Tetracycline is an antibiotic with extensive veterinary use in the livestock industry. However, their widespread application poses risks to soil health as residue in livestock feces, and their removal is crucial for sustainable soil-ecosystem development. Physical and chemical approaches to extract tetracycline may have adverse effects on soil ecosystems, but no studies have thus far examined the potential for biological methods, such as collective degradation action of soil fauna. Thus, this study aimed to investigate the synergistic effects of lactic acid bacteria (LAB) and earthworms (Eisenia fetida) on biodegradation of tetracycline residues in sheep manure. We assessed earthworm biomass, tetracycline residue, and bacterial communities in both earthworm intestines and vermicompost. Earthworm biomass and tetracycline degradation efficiency increased significantly with LAB addition, with a degradation rate of up to 80.16%. This increase may be attributable to LAB acting as electron donors to spur tetracycline degradation. Additionally, we noted that tetracycline presence significantly influenced bacterial communities in earthworm intestines and vermicompost, elevating the abundance of potential pathogenic bacteria (e.g., Flavobacterium, Gammaproteobacteria, and Enterobacteriaceae). This finding suggests that heightened environmental stress from antibiotics could actually facilitate the growth of less prevalent bacteria, including potential pathogens. In conclusion, our study provides evidence supporting the effectiveness of LAB and earthworms in degrading tetracycline residues. In particular, LAB appears to mitigate stress from tetracycline exposure in earthworms, thus increasing their vermicomposting efficacy. Our work has important implications for soil management, with the potential to enhance pollution clean-up rates while minimizing negative side-effects to soil microbial communities.

This review analyzes the occurrence and co-exposure of aflatoxins and fumonisins in conventional and organic corn, and compares the vulnerability to contamination of both. The risks of fungal contamination in corn are real, mainly by the genera Aspergillus and Fusarium, producers of aflatoxins and fumonisins, respectively. Aflatoxins, especially AFB1, are related to a high incidence of liver cancer, and the International Agency Research of Cancer (IARC) classified them in group 1A \'carcinogenic to humans\'. The occurrence in conventional corn is reported in many countries, including at higher levels than those established by legislation. IARC classified fumonisins in group 2B \'possibly carcinogenic to humans\' due to their link with incidence of esophageal cancer. However, comparing corn and organic and conventional by-products from different regions, different results are observed. The co-occurrence of both mycotoxins is a worldwide problem; nevertheless, there is little data on the comparison of the co-exposure of these mycotoxins in corn and derivatives between both systems. It was found that the agricultural system is not a decisive factor in the final contamination, indicating the necessity of effective strategies to reduce contamination and co-exposure at levels that do not pose health risks.

How to achieve sustainable food production while reducing environmental impacts is a major concern in agricultural science, and advanced breeding techniques are promising for achieving such goals. However, rice is usually grown under field conditions and influenced by surrounding ecological community members. How ecological communities influence the rice performance in the field has been underexplored despite the potential of ecological communities to establish an environment-friendly agricultural system. In the present study, we demonstrate an ecological-network-based approach to detect potentially influential, previously overlooked organisms for rice (Oryza sativa). First, we established small experimental rice plots, and measured rice growth and monitored ecological community dynamics intensively and extensively using quantitative environmental DNA metabarcoding in 2017 in Japan. We detected more than 1000 species (including microbes and macrobes such as insects) in the rice plots, and nonlinear time series analysis detected 52 potentially influential organisms with lower-level taxonomic information. The results of the time series analysis were validated under field conditions in 2019 by field manipulation experiments. In 2019, we focused on two species, Globisporangium nunn and Chironomus kiiensis, whose abundance was manipulated in artificial rice plots. The responses of rice, namely, the growth rate and gene expression patterns, were measured before and after the manipulation. We confirmed that, especially in the G. nunn-added treatment, rice growth rate and gene expression pattern were changed. In the present study, we demonstrated that intensive monitoring of an agricultural system and the application of nonlinear time series analysis were helpful to identify influential organisms under field conditions. Although the effects of the manipulations were relatively small, the research framework presented here has future potential to harness the ecological complexity and utilize it in agriculture. Our proof-of-concept study would be an important basis for the further development of field-basis system management.

The amount of nitrogen stored in terrestrial soils, its \"nitrogen pool\", moderates biogeochemical cycling affecting primary productivity, nitrogen pollution and even carbon budgets. The soil nitrogen pools and the transformation of nitrogen forms within them are heavily influenced by environmental factors including anthropogenic activities. However, our understanding of the global distribution of soil nitrogen with respect to anthropogenic activity and human land use remains unclear. We constructed a meta-analysis from a global sampling, in which we compare soil total nitrogen pools and the driving mechanisms affecting each pool across three major classifications of human land use: natural, agricultural, and urban. Although the size of the nitrogen pool can be similar across natural, agricultural and urban soils, the ecological and human associated drivers vary. Specifically, the drivers within agricultural and urban soils as opposed to natural soils are more complex and often decoupled from climatic and soil factors. This suggests that the nitrogen pools of those soils may be co-moderated by other factors not included in our analyses, like human activities. Our analysis supports the notion that agricultural soils act as a nitrogen source while urban soils as a nitrogen sink and informs a modern understanding of the fates and distributions of anthropogenic nitrogen in natural, agricultural, and urban soils.

Vineyard landscapes significantly contribute to the economy, identity, culture, and biodiversity of many regions worldwide. Climate change, however, is increasingly threatening the resilience of vineyard landscapes and of their ecological conditions, undermining the provision of multiple ecosystem services. Previous research has often focused on climate change impacts, ecosystem conditions and ecosystem services without systematically reviewing how they have been studied in the literature on viticulture. Here, we systematically review the literature on vineyard landscapes to identify how ecosystem conditions and services have been investigated, and whether an integrative approach to investigate the effects of climate change was adopted. Our results indicate that there are still very few studies that explicitly address multiple ecosystem conditions and services together. Only 28 and 18% of the reviewed studies considered more than two ecosystem conditions or services, respectively. Moreover, while more than 97% of the relationships between ecosystem conditions and services studied were addressing provisioning and regulating services, only 3% examined cultural services. Finally, this review found that there is a lack of integrative studies that address simultaneously the relationships between ecosystem condition, ecosystem services and climate change (only 15 out of 112 studies). To overcome these gaps and to better understand the functioning of vineyard socio-ecological systems under climate change, multidisciplinary, integrative, and comprehensive approaches should be adopted by future studies. A holistic understanding of vineyard landscapes will indeed be crucial to support researchers and decision makers in developing sustainable adaptation strategies that enhance the ecological condition of vineyards and ensure the provision of multiple ecosystem services under future climate scenarios.
UNASSIGNED: The online version contains supplementary material available at 10.1007/s11625-022-01223-x.

Climate change resultant hazards have become a major threat to farming, food production systems and agricultural sustainability globally. Like many other countries, Bangladesh is also the prey of climate change extremities. Haor wetlands of this country, a major rice growing area, are subjected to extreme climate tremors where millions of inhabitants lose their boro rice production due to recurring flash flood events. This study examined the barriers to adapt rice farming to recurring flash floods in the haor wetlands of Bangladesh. The ways of overcoming barriers to adapt rice farming to recurring flash floods in the haor wetlands of Bangladesh were also explored during the research work. The research was conducted in the Sunamganj district of Bangladesh and data was collected through a mixed-method approach. A survey was conducted with 115 haor farmers and FGD and key informant interviews were conducted with 32 and 4 respondents respectively. The results showed that the lack of availability of submergence tolerant variety (a rice variety that can survive and continue growing after being completely submerged in water for several days) is the major barrier to farmers\' adaptation to flooding events followed by limited market access and lack of access to inputs. A total of 85% of respondents reported encountering moderate to severe barriers to adapt to flash flooding. Besides, some socio-economic traits, including annual family income, extension media exposure, and perception on climate change have been identified to be influencing farmers\' adaptation behaviour to adapt their rice farming system to recurring flash flood events. This study elaborated pathways and suggested policy recommendations to adapt to flash flooding and to ensure sustainability in the agricultural system in the haor wetlands of Bangladesh.

The great challenge of reducing soil nutrient depletion and assuring agricultural system productivity in low-income countries caused by limited synthetic fertilizer use necessitates local and cost-effective nutrient sources. We estimated the changes of the nitrogen budget of agricultural systems in the East African Community from 1961 to 2018 to address the challenges of insufficient nitrogen inputs and serious soil nitrogen depletion in agricultural systems of the East African Community region. Results showed that total nitrogen input increased from 12.5 kg N ha-1yr-1 in the 1960s to 21.8 kg N ha-1yr-1 in the 2000s and 27 kg N ha-1yr-1 in the 2010s. Total nitrogen crop uptake increased from 12.8 kg N ha-1yr-1 in the 1960s to 18.2 kg N ha-1yr-1 in the 2000s and 21.8 kg N ha-1yr-1 in the 2010s. Soil nitrogen stock increased from -2.0 kg N ha-1yr-1 in the 1960s to -0.5 kg N ha-1yr-1 in the 2000s and 0.3 kg N ha-1yr-1 in the 2010s. Our results allow us to substantiate for the first time that soil nitrogen depletion decreases with increasing input of nitrogen in agricultural systems of the East African Community region. This suggests that increases in nitrogen inputs through biological nitrogen fixation and animal manure are the critical nitrogen management practices to curb soil nitrogen depletion and sustain agricultural production systems in the East African Community region in order to meet food demand for a growing population.
UNASSIGNED: The online version contains supplementary material available at 10.1007/s13593-023-00881-0.

In this research, we build two food systems datasets in Mexico; The first one describes the structure of agricultural production units and the second one describes food security aspects of the rural population in these agricultural production units. We also build a third dataset, consisting of path diagrams and path coefficients (derived from Structural Equation Modeling) that relate the first dataset to the second dataset in the four most populated ecoregions of Mexico. The description of the path models and the insights they bring to the current state of food security in Mexican rural households are detailed in an associated article entitled \"Is food security primarily associated with smallholder agriculture or with commercial agriculture?: An approach to the case of Mexico using structural equation modeling\" (https://doi.org/10.1016/j.agsy.2021.103091). The agricultural variables (in the first dataset) include farm size, destination of the farmer\'s production, cultivation practice / water management, predominant source of income of the household, land tenure type, crop diversity, agricultural surface expansion, and the presence of forest cover. They are based on the primary data of the full, latest available agricultural census in Mexico and corresponding official land use / land cover data. The second dataset consists of four food security indicators designed and built for the first food security model in Mexico that incorporates food availability, food accessibility and food utilization aspects. They include the Food Self-sufficiency Index (the balance between food production and food consumption), the Food Access Index (inversely related to marginalization), the Entitlement to Public Health Care index, and the Undernutrition Infrequency index (related to hospital sickness records). We provide the path tables and diagrams that describe the links between the agricultural structure and food security. These diagrams provide the first nationwide statistical evidence for the prominent role of smallholder agriculture in rural food security at the national level and at ecoregion scale for a country of the global South. In order to further investigate the structure of the agricultural production units and their relationships with socio-economic, territorial and landscape data, artificial intelligence (i.e. data mining and machine learning) techniques could be performed on this compendium of datasets. The food security data may stir the development of more food security models in Mexico in relation to other drivers such as consumption habits and non-agricultural activities of rural households.

In this study, an inexact fuzzy-flexible left-hand-side chance-constrained programming (IFLCCP) method is proposed for optimizing an agricultural nonpoint-source water quality management problem under uncertainty. The developed method can address complex uncertainties resulted from system fuzzy flexible under various level of decision-making requirements and randomness parameters appeared on the left-hand side of the constraints, and deal with the conflict between water quality protection and agricultural system economic development. The IFLCCP model is formulated through incorporating inexact left-hand-sided chance-constrained programming into interval fuzzy flexible programming framework. The decision schemes obtained by the IFLCCP are analyzed under scenarios at different confidence level of environmental constraint. The results demonstrate that the scale of crop planting and breeding industries reduces as the confidence coefficient of environmental constraint (1-pi) increases, in order to satisfy pollutant discharge constraints, which results in the reduction of the system net benefit from scenarios 1 to 3. Meanwhile, the interval control variables λ± are introduced for quantifying the degrees of overall satisfaction for the objective function and the constraints, which get optimal adjustment to guarantee the net benefit to be as close as possible to the upper bound. The IFLCCP is able to provide management schemes with high system benefits under different levels of acceptable environmental risk, taking full consideration of decision makers\' environmental management requirements. This study is a new application of the IFLCCP model to agricultural water quality management problem, demonstrating its applicability to practical environmental problems with high complexity and uncertainty.

Agricultural Life Cycle Assessment (LCA) is an effective tool for the quantitative evaluation and analysis of agricultural materials production and operation activities in various stages of the agricultural system. Based on the concept of life cycle, it comprehensively summarizes the impact of agriculture on the environment, which is an effective tool to promote the sustainability and green development of agriculture. In recent years, agricultural LCA has been widely used in the agroecosystem for resource and environmental impacts analysis. However, some challenges still exist in agricultural LCA, i.e., the environmental impact assessment index system needs to be improved; its application in different production mode is limited; and combination research with other models needs more attention. This paper discusses the above-mentioned challenges and recommends research priorities for both scientific development and improvements in practical implementation. In summary, further research is needed to construct a regional heterogeneity database and develop innovated methodologies to develop more meaningful functional units for agricultural products to complement LCA by other models. These efforts will make agricultural LCA more robust and effective in environmental impacts assessment to support decision making from individual farm to regional or (inter)national for the sustainable future of agriculture.