Soil Respiration in a Desert Steppe Varies by Different Grazing Regimes in Northern China

Recent studies have identified soil respiration as one of the most important research topics (Thomey et al., 2011) because it is the second largest flux between terrestrial ecosystems and the atmosphere, and plays an important role in regulating the soil carbon (C) pool and ecosystem C-cycling (Saiz et al., 2006). Soil respiration represents the carbon dioxide (CO2) released from the soil surface, generated mainly from a combination of the metabolic activity of roots and microorganisms. Soil temperature, soil water content, plant growth, soil carbon (C) and nitrogen (N) contents all affect soil respiration. In this water-limited ecosystem, we hypothesize that soil respiration will vary with different types of grazing management and that this variation is regulated by grazing-induced changes in abiotic (soil temperature and soil water content) and biotic (plant above-ground and below-ground production) factors

Effect of Overgrazing and Enclosure on Ecosystem Functioning and Biological Capacity in the Typical Steppe

Overgrazing is one of the most important human-induced causes for arid and semi-arid grassland degradation, which can result in widespread deterioration of biodiversity, ecosystem services and destroys soil structure (Louhaichi et al. 2012). Overgrazing is likely to reduce a plant’s individual aboveground biomass (AB) directly through influence on the phenotype plasticity of different traits and indirectly through the allometric relationships among plant that can have impacts on grassland productivity and biodiversity. Grazing can reduced nutrient cycling by inhibiting the growth of palatable and nutrient-rich species with high litter quality and promoting the dominance of those nutrient-poor or chemically defended species with low litter quality that slow rates of nutrient cycling. However, fencing and the exclusion of domestic livestock is the most common management tool used for restoring vegetation productivity in degraded grassland (Liu et al., 2007a, b). Although some previous studies have predicted that overgrazing may lead to a shift to dominant species and change soil nutrient content and nitrogen mineralization rate, the mechanisms underpinning this shift and change are very clear. We addressed the following objectives to determine the effects of overgrazing and exclusion from grazing on communities composed of dominant species (L. chinensis and S. grandis), and on soil nutrient content and nitrogen mineralization rate

Herders’ Forage-Livestock Decision Behavior in Northern Grassland regions of China

China has approximately 393 million hectares of grasslands, accounting for 41.7% of the national land area. However, 90% of useable grasslands are degraded because of human and natural reasons. Overgrazing was the dominant factor affecting grassland condition. In order to control the grassland degradation problems, the government has proposed the „forage-livestock balance‟ policy in 2002. A series of ecological policies were (Hou et al., 2013) and outcomes have been described as a “partial improvement amidst overall deterioration”. Reasons for apparent failure of the policy have been the subject of much discussion over the years. However, there has been a lack of research on the role of herder decision making behavior regarding the balance between animals and grass. Under the Household Responsibility System, the herders are directly responsible for managing these vast and important lands for China, and their decisions have both direct and indirect impact on the balance between animal needs and forage supply. Self-reliant herders are the main livestock producers in the Chinese northern grassland regions. Those herders breed animals mainly based on their own available rangelands, and buy forage and fodder only for winter use. They often consider they have lived in pastoral areas for generations, and have their understanding of the rangeland carrying capacity, thus always breed livestock number that they think are reasonable. As a result, overgrazing is universal. A better understanding of the effect herders‟ behavior has on the grassland condition and the details of decision making and their stock-breeding practices is urgently needed to develop more effective policies and programs to alleviate the degradation of grassland

Framing Effect and Pastoralist Decision Making Behavior Regarding Lambing Time-An Analysis from Inner Mongolia, China

Grassland is the largest terrestrial ecosystem in China. However, it is seriously degraded. Lower stocking rates have been necessary for rehabilitating the degraded grassland. In order to rehabilitate the grassland the government proposed the “balancing animals and grass” policy. However, it has been resisted by pastoralists. (Brown et al., 2009). The reasons for the policy’s failure have been widely discussed. To date, there has been a lack of discussion on explicitly addressing the role of pastoralist behavior regarding stock numbers and lambing time. The pastoralists continue to maintain their traditional stocking rate, and take short-term adaptive measures to balance their animal’s needs with feed supply. Winter lambing is considered as one of efficient measures rehabilitating grasslands degradation. In northern China, however, those pastoralists generally buy little forage for sheep and lambs. Because they would graze the livestock, including lambs, on the grassland in the early growing season. However, early season growth on the grasslands is unpredictable and winter lambing could increase the grazing pressure and exacerbate degradation problems. If pastoralists have enough forage supply and sheds for stall-feeding, they could choose to lamb in winter and at the same time comply with the grazing-rest policy. Under the Household Contract Responsibility System, the pastoralists hold the grasslands and breed livestock themselves, and their decisions have both direct and indirect impact on the balance between animal needs and forage supply. However, unpredictable markets and climate change result in pastoralists facing increasingly more decisions making about lambing time and buying forage. Thus, it is becoming imperative to understand how pastoralists make decisions and the biases they exhibit. The framing effect is observed when a decision maker’s risk tolerance depends on how the alternatives are described. Many empirical studies have been conducted to demonstrate and investigate the framing effect in different contexts. Similarly, many theories have been developed to explain human decision making behavior based on gains and losses. However, little is known about pastoralist decision making behavior from a “framing effect” perspective, especially in pastoral areas of northern China. Early research has indicated agricultural decisions vary substantially by ethnicity (Heinimann et al., 2013). In northern China, the majority of pastoralists are with Mongolian background. They have their own culture, values and norms. While most Han pastoralists migrated from agricultural areas, generally take into account more economic interests when making decisions, More importantly, for all those pastoralists who livelihoods depend solely on grassland resources, stockbreeding not only supplies them with monetary income, but also many economic outputs. All these aspects have a substantial impact on pastoralists’ making decisions. Their decisions are an important factor to consider in policy formulation and implementation. However, the importance of ethnicity tends to be ignored in addressing grassland sustainability issues. The objective of this study is to explore the pastoralist decision-making behavior about lambing time, and to propose potential and efficient measures for controlling degradation problems for sustainable grassland development

CTRL: Connect Tabular and Language Model for CTR Prediction

Traditional click-through rate (CTR) prediction models convert the tabular data into one-hot vectors and leverage the collaborative relations among features for inferring user's preference over items. This modeling paradigm discards the essential semantic information. Though some recent works like P5 and M6-Rec have explored the potential of using Pre-trained Language Models (PLMs) to extract semantic signals for CTR prediction, they are computationally expensive and suffer from low efficiency. Besides, the beneficial collaborative relations are not considered, hindering the recommendation performance. To solve these problems, in this paper, we propose a novel framework \textbf{CTRL}, which is industrial friendly and model-agnostic with high training and inference efficiency. Specifically, the original tabular data is first converted into textual data. Both tabular data and converted textual data are regarded as two different modalities and are separately fed into the collaborative CTR model and pre-trained language model. A cross-modal knowledge alignment procedure is performed to fine-grained align and integrate the collaborative and semantic signals, and the lightweight collaborative model can be deployed online for efficient serving after fine-tuned with supervised signals. Experimental results on three public datasets show that CTRL outperforms the SOTA CTR models significantly. Moreover, we further verify its effectiveness on a large-scale industrial recommender system

Carbon Density Distribution and Carbon Storage Estimation under Different Grazing Degradation in the Typical Steppe

Carbon (C) is a crucial component of living organisms on planet earth, and C cycling is an important symbol of healthy development of the biosphere (Han et al. 1999). Human activity has adversely affected the global C cycle, and contributed to an alteration of climate that will generate discernible feedbacks to all organisms and ecosystems on earth (He et al. 2008). Grasslands are one of the most widely distributed terrestrial ecosystems on the earth and it is estimated that C storage of global grassland ecosystem was 761Gt (1Gt = 09t), which accounts for about 15.2% C storage in terrestrial ecosystem (Scurlock et al. 2002). A typical steppe consisting of Stipa grandis and Leymus chinensis was the most representative grassland to research the response mechanism of an ecosystem to human disturbance and climate change. It is of great scientific value to do research about C distribution and storage in this area

The biodiversity and stability of alpine meadow plant communities in relation to altitude gradient in three headwater resource regions

Kobresia pygmaea meadow community diversities in relation to altitude gradients (4200, 4300, 4400, 4450) on free grazing grassland was studied in the range of Chenduo county, Yushu prefecture, Qinghai province. Species richness and diversity index of vegetations in the four altitudes were comparatively analyzed. The results showed that the shape of species richness responsive curves to altitude gradient is “Bell-shape”. There were the same 11 common species in the four communities. The relative abundance of K. pygmaea decreased along increasing altitude. Moreover, the fuzzy membership functions were used to calculate the degree of stability, showing medium altitude > high altitude > low altitude, which suggested that grass land vegetation in low altitude of the sampling site had lower diversity, and the grade of species vulnerability risks may be decided with the help of the degree of stability.Key words: Alpine meadow, Yangtze, Yellow and Yalu Tsangpo river source region, altitude gradient, species diversity, membership functions