Primary Productivity and Precipitation-Use Efficiency in Temperate Grassland in the Loess Plateau of China

Clarifying spatial variations in aboveground net primary productivity (ANPP) and precipitation-use efficiency (PUE) of grasslands is critical for effective prediction of the response of terrestrial ecosystem carbon and water cycle to future climate change. Though the combination use of remote sensing products and in situ ANPP measurements, we quantified the effects of climatic [mean annual precipitation (MAP) and precipitation seasonal distribution (PSD)], biotic [leaf area index (LAI)] and abiotic [slope gradient, aspect, soil water storage (SWS) and other soil physical properties] factors on the spatial variations in ANPP and PUE across different grassland types (i.e., meadow steppe, typical steppe and desert steppe) in the Loess Plateau. Based on the study, ANPP increased exponentially with MAP for the entire temperate grassland; suggesting that PUE increased with increasing MAP. Also PSD had a significant effect on ANPP and PUE; where more even PSD favored higher ANPP and PUE. Then MAP, more than PSD, explained spatial variations in typical steppe and desert steppe. However, PSD was the dominant driving factor of spatial variations in ANPP of meadow steppe. This suggested that in terms of spatial variations in ANPP of meadow steppe, change in PSD due to climate change was more important than that in total annual precipitation. LAI explained 78% of spatial PUE in the entire Loess Plateau temperate grassland. As such, LAI was the primary driving factor of spatial variations in PUE. Although the effect of SWS on ANPP and PUE was significant, it was nonetheless less than that of precipitation and vegetation. We therefore concluded that changes in vegetation structure and consequently in LAI and/or altered pattern of seasonal distribution of rainfall due to global climate change could significantly influence ecosystem carbon and water cycle in temperate grasslands.     

降水时间对内蒙古温带草原地上净初级生产力的影响

全球气候变化下降水时间的改变将深刻影响草原生态系统地上净初级生产力(ANPP),而草原生态系统ANPP是区域碳循环的重要过程.利用1998-2007年的SPOT-VEG NDVI数据并结合111个样点的ANPP地面样方调查数据,获得了内蒙古温带草原1998-2007年的ANPP区域数据,依此分析了中国内蒙古温带草原以及区域内的3种植被类型(荒漠草原、典型草原、草甸草原)降水时间对ANPP的影响.研究结果表明,对于整个内蒙古温带草原来说,一个水分年内(从上一年9月份到当年地上生物量达最大值时的8月份)影响ANPP较为重要的降水月份为2-7月份,其中,5-7月份降水尤为重要.具体到每个月降水的影响,研究发现,7月份降水最重要,而仍处于生长季的8月份降水相对于其他生长季降水作用最小;影响不同草地类型最重要的降水时期存在一定差异,对荒漠草原和典型草原地区来说,ANPP达最大值前3个月(5-7月份)的生长季降水最重要,而8月份降水影响较小,而草甸草原地区8月份和非生长季的3、4月份降水最重要,但各个降水时期降水对ANPP的影响都较荒漠草原和典型草原小,大部分地区降水对ANPP的影响不显著.     

荒漠草原与典型草原NPP、碳积累对不同降雨年份和利用方式的响应

不同草原利用方式正在影响着内蒙古的草原生态系统,而且在未来降水空间格局变化的背景下,它们共同决定了生态系统植被类型、净初级生产力(NPP)和生态系统碳积累。选取内蒙古中部两个重要的草地类型:荒漠草原和典型草原,研究不同草原利用方式(围栏禁牧、划区轮牧、割草、自由放牧)植物群落在降雨量不同的两个生长季节地上(ANPP)、地下净初级生产力(BNPP)的变化,同时也评估了植物群落的碳积累,研究结果表明:1)在降雨量亏缺年份,与围封相比,荒漠草原自由放牧区ANPP、BNPP及碳积累分别下降了57.1%、51.7%和56.0%,而典型草原自由放牧区分别下降了18.4%、25.1%和17.9%。2)在降雨量充足年份,与围封相比,荒漠草原划区轮牧区ANPP、BNPP以及碳积累分别增加了18.2%、9.8%和21.9%,而典型草原各处理下围封禁牧区ANPP仍是最高;3)两种草地类型下,降雨量对自由放牧的调控作用高于其它草地利用方式;4)荒漠草原ANPP在丰雨年是欠雨年的2倍,而典型草原仅增加了79.0%,降雨量对荒漠草原生产力的季节调控作用远高于典型草原。在未来全球气候变暖和降水格局变化的情况下,荒漠草原降雨量是影响荒漠植物群落NPP和碳积累的主导因子。     

The spatial pattern of grassland aboveground biomass on Xizang Plateau and its climatic controls

Aims Grassland is the most widely distributed vegetation type on the Xizang Plateau. Accurate remote sensing estimation of the grassland aboveground biomass (AGB) in this region is influenced by the types of vegetation indexes (VIs) used, the grain size (resolution) of the remote sensing data and the targeted ecosystem features. This study attempts to answer the following questions: (i) Which VI can most accurately reflect the grassland AGB distribution on the Xizang Plateau? (ii) How does the grain size of remote sensing imagery affect AGB reflection? (iii) What is the spatial distribution pattern of the grassland AGB on the plateau and its relationship with the climate?Methods We investigated 90 sample sites and measured site-specific AGBs using the harvest method for three grassland types (alpine meadow, alpine steppe and desert steppe). For each sample site, four VIs, namely, Normalized Difference VI (NDVI), Enhanced VI, Normalized Difference Water Index (NDWI) and Modified Soil-Adjusted VI (MSAVI) were extracted from the Moderate Resolution Imaging Spectroradiometer (MODIS) products with grain sizes of 250 m and 1 km. Linear regression models were employed to identify the best estimator of the AGB for the entire grassland and the three individual grassland types. Paired Wilcoxon tests were applied to assess the grain size effect on the AGB estimation. General linear models were used to quantify the relationships between the spatial distribution of the grassland AGB and climatic factors.Important findings The results showed that the best estimator for the entire grassland AGB on the Xizang Plateau was MSAVI at a 250 m grain size (MSAVI 250 m). For each individual grassland type, the best estimator was MSAVI at a grain size of 250 m for alpine meadow, NDWI at a grain size of 1 km for alpine steppe and NDVI at a grain size of 1 km for desert steppe. The explanation ability of each VI for the grassland AGB did not significantly differ for the two grain sizes. Based on the best fit model (AGB =^-10.80 + 139.13 MSAVI 250 m), the spatial pattern of the grassland AGB on the plateau was characterized. The AGB varied from 1 to 136g m ?2. Approximately 59% of total spatial variation in the AGB for the entire grassland was explained by the combination of the mean annual precipitation (MAP) and mean annual temperature. The explanatory power of MAP was weaker for each individual grassland type than that for the entire grassland. This study illustrated the high efficiency of the VIs derived from MODIS data in the grassland AGB estimation on the Xizang Plateau due to the vegetation homogeneity within a 1×1 km pixel in this region. Furthermore, MAP is a primary driver on the spatial variation of AGB at a regional scale.     

内蒙古温带草原土壤微生物生物量碳的空间分布及驱动因素

【目的】探索内蒙古温带草原土壤微生物生物量碳的空间分布特征以及驱动因素。【方法】在内蒙古自治区境内沿着年均温、年降水梯度选择17个草原样点,在土壤剖面上分0-10 cm、10-20 cm、20-40 cm、40-60 cm、60-100 cm五层,分别采集土壤样品,测定土壤微生物生物量碳以及主要的环境和生物影响因子,分析不同草地类型以及不同土壤深度土壤微生物生物量碳的差异,探索非生物因子和生物因子对土壤微生物量碳的影响。【结果】草甸草原土壤微生物量碳最高,典型草原次之,荒漠草原最低。在0-10 cm土壤中,草地类型间的微生物量碳变异系数高于草甸草原和典型草原,低于荒漠草原;在0-100 cm土壤中,草甸草原样点间的微生物量碳的变异系数低于典型草原和荒漠草原。土壤微生物量碳与年降水、土壤含水量、粘粒含量、土壤养分元素、地上生物量、地下生物量呈显著正相关,与年均温和土壤p H值呈显著负相关关系。随着土壤深度的增加,土壤微生物量碳显著减少,非生物因子与微生物量碳的相关性减弱,草地类型间以及同一草地类型不同样点间的变异系数增加。0-10 cm土壤微生物量碳与10-40 cm土壤微生物量碳的相关指数高于0.5,与40-100 cm的土壤微生物量碳的相关指数小于0.3。【结论】内蒙古温带草原土壤微生物量碳的垂直分布呈现一定的规律性,且非生物因子对微生物量碳的影响也呈现垂直减弱的规律。     

Trends in extreme climatic indices across the temperate steppes of China from 1961 to 2013

Aims Extreme climate events have become more severe and frequent with global change in recent years. The Chinese temperate steppes are an important component of the Eurasian steppes and highly sensitive and vulnerable to climatic change. As a result, the occurrence of extreme climate events must have strong impacts on the temperate steppes. Therefore, understanding the spatio-temporal trends in extreme climate is important for us to assess the sensitivity and vulnerability of Chinese temperate steppes to climatic changes. This research had two specific objects to (i) specify the temporal changes in extreme climate events across the whole steppe and (ii) compare the trend differences for extreme climate events in different types of steppes—meadow steppe, typical steppe and desert steppe.     

1982-2010年中国草地净初级生产力时空动态及其与气候因子的关系

植被净初级生产力（NPP）及其与气候变化的响应研究是全球变化的核心内容之一。论文基于长时间序列遥感数据和气象数据,通过光能利用率模型（Carnegie-Ames-Stanford approach, CASA模型）模拟了1982-2010 年中国草地NPP,进而分析其时空变化特征及其与气候水热因子的相关性。结果表明：（1）1982-2010年中国草地年平均NPP为282.0 gC m^-2a^-1,年总NPP的多年平均值为988.3 TgC;空间分布上呈现东南部高西北部低的特征。（2）近30年中国草地NPP增加速率为0.6 gC m^-2a^-1,呈增加趋势的面积占中国草地总面积的67.2%;总体上,中国草地NPP呈极显著和显著增加的比例（35.8%、8.0%）大于呈极显著和显著减少的比例（5.8%、4.8%）;NPP明显增加的区域主要包括青藏高原西部、阿拉善高原、新疆西部;明显降低的区域主要分布在内蒙古地区;不同年代际和不同草地类型的NPP变化趋势差异明显。（3）草地NPP与降水量的相关性高于与温度的相关性。不同草地类型NPP对气温、降水量的响应程度不同,其中温性荒漠草原 、温性草原、温性草甸草原的NPP与降水量均达到显著正相关（P<0.05）。     

Relationship of Productivity to Species Richness in the Xinjiang Temperate Grassland

The relationship between species richness (SR) and aboveground net primary productivity (ANPP) is still a central and debated issue in community ecology. Previous studies have often emphasized the relationship of alpha diversity (number of species identity) to the mean ANPP with respect to the SR-ANPP relationship while neglecting the contribution of beta diversity (dissimilarity in species composition) to the mean ANPP and to the stability of ANPP (coefficient of ANPP: CV of ANPP). In this study, we used alpha and beta diversity, mean ANPP and the CV of ANPP collected from 159 sites and belonging to three vegetation types in the Xinjiang temperate grassland to first examine their trends along climatic factors and among different vegetation types and then test the relationship among alpha (beta) diversity and mean ANPP and the CV of ANPP. Our results showed that in the Xinjiang temperate grasslands, alpha diversity was positively and linearly correlated with MAP but unimodally correlated with MAT. Meanwhile, beta diversity was unimodally correlated with MAP but linearly correlated with MAT. Relative to desert steppe, meadow steppe and typical steppe had the highest alpha and beta diversity, respectively. Except for ANPP exhibiting a quadratic relationship with MAP, no significant relationship was found among ANPP, the CV of ANPP and climatic factors. ANPP and the CV of ANPP also exhibited no apparent patterns in variation among different vegetation types. Our results further showed that mean ANPP was closely associated with alpha diversity. Both linear and unimodal relationships were detected between alpha diversity and mean ANPP, but their particular form was texture-dependent. Meanwhile, the CV of ANPP was positively correlated with beta diversity. Our results indicated that in addition to incorporating alpha diversity and mean ANPP, incorporating beta diversity and the CV of ANPP could expand our understanding of the SR-ANPP relationship.     

内蒙古中西部优势植物春季返青对降水的非线性响应

长期以来,研究植被物候变化与气候因子的关系多基于线性模型,事实上植被物候对气候变化的响应可能是非线性的。以1984-2017年内蒙古中西部温性典型草原和温性草原化荒漠长时间序列植被物候观测资料为基础,分析了近40年来气候变化背景下不同草地类型优势植物返青期变化特征及其对春季降水的非线性响应。结果表明：（1）温性典型草原冷蒿返青期主要受水分控制,与春季降水量表现为开口向下的二次函数关系。气候暖干化导致的水分亏缺是冷蒿返青期呈极显著延迟趋势（1.32 d/a）的主要原因;春季降水量超过60 mm时,冷蒿返青期表现出由延迟转变为提前的趋势。（2）温性草原化荒漠猫头刺返青期主要受热量控制。受春季显著升温影响,猫头刺返青期呈极显著提前趋势（0.63 d/a）。春季降水增多利于猫头刺提早返青,二者表现为开口向上的二次函数关系;春季降水量超过40 mm时,猫头刺返青期对降水的响应程度逐渐降低,这可能与荒漠植物本身的生理特性有关。     

气候变化和人为活动在宁夏草地变化中的相对作用

气候变化和人为活动是草地生态系统退化或恢复过程中的两大驱动因素。选取植被净初级生产力（NPP）为衡量指标,利用改进的Carnegie-Ames-Stanford Approach （CASA）模型、Thornthwaite Memorial模型以及残差趋势法分别计算了宁夏草地实际净初级生产力（ANPP）、潜在净初级生产力（PNPP）和人为活动影响的生产力（HNPP）及其变化趋势,定量评估了2001-2019年气候变化和人为活动在宁夏4种类型草地（温性草甸、温性草原、温性荒漠草原和温性草原化荒漠）动态变化中的相对作用。结果表明,2001-2019年宁夏草地实际净初级生产力增加的面积占宁夏草地总面积的97.84%;全区草地潜在净初级生产力均表现为增加趋势,表明气候变化有利于植被恢复。草地恢复过程中,气候变化引起的草地恢复面积占草地恢复总面积的61.68%,气候变化和人为活动共同作用引起的草地恢复面积占38.32%;人为活动是导致草地退化的绝对主导因素。4种类型草地动态变化的驱动因素存在差异,气候变化是促进温性草甸（68.94%）和温性草原化荒漠（70.51%）恢复的主导因素,气候变化和人为活动共同作用是促进温性草原恢复的主导因素（62.30%）,温性荒漠草原的恢复是气候变化和人为活动共同作用的结果（97.93%）。水热条件好转,尤其是降水增加是宁夏草地恢复的主导气候因子,生态保护政策的实施是促进草地恢复的主要人为因素,对草地的不合理利用是导致草地退化的主要人为因素。