Asymmetric effects of grazing intensity on macroelements and microelements in grassland soil and plants in Inner Mongolia Grazing alters nutrient dynamics of grasslands

Grazing is a traditional grassland management technique and greatly alters ecosystem nutrient cycling. The effects of grazing intensity on the nutrient dynamics of soil and plants in grassland ecosystems remain uncertain, especially among microelements. A 2-year field grazing experiment was conducted in a typical grassland with four grazing intensities (ungrazed control, light, moderate, and heavy grazing) in Inner Mongolia, China. Nutrient concentration was assessed in soil and three dominant plant species (Stipa krylovii,Leymus chinensis, andCleistogenes squarrosa). Assessed quantities included four macroelements (carbon (C), nitrogen (N), phosphorus (P), and magnesium (Mg)) and four microelements (copper (Cu), iron (Fe), manganese (Mn), and zinc (Zn)). Soil total C, total N, total P, available N, and available P concentrations significantly increased with grazing intensity but soil Mg, Cu, Fe, Mn, Zn concentrations had no significant response. Plant C concentration decreased but plant N, P, Mg, Cu, Fe, Mn, and Zn concentrations significantly increased with grazing intensity. In soil, macroelement dynamics (i.e., C, N, and P) exhibited higher sensitivity with grazing intensity, conversely in plants, microelements were more sensitive. This result indicates macroelements and microelements in soil and plants had asymmetric responses with grazing intensity. The slopes of nutrient linear regression inC. squarrosawere higher than that ofS. kryloviiandL. chinensis, indicating thatC. squarrosahad higher nutrient acquisition capacity and responded more rapidly to heavy grazing. These findings indicate that short-term heavy grazing accelerates nutrient cycling of the soil-plant system in grassland ecosystems, elucidate the multiple nutrient dynamics of soil and plants with grazing intensity, and emphasize the important function of microelements in plant adaptation in grazing management

Asymmetric effects of litter accumulation on soil temperature and dominant plant species in fenced grasslands

Excess litter accumulates on the soil surface of fenced grasslands and alters the abiotic environment and plant population dynamics. However, little is known about the effect of litter accumulation on the interaction between environmental factors and plant population characteristics in fenced grasslands, especially over different time scales. We applied a three-year litter removal experiment to two kinds of fenced grasslands in Inner Mongolia, China. We measured soil temperature in situ and plant phenology and population characteristics of three dominant species (Stipa grandis, S. krylovii, and Leymus chinensis). During the growing season, litter accumulation (i.e., the control) significantly decreased soil temperature, with a larger effect in the daytime than at night. The diurnal negative effect gradually weakened across the growing season, whereas the negative effect in the nighttime shifted to a positive effect on soil temperature in the late growing season. The decreased soil temperature delayed plant phenology, with longer delays in S. grandis and S. krylovii than L. chinensis. Litter accumulation also significantly increased the height, cover, root biomass, and relative dominance of L. chinensis but decreased cover, density, root biomass, and relative dominance of both Stipa, driving replacement of S. grandis or S. krylovii by L. chinensis in two grasslands. Our findings emphasize the critical function of litter in grassland management and provide a new insight to elucidating the mechanism of how litter accumulation regulates the abiotic environment, community composition and structure, and successional change in fenced grasslands

A Recommendation System Based on Regression Model of Three-Tier Network Architecture

The sparsity problem of user-item matrix is a major obstacle to improve the accuracy of the traditional collaborative filtering systems, and, meanwhile, it is also responsible for cold-start problem in the collaborative filtering approaches. In this paper, a three-tier network Architecture, which includes user relationship network, item similarity network, and user-item relationship network, is constructed using comprehensive data among the user-item matrix and the social networks. Based on this framework, a Regression Model Recommendation Approach (RMRA) is established to calculate the correlation score between the test user and test item. The correlation score is used to predict the test user preference for the test item. The RMRA mines the potential information among both social networks and user-item matrix to improve the recommendation accuracy and ease the cold-start problem. We conduct experiment based on KDD 2012 real data set. The result indicates that our algorithm performs superiorly compared to traditional collaborative filtering algorithm

Litter accumulation alters the abiotic environment and drives community successional changes in two fenced grasslands in Inner Mongolia

Fencing is an effective and practical method for restoring degraded grasslands in northern China. However, little is known about the role of excess litter accumulation due to long-term fencing in regulating abiotic environment and driving changes in community structure and function. We conducted a three-year field experiment in two fenced grasslands in Inner Mongolia, and monitored light quantity, soil temperature, and soil moisture continuously, and determined community height, community aboveground net primary productivity (ANPP), and the relative dominance of different plant functional groups. Litter accumulation reduced light quantity and soil temperature but increased soil moisture. The regulating effects of litter accumulation on soil temperature and soil moisture fluctuated temporally and gradually weakened over the growing season. Litter accumulation also altered community vertical structure and function by increasing community height and ANPP. The increase in soil moisture increased the relative dominance of rhizome grasses but suppressed bunch grasses, thereby shifting bunch grass grasslands to rhizome grass grasslands. Our findings provide a potential mechanism for community succession in the context of litter accumulation in fenced grasslands and indicate that the vegetation and ecosystem services of degraded grasslands are improved after appropriate fencing

Litter accumulation alters the abiotic environment and drives community successional changes in two fenced grasslands in Inner Mongolia

Fencing is an effective and practical method for restoring degraded grasslands in northern China. However, little is known about the role of excess litter accumulation due to long-term fencing in regulating abiotic environment and driving changes in community structure and function. We conducted a three-year field experiment in two fenced grasslands in Inner Mongolia, and monitored light quantity, soil temperature, and soil moisture continuously, and determined community height, community aboveground net primary productivity (ANPP), and the relative dominance of different plant functional groups. Litter accumulation reduced light quantity and soil temperature but increased soil moisture. The regulating effects of litter accumulation on soil temperature and soil moisture fluctuated temporally and gradually weakened over the growing season. Litter accumulation also altered community vertical structure and function by increasing community height and ANPP. The increase in soil moisture increased the relative dominance of rhizome grasses but suppressed bunch grasses, thereby shifting bunch grass grasslands to rhizome grass grasslands. Our findings provide a potential mechanism for community succession in the context of litter accumulation in fenced grasslands and indicate that the vegetation and ecosystem services of degraded grasslands are improved after appropriate fencing

Vegetation classification at the association level under the China Vegetation Classification System: an example of six Stipa steppe formations in China

Aims The latest China Vegetation Classification System (China-VCS) for natural/semi-natural vegetation has eight hierarchical levels: Association < Association-group < Subformation < Formation < Formation-group < Vegetation-subtype < Vegetation-type < Vegetation-type-group. The classification is based on dominant species and their growth forms and has been completed at the formation level. The principal challenge today in Chinese vegetation classification is to develop the China-VCS at levels below the formation in a way that is consistent with current international standards. We explored the following question: how can existing vegetation plot data help develop the China-VCS and improve its compatibility with other international classification systems? Methods We compiled 401 plots having plant cover and/or aboveground biomass measurements collected in six Stipa steppe formations and divided them into those with cover data (299 plots) and/or biomass data (283 plots). We applied a combination of hierarchical clustering and ordination to partition the cover and biomass data sets into formations and constituent associations. We then used supervised noise clustering to improve the classification and to identify the core plots representing each association. Diagnostic species were also identified at both association and formation levels. Finally, we compared the classification results based on cover and biomass data sets and combined these results into a comprehensive classification framework for the six formations. Important Findings Our results using cover data were comparable with those using biomass data at both formation and association levels. Three Stipa formations were classified into associations based on cover data, two based on biomass data and one based on both biomass and cover data. Twenty-seven associations were defined and proposed within the six formations, using cover or biomass data as consistent classification sections (CCSs). Both dominant species in the dominant stratum and diagnostic species from multiple strata of the core plots were used to characterize vegetation types at both formation and association levels, improving the compatibility of our classification with the International Vegetation Classification. Temperature and precipitation were found to be important climatic factors determining the distribution pattern and species composition of Stipa-dominated vegetation. We propose a framework for plot-based vegetation classification in the China-VCS, using our work with Stipa-dominated steppe vegetation as an example. We applied the concept of CCS to make optimal use of available data representing both plant cover and biomass. This study offers a model for developing the China-VCS to the association level in a way that is consistent with current international standards