Monitoring the dynamics of vegetation growth and its response to climate change is important to understand the mechanisms underlying ecosystem behaviors. This study investigated the relationship between vegetation growth and climate change during the growing seasons on the Loess Plateau in China by analyzing the normalized difference vegetation index (NDVI) derived from the Land Long Term Data Record dataset from 1982 to 2011. Results showed that growing-season NDVI had increased at an annual rate of 0.0028, particularly in the semi-arid and semi-humid regions. By contrast, the NDVI first increased from 1982 to 1994 (0.0013 year?1, P < 0.05) and then decreased from 1994 to 2011 (0.0016 year?1, P < 0.05) in the arid region. Temperature had a positive effect on NDVI in most periods within and across seasons in the semi-humid region but had no significant effect in the arid region. Precipitation had a positive effect on NDVI in the arid region in summer and in the semi-arid region in autumn. Summer precipitation was important for autumn vegetation growth in the arid region, whereas summer temperature increased autumn vegetation growth in the semi-arid and semi-humid regions. Further analyses supported the lag-time effects of climate change on vegetation growth on the Loess Plateau. Precipitation shifts had 15- to 18-month time lag effects on vegetation growth in the three climate regions. Vegetation NDVI had a 17-month lag response to temperature in the semi-arid region. Human activities should not be neglected in analyzing the relationship between vegetation growth and climate change on the Loess Plateau. 相似文献
The optimal allocation of sediment resources needs to balance three objectives including ecological, economic, and social benefits so as to realize sustainable development of sediment resources. This study aims to apply fuzzy programming and bargaining approaches to solve the problem of optimal allocation of sediment resources. Firstly, Pareto-optimal solutions of multi-objective optimization were introduced, and the multi-objective optimal allocation model of sediment resources and fuzzy programming model was constructed. Then, from the perspective of multiplayer cooperation, the optimal allocation model of sediment resources was transformed into a game model by using Nash bargaining, and Nash bargaining solution was obtained as the optimal equilibrium strategy. Finally, the influence of different disagreement utility points and bargaining weights on the results was discussed, and the results of Nash bargaining and fuzzy programming methods were compared and analyzed. Results corroborate that Nash bargaining can achieve the cooperative optimization of multiple objectives with competitive relationship and obtain satisfactory scheme. Disagreement utility points and bargaining weights have a certain impact on the optimization results. The solution of fuzzy programming is close to that of Nash bargaining, which provides different ideas for multi-objective optimization problem.