Aims Determining the ecological consequences of interactions between slow changes in long-term climate means and amplified variability in climate is an important research frontier in plant ecology.We combined the rece...Aims Determining the ecological consequences of interactions between slow changes in long-term climate means and amplified variability in climate is an important research frontier in plant ecology.We combined the recent approach of climate sensitivity functions with a revised hydrological‘bucket model’to improve predictions on how plant species will respond to changes in the mean and variance of groundwater resources.Methods We leveraged spatiotemporal variation in long-term datasets of riparian vegetation cover and groundwater levels to build the first groundwater sensitivity functions for common plant species of dryland riparian corridors.Our results demonstrate the value of this approach to identifying which plant species will thrive(or fail)in an increasingly variable climate layered with declining groundwater stores.Important Findings Riparian plant species differed in sensitivity to both the mean and variance in groundwater levels.Rio Grande cottonwood(Populus deltoides ssp.wislizenii)cover was predicted to decline with greater inter-annual groundwater variance,while coyote willow(Salix exigua)and other native wetland species were predicted to benefit from greater year-to-year variance.No non-native species were sensitive to groundwater variance,but patterns for Russian olive(Elaeagnus angustifolia)predict declines under deeper mean groundwater tables.Warm air temperatures modulated groundwater sensitivity for cottonwood,which was more sensitive to variability in groundwater in years/sites with warmer maximum temperatures than in cool sites/periods.Cottonwood cover declined most with greater intra-annual coefficients of variation(CV)in groundwater,but was not significantly correlated with inter-annual CV,perhaps due to the short time series(16 years)relative to cottonwood lifespan.In contrast,non-native tamarisk(Tamarix chinensis)cover increased with both intra-and inter-annual CV in groundwater.Altogether,our results predict that changes in groundwater variability and mean will affect riparian plant communities through the differential sensitivities of individual plant species to mean versus variance in groundwater stores.展开更多
By analyzing phonon dispersion, we have evaluated the average Young＇s modulus and Poisson＇s ratio in graphite and in graphene grown on Ru（0001）, Pt（111）, Ir（111）, Ni（111）, and BC3/NbB2（0001）. In both flat ...By analyzing phonon dispersion, we have evaluated the average Young＇s modulus and Poisson＇s ratio in graphite and in graphene grown on Ru（0001）, Pt（111）, Ir（111）, Ni（111）, and BC3/NbB2（0001）. In both flat and corrugated graphene sheets and in graphite, we find a Poisson＇s ratio of 0.19 and a Young＇s modulus of 342 N/m. The unique exception is graphene/Ni（111）, for which we find different values because of the stretching of C-C bonds occurring in the commensurate overstructure （0.36 and 310 N/m for the Poisson＇s ratio and Young＇s modulus, respectively）. Such findings are in excellent agreement with calculations performed for a free-standing graphene membrane. The high crystalline quality of graphene grown on metal substrates leads to macroscopic samples with high tensile strength and bending flexibility for use in technological applications such as electromechanical devices and carbon-fiber reinforcements.展开更多
基金supported by grants from the National Science Foundation to the University of New Mexico(UNM)for Long-term Ecological Research,most recently DEB#1655499 and by the UNM Department of Biology.
文摘Aims Determining the ecological consequences of interactions between slow changes in long-term climate means and amplified variability in climate is an important research frontier in plant ecology.We combined the recent approach of climate sensitivity functions with a revised hydrological‘bucket model’to improve predictions on how plant species will respond to changes in the mean and variance of groundwater resources.Methods We leveraged spatiotemporal variation in long-term datasets of riparian vegetation cover and groundwater levels to build the first groundwater sensitivity functions for common plant species of dryland riparian corridors.Our results demonstrate the value of this approach to identifying which plant species will thrive(or fail)in an increasingly variable climate layered with declining groundwater stores.Important Findings Riparian plant species differed in sensitivity to both the mean and variance in groundwater levels.Rio Grande cottonwood(Populus deltoides ssp.wislizenii)cover was predicted to decline with greater inter-annual groundwater variance,while coyote willow(Salix exigua)and other native wetland species were predicted to benefit from greater year-to-year variance.No non-native species were sensitive to groundwater variance,but patterns for Russian olive(Elaeagnus angustifolia)predict declines under deeper mean groundwater tables.Warm air temperatures modulated groundwater sensitivity for cottonwood,which was more sensitive to variability in groundwater in years/sites with warmer maximum temperatures than in cool sites/periods.Cottonwood cover declined most with greater intra-annual coefficients of variation(CV)in groundwater,but was not significantly correlated with inter-annual CV,perhaps due to the short time series(16 years)relative to cottonwood lifespan.In contrast,non-native tamarisk(Tamarix chinensis)cover increased with both intra-and inter-annual CV in groundwater.Altogether,our results predict that changes in groundwater variability and mean will affect riparian plant communities through the differential sensitivities of individual plant species to mean versus variance in groundwater stores.
文摘By analyzing phonon dispersion, we have evaluated the average Young＇s modulus and Poisson＇s ratio in graphite and in graphene grown on Ru（0001）, Pt（111）, Ir（111）, Ni（111）, and BC3/NbB2（0001）. In both flat and corrugated graphene sheets and in graphite, we find a Poisson＇s ratio of 0.19 and a Young＇s modulus of 342 N/m. The unique exception is graphene/Ni（111）, for which we find different values because of the stretching of C-C bonds occurring in the commensurate overstructure （0.36 and 310 N/m for the Poisson＇s ratio and Young＇s modulus, respectively）. Such findings are in excellent agreement with calculations performed for a free-standing graphene membrane. The high crystalline quality of graphene grown on metal substrates leads to macroscopic samples with high tensile strength and bending flexibility for use in technological applications such as electromechanical devices and carbon-fiber reinforcements.
