Mean Minimum Temperature Research Articles

Responses of radial growth of Pinus sylvestris var. mongolica and Larix gmelinii to climate change

In the context of global warming, the increases of temperature may affect tree growth and thus disturb ecosystem balance. In this study, we explored the main limiting factors for radial growth of Pinus sylvestris var. mongolica and Larix gmelinii in the Mohe area of Greater Khingan Mountains by using growth-climate response function analysis and moving correlation analysis, as well as the interspecific difference of the responses of radial growth to rapid warming. The results showed that the radial growth of P. sylvestris var. mongolica and L. gmelinii was affected by both temperature and precipitation. P. sylvestris var. mongolica was more sensitive to climate change than L. gmelinii, and its sensitivity to climate factors was more stable than L. gmelinii. The radial growth of P. sylvestris var. mongolica was significantly positively correlated with the monthly mean temperature and the monthly mean minimum temperature of the growing season, while that of L. gmelinii was significantly positively correlated with the monthly mean temperature and the monthly mean maximum temperature of winter. Precipitation in winter promoted the growth of P. sylvestris var. mongolica, whereas precipitation in the late growing season of the previous year inhibited the radial growth of L. gmelinii. After the rapid warming in 1990, the limiting effect of precipitation on P. sylvestris var. mongolica changed from negative to significantly positive, with the inhibition effect of high temperature being greater than the promotion effect. The inhibitory effect of high temperature on L. gmelinii was enhanced, and the limiting effect of precipitation on L. gmelinii was also enhanced after heating up. The growth rate decreased significantly, with obvious difference being observed in the correlations between the growth rate of two species with temperature and precipitation. Our results could provide scientific basis for forest ecosystem management and protection in Greater Khingan Mountains.

Constructal optimization of heat conduction with minimum entransy dissipation rate for leaf-shaped quadrilateral heat-generating body

<p indent=0mm>In this work, a constructal study of a leaf-shaped quadrilateral heat-generating body based on the bionic quadrilateral of the common leaf vein shape was performed by combining the constructal and entransy theories, thus allowing the optimal construct of the leaf quadrilateral heat-generating body to be derived. The effect of the number of intervals, i.e., the number of branches containing high thermal conductivity materials, <italic>n</italic>, and angle <italic>θ</italic> between the high thermal conductivity material in the branch and the center, on the optimal construction of the heat-generating body was also studied. The constructal differences of the heat-generating body were compared under the minimum entransy dissipation rate and minimum temperature difference. The results show that the mean heat transfer temperature difference of the heat-generating body is the smallest in the optimal constructal when the entransy dissipation rate is the lowest. With the increase in the number of intervals (<italic>n</italic>≥20), the optimal aspect ratio and minimum mean temperature difference of the heat-generating body decreased slightly. Therefore, increasing the complexity of the high heat conduction passage in the heat-generating body can decrease the mean heat transfer temperature difference. Different optimal constructs of the heat-generating body were obtained using the entransy dissipation rate and maximum temperature difference as the optimization objective; both provide more optimal solutions when the high thermal conductivity material of the branch and center are perpendicular. Furthermore, minimizing the entransy dissipation rate allowed for a smaller mean temperature difference to be obtained. Therefore, using the minimum entransy dissipation rate as the optimization objective can reduce the mean heat transfer temperature difference more effectively in a leaf-shaped quadrilateral heat-generating body.

Impact of global climate change on temperature seasonal and annual of Arak city in the 2040s

Introduction: Global warming is the most important challenge facing man in the 21st century. Warmer weather will increase evapotranspiration, which will exacerbate droughts. One of the main causes of global warming is man himself. Humans have accelerated the Earth's climate change by producing large amounts of greenhouse gases. For this reason, information about changes in the earth's temperature in the next decades has always been considered. The results of the researchers show that climate change has obvious and significant effects on temperature and rainfall in different parts of Iran in the next decades. By predicting and estimating the extent of these effects, climate change impacts can be mitigated with adequate preparedness, low cost, and greater speed.Material and methods: In this study, the effect of climate change on the mean maximum and minimum annual and seasonal temperatures in Arak under the emission scenarios of RCP2.6, RCP4.5, RCP8.5 for the 2040s was investigated. To use the output of General Circulation Models at regional and local scales is that they are using downscaling models, are downscaled. In this study, Statistical Downscaling Model (SDSM) to downscale output of General Circulation Models CanESM2 were used. This model had an acceptable ability to simulate the average maximum and minimum seasonal and annual temperatures in the study area. Results and discussion: According to the obtained results, the mean maximum temperature in winter and spring will decrease under all three scenarios RCP2.6, RCP4.5, RCP8.5, which can indicate that the daily temperature will be cooler in these seasons. However, the mean maximum temperature will increase in summer and autumn, which may indicate that the daily temperature will be warmer in these seasons. The mean minimum temperature in winter and spring under all three scenarios RCP2.6, RCP4.5, RCP8.5 will decrease and increase in summer seasons. These results show that in the 2040s, the city of Arak has colder night temperatures in winter and spring and warmer temperatures in summer and spring. Due to the fact that warmer weather increases the demand for water and electricity, and because Arak is an industrial city with a dry climate, it can face serious challenges of water and electricity shortage in the future.Conclusion: According to the results obtained in this study, in the 2040s, Arak will have colder winters and springs, and warmer summers and autumns. The highest effect of climate change on the temperature of Arak is related to the average minimum temperature in autumn, which under the scenarios of RCP2.6, RCP4.5, RCP8.5, the average minimum temperature in autumn increased by 206.88, 196.37 and 192.27 percent, respectively. The mean annual maximum and minimum temperature under all three scenarios will increase in the 2040s. The highest increase in the mean annual maximum and minimum temperature is related to RCP8.5 and RCP2.6 scenarios, respectively, which they are equal to 4.14 and 4.38.

Assessment of trends in climatic extremes from observational data in the Kashmir basin, NW Himalaya.

The present study aims to assess the recent changes and trends in the extreme climate indices in the Kashmir basin using the observational records from 1980 to 2016. The extreme climate indices were computed using the ClimPACT2 software and a total of 39 indices were selected for the analysis having particular utility to various sectors like agriculture, water resources, energy consumption, and human health. Besides adopting the station scale analysis, regional averages were computed for each index. In terms of the mean climatology, an increase has been observed in the annual mean temperature with a magnitude of 0.024°C/year. Further, differential warming patterns have been observed in the mean maximum and minimum temperatures with mean maximum temperature revealing higher increases than mean minimum temperature. On the other hand, the annual precipitation shows a decrease over most of the region, and the decreases are more pronouncing in the higher altitudes. The trend analysis of the extreme indices reveals that in consonance with the rising temperature there has been an increase in the warm temperatures and decrease in the cold temperatures across the Kashmir basin. Furthermore, our analysis suggests a decrease in the extreme precipitation events. The drought indices viz., Standardised Precipitation Index (SPI), and Standardised Precipitation Evapotranspiration Index (SPEI) manifest decreasing trends with the tendency towards drier regimes implying the need for better water resource management in the region under changing climate.

Assessing the performance and accuracy of invasive plant habitat suitability models in detecting new observations in Wisconsin

AbstractLand managers require tools that improve understanding of suitable habitat for invasive plants and that can be incorporated into survey efforts to improve efficiency. Habitat suitability models (HSMs) contain attributes that can meet these requirements, but it is not known how well they perform, as they are rarely field-tested for accuracy. We developed ensemble HSMs in the state of Wisconsin for 15 species using five algorithms (boosted regression trees, generalized linear models, multivariate regression splines, MaxEnt, and random forests), evaluated performance, determined variables that drive suitability, and tested accuracy. All models had good model performance during the development phase (Area Under the Curve [AUC] &gt; 0.7 and True Skills Statistic [TSS] &gt; 0.4). While variable importance and directionality was species specific, the most important predictor variables across all of the species’ models were mean winter minimum temperatures, total summer precipitation, and tree canopy cover. Post model development, we obtained 5,005 new occurrence records from community science observations for all 15 focal species to test the models’ abilities to accurately predict results. Using a correct classification rate of 80%, just 8 of the 15 species correctly predicted suitable habitat (α ≤ 0.05). Exploratory analyses found the number of reporters of these new data and the total number of new occurrences reported per species contributed to increasing correct classification. Results suggest that while some models perform well on evaluation metrics, relying on these metrics alone is not sufficient and can lead to errors when utilized for surveying. We recommend any model should be tested for accuracy in the field before use to avoid this potential issue.

Evidences of climate change presences in the wettest parts of southwest Ethiopia

Climate change has been identified as a major challenge of rainfed agriculture. To contextualize whether there is climate change footprint, identification of rainfall and temperature trend at regional and local scale is helpful for designing long-term adaptation and mitigation strategies. The present study therefore aims to assess evidences of climate change presences in terms of, climate variability and trend in the wettest parts of Southwest Ethiopia. Daily and monthly historical gridded rainfall and temperature data (1983–2016) of ten stations were provided by Ethiopian National Metrological Agency. Moreover, long years historical recorded climate data of Nekemte and Bedele (1971–2020) and Sekoru (1981–2020) were used in the present study. Coefficient of variation, the Mann-Kendall non-parametric statistical test and Sen's slope estimator, linear regression analysis and the precipitation concentration index were applied to detect the presence of climate change in the southwest parts of Ethiopia. In this study, the trend package of open R software employed for trend identification and rate of change per year. The results indicate that the annual rainfall has declining trend at five stations with statistically significant at one station while the mean maximum and minimum temperature shows a statistically significant increasing trend at eight and six stations, respectively. At a seasonal scale, the amount of rainfall in the main rainy season (June to August) is dominated by a downward trend (eight out of ten stations) while, the autumn season (September to November) shows an increasing trend in all stations with statistically significant at one station. The precipitation concentration index analysis revealed that inconsistent and significantly irregular precipitation is observed at six stations (60%) of the ten stations. This study concludes that the climate of the wettest parts of Ethiopia is getting warmer and the amount of rainfall in the main rainy season has declined in the vast majority of the study area.

Modelling Chablis vintage quality in response to inter-annual variation in weather

The weather during grape production affects wine quality. Changes in the weather in the Chablis region of France and in the quality of Chablis wines (vintage scores) from 1963 to 2018 were analysed. Chablis wine quality improved over this period, with no Poor vintages after 1991. Summer temperature and sunshine duration both increased progressively between 1963 to 2018 with fewer frost days but no linear change detected in precipitation. Chablis vintage score was modelled as a function of mean temperature from April to September (curvilinear relation, maximum score at 16–17 °C), mean minimum temperature in September (an index of cool nights; negative relation), and total rainfall from June to September (negative relation). This simple three-factor model distinguished between Poor and higher-quality Chablis vintages well, but less so between Good and Excellent vintages. Application of the model to different climate change scenarios (assuming current viticultural and oenological practices) suggests that vintage scores will decline (slightly to substantially, dependent upon emissions scenario) by the 2041 to 2070 period. This reduction in quality would, however, be minimised if the warming of cool nights is less than currently forecast. The Chablis vintage score model may help identify sites with suitable climates for premium white wine from Chardonnay grapevines in emerging cool climate viticulture regions as well as aiding Chablis producers mitigate the effects of climate change.

Trends of Rainfall and Temperature in Bangladesh: A Comparative Analysis of CMIP5 Results and Meteorological Station Data

The Coupled Model Inter-comparison Project phase 5 (CMIP5) dataset along with rainfall and temperature data, recorded at 34 stations of Bangladesh Meteorological Department (BMD), is analyzed to examine the recent changes in rainfall and temperature over Bangladesh during the period 1981-2019. In the historical period, all three CMIP5 models (MPI-ESM-LR, MPI-ESM-MR and NorESM1-M) underestimated the observed mean rainfall data collected from BMD, whereas for temperature the result is found to be nearly similar between model and observation. The result shows a trend of increasing mean maximum temperature of Bangladesh at a rate of 0.19°C and 0.26°C per decade and increasing mean minimum temperature at a rate of 0.18°C and 0.15°C per decade, for model and observation respectively. The study found a decreasing trend of annual rainfall in Bangladesh observed at a rate of 41.60 mm and 39.77 mm per decade, respectively, for model and observation. Spatial distribution shows an increase in annual rainfall in the northeastern part of Bangladesh. The Dhaka University Journal of Earth and Environmental Sciences, Vol. 9(2), 2020, P 9-18

Quantifying maize grain yield losses caused by climate change based on extensive field data across China

Climate change can have significant impacts on maize (Zea mays L.) grain yield. In this study, we used extensive multi-year field experimental data (n = 423) across different climatic regions of China to distinguish effects of different climate factors on maize grain yield and mimicking the effect of climate change, in particular, temperature and solar radiation. Across the years and climatic regions, the major driver for the yield difference was found to be the diurnal temperature range (DTR) and accumulated photosynthetically active radiation (PAR). 1 °C decrease in DTR and 100 MJ decrease in accumulated PAR resulted in 1.0 t ha−1 and 0.85 t ha−1 reduction in maize grain yield, respectively. 1 °C increase in growing season mean temperature (Tmean) and minimum temperature (Tmin) resulted in 0.83 t ha−1 and 0.67 t ha−1 maize grain yield reduction. By mimicking the effect of climate change on maize grain yield, it was found that 1 °C increase in Tmean resulted in 0.83 t ha−1 (5.8%) maize grain yield reduction. Decrease in PAR also decreased maize grain yield significantly and the 1% decrease in PAR decreased maize grain yield by 0.15 tons per ha. Among all the five cultivars in this study, yield reductions of ZD958 and NH101 induced by 1 °C increase in Tmean were the smallest compared to other three cultivars. The quantitative analysis can provide important guidance to predict possible quantitative outcomes of future changes in crop productivity due to climate change and search for effective mitigation strategies such as cultivar selection.

Rainfall and Temperature Projections and their Impact Assessment Using CMIP5 Models under Different RCP Scenarios for The Eastern Coastal Region of India

Trend analysis of annual rainfall over the coastal districts of Odisha, India showed statistically nonsignificant increasing trend in all districts, except Ganjam. Whereas the maximum and minimum temperature showed significant increasing trend. Warming in these districts is mainly due to increasing minimum temperature during summer and rainy season, and maximum temperature during winter. Future climate projection results revealed, the annual mean rainfall is expected to change by 0.1–2.2%, –0.3–0.7% and 1.5–3.2% (RCP 4.5), and 3.6–7.9%, 3.7–6.6% and 8.5–14% (RCP 8.5) during the near (2011–39), mid (2040–69) and late (2070–99) centuries respectively. Anticipate climate change will have a marginal impact on total rainfall, and a major impact on its distribution. The annual mean minimum temperature is expected to increase by 0.60–0.73°C, 0.71–0.88°C, 1.20–1.42°C (RCP 4.5), and 1.77–2.14°C, 1.56–1.68°C, 3.06–3.73°C (RCP 8.5) during near, mid and late centuries respectively. Similarly, the annual mean maximum temperature is expected to increase by 0.61–0.66°C, 0.68–0.72°C and 1.35–1.55°C (RCP 4.5), and 1.79–1.97°C, 1.73–2.01°C and 3.08–3.44°C (RCP 8.5) during near, mid and late centuries respectively. Season-wise projection revealed that the change in rainfall and temperature is expected to be more in winter and summer under both the RCP scenarios. The projected future climate change will have both positive and negative impacts on agriculture. The negative impacts are expected to be more pronounced during kharif in comparison to rabi .

A meta-analysis of the possible impact of climate change on global cotton yield based on crop simulation approaches

CONTEXT:Cotton is one of the most widely planted fiber crops in the world. Its growth, development, and yield are influenced by elevated atmospheric CO2 concentrations, temperature increases, and seasonal rainfall patterns. However, due to differences in research methods (such as crop models, climate models, and climate scenarios), there are uncertainties in the magnitude and direction of the impact of future climate change on cotton yields in existing studies. OBJECTIVETo comprehensively assess the potential impact of climate change and adaptation on yieldand analyze the associated uncertainties, 27 published studies (including 1353 samples) were used to establish a meta database of changes in future cotton yield. METHODSThe responses of cotton relative yield change to changes in mean temperature, minimum temperature, maximum temperature, precipitation, and CO2 concentration were studied using local polynomial (Loess) regression in a full dataset. A linear mixed-effect model was then used to explore the quantitative relationship between them in a restricted dataset. RESULTS AND CONCLUSIONSUsing the established full dataset, we found that when the average temperature exceeded 4.3 °C, or the average precipitation decreased or increased too much (>200%), the simulated cotton yield decreased. Elevated CO2 concentrations and appropriate management measures could alleviate the negative impact of climate change. By establishing a linear mixed-effect model, we found that temperature, precipitation, CO2 concentration changes, adaptive measures, study area, climate models, and climate scenarios had significant impacts on cotton yield change. For every 1 °C increase in average temperature, the cotton yield decreased by 1.64%. For every 1% increase in precipitation and 1 ppm increase in CO2 concentration, cotton yield increased by 0.09% and 0.05%, respectively. Cotton yield under adaptation measures was 8.97% higher than without any adaptation. SIGNIFICANCEThe first systematic meta-analysis of the impact of climate change on cotton yield in major cotton-planting regionswas conducted herein. The findings provide new information for policies related to the impact of climate change and enhance our understanding of the future resilience of the cotton system.

Distribution and Damage Assessment of Icerya seychellarum (Westwood) (Hemiptera: Monophlebidae) on Guava Trees Under Environmental Conditions of Luxor, Egypt

Field evaluation studies were conducted during two years (2017/ 2018 and 2018/ 2019) to investigate the distribution and assess infestation degrees of Icerya seychellarum (Westwood) (Hemiptera: Monophellidae) on guava trees under selected prevalent climatic factors (daily mean maximum air temperature, minimum air temperature, daily mean of relative humidity and mean of dew point) at Esna district, Luxor Governorate, Egypt. The invasion of I. seychellarum was prevalent all year-round. In the first year (2017/ 2018), the population of pests formed three to four peaks (At the beginning of June, mid-September, and mid-November). Afterward, throughout the second year (2018/2019), the outbreaks of the pest were occurred in (The beginning of April, mid-June, mid-August, and mid of October). Furthermore, the percentages of infestation incidence by pests showed three to four peaks per year. With respect to climatic conditions, the autumn months during the two years were more favorable for the seasonal activity of total population density where the maximum values of infestation occurred by I. seychellarum. The weather factors showed an effect on pest activity and percentages of infestations during years of study which varied from year to another with an obvious to the most effective variables [daily mean maximum air temperature °C (DMaxT), daily mean minimum air temperature °C (DMinT), daily mean of relative humidity % (DRH%), and mean of dew point ° C (MDP)] for these changes for both years.

Substantial shifts in flowering phenology of Sternbergia vernalis in the Himalaya: Supplementing decadal field records with historical and experimental evidences

In an age of anthropocene, shifting plant phenology is one of the most striking biological indicators of global environmental change. Majority of the studies reporting shifts in plant phenology are available from the North America and Europe and largely scarce from the developing world, including the Himalaya; and studies integrating multiple methodological approaches to investigate the climate-driven phenological shifts are too rare. Here, we report the shifts in spring flowering phenology of model plant species, Sternbergia vernalis in response to the changing climate in Kashmir Himalaya, by integrating decadal field observational records with long-term herbarium and dated-photograph data, and supported with experimental evidences. Our results revealed a significant increasing trend of 0.038, 0.016 and 0.023 °C/year in the annual mean maximum temperature (Tmax), mean minimum temperature (Tmin) and diurnal temperature range (DTR) respectively; but an insignificant decreasing trend in annual precipitation of −1.24 mm/year over the last four decades (1980–2019) in this Himalayan region. The flowering phenology of S. vernalis has significantly advanced by 11.8 days/°C and 27.8 days/°C increase in Tmax and Tmin respectively, indicating that the climate warming has led to substantial shifts in flowering phenology of the model plant species. We also observed a strong association of seasonal Tmax (December–February) and DTR on the early onset of spring flowering, however precipitation had no significant effect on the timing of flowering. The greenhouse experiment results further supported a significant effect of temperature in triggering the phenological shifts, wherein the model plant grown under different temperature treatments flowered 9–20 days earlier compared to the control. Our study showcases the integrated use of multiple methodological approaches for unravelling the long-term phenological shifts in response to climate change, and contributes in filling the knowledge gaps in the phenological research from the developing world in general and the Himalaya in particular.

بررسی مقایسه ای فلفل قرمز با محرکهای رشد تجاری بر عملکرد جوجههای گوشتی در شرایط تنش گرمایی

Effect of red pepper in comparison to commercial growth promoters, Biostrong and Oleobiotec, on growth performance, nutrient digestibility, and other traits of broilers under heat stress conditions using 200 day-old broiler chickens mixed male and female of ArborAcers strain in a completely randomized design with four treatments, five replications and ten chickens per replicate were evaluated. Treatments included a basal diet without additives and a basal diet containing 10, 0.1, 0.15 g/kg red pepper, Biostrong, and Oleobiotec,respectively. At the beginning of third week, the birds were exposed to heat stress for six hours per day. During the 42 days of the experiment, the mean minimum and maximum temperatures were 25°C and 33°C. Feed intake, weight gain, feed conversion ratio, the weight of internal organs, caecal microflora, and precaecal nutrient digestibility were measured for the heat stress period. The use of red pepperimproved the feed conversion ratio and daily weight gain in grower and finisher periods and increased protein, lipid, and dry matter precaecal digestibility, the relative weight of bursa of Fabricius, spleen, and gizzard, and decreased the Ecoli population in caecum compared to the control treatment (P≤0.05). Biostrong and Oleobiotec did not affect growth performance, prececal nutrient digestibility, and the E.colipopulation. Overall, using the red pepper in the diet of broilers compared to commercial growth promoters reduced the adverse effects of heat stress on growth performance, nutrient digestibility, and caecal microflora.

Natural History of a Highly Medically Important Snake, Russell's Viper (Daboia russelii), in a Human-Dominated Indian Rural Landscape

Venomous snakes are a public health concern in India, where they kill tens of thousands of people annually. Russell's Vipers are the major culprit, but despite their clinical significance, there is virtually no information on their ecology. I used radiotelemetry for a 9-mo period to study the spatial and behavioral ecology of a population of Russell's Vipers (Daboia russelii) in a human-dominated rural landscape in Karnataka, India. Russell's Vipers spent a substantial amount of time in plantations, which make up a significant proportion of the landscape. Snakes were the least active in March, a dry month with the hottest monthly mean maximum temperatures recorded; and spatial activity comparatively increased in late fall-early winter and May, corresponding with the timing of mating activities and the end of the dry season, respectively. Russell's Vipers basked throughout the year, but basking behavior was more frequent in January and February, when the monthly mean minimum temperatures were the lowest. The probability of observing a snake basking increased with decreasing minimum temperatures. Similarly, the snakes were found in ambush foraging postures during daytime throughout the year, and the odds of observing diurnal foraging increased with increasing minimum temperatures and was affected by an interaction between maximum temperature and sex. Overall, the data indicate that this tropical viper actively thermoregulates and is to some extent diurnal. This study provides the first quantitative field-based natural history information on Russell's Vipers, one of the most medically important snakes in the world.

Spatial and Temporal Variations of Temperature in the Punjab Province, Pakistan

Identifying the temperature change at a regional level is one of the essential parameters to determine the intensity of climate change. The current investigation provides an examination of changing trends of temperature in the Punjab province from 1970 to 2019. Sen's slope estimator method is applied to monthly data of mean temperature (Tmean), maximum temperature (Tmax), and minimum temperature (Tmin) to calculate the rate of temperature change. Statistical methods were used to find out the level of significance in terms of negative or positive trends to examine the variability among various weather observatories. Moreover, predicted values have also been observed for a detailed analysis of temperature variability and trends. Significant and pronounced changes in the mean temperature (T mean) are distinguished all over the Punjab regions with an increasing trend from North to South Punjab. In the case of maximum temperature (Tmax), a faster rate of rising in temperature is observed over the Southern and Western regions of Punjab. In contrast, the minimum temperature (Tmin) shows an increasing trend in Central Punjab. The findings provide detailed insight to policymakers for the planning of mitigating efforts and adaptation strategies in response to climate change.

The effect of meteorological variables on salmonellosis incidence in Kermanshah, West of Iran: a generalized linear model with negative binomial approach.

Salmonella is one of the main causes of gastroenteritis, and its incidence may be affected by meteorological variables. This is the first study about the effect of climatic factors on salmonella incidence in Kermanshah, Iran. Data about salmonellosis cases in Kermanshah were inquired from Center for Communicable Disease Control, at the Ministry of Health and Medical Education of Iran, for the 2008 to 2018 time-frame. Meteorological variables including maximum, minimum and mean of temperature and humidity, sunshine hours and rainfall were inquired for the same time frame. Negative binomial generalized linear models (GLM) were used to assess the effect of meteorological variables on the weekly incidence of salmonellosis. During the years under study, 569 confirmed cases were registered in Kermanshah province. Study results showed a 3 % increase in salmonellosis incidence, after 1 % increase in minimum humidity in the week before (incidence rate ratio (IRR): 1.03; 95 % confidence interval (CI):1.02-1.05) and also a 4 % increase in incidence for 1°C increase in mean temperature in the same week (IRR: 1.04; 95 % CI:1.02-1.06). Increase in minimum humidity and mean temperature may have a role in increasing the incidence of salmonellosis in Iran.

Modeling riparian species occurrence from historical surveys to guide restoration planning in northwestern USA

AbstractSuccessful restoration of riparian habitats and functions depends in part on selection of plant species that are suited to local geomorphic and climatic conditions, which often relies on contemporary reference sites to characterize target riparian vegetation communities. In heavily modified landscapes, a lack of undisturbed sites hinders the description of reference conditions to help guide planning efforts. In lieu of contemporary reference sites, we used historical Public Land Survey data from the late 1800s and early 1900s to document historical streamside vegetation at 1685 sites distributed throughout the Columbia River basin. We used those data to construct a random forest classification model using climatic and geomorphic variables to predict the probability of occurrence of riparian vegetation groups (conifer, deciduous, shrub, and willow) and individual taxa (fir, pine, cedar, cottonwood, alder, sagebrush) for all stream reaches with bankfull width &gt;6 m in the interior Columbia River basin. The most common predictor variables included in the best models for vegetation groups or individual taxa were mean annual precipitation, minimum temperature, elevation, and bankfull width. For some taxa, temperature range and floodplain width were also important predictors. The probability maps indicate that riparian zones were likely dominated by willow species in semi‐desert regions and by conifer species in the humid mountain regions. Deciduous species dominated riparian areas in transition zones between conifer forests and semi‐deserts. Species distributions suggest that streams in the semi‐deserts were likely characterized by little shade and low wood abundance, whereas streams in the humid mountains would have been more heavily shaded with high wood abundance. The transitional deciduous areas were likely shaded with moderate wood abundance. Historical trends in air temperature and precipitation suggest relatively small changes in climate since the time of the surveys, indicating that current species ranges are likely similar to historical species ranges. Hence, these maps can be used to help identify suitable taxonomic groups and expected riparian functions for riparian restoration in the Columbia River basin, with appropriate adjustments made to site‐specific restoration designs to account for model uncertainty, future climate change, or land use constraints.

Climatic and Topographic Control of the Stable Isotope Values of Rivers on the South Island of New Zealand

AbstractWe show that climate and topography control the spatial distribution of stable isotope values on the South Island of New Zealand, based on a spatially dense (n = 193) river isotopic survey. Our data show a δ18O minimum in isotope values east of the Southern Alps that demonstrates topographically driven continentality associated with the Southern Alps, which intersect the prevailing, moisture‐laden westerlies. Our data define a South Island surface water line of δ2H = 8.17 (±0.26) × δ18O + 10.57 (±2.04), which is identical within 95% confidence intervals to the global and New Zealand meteoric water lines established from monthly precipitation samples. The observed river δ18O values are strongly correlated with annual temperature range and winter temperature. Strongest correlations are between δ18O and mean minimum winter temperatures (r &gt; 0.7 for June, July, August), with gradients of 0.58–0.66‰ /°C. Based on a multiple regression analysis of δ18O against climate data, we present a river δ18O model and isoscape that demonstrate the control of continentality and moisture source on New Zealand surface water isotope spatial patterns. Model validation against previously published river samples shows skill in predicting river δ18O values (root‐mean‐square error = 0.83), confirming that the spatial variations in river δ18O (and δ2H) are robust to sampling period and reflect continental, precipitation source and temperature effects. Our data suggest that oxygen or hydrogen isotope paleoclimate proxies derived from rivers or open‐system lakes on the South Island should be sensitive to winter temperature.

Effects of climate variables on the COVID-19 outbreak in Spain.

An outbreak of the novel COVID-19 virus occurred during February 2020 onwards in almost all the European countries, including Spain. This study covers the correlation found between weather variables (Maximum Temperature, Minimum Temperature, Mean Temperature, Atmospheric Pressure, Daily Rainfall, Daily Sun hours) and the coronavirus propagation in Spain. A strong relationship is found when correlating the virus spread to the mean temperature, minimum temperature, and atmospheric pressure in different Spanish provinces. In this analysis we have used the ratio of the PCR COVID-19 positives with respect to the population size. A linear regression model using the mean temperature is implemented. Moreover, an analysis of variance is used to confirm the influence of mean temperature on the spread of virus. As a second measurement of the COVID-19 outbreak we have used the results of the antibodies tests carried out in Spain that provide an estimation of the heard immunity achieved. Based on this analysis, an estimation of the asymptomatic population is performed. All these results exhibit significant correlation with weather variables. The most affected provinces were Soria, Segovia and Ciudad Real, which are the coldest. On the opposite side, places such as Southern Spain, the Baleares, and Canary Islands showed a lower rate of spread. This might be related to the warmer climate and the insularity of these islands. Besides, the coastal influence and the daily sun hours might also influence the lower rates in the east and west regions in Spain. This analysis provides a deeper insight of the influence of weather variables onto the COVID-19 spread in Spain.