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Climate change affects the phenology of many species. As temperature and precipitation are thought to control autumn color change in temperate deciduous trees, it is possible that climate change might also affect the phenology of autumn colors. Using long-term data for eight tree species in a New England hardwood forest, we show that the timing and cumulative amount of autumn color are correlated with variation in temperature and precipitation at specific times of the year. A phenological model driven by accumulated cold degree-days and photoperiod reproduces most of the interspecific and interannual variability in the timing of autumn colors. We use this process-oriented model to predict changes in the phenology of autumn colors to 2099, showing that, while responses vary among species, climate change under standard IPCC projections will lead to an overall increase in the amount of autumn colors for most species.

AbstractBecause of its low level of energy consumption and the small scale of its industrial development, the Tibet Autonomous Region has historically been excluded from China's reported energy statistics, including those regarding CO2 emissions. In this paper, we estimate Tibet's energy consumption using limited online documents, and we calculate the 2014 energy‐related and process‐related CO2 emissions of Tibet and its seven prefecture‐level administrative divisions for the first time. Our results show that 5.52 million tons of CO2 were emitted in Tibet in 2014; 33% of these emissions are associated with cement production. Tibet's emissions per capita amounted to 1.74 tons in 2014, which is substantially lower than the national average, although Tibet's emission intensity is relatively high at 0.60 tons per thousand yuan in 2014. Among Tibet's seven prefecture‐level administrative divisions, Lhasa City and Shannan Region are the two largest CO2 contributors and have the highest per capita emissions and emission intensities. The Nagqu and Nyingchi regions emit little CO2 due to their farming/pasturing‐dominated economies. This quantitative measure of Tibet's regional CO2 emissions provides solid data support for Tibet's actions on climate change and emission reductions.

Purpose In Italy, composting olive mill waste has become a common practice, since it mitigates the environmental problems associated with spreading the waste on land. Compost can be used to prepare growth media for plant nursery cultivation as a substitute for peat, a non-renewable resource whose extraction has long raised environmental concerns. Here, we investigate two common composting procedures--open windrow and static-pile in gas-permeable bags--and compare them to evaluate their environmental impact. Methods We perform a cradle-to-grave life cycle assessment (LCA) in accordance with ISO 14040 and 14044. The LCA considers carbon storage in the soil after 100 years, fugitive greenhouse gas (GHG) emissions, and the impacts avoided by substituting for peat. We use cumulative energy demand, global warming potential (GWP), acidification potential, and eutrophication potential indicators in a contribution analysis and explore how the re-use of olive pits for energy production and reduction of commercial fertilizers improves the environmental balance. We also present a scenario analysis that indicates how parameter fluctuations affect the results. Results and discussion Our study shows that peat's impacts can be significantly reduced from 1162.3 to 96.3 kg CO2-eq/Mg for open windrow compost or 43.1 kg CO2-eq/Mg for static-pile compost in gas-permeable bags. For static-pile composting, the lack of volatile organic compound and ammonia emissions and the detection of oxygen concentrations above 12% vol. suggest fully aerobic conditions. Fugitive greenhouse gas emissions were the most important contributions to the GWP. In the contribution analysis for static-pile composting, the avoidance of compost spreading and the carbon storage effect (due to compost usage) contributed 54% of the overall impacts to GWP and between 21 and 45% to the other indicators. Conclusions This LCA study illustrates how horticulturists can improve their resource management practices by recycling olive mill waste materials. Proper management of composting unit aeration can reduce fugitive GHG emissions.

Shifts in rainfall patterns and increasing temperatures associated with climate change are likely to cause widespread forest decline in regions where droughts are predicted to increase in duration and severity. One primary cause of productivity loss and plant mortality during drought is hydraulic failure. Drought stress creates trapped gas emboli in the water transport system, which reduces the ability of plants to supply water to leaves for photosynthetic gas exchange and can ultimately result in desiccation and mortality. At present we lack a clear picture of how thresholds to hydraulic failure vary across a broad range of species and environments, despite many individual experiments. Here we draw together published and unpublished data on the vulnerability of the transport system to drought-induced embolism for a large number of woody species, with a view to examining the likely consequences of climate change for forest biomes. We show that 70% of 226 forest species from 81 sites worldwide operate with narrow (<1 megapascal) hydraulic safety margins against injurious levels of drought stress and therefore potentially face long-term reductions in productivity and survival if temperature and aridity increase as predicted for many regions across the globe. Safety margins are largely independent of mean annual precipitation, showing that there is global convergence in the vulnerability of forests to drought, with all forest biomes equally vulnerable to hydraulic failure regardless of their current rainfall environment. These findings provide insight into why drought-induced forest decline is occurring not only in arid regions but also in wet forests not normally considered at drought risk.

Ricardian (hedonic) analyses of the impact of climate change on farmland values typically assume additively separable effects of temperature and precipitation. Model estimation is implemented on data aggregated across counties or large regions. We investigate the potential bias induced by such approaches by using a large panel of farm-level data. Consistent with the literature on plant physiology, we observe significant non-linear interaction effects, with more abundant precipitation acting as a mitigating factor for increased heat stress. This interaction disappears when the same data is aggregated in the conventional manner, leading to predictions of climate change impacts which are significantly distorted.