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Evaluating the response of vegetation to climate change is relevant to improving the management of both human and natural systems. Here, we quantify the response of the MODIS-based enhanced vegetation index (EVI) to temperature, precipitation, and large-scale natural variability across the South-Central U.S. for summer (JJA) from 2000 to 2013. We find statistically significant relationships between climate and EVI that vary across the region and are distinct for each land cover type: the mean coefficient of determination (R 2 ) between EVI and climate is greatest for pasture (0.61 ± 0.13) and lowest for forest (0.55 ± 0.14). Among the climate variables, three-month cumulative precipitation has the strongest influence on summer vegetation, particularly in semi-arid west Texas and eastern New Mexico. Summer monthly maximum temperature plays an important role in the eastern half of Texas and Oklahoma, moderated by the influence of both Atlantic and Pacific teleconnection indices over inter-annual time scales. Based on these relationships, we train, cross-validate, and, where statistically significant relationships exist, combine this multivariate predictive model with projected changes in teleconnection indices and statistically-downscaled temperature and precipitation from 16 CMIP5 global climate models to quantify future changes in EVI. As global mean temperature increases, projected EVI decreases, indicative of stressed and dry vegetation, particularly for grasslands as compared to other land types, and in Oklahoma and western, central and Gulf Coast Texas for mid- and end-of-century. These trends have potentially important implications for agriculture and the regional economy, as well as for ecosystems and endemic species that depend on vegetation. [ABSTRACT FROM AUTHOR]

• Some types of weather affect Americans' belief that they have experienced global warming. • Americans associate hot, dry days and extreme drought with global warming. • People often fail to interpret extreme rainfall or flooding as due to global warming. Public perceptions of climate change in the United States are deeply rooted in cultural values and political identities. Yet, as the public experiences extreme weather and other climate change-related impacts, their perceptions of the issue may shift. Here, we explore whether, when, and where local climate trends have already influenced perceived experiences of global warming in the United States. Using a large national survey dataset (n = 13,607), we compare Americans' experiences of climate with corresponding trends in seven different high-resolution climate indicators for the period 2008 to 2015. We find that increases in hot dry day exposure significantly increases individuals' perceptions that they have personally experienced global warming. We do not find robust evidence that other precipitation and temperature anomalies have had a similar effect. We also use multilevel modeling to explore county-level patterns of perceived experiences with climate change. Whereas the individual-level analysis describes a likely causal relationship between a changing climate and individuals' perceived experience, the multilevel model depicts county-level changes in perceived experience resulting from particular climate trends. Overall, we find that exposure to hot dry days, has a modest influence on perceived experience, independent of the political and socio-demographic factors that dominate U.S. climate opinions today. [ABSTRACT FROM AUTHOR]

To what extent will increasing High Occupancy Vehicle (HOV) lane-kilometer incentivize carpooling and reduce emissions of air pollutants and greenhouse gases? To answer these questions, we develop a multiple regression model relating HOV lanes and other socioeconomic factors to carpooling propensity in all 50 U.S. states and the District of Columbia, then calculate the extent to which increasing HOV lane-kilometers would lead to reductions in carbon dioxide equivalent (CO 2 e) and major air pollutants across the U.S., by state. Increasing HOV lane extent has the greatest potential to reduce annual CO 2 e in the District of Columbia, followed by Hawaii and New York. The smallest potential is found in states with the lowest population density, led by North Dakota. We then explore the extent to which recommendations made at one level of data aggregation (that of individual states) may be valid for another level, such as individual counties. The only state with sufficient data available to disaggregate the model to the county level is California, where we found a lower potential for state-wide CO 2 e emission reductions under the county-level model as compared to the state-level model (0.69% as compared to 1.08%, under the same hypothetical scenario), albeit with significant differences in emission reduction potential between counties with higher vs. lower population densities. This analysis demonstrates the potential to generate generalizable insight into the magnitude of vehicle emission reductions that might be achieved through expanding HOV lanes, and highlights the importance of data disaggregation in identifying the optimal locations for potential reductions. [ABSTRACT FROM AUTHOR]

Carbon dioxide emissions from human activities are the primary cause of recent climate change. In the United States, the road transportation sector is one of the largest sources of these emissions. Any policies to reduce emissions must therefore include mitigation strategies for on-road transportation. The aim of this paper is to propose a multi-criteria method, Analytical Hierarchy Process, to rank various on-road emissions mitigation strategies including reduce, avoid, and replace strategies. The method׳s results are obtained based on a survey of transportation and climate science professionals. The Analytical Hierarchy Process was applied to two regional scenarios of a midsize-small city (Lubbock, Texas) and a metropolitan area (Dallas, Texas). To evaluate the effectiveness of these strategies, the Motor Vehicle Emissions Simulator model was run for Dallas. The aim of the model was to estimate the potential carbon dioxide mitigation for a given strategy allocation. Our survey identified no difference between the rankings of reduce, avoid, and replace strategies for our metropolitan and midsize-small city areas. Reduce strategies had the highest preference score of 40% followed by avoid strategies with 36% and replace strategies with 24%. An optimum mixed mitigation scenario would achieve reductions in carbon dioxide emissions of 17% by 2030 from 2010 levels. The contributions of this study are two-fold. First, we evaluate generic scenarios in detail and apply them to a real-world case study. Second, the approach is both simple and generalizable. Applications of this type of platform include ranking transportation strategies on mitigating carbon dioxide emissions, evaluating the strategies, prioritizing budgets, and developing assessments of mitigation potential. [ABSTRACT FROM AUTHOR]

Abstract Statistically downscaled climate change scenarios from four General Circulation Models for two Representative Concentration Pathways (RCP) were applied as inputs to a biogeochemical model, PnET-BGC, to examine potential future dynamics of water, carbon, and nitrogen in an old-growth Douglas-fir forest in the western Cascade Range. Projections show 56% to 77% increases in stomatal conductance throughout the year from 1986–2010 to 2076–2100, and 65% to 104% increases in leaf carbon assimilation between October and June over the same period. However, future dynamics of water and carbon under the RCP scenarios are affected by a 49% to 86% reduction in foliar biomass resulting from severe air temperature and humidity stress to the forest in summer. Important implications of future decreases in foliar biomass include 1) 20% to 71% decreases in annual transpiration which increase soil moisture by 7% to 15% in summer and fall; 2) decreases in photosynthesis by 77% and soil organic matter by 62% under the high radiative forcing scenario; and 3) altered foliar and soil carbon to nitrogen stoichiometry. Potential carbon dioxide fertilization effects on vegetation are projected to 1) amplify decreases in transpiration by 4% to 9% and increases in soil moisture in summer and fall by 1% to 2%; and 2) alleviate decreases in photosynthesis by 4%; while 3) having negligible effects on the dynamics of nitrogen. Our projections suggest that future decrease in transpiration and moderate water holding capacity may mitigate soil moisture stress to the old-growth Douglas-fir forest. Future increases in nitrogen concentration in soil organic matter are projected to alleviate the decrease in net nitrogen mineralization despite a reduction in decomposition of soil organic matter by the end of the century. Graphical abstract Unlabelled Image Highlights • Element dynamics projected in an old-growth Douglas-fir forest under RCP scenarios • Future increasing temperature causes severe physiological stress on the vegetation • Decreasing photosynthesis, plant biomass, and soil organic matter are projected • Projected mortality decreases transpiration and slightly increases soil moisture • Future climate change alters foliar and soil carbon to nitrogen stoichiometry [ABSTRACT FROM AUTHOR]

Abstract Using statistically downscaled future climate scenarios and a version of the biogeochemical model (PnET-BGC) that was modified for use in the alpine tundra, we investigated changes in water, carbon, and nitrogen dynamics under the Representative Concentration Pathways at Niwot Ridge in Colorado, USA. Our simulations indicate that future hydrology will become more water-limited over the short-term due to the temperature-induced increases in leaf conductance, but remains energy-limited over the longer term because of anticipated future decreases in leaf area and increases in annual precipitation. The seasonal distribution of the water supply will become decoupled from energy inputs due to advanced snowmelt, causing soil moisture stress to plants during the growing season. Decreases in summer soil moisture are projected to not only affect leaf production, but also reduce decomposition of soil organic matter in summer despite increasing temperature. Advanced future snowmelt in spring and increasing rain to snow ratio in fall are projected to increase soil moisture and decomposition of soil organic matter. The extended growing season is projected to increase carbon sequestration by 2% under the high radiative forcing scenario, despite a 31% reduction in leaf display due to the soil moisture stress. Our analyses demonstrate that future nitrogen uptake by alpine plants is regulated by nitrogen supply from mineralization, but plant nitrogen demand may also affect plant uptake under the warmer scenario. PnET-BGC simulations also suggest that potential CO 2 effects on alpine plants are projected to cause larger increases in plant carbon storage than leaf and root production. Graphical abstract Unlabelled Image Highlights • Future dynamics of water, carbon, and nitrogen are projected in an alpine tundra. • Budyko curve applied to examine evapotranspiration and runoff under RCP scenarios. • Advanced snowmelt in spring and lower soil moisture in summer are projected. • Future dynamics of C N are significantly affected by altered hydrological patterns. • Extended growing season and elevated CO 2 affect major C N pools and fluxes. [ABSTRACT FROM AUTHOR]