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Rice–crayfish coculture systems (RCSs) have been widely promoted in China as an efficient circular agriculture model that can simultaneously improve rice quality, raise the efficiency of utilization of resources, and increase farmers' incomes. However, the herd behavior of farmers in the adoption of the rice–crayfish coculture system warrants more attention, as the rational adoption of this system by farmers is a prerequisite for achieving the above objectives. This paper analyses the formation mechanism of farmers' herd behavior based on information cascade theory. Using micro-survey data from 603 farmers in China and a bivariate probit model, we examine the existence of herding effects in the adoption of RCSs by farmers and the inhibitory effect of information acquisition capability on herd behavior. To address possible endogeneity issues, we also conducted a robustness test using the IV-probit model. Furthermore, we tested for between-group differences in agricultural income between farmers with herding adoption and non-herding adoption. The study reveals that the larger the number of prior adopters, the higher the probability of blind adoption behavior by farmers, indicating the existence of a herd effect. Information acquisition ability could significantly inhibit the herd behavior of farmers in the adoption of RCSs. We also found that farmers' herd behavior in the adoption of these systems was not economically rational. Based on the research findings, we proposed several constructive suggestions for policy perfection. [ABSTRACT FROM AUTHOR]

Integrating pig production stability and pollution control is a matter of social livelihood and green development. This paper estimates the policy effectiveness of environmental regulation based on the big data of Chinese government websites and combines the pig production data of various provinces in China from 2008 to 2018 to construct a mediating effect model, empirically analyzing the relationship between environmental regulations, herd structure, and pig production. Research shows: (1) Improving environmental regulations in the short term will increase the slaughter of pigs, but in the long run it will decrease first and then increase; (2) At this stage, environmental regulations can increase the slaughter of pigs by changing the herd structure; (3) Reasonable adjustment of the herd structure can effectively increase the slaughter of pigs; (4) The herd structure can be used as a supplementary monitoring indicator to stabilize the supply of pigs. Combine it with the change rate of sow stock to provide early warning of fluctuations in pig production, and the early warning herd structure values are 0.0980 and 0.1135. There are two key initiatives to achieve supply and price stability in the pig industry that taking into account environmental protection: first, an industrial regulation instrument based on the herd structure needs to be established; second, an early warning system for pig production fluctuations should be established with reference to the early warning system for pork price fluctuations. [ABSTRACT FROM AUTHOR]

Currently, PRRSV-1 causes a large number of clinical infections in Chinese swine herds, and the prevalence of new strains has presented great challenges. In this study, the novel PRRSV-1 strain SL-01 was isolated, with a genome length of 14,978 bp, and genetic evolution analysis revealed that it belonged to a new subtype branch. Sequence homology analysis showed that the strain was only 82.2%–86.7% identical to the current classical PRRSV-1 strains. In particular, the novel strain exhibited a unique deletion pattern in Nsp2. In addition, GP3 and GP4 of the SL-01 strain showed four consecutive amino acid deletions in the highly variable regions at amino acids 243–248 and 63–68, respectively. Further challenges in piglet and pregnant sow demonstrated that the SL-01 strain could cause the piglet fever and death but less pathogenic to pregnant sow. Overall, the characterization and pathogenicity of a novel PRRSV-1 strain were first explored and provide a prevention for pig farms. [ABSTRACT FROM AUTHOR]

Background: Nitrate leaching to groundwater and surface water and ammonia volatilization from dairy farms have negative impacts on the environment. Meanwhile, the increasing demand for dairy products will result in more pollution if N losses are not controlled. Therefore, a more efficient, and environmentally friendly production system is needed, in which nitrogen use efficiency (NUE) of dairy cows plays a key role. To genetically improve NUE, extensively recorded and cost-effective proxies are essential, which can be obtained by including mid-infrared (MIR) spectra of milk in prediction models for NUE. This study aimed to develop and validate the best prediction model of NUE, nitrogen loss (NL) and dry matter intake (DMI) for individual dairy cows in China. Results: A total of 86 lactating Chinese Holstein cows were used in this study. After data editing, 704 records were obtained for calibration and validation. Six prediction models with three different machine learning algorithms and three kinds of pre-processed MIR spectra were developed for each trait. Results showed that the coefficient of determination (R2) of the best model in within-herd validation was 0.66 for NUE, 0.58 for NL and 0.63 for DMI. For external validation, reasonable prediction results were only observed for NUE, with R2 ranging from 0.58 to 0.63, while the R2 of the other two traits was below 0.50. The infrared waves from 973.54 to 988.46 cm−1 and daily milk yield were the most important variables for prediction. Conclusion: The results showed that individual NUE can be predicted with a moderate accuracy in both within-herd and external validations. The model of NUE could be used for the datasets that are similar to the calibration dataset. The prediction models for NL and 3-day moving average of DMI (DMI_a) generated lower accuracies in within-herd validation. Results also indicated that information of MIR spectra variables increased the predictive ability of models. Additionally, pre-processed MIR spectra do not result in higher accuracy than original MIR spectra in the external validation. These models will be applied to large-scale data to further investigate the genetic architecture of N efficiency and further reduce the adverse impacts on the environment after more data is collected. [ABSTRACT FROM AUTHOR]

In the financial market, because of information asymmetry, investors often ignore private information. Herding behavior in financial markets has become an important research branch of behavioral finance. China stock market has implemented the Shanghai-Hong Kong Stock Connect (SHKSC) policy and introduced mature funds, however, has it alleviated the herd effect? This article empirically verifies the existence of China's stock market before and after the implementation of the SHKSC policy. The research in this article found that the implementation of the SHKSC policy has not changed herding behavior. On the contrary, the herding effect has become more serious. It is further found that investors have no obvious investment preference for the industry to which the stock belongs. Investor investment is in line with the phenomenon of "slow rise and sharp fall." When stock prices fall, the herd effect of the Chinese stock market is also more obvious. [ABSTRACT FROM AUTHOR]

Unanticipated environmental shocks impact the livelihoods of many resource users around the world. These shocks are likely to be more unpredictable as the effects of climate change continue to mount. Yet how households adapt to these changing climatic conditions especially in the context of rapidly changing market conditions in most areas of the world, is poorly understood. These interactions have wide implications for both smallholder livelihoods and sustainable use of natural resources. In this paper, we examine the relationship between environmental shocks and stocking rates in livestock herds in the Inner Mongolian grasslands of northern China. We uniquely examine three types of shocks and how households adapt livestock production strategies in response to each. Separately and in aggregate, we look at three common shocks in Inner Mongolia: droughts, snowstorms, and locust outbreaks. We use a difference-in-differences approach to estimate changes in stocking rates among households that experience shocks versus those that do not with a panel dataset from 2009 to 2014 of 597 households. While we find no clear impact from locusts, our results suggest droughts and snowstorms have opposite effects: droughts are associated with increases in herd sizes, but snowstorms result in decreased herds. We suggest these differences are due to interactions between shocks, emerging options to borrow on credit, and livestock markets. Household adaptation to climate change will be strategic and take advantage of both available resources as well as market conditions. • Climate change is causing stronger and more unpredictable environmental shocks. • We use a difference-in-differences model to estimate the impact of shocks on stocking rate. • Drought relates to bigger herds; snowstorms relate to smaller herds. • Households adapt to shocks taking advantage of both available resources and market conditions. • Shaping well-functioning market may reduce opportunistic resource exploitation. [ABSTRACT FROM AUTHOR]