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...     

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...     

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.     

Farmland Abandonment Research Progress: Influencing Factors and Simulation Model

Farmland abandonment is a global problem and considered one of the most important areas in land use change research. Farmland abandonment research currently focuses on understanding the factors that affect farmland abandonment and developing scientific models to simulate farmland abandonment. The study reviewed the natural and political factors driving farmland abandonment and summarized the main models for farmland abandonment simulation together with their advantages and disadvantages. We discuss the main ecological effects of farmland abandonment and propose farmland abandonment research directions. The study found that: (1) the influence of labor cost change and ageing labor force on farmland abandonment needs further investigation, (2) simulation models for farmland abandonment must include the decision-making mechanism of individual farmers and focus on macro large-scale abandonment prediction models, and (3) the influence of farmland abandonment on landscape culture must be investigated in detail.     

Species Abundance Distribution Patterns of a Toona ciliata Community in Xingdoushan Nature Reserve

With the goal of model fitting species abundance distribution patterns of the tree, shrub and herb layers of the natural Toona ciliata community in Xingdoushan Nature Reserve, Enshi Autonomous Prefecture, Hubei Province, we used the data collected from the field survey and employed different ecological niche models. The models tested were the broken stick model (BSM), the overlapping niche model (ONM) and the niche preemption model (NPM), as well as three statistic models, the log-series distribution model (LSD), the log-normal distribution model (LND) and the Weibull distribution model (WDM). To determine the fitted model most suitable to each layer, the fitting effects were judged by criteria of the lowest value of Akaike Information Criterion (AIC), Chi-square and the K-S values with no significant difference (P>0.05) between the theoretical predictions and observed species abundance distribution values. The result showed: (1) The fitting suitability and goodness of fit of the tree, shrub and herb layers by using the three ecological niche models were ranked as: NPM>BSM>ONM. Of the three statistical models, by accepting the fitting results of the three layers, WDM was the best fitting model, followed by LND. By rejecting the fitting tests of the herb layer, LSD had the worst fitting effect. The goodness of the statistical models was ranked as: WDM>LND>LSD. In general, the statistical models had better fitting results than the ecological models. (2) T. ciliata was the dominant species of the tree layer. The species richness and diversity of the herb layer were much higher than those of either the tree layer or the shrub layer. The species richness and diversity of the shrub layer were slightly higher than those of the tree layer. The community evenness accorded to the following order: herb>shrub>tree. Considering the fitting results of the different layers, different ecological niche models or statistical models with optimal goodness of fit and ecological significance can be given priority to in studying the species abundance distribution patterns of T. ciliata communities.     

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。     

Temporal Variations and Driving Factors of Cultivated Land Use Intensity in Shandong Province from 1980 to 2015

Based on the cost-income data of agricultural products and relevant statistical data, taking major grain crops and economic crops in the process of cultivated land use as study cases, we studied characteristics of the temporal variation of cultivated land use intensity and its composition in Shandong Province from 1980 to 2015, and then analyzed its main driving factors. The results showed that: (1) The total intensity of major crops in Shandong Province showed a rising trend from 919.73 Yuan ha^-1 in 1980 to 3285.06 Yuan ha^-1 in 2015, and the average annual intensity of economic crops was higher than that of grain crops. The labor cost and material cost of major crops both showed an increasing trend, but the material input was much higher than labor input for grain crops, while the labor input was much higher than material input for economic crops. (2) The labor intensity of major crops in Shandong Province showed a decreasing trend from 501.75 man-day ha^-1 in 1980 to 161.93 man-day ha^-1 in 2015. The labor intensity of grain crops was lower than that of economic crops and its decline rate was fast. On the contrary, the capital intensity showed an increasing trend from 518.33 Yuan ha^-1 in 1980 to 1159.95 Yuan ha^-1 in 2015. In the internal composition of capital intensity, the proportion of yield-increasing inputs such as seed, farmyard manure, fertilizer, pesticide and drainage and irrigation decreased gradually, while the proportion of labor-saving inputs such as agricultural machinery increased significantly. (3) The cultivated land use intensity in Shandong Province had significant negative correlations with the amount of agricultural labor and cultivated land area per capita. The primary direct driving factor was the net income per unit cost of major crops, but the time response lagged by 1-3 years. The main indirect driving factor was the reform of agricultural policy.     

Soil Respiration Dynamics and Influencing Factors in Typical Steppe of Inner Mongolia under Long-term Nitrogen Addition

We investigated soil respiration (Rs) dynamics and influencing factors under different nitrogen (N) addition levels (0, 2, 4, 8, 16, 32 g m^-2 yr^-1) on typical grassland plots in Inner Mongolia. We measured soil respiration, temperature, moisture and nutrients. We found that N addition did not change dynamic characteristics of Rs; daily and seasonal dynamics followed a single peak curve. N addition reduced Rs during the growing season. Rs under N2, N4, N8, N16 and N32 treatments decreased by 24.00%, 21.93%, 23.49%, 30.78% and 28.20% in the growing season, respectively, compared to the N0 treatment. However, Rs in the non-growing season was not different across treatments. Rs was significantly positively correlated with soil temperature and moisture and these two factors accounted for 72%-97% and 74%-82% of variation in Rs, respectively. The soil respiration temperature sensitivity (Q₁₀) was between 2.27 and 4.16 and N addition reduced Q₁₀ except in the N8 treatment.