Diurnal Temperature Amplitude Research Articles

Global critical soil moisture thresholds of plant water stress

During extensive periods without rain, known as dry-downs, decreasing soil moisture (SM) induces plant water stress at the point when it limits evapotranspiration, defining a critical SM threshold (θcrit). Better quantification of θcrit is needed for improving future projections of climate and water resources, food production, and ecosystem vulnerability. Here, we combine systematic satellite observations of the diurnal amplitude of land surface temperature (dLST) and SM during dry-downs, corroborated by in-situ data from flux towers, to generate the observation-based global map of θcrit. We find an average global θcrit of 0.19 m3/m3, varying from 0.12 m3/m3 in arid ecosystems to 0.26 m3/m3 in humid ecosystems. θcrit simulated by Earth System Models is overestimated in dry areas and underestimated in wet areas. The global observed pattern of θcrit reflects plant adaptation to soil available water and atmospheric demand. Using explainable machine learning, we show that aridity index, leaf area and soil texture are the most influential drivers. Moreover, we show that the annual fraction of days with water stress, when SM stays below θcrit, has increased in the past four decades. Our results have important implications for understanding the inception of water stress in models and identifying SM tipping points.

Elevated body temperature is associated with depressive symptoms: results from the TemPredict Study

Correlations between altered body temperature and depression have been reported in small samples; greater confidence in these associations would provide a rationale for further examining potential mechanisms of depression related to body temperature regulation. We sought to test the hypotheses that greater depression symptom severity is associated with (1) higher body temperature, (2) smaller differences between body temperature when awake versus asleep, and (3) lower diurnal body temperature amplitude. Data collected included both self-reported body temperature (using standard thermometers), wearable sensor-assessed distal body temperature (using an off-the-shelf wearable sensor that collected minute-level physiological data), and self-reported depressive symptoms from > 20,000 participants over the course of ~ 7 months as part of the TemPredict Study. Higher self-reported and wearable sensor-assessed body temperatures when awake were associated with greater depression symptom severity. Lower diurnal body temperature amplitude, computed using wearable sensor-assessed distal body temperature data, tended to be associated with greater depression symptom severity, though this association did not achieve statistical significance. These findings, drawn from a large sample, replicate and expand upon prior data pointing to body temperature alterations as potentially relevant factors in depression etiology and may hold implications for development of novel approaches to the treatment of major depressive disorder.

Earlier Flowering Phenology and Pollinator Visitation on Urban Green Roofs Compared to Ground-Level Gardens

Urban green space, green infrastructure, and horticultural installations are gaining recognition for their potential to foster biodiversity. Green roofs are challenging growing environments for plants, characterized by extreme substrate temperatures, high light intensity, limited moisture availability, and limited substrate depth. Plants have a variety of physiological responses to these unique conditions, but little is known about how green roof growing conditions affect ecological characteristics like plant flowering phenology. Meanwhile, studies are only just uncovering the degree to which green roofs can provide habitat and support urban pollinator biodiversity. We evaluated the flowering phenology and made in situ pollinator observations of 15 plant taxa growing both on green roof systems and at ground level in Denver, Colorado, over two growing seasons. We found that flowering phenology occurs substantially earlier on green roofs compared to ground level among the observed plant taxa and observed a greater number of pollinators on green roofs early in the season, compared to ground level, presumably due to the availability of floral resources among the observed plant taxa. We observed significantly higher substrate temperatures along with wider diurnal temperature amplitude during the growing season that may contribute to the observed phenological patterns. Divergence in flowering phenology between individual plants of the same species on green roofs and plants at ground-level may have implications for organisms that rely on floral resources in urban environments. Earlier flower initiation on green roofs may provide pollinators with unique foraging opportunities and aid targeted conservation where early-season floral resources are limited.

Mechanisms of non-stationary influence of urban form on the diurnal thermal environment based on machine learning and MGWR analysis

The non-stationary impact of urban form at block scale on the diurnal thermal environment has not been extensively studied. To fill the gap, a comprehensive multi-scale research framework was constructed, integrating machine learning algorithms and multiscale geographically weighted regression (MGWR) analysis. The urban form types were extracted by machine learning algorithms from 2282 blocks of Dalian, a coastal city, and the contribution to the diurnal land surface temperature (LST) was evaluated. Based on MGWR, the non-stationary effects of urban form, human activity and spatial location on the diurnal LST were quantified, which indicated the contributing factors to the diurnal thermal differences among the form types. The result was as follows: 1) Blocks characterized by low vegetation and mid/low-rise buildings had the highest warming contribution for diurnal LST. 2) The impact of sky view factor (SVF) on diurnal temperature amplitude exhibited no significant spatial-temporal heterogeneity. 3) Building density had a prominent effect on diurnal temperature amplitude. 4) High-vegetation and open (SVF > 0.5) mid/mid-high/low-rise (15–50 m) buildings were recommended. This study provides a more precise basis for policymakers to develop climate adaptation strategies throughout day and night, particularly for coastal cities.

Analysis of Diurnal Sea Surface Temperature Variability in the Tropical Indian Ocean

Based on the 30-year global hourly sea surface temperature (SST) dataset (MLSST) produced by the National Marine Environmental Forecasting Center, Ministry of Natural Resources of China, we analyzed the variability of diurnal sea surface temperature amplitude (DSST) of the tropical Indian Ocean at multiple time scales, as well as its influencing factors. The results show that the DSST in the Arabian Sea, Bay of Bengal, and equatorial Indian Ocean exhibits a bimodal seasonal variation with a semi-annual cycle, while the DSST in the southern Indian Ocean shows an annual cycle. The seasonal variation of DSST is mainly influenced by factors such as sea surface wind speed, shortwave solar radiation, and precipitation. The DSST in the equatorial Indian Ocean is generally higher during El Niño years compared to La Niña years. At the intraseasonal scale, the large standard deviation of DSST in boreal winter is mainly distributed in the southern hemisphere, while the large standard deviation of DSST in boreal summer shifts northward. The intraseasonal variation amplitude of DSST in boreal winter of the tropical Indian Ocean is greater than that in boreal summer. The DSST in the tropical Indian Ocean exhibits significant variation characteristics at multi-time scales. This study provides reference for numerical simulation of air-sea interaction patterns in the tropical Indian Ocean, as well as improvement of short-term climate prediction.

Adaptive tuning of uncertain parameters in a numerical weather prediction model based upon data assimilation

AbstractIn numerical weather prediction models, near‐surface quantities like 10‐m wind speed (FF10M) or 2‐m temperature (T2M) tend to exhibit significantly larger forecast errors than the related variables in the free troposphere. Besides representativeness issues of surface stations, this is primarily related to parametrization errors and insufficient knowledge of relevant physical properties of the soil and the surface layer. For instance, the vegetation roughness length is usually derived from land‐cover classifications that may contain errors and reflect only part of the natural variability. This article describes a methodology implemented into Deutscher Wetterdienst's operational numerical weather prediction model ICON in order to improve the estimate of such parameters by using information from the data assimilation system. Building upon the condition that FF10M, T2M, and 2‐m relative humidity are assimilated, time‐filtered assimilation increments are calculated for the respective fields at the lowest model level. These are taken as proxies for the related model biases. For T2M, an additional weighted increment field is computed that indicates the model bias in the diurnal temperature amplitude. Based on these increment fields, several physical parameter fields and a few model tuning parameters are varied around their base values. This adaptive parameter adjustment is used operationally in the global and regional forecasting systems of Deutscher Wetterdienst. The ensuing reduction of the FF10M, T2M, and 2‐m relative humidity errors typically lies on the order of 5% on a hemispheric average but has substantial regional and seasonal variability that depends on the original magnitude of the model error. A weaker but still statistically significant positive impact is seen in the radiosonde verification of wind speed, humidity, and temperature in the lower troposphere, giving confidence that the adaptive tuning indeed reduces model errors rather than pushing the model towards unrepresentative station observations.

Potential of remote sensing surface temperature- and evapotranspiration-based land-atmosphere coupling metrics for land surface model calibration

Imperfect land physics introduce significant levels of uncertainty into current land surface models (LSMs) and can cause bias in their representation of land-atmosphere coupling strength (ρ). When LSMs are coupled with atmospheric prediction models, such errors will eventually degrade the accuracy of lower atmosphere forecasts. Here, we investigate the potential of two remote sensing (RS)-based ρ references for addressing LSM ρ bias. To minimize meteorological uncertainty and maximally attribute LSM ρ bias to land sources, we focus specifically on off-line LSM calibration forced using high-quality, observation-based meteorological data. Both ρ references are based on a newly proposed two-system approach for eliminating the impact of random errors in RS retrievals and quantified using the temporal correlations of soil moisture (SM) versus both evapotranspiration (ET) and the diurnal amplitude of surface temperature (dT). Experiments are conducted to calibrate an off-line LSM individually against each resulting ρ reference and using a combination of both dT- and ET-represented ρ references. The resulting calibrated LSM is further evaluated using independent ground-based ET observations and RS dT retrievals. Results show that although dT- and ET-represented ρ references are physically consistent across space, model calibration results based on them are quite different. Specifically, the calibration experiment targeting ET-represented ρ outperforms that targeting dT-represented ρ in ET and dT modeling. Diagnostic results indicate that the failure of dT-based calibration experiments is due to the confounding impacts of transpiration/evapotranspiration partitioning error and large dT uncertainties in LSM. However, results also confirm the potential of both dT- and ET-represented ρ references for jointly diagnosing and understanding LSM ρ bias. As a result, we suggest diagnosing LSM ρ bias using both ET- and dT-represented ρ references – but calibrating LSM using only ET-represented ρ reference data.

Diurnal temperature amplitude affects diamondback moth adult and next‐generation traits

AbstractTemperature fluctuation is one of the most important factors in climate change, and research into its effects on organisms is increasing. Nonetheless, few studies have addressed its effects on insects and particularly on the parental generation. We therefore simulated temperature amplitudes (± 0, 4, 6, 8, 10°C) for a mean environmental temperature of 25°C and studied their immediate and maternal effects on a global pest, the diamondback moth Plutella xylostella (Lepidoptera: Plutellidae), focusing on adult longevity and fecundity and egg development and survivorship in the next generation. Relative to constant temperature, moderate amplitudes (4 and 6°C) did not affect the adults, whereas 8 and 10°C amplitudes hindered adult longevity and fecundity, but significantly increased the proportional of early fecundity after each treatment. Temperature amplitude 10°C inhibited development of Day 2 and Day 3 laid eggs. These findings show that temperature amplitude affects both the maternal and offspring phenotype and indicate that the influence of temperature amplitude on diamondback moth population models requires further research.

Observed Landscape Responsiveness to Climate Forcing

AbstractClimate variability and change shift environmental conditions on global land surfaces, creating uncertainties in predicting hydrologic flows, crop yields, and land carbon uptake. Land surfaces can present varying degrees of inertia to atmospheric forcing variability (e.g., precipitation). This study asks: are regions with the most variable environmental forcing necessarily the regions with the largest land surface variability? Specifically, it seeks to determine why land surfaces show varying responsiveness to environmental forcing. The degree to which and the mechanisms for how landscapes modulate the forcing are evaluated using a decade‐long satellite observation record of Africa's diverse climates. Surface responsiveness is quantified using intra‐seasonal energy flux variability, based on the observed diurnal temperature amplitude. We map the responsiveness and analyze the underlying mechanisms over intra‐seasonal timescales (especially interstorms). We show that, at a location, land surface responsiveness is dependent on the soil moisture distribution and the nonlinear relationship between energy fluxes and soil moisture. Land surfaces with greater responsiveness to climate are those with soil moisture distributions that span the threshold between evaporation regimes and spend most of their time in the water‐limited regime. Consequently, surface responsiveness mechanisms drive land surface variability beyond high climatic variability. Since we find these results to hold from intra‐seasonal to interannual timescales, we expect that these responsive regions will be most vulnerable to long‐term shifts in climate forcing. The quantification of these phenomena and determination of their geographic distributions based on observations can help assess land surface models used to evaluate hydrologic consequences of climate change.

Night-Restricted Feeding Improves Gut Health by Synchronizing Microbe-Driven Serotonin Rhythm and Eating Activity-Driven Body Temperature Oscillations in Growing Rabbits.

The circadian misalignment of the gut microbiota caused by unusual eating times in adult animals is related to disease development. However, whether the composition and diurnal rhythm of gut microbiota can be optimized by synchronizing the window period of eating with natural eating habits to reduce the risk of diarrhea remains unclear, especially in growing animals. In this study, 108 5-week-old weaned rabbits (nocturnal animals) were randomly subjected to daytime feeding (DF) and night-restricted feeding (NRF). At age 12 weeks, six rabbits were selected from each group, and caecum and cecal contents, as well as serum samples were collected at 4-h intervals during 24 h. Overall, NRF was found to reduce the risk of diarrhea in growing rabbits, improved the diurnal rhythm and abundance of beneficial microorganisms, along with the production of beneficial metabolites, whereas reduced the abundance of potential pathogens (Synergistes, Desulfovibrio, and Alistipes). Moreover, NRF improved diurnal rhythm of tryptophan hydroxylase isoform 1 and serotonin. Furthermore, NRF strengthened the diurnal amplitude of body core temperature, and promoted the diurnal expression of intestinal clock genes (BMAL1, CLOCK, REV-ERBα, and PER1), and genes related to the regulation of the intestinal barrier (CLAUDIN-1), and intestinal epithelial cell self-proliferation and renewal (BMI1). In vitro simulation experiments further revealed that synchronization of microbial-driven serotonin rhythm and eating activity-driven body temperature oscillations, which are important zeitgebers, could promote the diurnal expression of clock genes and CLAUDIN-1 in rabbit intestinal epithelial cells (RIEC), and enhance RIEC proliferation. This is the first study to reveal that NRF reprograms the diurnal rhythm of the gut microbiome, promotes the diurnal expression of clock genes and tight junction genes via synchronization of microbial-driven serotonin rhythm and eating activity-driven body temperature oscillations, thereby improving intestinal health and reducing the risk of diarrhea in growing rabbits. Collectively, these results provide a new perspective for the healthy feeding and management of growing animals.

Frost‐driven lower treelines in Angola and their implications for tropical forest–grassland mosaics

AbstractQuestionsForest–grassland boundaries in the tropics are primarily interpreted as driven by fire and herbivory. So far, frost has received little attention as driver of tropical vegetation boundaries. Here, we study mid‐altitudes in south‐central Africa and ask the following questions: (a) is there a lower treeline between grasslands and forests on the Angolan Plateau; (b) if so, do topoclimatic differences play a role in it; and (c) what do our results imply for tropical highlands globally?LocationThe Angolan Plateau (10°–16°S and 13°–21° E).MethodsWe mapped vegetation by applying a supervised support vector machine‐based classification on a Landsat satellite image. We used a 1,000‐m spaced point grid to extract the mean vertical distribution of the vegetation units from a digital elevation model. The topographic position of each point was calculated using a channel network approach. Microclimatic data were collected across topographic gradients at two sites along the Plateau. Analyses focussed on the number of nights where temperature dropped below 0℃, median and minimum temperatures, and diurnal temperature ranges.ResultsLower treelines separate Miombo forests from geoxyle grasslands in all major valley systems. Treelines are located 150–200 m below the headwater divides. Nocturnal outgoing net long‐wave radiation and resulting cold‐air pooling cause frequent frosts in the valleys during the dry season. Topography controls frost patterns, with minima of down to −7.5℃ and diurnal temperature amplitudes up to 40℃.ConclusionsThe results show that vegetation patterns in central Angola are shaped by frost. The processes causing frost depend on air humidity. Drier atmosphere and lower global temperatures indicate a longer frost season, lower minima and frost extending to lower elevations and latitudes for the Pleistocene. Pleistocene forest fragmentations and the rise of endemism‐rich grasslands in comparable tropical highlands worldwide may be explained by crossing thermic thresholds via increasing seasonal aridity.

Within- and Trans-Generational Life History Responses to Diurnal Temperature Amplitudes of the Pupal Stage in the Diamondback Moth

Diurnal temperature fluctuations in nature can have a significant effect on many ectodermic traits. However, studies on the effects of diurnal temperature fluctuations on organisms, especially the effects on specific life stages, are still limited. We examined the immediate effects of the same average temperature (25°C) and different temperature amplitudes (±4, ±6, ±8, ±10, ±12°C) on the development and survival of Plutella xylostella (Lepidoptera: Plutellidae). We also assessed carry-over effects on adult longevity, reproduction, development, and survival of offspring across generations. The effect of moderate temperature amplitudes was similar to that of constant temperature. Wide temperature amplitudes inhibited the development of pupae, reduced total reproduction, lowered intrinsic rates of population growth, and slowed the development and survival of eggs on the first day, but the proportion of females ovipositing on the first three days increased. Insects coped with the adverse effects of wide temperature amplitudes by laying eggs as soon as possible. Our results confirmed that a logistic model based on daily average temperature cannot predict development rates under wide temperature amplitudes. These findings highlight the effect of environmental temperature fluctuations at the pupal stage on the development and oviposition patterns of P. xylostella and should be fully considered when predicting field occurrence.

Small Island Effects in DYNAMO and Their Impact on Large-Scale Budget Analyses

AbstractDuring the Dynamics of the MJO (DYNAMO) field campaign, radiosonde launches were regularly conducted from three small islands/atolls (Malé and Gan, Maldives, and Diego Garcia, British Indian Ocean Territory) as part of a large-scale sounding network. Comparison of island upsondes with nearby and near-contemporaneous dropsondes over the ocean provides evidence for the magnitude and scope of the islands’ influence on the surrounding atmosphere and on the island upsonde profiles. The island’s impact on the upsonde data is most prominent in the lowest 200 m. Noting that the vertical gradients of temperature, moisture, and winds over the ocean are generally constant in the lowest 0.5 km of dropsondes, a simple procedure was constructed to adjust the upsonde profiles in the lowest few hundred meters to resemble the atmospheric structures over the open ocean. This procedure was applied to the soundings from the three islands mentioned above for the October–December 2011 period of DYNAMO. As a result of this procedure, the adjusted diurnal cycle amplitude of surface temperature is reduced fivefold, resembling that over the ocean, and low-level wind speeds are increased in ~90% of the island soundings. Examination of the impact of these sounding adjustments shows that dynamical and budget fields are primarily affected by adjustments to the wind field, whereas convective parameters are sensitive to the adjustments in thermodynamic fields. Although the impact of the adjustments is generally small (on the order of a few percent), intraseasonal wind regime changes result in some systematic variations in divergence and vertical motion over the sounding arrays.

Wide Diurnal Temperature Amplitude and High Population Density Can Positively Affect the Life History of Sitobion avenae (Hemiptera: Aphididae).

Diurnal temperature amplitude is known to have a large influence on insect life history. Population density affects intraspecific competition and many other aspects of insect life history. However, there is limited information on the interactive effects of these factors on insects. Here, we tested the interactive effects of three diurnal temperature amplitudes (22 ± 0°C, 22 ± 6°C, and 22 ± 12°C) and three population densities on the development, survival, longevity, and fecundity of the English grain aphid Sitobion avenae (Fabricius) (Homoptera: Aphididae). At a constant temperature, increasing population density reduced the growth and survival of early-instar nymphs, increased longevity, and reduced fecundity. At a low population density, increasing temperature amplitude inhibited nymph development. However, even at a high temperature amplitude, nymph survival rate was higher than expected, and reproduction was possible because the recovery of the lower night-temperatures eliminated thermal stress. Increasing the population density reduced, and even reversed, the negative effects of the wide temperature amplitude. This may reflect synergistic interactions between population density and wide temperature amplitude as these stressors each incur energetic costs. These findings emphasize the importance of temperature amplitude and population density for improving prediction accuracy and damage assessment during pest control modeling.

Modeled Response of South American Climate to Three Decades of Deforestation

AbstractThis study investigates the potential effects of historical deforestation in South America using a regional climate model driven with reanalysis data. Two different sources of data were used to quantify deforestation during the 1980s to 2010s, leading to two scenarios of forest loss: smaller but spatially continuous in scenario 1 and larger but spatially scattered in scenario 2. The model simulates a generally warmer and drier local climate following deforestation. Vegetation canopy becomes warmer due to reduced canopy evapotranspiration, and ground becomes warmer due to more radiation reaching the ground. The warming signal for surface air is weaker than for ground and vegetation, likely due to reduced surface roughness suppressing the sensible heat flux. For surface air over deforested areas, the warming signal is stronger for the nighttime minimum temperature and weaker or even becomes a cooling signal for the daytime maximum temperature, due to the strong radiative effects of albedo at midday, which reduces the diurnal amplitude of temperature. The drying signals over deforested areas include lower atmospheric humidity, less precipitation, and drier soil. The model identifies the La Plata basin as a region remotely influenced by deforestation, where a simulated increase of precipitation leads to wetter soil, higher ET, and a strong surface cooling. Over both deforested and remote areas, the deforestation-induced surface climate changes are much stronger in scenario 2 than scenario 1; coarse-resolution data and models (such as in scenario 1) cannot represent the detailed spatial structure of deforestation and underestimate its impact on local and regional climates.

Land‐Atmosphere Drivers of Landscape‐Scale Plant Water Content Loss

AbstractPlant water content observations using microwave remote sensing measurements allow monitoring of landscape‐scale plant water stress. During soil drying following rainfall events, we use a Granger causality framework to quantify the degree to which environmental factors drive satellite‐based plant water content loss across Africa's diverse biomes. After soil drying into the water‐limited regime, satellite observations show that plants dry while solar radiation, vapor pressure deficit, and diurnal temperature amplitude increase. We find that soil drying primarily drives plant water content loss across African drylands, though with regional effects of diurnal temperature amplitude increases (found to indicate vapor pressure deficit increases here). We also detect interactions between these factors that reinforce plant drying during periods of soil moisture loss. Our results provide observational evidence across Africa that individual and interactive components of surface drying and heating can all drive plant water stress, especially during intermittent poststorm drying periods.

Alternating wide ridges and narrow furrows with film mulching improves soil hydrothermal conditions and maize water use efficiency in dry sub-humid regions

The ridge-furrow mulching system (RFMS) is widely used to improve crop yields and water use efficiency in arid and semi-arid rainfed agricultural regions. However, the effects of RFMS on hydrothermal states and maize (Zea mays L.) yields in dry sub-humid regions remain unclear. The objective of this study was to determine the influence of ridge-furrow construction and plastic film mulching on soil moisture and temperature, evapotranspiration (ET), maize growth and yield, water use efficiency (WUE), and thermal time use efficiency (TUE) in dry sub-humid regions of the Loess Plateau. A three-year field study was conducted in which four different planting practices were evaluated: (1) alternating wide ridges and narrow furrows with film mulching (WRM), (2) alternating equal-width ridges and furrows with film mulching (ERM), (3) equal row spacing in flat plot with half film mulching (EFM), and (4) conventional flat plot without mulching (CK). The results demonstrated that at early maize growth stages, soil water storage within the 0–200 cm soil profile and soil temperatures were increased for mulching treatments compared with CK. RFMS utilized soil water efficiently by increasing rainwater harvesting efficiency and transpiration while decreasing soil evaporation. RFMS significantly increased soil temperature in the ridges by 4.0–4.4 °C and reduced diurnal soil temperature amplitude in the furrows, thereby increasing soil thermal time. These positive effects of RFMS compared with CK improved maize growth and crop yields because of adequate absorption and utilization of water and thermal resources. RFMS increased average maize yield by 24.9–32.8%, WUE by 34.1–45.7%, and TUE by 15.9–21.1%. The highest grain yield, WUE, and TUE were observed with WRM due to its favorable soil hydrothermal conditions. The WRM treatment is a promising water-saving and high-yielding maize cultivation practice to improve grain yields and resource use efficiency in dry sub-humid regions.

Variability of Diurnal Sea Surface Temperature during Short Term and High SST Event in the Western Equatorial Pacific as Revealed by Satellite Data

Near-surface diurnal warming is an important process in the climate system, driving exchanges of water vapor and heat between the ocean and the atmosphere. The occurrence of the hot event (HE) is associated with the high diurnal sea surface temperature amplitude (δSST), which is defined as the difference between daily maximum and minimum sea surface temperature (SST). However, previous studies still show some inconsistency for the area of HE occurrence and high δSST. The present study produces global δSST data based on the SST, sea surface wind data derived from microwave radiometers, and solar radiation data obtained from visible/infrared radiometers. The value of δSSTs are estimated and validated over tropical oceans and then used for investigating HE in the western equatorial Pacific. A three-way error analysis was conducted using in situ mooring buoy arrays and geostationary SST measurements by the Himawari-8 and Geostationary Operational Environmental Satellite (GOES). The standard deviation error of daily and 10-day validation is around 0.3 °C and 0.14–0.19 °C, respectively. Our case study in the western Pacific (from 110°E to 150°W) shows that the area of HE occurrence coincided well with the area of high δSST. Climatological analysis shows that the collocated area between high occurrence rate of HE and high δSST, which coincides with the western Pacific warm pool region in all seasons. Thus, this study provides more persuasive evidence of the relation between HE occurrence and high δSST.

The response of CO<sub>2</sub> fluxes to the amplitude of diurnal temperature in alpine meadow during growing season from 2002 to 2016 at the southern foot of Qilian Mountains

Known as the “Third Pole” and “Early-warning region” of the world, the Qinghai-Tibetan Plateau (QTP) had an intense increase in surface temperature and marked change in the amplitude of diurnal temperature (ADT), which could have significant influences on the ecosystem carbon cycle. The increasing rate of the mean daily minimum temperature (MinTa) was about two times higher than that of maximum temperature (MaxTa) in the last five decades, and this asymmetric pattern has resulted in a smaller ADT, which substantially affected the plant phenology and vegetation productivity. The reduction in the ADT caused by global climate change would have a profound impact on the carbon balance of alpine ecosystems. However, the response of carbon budgets to the ADT over the QTP remained unclear. Here, we analyzed the 15-a growing seasonal (June−September) carbon fluxes (measured by the eddy covariance [EC] technique) in alpine meadow at the southern foot of Qilian Mountains, which is one of the most extensive vegetation types on the QTP. This study aimed to clarify how carbon fluxes respond to ADT at different temporal (daily, monthly and annual) scales in alpine meadow and to understand their potential response to future climate change. The results indicated that both the MaxTa and MinTa showed bell-shaped seasonal patterns, whereas the ADT failed to show an obvious trend during the growing season from 2002 to 2016. Besides, there was a non-significant increase in annual MaxTa, MinTa and ADT ( P >0.05). Meanwhile, daily gross primary productivity (GPP) and ecosystem respiration (Re) exhibited a single-peaked trend that increased and then decreased, whereas daily net ecosystem CO2 exchange (NEE) showed a v-shaped trend. The alpine meadow ecosystem is a carbon sink during the growing season, and the annual NEE, GPP, and Re were −230.4±17.3, 668.8±25.5, 438.3±27.5 g C m–2, respectively. Moreover, the annual GPP and Re of alpine meadow in the growing season showed a significant increase trend ( P P >0.05). Annual CO2 fluxes were not related annual ADT. Only annual MaxTa exerted significant influence on variations in annual GPP and Re. Interestingly, the slopes of GPP and Re with respect to MaxTa were similar, also indicating the little impact of MaxTa on annual NEE. On a monthly scale, ADT exerted a negligible influence on CO2 fluxes ( P >0.05), but there were significant correlations between MinTa and MaxTa with CO2 fluxes. On a daily scale, there was a significant quadratic relationship between daily NEE and ADT during the whole growing season ( P P

Narrowing Diurnal Temperature Amplitude Alters Carbon Tradeoff and Reduces Growth in C4 Crop Sorghum.

Effect of diurnal temperature amplitude on carbon tradeoff (photosynthesis vs. respiration) and growth are not well documented in C4 crops, especially under changing temperatures of light (daytime) and dark (nighttime) phases in 24 h of a day. Fluctuations in daytime and nighttime temperatures due to climate change narrows diurnal temperature amplitude which can alter circadian rhythms in plant, thus influence the ability of plants to cope with temperature changes and cause contradictory responses in carbon tradeoff, particularly in night respiration during dark phase, and growth. Sorghum [Sorghum bicolor (L.) Moench] is a key C4 cereal crop grown in high temperature challenging agro-climatic regions. Hence, it is important to understand its response to diurnal temperature amplitude. This is the first systematic investigation using controlled environmental facility to monitor the response of sorghum to different diurnal temperature amplitudes with same mean temperature. Two sorghum hybrids (DK 53 and DK 28E) were grown under optimum (27°C) and high (35°C) mean temperatures with three different diurnal temperature amplitudes (2, 10, and 18°C) accomplished by modulating daytime and nighttime temperatures [optimum daytime and nighttime temperatures (ODNT): 28/26, 32/22, and 36/18°C and high daytime and nighttime temperatures (HDNT): 36/34, 40/30, and 44/26°C]. After exposure to different temperature conditions, total soluble sugars, starch, total leaf area and biomass were reduced, while night respiration and specific leaf area were increased with narrowing of diurnal temperature amplitude (18 to 2°C) of HDNT followed by ODNT. However, there was no influence on photosynthesis across different ODNT and HDNT. Contradiction in response of foliar gas exchange and growth suggests higher contribution of night respiration for maintenance rather than growth with narrowing of diurnal temperature amplitude of ODNT and HDNT. Results imply that diurnal temperature amplitude has immense impact on the carbon tradeoff and growth, regardless of hybrid variation. Hence, diurnal temperature amplitude and night respiration should be considered while quantifying response and screening for high temperature tolerance in sorghum genotypes and comprehensive understanding of dark phase mechanisms which are coupled with stress response can further strengthen screening procedures.