service brand loyalty, corporate associations, CSR, brand identification, service quality, customer satisfaction,

Increasing drought and extreme rainfall are major threats to maize production in the United States. However, compared to drought impact, the impact of excessive rainfall on crop yield remains unresolved. Here, we present observational evidence from crop yield and insurance data that excessive rainfall can reduce maize yield up to −34% (−17 ± 3% on average) in the United States relative to the expected yield from the long‐term trend, comparable to the up to −37% loss by extreme drought (−32 ± 2% on average) from 1981 to 2016. Drought consistently decreases maize yield due to water deficiency and concurrent heat, with greater yield loss for rainfed maize in wetter areas. Excessive rainfall can have either negative or positive impact on crop yield, and its sign varies regionally. Excessive rainfall decreases maize yield significantly in cooler areas in conjunction with poorly drained soils, and such yield loss gets exacerbated under the condition of high preseason soil water storage. Current process‐based crop models cannot capture the yield loss from excessive rainfall and overestimate yield under wet conditions. Our results highlight the need for improved understanding and modeling of the excessive rainfall impact on crop yield.

Forests are undergoing significant changes throughout the globe. These changes can modify water, energy, and carbon balance of the land surface, which can ultimately affect climate. We utilize satellite data to quantify the potential and actual impacts of forest change on land surface temperature (LST) from 2003 to 2013. The potential effect of forest change on temperature is calculated by the LST difference between forest and nearby nonforest land, whereas the actual impact on temperature is quantified by the LST trend difference between deforested (afforested) and nearby unchanged forest (nonforest land) over several years. The good agreement found between potential and actual impacts both at annual and seasonal levels indicates that forest change can have detectable impacts on surface temperature trends. That impact, however, is different for maximum and minimum temperatures. Overall, deforestation caused a significant warming up to 0.28 K/decade on average temperature trends in tropical regions, a cooling up to −0.55 K/decade in boreal regions, a weak impact in the northern temperate regions, and strong warming (up to 0.32 K/decade) in the southern temperate regions. Afforestation induced an opposite impact on temperature trends. The magnitude of the estimated temperature impacts depends on both the threshold and the data set (Moderate Resolution Imaging Spectroradiometer and Landsat) by which forest cover change is defined. Such a latitudinal pattern in temperature impact is mainly caused by the competing effects of albedo and evapotranspiration on temperature. The methodology developed here can be used to evaluate the temperature change induced by forest cover change around the globe.

Changes in vegetation activity are driven by multiple natural and anthropogenic factors, which can be reflected by Normalized Difference Vegetation Index (NDVI) derived from satellites. In this paper, NDVI trends from 1982 to 2012 are first estimated by the Theil-Sen median slope method to explore their spatial and temporal patterns. Then, the impact of climate variables and human activity on the observed NDVI trends is analyzed. Our results show that on average, NDVI increased by 0.46 × 10 1982-2004, 1995-2004, and 2005-2012, respectively. A positive partial correlation of NDVI and temperature is observed in the first period but it decreases and occasionally becomes negative in the following periods, especially in the Humid Temperate and Dry Domain Regions. This suggests a weakened effect of temperature on vegetation growth. Precipitation, on the other hand, is found to have a positive impact on the NDVI trend. This effect becomes stronger in the third period of 1995-2004, especially

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The learner's acceptance of e-learning systems has received extensive attention in prior studies, but how their experience of using e-learning systems impacts on their behavioural intention to reuse those systems has attracted limited research. As the applications of e-learning are still gaining momentum in developing countries, such as China, it is necessary to examine the relationships between e-learners' experience and perceptions and their behavioural intention to reuse, because it is argued that system reuse is an important indicator of the system's success. Therefore, a better understanding of the multiple factors affecting the e-learner's intention to reuse could help e-learning system researchers and providers to develop more effective and acceptable e-learning systems. Underpinned by the information system success model, technology acceptance model and self-efficacy theory, a theoretical framework was developed to investigate the learner's behavioural intention to reuse e-learning systems. A total of 280 e-learners were surveyed to validate the measurements and proposed research model. The results demonstrated that e-learning service quality, course quality, perceived usefulness, perceived ease of use and self-efficacy had direct effects on users' behavioural intention to reuse. System functionality and system response have an indirect effect, but system interactivity had no significant effect. Furthermore, self-efficacy affected perceived ease of use that positively influenced perceived usefulness.

Wind and solar farms offer a major pathway to clean, renewable energies. However, these farms would significantly change land surface properties, and, if sufficiently large, the farms may lead to unintended climate consequences. In this study, we used a climate model with dynamic vegetation to show that large-scale installations of wind and solar farms covering the Sahara lead to a local temperature increase and more than a twofold precipitation increase, especially in the Sahel, through increased surface friction and reduced albedo. The resulting increase in vegetation further enhances precipitation, creating a positive albedo-precipitation-vegetation feedback that contributes ~80% of the precipitation increase for wind farms. This local enhancement is scale dependent and is particular to the Sahara, with small impacts in other deserts.

SummaryMitochondrial alternative oxidase (AOX) is involved in a large number of plant physiological processes, such as growth, development and stress responses; however, the exact role of AOX in response to drought remains unclear. In our study, we provide solid evidences that the activated AOX capacity positively involved in ethylene‐induced drought tolerance, in tomato (Solanum lycopersicum), accompanied by the changing level of hydrogen peroxide (H2O2) and autophagy. In AOX1a‐RNAi plants, the ethylene‐induced drought tolerance was aggravated and associated with decreasing level of autophagy. The H2O2 level was relatively higher in AOX1a‐RNAi plants, whereas it was lower in AOX1a‐overexpressing (35S‐AOX1a‐OE) plants after 1‐(aminocarbonyl)‐1‐cyclopropanecarboxylic acid (ACC) pretreatment in the 14th day under drought stress. Interestingly, the accumulation of autophagosome was accompanied by the changing level of reactive oxygen species (ROS) in AOX transgenic tomato under drought stress whether or not pretreated with ACC. Pharmacological scavenging of H2O2 accumulation in AOX1a‐RNAi (aox19) stimulated autophagy acceleration under drought stress, and it seems that AOX‐dependent ROS signalling is critical in triggering autophagy. Lower levels of ROS signalling positively induce autophagy activity, whereas higher ROS level would lead to rapid programmed cell death (PCD), especially in ethylene‐mediated drought tolerance. Moreover, ethylene‐induced autophagy during drought stress also can be through ERF5 binding to the promoters of ATG8d and ATG18h. These results demonstrated that AOX plays an essential role in ethylene‐induced drought tolerance and also played important roles in mediating autophagy generation via balancing ROS level.