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● The framework of multi-objective nitrogen (N) management was developed.● Multi-objective targets were established to support agriculture sustainable production.● A food chain approach was developed to accurately quantify N flow in food system.● “3R” principle was used in developing N management strategy.● The collaboration with different stakeholders is crucial for promoting technologies.Nitrogen (N) is an essential nutrient for food production. The rapid increase in population requires high inputs of N to meet the growing food demand. If not managed well, the substantial loss of N from the food system has multiple impacts on grain yield, air and water pollution, and the economic benefits of agricultural. Multi-objective (food security, environmental sustainability and economic sustainability) synergistic consideration of N management in the food system is still lacking. This study employed strategies for optimizing N management in the food system, using Quzhou County as a typical example on the North China Plain. Firstly, a food chain approach was adopted to understand drivers and reasons behind N losses from the food system. Secondly, a top-down approach was used to define multi-objective N management, taking into consideration food security, environmental sustainability and economic sustainability. Multi-objective N management aims to reduce N losses to the environment and increase N use efficiencies, while simultaneously increasing yields and economic benefits. Thirdly, 3R (reduce-retain-recycle) N management strategies were identified for specific crops and animals through a bottom-up approach and then analyzed the potential of these strategies to achieve the multi-objectives. Finally, there is a discussion of how to engage different stakeholders to promote the technologies implementation. This study provides new insights into the synergistic achievement of multi-objective N management in the food system and the development of environmentally-friendly agriculture.

AbstractWhile research on spatial lag quantile regression models exists, the extension to incorporating compositional data within this framework remains unexplored. The unique characteristics of compositional data present significant issues in constructing such a model. In this paper, we investigate the estimation problems for the spatial lag quantile regression model in compositional data. We propose the constrained two-stage quantile regression (CTS-QR) and constrained instrumental variable quantile regression (CIV-QR) methods based on linear programming. Numerical simulations show that our proposed methods are more accurate than traditional unconstrained estimation methods. A real data application of our methods is also provided. [ABSTRACT FROM AUTHOR]

[Objective] The effects of quinoa sowing date and density on soil nutrients, enzyme activities and microbial community structure were analyzed, and the optimal sowing date and sowing density of quinoa in Gannan area were determined, aiming to provide a theoretical basis and scientific reference for the adjustment of quinoa cultivation system and the promotion of quinoa industry. [Method] Using quinoa variety 'Longquinoa No. 5' as the material, a two-factor random block design was adopted, and two factors were set, including early sowing (sowing on May 15, E) and late sowing (sowing on June 24, L), and low density (1.2X104 plants/hm², D1), medium density (1.6X104 plants/hm², D2) and high density (2.0X104 plants/hm², D3), a total of 6 treatments, namely early sowing low density (ED1), early sowing medium density (ED2), early sowing high density (ED3), late sowing low density (LD1), late sowing medium density (LD2) and late sowing low density (LD3), the yield and its constituent factors of different treatments of quinoa were analyzed, and the rhizosphere soil pH of different treatments was determined. Nutrient content and soil enzyme activity, Illumina-HiSeq high-throughput sequencing technology was used to analyze the composition and diversity of bacterial community in rhizosphere soil of quinoa under different treatments, and finally the correlation between soil pH and nutrient content, relative abundance of bacterial community and enzyme activity was analyzed. [Result] Sowing date and density had significant effects on quinoa yield and its constituent factors. There was no significant difference in main panicle length among the treatments. Among the six treatments, the effective branch number and 1 000-grain weight of quinoa in LD1 treatment were the highest, and the total yield of ED2 and ED3 treatments was higher. Sowing date and density had no significant effect on soil pH in the rhizosphere of quinoa, but had a significant effect on soil nutrient content and enzyme activity. At the same density, the contents of total phosphorus, total potassium, total nitrogen and organic matter in the rhizosphere soil of late sowing quinoa were generally higher than those in the early sowing treatment, both at the branching stage and at the grain-filling stage. At the same density, the activities of catalase, sucrase and urease in the rhizosphere soil of late sowing quinoa at the branching stage were generally higher than those in the early sowing treatment, while the alkaline phosphatase in the early sowing treatment was lower than that in the late sowing treatment, and the catalase and alkaline phosphatase activities in the rhizosphere soil of late sowing quinoa at the grain filling stage were generally lower than those in the early sowing treatment, and the sucrase activities in the late sowing treatment were higher than those in the early sowing treatment. Sowing date and density had significant effects on the bacterial community structure of quinoa rhizosphere soil.In the branching stage, the average Shannon index and Simpson index of ED2 treatment were the highest, and the Chao1 index of LD2 treatment was the highest, and the coverage index of ED3 treatment was the highest. The results of correlation analysis showed that soil nutrient content and enzyme activity were significantly correlated with soil bacterial community structure, among which soil urease activity was significantly positively correlated with available phosphorus content, catalase activity was significantly positively correlated with available potassium content, soil sucrase was significantly positively correlated with total nitrogen content, catalase activity was significantly positively correlated with actinomycetes, urease activity was significantly positively correlated with Proteobacteria, and sucrase activity was significantly positively correlated with Blastomonas. [Conclusion] In the high-altitude cold areas of Gansu Province, the sowing date and density had significant effects on the yield of quinoa, its rhizosphere soil nutrient content, enzyme activity and bacterial community, and the sowing time of quinoa in this area was mid-May and the sowing density was (1.6-2.0)X104 plants/hm². [ABSTRACT FROM AUTHOR]

Habitat selection has been a central focus of animal ecology, with research primarily concentrating on habitat choice, utilization, and evaluation. However, studies confined to a single scale often fail to reveal the habitat selection needs of animals fully and accurately. This paper investigates the wintering whooper swan (Cygnus cygnus) in Manas National Wetland Park, Xinjiang, using satellite tracking to determine their locations. The Maximum Entropy model (MaxEnt) was applied to explore the multi-scales habitat selection needs of Manas National Wetland Park's wintering whooper swans across nighttime, daytime, and landscape scales. This study showed that the habitat selection of the wintering whooper swans varied in different scales. At the landscape scale, wintering whooper swans prefer habitats with average winter precipitations of 6.9 mm and average temperatures of −6 °C, including water bodies and wetlands, indicating that climate (precipitation and temperature) and land type (wetlands and water bodies) influence their winter habitat selection. During daytime, whooper swans prefer areas close to wetlands, water bodies, and bare land, with a more dispersed distribution of water bodies. For nighttime, they tend to choose areas within the wetland park where human disturbance is minimal and safety is higher. This study can provide scientific basis and data support for habitat conservation and management of wintering waterbirds like whooper swans, recommending targeted conservation measures to effectively manage and protect the wintering grounds of whooper swans. [ABSTRACT FROM AUTHOR]

Abstract.We propose the auto multivariate distance covariance for time series, which extends the concept of joint high distance covariance. Furthermore, we develop two new procedures for testing mutual independence in multivariate time series that combine the auto multivariate distance covariance with either the Box and Pierce (1970) or the Li and McLeod (1981) tests. Simulation results suggest that the proposed method is highly effective. We also apply our methods to analyze the relationships between the real gross domestic products of the United Kingdom, Canada, and the United States. [ABSTRACT FROM AUTHOR]