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
Vegetation cover pattern is one of the factors controlling hydrological processes. Spatially distributed models are the primary tools previously applied to document the effect of vegetation cover patterns on runoff an...Vegetation cover pattern is one of the factors controlling hydrological processes. Spatially distributed models are the primary tools previously applied to document the effect of vegetation cover patterns on runoff and soil erosion. Models provide precise estimations of runoff and sediment yields for a given vegetation cover pattern. However, difficulties in parameterization and the problematic explanation of the causes of runoff and sedimentation rates variation weaken prediction capability of these models. Landscape pattern analysis employing pattern indices based on runoff and soil erosion mechanism provides new tools for finding a solution. In this study, the vegetation cover pattern was linked with runoff and soil erosion by two previously de- veloped pattern indices, which were modified in this study, the Directional Leakiness Index （DL[） and Flowlength. Although they use different formats, both indices involve connectivity of sources ,areas （interpatch bare areas）. The indices were revised by bringing in the functional heterogeneity of the plant cover types and the landscape position. Using both artificial and field verified vegetation cover maps, observed runoff and sediment production on experiment plots, we tested the indices＇ efficiency and compared the indices with their antecedents. The results illustrate that the modified indices are more effective in indicating runoff at the plot/hillslope scale than their antecedents. However, sediment export levels are not provided by the modified indices. This can be attributed to multi-factor interaction on the hydrological process, the feedback mechanism between the hydrological function of cover patterns and threshold phenomena in hydrological processes.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.40930528&41101096)the Chinese Academy of Sciences/State Administration for Foreign Experts Affairs International Partnership Program for Creative Research Teams of"Ecosystem Processes and Services"
文摘Vegetation cover pattern is one of the factors controlling hydrological processes. Spatially distributed models are the primary tools previously applied to document the effect of vegetation cover patterns on runoff and soil erosion. Models provide precise estimations of runoff and sediment yields for a given vegetation cover pattern. However, difficulties in parameterization and the problematic explanation of the causes of runoff and sedimentation rates variation weaken prediction capability of these models. Landscape pattern analysis employing pattern indices based on runoff and soil erosion mechanism provides new tools for finding a solution. In this study, the vegetation cover pattern was linked with runoff and soil erosion by two previously de- veloped pattern indices, which were modified in this study, the Directional Leakiness Index （DL[） and Flowlength. Although they use different formats, both indices involve connectivity of sources ,areas （interpatch bare areas）. The indices were revised by bringing in the functional heterogeneity of the plant cover types and the landscape position. Using both artificial and field verified vegetation cover maps, observed runoff and sediment production on experiment plots, we tested the indices＇ efficiency and compared the indices with their antecedents. The results illustrate that the modified indices are more effective in indicating runoff at the plot/hillslope scale than their antecedents. However, sediment export levels are not provided by the modified indices. This can be attributed to multi-factor interaction on the hydrological process, the feedback mechanism between the hydrological function of cover patterns and threshold phenomena in hydrological processes.
