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The genetic progress achieved by animal breeding programs may be affected by genotype-by-climate interactions (GxC). This systematic literature review assesses the scientific evidence for GxC on multiple traits of cattle, pigs, and poultry. Two search engines (Scopus, Web of Science) were queried for original peer-reviewed scientific (English full-text) studies. We included (1) observational studies and designed experiments considering dairy or beef cattle, swine, chicken or turkeys, where (2) at least one production, fertility, or health trait was tested for GxC, (3) the existence of GxC was tested directly based on temperature, relative humidity, or climatic indices for heat or cold stress, and (4) genetic effects within a breed or line were investigated. The search resulted in 46 eligible studies, with a (low) risk that the requirement of full-text English studies may have resulted in some work not included in this review. Our review shows an increase in GxC studies from 2015 onwards. Cattle was the most studied species (n = 36; 78.3%), whereas eligible studies on turkeys were lacking. Climatic parameters used in the studies ranged from well-known parameters (e.g., temperature, temperature-humidity index) to more complex indices combining temperature, relative humidity, wind speed and solar radiation. All observational studies (n = 40; 87.0%) used weather station data. In total, 75 traits were studied, which were predominantly production traits regardless of species. Studies on fertility and health traits have been emerging from 2010 onwards, but their numbers still lag far behind those for production traits. Genotype-by-climate interaction was confirmed in 54.0% of the study outcomes. This systematic review shows that little is known about the role of GxC in health and fertility traits in cattle, and for all traits in pigs and poultry in general. As current evidence shows that genotype-by-climate interaction is common across species and traits, we suggest to collect detailed climatic data and use them to assess the presence of GxC in indoor and outdoor production systems, as well. [ABSTRACT FROM AUTHOR]

The paper considers a problem of modeling the impact of the future climate on the yield of crops (in the example of spring wheat). The authors have analyzed the sources of climatic data and values of agrometeorological indicators for past and future periods. Using agroclimatic parameters, they have developed a mathematical model of the dependence of the median of the distribution function of spring wheat yield on climatic changes. The authors performed the calculations using this model and analyzed the obtained results. The analysis indicates a significant increase in the yield level of spring wheat in 2030–2040 and an increase in the risk of losses of its yield compared to historical data. [ABSTRACT FROM AUTHOR]

Soil temperatures at both surface and various depths are important in changing environments to understand the biological, chemical, and physical properties of soil. This is essential in reaching food sustainability. However, most of the developing regions across the globe face difficulty in establishing solid data measurements and records due to poor instrumentation and many other unavoidable reasons such as natural disasters like droughts, floods, and cyclones. Therefore, an accurate prediction model would fix these difficulties. Uzbekistan is one of the countries that is concerned about climate change due to its arid climate. Therefore, for the first time, this research presents an integrated model to predict soil temperature levels at the surface and 10 cm depth based on climatic factors in Nukus, Uzbekistan. Eight machine learning models were trained in order to understand the best-performing model based on widely used performance indicators. Long Short-Term Memory (LSTM) model performed in accurate predictions of soil temperature levels at 10 cm depth. More importantly, the models developed here can predict temperature levels at 10 cm depth with the measured climatic data and predicted surface soil temperature levels. The model can predict soil temperature at 10 cm depth without any ground soil temperature measurements. The developed model can be effectively used in planning applications in reaching sustainability in food production in arid areas like Nukus, Uzbekistan. [ABSTRACT FROM AUTHOR]

This work investigates the impact of environmental changes on the efficiency of the photovoltaic panel system. To analyze the impact, we first study the effect of the current climatic parameters on the evolution of the output energy of two solar photovoltaic modules, such as irradiance, temperature and wind speed. Meteorological data was acquired using specific sensors for temperature, irradiance, and wind speed; these data have been initially conditioned by using of 34972A LXI data acquisition and thereafter, interfaced to a PC using IEEE 488.2 general purpose interface bus (GPIB). We use the LabVIEW real-time interface to display and store the collected data in the PC. Finally, from the data stored, we have carried out the discussions on the experimental results-based data driven analysis using clustered heatmap which supports the approval of this impact using climate forecasts and strategy to adopt for an efficient and economical used and consequently a solar photovoltaic energy under climatic constraints is proposed. [ABSTRACT FROM AUTHOR]

Copyright of Arab Journal of Plant Protection is the property of Arab Society for Plant Protection and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Outdoor thermal comfort is an essential aspect of sustainable architecture, and it is key to maintaining a safe outdoor environment. Several programs have been developed to predict thermal comfort based on climate parameters, as well as the built environment, and to forecast comfort within the urban context. Solar radiation and wind speed can be manipulated by the constructed environment. This research uses Jabal Al Natheef as a case study. An attempt is made to evaluate the outdoor thermal comfort of the urban environment and to identify the contributing factors that impede or facilitate outdoor thermal comfort in Amman. The goal of this research is to investigate behavioral factors, including perception, in addition to environmental parameters, such as thermal adaptation and solar radiation intensity, as well as the green infrastructure implementation. A comprehensive literature analysis of outdoor thermal comfort over the last decade is conducted in this paper, which included adaptive and rational thermal comfort approaches, from the standpoint of contextualizing the behavioral perspective that is connected to the use of urban space. This research employed a scenario-based approach, enabling site assessment and community participation. The possibility of enhancing the outdoor thermal comfort in Jabal Al Natheef is discussed. Furthermore, we identify the effect of design measures that influence outdoor thermal comfort. Recommendations for improving outdoor thermal conditions in the region to improve urban life and stimulate outdoor activities are provided. The results indicate that vegetation has a significant effect on reducing air temperature by providing shade. Urban areas with more vegetation have a mean radiant temperature that is significantly reduced, by almost 7 °C, especially during the summer. [ABSTRACT FROM AUTHOR]

The mountain forests of the Northwestern Caucasus represent unique refugia for the native biodiversity of flora and fauna. Endemic species are also preserved among soil invertebrates, including the group of earthworms, which are important ecosystem engineers. This study assesses the spatial distribution of the endemic anecic species of earthworms Dendrobaena nassonovi nassonovi Kulagin, 1889 in deciduous, coniferous–deciduous, small-leaved, and conifer forests of the Northwestern Caucasus (a total of 1028 geographical points were surveyed, of which the species was found in 185 points) based on our own field data by modeling the current potential areas using the Maxent software. The D. n. nassonovi potential area maps show a high probability of the species inhabiting mid- and high-mountain forests of the Northwestern Caucasus and being confined to mixed coniferous–deciduous and beech forests. The optimum soil and climatic parameters, as well as a lack of large-scale business operations in the mid- and high-mountain forests, make it possible for these ecosystems to remain suitable refugia, in particular for the endemic anecic species of Caucasus earthworms D. n. nassonovi. [ABSTRACT FROM AUTHOR]

In the context of climate change, the paper presents an analysis of the evolution of grapevine phenophases, in the period 1991-2021, for four grapevine cultivars Selena, Blasius, Rubin and Radames, and two clones Sauvignon blanc 9 Bl, Feteasca alba 29 Bl homologated at SCDVV Blaj. The study is based on the climatic and phenological data from SCDVV Blaj. The climatic data have been processed into fourteen parameters and for the phenological periods the starting date was analyzed. Regarding the average annual temperature, during 2010-2021 there is an increase of 1.1 ºC compared to the multiannual average reference temperature (calculated as the annual average of the years 1975-2010), which means that in the studied area, during the period 2010-2021 there was a warming compared to reference years. The average duration of the vegetation period from 2010-2021 is shorter than the reference period by 3.2 days. In 2011 the annual aridity index denotes a semi-arid dry climate, and in 2012, 2015, 2017 and 2019 a moderately humid climate. The hydrothermal coefficient was higher in the studied period compared to the reference period, registering values between 1.0 (2011) and 2.8 (2016), which has a positive influence on grape production. The Huglin index for the studied period is between 2237.6 in 2021 and 2928.5 in 2012, with an average of 2542.6 which places Tarnave vineyard area in a warm climate zone. Concerning the precipitation, a slight increase of 34.7 mm/m2 compared to the multiannual reference amount was monitored. In these conditions the warming of the climate induced an earlier budburst with an average of 8 days, correlated with an earlier maturation with 9-11 days in average. So far for the blooming and veraison phenophases starting date, no differences of the outrunning were clearly observed. [ABSTRACT FROM AUTHOR]

The uncertainty of climatic or weather variations makes human adaptation a challenging task. Though lots of techno developments have taken place addressing the need of predictions and forecasting of climatic behavior, the uncertainty of atmospheric and geoprocesses poses a severe challenge to the effectivity of efforts in dealing with disasters. It has become very crucial to understand the future atmospheric uncertainty process and further predict and forecast for analysis of different activities based on geographical locations. Climate parameters are mandatorily required to improve system activities and output analysis of acquired data. For a sustainable adaptation, this is very important on how the uncertainty of variations in climatic parameters is dealt and the decisions based upon appropriate forecasting model are taken. The work has primarily focused on the development of an appropriate model, training the model with massive monthly rainfall and temperature data which can be used to analyze any climatic predictions and provide support to deal with adverse future situations. This model determines the appropriate amount of rainfall and temperature varied during the dry season and helps set a relationship with other input variables like humidity and maximum and minimum temperature. The model has been trained and tested using the obtained data and performed well with better accuracy. The model developed using long short-term memory algorithm of deep learning for predicting rainfall and temperature climatic variables is supported with the study of the main factors affecting monthly climatic change analysis. Monthly precipitation, rainfall intensity, and temperature have been used in the multipurpose prediction model to analyze the monthly and yearly climatic change prediction. The model has also been optimized for precision, accuracy, and computational speed, which are affected by number of iterations, neurons of a hidden layers, epochs, and batch size. [ABSTRACT FROM AUTHOR]

Plentiful and diverse Organic wastes such as green, food, pruning and landscaping waste necessitate upon effective and efficient recycling strategies such as composting. In this article, for the first time, machine learning (ML) models have been applied to model compost generation rate as a function of climatic parameters and organic waste content. The data size contained approximately 864 sample points records of the meteorological parameters (Modern-Era Retrospective Analysis), organic waste (Central Pollution Control Board) and compost yields (Open Government Data) data for 2010–2021. The modelling efforts involved the consideration of MLP and traditional ML algorithms namely k-nearest neighbour (kNN), gradient boosting (GB) and random forest (RF) for prediction and autoregressive integrated moving average (ARIMA) model supplemented ML models for long-term forecasting of the compost generation rate. Model validation resulted in an RMSE of 0.757 and R2 of 0.99 for GB model, and a correlation index of 0.68 between observed and predicted values to thereby outperform all other models. However, forecasted data for ten years after the predicted outcomes resulted in the best performance of ARIMA–MLP model with a standard error of 21.1152 and a CP yield of 74,958 kg. Thereby, the findings affirm upon the evidence for the limitations of the broader application of the empirical approaches and the feasibility of ML algorithms as a potential reconstruction technique for developing robust and accurate region-specific compost prediction and forecasting models to assist integrated circular agricultural system development for a sustainable global future. [ABSTRACT FROM AUTHOR]

Artemisia jacutica Drob. (Yakut wormwood) is a biennial plant endemic to Eastern Siberia. This species is distributed across the Republic of Sakha (Yakutia) and southern Central Siberia, colonizing salt meadows and grasslands, steppe areas, saline to sodic surface soil patches, abandoned agricultural lands, and ruderal habitats. The species is rather rare in Buryatia, due to the southeastern frontier of its area. The essential oil of the Yakut wormwood contains chamazulene as a principal compound component with an anti-inflammatory effect. The data generated within the survey and the published statistics indicate that the climatic conditions affect the formation of the essential oil component composition in plants, which is obviously appropriate to provide the best adaptation of the plants to their environmental growing conditions. Therefore, the effects of climatic conditions on the essential oil component composition in the Yakut wormwood plants result in the formation of two chemotypes known as Buryat and Yakut. It has been ascertained that the formation of these chemotypes occurs due to the differences between the rates of heat and moisture supply to the lands favorable for plant growth, expressed by the hydrothermal coefficient (HTC). The temperature–humidity extremeness parameters defining the coefficient based on annual data greatly affect the ratio of components in the essential oil. The climate-related factors (air temperature, precipitation, etc.) and their integrated potential can influence certain constituents and their proportions in the essential oil, affecting their variability. [ABSTRACT FROM AUTHOR]

Reliable identification of realistic biomass at regional level is particularly important in creating a real energy strategy. It must stand for the region in particular in the long-term aspect of its sustainable development. The aim of the paper is to identify and quantify environmental impacts, especially microclimatic impacts, on the possibility of establishing and growing economically and energy-efficient plantations of fast-growing energy plants in Slovakia regions. The NUTS III methodology was used to locate the climatic conditions of the Slovakia regions. Climatic factors in Slovakia regions were expressed as average monthly air temperatures and average monthly precipitation for the vegetation period from April to October. The climatic parameters of the model plantation in the Nitra region were defined on the basis of measurements of the Physicus Meteostation, located in the field conditions of Kolíòany village. Regions in the southern and south-eastern regions of Slovakia (Bratislava, Trnava, Nitra, Košice) are the most climatic friendly for the growing Mustanthus and Populus. The Northern regions (Žilina and Prešov) are less suitable for climatic reasons - the shorter length of vegetation period required for the economically efficient production of above-ground biomass. In the Nitra region, productivity in real climatic conditions is 33.66 t.ha-1 (Miscanthus) and 135.14 t.ha-1 (Populus). [ABSTRACT FROM AUTHOR]

Prediction of soil temperature (ST) at multiple depths is important for maintaining the physical, chemical, and biological activities in soil for various scientific aspects. The present study was conducted in a semi-arid region of Punjab to predict the daily ST at 5-cm (ST5), 15-cm (ST15), and 30-cm (ST30) soil depths by employing the three-hybrid machine learning (ML) paradigms, i.e. support vector machine (SVM), multilayer perceptron (MLP), adaptive neuro-fuzzy inference system (ANFIS) optimized with slime mould algorithm (SMA), particle swarm optimization (PSO), and spotted hyena optimizer (SHO) algorithms. Five scenarios with different input variables were constructed using daily meteorological parameters, and the optimal one was extracted by exploiting the GT (gamma test). The feasibility of the proposed hybrid SVM, MLP, and ANFIS models was inspected based on performance metrics and visual interpretation. According to the results, the SVM-SMA model yields better estimates than other models at 5-cm, 15-cm, and 30-cm soil depths, respectively, for scenario 5 in the validation phase. Furthermore, conferring to the results, the SMA algorithm-based SVM model had lower (higher) values of mean absolute error, root mean square error, and index of scattering (Nash–Sutcliffe efficiency, coefficient of correlation, and Willmott index of agreement) and proved the better feasibility of SVM models in predicting daily ST at multiple depths on the study site. [ABSTRACT FROM AUTHOR]

Nowadays, Surabaya experience Urban Heat Island (UHI) phenomenon because of the increase of surface temperature from 1994 until 2011. The urban structure parameters have a role in decreasing the UHI phenomenon. Rajawali is a historic area where it can be sensitive to climatic condition and urban heat island. This paper aimed to analyze the correlation of urban structure parameters toward climatic variables (as an indicator affecting UHI) in the heritage area of Rajawali. This study focuses on some urban structure parameters that are Building Coverage Ratio (BCR), Floor Area Ratio (FAR), aspect ratio (H/W), Volumetric Compactness (S/V) and land cover in the site. The analysis method is a simulation from Envi-met where simulation performed is run in March 2018. In order to check how far the urban structure affects climatic variable, the urban structure parameters are compared with each variable of climatic using the statistical package, R. For correlation analysis Pierson's r coefficient is used. The result shows that not all urban structure parameters correlate with climatic variables in the Heritage Area. The findings of this study are expected to be the basis for designing the heritage area in Rajawali so that the design can respond to the UHI phenomenon in Surabaya. [ABSTRACT FROM AUTHOR]

Copyright of Periódico Tchê Química is the property of Grupo Tche Quimica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

McArthur's fire danger index (FDI) is an integrated measure of the risk of fire occurrence, spreading speed and containment difficulty. The climatic parameter-dependent McArthur forest and grass fire danger indices were used to categorize fire danger severity. This paper explored the characteristics of four different climatic stations in Victoria, Australia, to determine their spatial and temporal variations impacting FDIs and the risk of fire occurrence. Sensitivity analysis was performed to develop nomograms to relate the variation of FDIs with key climatic parameters. These nomograms combine temperature, relative humidity and wind speed to determine fire risk categories in assisting field-based emergency and fire management authorities to identify danger and response plans to mitigate risks by mobilizing human and mechanical resources. [ABSTRACT FROM AUTHOR]

Climate change threatening the word food security including fisheries production. The current study aimed to find the relationship between different climatic variables and fish production by generating spatial maps. The climatic parameters data viz., mean maximum temperature; mean minimum temperature; total rainfall, and mean wind speed were plotted in GIS (Geographical Information System) platform and thematic mapping of it's for all the districts of Maharashtra for the year 1975 and 2017 on quarter basis was done using QGIS 3.6.1. The thematic maps of the percentage change in parameters of all the quarters of the year 2017 and 1975 were done for all the zone of Maharashtra. In addition, the thematic maps of the percentage change in parameters along with fish production of all the quarters of the year 2017-18 for the year 2012 were done for all the zone. The sensitivity analysis of climatic parameters with inland fish production for Maharashtra state and all the seven zones were done using GAM (Generalized Additive Model). The mean maximum temperature (MMAX) and total monthly rainfall (TMRF) were found to the most significant factors in the prediction of inland fish production. The average increase in MMAX during the 2nd and 3rd quarters (April to September) was less than the average increase in MMAX during the 1st and 4th quarters, whereas, in case of rainfall an average decrease was estimated during the 2nd and 3rd quarter. The current study found that Nagpur and Pune were the two highest fish-producing regions, and Konkan and Aurangabad were the two least productive regions. [ABSTRACT FROM AUTHOR]

Motivation: Leaf traits represent an important component of plant functional strategies, and those related to carbon fixation and nutrient acquisition form the leaf economics spectrum. However, observations of functional leaf traits are underrepresented in tropical regions in comparison with those in temperate areas. Brazil, a country with continental scale and vast biodiversity is a timely example, where many biomes are impacted by human activities and climate change. However, leaf traits relevant to understand vegetation responses to these impacts remain poorly quantified for many species found in the country. We compiled an extensive data set of four functional leaf traits for native woody species occurring in the Brazilian territory. In addition to trait observations, sampling dates and geo‐references were compiled and climatic parameters and soil properties of each sampling site were extracted from several databases. Main types of variables contained: The LT‐Brazil data set contains 3,479, 1,216, 775 and 775 clean observations of leaf mass per area, leaf nitrogen (N) concentration per unit mass, leaf phosphorus (P) concentration per unit mass, and leaf N : P ratio, respectively, from native woody species, encompassing information of biome, vegetation, taxonomic data, geographical coordinates, climatic parameters, as well as soil properties. Spatial location and grain: We compiled trait observations from 223 sites under native vegetation distributed in all main biomes (i.e., Amazônia, Caatinga, Cerrado, Mata Atlântica, Pampa and Pantanal) across the Brazilian territory. Time period and grain: The data represent information published and/or sampled during the last 25 years. Major taxa and level of measurement: Our compilation was focused on trait data observed for native woody species, excluding monocots, palm trees, herbs, and hemiparasitic plants. Thus, 108, 478 and 1,321 botanical families, genera and species were included, covering c. 9% of the woody angiosperm flora of Brazil. Software format: Data are provided as comma‐separated value (.csv) files. [ABSTRACT FROM AUTHOR]

Copyright of Kemija u Industriji is the property of Croatian Society of Chemical Engineers and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Inevitable issues concerning the sustainability of groundwater resources are crucial under the present climatic situation. Therefore, the prevision of groundwater environments may able to reinforce the management system. In this respect present study considered a new method to predict long-term groundwater level framework as an alternative option of expensive physical models. The proposed Bidirectional Long Short-Term Memory (BLSTM) model can efficiently capture Spatio-temporal features from historical data. A highway LSTM network is also introduced within the architecture of the model to optimize the analysis. The relative performance of the proposed BLSTM with the highway LSTM (BHLSTM) network compared with simple BLSTM. Stack size increment of the BHLSTM and BLSTM layers can enhance the learning ability and improve by incorporating straight LSTM at the top of the architecture. The proposed model was applied to predict the groundwater level exemplary of the Varuna River basin for twenty years. The model incorporates the historical annual average of total precipitation, temperature, relative humidity, actual evapotranspiration, and groundwater level data to develop and validate the models. The result shows that the signals are captured reasonably well by a stack of four BHLSTM and straight LSTM models in forecasting groundwater levels. The predicted water level range (0—20 mbgl) has four categories low, medium, high, and very high which eventually, illustrates the water-threatened situation in upcoming years in the study area. It is also recommended to exploring this proposed method for further improvements and extensions towards interpreting spatial features. [ABSTRACT FROM AUTHOR]

• Key message: This document provides valuable environmental information about a triplets' essay of Scots pine and Maritime pine in Spain. The dataset characterizes the soil profile (physicochemical parameters of organic and mineral horizons), climate, physiography, understory and overstory. Dataset access is athttps://doi.org/10.5281/zenodo.4384530and associated metadata is available athttps://metadata-afs.nancy.inra.fr/geonetwork/srv/fre/catalog.search#/metadata/21cca830-daf9-4913-9b5b-a185d77943d5 [ABSTRACT FROM AUTHOR]

Considering the very important role of climatic parameters on the yield and biomass of plants (especially in rain-fed agriculture), in this research, using data series of 9 stations during 1968–2017 the influence of 6 climatic parameters including the average of annual maximum and minimum temperature (Max-T and Min-T), the average of annual sunshine (Su-Sh), the average of annual relative humidity (H), the average of annual wind speed (Wi) and the average annual precipitation (P) on the yield and biomass of winter wheat (YWW and BWW) and barley (YB and BB) as two important and strategic species to provide the human food and the livestock feed in Iran, was investigated and prioritized. To assess the effectiveness rate of the climatic parameters on the response variables (YWW, BWW, YB and BB), the random forest algorithm (RF) was used. The results indicated that the RF algorithm had a good ability to predict the response variables because (1) the linear regression between simulated and predicted YWW, BWW, YB and BB using the AquaCrop model and the RF algorithm (respectively) had no difference with perfect reliable line (Y = X) in 0.05 or 0.01 significant levels and (2) R2 between simulated and predicted YWW, BWW, YB and BB was significant at 0.01 levels. According to the results, the P, Wi and Min-T parameters were the most influential climatic parameters on the YWW (respectively), the Min-T, Wi and P parameters were the most influential parameters on the YB and the Wi and Min-T parameters were the most influential parameters on the BWW and BB. On the other hand, in all stations, the Su-Sh and Hu were the least influential parameters on the YWW, BWW, YB and BB. [ABSTRACT FROM AUTHOR]

The present study aims to investigate the morphological characteristics of the Blanche de Montagne sheep breed, mainly known by its long white fleece. The morphological characterization was performed on a total of 70 unrelated individuals of both sexes, having between 2 and 8 teeth and belonging to 13 farms located in the Ouarzazate region. The body measurements studied were body weight, body length, chest circumference, height at withers, rump height, chest depth, chest width, hip width, head length, head width, ear length, ear width, horn length, cannon circumference, wool length, and tail length. These measurements averaged 28.2±8.10 kg, 65.8±6.25 cm, 73.5±6.71 cm, 59.5±4.39 cm, 59.5±4.72 cm, 27.4±2.90 cm, 19.8±2.70 cm, 21.0±2.14 cm, 19.2±1.57 cm, 11.0±1.01 cm, 9.71±1.02 cm, 5.47±0.53 cm, 43.2±13.8 cm, 7.44±0.77 cm, 10.9±3.56 cm, and 31.8±4.36 cm, respectively. Descriptive statistics presented an overall coefficient of variation less than 15%, showing a homogeneous morphostructure of the breed. Most characters were small in relation with the low productivity of pastures. Moreover, 77.5% of correlation coefficients among the different body measurements were positive and significant, reflecting the strong morphological harmony of the breed, suggesting a long period of adaptation to its environment. The variance analysis showed that sex influenced the measurements, with males having the highest values. Similarly, individuals with 6 or 8 teeth showed higher values than those with 2 or 4 teeth. Through the comparison with other Moroccan breeds, the variation of some morphological traits was found in relation to some climatic parameters (mainly winter temperatures) and feeding supplementation. [ABSTRACT FROM AUTHOR]

The southern part of Bangladesh is one of the most affected regions facing the devastating impacts of climate change particularly in case of crop production. Impacts of climate-induced disasters and climatic variability on cropping pattern and crop production in Satkhira district have been studied. Thirty-five year (1980–2014) climatic data (temperature, humidity, and rainfall) were used for seasonal (Kharif-I, Kharif-II, and Robi) trend analysis. It has been identified that the cropping pattern needed to be modified by local farmers due to climate change impacts and crop production has declined severely in the study areas. For instance, in the Kharif-II season, during the period 2008–2009 with an agricultural land area of 13,670 hectares, the average production was only 2.58 mt per hectare. The study shows a significant strong positive correlation between seasonal average rainfall and seasonal average humidity (r = 0.75, p < 0.05) during the Robi season. A significant strong negative correlation between seasonal average temperature and seasonal average humidity (r = − 0.60, p < 0.05) during the Kharif-I season was also found. We suggest some adaptation strategies to cope with the changing condition such as increased use of salt- and flood-tolerant varieties, floating bed vegetable cultivation, and dyke cropping system (mainly for vegetable), which can eventually reduce vulnerabilities and increase food security. [ABSTRACT FROM AUTHOR]

Human interest in meteorological domain has been manifested since ancient times, when scientists began to observe and describe the weather and have tried to explain most of the weather phenomena. Science in 2007 at North University of Baia Mare is continuously registered meteorological data with Oregon Scientific WMR 100 weather station type. It can follow the climatic parameters continuously from the urban area and microclimates. Recorded weather data are displayed on the main console; it has the possibility to connect to a computer and through a program allows unlimited recording of the data. Recorded weather variables are temperature indoor/outdoor, humidity indoor/outdoor, wind speed and direction, average monthly rainfall, daily, annual, atmospheric pressure, dew point temperature, the cooling produced by wind, temperature index and more. The main aim of this paper is to survey the environment for application meteoinformatics importance of projects and for ecological research. As we know, it is necessary to extend the perspectives in studying of Environment Information Systems (EISs) integrated in the urban ambient problematic. Meteoinformatic systems became usable in terms of research recently, but their efficiency and ease of use has led to an increasing rate of their use. As prospects for the future would be to create a computerized network through which to connect personal weather stations, obtaining valuable information from several regions of the country and can, thus clearly distinguish details of the mezoclimate of each region. [ABSTRACT FROM AUTHOR]

Evaluation of the spatial distribution of 2 ecologically similar, but different, in terms of their spatial ranges, earthworm species, D. octaedra and D. attemsi, in the belt forests of northwestern Caucasus were based on our own natural data and using geographic information system (GIS) modeling of modern potential distributions. The quantitative records of earthworms were collected in beech, deciduous, dark coniferous, coniferous-deciduous, and pine forests (1028 geographic locations). Of the most important microsites inhabited by the epigeic earthworms, 2 (plant litter and deadwood) were examined. It was demonstrated that there was high correlation of the 2 species with the humidity of the habitat and the presence of deadwood at different stages of decomposition, especially for D. attemsi, which lives mainly in deadwood in all of the forest types. The high correlation of these species to coniferous-deciduous forests and dark coniferous forests was demonstrated on both the basis of the field data analysis and the GIS modeling results. [ABSTRACT FROM AUTHOR]

In Romania, foehn winds are short-time atmospheric phenomena of low-to-medium intensity, which do not appear always in the weather station-performed observations. Such situations require additional data to provide a larger and dynamic picture in comparison with the punctual information sent by stations. This paper aims to capture, present and analyze the characteristic parameters of northern Oltenia foehn winds, in the Carpathian-Balkan Internal Curvature. Herein, it is shown a typical foehn situation revealed by weather stations and also by satellite images (MSG), atmospheric radio soundings and numerical modeling. [ABSTRACT FROM AUTHOR]

Forest herb-layer vegetation responds sensitively to environmental conditions. This paper compares drivers of both taxonomic, i.e., species richness, cover and evenness, and functional herb-layer diversity, i.e., the diversity of clonal, bud bank and leaf-height-seed plant traits. We investigated the dependence of herb-layer diversity on ecological determinants related to soil properties, climatic parameters, forest stand characteristics, and topographic and abiotic and biotic factors associated with forest floor structure. The study was conducted in different forest types in Slovenia, using vegetation and environmental data from 50 monitoring plots (400 m2 each) belonging to the ICP Forests Level I and II network. The main objective was to first identify significant ecological predictors and then quantify their relative importance. Species richness was strongly determined by forest stand characteristics, such as richness of the shrub layer, tree layer shade-casting ability as a proxy for light availability and tree species composition. It showed a clear positive relation to soil pH. Variation in herb-layer cover was also best explained by forest stand characteristics and, to a lesser extent, by structural factors such as moss cover. Species evenness was associated with tree species composition, shrub layer cover and soil pH. Various ecological determinants were decisive for the diversity of below-ground traits, i.e., clonal and bud bank traits. For these two trait groups we observed a substantial climatic signal that was completely absent for taxonomy-based measures of diversity. In contrast, above-ground leaf-height-seed (LHS) traits were driven exclusively by soil reaction and nitrogen availability. In synthesis, local stand characteristics and soil properties acted as the main controlling factors for both species and trait diversity in herb-layer communities across Slovenia, confirming many previous studies. Our findings suggest that the taxonomic and functional facets of herb-layer vegetation are mainly influenced by a similar set of ecological determinants. However, their relative importance varies among individual taxonomy- and functional trait-based diversity measures. Integrating multi-faceted approaches can provide complementary information on patterns of herb-layer diversity in European forest plant communities. [ABSTRACT FROM AUTHOR]

Flax (Linum usitatissimum L.) is one of the promising oil crops in the north of Kazakhstan. Over the last 10 years, the total area under this crop in the region has increased fourteen-fold, since flax is a very plastic crop for steppe and dry steppe conditions, and oil seeds are in high demand in the world market. Flaxseed oil, due to the content of polyunsaturated fatty acids, occupies one of the first positions among other edible vegetable oils. Depending on the environmental conditions, the oil content of the crop may vary from 36.4% to 52.0%, while, as noted by many researchers, the change in the oil content depends on the genotypic characteristics. Therefore, the study aims to analyze the influence of the genotype and climatic conditions of cultivation on the fat biosynthesis in flax seeds in the context of the dry steppe zone of Northern Kazakhstan on dark chestnut soils of the Akmola region. Field experiments were conducted in 2015-2017 with the study of nine oil flaxseed cultivars (of mid-season varieties) sown on May 20th at the seeding rate of 7 million seeds/ha based on the traditional technology of cultivation recommended for the region. The climatic parameters were taken into account according to the meteorological service data. The fat content was determined by the extraction method using a Soxhlet apparatus, in accordance with GOST (All-Union State Standard) 10857-64, and the moisture content was determined by means of the thermogravimetric method, according to the National Standard of the Republic of Kazakhstan 2.195-2010, for the recalculation of the oil content for absolutely dry matter. It was found that the formation of oil depends on the climatic parameters and on the sum of active temperatures during the ripening period, in particular. The evaluation of plasticity and stability of the cultivars (genotypes) showed that VNIIMK 620, Lirina, Karabalyksky 7 can be considered highly valuable cultivars and Severny, Biryuza, Kazar, Ilyich - valuable cultivars in terms of the oil content for the dry steppe zone. [ABSTRACT FROM AUTHOR]

A numerical simulation of a basin solar still under various climatic parameters was performed. The proposed system was modeled using the mass and energy balance equations of different parts of the solar still. The resulting system of nonlinear algebraic equations was solved numerically and the effect of various parameters, such as wind speed, air temperature and solar radiation on the amount of distilled water produced was described. The results showed that the ambient temperature and wind speed had no significant effect on the amount of distilled water produced, while the amount of solar radiation exerted a direct effect on the amount of distilled water produced and performance of the system. [ABSTRACT FROM AUTHOR]

Insect-proof screens constitute efficient physical means of protecting horticultural crops against insect pests and their use has become widespread. However, they may have a negative impact on plant growth and fruit quality by modifying climatic parameters of greenhouses. In case of tomato crops, they are used mainly against white flies and the tomato leaf miner Tuta absoluta (Meyrick). In Tunisia, tomato plastic tunnels are often netted following two modalities: i) complete netting of the greenhouse under the plastic screen (total netting); or ii) netting only doors and lateral aeration windows (partial netting). Weekly monitoring of T. absoluta in two tomato greenhouses with different netting setups using pheromone traps and sampling of leaves and fruits showed no differences in the levels of infestation by the pest with a maximum average values of 6.66 eggs/leaf, 4.16 larvae/leaf and 4.16 mines/leaf. The maximum infestation rate of leaves was 86.66% and that of fruits was 10.83%. No effects of the netting setup used on plant growth parameters were detected. However, the study of fruit quality parameters revealed significant decrease in sugar contents in tomato fruits when using total netting setup (4.26°Brix versus 3.68°Brix). Recommendations regarding the combined use of pheromones traps and insect-proof nets are given and possibilities to enhance the efficiency of nets as physical barrier against T. absoluta are explored. [ABSTRACT FROM AUTHOR]

The main objective of this investigation was to understand the desiccation behavior of treated oil sand fine tailings. A numerical model was developed to understand the interaction of material properties with the climatic parameters. The material properties included a depositional solids content of 60 %, an air entry value of 1000 kPa and a residual suction of 3,0000 kPa, a J-shaped shrinkage curve, a saturated hydraulic conductivity of 3 × 10 m/s, and a vapor conductivity of 5 × 10 m/s. Likewise, the climate data indicated the presence of three distinct seasons (winter, spring, and summer). Under the mean climate conditions, desiccation at the surface is negligible till the end of March (99 % saturation) but picks up during the remainder of the year to 70 % in May, 76 % in September, and 88 % in December. Furthermore, de-saturation occurs up to about 4 m beyond which the deposit is not affected by atmospheric parameters. The corresponding values of soil properties at the surface by the end of May and the end of September are as follows: soil suction 2500 and 1900 kPa, solids content 72 and 71 %, and settling potential 25 and 20 %. [ABSTRACT FROM AUTHOR]

Aim To describe the main vegetation types of the Korean zonal forests and explore their relationship with the main environmental and geographic gradients. Location Korean Peninsula. Methods A data set of 3847 relevés of zonal (semi)natural forest stands, together with environmental factors recorded in the field or derived from interpolated climatic data was collected. Using the hierarchical ISOPAM method, the relevés were classified into main forest types and their species composition, diversity and distribution were described. Their differentiation along main environmental gradients was analysed with classification and regression trees. Results Eleven vegetation types of forests were distinguished and assigned to five vegetation classes: Quercetea mongolicae (representing the core of the Korean temperate forests), Vaccinio-Piceetea (subalpine coniferous forest), Fagetea crenatae (rare beech-dominated forest included within a sub-montane and sub-oceanic type of oak-dominated forest), Querco mongolicae- Betuletea davuricae (sub-continental drought- and fire-tolerant forest, differentiated along elevational gradient) and Camellietea japonicae (oceanic evergreen forest). At a higher hierarchical level, these 11 vegetation types were grouped into three clusters, which most probably reflect different vegetation development in the Late Pleistocene and Holocene. Within the three major vegetation clusters, each forest type occupies a distinct environment. The forest types are especially well separated along elevational and temperature gradients. The distribution of individual forest types is joinly driven by total amount of incoming energy and thermal extremes, both affecting water supply to plant communities. Conclusions All distinguished vegetation types can be assigned to the recent syntaxonomic classification system. However, three main vegetation clusters do not correspond to traditionally distinguished syntaxonomic units. Nevertheless, the forest types within these clusters share common species with similar ecology and, especially, migration histories during the late glacial and post-glacial periods. Therefore, we interpret these clusters as biogeographic patterns reflecting vegetation history rather than the current environmental conditions. [ABSTRACT FROM AUTHOR]

The authors thank the writers of the rebuttal for their interest in the paper. This provides an opportunity to elaborate on the scope and results of the numerical simulation study presented in the paper. [ABSTRACT FROM AUTHOR]

Long-term effects of the different combinations of nutrient-management treatments were studied on crop yields of sorghum + cowpea in rotation with cotton + black gram. The effects of rainfall, soil temperature, and evaporation on the status of soil fertility and productivity of crops were also modeled and evaluated using a multivariate regression technique. The study was conducted on a permanent experimental site of rain-fed semi-arid Vertisol at the All-India Coordinated Research Project on Dryland Agriculture, Kovilpatti Centre, India, during 1995 to 2007 using 13 combinations of nutrient-management treatments. Application of 20 kg nitrogen (N) (urea) + 20 kg N [farmyard manure (FYM)] + 20 kg phosphorus (P) ha−1 gave the greatest mean grain yield (2146 kg ha−1) of sorghum and the fourth greatest mean yield (76 kg ha−1) of cowpea under sorghum + cowpea system. The same treatment maintained the greatest mean yield of cotton (546 kg ha−1) and black gram (236 kg ha−1) under a cotton + cowpea system. When soil fertility was monitored, this treatment maintained the greatest mean soil organic carbon (4.4 g kg−1), available soil P (10.9 kg ha−1), and available soil potassium (K) (411 kg ha−1), and the second greatest level of mean available soil N (135 kg ha−1) after the 13-year study. The treatments differed significantly from each other in influencing soil organic carbon (C); available soil N, P, and K; and yield of crops attained under sorghum + cowpea and cotton + black gram rotations. Soil temperature at different soil depths at 07:20 h and rainfall had a significant influence on the status of soil organic C. Based on the prediction models developed between long-term yield and soil fertility variables, 20 kg N (urea) + 20 kg N (FYM) + 20 kg P ha−1 could be prescribed for sorghum + cowpea, and 20 kg N (urea) + 20 kg N (FYM) could be prescribed for cotton + black gram. These combinations of treatments would provide a sustainable yield in the range of 1681 to 2146 kg ha−1 of sorghum, 74 to 76 kg ha−1 of cowpea, 486 to 546 kg ha−1 of cotton, and 180 to 236 kg ha−1 of black gram over the years. Beside assuring greater yields, these soil and nutrient management options would also help in maintaining maximum soil organic C of 3.8 to 4.4 g kg−1 soil, available N of 126 to 135 kg ha−1, available soil P of 8.9 to 10.9 kg ha−1, and available soil K of 392 to 411 kg ha−1 over the years. These prediction models for crop yields and fertility status can help us to understand the quantitative relationships between crop yields and nutrients status in soil. Because black gram is unsustainable, as an alternative, sorghum + cowpea could be rotated with cotton for attaining maximum productivity, assuring sustainability, and maintaining soil fertility on rain-fed semi-arid Vertisol soils. [ABSTRACT FROM AUTHOR]

The variations of tropospheric ozone levels was assessed for the first time in the Boukornine National Park (N.E. Tunisia) by detection of leaf injury development on Nicotiana tabacum “Bel-W3” exposed to environmental conditions during summer 2004. Two cultivars of tobacco ( Nicotiana tabacum), Bel-W3 (sensitive) and Bel-B (resistant to ozone), were used for this biomonitoring study. These cultivars were dispersed in 24 different biostations, according to a square grid mesh, every 2 weeks. Four successive cultures were utilized to follow the ozone levels inside the park during the summer exposure period. Levels of ozone may vary in time and space depending on the local environmental and meteorological conditions. The results showed a positive correlation between ozone concentration and foliar injury index (FII; r = 0.958; p < 0.05). A significant positive correlation was observed between the FII of Bel-W3 tobacco plant and AOT40 (accumulated over the threshold of 40 ppb). The altitude appeared to be the most important variable explaining the variation of ozone pollution with the highest correlation coefficient ( r = 0.964; p < 0.0001). The altitude was followed by topography for the prediction of ozone concentration levels. Maximal temperature was also an important factor in addition to the others in determining the FII and was negatively correlated with the FII ( r = −0.979; p < 0.05). Average ambient ozone levels were positively linked to plant leaf damage. The ozone profile characterizing the study area was primarily influenced by wind direction and speed in relation to intercontinental transport, in addition to the local influence of motor vehicles traffic flow in the Tunis region. [ABSTRACT FROM AUTHOR]

Maize samples collected from storage bins and feed mills in Northern Italy between 1995 and 1999 were surveyed for the occurrence of aflatoxin B 1 (AFB 1 ), zearalenone (ZEA), deoxynivalenol (DON) and fumonisin (FB1); further, ergosterol was analysed as a fungal growth marker. The incidence and mean content of AFB1 were generally low; nevertheless, a remarkable contamination was found in two samples (109 and 158 μg kg -1 ), while five others exceeded 20 μg kg -1 . DON and ZEA mean levels were significantly higher in 1996 (2716 and 453 μg kg -1 ) with respect to the other years, when mean contents ranged from 7 to 30% and from 3 to 17%, respectively, expressed in per cent of 1996 contents. FB1 was present in all samples and was by far the most remarkable mycotoxin in Northern Italian maize, with the exception of samples from 1996. The average level was 3064 μg kg-1 , 69.6% of samples resulted over 1000 μg kg-1 and 16.9% over 5000 μg kg-1 . Significant correlations were found between ergosterol and the major mycotoxin(s) in each year (FB1 in 1995 and 1997-99; ZEA + DON in 1996). Consequently, ergosterol seems to be a good index of the toxicological quality of maize. Climatic conditions influenced the growth of different fungal species. In 1996, the first 20 days of October were extremely rainy; these weather conditions delayed the harvest until the first week of November and favoured the growth of DON and ZEA producing fungi and the synthesis of mycotoxins. On the contrary, the temperate and dry climate of the other years supported the growth of FB1 -producing fungi. [ABSTRACT FROM AUTHOR]

Reference evapotranspiration (ET0) is important to the global energy balance and to hydrological cycling. However, the extent to which ET0 changes, the main driving factors, and especially the implications of its shift for drought in Southwest China are not clear. In this study, trends in Penman–Monteith ET0 and other climatic parameters at 79 stations in Southwest China from 1960 to 2018 were investigated by using the Mann–Kendall test. Furthermore, partial correlation analysis and multiple linear regression were used to determine the dominant climate driving factors in changes in ET0. The relative contribution of precipitation and ET0 to drought duration was also quantified based on spatial multiple linear regression. Results revealed that annual ET0 decreased significantly (p < 0.01) at a rate of 14.1 mm per decade from 1960 to 2000, and this decrease disappeared around 2000. For the entire study period, the sunshine duration (Tsun) was the most closely correlated with and played a dominant role in the variations in ET0 at both annual and seasonal (summer and autumn) timescales, whereas the relative humidity was the most dominant factor in the spring and winter. Trends in the Standardized Precipitation Evapotranspiration Index revealed that drought has become more serious in Southwest China, and ET0 has made a greater contribution to the duration of drought than precipitation. Our findings highlight that more attention should be paid to the impacts of ET0 changes on drought in Southwest China. Furthermore, these results can provide a reference for the allocation of water resources and the implementation of countermeasures to climate change. [ABSTRACT FROM AUTHOR]