer, 7.20 km2 in autumn, and 4.23 km2 in winter. The environmental variables explained 63.60% of home range use intensity in spring, 72.21% in summer, 26.52% in autumn, and none in winter, and some environmental variables contributed to the spatial variation in home range use intensity. Water sources, tree density, and dominant trees of Chinese wingnut (Pterocarya stenoptera) were the important environmental factors determining home range use. These environmental factors require protection to ensure the survival of the golden snub-nosed monkey.

17.
Artigo em Inglês | MEDLINE | ID: mdl-36142105

RESUMO

Background: Tickborne-encephalitis (TBE) is a potentially life-threating neurological disease that is mainly transmitted by ticks. The goal of the present study is to analyze the potential uniform environmental patterns of the identified TBEV microfoci in Germany. The results are used to calculate probabilities for the present distribution of TBEV microfoci in Germany based on a geostatistical model. Methods: We aim to consider the specification of environmental characteristics of locations of TBEV microfoci detected in Germany using open access epidemiological, geographical and climatological data sources. We use a two-step geostatistical approach, where in a first step, the characteristics of a broad set of environmental variables between the 56 TBEV microfoci and a control or comparator set of 3575 sampling points covering Germany are compared using Fisher's Exact Test. In the second step, we select the most important variables, which are then used in a MaxEnt distribution model to calculate a high resolution (400 × 400 m) probability map for the presence of TBEV covering the entire area of Germany. Results: The findings from the MaxEnt prediction model indicate that multi annual actual evapotranspiration (27.0%) and multi annual hot days (22.5%) have the highest contribution to our model. These two variables are followed by four additional variables with a lower, but still important, explanatory influence: Land cover classes (19.6%), multi annual minimum air temperature (14.9%), multi annual sunshine duration (9.0%), and distance to coniferous and mixed forest border (7.0%). Conclusions: Our findings are based on defined TBEV microfoci with known histories of infection and the repeated confirmation of the virus in the last years, resulting in an in-depth high-resolution model/map of TBEV microfoci in Germany. Multi annual actual evapotranspiration (27%) and multi annual hot days (22.5%) have the most explanatory power in our model. The results may be used to tailor specific regional preventive measures and investigations.


Assuntos
Vírus da Encefalite Transmitidos por Carrapatos , Encefalite Transmitida por Carrapatos , Ixodes , Animais , Geografia , Alemanha , Humanos
18.
Environ Res ; 214(Pt 3): 114102, 2022 11.
Artigo em Inglês | MEDLINE | ID: mdl-35973464

RESUMO

Landfills are the third largest source of anthropogenic CH4 emissions. Anaerobic oxidation of methane (AOM) activity and communities of methane-oxidizing bacteria were investigated in three informal landfills in this study, namely, BJ, CH and SZ landfills, among which BJ and CH represent traditional anaerobic landfills, while the SZ landfill was subjected to aeration to accelerate waste stabilization. The AOM rates of the investigated landfilled wastes ranged from 3.66 to 23.91 nmol g-1 h-1. Among the three landfills, the AOM rate was highest in the SZ-1-Top sample, which was closest to the aeration pipe. Among the possible electron acceptors for AOM, including NO3-, NO2-, SO42- and Fe3+, the NO2--N content was the only variable that was positively correlated with the AOM rate. Compared with α-Proteobacteria methanotrophs, γ-Proteobacteria methanotrophs were more abundant in the landfilled waste, especially Methylobacter, which was detected in nearly all samples. Members of the family Methylomirabilaceae, including Candidatus Methylomirabilis, were also detected in the SZ-1 and SZ-2-Bot samples. The relative abundance of the main methanotrophs in the families Methylomonadaceae, Methylococcaceae, Rokubacteriales and Methylomirabilaceae, the genus Methylocystis and the phylum NC10 were all positive correlations with the contents of NO2--N in the landfilled waste samples. Additionally, significantly positive correlations were observed between the AOM rates and the relative abundance of the main methanotrophs except for the family Methylococcaceae. This indicated that aeration could enhance the conversion of nitrogen compounds in the landfilled waste, in which the high contents of NO2--N could stimulate the growth of methanotrophs and increase AOM rate. These findings are helpful for understanding the mechanisms of CH4 oxidation in landfills and for taking effective measures to mitigate CH4 emissions from landfills.


Assuntos
Methylococcaceae , Microbiota , Anaerobiose , Humanos , Metano , Dióxido de Nitrogênio , Oxirredução , Instalações de Eliminação de Resíduos
19.
Animals (Basel) ; 12(15)2022 Jul 29.
Artigo em Inglês | MEDLINE | ID: mdl-35953924

RESUMO

The Iberian porpoise population is small and under potentially unsustainable removal by fisheries bycatch. Recently, a marine Site of Community Importance (SCI) was legally approved in Portugal, but no measures ensued to promote porpoise conservation. Information about porpoise abundance and distribution is fundamental to guide any future conservation measures. Annual aerial surveys conducted between 2011 and 2015 show a low overall porpoise abundance and density (2254 individuals; 0.090 ind/km2, CV = 21.99%) in the Portuguese coast. The highest annual porpoise estimates were registered in 2013 (3207 individuals, 0.128 ind/km2), followed by a sharp decrease in 2014 (1653 individuals, 0.066 ind/km2). The porpoise density and abundance estimated in 2015 remained lower than the 2013 estimates. A potential distribution analysis of the Iberian porpoise population was performed using ensembles of small models (ESMs) with MaxEnt and showed that the overall habitat suitability is particularly high in the Portuguese northern area. The analysis also suggested a different pattern in porpoise potential distribution across the study period. These results emphasize the importance of further porpoise population assessments to fully understand the spatial and temporal porpoise habitat use in the Iberian Peninsula as well as the urgent need for on-site threat mitigation measures.

20.
Sci Total Environ ; 849: 157856, 2022 Nov 25.
Artigo em Inglês | MEDLINE | ID: mdl-35934043

RESUMO

Annual gross primary productivity (AGPP) of terrestrial ecosystems is the largest carbon flux component in ecosystems; however, it's unclear whether photosynthetic capacity or phenology dominates interannual variation of AGPP, and a better understanding of this could contribute to estimation of carbon sinks and their interactions with climate change. In this study, observed GPP data of 494 site-years from 39 eddy covariance sites in Northern Hemisphere were used to investigate mechanisms of interannual variation of AGPP. This study first decomposed AGPP into three seasonal dynamic attribute parameters (growing season length (CUP), maximum daily GPP (GPPmax), and the ratio of mean daily GPP to GPPmax (αGPP)), and then decomposed AGPP into mean leaf area index (LAIm) and annual photosynthetic capacity per leaf area (AGPPlm). Furthermore, GPPmax was decomposed into leaf area index of DOYmax (the day when GPPmax appeared) (LAImax) and photosynthesis per leaf area of DOYmax (GPPlmax). Relative contributions of parameters to AGPP and GPPmax were then calculated. Finally, environmental variables of DOYmax were extracted to analyze factors influencing interannual variation of GPPlmax. Trends of AGPP in 39 ecosystems varied from -65.23 to 53.05 g C m-2 yr-2, with the mean value of 6.32 g C m-2 yr-2. Photosynthetic capacity (GPPmax and AGPPlm), not CUP or LAI, was the main factor dominating interannual variation of AGPP. GPPlmax determined the interannual variation of GPPmax, and temperature, water, and radiation conditions of DOYmax affected the interannual variation of GPPlmax. This study used the cascade relationship of "environmental variables-GPPlmax-GPPmax-AGPP" to explain the mechanism of interannual variation of AGPP, which can provide new ideas for the AGPP estimation based on seasonal dynamic of GPP.


Assuntos
Ecossistema , Fotossíntese , Ciclo do Carbono , Mudança Climática , Estações do Ano , Água
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