黑河上游山地土壤容重分布特征及影响因素

土壤容重不仅可用作计算土壤持水力和导水性,也是估算土壤养分和碳储量的重要变量。野外测定土壤容重一般费时费力,特别是在地形复杂的山区,因此山地土壤容重在国内外大多数清查数据库中缺失。本文以黑河上游山地为例,基于野外调查的124个土壤剖面,研究了山地土壤容重的空间分布特征及影响因素。结果表明:黑河上游山地0~10 cm和0~60 cm土壤容重分别为0.91±0.02 g·cm^-3 和1.04±0.01 g·cm^-3;不同植被类型下,高山寒漠容重最大,山地森林最小。随着土壤深度的增加,容重呈幂函数递增;随着土壤有机质含量的增加,容重呈指数递减。区域上,黑河上游从西北到东南,容重呈递减趋势,从高海拔到低海拔,容重呈先减小后增大趋势。主成分分析(PCA)和一般线性模型(GLM)表明,与土壤容重相关的环境因子中,海拔是影响土壤表层容重的第一主成分,土壤有机质含量是第二主成分,黏粒含量和大于2.0 mm砾石含量分别为第三、四主成分。第一、二、三、四主成分分别解释土壤容重空间变异的24.00%、29.40%、0.01%、6.20%。     

The spatial local accuracy of land cover datasets over the Qiangtang Plateau,High Asia

We analyzed the spatial local accuracy of land cover (LC) datasets for the Qiangtang Plateau, High Asia, incorporating 923 field sampling points and seven LC compilations including the International Geosphere Biosphere Programme Data and Information System (IGBPDIS), Global Land cover mapping at 30 m resolution (GlobeLand30), MODIS Land Cover Type product (MCD12Q1), Climate Change Initiative Land Cover (CCI-LC), Global Land Cover 2000 (GLC2000), University of Maryland (UMD), and GlobCover 2009 (Glob-Cover). We initially compared resultant similarities and differences in both area and spatial patterns and analyzed inherent relationships with data sources. We then applied a geographically weighted regression (GWR) approach to predict local accuracy variation. The results of this study reveal that distinct differences, even inverse time series trends, in LC data between CCI-LC and MCD12Q1 were present between 2001 and 2015, with the exception of category areal discordance between the seven datasets. We also show a series of evident discrepancies amongst the LC datasets sampled here in terms of spatial patterns, that is, high spatial congruence is mainly seen in the homogeneous southeastern region of the study area while a low degree of spatial congruence is widely distributed across heterogeneous northwestern and northeastern regions. The overall combined spatial accuracy of the seven LC datasets considered here is less than 70%, and the GlobeLand30 and CCI-LC datasets exhibit higher local accuracy than their counterparts, yielding maximum overall accuracy (OA) values of 77.39% and 61.43%, respectively. Finally, 5.63% of this area is characterized by both high assessment and accuracy (HH) values, mainly located in central and eastern regions of the Qiangtang Plateau, while most low accuracy regions are found in northern, northeastern, and western regions.

     

Spatial patch structure and adaptive strategy for desert shrub of Reaumuria soongorica in arid ecosystem of the Heihe River Basin

In many arid ecosystems, vegetation frequently occurs in high-cover patches interspersed in a matrix of low plant cover. However, theoretical explanations for shrub patch pattern dynamics along climate gradients remain unclear on a large scale. This context aimed to assess the variance of the Reaumuria soongorica patch structure along the precipitation gradient and the factors that affect patch structure formation in the middle and lower Heihe River Basin (HRB). Field investigations on vegetation patterns and heterogeneity in soil properties were conducted during 2014 and 2015. The results showed that patch height, size and plant-to-patch distance were smaller in high precipitation habitats than in low precipitation sites. Climate, soil and vegetation explained 82.5% of the variance in patch structure. Spatially, R. soongorica shifted from a clumped to a random pattern on the landscape towards the MAP gradient, and heterogeneity in the surface soil properties (the ratio of biological soil crust (BSC) to bare gravels (BG)) determined the R. soongorica population distribution pattern in the middle and lower HRB. A conceptual model, which integrated water availability and plant facilitation and competition effects, was revealed that R. soongorica changed from a flexible water use strategy in high precipitation regions to a consistent water use strategy in low precipitation areas. Our study provides a comprehensive quantification of the variance in shrub patch structure along a precipitation gradient and may improve our understanding of vegetation pattern dynamics in the Gobi Desert under future climate change.

     

Developing a comprehensive evaluation method for Interconnected River System Network assessment: A case study in Tangxun Lake group

Journal of Geographical Sciences - The Interconnected River System Network (IRSN) plays a crucial role in water resource allocation, water ecological restoration and water quality improvement. It...     

Does geographic distance have a significant impact on enterprise financing costs?

Journal of Geographical Sciences - As information technology has been applied more broadly and transportation infrastructure has improved, persistent debate has existed as to the question of...     

Multiscale geographically and temporally weighted regression: exploring the spatiotemporal determinants of housing prices

Understanding scale effects is important and indispensable for geography studies. However, spatial and spatiotemporal statistical tools for measuring the operational scales of different processes are rather limited. This article extends the popular geographically and temporally weighted regression (GTWR) model to consider operational scale effects by proposing multiscale GTWR (MGTWR), which offers a flexible and scalable framework for identifying and analysing multiscale processes by specifying flexible bandwidths for various covariates. Then, MGTWR is employed to explore spatiotemporal variations and how influential factors are associated with housing prices in Shenzhen. This article attempts to extend GTWR to MGTWR in consideration of scale effects, thereby highlighting the importance of different levels of spatiotemporal heterogeneity. Furthermore, the empirical results of this study can provide valuable policy implications for real estate development in areas where urban planning should address multiscale effects in both temporal and spatial dimensions.     

Novel Hybrid Integration Approach of Bagging-Based Fisher’s Linear Discriminant Function for Groundwater Potential Analysis

Natural Resources Research - Groundwater is a vital water source in the rural and urban areas of developing and developed nations. In this study, a novel hybrid integration approach of...     

Responding to Global Warming: Mitigation Policies and Actions of Stakeholders in China’s Tourism Industry

China’s tourism industry has witnessed rapid progress in recent years, and is now an important part of global tourism in dealing with climate change. Within a framework of Pressure-State-Response (PSR), this paper focuses on the emission reduction pressure, carbon emission status, and responses of stakeholders in China’s tourism industry. Findings include: 1) The central government’s strategy and rapid growth of the industry scale exert rising pressure on China’s tourism to reduce carbon emissions. 2) Carbon emissions of China's tourism account for 13%-14.6% of global tourism, and about 3% of China’s emissions overall. Chinese tourists’ per capita carbon emission is lower than half of the global level. 3) The Chinese government attaches great importance to energy-saving and carbon emission reduction. In the tourism industry, documents, standards and other regulative measures have been issued to ensure that business practitioners set up green operational and managerial systems. In the field of tourism transportation, China's high-speed rail, new energy vehicles, and urban shared bicycles, have developed very rapidly in recent years, and they have effectively reduced the carbon emissions in traveling. Furthermore, this paper finds that Chinese tourists already have awareness and willingness for low-carbon tourism.     

中国半干旱草原施氮梯度下的土壤激发效应（英文）

为了探究施氮对土壤有机质(SOM)的激发效应,本研究在施氮梯度样地(0、4和16 g N m^–2 yr^–1)上进行了¹³C标记葡萄糖的原位添加实验,并对土壤CO_2排放量和磷脂脂肪酸(PLFA)含量进行了测定。研究发现施氮降低了土壤CO_2排放、土壤PLFA含量以及土壤真菌细菌比。在0 g N m^–2 yr^–1样地上葡萄糖添加导致的正向激发效应最强,同时4 g N m^–2 yr^–1样地释放的葡萄糖来源的碳最多。因此,施氮减少了土壤中SOM转化产生的CO_2,微生物碳的来源由SOM转变为添加的易分解碳。本研究采样早期土壤微生物生物量和群落结构稳定,表明该草原存在"表观激发效应",因此未来研究应着重对微生物功能的多样性进行探讨。     

Response of Microbial Communities in Soil to Multi-level Warming in a Highland Barley System of the Lhasa River

No studies have examined the effect of experimental warming on the microbial biomass and community composition of soil in agricultural ecosystem on the Qinghai-Tibet Plateau. Thus it is unclear whether the influences of experimental warming on microbial communities in soil are related to warming magnitude in croplands on this Plateau. This study performed warming experiment (control, low- and high-level) in a highland barley system of the Lhasa River in May 2014 to examine the correlation between the response of microbial communities in soil to warming and warming magnitude. Topsoil samples (0-10 and 10-20 cm) were collected on September 14, 2014. Experimental warming at both low and high levels significantly increased soil temperature by 1.02 ℃ and 1.59 ℃, respectively at the depth of 15 cm. Phospho lipid fatty acid (PLFA) method was used to determine the microbial community in soil. The low-level experimental warming did not significantly affect the soil’s total PLFA, fungi, bacteria, arbuscular mycorrhizal fungi (AMF), actinomycetes, gram-positive bacteria (G⁺), gram-negative bacteria (G^-), protozoa, the ratio of fungi to bacteria (F/B ratio), and ratio of G⁺ to G^- (G⁺/G^- ratio) at the 0-10 and 10-20 cm depth. The low-level experimental warming also did not significantly alter the composition of microbial community in soil at the 0-10 and 10-20 cm depth. The high-level experimental warming significantly increased total PLFA by 74.4%, fungi by 78.0%, bacteria by 74.0%, AMF by 66.9%, actinomycetes by 81.4%, G⁺ by 67.0% and G^- by 74.4% at the 0-10 cm depth rather than at 10-20 cm depth. The high-level experimental warming significantly altered microbial community composition in soil at the 0-10 cm depth rather than at 10-20 cm depth. Our findings suggest that the response of microbial communities in soil to warming varied with warming magnitudes in the highland barley system of the Lhasa River.