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Considers how science can be presented in a format that will allow college-level undergraduates not majoring in the sciences to understand science in terms of everyday life and in the context that science is important in their own fields of interest. (Contains 49 references.) (DDR)

Discusses public confusion about the science related to climate change and public apathy towards related issues. This confusion can be related to a combination of factors, including ineffective communication. (Contains 39 references.) (DDR)

Analyzes texts published by ExxonMobil on the issue of climate change, employing both rhetorical analysis and discourse analysis to show their uses and potential value in business communication research. Shows how both reveal the socially constructed nature "reality" and the social effects of language, but are never the less distinct in their emphases. (SR)

Discusses the reliability and versatility of using photovoltaics whereby solar cells convert sunlight directly into electricity. The growing concern of global warming promises to transform photovoltaics into a major energy producer. (Author/SAH)

Expands on earlier work to examine pre-service teachers' views on environmental issues, especially global warming and the related term "greenhouse effect." Suggests that pre-service elementary teachers hold many misconceptions about environmental issues. (DDR)

Abstract: Ships brighten low marine clouds from emissions of sulfur and aerosols, resulting in visible “ship tracks”. In 2020, new shipping regulations mandated an ∼80% reduction in the allowed fuel sulfur content. Recent observations indicate that visible ship tracks have decreased. Model simulations indicate that since 2020 shipping regulations have induced a net radiative forcing of +0.12 Wm−2. Analysis of recent temperature anomalies indicates Northern Hemisphere surface temperature anomalies in 2022–2023 are correlated with observed cloud radiative forcing and the cloud radiative forcing is spatially correlated with the simulated radiative forcing from the 2020 shipping emission changes. Shipping emissions changes could be accelerating global warming. To better constrain these estimates, better access to ship position data and understanding of ship aerosol emissions are needed. Understanding the risks and benefits of emissions reductions and the difficultly in robust attribution highlights the large uncertainty in attributing proposed deliberate climate intervention.

Seasonal floodplains in the Amazon basin are important sources of methane (CH4), while upland forests are known for their sink capacity. Climate change effects, including shifts in rainfall patterns and rising temperatures, may alter the functionality of soil microbial communities, leading to uncertain changes in CH4 cycling dynamics. To investigate the microbial feedback under climate change scenarios, we performed a microcosm experiment using soils from two floodplains (i.e., Amazonas and Tapajós rivers) and one upland forest. We employed a two-factorial experimental design comprising flooding (with non-flooded control) and temperature (at 27 °C and 30 °C, representing a 3 °C increase) as variables. We assessed prokaryotic community dynamics over 30 days using 16S rRNA gene sequencing and qPCR. These data were integrated with chemical properties, CH4 fluxes, and isotopic values and signatures. In the floodplains, temperature changes did not significantly affect the overall microbial composition and CH4 fluxes. CH4 emissions and uptake in response to flooding and non-flooding conditions, respectively, were observed in the floodplain soils. By contrast, in the upland forest, the higher temperature caused a sink-to-source shift under flooding conditions and reduced CH4 sink capability under dry conditions. The upland soil microbial communities also changed in response to increased temperature, with a higher percentage of specialist microbes observed. Floodplains showed higher total and relative abundances of methanogenic and methanotrophic microbes compared to forest soils. Isotopic data from some flooded samples from the Amazonas river floodplain indicated CH4 oxidation metabolism. This floodplain also showed a high relative abundance of aerobic and anaerobic CH4 oxidizing Bacteria and Archaea. Taken together, our data indicate that CH4 cycle dynamics and microbial communities in Amazonian floodplain and upland forest soils may respond differently to climate change effects. We also highlight the potential role of CH4 oxidation pathways in mitigating CH4 emissions in Amazonian floodplains.

Humid heatwaves, characterized by high temperature and humidity combinations, challenge tropical societies. Extreme wet-bulb temperatures (TW) over tropical land are coupled to the warmest sea surface temperatures by atmospheric convection and wave dynamics. Here, we harness this coupling for seasonal forecasts of the annual maximum of daily maximum TW (TWmax). We develop a multiple linear regression model that explains 80% of variance in tropical mean TWmax and significant regional TWmax variances. The model considers warming trends and El Niño and Southern Oscillation indices. Looking ahead, the strong-to-very-strong El Niño at the end of 2023, with an Oceanic Niño Index of ∼2.0, suggests a 2024 tropical land mean TWmax of 26.2°C (25.9–26.4°C), and a 68% chance (24%–94%) of breaking existing records. This method also predicts regional TWmax in specific areas.

Soil carbon (C) responses to environmental change represent a major source of uncertainty in the global C cycle. Feedbacks between soil C stocks and climate drivers could impact atmospheric CO2 levels, further altering the climate. Here, we assessed the reliability of Earth system model (ESM) predictions of soil C change using the Coupled Model Intercomparison Project phases 5 and 6 (CMIP5 and CMIP6). ESMs predicted global soil C gains under the high emission scenario, with soils taking up 43.9 Pg (95% CI: 9.2–78.5 Pg) C on average during the 21st century. The variation in global soil C change declined significantly from CMIP5 (with average of 48.4 Pg [95% CI: 2.0–94.9 Pg] C) to CMIP6 models (with average of 39.3 Pg [95% CI: 23.9–54.7 Pg] C). For some models, a small C increase in all biomes contributed to this convergence. For other models, offsetting responses between cold and warm biomes contributed to convergence. Although soil C predictions appeared to converge in CMIP6, the dominant processes driving soil C change at global or biome scales differed among models and in many cases between earlier and later versions of the same model. Random Forest models, for soil carbon dynamics, accounted for more than 63% variation of the global soil C change predicted by CMIP5 ESMs, but only 36% for CMIP6 models. Although most CMIP6 models apparently agree on increased soil C storage during the 21st century, this consensus obscures substantial model disagreement on the mechanisms underlying soil C response, calling into question the reliability of model predictions.

The possibility that the Amazon forest system could soon reach a tipping point, inducing large-scale collapse, has raised global concern1-3. For 65 million years, Amazonian forests remained relatively resilient to climatic variability. Now, the region is increasingly exposed to unprecedented stress from warming temperatures, extreme droughts, deforestation and fires, even in central and remote parts of the system1. Long existing feedbacks between the forest and environmental conditions are being replaced by novel feedbacks that modify ecosystem resilience, increasing the risk of critical transition. Here we analyse existing evidence for five major drivers of water stress on Amazonian forests, as well as potential critical thresholds of those drivers that, if crossed, could trigger local, regional or even biome-wide forest collapse. By combining spatial information on various disturbances, we estimate that by 2050, 10% to 47% of Amazonian forests will be exposed to compounding disturbances that may trigger unexpected ecosystem transitions and potentially exacerbate regional climate change. Using examples of disturbed forests across the Amazon, we identify the three most plausible ecosystem trajectories, involving different feedbacks and environmental conditions. We discuss how the inherent complexity of the Amazon adds uncertainty about future dynamics, but also reveals opportunities for action. Keeping the Amazon forest resilient in the Anthropocene will depend on a combination of local efforts to end deforestation and degradation and to expand restoration, with global efforts to stop greenhouse gas emissions.

Global warming modulates soil respiration (RS) via microbial decomposition, which is seasonally dependent. Yet, the magnitude and direction of this modulation remain unclear, partly owing to the lack of knowledge on how microorganisms respond to seasonal changes. Here, we investigated the temporal dynamics of soil microbial communities over 12 consecutive months under experimental warming in a tallgrass prairie ecosystem. The interplay between warming and time altered (P

Street networks allow people and goods to move through cities, but they are vulnerable to disasters like floods, earthquakes, and terrorist attacks. Well-planned network design can make a city more resilient and robust to such disruptions, but we still know little about worldwide patterns of vulnerability, or worldwide empirical relationships between specific design characteristics and resilience. This study quantifies and measures the vulnerability of the street networks of every urban area in the world then models the relationships between vulnerability and street network design characteristics. To do so, we simulate over 2.4 billion trips across more than 8,000 urban areas in 178 countries, while also simulating network disruption events representing floods, earthquakes, and targeted attacks. We find that disrupting high-centrality nodes severely impacts network function. All else equal, networks with higher connectivity, fewer chokepoints, or less circuity are less vulnerable to disruption's impacts. This study thus contributes a new global understanding of network design and vulnerability to the literature. We argue that these design characteristics offer high leverage points for street network resilience and robustness that planners should emphasize when designing or retrofitting urban networks.

2022 marked the third consecutive La Niña and extended the longest consecutive stretch of negative Oceanic Niño Index since 1998-2001. While physical and biological conditions in winter and spring largely adhered to prior La Niña conditions, summer and fall were very different. Similar to past La Niña events, in winter and spring coastal upwelling was either average or above average, temperature average or below average, salinity generally above average. In summer and fall, however, upwelling and temperature were generally average or slightly below average, salinity was close to average and chlorophyll a was close to average. Again, as during prior La Niña events, biomass of northern/southern copepods was above/below average off Oregon in winter, and body size of North Pacific krill in northern California was above average in winter. By contrast, later in the year the abundance of northern krill dropped off Oregon while southern copepods increased and body sizes of North Pacific krill fell in northern California. Off Oregon and Washington abundances of market squid and Pacific pompano (indicators of warm, non-typical La Niña conditions) were high. In the 20th century, Northern anchovy recruitment tended to be high during cold conditions, but despite mostly warm conditions from 2015-2021 anchovy populations boomed and remained high in 2022. Resident seabird reproductive success, which tended in the past to increase during productive La Niña conditions was highly variable throughout the system as common murre and pelagic cormorant, experienced complete reproductive failure at Yaquina Head, Oregon while Brandt’s cormorant reproduction was average. At three sampling locations off central California, however, common murre reproduction was close to or above average while both pelagic and Brandt’s cormorant were above average. California sealion reproduction has been above average each year since 2016, and pup weight was also above average in 2022, likely in response not to La Niña or El Niño but continuous high abundance of anchovy. The highly variable and often unpredictable physical and biological conditions in 2022 highlight a growing recognition of disconnects between basin-scale indices and local conditions in the CCE. “July-December 2022 is the biggest outlier from individual “strong” La Niña (events) ever going back to the 50s.” – Nate Mantua

Plants infected by parasitic species might be further stressed by climate warming as both factors can influence the host plant's nutrient acquisition and growth. The root economics space, defined by root functional traits, reflects a plant's nutrient acquisition strategy. However, the combined effects of warming and parasitism on root functional traits and their positions within the root economics space have not been extensively studies. We grew soybean plants in pot cultures outdoor in the absence or presence of parasitism by Cuscuta gronovii and with or without simulated climate warming using infrared heater lamps. We measured various root functional traits of soybean, including root morphological traits, symbiosis with arbuscular mycorrhizal fungi (AMF) and rhizobia and enzyme activity. Correlations among these traits were analysed, and principal component analysis was used to determine the position of the plants in the root economics space. Parasitism significantly reduced AMF colonization rate, nodule biomass, root tissue density (RTD) and phosphatase activity in the rhizosheath, while increasing root nitrogen concentration (RN). Nodule biomass was positively correlated with AMF colonization, indicating an ‘outsourcing’ strategy for nutrient foraging. Parasitized soybeans occupied a trait space with higher RN and lower RTD, indicative of a ‘fast’ nutrient acquisition strategy. Warming did not significantly affect root functional traits or the plants' positions in the root economics space, regardless of parasitism presence. This study is the first to demonstrate that rhizobial colonization, similar to AMF colonization, is part of the ‘outsourcing’ strategy and that parasitism shifts host plants from a ‘slow’ to a ‘fast’ nutrient uptake strategy. These findings provide new insights into plant below‐ground strategies under warming and parasitism. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Societal Impact Statement Summary The iconic Yoshino cherry tree in Japan is experiencing shifts in its blossom timing due to climate warming. To develop a genetically informed predictive model for bud dormancy release, we examined seasonal gene expression in Yoshino cherry trees at three different locations. Our experiments, coupled with the analysis of DORMANCY‐ASSOCIATED MADS‐box (DAM) genes, highlighted DAM4 as the most reliable indicator for the rate of bud dormancy release. Our study demonstrated that seasonal gene expression profiles serve as a valuable indicator for forecasting the timing of dormancy release, benefiting Japanese traditions and providing insights into the biological impacts of climate change. The Yoshino cherry tree Cerasus × yedoensis ‘Somei‐yoshino’ stands out as an iconic springtime symbol in Japan. For the Yoshino cherry trees to bloom in the spring, dormant buds must undergo a period of exposure to low temperatures, allowing them to break dormancy. Key genes related to dormancy release, known as DORMANCY‐ASSOCIATED MADS‐box (DAM), have been extensively studied. However, it remains unclear how these genes function in natural environments to regulate the timing of bud dormancy release. To develop a genetically informed predictive model for bud dormancy release, we explored seasonal changes in genome‐wide gene expression profiles in the Yoshino cherry trees at three distinct sites in Japan. Five distinct genome‐wide transcription profiles, subjectively named as modes—early summer, summer, autumn, winter, and spring—were identified, with the winter and spring modes observed when the daily mean temperature was below approximately 10°C. Our experiments of bud dormancy release, along with the assessment of expression profiles of DAM genes, have revealed that among the six DAM genes, DAM4 expression profile is the most indicative of the rate of bud dormancy break. Our estimates suggest that, on average, the tree needs to be exposed to temperatures below 10.1°C for 61.1 days to suppress DAM4 expression to the threshold required for bud dormancy release. Our projections for the timing of bud dormancy release indicated a delay of approximately 2.3 days per decade from 1990 to 2020. Our study demonstrated that gene expression serves as a valuable indicator for forecasting the timing of dormancy release. [ABSTRACT FROM AUTHOR]

Reducing uncertainty in the response of the Amazon rainforest, a vital component of the Earth system, to future climate change is crucial for refining climate projections. Here we demonstrate an emergent constraint (EC) on the future response of the Amazon carbon cycle to climate change across CMIP6 Earth system models. Models that overestimate past global warming trends, tend to estimate hotter and drier future Amazon conditions, driven by northward shifts of the intertropical convergence zone over the Atlantic Ocean, causing greater Amazon carbon loss. The proposed EC changes the mean CMIP6 Amazon climate-induced carbon loss estimate (excluding CO2 fertilisation and land-use change impacts) from −0.27 (−0.59–0.05) to −0.16 (−0.42–0.10) GtC year−1 at 4.4 °C warming level, reducing the variance by 34%. This study implies that climate-induced carbon loss in the Amazon rainforest by 2100 is less than thought and that past global temperature trends can be used to refine regional carbon cycle projections. A study shows an emergent constraint on the Amazon carbon cycle response to climate change. The CMIP6 ESMs that overestimate past global temperature trends, tend to project hotter, drier conditions and greater climate-induced Amazon carbon source. [ABSTRACT FROM AUTHOR]

Introduction: Jacaranda mimosifolia, native to South America, is a notable ornamental tree widely used in Chinese urban landscaping due to its aesthetic and environmental value. Despite its popularity, the cultivation of J. mimosifolia in China faces challenges, including intermittent failures in various regions. This study assesses the potential distribution of J. mimosifolia in China and its response to climate change, providing insights for its application and promotion. Methods: Using MaxEnt software, we developed an ecological niche model from 218 distribution records and selected 10 environmental variables to predict the tree's distribution under various climate scenarios (SSP126, SSP245, SSP370). Results: Our model demonstrates high predictive accuracy (AUC > 0.90) across scenarios, identifying key factors such as the mean temperature of the coldest quarter (bio11), precipitation of the driest month (bio14), temperature annual range (bio7), and minimum temperature of the coldest month (bio6). Their relative contribution rates were 49.3%, 18.4%, 15.6%, and 2.0%, respectively. The average temperature of the coldest quarter was not lower than 5°C, with the ideal range being 7.38~14.88°C. Currently, J. mimosifolia predominantly thrives in Taiwan, Fujian, Guangdong, Hainan, Guangxi, Yunnan, and to a lesser extent in the Sichuan Basin, southern Guizhou, Tibet, Hunan, Jiangxi, and Zhejiang province, covering a total area of approximately 122.19×104 km2. Future predictions indicate that under the SSP126 scenario, the most significant contraction occurs between the 2050s and 2070s, with a total change of -1.08×104 km2. Conversely, under the SSP370 scenario, the greatest expansion is observed from the 2030s to the 2050s, amounting to a change of 2.08×104 km2. Suitable area expansion is anticipated in most periods and scenarios, except for SSP126 in the 2070s, SSP245 in the 2050s, and SSP370 in the 2030s and 2070s. The distribution center shifts observed include movements northwestward, southwestward, and eastward with distances ranging from 5.12 km to 18.84 km. These shifts are likely driven by global warming, resulting in movements to higher elevations and latitudes. Discussion: These predictions will provide a solid theoretical foundation for the future application of J. mimosifolia in urban landscaping and serve as a valuable reference for its introduction and cultivation. [ABSTRACT FROM AUTHOR]

Mosquito vectors of pathogens (e.g., Aedes, Anopheles, and Culex spp. which transmit dengue, Zika, chikungunya, West Nile, malaria, and others) are of increasing concern for global public health. These vectors are geographically shifting under climate and other anthropogenic changes. As small-bodied ectotherms, mosquitoes are strongly affected by temperature, which causes unimodal responses in mosquito life history traits (e.g., biting rate, adult mortality rate, mosquito development rate, and probability of egg-to-adult survival) that exhibit upper and lower thermal limits and intermediate thermal optima in laboratory studies. However, it remains unknown how mosquito thermal responses measured in laboratory experiments relate to the realized thermal responses of mosquitoes in the field. To address this gap, we leverage thousands of global mosquito occurrences and geospatial satellite data at high spatial resolution to construct machine-learning based species distribution models, from which vector thermal responses are estimated. We apply methods to restrict models to the relevant mosquito activity season and to conduct ecologically plausible spatial background sampling centered around ecoregions for comparison to mosquito occurrence records. We found that thermal minima estimated from laboratory studies were highly correlated with those from the species distributions (r = 0.87). The thermal optima were less strongly correlated (r = 0.69). For most species, we did not detect thermal maxima from their observed distributions so were unable to compare to laboratory-based estimates. The results suggest that laboratory studies have the potential to be highly transportable to predicting lower thermal limits and thermal optima of mosquitoes in the field. At the same time, lab-based models likely capture physiological limits on mosquito persistence at high temperatures that are not apparent from field-based observational studies but may critically determine mosquito responses to climate warming. Our results indicate that lab-based and field-based studies are highly complementary; performing the analyses in concert can help to more comprehensively understand vector response to climate change. Author summary: Mosquito vectors are strongly affected by temperature, and their distributions are likely to shift under climate change. Lab studies show that mosquito abundance has a unimodal response to temperature with thermal optima, upper and lower thermal limits. However, it remains unknown how mosquito laboratory-derived thermal responses relate to the thermal responses of mosquitoes in nature. We used a global database of field-collected mosquito occurrences, geospatial environmental covariates, and species distribution models to estimate the relationship between temperature and probability of mosquito occurrence. We found that thermal minima (r = 0.87) and, to a lesser degree, thermal optima (r = 0.69) estimated from laboratory studies were correlated with those from the species distribution models. For most species, we did not detect thermal maxima. These results suggest that laboratory studies and field-based machine learning studies are complementary. Together, they can help to better understand vector response to climate change. [ABSTRACT FROM AUTHOR]

Dust and high cloud interactions are critical for climate change, primarily due to the dominant roles of high cloud in the greenhouse effect and the continental precipitation. Nonetheless, disentangling the specific impacts of dust from the overlying meteorology influence on high clouds presents great challenges. In this study, we construct a meteorological pattern that successfully reveal the intricate connection between high cloud distribution and atmospheric conditions. Through this strong bounded relationship, we find that dust exhibits notable controls over the facilitation or inhibition of ice particle growth contingent upon the prevailing meteorological fields. More dust can increase precipitation rate and shorten high cloud lifetime particularly under favorable meteorology. These findings underscore the crucial role of dust concentration in mitigating global warming for future climate change. Plain Language Summary: Dust particles in the atmosphere play a crucial role in the formation and dissipation of high clouds, which can significantly impact global climate and weather patterns. By analyzing satellite observations and climate model data, we discovered that dust can either enhance or suppress the growth of ice crystals, depending on the atmospheric conditions. In moist environments with favorable weather, increased dust leads to larger ice crystals and more precipitation, accelerating the life cycle of high clouds. Conversely, in dry conditions with unfavorable weather, excessive dust competes for limited moisture, resulting in smaller ice crystals, although it can still increase rainfall during the dissipation stage of high clouds. As climate change progresses and dust storms become more frequent, the increased presence of dust in the atmosphere may lead to more extreme weather events and potentially mitigate some of the warming effects caused by high clouds. Understanding these complex interactions between dust, high clouds, and weather conditions is essential for improving climate models and predicting future changes in Earth's water cycle and energy balance. Key Points: Extracted first principal component, highly correlated with high cloud fraction, isolating meteorological effects on cloudsDust facilitates ice crystal formation and precipitation, catalyzing cloud lifecycle and ultimately modifying radiative effectsIncreased dust accelerates high cloud lifecycle, causing more extreme weather and mitigating climate warming [ABSTRACT FROM AUTHOR]

Horizontal and vertical moisture advection in the lower troposphere of the Arctic under progressing global warming is examined using a large‐scale ensemble model data set. Advection is decomposed into terms related to the basic state of the atmosphere and transient eddies and compared against a non‐warming experiment. During summer, horizontal moisture advection increases mainly by transient eddies advecting moisture from the lower latitudes. During winter, enhanced evaporation due to reduced sea ice becomes a source of moisture diminishing the role of transient eddies moistening the atmosphere. This effect intensifies under extreme global warming, turning the change in total horizontal advection in the lower troposphere negative. Diminished horizontal advection during winter is counteracted by vertical advection accompanied with enhanced evaporation and upper‐level horizontal advection maintaining the increase in column moisture. These results improve our understanding of how the water cycle in the Arctic responds via atmospheric processes under global warming. Plain Language Summary: This study uses a data set with a large number of members to investigate how the atmosphere is moistened in the Arctic (north of 70˚N) under various stages of global warming. The movement of moisture is summarized in terms of horizontal and vertical components of advection, a measure of how the atmosphere is moistened in a given specific humidity gradient and wind, which is decomposed into parts related to the average state of the atmosphere and parts related to high‐frequency phenomena, such as cyclones. It is found that (a) during summer, moisturization of the Arctic is mainly driven by horizontal movement of moisture from a remote source in the lower latitude, (b) during winter, this moisturization due to horizontal movement of moisture is suppressed and is driven more by vertical movement of moisture due to reduction of sea ice and increased evaporation. As global warming progresses, the role or horizontal movement of moisture is taken over by the local process of evaporation and vertical movement of moisture. This research helps us understand how the water cycle in the Arctic changes with severe global warming and improves our knowledge of the atmospheric processes that govern the climate system through various feedbacks. Key Points: Moisture advection in the Arctic under progressing global warming is examined using a large‐scale ensemble model simulation data setMoistening effect of horizontal advection in the lower troposphere is enhanced for summer and diminished for winter under extreme warmingEnhanced horizontal advection in the upper layer and surface evaporation are consistent with increased column moisture during winter [ABSTRACT FROM AUTHOR]