climatic parameters
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2022 ◽  
Vol 81 (1) ◽  
Author(s):  
Dávid Schmidt ◽  
Attila Mesterházy ◽  
János Csiky

Lepidium oblongum, of American origin is a new member of the European adventive flora, only detected in Romania so far. The first Hungarian stand was discovered in 2018, and others in 2020. Based on our studies, we detail its morphological characteristics in comparison with other Lepidium species. We present a new drawing and a table to help identify the species. Lepidium oblongum is easily identifiable by its divided (lobed or lobed-dentated) upper stem leaves. By analyzing selected climatic parameters we show that the new European habitats are found in the drier and cooler summer subtype of the humid continental climate belt. In Hungary, it spreads directly along the railways. The establishment of individual populations can be influenced by the location of cargo unloading and the movement of railway workers. Lepidium oblongum occupies gravelly, sun-exposed habitats along Hungarian railway tracks such as loading platforms, guardhouses and goods stations. Based on its high stress and climatic tolerance and initial spread-rate, it is consider to be a naturalized member of the European adventive flora, that could be potentially invasive along the European railways


2022 ◽  
Vol 962 (1) ◽  
pp. 012025
Author(s):  
O F Malykh ◽  
V P Makarov ◽  
T V Zhelibo ◽  
E A Banshchikova

Abstract In light coniferous forests of the Baikal-Dzhugdzhur type fires are considered as factors and processes inseparable from the forest landscapes and their dynamics. The study period of 1998–2015 is highlighted as extremely arid. In 2008, 2013–2014, 2018 conducted ground studies of the state of vegetation after fires in the area of Vitim Plateau. The conditions of arid period with high frequency, duration and intensity of fires were the main factors in the dynamics of transformation of the structure of mountain-taiga larch forests. Analysis of cruising materials and expedition research showed that from 1996 to 2015 the area of larch forests with canopy density of 5–7% decreased by 45–50%. The area of burned forests and thin forests increased by 45-48%, and the area of shrubs – by 17.0%. The main part of forests is disturbed at the foot of the mountains and in intermountain depressions, at altitudes of 942 -1100 m. Strong desiccation of the ground cover and consistent ground fires with complete loss of trees and undergrowth activated natural processes of bush formation and prairiefication. The duration and degree of fluctuations in climatic parameters determine the nature of the impact of fires on Baikal-Dzhugdzhur larch forests and the degree of their transformation.


2022 ◽  
Vol 10 (1) ◽  
pp. 0-0

India is an agricultural region and the economy of the country depends upon agriculture. Change in climatic parameters (like rainfall, soil, etc) directly affect the growth of crops. This parameter has an unswerving effect on the quantity of food production. Information extraction from the agricultural domain through rainfall prediction has been one of the most challenging issues around the world in recent years because of climatic changes. To evaluate the feasibility of rain by employing some data analytics and machine learning techniques are developed. This paper proposes an enhanced deep learning-based approach known as Deep Regression Network (DRN). The proposed DRN is a 6-layer deep neural network. The proposed algorithm trains and tests on the agricultural corpus, collected from Dehradun (India) region. The experimental outcomes state that the proposed DRN method attained a prediction accuracy approx 86.56%. The comparative analysis shows that the proposed method outperformed existing methods like Ensemble Neural Network, Naïve Bayes, KNN, and Weighted Self-Organizing Map.


Author(s):  
Mostafa Dastorani ◽  
Vahid Safarianzengir ◽  
Bromand Salahi

Introduction: The present study investigated one of these types of disease (skin cancer) and its relationship with climatic parameters. The aim of this study was to investigate the relationship between climate change and skin cancer in Ardabil province. Materials and Methods: This descriptive correlational study was conducted to investigate the effect of six climatic parameters (frost, sunny hours, minimum mean humidity, maximum absolute temperature, minimum absolute temperature, and mean temperature) on skin cancer in Ardabil province in a 3-year statistical period (2012-2014). The data were analyzed using the Spearman correlation relationship in SPSS version 24 software, also Minitab version 16 software was used for linear interpolation. Results: According to the findings, the highest correlation (more than 95%) of skin cancer in three cities of Parsabad, Khalkhal, and Ardabil with the climatic parameter was related to minimum absolute temperature. However, in Khalkhal station in three years of study, sunny hours had the highest correlation and the lowest correlation was related to glacial climate parameter in all four cities. It can be said that the factors of sunny hours and maximum temperature have an effect on the incidence of skin cancer, and the minimum absolute temperature increases the exacerbation of this type of disease. Conclusion: According to the results of statistical correlation and the effects of climatic parameters on skin cancer, it can be concluded that climate parameters are one of the effective factors in skin cancer.


Author(s):  
N. I. Riznychuk ◽  
M. M. Mylenka ◽  
O. V. Babak

Grouping of research sites according to the set of analyzed edapho-climatic parameters by the method of cluster analysis showed that the dominant factor in the formation of abiotic conditions is the type of habitat. Therefore, characterized the population and ecological characteristics of species of the genus Polygonatum Mill. in the Precarpathians by analyzing the key edapho-climatic factors of the studied habitats, namely the humus content, acidity, moisture content, the sum of active temperatures, light levels and N, P, K.


2021 ◽  
Vol 4 ◽  
Author(s):  
Jalil Helali ◽  
Hossein Momenzadeh ◽  
Vahideh Saeidi ◽  
Christian Brischke ◽  
Ghanbar Ebrahimi ◽  
...  

The intensive use of wood resources is a challenging subject around the world due to urbanization, population growth, and the biodegradability of wooden materials. The study of the climatic conditions and their effects on biotic wood degradation can provide a track of trends of wood decay and decomposition at regional and global scales to predict the upcoming responses. Thus, it yields an overview for decision-makers and managers to create a precise guideline for the protection of wooden structures and prolonged service life of wooden products. This study aimed at investigating the decay hazard in Iran, its decadal changes, and how it is affected by different phases of the El Niño Southern Oscillation (ENSO). Therefore, the risk for fungal decay of wood was estimated based on the Scheffer Climate Index (SCI) at 100 meteorological stations located in Iran, for the period 1987–2019 (separately for first, second, and third decade as decadal analysis). Subsequently, SCI value trends were analyzed using the Mann–Kendall and Sen’s slope method. Finally, the relationship between SCI and climatic parameters (temperature and precipitation) was explored. Generally, the SCI fluctuated between 2 and 75 across the region. The decay risk was ranked as low in most parts, but moderate in the northern part of the country along the Caspian Sea coastlines. Decadal analysis demonstrated that the highest mean SCI values took more place in the third decade (58% of stations) and the lowest mean SCI values in the second decade (71% of stations). Furthermore, the highest and the lowest SCI values occurred at 70 and 66% of stations in El Niño and Neutral phase, respectively. Trend analysis of SCI values showed that large parts of several provinces (i.e., Markazi, Tehran, Alborz, Qazvin, Zanjan, Ardebil, East Azarbayjan, West Azarbayjan, Kurdestan, Kermanshah, and Ilam) exhibited a significantly increasing decay hazard with a mean SCI of 2.9 during the period of 33 years. An analysis of causative factors (climatic parameters) for these changes revealed that all the meteorological stations experienced a significant increase in temperature while the number of days with more than 0.25 mm precipitation increased at some stations but decreased at others. However, in summary, the SCI increased over time. Hence, in this study, the effect of precipitation on SCI was confirmed to be greater than the temperature. Analysis of the results shows that the correlation between the SCI and ENSO was positive in most of the stations. Moreover, the results of spectral coherent analysis of SCI and ENSO in different climates of Iran showed that the maximum values of SCI do not correspond to the maximum values of ENSO and are associated with lag time. Therefore, the extreme values of the SCI values cannot be interpreted solely on the basis of the ENSO.


2021 ◽  
Vol 22 (4) ◽  
pp. 494-500
Author(s):  
S.J. KADBHANE ◽  
V.L.MANEKAR

Prediction of the crop yield is need of time according to the change in climate conditions. In the present study, the Agro-Climatic Grape Yield (ACGY) model has been developed with monthly climatic parameters using multi-regression analysis approach. The developed model was statistically tested for its predictive ability. The discrepancy ratio, the standard deviation of discrepancy ratio, mean percentage error and standard deviation of mean percentage error for the model was obtained as 1.03, 0.19, 0.03% and 0.19, respectively. Sensitivity analysis was carried out for the developed ACGY model using the parametric sensitivity method. In order to know the future grape yield using ACGY model, climate scenarios were generated under Canadian Earth System Model (CanESM2) for three emissions representative concentration pathways as RCP2.6, RCP4.5, and RCP8.5. According to the analysis using ACGY model, increasing yield was observed in grape up to year 2050 as compared to current yield.


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