Night Air Temperature Research Articles

Protecting Flowers of Fruit Trees From Frost With Dynamic Agrivoltaic Systems

Spring frost is a risk for fruit tree production. In this study, a dynamic agrivoltaic system (AV) was tested as a solution to protect trees from frosts. The study was done in a nectarine AV in France in 2022 and 2023. The AV plot was paired with an adjacent control plot without panels. Air temperature nearby the trees was measured continuously with thermo-hygrometers each year. In 2022 and 2023 frost sensors to mimic organ temperature were also used. In 2023, bud temperatures were continuously measured during bloom. Frosts during bloom were observed in 2022 and 2023 but only the 2022 frost was associated with flower damage. Solar panels were positioned in horizontal position during the nights with frost. Night air temperature nearby the AV trees was warmer in comparison with control trees (increases between 0.27 and 0.47 °C). An increase between 0.25-1.29 °C was also observed for frost sensors and between 1.61-1.69 °C for the flower buds. Phenology was similar between control and AV trees. In 2002, 35% of control flowers were injured during frost while less than 10% were injured in the AV. We conclude that agrivoltaics can be used to protect flowers from frost.

Enhancing Cowpea Tolerance to Elevated Temperature: Achievements, Challenges and Future Directions

Despite its ability to thrive in high-temperature environments, cowpea productivity can be hampered by heat stress, particularly when night air temperatures exceed 17 °C. The crop’s germplasm pool potentially possesses significant genetic variability that can be harnessed to breed for heat-tolerant varieties. Progress in improving the crop for heat tolerance has been limited, especially under the hot, short-day environments typical of sub-Saharan Africa. Only a few heat-tolerant varieties have been released, partly due to the limited understanding of heat stress tolerance mechanisms and environmental interaction effects on genotypes, as well as imprecise phenotyping. This review contributes to the literature on cowpea heat stress by highlighting key achievements, challenges, and future directions in breeding heat-tolerant cowpea genotypes and by providing additional information from the recent literature. We opine that the genetic variability for heat tolerance-related traits in cowpea has not been sufficiently exploited in developing varieties adapted to the target production environments. Therefore, attention should be given to assessing the crop’s genetic repository by targeting adaptive, morphological, and physiological traits that enhance heat stress tolerance. We propose that breeding programs integrate phenotyping of whole-plant physiological traits and molecular breeding to identify breeder-friendly markers for routine selection. This should be followed by introgression of the heat-tolerant favourable alleles to adapted susceptible varieties using rapid and precise approaches that take advantage of modern genetic and genomic resources such as innovative genetic resources, genomic selection, speed breeding, and genome editing technologies. These tools hold great promise in fast-tracking the development of improved heat-tolerant varieties and incorporating the must-have traits preferred by cowpea farmers and consumers. In view of the likely increase in atmospheric temperature to be occasioned by climate change, there is an urgent need to develop heat-tolerant cowpea varieties to ensure the sustainability of current and future cropping and agri-food systems.

Phenology and radial growth of poplars in wide alley agroforestry systems and the effect on yield of annual intercrops in the first four years of tree age

Silvoarable agroforestry systems have the potential to combat the negative effects of climate change while also enhancing productivity per unit land. Although the growth rate of large-spaced trees remains poorly investigated and the yield of annual intercrops uncertain, silvoarable agroforestry systems with poplar are receiving an ever-growing interest. This study assessed the growth of the new HES (High Environmental Sustainability) poplar clone, Moncalvo, arranged in 40-m spaced parallel alleys with a density of 35 trees ha−1 (SA, silvoarable). Their growth was compared to those cultivated in a specialized poplar plantation (C, control) with 277 trees ha−1, and the agronomic impact on wheat and soybean as intercrops was explored. Measurements took place between 2018 and 2021 during the first 4 years, which represents the midpoint of the expected poplar rotation. Here it was demonstrated that at the end of the investigated period, diameter at breast height was significantly greater (23.8 vs. 20.5 cm, +16%) and the plant height lower (14.3 vs. 15.5 m, −8%) in poplar grown in SA as compared to those in C, likely due to reduced intraspecific competition for environmental resources. In SA, seasonal tree phenology was delayed by approximately two weeks in spring, possibly due to the high sensitivity of poplar to low soil water content and cooler night air temperatures in springtime. The grain yield of wheat was not impaired by tree shading but instead occasionally improved when neighboring the poplar alley (e.g., year 2021: +28% at 12 m from the tree row vs. full sun conditions), while soybean yield was generally reduced (maximum −38% at 6 m from the tree row). This study innovatively studied the growth response of HES poplar clones in silvoarable systems by providing valuable insights into the growth dynamics of trees grown in combination with field crops. It is concluded that poplars in wide spaced alleys of silvoarable systems in temperate climates grow faster than poplars in plantations of high population density due to enhanced access to resources, while future investigations will allow for the identification of clone-specific rotation durations. In the arable tree interrow, winter crops more readily benefit from such agroforestry system than summer crops due to reduced cycle overlap and light competition with the tree canopy.

Field‐based infrastructure and cyber–physical system for the study of high night air temperature stress in irrigated rice

AbstractHigh night air temperature (HNT) stress negatively impacts both rice (Oryza sativa L) yield and grain quality and has been extensively investigated because of the significant yield loss observed (10%) for every increase in air temperature (1°C). Most of the rice HNT studies have been conducted under greenhouse conditions, with limited information on field‐level responses for the major rice sub‐populations. This is due to a lack of a field‐based phenotyping infrastructure that can accommodate a diverse set of accessions representing the wider germplasm and impose growth stage‐specific stress. In this study, we built six high‐tunnel greenhouses and screened 310 rice accessions from the Rice Diversity Panel 1 (RDP1) and 10 commercial hybrid cultivars in a replicated design. Each greenhouse had heating and a cyber–physical system that sensed ambient air temperature and automatically increased night air temperature to about 4°C relative to ambient temperature in the field for two cropping seasons. The system successfully imposed HNT stress of 4.0 and 3.94°C as recorded by Raspberry Pi sensors for 2 weeks in 2019 and 2020, respectively. HOBO sensors (Onset Computer Corporation) recorded a 2.9 and 2.07°C temperature differential of ambient air between control and heated greenhouses in 2019 and 2020, respectively. These greenhouses were able to withstand constant flooding, heavy rains, strong winds (140 mph), and thunderstorms. Selected US rice cultivars showed an average of 24% and 15% yield reduction under HNT during the 2019 and 2020 cropping seasons, respectively. Our study highlights the potential of this computer‐based infrastructure for accurate implementation of HNT or other abiotic stresses under field‐growing conditions.

Application of Neural Network Modeling in Problems of Predicting the Level of River Floods

The purpose of this article is to consider the theoretical and practical issues of developing neural network models for river flood forecasting (in case of the Belaya River near Ufa), as well as to implement the corresponding neural network in Python. To build a training sample, archival data from meteorological services and meteorological observation sites for the flood periods of the Belaya (Agidel) River in 2018–2022 were used. The following indicators were collected and analyzed: water level, water temperature, day and night air temperature, precipitation, snow depth, including information about the pre-flood condition of the snow cover. The software implementation of the neural network was performed using the PyTorch deep learning library; in addition, modules from the Matplotlib and Pandas libraries were used. The stability of the operation of this neural network was studied when the following parameters were changed: the optimizers used (Adam, Adamax and Rprop); learning rate coefficient; the number of neurons in the hidden layer; number of learning epochs. It is concluded that the developed neural network can be used to model the flood level when creating short-term forecasts. In order to move to longer-term forecasts in the future, it is planned to further expand the size of the factors in the training sample.

Анализ последствий изменения климата для управления климатическими рисками на железнодорожном транспорте

Purpose: Meta-analysis of the consequences of climate change for climate risk management in railway transportation. Methods: Analysis the consequences of climate change, based on an array of statistical data for the period from 1990 to 2019, thermal risks for railway infrastructure facilities have been identified. Results: It has been shown that the degree of heating of railway infrastructure objects can vary significantly depending on the specific location and type of object. The causes of failures associated with thermal risks on the railway network have been identified: most of the incidents associated with the heat occur during the period from the beginning to the middle of summer. There is a significant vulnerability of equipment to heat. A wide range of equipment fails due to heating at ambient temperatures within the operating range, as well as within the climatic norms of the given region. Practical significance: Ways to increase the stability of transport infrastructure and adaptation to climate change have been formulated. It is shown that climate change increases the likelihood of natural disasters and dangerous natural processes that can initiate emergency situations in transportation. The growth of annual extremums of air temperature is predicted in most of Russia. In this case, an increase in the number of days with abnormally high values of air temperature and a decrease in the number of days with extremely low night air temperatures is expected. The assessment shows that in some cases, the factors of climatic risk may not be dangerous natural phenomena themselves, but the dangerous technogenic events created by them.

Processing algorithm of weekly records of the Roztochia landscape-geophysical station thermograph М-16АН as a response source of air temperature data

Formulation of the problem. During the database processing of the Roztochia landscape-geophysical station (RLGS), located in the village of Bryukhovychi, Lviv, an air temperature data gap for 1990–1991 was found. The task of the research was to find those sources about air temperature at RLGS, which would allow us to fill in the gaps during the night hours when, unfortunately, observers did not make measurements. Problems of further research. In comparison with the method adopted in Ukraine for processing weekly thermograph tapes, in this study, it is proposed to correct the air temperature value during their processing, compensating for accelerated or slowed rotation of the weekly thermograph drum. It is suggested to use only those dry bulb measurements carried out on days with cloudy or rainy weather. The purpose. The main goal was to find an algorithm for processing weekly thermograph tapes under the conditions of a partial absence of temperature measurements using a dry thermometer by an observer to fill in the gaps regarding night air temperature data. Research methods. The air temperature values falling during the measurement period were read from the thermograph tapes, and an electronic table was formed. The temperature values (difference estimation) were compared with the corresponding ones recorded in the "Books" of KM-1. At the same time, it was necessary to make two new corrections. The first correction will be made along the ordinate axis, changing the value of the temperature recorded by the thermograph compared to the values of the temperature measured by the dry thermometer. The second correction was made along the abscissa axis, compensating for the drum's slowed down or accelerated rotation. Presentation of the main research material. A brief description of the proposed algorithm for thermograph tape processing is as follows. In the spreadsheet, in separate columns, we record the temperature values during the observation periods: a) by dry thermometer and b) by thermograph at the points corresponding to the observation periods. Subtracting columns (a) and (b) values, we determine those dry bulb temperature values suitable for calculating corrections. We reject too significant differences that occur during rapid temperature changes. Next, we look for points on the thermograph tape that serve as time benchmarks (the starting and ending points of the temperature curve and the places where the observer draws vertical lines). These temperature values will form column (c). It will additionally include the temperature values obtained by reading the temperature from the tape for rainy and/or overcast days for points whose localization is corrected for time. The difference between column (a) and column (c) will give the temperature correction for several observation periods on each weekly strip taken separately. The last step is the linear interpolation of temperature corrections between neighbouring points of intermediate observation periods. Practical value. The proposed algorithm may help eliminate gaps in temperature data at other observation points, where the thermograph served as a backup device for recording air temperature. Research results. The measurements that fall on rainy and overcast weather are best suited for calculating thermograph corrections when air temperature changes slow down. It is necessary to identify benchmark points of time fixation, to which the observer must add the moments of putting on and removing the tape from the drum.

A simple method for the estimation of minimum and maximum air temperature monthly mean maps using MODIS images in the region of Murcia, Spain

Air temperature records are acquired by networks of weather stations which may be several kilometres apart. In complex topographies the representativeness of a meteorological station may be diminished in relation to a flatter valley, and the nearest station may have no relation to a place located near it. The present study shows a simple method to estimate the spatial distribution of minimum and maximum air temperatures from MODIS land surface temperature (LST) and normalized difference vegetation index (NDVI) images. Indeed, there is a strong correlation between MODIS day and night LST products and air temperature records from meteorological stations, which is obtained by using geographically weighted regression equations, and reliable results are found. Then, the results allow to spatially interpolate the coefficients of the local regressions using altitude and NDVI as descriptor variables, to obtain maps of the whole region for minimum and maximum air temperature. Most of the meteorological stations show air temperature estimates that do not have significant differences compared to the measured values. The results showed that the regression coefficients for the selected locations are strong for the correlations between minimum temperature with LSTnight (R2 = 0.69–0.82) and maximum temperature with LSTday (R2 = 0.70–0.87) at the 47 stations. The root mean square errors (RMSE) of the statistical models are 1.0 °C and 0.8 °C for night and daytime temperatures, respectively. Furthermore, the association between each pair of data is significant at the 95% level (p<0.01).

Supplemental light with different blue and red ratios in the physiology, yield and quality of Impatiens

• LED 83R:17B increased the cuttings number per Impatiens plant in winter by 35.4%. • Anthocyanin content in Impatiens leaves did not increase with the use of LED. • Impatiens mother plants did not show oxidative stress with LED use and keep quality. • The 83R:17B LED reduced plugs height Impatiens White by 21.3%, even after light off. • The 67R:33B and 83R:17B LEDs, increased average 41.0% trichomes number on leaves. The yield of many ornamental plant species decreases sharply in the fall and winter seasons due to the decrease in solar radiation and temperature. The aim of this study was to verify the response of two Impatiens hybrid hort cultivars Sunpatiens Compact Royal Magenta and Sunpatiens Compact White to LED supplemental light with different ratios of red and blue: 83% red (640-660 nm): 17% blue (460-470 nm), 75% red (640-660 nm): 25% blue (460-470 nm), 67% red (640-660 nm): 33% blue (460-470 nm), and 50% red (640-660 nm): 25% red (620-630 nm): 25% blue (460-470 nm); and control (only natural light). Plants were grown in a nursery greenhouse at Atibaia, SP, Brazil, with day and night air temperature of 28°C and 21°C, respectively. Mother plants were grown with a spacing of 12 cm x 14 cm in plastic boxes (36 cm width x 56 cm length x 14 cm height) with 50% vermiculite and 50% perlite. Lights were placed at 1 m distance from the plants base, emitting a PPFD of 150 µmol m −2 s −1 . The daily supplemental light for 12 hours (6 am to 6 pm) began after mother plants transplant and was maintained for seven months until the end of the experiment. The yield and quality of both mother plants and cuttings collected from them, as well as of the plugs developed after three weeks were evaluated regarding to biometric characteristics, pigments, antioxidant enzymes, stress indicators, photosynthetic activity and trichomes counting. Impatiens response varied according to the growing season. In the winter season, at 202 DAT, the 83R:17B LED light increased in 35.4% the number of cuttings produced per plant compared to the control. The light supplementation with different spectral proportions did not cause oxidative stress of the Impatiens mother plants, maintaining its quality. The performance of Royal Magenta cv. differed from the White cv. regarding to the use of artificial lighting, mainly due to the higher concentration of anthocyanin in leaves of the Royal Magenta cv. The supplemental light effect during the cuttings production of the White cv. continued until the final phase of the plugs production, due to more compact cuttings produced in the 83R:17B LED light treatment.

Performance analysis of the urban climate model MUKLIMO_3 for three extreme heatwave events in Bern

Extreme heatwaves represent a health hazard that is expected to increase in the future, and which particularly affects urban populations worldwide due to intensification by urban heat islands. To analyze the impact of such extreme heatwaves on urban areas, urban climate models are a valuable tool. This study examines the performance of the urban climate model MUKLIMO_3 in modelling spatial air temperature patterns in the greater urban area of Bern, Switzerland, a city in complex topography, during three distinct extreme heatwaves in 2018 and 2019 over a total of 23 days. The model is validated using low-cost air temperature data from 79 (2018) and 84 (2019) measurement sites. The intercomparison of the three extreme heatwaves shows that during the first extreme heatwave 2019 at lower elevation regions in the outskirts of the city, modelled air temperature was higher than observation, which was likely due to pronounced mesoscale cold air advection. During calm and dry days, the air temperature distribution was modelled realistically over all three extreme heatwaves investigated. During daytime, modelled air temperatures were lower across all evaluation sites and all extreme heatwaves when compared to the measured values, with highest median air temperature differences of −3.7 K to −4.8 K found in the late afternoon. At night, MUKLIMO_3 generally shows a slowed cooling, so that higher air temperatures were modelled when compared to measured values, with median air temperature biases of +1.5 K to +2.8 K at midnight. By sunrise, the model biases continuously decreased, so that the lowest air temperatures at 7 a.m. were modelled with a bias of +0.2 K to +0.7 K. Peak biases exceed 7 K both during day and night. In sum, our results show that MUKLIMO_3 allows to realistically model the urban air temperature distributions during the peaks of the heatwaves investigated with the highest day and night air temperatures, which may assist in the development of heat mitigation measures to reduce the impacts of heat extremes and improve public health in cities with complex topography.

Effect of meteorological factors on the radial growth of pine latewood in northern taiga

Abstract The purpose of this study is to evaluate the influence of day and night meteorological parameters (air temperatures and dew points, relative humidity, wind speed and precipitation) on the radial growth of pine latewood in northern taiga, in typical conditions of its growth. The study was conducted in the north of the Arkhangelsk region (Russia). A total of 63 cores were selected from seven most representative sites. Meteorological parameters were obtained from the WMR 918 H digital weather station (Huger GmbH, Germany), located directly on the study area and operating in monitoring mode. The analysis used meteorological data for the period 2008–2015. Correlation with night and day air temperature in June and July (0.72–0.77) was revealed in blueberry type. In all the stands studied, a reliable correlation with wind speed was established, direct (0.77–0.88) and inverse (−0.7 to −0.99), but each sample plot had an individual dependence. A reliable correlation with the humidity of August and September (0.64–0.87) and an inverse correlation with precipitation in May and August (−0.63 to −0.75) were established. In general, pine in blueberry, cowberry and pine on swamp types have a similar reaction to the variability of meteorological factors, the most important of which is the temperature regime of air and wind speed.

Factors Influencing Changes of the Initial Stable Water Isotopes Composition in the Seasonal Snowpack of the South of Western Siberia, Russia

Stable water isotopes in snowpack and snowfalls are widely used for understanding hydrological processes occurring in the seasonally snow-covered territories. The present study examines the main factors influencing changes of the initial stable water isotopes composition in the seasonal snow cover of the south of Western Siberia. Studies of the isotopic composition of snow precipitation and snow cover, as well as experiments with them, were carried out during two cold seasons of 2019–2021, and laser spectroscopy PICARRO L2130-i (WS-CRDS) was used for the determination of water isotope composition (δ18O and δD). The main changes in the isotopic composition of the snow cover layers in the studied region are associated with the existence of a vertical temperature gradient between the layers and with the penetration of soil moisture into the bottom layers in the absence of soil freezing. During the winter period, the sublimation from the top layer of snow is observed only at the moments of a sharp increase in the daily air temperature. At the end of winter, the contrast between day and night air temperatures determines the direction of the shift in the isotopic composition of the top layer of snow relative to the initial snow precipitation.

MODELING OF PHENOTYPIC PRODUCTIVITY OF COWS DEPENDING ON PARATYPIC FACTORS

The results of the regression analysis of the influence of phenotypic factors on the milk productivity of cows and milk quality are presented. Reliable values of the regression coefficients of the second degree for the lactation month and lactation number indicate a non-linear relationship between these model indicators and milk yield. The value of the regression coefficient for day length indicates a positive effect of this indicator on daily hopes. The high daily air temperature had a negative impact on the milk production of cows. The negative value of the regression coefficient for the length of daylight hours is associated with a negative relationship between fat content and daily milk yield (0.225). This is also the reason for the opposite direction of the regression relationship between the fat content and the lactation month. A negative coefficient for the “daytime temperature” factor indicates that high critical air temperatures have a negative impact on both daily expectations and the fat content in milk. The negative value of the regression coefficient for the length of daylight hours is associated with a negative relationship between protein content and milk yield (0.305). This is also the reason for the opposite direction of the regression relationship of the protein content with the lactation month. A negative coefficient for daily air temperature indicates that high critical air temperatures negatively affect both daily milk yield and protein content in milk. The absence of a regression relationship between the age of the cow and the protein content in milk indicates a greater genetic dependence of this phenotypic indicator. The obtained regression coefficients indicate an increase in the somatic cells count in the milk of cows with age and month of lactation. Daylight hours and night air temperature have a negative relationship with the somatic cells count in the daily milk yield of cows. High daytime air temperature increases the somatic cells count in milk.

Study of Atomic Oxygen Airglow Intensities and Air Temperature near Mesopause Obtained by Ground-Based and Satellite Instruments above Baikal Natural Territory

The research studied the comparison of the night air temperatures and the atomic oxygen airglow intensities at the mesopause obtained with satellite and ground-based instruments. Satellite data used in this study were obtained with the SABER limb-scanning radiometer operating aboard the TIMED satellite. Data of ground-based monitoring were obtained using the KEO Scientific “Arinae” Fabry–Pérot interferometer adapted for aeronomic research. Since an interferometer detects parameters of the 557.7 nm line for the entire emission layer, it is not quite appropriate to perform a direct comparison between the upper atmospheric temperature obtained from ground-based observations and that from a satellite at a particular height. To compare temperatures correctly, the effective temperature must be calculated based on satellite data. The effective temperature is a height-averaged temperature profile with the weight factors equal to the 557.7 nm line intensity at relevant heights. The height profile of intensity of this natural green airglow of the upper atmosphere is calculated from the height profile of atomic oxygen concentration. Data on chemical composition and air temperature at the mesopause from SABER were used to calculate the profiles. The night intensity of the 557.7 nm emission obtained from satellite data in this way was in good accordance with the results of ground-based observations, but the temperatures were different. The reason for temperature discrepancy was assumed to lie in the incorrect position of the intensity maximum of the reconstructed emission layer. According to our calculations based on SABER data, the intensity peak was observed at the height of 94–95 km. By shifting it relative to the SABER temperature height profile, we re-calculated the effective temperatures and compared them with the interferometer data. The best coincidence between seasonal temperature variations obtained using the proposed method was achieved when the maximum of the reconstructed 557.7 nm intensity height profile was shifted to 97 km, but it could not eliminate minor local differences in temperature behavior.

Downscaled night air temperatures between 2030 and 2070: The case of cities with a complex- and heterogeneous-topography

Global and regional climate models tend to underestimate temperatures over urban areas. This limitation is exacerbated in complex-topography regions, where coarse spatial resolutions of climate models fail to detect large apparent change in cities' microclimates. In this study, a night air temperature downscaling approach was proposed in cities with heterogeneous- and complex-topography. It was developed based on six ground-based national weather station datasets along the 1-km remote-sensing-based MODIS land surface temperature (LST) data, between 2000 and 2020. An ordinary least square (OLS) statistical test was applied, including the 1-km MODIS normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), evapotranspiration (ET) and the digital elevation model (DEM) datasets as independent variables. Based on the generated regression relationship and a five-year pixel-based trend analysis, the 25-km NASA NEX-GDDP datasets were downscaled into 1-km spatial resolution night air temperatures between 2030 and 2072 and under two scenarios (i.e. RCP 4.5 and 8.5), averaged from 21 CMIP5 models. Validations were carried out showing good results with an RMSE of 0.49 °C, an AME of 0.42 °C and an R-squared value of 89.5%.Further assessment was made over the largest cities in Lebanon, namely Beirut, Tripoli, Zahle and Baalbeck. Main results showed that, on average, urban night air temperatures under the intermediate RCP 4.5 scenario are expected to increase by 0.12 °C or 0.61% in 2030, 0.36 °C or 1.82% in 2050 and 0.6 °C or 3.07% in 2070. Under the worst-case climate change RCP 8.5 scenario, the average increase would be an overwhelming 7.41 °C or 38.4% by 2070. City and policy makers are invited to implement the proposed straightforward and validated downscaling approach and to use the findings for a more responsive urban planning and design to the particular environemntal and geographic conditions; this isespecially required in cities and agglomorations dominated by complex- and heterogeneous-topographic characteristics.

Microclimatic Warming Leads to a Decrease in Species and Growth Form Diversity: Insights From a Tropical Alpine Grassland

Due to warming, changes in microclimatic temperatures have shifted plant community structure and dynamics in tundra and alpine regions. The directionality and magnitude of these changes are less known for tropical alpine ecosystems. To understand the likely trajectory of these shifts in the Andes, we conducted a warming experiment in the northern Andes—using open-top chambers (OTC). In this study, we ask (1) how do OTCs affect air and soil temperatures in microclimates of tropical alpine regions, year-round and during the dry season? (2) What are the effects of 7 years of warming on (a) the aboveground biomass (AGB) and (b) the plant taxonomic and growth form diversity? We installed five monitoring blocks in 2012 at ca. 4,200 m asl with 20 OTCs and 50 control plots randomly distributed within each block. We measured AGB, plant community diversity, and growth form diversity between 2014 and 2019. After 7 years of warming, we found significant increases in mean monthly (+0.24°C), daily (+0.16°C), and night air temperatures (+0.33°C) inside the OTCs, and the OTCs intensified microclimatic conditions during the dry season. Additionally, OTCs attenuated extreme temperatures—particularly in the soil—and the number of freezing events. AGB significantly increased in OTCs, and by 2019, it was 27% higher in OTCs than in control. These changes were driven mainly by a progressive increment of tussock grasses such as Calamagrostis intermedia, typical of lower elevations. The increase of tussocks led to a significant decrease in species diversity and evenness inside OTCs, but not in species richness after accounting by sampling time. Furthermore, cushions and herbs decreased inside OTCs. Our results show that experimental warming using OTCs in equatorial regions leads to decreased daily thermal amplitude and night temperatures rather than the level of increase in mean temperatures observed in temperate regions. The increase of tussocks and decrease in diversity of species and growth forms due to prolonged modifications in microclimatic temperature might be a step toward shrub-dominated ecosystems. Further research on this topic would help understand shifts in growth form dominance and the direction and rate of change of the system.

Keanekaragaman Jenis Serangga di Berbagai Lahan Pertanian Kelurahan Maubeli Kabupaten Timor Tengah Utara

The presence of insects in an ecosystem varies widely, the diversity of insects in various agricultural lands can act as polydonature insects, pests, parasites, and predators for other insects. Referring to the role of insects, this study aims to determine what insects are present in various agricultural lands, to analyze insect diversity and to analyze environmental factors that influence the presence of insects. This research was conducted in Maubeli Village, North Central Timor Regency in July-August 2020. The sampling technique was carried out with pitfall traps, light traps and sweep nets, the data obtained were analyzed using the Shannon-Wiener diversity index. The research that has been carried out has found insects at the research location consisting of the families of Acrididae, Coccinelidae, Libellulidae, Mantidae, Nymphalidae, Papiolinidae, Pieridae, and Tettigonidae. The highest diversity of 11 families was found with the highest value H` = 1.34 and the lowest H` = 0.26. The results of measurement of environmental parameters at the research location show that morning, evening and night air temperatures range from 260C-280C, 270C-310C, 250C-360C, and humidity ranges from 60% -70%, soil pH ranges from 6 and soil moisture ranges from 2%.

Day and Night Thermal Mass Performance Studies on Wetland Settlement in Palembang

The phenomenon of urban heat island was affected by the thermal mass of the area. The massive development of settlement in the wetland of Palembang had changed the natural thermal mass composition. This paper discussed the effect of the settlement development in the urban thermal environment of the wetland of Palembang. We measured the effect of building, pavement, water body and vegetation factors in the day and night air temperature of the settlement area. Direct field measurement was done using the wet and dry thermometer, anemometer and globe thermometer for 3x24 hours. The result showed that there were differences in day and night air temperature in the area with different thermal mass composition. It was also affected by wind direction and weather conditions. We concluded that the day and night temperature balance of the area could be control by the composition of thermal mass in the settlement area.

Significant Shift of Ambient Night-Time Air Temperature during Rice Growing Season in Major US Rice States

Heat stress studies in rice (Oryza sativa sp.) under extreme weather scenarios generally use constant temperatures to influence the crop responses without relation to actual weather changes. These heat stress studies may have limited implications for future crop yields because elevated temperatures are not based on local temperature fluctuations. This study investigated the night-time air temperature pattern and assessed the status and reliability of available weather station data in four major rice growing states; Arkansas (AR), California (CA), Louisiana (LA) and Texas (TX) using four public weather station databases. Hourly and daily night-time air temperatures from 20:00 to 06:00 were obtained from 1940 to 2018 during the rice growing period. During the 67-year period, a significant increase of 1.12°C and 0.53°C in seasonal night air temperature occurred in CA and AR (P ≤ 0.001) while LA and TX showed minimal to no increase in night air temperature. Across all rice states and years, night air temperature fluctuations ranged between ±0.2°C and ±4°C with the greatest occurred in CA (2.9°C) and AR (4.5°C). Mean night-time air temperature across all states ranged from 22.6°C to 29.5°C with a rate of increase of 0.01°C to 0.02°C per year since 1941. Due to a relatively smaller spatial dataset (from 1941-2018), trend analyses for AR, TX and LA showed modest bias with root mean square errors (RMSE) of 0.5°C to 1.1°C of absolute mean temperature across all locations. Results in this study showed seasonal night-time air temperature change occurred in some major US rice producing states during the last 67-years. This study highlights the need for more weather stations near agricultural farms to reliably derive actual temperature patterns in the rice growing regions.

Convective circulation influences horizontal movement by planktonic crustaceans in the littoral zone of a mesotrophic lake

Abstract Crustacean zooplankton perform diel vertical and horizontal migrations in lakes to avoid predators and/or exploit food resources more efficiently. Crustaceans may also move passively with convective flows that are generated by the nocturnal cooling of the surface water. Water in the shallow littoral zone cools faster than deeper pelagic waters. Therefore, bottom water moves from inshore to the pelagic zone while surface water moves in the opposite direction. The purpose of this study was to determine if crustaceans performed horizontal movements in the bottom and surface layers of a mesotrophic lake, Lake Obsterno in north‐west Belarus. We installed plankton nets horizontally in the bottom and surface layers of the lake at three sites located at different distances from the shore. We hypothesised that (1) if crustaceans performed diel horizontal migration, they would move in identical directions in the bottom and surface layers either from nearshore to open waters in the evening and back in the morning, or vice versa; (2) if crustaceans moved with convective flows, they would be carried to the shore in the surface layer and to the open waters in the bottom layers. Day and night air temperatures differed by more than 10°C over 24 hr. We assumed that the rates of convective currents were similar to those reported for other lakes exposed to a similar range of air temperatures. Rates of convective currents were also measured in Lake Obsterno and varied between 0.6–0.7 cm/s. These rates of convective currents were shown to exceed the cruise speed of planktonic crustaceans. The direction of movement of the most abundant taxa coincided with the direction of convective currents in more than 90% of the cases in the bottom layer and 70–80% of the cases in the surface layer. The abundance of invertebrate predators (mainly predatory cladocerans and boatmen (Hemiptera, Heteroptera) was negatively related to the abundance of crustaceans in the surface layer. Deviations in the distribution patterns of some crustacean species compared to distributions induced by convection currents in the upper layers may have been associated with the avoidance of invertebrate predators and/or predator grazing. Abundances of crustaceans were positively correlated between the sites located at different distances from the shore, and individual taxa were positively related to each other indicating that they moved in the same direction. Based on the fact that the directions of crustacean movements and convective currents mostly coincided, we concluded that convective currents passively carried the crustaceans. At low light intensities and low predation pressure (by visual fish predators), the direction of horizontal movement by zooplankton was mainly determined by convective circulation generated by cooling of the lake surface. Actively swimming planktonic invertebrate predators are likely to move in the same direction as herbivorous crustaceans. Therefore, predators could influence zooplankton distribution regulated by convective flows. We suggest that studies of horizontal migration and coupling between pelagic and littoral zones need to account for diurnal water currents in lakes.