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Abstract In recent decades, terrestrial vegetation in the northern hemisphere (NH) has been exposed to warming and more extremely high temperatures. However, the consequences of these changes for terrestrial vegetation growth remain poorly quantified and understood. By examining a satellite-based vegetation index, tree-ring measurements and land-surface model simulations, we discovered a consistent convex pattern in the responses of vegetation growth to temperature exposure (TE) for forest, shrub and grass in both the temperate (30°−50° N) and boreal (50°−70° N) NH during the period of 1982−2012. The response of vegetation growth to TE for the three vegetation types in both the temperate and boreal NH increased convergently with increasing temperature, until vegetation type-dependent temperature thresholds were reached. A TE beyond these temperature thresholds resulted in disproportionately weak positive or even strong negative responses. Vegetation growth in the boreal NH was more vulnerable to extremely high-temperature events than vegetation growth in the temporal NH. The non-linear responses discovered here provide new insights into the dynamics of northern terrestrial ecosystems in a warmer world.
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Abstract Despite the importance of net primary productivity (NPP) and net biome productivity (NBP), estimates of NPP and NBP for China are highly uncertain. To investigate the main sources of uncertainty, we synthesized model estimates of NPP and NBP for China from published literature and the Multi‐scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP). The literature‐based results showed that total NPP and NBP in China were 3.35 ± 1.25 and 0.14 ± 0.094 Pg C yr −1 , respectively. Classification and regression tree analysis based on literature data showed that model type was the primary source of the uncertainty, explaining 36% and 64% of the variance in NPP and NBP, respectively. Spatiotemporal scales, land cover conditions, inclusion of the N cycle, and effects of N addition also contributed to the overall uncertainty. Results based on the MsTMIP data suggested that model structures were overwhelmingly important (>90%) for the overall uncertainty compared to simulations with different combinations of time‐varying global change factors. The interannual pattern of NPP was similar among diverse studies and increased by 0.012 Pg C yr −1 during 1981–2000. In addition, high uncertainty in China's NPP occurred in areas with high productivity, whereas NBP showed the opposite pattern. Our results suggest that to significantly reduce uncertainty in estimated NPP and NBP, model structures should be substantially tested on the basis of empirical results. To this end, coordinated distributed experiments with multiple global change factors might be a practical approach that can validate specific structures of different models. , Key Points Large uncertainty exists in estimates of terrestrial NPP and NBP in China Methodological differences greatly contribute to the uncertainty in NPP and NBP Uncertainty in the interannual pattern of NBP is greater than that of NPP