The driving effects of climate change and human activities on vegetation NPP (net primary productivity) is known as a research hotspot in the context of global climate change, of which the consensus cannot be reached at different spatiotemporal scales. The vegetation ecosystem in cold and arid pastoral areas of northwest China is fragile and highly sensitive to climate change and human activities. In this study, Wulan County, Qinghai Province was taken as the representative study area. Based on the long sequence NDVI (normalized difference vegetation index) dataset constructed by GIMMS-NDVI and MOD-NDVI, combined with the CASA (carnegie-ames-stanford approach) model, the vegetation growing season NPP of the study area from 1982 to 2020 was obtained. The spatiotemporal evolution characteristics of growing season NPP in the study area over the past 40 years were explored using the Sen+MK method, and then the proposed quantitative attribution method of ADE+Sen was used to quantitatively identify the driving forces of different climate factors and human activities to the dynamics of growing season NPP. The results showed that the annual mean of growing season NPP in the study area was (205.9±11.5) g/(m2·a) (measured in C), and the interannual variation of growing season NPP had no significant trend. The interannual variation of growing season NPP for different vegetation types was basically consistent with the regional growing season NPP. Over the space, the multi-year mean of growing season NPP gradually increased from west to east. The change patterns of growing season NPP exhibited significant spatial heterogeneity and were mainly characterized by degradation with the average rate of -0.151 g/(m2·a2). The areas with severe and slight degradation accounted for 31.7% and 29.5%, respectively. Climate change was the dominant driving factor for the dynamics of growing season NPP, with a dominant vegetation area accounting for 85.2%. The absolute average value of the contribution of climate change was 1.025 g/(m2·a2), which was nearly twice the absolute average value of the contribution of human activities. Solar radiation, precipitation, average temperature, and average wind speed were the main climate factors affecting the dynamics of growing season NPP. In conclusion, the vegetation in the study area was mainly in a degraded state, and climate change was the dominant driving factor leading to this phenomenon. The findings can provide reference for the sustainable utilization and protection of vegetation ecosystem in cold and arid pastoral areas of northwest China.
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Modeling the soil evaporation under vegetation conditions is of theoretical and practical significance for water resources management in the Loess Plateau. In this study, a three-year field experiment was conducted in a bare land and three grasslands to measure soil evaporation using micro-lysimeters. The Van Bavel-Hillel model was then validated in the bare land. Based on this, the vegetation coverage resistance was proposed to reflect the comprehensive effects of vegetation, and it was applied into the Van Bavel-Hillel model to improve the model’s applicability under vegetation conditions. The results showed that the Van Bavel-Hillel model was effective in simulating evaporation from bare land, and the application of validated soil surface resistance and vegetation coverage resistance can make it perform well in the evaporation simulation in all studied grasslands. The obtained vegetation coverage resistances decreased linearly with the increase of soil moisture contents in all three grasslands, and the decreasing rates were similar in the M. sativa and P. giganteum plots, which were higher than that in the I. cylindrica plot. Soil surface resistances ranged between 533.4-746.5, 767.4-1154.7, and 133.4-1334.5 s/m in the I. cylindrica, M. sativa, and P. giganteum plots, respectively, and all showed the characteristics of first increasing and then decreasing during the growing season. When compared with natural grassland, M. sativa increased the soil surface resistance in all months, while P. giganteum reduced it in the early growing season, but increased it in the middle and late growing season. This research proposes a new idea for the simulation of soil evaporation under vegetated conditions, and provides a basic reference for water resources management in the vegetation restoration of the Loess Plateau.
In order to protect the ecological environment of China’s alpine desert steppe and guide the comprehensive and sustainable development of grassland pastoral areas, this study took the alpine desert steppe as the research object, and the optimization simulation calculation and dynamic balance analysis of grassland and livestock were carried out.
In this paper, based on the characteristics of seasonal rotational grazing and livestock production rhythms, the spatial and temporal segregation of grassland resources and the dynamic changes in livestock numbers were considered, and the two pasture grazing time periods of warm season and cold season were refined. On the basis of the existing reasonable livestock carrying capacity calculation method, the maximum livestock carrying capacity was the goal, the dynamic grass-livestock balance was the constraint, and the turnout time and slaughter rate were the optimization parameters. A grazing-management optimization model was established, and the Ulan County Pastoral area of Qinghai Province was selected as the typical representative of alpine desert seasonal pastoral area. Based on the genetic algorithm optimization, the optimal grazing conditions under the three precipitation scenarios of wet, normal and dry in the pastoral area of Ulan County were determined, a simulation to optimize the forage-livestock balance and dynamic forage-livestock balance analysis was carried out, and then the results with those before optimization were compared.
The simulation results of the grazing-management optimization model were better for different precipitation scenarios in the grazing area. Based on the lowest amount of unutilized forage, the optimal grazing conditions under the three precipitation scenarios of wet, normal and dry in the pastoral area of Ulan County were determined to be the transition of livestocks on November 1 with a slaughter rate of 43.4%, the transition of livestocks on November 3 with a slaughter rate of 38.2% and the transition of livestocks on November 3 with a slaughter rate of 36.7%, respectively. The optimal proper carrying capacity was 1.099 million sheep unit, 0.961 million sheep unit and 0.836 million sheep unit in high, normal, and low flow years, respectively, which were 11.75%, 10.44% and 10.43% higher than the proper carrying capacity before optimization, respectively. In addition to the livestock slaughter rate and the transition time, the precipitation was also an important factor affecting the proper carrying capacity in pastoral areas. Before and after optimization, the proper carrying capacity of Ulan County’s pastoral area in wet years was 0.983 and 1.099 million sheep unit, respectively, which was 30% higher than the proper carrying capacity of 0.757 and 0.836 million sheep unit in dry years, respectively. Through the analysis of pasture grass production process and livestock dynamic grass demand process, the dynamic grass-livestock balance calculation for the normal flow year in the pasture area of Ulan County was found that the available forage in the cold season pasture before optimization could not be fully utilized, the grazing process was unreasonable, and the surplus grass amount was more than 61.3 million kg, while after optimization, the problem of underutilization of available forage was effectively solved and the forage resources were efficiently utilized. For the whole grazing area of Ulan County, the adjusting grazing turnout time and livestock slaughter rate was a reliable way to improve the grazing system. The grazing-management optimization model was used to optimize the grazing process in the grazing area, which could ensure the high proper annual carrying capacity in the grazing area while being able to achieve a dynamic grass-livestock balance in the seasonal grazing area.
The grazing-management optimization had the good applicability to alpine desert seasonal pasturing areas and had the certain superiority in the regulation of grazing management process and the optimization of forage-livestock balance in rotating pastoral areas. The grazing-management optimization model could effectively regulate the livestock carrying capacity of a grazing area, and its optimization results could provide reference for the development of a reasonable grazing system. Therefore, the model could be used to optimize the grazing process of a single herding household or ranch, to obtain the optimal grazing conditions for a single herding household or ranch, so as to develop the corresponding grazing system, which was more practical guidance and operability for the production practice of a single herding household or ranch.
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