scholarly journals Principal component regression analysis demonstrates the collinearity-free effect of sub estimated climatic variables on tree growth in the central Amazon

2021 ◽  
Vol 69 (2) ◽  
Author(s):  
Ricardo Antonio Marenco ◽  
Saul Alfredo Antezana-Vera
Keyword(s):  
Relative Humidity ◽  
Tree Growth ◽  
Seasonal Pattern ◽  
Climatic Variability ◽  
Principal Component Regression ◽  
Principal Component ◽  
Climatic Variables ◽  
Maximum Temperature ◽  
Central Amazon ◽  
Minimum Relative Humidity

Introduction: Climatic variables show a seasonal pattern in the central Amazon, but the intra-annual variability effect on tree growth is still unclear. For variables such as relative humidity (RH) and air vapor pressure deficit (VPD), whose individual effects on tree growth can be underestimated, we hypothesize that such influences can be detected by removing the effect of collinearity between regressors. Objective: This study aimed to determine the collinearity-free effect of climatic variability on tree growth in the central Amazon. Methods: Monthly radial growth was measured in 325 trees from January 2013 to December 2017. Irradiance, air temperature, rainfall, RH, and VPD data were also recorded. Principal Component Regression was used to assess the effect of micrometeorological variability on tree growth over time. For comparison, standard Multiple Linear Regression (MLR) was also used for data analysis. Results: Tree growth increased with increasing rainfall and relative humidity, but it decreased with rising maximum VPD, irradiance, and maximum temperature. Therefore, trees grew more slowly during the dry season, when irradiance, temperature and VPD were higher. Micrometeorological variability did not affect tree growth when MLR was applied. These findings indicate that ignoring the correlation between climatic variables can lead to imprecise results. Conclusions: A novelty of this study is to demonstrate the orthogonal effect of maximum VPD and minimum relative humidity on tree growth.

scholarly journals Modelling Trends of Climatic Variability and Malaria in Ghana Using Vector Autoregression

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Sylvia Ankamah ◽  
Kaku S. Nokoe ◽  
Wahab A. Iddrisu
Keyword(s):  
Relative Humidity ◽  
Vector Autoregression ◽  
Climatic Variability ◽  
Age Groups ◽  
Sub Saharan Africa ◽  
Climatic Variables ◽  
Health Concern ◽  
Maximum Temperature ◽  
Climatic Data ◽  
The Impact

Malaria is considered endemic in over hundred countries across the globe. Many cases of malaria and deaths due to malaria occur in Sub-Saharan Africa. The disease is of great public health concern since it affects people of all age groups more especially pregnant women and children because of their vulnerability. This study sought to use vector autoregression (VAR) models to model the impact of climatic variability on malaria. Monthly climatic data (rainfall, maximum temperature, and relative humidity) from 2010 to 2015 were obtained from the Ghana Meteorological Agency while data on malaria for the same period were obtained from the Ghana Health Service. Results of the Granger and instantaneous causality tests led to a conclusion that malaria is influenced by all three climatic variables. The impulse response analyses indicated that the highest positive effect of maximum temperature, relative humidity, and rainfall on malaria is observed in the months of September, March, and October, respectively. The decomposition of forecast variance indicates varying degree of malaria dependence on the climatic variables, with as high as 12.65% of the variability in the trend of malaria which has been explained by past innovations in maximum temperature alone. This is quite significant and therefore, policy-makers should not ignore temperature when formulating policies to address malaria.

scholarly journals SEASONAL AND INTERANNUAL PATTERN OF METEOROLOGICAL VARIABLES IN CUIABÁ, MATO GROSSO STATE, BRAZIL

2015 ◽  
Vol 33 (3) ◽  
pp. 477 ◽  
Author(s):  
Nadja Gomes Machado ◽  
Marcelo Sacardi Biudes ◽  
Carlos Alexandre Santos Querino ◽  
Victor Hugo De Morais Danelichen ◽  
Maísa Caldas Souza Velasque
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Meteorological Data ◽  
Seasonal Pattern ◽  
Global Radiation ◽  
Meteorological Variables ◽  
Maximum Temperature ◽  
Wet Season ◽  
Agricultural Producers ◽  
Mato Grosso

ABSTRACT. Cuiab´a is located on the border of the Pantanal and Cerrado, in Mato Grosso State, which is recognized as one of the biggest agricultural producers of Brazil. The use of natural resources in a sustainable manner requires knowledge of the regional meteorological variables. Thus, the objective of this study was to characterize the seasonal and interannual pattern of meteorological variables in Cuiab´a. The meteorological data from 1961 to 2011 were provided by the Instituto Nacional de Meteorologia (INMET – National Institute of Meteorology). The results have shown interannual and seasonal variations of precipitation, solar radiation, air temperature and relative humidity, and wind speed and direction, establishing two main distinct seasons (rainy and dry). On average, 89% of the rainfall occurred in the wet season. The annual average values of daily global radiation, mean, minimum and maximum temperature and relative humidity were 15.6 MJ m–2 y–1, 27.9◦C, 23.0◦C, 30.0◦C and 71.6%, respectively. Themaximum temperature and the wind speed had no seasonal pattern. The wind speed average decreased in the NWdirectionand increased in the S direction.Keywords: meteorological variables, climatology, ENSO. RESUMO. Cuiabá está localizado na fronteira do Pantanal com o Cerrado, no Mato Grosso, que é reconhecido como um dos maiores produtores agrícolas do Brasil. A utilização dos recursos naturais de forma sustentável requer o conhecimento das variáveis meteorológicas em escala regional. Assim, o objetivo deste estudo foi caracterizar o padrão sazonal e interanual das variáveis meteorológicas em Cuiabá. Os dados meteorológicos de 1961 a 2011 foram fornecidos pelo Instituto Nacional de Meteorologia (INMET). Os resultados mostraram variações interanuais e sazonais de precipitação, radiação solar, temperatura e umidade relativa do ar e velocidade e direção do vento, estabelecendo duas principais estações distintas (chuvosa e seca). Em média, 89% da precipitação ocorreu na estação chuvosa. Os valores médios anuais de radiação diária global, temperatura do ar média, mínima e máxima e umidade relativa do ar foram 15,6 MJ m–2 y–1, 27,9◦C, 23,0◦C, 30,0◦C e 71,6%, respectivamente. A temperatura máxima e a velocidade do vento não tiveram padrão sazonal. A velocidade média do vento diminuiu na direção NW e aumentou na direção S.Palavras-chave: variáveis meteorológicas, climatologia, ENOS.

scholarly journals ASSESSMENT OF LONG TERM CLIMATIC VARIABILITY OF UTTARAKHAND

2018 ◽  
Vol 1 (4) ◽  
Author(s):  
Sujeet Kumar ◽  
Shakti Suryavanshi
Keyword(s):  
Minimum Temperature ◽  
Monsoon Season ◽  
Climatic Variability ◽  
Kendall Test ◽  
Summer Season ◽  
Climatic Variables ◽  
Maximum Temperature ◽  
Mountain Areas ◽  
Mk Test ◽  
Increasing Trend

A trend analysis was performed for historic (1901-2002) climatic variables (Rainfall, Maximum Temperature and Minimum Temperature) of Uttarakhand State located in Northern India. In the serially independent climatic variables, Mann-Kendall test (MK test) was applied to the original sample data. However, in the serially correlated series, prewhitening is utilized before employing the MK test. The results of this study indicated a declining trend of rainfall in monsoon season for seven out of thirteen districts of Uttarakhand state. However, an increasing trend was observed in Haridwar and Udhamsingh Nagar districts for summer season rainfall. For maximum and minimum temperature, a few districts exhibited a declining trend in monsoon season whereas many districts exhibited an increasing trend in winter and summer season. Mountain dominated areas (as Uttarakhand state) are specific ecosystems, distinguished by their diversity, sensitivity and intricacy. Thus the variability of rainfall and temperature has a severe and rapid impact on mountainous ecosystems. Nevertheless, mountains have significant impacts on hydrology, which may further threaten populations living in the mountain areas as well as in adjacent, lowland regions.

scholarly journals Effects of Climatic Variability on Cassava Production in Nigeria

2020 ◽  
Vol 57 (3) ◽  
Author(s):  
Fatai Abiola Sowunmi
Keyword(s):  
Relative Humidity ◽  
Crop Production ◽  
Climatic Variability ◽  
Climatic Variables ◽  
Annual Rainfall ◽  
Mean Annual Temperature ◽  
Ecological Zones ◽  
Cassava Production ◽  
Rainforest Zone ◽  
Agro Ecological Zones

Climate change has brought about irregularity in pattern and intensity of climatic variables such as rainfall and temperature that are important in crop production; making planning in agriculture difficult. The importance of cassava in the diet of Nigerian and its industrial use necessitate the need to examine the effects of climatic variability on cassava production. Secondary data obtained from Nigerian Meteorological Agency (NIMET) were used for the study. Analysis of Variance and Error Correction model were utilized.  The study showed that the rainforest zone had the highest averages of annual rainfall (1709mm) and relative humidity (82.1%) while the Sahel savannah had the highest mean annual temperature (35.3oC). The variability in annual rainfall and relative humidity was low in the rainforest zone. The study showed that the rainforest zone had the least dispersion of average annual relative humidity (2.06%) while the guinea savannah had highest dispersion (4.68%). The average cassava output from the agro-ecological zones was 49,118,871MT per year. Rainforest and guinea savannah accounted for 56.3% and 41.9% of total cassava output respectively. There were significant variations in the climatic variables (rainfall and temperature) among the agro-ecological zones but not significant among the years (p>0.05).  The annual rainfall and solar radiation were the factors that influenced cassava output in all the agro-ecological zones. The need for affordable irrigation by cassava farmers and the adoption of Climate-Smart Agriculture are recommended to boost cassava production in Sudan savannah and Sahel savannah.

scholarly journals Determination of Factors Affecting Dengue Occurrence in Representative Areas of China: A Principal Component Regression Analysis

2021 ◽  
Vol 8 ◽  
Author(s):  
Xiaobo Liu ◽  
Keke Liu ◽  
Yujuan Yue ◽  
Haixia Wu ◽  
Shu Yang ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Linear Regression Analysis ◽  
Principal Component Regression ◽  
Principal Component ◽  
Maximum Temperature ◽  
Factors Affecting ◽  
Positive Correlation ◽  
Guangzhou City ◽  
Monthly Average

Background: Determination of the key factors affecting dengue occurrence is of significant importance for the successful response to its outbreak. Yunnan and Guangdong Provinces in China are hotspots of dengue outbreak during recent years. However, few studies focused on the drive of multi-dimensional factors on dengue occurrence failing to consider the possible multicollinearity of the studied factors, which may bias the results.Methods: In this study, multiple linear regression analysis was utilized to explore the effect of multicollinearity among dengue occurrences and related natural and social factors. A principal component regression (PCR) analysis was utilized to determine the key dengue-driven factors in Guangzhou city of Guangdong Province and Xishuangbanna prefecture of Yunnan Province, respectively.Results: The effect of multicollinearity existed in both Guangzhou city and Xishuangbanna prefecture, respectively. PCR model revealed that the top three contributing factors to dengue occurrence in Guangzhou were Breteau Index (BI) (positive correlation), the number of imported dengue cases lagged by 1 month (positive correlation), and monthly average of maximum temperature lagged by 1 month (negative correlation). In contrast, the top three factors contributing to dengue occurrence in Xishuangbanna included monthly average of minimum temperature lagged by 1 month (positive correlation), monthly average of maximum temperature (positive correlation), monthly average of relative humidity (positive correlation), respectively.Conclusion: Meteorological factors presented stronger impacts on dengue occurrence in Xishuangbanna, Yunnan, while BI and the number of imported cases lagged by 1 month played important roles on dengue transmission in Guangzhou, Guangdong. Our findings could help to facilitate the formulation of tailored dengue response mechanism in representative areas of China in the future.

scholarly journals Population dynamics of aphid and coexisting predators in tomato agroecosystem

2021 ◽  
Vol 23 (2) ◽  
pp. 200-206
Author(s):  
SHIVANI KHOKHAR ◽  
KRISHNA ROLANIA
Keyword(s):  
Population Dynamics ◽  
Relative Humidity ◽  
Aphis Gossypii ◽  
Management Strategies ◽  
Principal Component ◽  
Significant Negative Correlation ◽  
Aphid Species ◽  
Maximum Temperature ◽  
Positive Density ◽  
Aphid Infestation

Aphids generally attack vegetative plant parts, preferably leaves, and devitalize the plant by sucking the cell sap. Thorough knowledge of pest-predator ecology and their interaction is requisite to initiate timely pest management strategies. Therefore, we aimed to study the population dynamics of aphids and their predators on tomato in Hisar, Haryana during Rabi, 2016-17 and 2017-18. We observed two dominant aphid species viz., Aphis gossypii and Myzus persicae and three aphidophagous predator groups viz., coccinellids, spiders and syrphid fly maggots in the tomato agroecosystem. Aphid infestation started during the 9th standard meteorological week (SMW) and attained a peak during the 12th SMW (22.65 aphids per three leaves per plant). Aphid population exhibited highly significant negative correlation with minimum temperature (r= -0.917**), maximum temperature (r= -0.895**) and wind speed (r= -0.809**). However, it was positively correlated with morning relative humidity (r= 0.933**) and evening relative humidity (r= 0.856**). We used Principal component analysis (PCA) to reduce the dimensions of data and variables were transformed into principal components (PC) to explain the nature and extent of the relationships among different variables. PC1 and PC2 capture 57.6 and 20.3% of the variability in the data, respectively. Aphid predators exhibited a significant positive correlation with the prey population suggesting a positive density-dependent response.

scholarly journals Lagged meteorological impacts on COVID-19 incidence among high-risk counties in the United States—a spatiotemporal analysis

2021 ◽  
Author(s):  
Lung-Chang Chien ◽  
L.-W. Antony Chen ◽  
Ro-Ting Lin
Keyword(s):  
United States ◽  
High Risk ◽  
Relative Humidity ◽  
Weather Forecasting ◽  
Spline Interpolation ◽  
The United States ◽  
Meteorological Factor ◽  
Maximum Temperature ◽  
Minimum Relative Humidity ◽  
Spatial Function

Abstract Background The associations between meteorological factors and coronavirus disease 2019 (COVID-19) have been discussed globally; however, because of short study periods, the lack of considering lagged effects, and different study areas, results from the literature were diverse and even contradictory. Objective The primary purpose of this study is to conduct more reliable research to evaluate the lagged meteorological impacts on COVID-19 incidence by considering a relatively long study period and diversified high-risk areas in the United States. Methods This study adopted the distributed lagged nonlinear model with a spatial function to analyze COVID-19 incidence predicted by multiple meteorological measures from March to October of 2020 across 203 high-risk counties in the United States. The estimated spatial function was further smoothed within the entire continental United States by the biharmonic spline interpolation. Results Our findings suggest that the maximum temperature, minimum relative humidity, and precipitation were the best meteorological predictors. Most significantly positive associations were found from 3 to 11 lagged days in lower levels of each selected meteorological factor. In particular, a significantly positive association appeared in minimum relative humidity higher than 88.36% at 5-day lag. The spatial analysis also shows excessive risks in the north-central United States. Significance The research findings can contribute to the implementation of early warning surveillance of COVID-19 by using weather forecasting for up to two weeks in high-risk counties.

Seasonal abundance of Campoletis chlorideae Uchida (Hymenoptera:Ichneumonidae), A larval parasitoid of Helicoverpa armigera(Hubner) hardwick in chickpea

2016 ◽  
Vol 39 (4) ◽  
Author(s):  
A. Kuzhandhaivel Pillai ◽  
S. Selvaraj ◽  
Meena Agnihotri
Keyword(s):  
Climate Change ◽  
Relative Humidity ◽  
Significant Negative Correlation ◽  
Seasonal Abundance ◽  
Maximum Temperature ◽  
Weather Factors ◽  
Campoletis Chlorideae ◽  
Minimum Relative Humidity ◽  
Larval Parasitoid ◽  
Survival And Development

Climate change is likely to affect the insect host and the activity and abundance of biological control agents. Therefore, the present studies were conducted to understand the seasonal abundance of larval parasitoid, Campoletis chlorideae on chickpea at Pantnagar during the cropping season 2010-11 and 2011-12 revealed that the larval parasitoid exhibited its marked first appearance in 3rd standard meteorological week (SMW) and attained peak population in 7th (85.80%) and 8th (87.65%) SMW, respectively. Statistical analysis between the weather parameters and the population of the larval parasitoid showed a significant negative correlation with maximum temperature (r= - 0.698* and r= - 0.705*) and minimum temperature (r= - 0.706* and r= - 0.790*) whereas significant positive correlation with maximum relative humidity (r= 0.800** and r = 0.824**) and minimum relative humidity (r= 0.636* and r= 0.254) during 2010-11 and 2011-12, respectively. The results indicated that changes in weather factors as a result of climate change would have considerable influence on survival and development of C.chlorideae.

scholarly journals The Effects of Ecological Factors on the Main Medicinal Components of Dendrobium officinale under Different Cultivation Modes

Forests ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 94 ◽  
Author(s):  
Yingdan Yuan ◽  
Xinggang Tang ◽  
Zhaohui Jia ◽  
Chong Li ◽  
Jieyi Ma ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Sunshine Duration ◽  
Ecological Factors ◽  
Principal Component ◽  
Dendrobium Officinale ◽  
Maximum Temperature ◽  
Available Phosphorus ◽  
Quality Factors ◽  
Soil Available Phosphorus ◽  
Total Alkaloids

Dendrobium officinale is an important traditional Chinese medicinal plant and crop, which contains many kinds of medicinal components. The quality of medicinal plants is closely related to the ecological factors in a growing environment. The main components of D. officinale determined in this study were polysaccharides, total alkaloids and total flavonoids. In addition, this study dealt with the correlation of these components to 16 ecological factors under three different cultivation modes (Greenhouse, Bionic, Wild; Lu’an, Anhui Province, China). The relationship between ecological factors and quality factors was analyzed step by step using correlation analysis, principal component analysis and stepwise multiple linear regression. Eight ecological factors: maximum relative humidity, minimum relative humidity, maximum temperature, sunshine duration, soil pH, soil total nitrogen, soil total phosphorus and soil available phosphorus were considered as key factors that influenced the main medicinal qualities of cultivated D. officinale. This study provides an insight for exploring the complex relationship between ecological factors and D. officinale medicinal value in artificial cultivation.

scholarly journals Trend and Sensitivity Analysis of Reference Evapotranspiration in the Senegal River Basin Using NASA Meteorological Data

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1957
Author(s):  
Papa Malick Ndiaye ◽  
Ansoumana Bodian ◽  
Lamine Diop ◽  
Abdoulaye Deme ◽  
Alain Dezetter ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Wind Speed ◽  
Relative Humidity ◽  
River Basin ◽  
Reference Evapotranspiration ◽  
Climatic Variables ◽  
Maximum Temperature ◽  
Senegal River ◽  
Senegal River Basin ◽  
Basin Area

Understanding evapotranspiration and its long-term trends is essential for water cycle studies, modeling and for water uses. Spatial and temporal analysis of evapotranspiration is therefore important for the management of water resources, particularly in the context of climate change. The objective of this study is to analyze the trend of reference evapotranspiration (ET0) as well as its sensitivity to climatic variables in the Senegal River basin. Mann-Kendall’s test and Sen’s slope were used to detect trends and amplitude changes in ET0 and climatic variables that most influence ET0. Results show a significant increase in annual ET0 for 32% of the watershed area over the 1984–2017 period. A significant decrease in annual ET0 is observed for less than 1% of the basin area, mainly in the Sahelian zone. On a seasonal scale, ET0 increases significantly for 32% of the basin area during the dry season and decreases significantly for 4% of the basin during the rainy season. Annual maximum, minimum temperatures and relative humidity increase significantly for 68%, 81% and 37% of the basin, respectively. However, a significant decrease in wind speed is noted in the Sahelian part of the basin. The wind speed decrease and relative humidity increase lead to the decrease in ET0 and highlight a “paradox of evaporation” in the Sahelian part of the Senegal River basin. Sensitivity analysis reveals that, in the Senegal River basin, ET0 is more sensitive to relative humidity, maximum temperature and solar radiation.

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