Tree species respond to climate change at multiple scales,such as species physiological response at fine scale and species distribution (quantified by percent area) at broader spatial scale.At a given spatial scale,sp...Tree species respond to climate change at multiple scales,such as species physiological response at fine scale and species distribution (quantified by percent area) at broader spatial scale.At a given spatial scale,species physiological response and distribution can be correlated positively or negatively.The consistency of such correlation relationships at different spatial scales determines whether species responses derived from local scales can be extrapo-lated to broader spatial scales.In this study,we used a coupled modeling approach that coupled a plot-level ecosystem process model (LINKAGES) with a spatially explicit landscape model (LANDIS).We investigated species physio-logical responses and distribution responses to climate warming at the local,zonal and landscape scales respectively,and examined how species physiological response and distribution correlated at each corresponding scale and whether the correlations were consistent among these scales.The results indicate that for zonal and warming-sensitive species,the correlations between species physiological response and distribution are consistent at these spatial scales,and therefore the research results of vegetation response to climate warming at the local scale can be extrapolated to the zonal and landscape scales.By contrast,for zonal and warming-insensitive species the correlations among different spatial scales are consistent at some spatial scales but at other scales.The results also suggest that the results of azonal species at the local scale near their distribution boundaries can not be extrapolated simply to broader scales due to stronger responses to climate warming in those boundary regions.展开更多
In situ observations and numerical simulations of turbulence are essential to understanding vertical mixing processes and their dynamical controls on both physical and biogeochemical processes in coastal embayments. U...In situ observations and numerical simulations of turbulence are essential to understanding vertical mixing processes and their dynamical controls on both physical and biogeochemical processes in coastal embayments. Using in situ data collected by bottom-mounted acoustic Doppler current profilers(ADCPs) and a free-falling microstructure profiler, as well as numerical simulations with a second-moment turbulence closure model, we studied turbulence and mixing in the Xiamen Bay, a freshwater-influenced tidal bay located at the west coast of the Taiwan Strait. Dynamically, the bay is driven predominantly by the M2 tide, and it is under a significant influence of the freshwater discharged from the Jiulong River. It is found that turbulence quantities such as the production and dissipation rates of the turbulent kinetic energy(TKE) were all subject to significant tidal variations, with a pronounced ebb-flood asymmetry. Turbulence was stronger during flood than ebb. During the flooding period, the whole water column was nearly well mixed with the depth-averaged TKE production rate and vertical eddy viscosity being up to 5?10?6 W kg?1 and 2?10?2 m2 s?1, respectively. In contrast, during the ebb strong turbulence was confined only to a 5?8 m thick bottom boundary layer, where turbulence intensity generally decreases with distance from the seafloor. Diagnosis of the potential energy anomaly showed that the ebb-flood asymmetry in turbulent dissipation and mixing was due mainly to tidal straining process as a result of the interaction between vertically shared tidal currents and horizontal density gradients. The role of vertical mixing in generating the asymmetry was secondary. A direct comparison of the modeled and observed turbulence quantities confirmed the applicability of the second-moment turbulence closure scheme in modeling turbulent processes in this weakly stratified tidally energetic environment, but also pointed out the necessity of further refinements of the model.展开更多
基金Under the auspices of International Partnership Program of Chinese Academy of Sciences (No.KZCX2-YW-T06)Key Direction in Knowledge Innovation Programs of Chinese Academy of Sciences (No.KZCX2-YW-444)Major State Basic Research Development Program of China (No.2009CB421101)
文摘Tree species respond to climate change at multiple scales,such as species physiological response at fine scale and species distribution (quantified by percent area) at broader spatial scale.At a given spatial scale,species physiological response and distribution can be correlated positively or negatively.The consistency of such correlation relationships at different spatial scales determines whether species responses derived from local scales can be extrapo-lated to broader spatial scales.In this study,we used a coupled modeling approach that coupled a plot-level ecosystem process model (LINKAGES) with a spatially explicit landscape model (LANDIS).We investigated species physio-logical responses and distribution responses to climate warming at the local,zonal and landscape scales respectively,and examined how species physiological response and distribution correlated at each corresponding scale and whether the correlations were consistent among these scales.The results indicate that for zonal and warming-sensitive species,the correlations between species physiological response and distribution are consistent at these spatial scales,and therefore the research results of vegetation response to climate warming at the local scale can be extrapolated to the zonal and landscape scales.By contrast,for zonal and warming-insensitive species the correlations among different spatial scales are consistent at some spatial scales but at other scales.The results also suggest that the results of azonal species at the local scale near their distribution boundaries can not be extrapolated simply to broader scales due to stronger responses to climate warming in those boundary regions.
基金supported by the National Natural Science Foundation of China(Grant Nos.41006017,41476006)the Natural Science Foundation of Fujian Province of China(Grant No.2015J06010)
文摘In situ observations and numerical simulations of turbulence are essential to understanding vertical mixing processes and their dynamical controls on both physical and biogeochemical processes in coastal embayments. Using in situ data collected by bottom-mounted acoustic Doppler current profilers(ADCPs) and a free-falling microstructure profiler, as well as numerical simulations with a second-moment turbulence closure model, we studied turbulence and mixing in the Xiamen Bay, a freshwater-influenced tidal bay located at the west coast of the Taiwan Strait. Dynamically, the bay is driven predominantly by the M2 tide, and it is under a significant influence of the freshwater discharged from the Jiulong River. It is found that turbulence quantities such as the production and dissipation rates of the turbulent kinetic energy(TKE) were all subject to significant tidal variations, with a pronounced ebb-flood asymmetry. Turbulence was stronger during flood than ebb. During the flooding period, the whole water column was nearly well mixed with the depth-averaged TKE production rate and vertical eddy viscosity being up to 5?10?6 W kg?1 and 2?10?2 m2 s?1, respectively. In contrast, during the ebb strong turbulence was confined only to a 5?8 m thick bottom boundary layer, where turbulence intensity generally decreases with distance from the seafloor. Diagnosis of the potential energy anomaly showed that the ebb-flood asymmetry in turbulent dissipation and mixing was due mainly to tidal straining process as a result of the interaction between vertically shared tidal currents and horizontal density gradients. The role of vertical mixing in generating the asymmetry was secondary. A direct comparison of the modeled and observed turbulence quantities confirmed the applicability of the second-moment turbulence closure scheme in modeling turbulent processes in this weakly stratified tidally energetic environment, but also pointed out the necessity of further refinements of the model.
