青藏高原高寒草甸土壤N_2O排放通量对温度和湿度的响应

试验采用室内培养的方法研究了青藏高原矮嵩草草甸土壤氧化亚氮(N2O)排放通量对土壤温度和湿度的响应过程。结果表明:随培养温度增加,培养初期矮嵩草草甸土壤N2O排放速率逐渐降低(P<0.05),最高排放速率为4.75±0.24g/(kg·h),最低排放速率仅为2.92±0.19g/(kg·h);而经过7d培养,高寒草甸土壤N2O排放速率先降低,而且转变为弱汇,而后升高,30℃时最高,为0.67±0.06g/(kg·h),各处理均显著低于短期培养时排放速率(P<0.05);随土壤湿度增加,短期培养矮嵩草草甸土壤N2O排放速率先降低随后升高,在土壤湿度为60%时排放速率最高,为(3.62±0.38)g/(kg·h),而在75%时排放速率最低,为(3.38±0.25)g/(kg·h);随着培养时间延长,高寒草甸土壤N2O排放速率逐渐降低,最高排放速率为(0.55±0.32)g/(kg·h);土壤湿度分别为45%和温度为20℃、以及60%和30℃时,1d和7d培养矮嵩草草甸土壤N2O排放速率最高;而在土壤湿度为45%和30℃、以及75%和30℃时,1d和7d培养矮嵩草草甸土壤N2O排放速率最低,后者呈现吸收现象,吸收速率约为-1.84g/(kg·h)。

家畜微量元素补饲的研究及进展

家畜补饲一直是养殖业界人士所关注的重点之一.长期以来,为提高畜产品量,在人们不断的研究中,出现了各种不同的补饲技术.本文在简要介绍家畜补饲技术历史的同时,重点介绍了目前国际上最新最为流行的补饲技术———微量元素氨基酸鳌合物技术.

Temporal and Spatial Distribution of Evapotranspiration and Its Influencing Factors on Qinghai-Tibet Plateau from 1982 to 2014

Evapotranspiration is the key driving factor of the earth’s water cycle, and an important component of surface water and energy balances. Therefore, it also reflects the geothermal regulation function of ecohydrological process. The Qinghai-Tibet Plateau is the birthplace of important rivers such as the Yangtze River and the Yellow River. The regional water balance is of great significance to regional ecological security. In this study, ARTS, a dualsource remote sensing evapotranspiration model developed on a global scale, is used to evaluate the actual evapotranspiration(ET) in the Qinghai-Tibet Plateau from 1982 to 2014, using meteorological data interpolated from observations, as well as FPAR and LAI data obtained by satellite remote sensing. The characteristics of seasonal. interannual and dynamic changes of evapotranspiration were analyzed. The rates at which meteorological factors contribute to evapotranspiration are calculated by sensitivity analysis and multiple linear regression analysis,and the dominant factors affecting the change of evapotranspiration in the Qinghai-Tibet Plateau are discussed.The results show that:(1) The estimated values can explain more than 80% of the seasonal variation of the observed values(R^2 = 0.80, P < 0.001), which indicates that the model has a high accuracy.(2) The evapotranspiration in the whole year, spring, summer and autumn show significant increasing trends in the past 30 years, but have significant regional differences. Whether in the whole year or in summer, the southern Tibetan Valley shows a significant decreasing trend(more than 20 mm per 10 years), while the Ali, Lhasa Valley and Haibei areas show increasing trends(more than 10 mm per 10 years).(3) Sensitivity analysis and multiple linear regression analysis show that the main factor driving the interannual change trend is climate warming, followed by the non-significant increase of precipitation. However, vegetation change also has a considerable impact, and together with climate factors, it can explain 56% of the interannual variation of evapotranspiration(multiple linear regression equation R^2= 0.56, P < 0.001). The mean annual evapotranspiration of low-cover grassland was 26.9% of high-cover grassland and 21.1% of medium-cover grassland, respectively. Considering significant warming and insignificant wetting in the Qinghai-Tibet Plateau, the increase of surface evapotranspiration will threaten the regional ecological security at the cost of glacial melting water. Effectively protecting the ecological security and maintaining the sustainable development of regional society are difficult and huge challenges.

Climatic Changes Dominant Interannual Trend in Net Primary Productivity of Alpine Vulnerable Ecosystems

The Three-River Headwaters(TRH), which is the source area of Yangtze River, Yellow River and Lancang River, is vulnerable and sensitive, and its alpine ecosystem is considered an important barrier for China’s ecological security. Understanding the impact of climate changes is essential for determining suitable measures for ecological environmental protection and restoration against the background of global climatic changes. However, different explanations of the interannual trends in complex alpine ecosystems have been proposed due to limited availability of reliable data and the uncertainty of the model itself. In this study, the remote sensing-process coupled model(GLOPEM-CEVSA) was used to estimate the net primary productivity(NPP) of vegetation in the TRH region from 2000 to 2012. The estimated NPP significantly and linearly correlated with the above-ground biomass sampled in the field(the multiple correlative coefficient R2 = 0.45, significant level P < 0.01) and showed better performance than the MODIS productivity product, i.e. MOD17 A3,(R2 = 0.21). The climate of TRH became warmer and wetter during 1990-2012, and the years 2000 to 2012 were warmer and wetter than the years1990–2000. Responding to the warmer and wetter climate, the NPP had an increasing trend of 13.7 g m^–2(10 yr)^–1 with a statistical confidence of 86%(P = 0.14). Among the three basins, the NPP of the Yellow River basin increased at the fastest rate of 17.44 g m^–2(10 yr)^–1(P = 0.158), followed by the Yangtze River basin, and the Lancang River, which was the slowest with a rate of 12.2 g m^–2(10 yr)^–1 and a statistical confidence level of only 67%. A multivariate linear regression with temperature and precipitation as the independent variables and NPP as the dependent variable at the pixel level was used to analyze the impacts of climatic changes on the trend of NPP. Both temperature and precipitation can explain the interannual variability of 83% in grassland NPP in the whole region, and can explain high, medium and low coverage of 78%, 84% and 83%, respectively, for grassland in the whole region. The results indicate that climate changes play a dominant role in the interannual trend of vegetation productivity in the alpine ecosystems on Qinghai-Tibetan Plateau. This has important implications for the formulation of ecological protection and restoration policies for vulnerable ecosystems against the background of global climate changes.

Review of Methods to Quantify Trade-offs among Ecosystem Services and Future Model Developments

Ecosystem services are spatially heterogeneous and temporal variability, which results in trade-offs,synergies and neutrality. The trade-off is a key problem in ecosystem management and requires optimized decision-making research. This paper reviews methods for identifying trade-offs and suggest future model developments. We conclude that(1) ecosystem service assessment depends on quantitative indicators and its modeling;(2)scenario analysis, multi-objective analysis and production possibility boundary are an effective means of ecosystem service trade-off decision-making;(3) future research needs to strengthen ecosystem service supply and demand flow and assist decision-making ecosystem mapping. Finally, integrated models should be developed to simulate and diagnose different scenarios and to optimize measures in land and ecosystem management for sustainability.