Climate Influence in Dendrochronological Series of Araucaria angustifolia from Campos do Jordão, Brazil

A dendrochronological series of Araucaria angustifolia was analyzed for a better understanding of the climatic factors that operate in Campos do Jordão city, São Paulo state, Brazil. The dendroclimatic analysis was carried out using 45 samples from 16 Araucaria angustifolia trees to reconstruct the precipitation and the temperature over the 1803–2012 yearly interval. To this end, Pearson’s correlation was calculated between mean chronology and the climatic time series using a monthly temporal resolution to calibrate our models. We obtained correlations as high as r=0.22(α=0.1) for precipitation (February), and r=0.21(α=0.1) for temperature (March), both corresponding to the end of the summer season. Our results show evidence of temporal instabilities because the correlations for the halves of 1963–2012 were very different, as well as for the full period. To overcome this problem, the dendrochronological series and the climatic data were investigated using the wavelet techniques searching for time-dependent cause–effect relationships. From these analyses, we find a strong influence of the region’s precipitation and temperature on the growth of tree ring widths.

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Assessing the Sensitivity of Main Crop Yields to Climate Change Impacts in China

Atmosphere ◽

10.3390/atmos12020172 ◽

2021 ◽

Vol 12 (2) ◽

pp. 172

Author(s):

Yuan Xu ◽

Jieming Chou ◽

Fan Yang ◽

Mingyang Sun ◽

Weixing Zhao ◽

...

Keyword(s):

Climate Change ◽

Crop Yield ◽

Food Production ◽

Crop Yields ◽

Climatic Factors ◽

Climatic Data ◽

The South ◽

The North ◽

Output Elasticity ◽

The Impact

Quantitatively assessing the spatial divergence of the sensitivity of crop yield to climate change is of great significance for reducing the climate change risk to food production. We use socio-economic and climatic data from 1981 to 2015 to examine how climate variability led to variation in yield, as simulated by an economy–climate model (C-D-C). The sensitivity of crop yield to the impact of climate change refers to the change in yield caused by changing climatic factors under the condition of constant non-climatic factors. An ‘output elasticity of comprehensive climate factor (CCF)’ approach determines the sensitivity, using the yields per hectare for grain, rice, wheat and maize in China’s main grain-producing areas as a case study. The results show that the CCF has a negative trend at a rate of −0.84/(10a) in the North region, while a positive trend of 0.79/(10a) is observed for the South region. Climate change promotes the ensemble increase in yields, and the contribution of agricultural labor force and total mechanical power to yields are greater, indicating that the yield in major grain-producing areas mainly depends on labor resources and the level of mechanization. However, the sensitivities to climate change of different crop yields to climate change present obvious regional differences: the sensitivity to climate change of the yield per hectare for maize in the North region was stronger than that in the South region. Therefore, the increase in the yield per hectare for maize in the North region due to the positive impacts of climate change was greater than that in the South region. In contrast, the sensitivity to climate change of the yield per hectare for rice in the South region was stronger than that in the North region. Furthermore, the sensitivity to climate change of maize per hectare yield was stronger than that of rice and wheat in the North region, and that of rice was the highest of the three crop yields in the South region. Finally, the economy–climate sensitivity zones of different crops were determined by the output elasticity of the CCF to help adapt to climate change and prevent food production risks.

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Anopheles species composition and some climatic factors that influence their survival and population abundance in Anambra East LGA, Anambra State, Nigeria

Nigerian Journal of Parasitology ◽

10.4314/njpar.v41i2.17 ◽

2020 ◽

Vol 41 (2) ◽

Author(s):

C.M Egbuche ◽

A.E Onyido ◽

P.U Umeanaeto ◽

E.N Nwankwo ◽

I.F Omah ◽

...

Keyword(s):

Relative Humidity ◽

Species Composition ◽

Climatic Factors ◽

Seasonal Abundance ◽

Human Landing Catch ◽

Morphological Identification ◽

Climatic Data ◽

Anopheles Species ◽

Anambra State ◽

Anopheles Mosquitoes

Malaria parasites are transmitted in nature through the bites of female Anopheles mosquitoes. However, the vector distribution varies in time and space. This study aimed to determine the species composition, abundance and climatic factors influencing Anopheles mosquitoes in Anambra East Local Government Area of Anambra State, Nigeria from October 2016 to September 2017. Adult Anopheles mosquitoes were collected from indoor and outdoor locations using Pyrethrum Knockdown Collection (PKC) and Human Landing Catch (HLC) Methods respectively. Anopheles mosquito larvae were collected using dipping method. Morphological identification of Anopheles species was carried out using standard identification keys. Climatic data was obtained from Nigerian Meteorological Agency Office in Anambra State. A total of 8181 female Anopheles mosquitoes which comprised 4127 (50.4%) larvae and 4054 (49.6%) adults were collected (P > 0.05) in the study. Four Anopheles species: An. gambiae s. l (70.1%), An. funestus group (18.2%), An. moucheti (6.3%) and An. nili (5.4%) were identified (P < 0.05). In the study area, 2608 (31.9%), 3025 (37.0%) and 2548 (31.1%) Anopheles mosquitoes were collected from Aguleri, Igbariam and Nsugbe respectively; with 100% species overlap. In each selected selected town, the Simpson’s index of diversity was ~2 and Shannon-wiener diversity was ~1. Only An. gambiaes l showed varied seasonal abundance with wet season contributing 67.9% and dry season 32.1% of the overall An. gambiaes. l collection (P < 0.05). The correlation between rainfall and An. gambiae s. l. abundance was significantly strong (r = 0.66; P < 0.05). No significant correlation was found between Anopheles species abundance and temperature as well as relative humidity. The study revealed the preponderance of four Anopheles species: An. gambiae s. l., An. funestus, An. moucheti and An. nili; and rainfall is the only climatic factor that causes temporal change in the abundance of one of the species, An. gambiaes. l. in the study area. Keywords: Anopheles mosquitoes, abundance, temperature, rainfall, relative humidity

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agroclimatic studies in the U.S.S.R.

Bulletin of the American Meteorological Society ◽

10.1175/1520-0477-50.2.67 ◽

1969 ◽

Vol 50 (2) ◽

pp. 67-75 ◽

Cited By ~ 4

Author(s):

F. F. Davitaya ◽

S. A. Sapozhnikova

Keyword(s):

Soviet Union ◽

Climatic Factors ◽

Soviet Period ◽

Plant Responses ◽

Climatic Data ◽

The Soviet Union

Agroclimatic studies in the Soviet Union, initiated in the 1920's, were built upon preceding works of Russian meteorological pioneers. During the Soviet period, indices have been refined to relate plant responses to specific climatic factors, and methods have been devised to derive desired indices from standard climatic data. Agricultural appraisals have been made of the climate over the entire territory of the Soviet Union, and maps have been constructed to show agroclimatic regions. Agroclimatic analogs have been developed for many crops and methods of agrometeorological prognosis have been perfected.

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DETERMINATION OF ATMOSPHERIC CORROSION RATE OF METALS IN 12 VIETNAMESE AREAS

Vietnam Journal of Science and Technology ◽

10.15625/2525-2518/55/5b/12235 ◽

2018 ◽

Vol 55 (5B) ◽

pp. 272

Author(s):

Pham Duy Nam

Keyword(s):

Carbon Steel ◽

Corrosion Rate ◽

Rural Areas ◽

Atmospheric Corrosion ◽

Climatic Factors ◽

Air Pollutant ◽

Climatic Data ◽

Corrosion Rates ◽

Copper Aluminum

The corrosion of materials is a result of complex impact from many climatic factors such as temperature, humidity, air pollutant content in the air, rainfall etc. In addition, the corrosion rate of metals can be measured. Each climatic zone is characterized by its corrosion rate. This article presents the testing results to determine the corrosion rate of carbon steel, copper, aluminum and zinc in 12 districts characterizing different climate zones of Vietnam. Testing, evaluation, and classification of atmospheric corrosion were conducted in accordance with the standard ISO 9223. The results show that for all types of studied metals, their corrosion rates which are determined from climatic data are higher than the corrosion rates in reality, especially for carbon steel and aluminum. This difference is more visible in the rural areas.

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Vertical Differences in the Long-Term Trends and Breakpoints of NDVI and Climate Factors in Taiwan

Remote Sensing ◽

10.3390/rs13224707 ◽

2021 ◽

Vol 13 (22) ◽

pp. 4707

Author(s):

Hui Ping Tsai ◽

Geng-Gui Wang ◽

Zhong-Han Zhuang

Keyword(s):

Climate Change ◽

Minimum Temperature ◽

Vegetation Index ◽

Climatic Factors ◽

Maximum Temperature ◽

Climatic Data ◽

Positive Effects ◽

Central Regions ◽

Long Term Trends

This study explored the long-term trends and breakpoints of vegetation, rainfall, and temperature in Taiwan from overall and regional perspectives in terms of vertical differences from 1982 to 2012. With time-series Advanced Very-High-Resolution Radiometer (AVHRR) normalized difference vegetation index (NDVI) data and Taiwan Climate Change Estimate and Information Platform (TCCIP) gridded monthly climatic data, their vertical dynamics were investigated by employing the Breaks for Additive Seasonal and Trend (BFAST) algorithm, Pearson’s correlation analysis, and the Durbin–Watson test. The vertical differences in NDVI values presented three breakpoints and a consistent trend from positive (1982 to 1989) to negative at varied rates, and then gradually increased after 2000. In addition, a positive rainfall trend was discovered. Average and maximum temperature had similar increasing trends, while minimum temperature showed variations, especially at higher altitudes. In terms of regional variations, the vegetation growth was stable in the north but worse in the central region. Higher elevations revealed larger variations in the NDVI and temperature datasets. NDVI, along with average and minimum temperature, showed their largest changes earlier in higher altitude areas. Specifically, the increasing minimum temperature direction was more prominent in the mid-to-high-altitude areas in the eastern and central regions. Seasonal variations were observed for each region. The difference between the dry and wet seasons is becoming larger, with the smallest difference in the northern region and the largest difference in the southern region. Taiwan’s NDVI and climatic factors have a significant negative correlation (p < 0.05), but the maximum and minimum temperatures have significant positive effects at low altitudes below 500 m. The northern and central regions reveal similar responses, while the south and east display different feedbacks. The results illuminate climate change evidence from assessment of the long-term dynamics of vegetation and climatic factors, providing valuable references for establishing correspondent climate-adaptive strategies in Taiwan.

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Forecasting Malaria Cases Using Climatic Factors in Delhi, India: A Time Series Analysis

Malaria Research and Treatment ◽

10.1155/2014/482851 ◽

2014 ◽

Vol 2014 ◽

pp. 1-6 ◽

Cited By ~ 14

Author(s):

Varun Kumar ◽

Abha Mangal ◽

Sanjeet Panesar ◽

Geeta Yadav ◽

Richa Talwar ◽

...

Keyword(s):

Time Series ◽

Relative Humidity ◽

Time Series Analysis ◽

Time Series Data ◽

Climatic Factors ◽

Series Data ◽

Maximum Temperature ◽

Climatic Data ◽

Training Centre ◽

Series Analysis

Background. Malaria still remains a public health problem in developing countries and changing environmental and climatic factors pose the biggest challenge in fighting against the scourge of malaria. Therefore, the study was designed to forecast malaria cases using climatic factors as predictors in Delhi, India. Methods. The total number of monthly cases of malaria slide positives occurring from January 2006 to December 2013 was taken from the register maintained at the malaria clinic at Rural Health Training Centre (RHTC), Najafgarh, Delhi. Climatic data of monthly mean rainfall, relative humidity, and mean maximum temperature were taken from Regional Meteorological Centre, Delhi. Expert modeler of SPSS ver. 21 was used for analyzing the time series data. Results. Autoregressive integrated moving average, ARIMA (0,1,1) (0,1,0)12, was the best fit model and it could explain 72.5% variability in the time series data. Rainfall (P value = 0.004) and relative humidity (P value = 0.001) were found to be significant predictors for malaria transmission in the study area. Seasonal adjusted factor (SAF) for malaria cases shows peak during the months of August and September. Conclusion. ARIMA models of time series analysis is a simple and reliable tool for producing reliable forecasts for malaria in Delhi, India.

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Changes in External and Internal Quality Characteristics of Three Tomato Cultivars Grown at Seven Different Sowing Seasons

HortScience ◽

10.21273/hortsci.33.3.470e ◽

1998 ◽

Vol 33 (3) ◽

pp. 470e-470

Author(s):

Md. Shahidul Islam ◽

S. Khan ◽

S.M.M. Hossain

Keyword(s):

Climatic Factors ◽

Seasonal Pattern ◽

Tomato Fruit ◽

Soluble Sugars ◽

Winter Season ◽

Quality Characteristics ◽

Summer Season ◽

Soluble Solids ◽

Internal Quality ◽

Sowing Time

Seasonal fluctuations of the physical and biochemical characteristics of three tomatoes, including two large-fruited and one cherry-fruited cultivars, were studied in seven different sowing time at an interval of 45 days. Seasonal variation were noted in the external and internal quality characteristics. The seasonal pattern of ripening exhibited a rapid first ripening during summer, followed by a progressive decline until the winter season. Fruits picked during early winter to spring had higher constituents compared to summer season. The fruits matured during the summer season showed higher accumulation of organic and ascorbic acid; but the crop duration was found to be shortened. On the other hand, the fruits matured during winter to spring season had higher firmness, soluble sugars and longer growing period. The lycopene synthesis was enhanced during spring to winter seasons. Of the climatic factors recorded, temperature is predominantly implicated in affecting tomato fruit quality. The results indicated that, firmness, total soluble solids and turning point of hue (arctan a*/b*) act as the indicators of fruit maturity, and breaker stage is more appropriate stage of harvesting in all the seasons studied. But regarding nutritional value and appearance, and for fresh consumption, pink stage of ripening is the best for harvesting. In the present study, although cropping season and growing temperature differed widely, but the cumulative temperature (°C day; from flowering to maturation) difference among growing seasons was small, and most suitable harvest period was found to be around 1000 °C day. Thus, for consumption, marketing and transportation, the fruits availing around 1000 °C days cumulative temperature are congenial to be harvested.

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Effect of town microclimate on the Queensland fruit fly Bactrocera tryoni

Australian Journal of Experimental Agriculture ◽

10.1071/ea04217 ◽

2006 ◽

Vol 46 (9) ◽

pp. 1239 ◽

Cited By ~ 28

Author(s):

B. C. Dominiak ◽

H. S. Mavi ◽

H. I. Nicol

Keyword(s):

Winter Season ◽

Fruit Fly ◽

Urban Environments ◽

Summer Season ◽

Climatic Data ◽

Potential Growth ◽

Rural Landscapes ◽

Rural Environments ◽

Study Results ◽

The Impact

Weekly data from the urban and rural environments of numerous Australian inland towns were used to assess the impact of urban environments on the potential growth rate of the Queensland fruit fly. The urban environments were warmer and more moist than adjacent rural environments, making rural landscapes less attractive for fruit fly. Further analysis of climatic data revealed an acute negative water balance during the summer season. Under this harsh environment, the health and greenness of urban backyards and parks is maintained with frequent use of urban irrigation. This study aims to quantify the impact of urban hydrology on environmental conditions for the population potential of Queensland fruit fly in south-eastern New South Wales. CLIMEX, a climate-driven simulation model, was used in this study. Results indicated that throughout the winter season, low temperatures kept the Queensland fruit fly under control, irrespective of any other factor, including favourable moisture conditions. During summer, moisture was the major limiting factor. Even partial irrigation reduced the limiting effects of the deficiency of rainfall often experienced during midsummer. Irrigation also resulted in a large increase in the duration of the favourable period for the potential growth of fruit fly and an almost complete removal of unfavourable periods. When irrigation water was applied at optimal or excessive levels, the duration of favourable conditions for the Queensland fruit fly extended beyond the summer season. For the Queensland fruit fly, towns appear to be oases compared with the surrounding rural desert. Queensland fruit fly is unlikely to travel freely between towns, minimising chances of reinvasion once a resident population has been eliminated.

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Re-Visiting the Incidence of Environmental Factors on a Pre-Imaginal Population of the Red Gum Lerp Psyllid, Glycaspis brimblecombei Moore

Insects ◽

10.3390/insects11120860 ◽

2020 ◽

Vol 11 (12) ◽

pp. 860

Author(s):

Jürgen Junk ◽

Michael Eickermann ◽

Milan Milenovic ◽

Pompeo Suma ◽

Carmelo Rapisarda

Keyword(s):

Relative Humidity ◽

Air Temperature ◽

Climatic Factors ◽

Eucalyptus Camaldulensis ◽

Fixed Number ◽

Invasive Pest ◽

Time Interval ◽

Climatic Data ◽

Glycaspis Brimblecombei ◽

Red Gum Lerp Psyllid

The red gum lerp psyllid, Glycaspis brimblecombei Moore (Hemiptera: Aphalaridae), is an invasive pest of Eucalyptus trees worldwide, responsible for serious damage, including the death of plants. Knowledge about the incidence of climatic factors on the insect development are essential to define useful strategies for controlling this pest. To this aim, G. brimblecombei has been sampled by two different methods from April 2012 to February 2013 in eastern Sicily on Eucalyptus camaldulensis in nine different sites, where the main climatic data (air temperature, relative humidity, and precipitation) have been also registered. The Glycaspis brimblecombei population showed a similar trend in all nine sites, positively correlated only with air temperature, but a negative correlation has emerged with precipitation and relative humidity. The results show the need for a deeper understanding of the role played by other abiotic (such as different concentrations of CO2) and biotic (e.g., the antagonistic action of natural enemies, competition with other pests, etc.) factors. The greater sensitivity, even at low densities of psyllid, of sampling methods based on the random collection of a fixed number of leaves compared to methods based on the collection of infested leaves in a fixed time interval has been also outlined.

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Climatic Characteristics and Modeling Evaluation of Pan Evapotranspiration over Henan Province, China

Land ◽

10.3390/land9070229 ◽

2020 ◽

Vol 9 (7) ◽

pp. 229

Author(s):

Miao Zhang ◽

Bo Su ◽

Majid Nazeer ◽

Muhammad Bilal ◽

Pengcheng Qi ◽

...

Keyword(s):

Neural Network ◽

Empirical Model ◽

Hydrological Modeling ◽

Climatic Factors ◽

Back Propagation ◽

Henan Province ◽

Generalized Regression Neural Network ◽

Climatic Data ◽

Ann Models ◽

Agricultural Water Resources

Pan evapotranspiration (E) is an important physical parameter in agricultural water resources research. Many climatic factors affect E, and one of the essential challenges is to model or predict E utilizing limited climatic parameters. In this study, the performance of four different artificial neural network (ANN) algorithms i.e., multiple hidden layer back propagation (MBP), generalized regression neural network (GRNN), probabilistic neural networks (PNN), and wavelet neural network (WNN) and one empirical model namely Stephens–Stewart (SS) were employed to predict monthly E. Long-term climatic data (i.e., 1961–2013) was used for the validation of the proposed model in the Henan province of China. It was found that different models had diverse prediction accuracies in various geographical locations, MBP model outperformed other models over almost all stations (maximum R2 = 0.96), and the WNN model was the best over two sites, the accuracies of the five models ranked as MBP, WNN, GRNN, PNN, and SS. The performances of WNN and GRNN were almost the same, five-input ANN models provided better accuracy than the two-input (solar radiation (Ro) and air temperature (T)) SS empirical model (R2 = 0.80). Similarly. the two-input ANN models (maximum R2 = 0.83) also generally performed better than the two-input (Ro and T) SS empirical model. The study could reveal that the above ANN models can be used to predict E successfully in hydrological modeling over Henan Province.

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