scholarly journals Spatiotemporal analysis of rabies in cattle in central Mexico

2019 ◽  
Vol 14 (2) ◽  
Author(s):  
Isabel Bárcenas-Reyes ◽  
Diana Paulina Nieves-Martínez ◽  
José Quintín Cuador-Gil ◽  
Elizabeth Loza-Rubio ◽  
Sara González-Ruíz ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Minimum Temperature ◽  
Spatial Epidemiology ◽  
Risk Estimation ◽  
Regional Distribution ◽  
Spatiotemporal Analysis ◽  
Maximum Temperature ◽  
Spatial Continuity ◽  
Simple Kriging ◽  
Annual Minimum Temperature

Spatial epidemiology of bat-transmitted rabies in cattle has been limited to spatial distribution of cases, an approach that does not identify hidden patterns and the spread resulting in outbreaks in endemic and susceptible areas. Therefore, the purpose of this study was to determine the relationship between the three variables average annual maximum, annual minimum temperature and precipitation in the region on the one hand, and the spatial distribution of cases on the other, using geographic information systems and co-Kriging considering that these environmental variables condition the existence of the rabies vector Desmodus rotundus. A stationary behaviour between the primary and the secondary variables was verified by basic statistics and moving window statistics. The directions of greater and lesser spatial continuity were determined by experimental cross-semivariograms. It was found that the highest risk for bovine paralytic rabies occurs in areas known as La Huasteca Potosina and La Sierra Gorda that are characterized by a maximum temperature of 29.5 °C, a minimum temperature of 16.5 °C and precipitation of 1200 mm. A risk estimation map was obtained for the presence of rabies with a determination coefficient greater than 95%, and a correlation coefficient greater than 0.95. Our conclusion is that ordinary co- Kriging provides a better estimation of risk and spatial distribution of rabies than simple Kriging, making this the method recommended for risk estimation and regional distribution of rabies.

scholarly journals Spatiotemporal Evolution of Fractional Vegetation Cover and Its Response to Climate Change Based on MODIS Data in the Subtropical Region of China

2021 ◽  
Vol 13 (5) ◽  
pp. 913
Author(s):  
Hua Liu ◽  
Xuejian Li ◽  
Fangjie Mao ◽  
Meng Zhang ◽  
Di’en Zhu ◽  
...  
Keyword(s):  
Vegetation Cover ◽  
Minimum Temperature ◽  
Maximum Temperature ◽  
Distribution Area ◽  
Spatiotemporal Pattern ◽  
Climate Factors ◽  
Important Indicator ◽  
Fractional Vegetation Cover ◽  
Annual Minimum Temperature ◽  
Total Study Area

The subtropical vegetation plays an important role in maintaining the structure and function of global ecosystems, and its contribution to the global carbon balance are receiving increasing attention. The fractional vegetation cover (FVC) as an important indicator for monitoring environment change, is widely used to analyze the spatiotemporal pattern of regional and even global vegetation. China is an important distribution area of subtropical vegetation. Therefore, we first used the dimidiate pixel model to extract the subtropical FVC of China during 2001–2018 based on MODIS land surface reflectance data, and then used the linear regression analysis and the variation coefficient to explore its spatiotemporal variations characteristics. Finally, the partial correlation analysis and the partial derivative model were used to analyze the influences and contributions of climate factors on FVC, respectively. The results showed that (1) the subtropical FVC had obvious spatiotemporal heterogeneity; the FVC high-coverage and medium-coverage zones were concentratedly and their combined area accounted for more than 70% of the total study area. (2) The interannual variation in the average subtropical FVC from 2001 to 2018 showed a significant growth trend. (3) In 76.28% of the study area, the regional FVC showed an increasing trend, and the remaining regional FVC showed a decreasing trend. However, the overall fluctuations in the FVC (increasing or decreasing) in the region were relatively stable. (4) The influences of climate factors to the FVC exhibited obvious spatial differences. More than half of all pixels exhibited the influence of the average annual minimum temperature and the annual precipitation had positive on FVC, while the average annual maximum temperature had negative on FVC. (5) The contributions of climate changes to FVC had obvious heterogeneity, and the average annual minimum temperature was the main contribution factor affecting the dynamic variations of FVC.

scholarly journals Long term monthly and inter-seasonal weather variability analysis for the lower Shivalik foothills of Punjab

MAUSAM ◽  
2022 ◽  
Vol 73 (1) ◽  
pp. 173-180
Author(s):  
NAVNEET KAUR ◽  
M.J. SINGH ◽  
SUKHJEET KAUR
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Minimum Temperature ◽  
Maximum Temperature ◽  
Linear Regression Method ◽  
Post Monsoon ◽  
Sunshine Hours ◽  
Annual Minimum Temperature ◽  
Weather Parameters

This paper aims to study the long-term trends in different weather parameters, i.e., temperature, rainfall, rainy days, sunshine hours, evaporation, relative humidity and temperature over Lower Shivalik foothills of Punjab. The daily weather data of about 35 years from agrometeorological observatory of Regional Research Station Ballowal Saunkhri representing Lower Shivalik foothills had been used for trend analysis for kharif (May - October), rabi (November - April), winter (January - February), pre-monsoon (March - May), monsoon (June - September) and post monsoon (October - December) season. The linear regression method has been used to estimate the magnitude of change per year and its coefficient of determination, whose statistical significance was checked by the F test. The annual maximum temperature, morning and evening relative humidity has increased whereas rainfall, evaporation sunshine hours and wind speed has decreased significantly at this region. No significant change in annual minimum temperature and diurnal range has been observed. Monthly maximum temperature revealed significant increase except January, June and December, whereas, monthly minimum temperature increased significantly for February, March and October and decreased for June. Among different seasons, maximum temperature increased significantly for all seasons except winter season, whereas, minimum temperature increased significantly for kharif and post monsoon season only. The evaporation, sunshine hours and wind speed have also decreased and relative humidity decreased significantly at this region. Significant reduction in kharif, monsoon and post monsoon rainfall has been observed at Lower Shivalik foothills. As the region lacks assured irrigation facilities so decreasing rainfall and change in the other weather parameters will have profound effects on the agriculture in this region so there is need to develop climate resilient agricultural technologies.

Detecting climate change in Ukraine: trends, prediction and extreme events

2021 ◽  
Author(s):  
Anna Bohushenko ◽  
Sergiy Stepanenko ◽  
Inna Khomenko
Keyword(s):  
Spatial Distribution ◽  
Minimum Temperature ◽  
Precipitation Amount ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Minimum Value ◽  
Maximum Value ◽  
Temperature Indices ◽  
Consecutive Dry Days

<p>In this study the trends and variations in 25 extreme temperature and precipitation indices<br>defined by ETCCDI, are examined using trend method, probability distribution analysis and<br>spatial statistics for periods of 71 to 137 years for 16 stations evenly distributed in Ukraine. Data<br>on the indices were obtained from www.ecad.eu.<br>Since 1981, temperature has increased by about 1ºC in all stations in question relative to the<br>period of 1945-1980. Analysis of the temperature indices indicates that during the 20th and the<br>beginning of the 21th century there is significant warming which is particularly pronounced in<br>annual mean and annual maximum temperatures. Occurrence of more summer days, warm days<br>and tropical nights and warm spell duration reached the record highest level, and conversely<br>occurrence of frost and ice days, cold days and cold spell duration fall to a record low for the last<br>three decades in the most of study territory.<br>Since 1981, precipitation amount has grown by 30-50 mm relative to the period of 1945-1980 for<br>the most of Ukrainian territory, except Uzhhorod and Uman where precipitation amount has<br>remained the same. For Ukraine average, an increase in maximum daily and maximum 5 days<br>precipitation amount, the maximum number of consecutive wet days, heavy and very heavy<br>precipitation days, and a decrease in the maximum number of consecutive dry days are observed<br>for the last three decades.<br>The analysis of the spatial distribution of trend of precipitation and temperature indices showed<br>that there are large differences between regions of Ukraine, and coherence of spatial distribution<br>of trends of various indices is low.<br>Spectral analysis and harmonic regression techniques were used to derive simulated and<br>predicted (2019-2050) values of annual precipitation and annual mean temperature and four<br>indices such as maximum value of daily maximum temperature, minimum value of daily<br>minimum temperature, the highest 1-day precipitation amount and maximum number of<br>consecutive dry days for some stations such as Kerch (the Crimean Peninsula), Kyiv (situated in<br>north-central Ukraine along the Dnieper River), Lubny (Dnieper Lowland), Lviv and Shepetivka<br>(Podillia Upland), Uzhhorod (Transcarpathia), Uman (Dnieper Upland).<br>Annual mean temperature and maximum value of daily maximum temperature were predicted to<br>increase by 0.33°C per decade in the period of 2019-2050 with respect to 1981-2018, while<br>minimum value of daily minimum temperature was predicted to grow slightly faster (by 0.43-<br>0.63ºC per decade).<br>Precipitation was predicted to increase for the stations in question by 20-66 mm up to 2050<br>relative to 1981-2018 and conversely maximum number of consecutive dry days will slightly<br>decline except Lubny where increase in an aridity index was predicted. In the next three decades<br>changes in maximum daily precipitation will be various: in Shepetivka and Kyiv such<br>precipitation will be decreased and in other stations increasement in such precipitation will be up<br>to 6 mm till 2050 with respect to 1981-2018.</p>

scholarly journals The Association between the Mapping Distribution of Melioidosis Incidences and Meteorological Factors in an Endemic Area: Ubon Ratchathani, Thailand (2009–2018)

2021 ◽  
Vol 20 (4) ◽  
Author(s):  
Jaruwan Wongbutdee ◽  
◽  
Wacharapong Saengnill ◽  
Jutharat Jittimanee ◽  
Pawana Panomket ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Minimum Temperature ◽  
Meteorological Factors ◽  
Interpolation Method ◽  
Public Health Problem ◽  
Kriging Interpolation ◽  
Maximum Temperature ◽  
Tropical Regions ◽  
Kriging Interpolation Method ◽  
Average Rainfall

Abstract Melioidosis is a public health problem in the tropical regions, occurring to meteorological variability. For 10 years of melioidosis outbreaks, we create probability maps of melioidosis distribution during 2009–2018 and determine the association with meteorological factors. The monthly average rainfall and incidence of melioidosis were high from July to September but they not significantly associated (P = 0.576). However, the monthly maximum and minimum temperature were significantly associated with melioidosis incidence (P = 0.002 and P = 0.029, respectively). We estimated the spatial distribution of rainfall and maximum and minimum temperature using the Co-Kriging interpolation method which found that the spatial distribution of the melioidosis incidence was significantly associated with rainfall in 2009, 2010, and 2015; with the maximum temperature in 2009, 2010, 2011, 2013, and 2015; and with the minimum temperature in 2010, 2011, and 2015. Our finding approach may support information and classify a pattern for melioidosis distribution. Keywords: Incidence, Melioidosis, Meteorological factors

scholarly journals Long-Term Trend Analysis in Annual and Seasonal Precipitation, Maximum and Minimum Temperatures in the Southwest United States

Climate ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 142
Author(s):  
Koffi Djaman ◽  
Komlan Koudahe ◽  
Ansoumana Bodian ◽  
Lamine Diop ◽  
Papa Malick Ndiaye
Keyword(s):  
United States ◽  
Trend Analysis ◽  
Minimum Temperature ◽  
Test Method ◽  
Maximum Temperature ◽  
Crop Season ◽  
Southwest United States ◽  
Annual Minimum Temperature ◽  
Increasing Trend

The objective of this study is to perform trend analysis in the historic data sets of annual and crop season [May–September] precipitation and daily maximum and minimum temperatures across the southwest United States. Eighteen ground-based weather stations were considered across the southwest United States for a total period from 1902 to 2017. The non-parametric Mann–Kendall test method was used for the significance of the trend analysis and the Sen’s slope estimator was used to derive the long-term average rates of change in the parameters. The results showed a decreasing trend in annual precipitation at 44.4% of the stations with the Sen’s slopes varying from −1.35 to −0.02 mm/year while the other stations showed an increasing trend. Crop season total precipitation showed non-significant variation at most of the stations except two stations in Arizona. Seventy-five percent of the stations showed increasing trend in annual maximum temperature at the rates that varied from 0.6 to 3.1 °C per century. Air cooling varied from 0.2 to 1.0 °C per century with dominant warming phenomenon at the regional scale of the southwest United States. Average annual minimum temperature had increased at 69% of the stations at the rates that varied from 0.1 to 8 °C over the last century, while the annual temperature amplitude showed a decreasing trend at 63% of stations. Crop season maximum temperature had significant increasing trend at 68.8% of the stations at the rates varying from 0.7 to 3.5 °C per century, while the season minimum temperature had increased at 75% of the stations.

Landscape-scale spatial distribution of spruce budworm defoliation in relation to bioclimatic conditions

2005 ◽  
Vol 35 (9) ◽  
pp. 2218-2232 ◽  
Author(s):  
Jean-Noël Candau ◽  
Richard A Fleming
Keyword(s):  
Spatial Distribution ◽  
Minimum Temperature ◽  
Classification Tree ◽  
Spruce Budworm ◽  
Forest Composition ◽  
Maximum Temperature ◽  
Tree Model ◽  
Bioclimatic Variables ◽  
Defoliation Frequency ◽  
Bioclimatic Conditions

Two empirical statistical models were developed to describe the spatial variation in defoliation by spruce budworm (Choristoneura fumiferana Clem.), as recorded by Ontario's Forest Health Survey from 1967 to 1998. These models revealed a number of relationships between the spatial distributions of aerially detectable spruce budworm defoliation and bioclimatic conditions over the landscape. A classification tree model relates the northern and southern boundaries of defoliation to the relative abundance of different tree species that host spruce budworm. Between these boundaries, the classification tree uses the maximum winter temperature and the minimum temperature in May to describe where detectable defoliation occurred. A regression tree model uses a total of eight variables related to winter temperatures, forest composition, spring temperatures, summer temperatures, and precipitation to estimate the defoliation frequency in areas where defoliation was detected at least once from 1967 to 1998. High defoliation frequencies were associated with dry Junes (precipitation, <86 mm) and cool springs (mean minimum temperature < –2.7 °C). Conversely, low frequencies were associated with cold winters (mean minimum temperature < –23.3 °C; mean maximum temperature > –11.0 °C) in the north and a low abundance of host species (percentage of the basal area occupied by balsam fir, white spruce, and black spruce, <14.3%) in the south. Spatial autocorrelation in the bioclimatic variables had little effect on their relationships with the spatial distribution of the defoliation frequency.

scholarly journals Agro-Climatic Characterization of Two Selected Stations in the Southern West Bengal, India

2013 ◽  
Vol 8 (1-2) ◽  
pp. 49-54
Author(s):  
Saon Banerjee ◽  
Asis Mukherj ◽  
Apurba Mukhopadhayal ◽  
B Saikia ◽  
S Bandyaopadhaya ◽  
...  
Keyword(s):  
Minimum Temperature ◽  
West Bengal ◽  
Seasonal Rainfall ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Positive Trend ◽  
Chain Model ◽  
Climatic Trend ◽  
Annual Minimum Temperature

Maximum temperature, minimum temperature and rainfall data of Bankura (1992-2007) and Canning (1960-2006) were analyzed for assessing climatic trend and agro-climatic characterization of red-lateritic and coastal Zones of West Bengal respectively. These two zones are the most vulnerable regions to climate change in West Bengal, hence selected for the present study. While average values of annual maximum temperature and annual minimum temperature were used for climatic trend analysis, no definite trend was observed. So, maximum temperature of the hottest month and minimum temperature of the coldest month were used for detecting climatic trend. The maximum temperature shows positive trend for both the stations. An increasing trend of annual rainfall was also observed. In case of agro-climatic characterization the agricultural draught, meteorological draught, seasonal rainfall and rainfall probability using Markov-chain model were analyzed for the said two stations. Kharif crops of Bankura encountered two years (2000 & 2005) agricultural draught within 2000 -2007, whereas kharif crops of Canning encountered agricultural draught in 2006 within the said period. Likewise, the deviation of seasonal rainfall and probability of two consecutive wet weeks with different levels (10, 20,30,40,50 and 60 mm) of weekly total rainfall was worked out. DOI: http://dx.doi.org/10.3329/jsf.v8i1-2.14619 J. Sci. Foundation, 8(1&2): 49-54, June-December 2010

scholarly journals Analysis of Past and Projected Trends of Rainfall and Temperature Parameters in Eastern and Western Hararghe Zones, Ethiopia

Atmosphere ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 67
Author(s):  
Helen Teshome ◽  
Kindie Tesfaye ◽  
Nigussie Dechassa ◽  
Tamado Tana ◽  
Matthew Huber
Keyword(s):  
Climate Change ◽  
Minimum Temperature ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Climate Change And Variability ◽  
Annual Minimum Temperature ◽  
Increasing Trend ◽  
Rcp 8.5 ◽  
The Mean ◽  
East And West

Smallholder farmers in East and West Hararghe zones, Ethiopia frequently face problems of climate extremes. Knowledge of past and projected climate change and variability at local and regional scales can help develop adaptation measures. A study was therefore conducted to investigate the spatio-temporal dynamics of rainfall and temperature in the past (1988–2017) and projected periods of 2030 and 2050 under two Representative Concentration Pathways (RCP4.5 and RCP8.5) at selected stations in East and West Hararghe zones, Ethiopia. To detect the trends and magnitude of change Mann–Kendall test and Sen’s slope estimator were employed, respectively. The result of the study indicated that for the last three decades annual and seasonal and monthly rainfall showed high variability but the changes are not statistically significant. On the other hand, the minimum temperature of the ‘Belg’ season showed a significant (p < 0.05) increment. The mean annual minimum temperature is projected to increase by 0.34 °C and 2.52 °C for 2030, and 0.41 °C and 4.15 °C for 2050 under RCP4.5 and RCP8.5, respectively. Additionally, the mean maximum temperature is projected to change by −0.02 °C and 1.14 °C for 2030, and 0.54 °C and 1.87 °C for 2050 under RCP4.5 and RCP 8.5, respectively. Annual rainfall amount is also projected to increase by 2.5% and 29% for 2030, and 12% and 32% for 2050 under RCP4.5 and RCP 8.5, respectively. Hence, it is concluded that there was an increasing trend in the Belg season minimum temperature. A significant increasing trend in rainfall and temperature are projected compared to the baseline period for most of the districts studied. This implies a need to design climate-smart crop and livestock production strategies, as well as an early warning system to counter the drastic effects of climate change and variability on agricultural production and farmers’ livelihood in the region.

scholarly journals Strong controls of daily minimum temperature on the autumn photosynthetic phenology of subtropical vegetation in China

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Peixin Ren ◽  
Zelin Liu ◽  
Xiaolu Zhou ◽  
Changhui Peng ◽  
Jingfeng Xiao ◽  
...  
Keyword(s):  
Climate Change ◽  
Minimum Temperature ◽  
Vegetation Index ◽  
Climatic Factors ◽  
Time Lag ◽  
Evergreen Forest ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Study Region ◽  
Cumulative Precipitation

Abstract Background Vegetation phenology research has largely focused on temperate deciduous forests, thus limiting our understanding of the response of evergreen vegetation to climate change in tropical and subtropical regions. Results Using satellite solar-induced chlorophyll fluorescence (SIF) and MODIS enhanced vegetation index (EVI) data, we applied two methods to evaluate temporal and spatial patterns of the end of the growing season (EGS) in subtropical vegetation in China, and analyze the dependence of EGS on preseason maximum and minimum temperatures as well as cumulative precipitation. Our results indicated that the averaged EGS derived from the SIF and EVI based on the two methods (dynamic threshold method and derivative method) was later than that derived from gross primary productivity (GPP) based on the eddy covariance technique, and the time-lag for EGSsif and EGSevi was approximately 2 weeks and 4 weeks, respectively. We found that EGS was positively correlated with preseason minimum temperature and cumulative precipitation (accounting for more than 73% and 62% of the study areas, respectively), but negatively correlated with preseason maximum temperature (accounting for more than 59% of the study areas). In addition, EGS was more sensitive to the changes in the preseason minimum temperature than to other climatic factors, and an increase in the preseason minimum temperature significantly delayed the EGS in evergreen forests, shrub and grassland. Conclusions Our results indicated that the SIF outperformed traditional vegetation indices in capturing the autumn photosynthetic phenology of evergreen forest in the subtropical region of China. We found that minimum temperature plays a significant role in determining autumn photosynthetic phenology in the study region. These findings contribute to improving our understanding of the response of the EGS to climate change in subtropical vegetation of China, and provide a new perspective for accurately evaluating the role played by evergreen vegetation in the regional carbon budget.

scholarly journals The effect of average temperature on suicide rates in five urban California counties, 1999–⁠2019: an ecological time series analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sierra Cheng ◽  
Rebecca Plouffe ◽  
Stephanie M. Nanos ◽  
Mavra Qamar ◽  
David N. Fisman ◽  
...  
Keyword(s):  
Public Health ◽  
Suicide Rate ◽  
Minimum Temperature ◽  
The United States ◽  
Additive Models ◽  
Maximum Temperature ◽  
Mortality Data ◽  
Average Temperature ◽  
Suicide Rates ◽  
Average Maximum

Abstract Background Suicide is among the top 10 leading causes of premature morality in the United States and its rates continue to increase. Thus, its prevention has become a salient public health responsibility. Risk factors of suicide transcend the individual and societal level as risk can increase based on climatic variables. The purpose of the present study is to evaluate the association between average temperature and suicide rates in the five most populous counties in California using mortality data from 1999 to 2019. Methods Monthly counts of death by suicide for the five counties of interest were obtained from CDC WONDER. Monthly average, maximum, and minimum temperature were obtained from nCLIMDIV for the same time period. We modelled the association of each temperature variable with suicide rate using negative binomial generalized additive models accounting for the county-specific annual trend and monthly seasonality. Results There were over 38,000 deaths by suicide in California’s five most populous counties between 1999 and 2019. An increase in average temperature of 1 °C corresponded to a 0.82% increase in suicide rate (IRR = 1.0082 per °C; 95% CI = 1.0025–1.0140). Estimated coefficients for maximum temperature (IRR = 1.0069 per °C; 95% CI = 1.0021–1.0117) and minimum temperature (IRR = 1.0088 per °C; 95% CI = 1.0023–1.0153) were similar. Conclusion This study adds to a growing body of evidence supporting a causal effect of elevated temperature on suicide. Further investigation into environmental causes of suicide, as well as the biological and societal contexts mediating these relationships, is critical for the development and implementation of new public health interventions to reduce the incidence of suicide, particularly in the face increasing temperatures due to climate change.

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