Recent publications
Agricultural production under contractual agreements is considered profitable, enabling the integration of smallholder farmers into agricultural commodity value chains. This calls for agricultural policies targeting rural development to emphasize the support for such initiatives. In Tanzania, small-scale farmers’ involvement in contract farming (CF) has remained consistently low. Therefore, this study analyzed the drivers influencing sorghum farmers’ engagement in CF offered by brewing companies in the country. Cross-sectional data from 400 sorghum farmers in the three districts of Kongwa, Mpwapwa and Chamwino in Tanzania were used. A binary logit model was employed to analyze the driving factors that influence CF engagement. The logit model shows that age, a mix of family-hired labor, extension services, both leased and owned land, saving and credit group membership, CF trust, and grain price significantly and positively drive farmers’ decisions toward CF. Conversely, household size, grain bulking distance and experience significantly and negatively affected farmers’ involvement in contract cultivation. Therefore, this study recommends effective policy efforts that promote improved extension services, saving and credit groups, and good grain pricing to enhance participation in CF by sorghum farmers.
Brazil is one of the world’s largest beer producers and also a major food producer. These activities generate a large amount of residues which, if disposed of inappropriately, can have adverse effects on the environment. The objective of this research was to evaluate the potential of using these residues for both mushroom cultivation (traditional use) and the production of mycelium-based composites (innovative use). Mushroom production (Pleurotus sajor-caju) was conducted using only brewer’s spent grains (fresh and dried) and also mixed with banana leaves (1:1) or peach palm leaves (1:1), which are residues widely available in the northern region of Santa Catarina, Brazil. The productivity of mushrooms cultivated using fresh and dried brewer’s spent grains did not exhibit a statistically significant difference, indicating that this residue can be utilized shortly after its generation in the industrial process, thereby reducing costs associated with production. Combining brewer’s spent grains with banana or peach palm leaves resulted in enhanced mushroom production (0.41 and 0.38 g day⁻¹, respectively) compared to using the leaves as a sole substrate. The mushrooms produced contain sugars and a minimal sodium content, and are considered a source of phosphorus. In addition, no toxic elements (Hg and Pb) were present. The mycelium-based composites produced using the residual substrate (after the mushroom harvest) exhibited better mechanical properties (compressive strength = 0.04 MPa, density = 242 kg m⁻³, and low humidity sorption) than those produced using fresh substrate. The results demonstrate the synergistic effect of combining the two approaches under investigation. The use of brewer´s spent enhance the mushroom productivity and the residual substrate enhance the mechanical properties of mycelium-based composites. The compressive strength, density, and air humidity sorption properties are essential for determining the potential applications of mycelium-based composites. The use of brewer’s spent grains mixed with banana leaves demonstrated significant promise for mushroom production and subsequent application in the development of mycelium-based composites. These sequential approaches contribute to waste valorization and the rational utilization of natural resources, as the mycelium-based composites are considered for substitution of synthetic materials, thereby promoting sustainability for future generations.
Our current global Food System is facing extraordinary challenges in both size and severity, including a rise in unsustainable consumption behaviours, continued environmental degradation, growing food insecurity, and widening social inequalities. A Food System transformation is now both critically important and overwhelmingly complex, requiring nothing less than a complete overhaul of the entire value chain. Everyone is needed: Small Medium Enterprises (SMEs) with technological solutions, Non-Governmental Organisations (NGOs) with social innovations, researchers with novel methodologies, governments with food policy advancements, professionals with varying expertise, and last but not least, empowered and informed citizens with the ability and resources for better decision-making. Living Labs offer a holistic, place-based approach needed to facilitate multi-actor inputs on various levels, specifically Food System Living Labs (FSLLs) like the ones established as part of the FoodSHIFT 2030 Project. Nine front-runner Food System Living Labs were operationalised alongside a novel framework merging high-level interdisciplinary initiatives with a diverse set of innovative approaches towards more Sustainable Food Systems (SFS). The FoodSHIFT Approach concept was praised by external evaluators for its ground-breaking framework, and the nearly completed project has been listed as a best practice. However, positive applications alone will not ensure a cross-sector European-wide Food System transformation, and the following text offers a critical reflection coupled with experience-based solutions to further improve the FoodSHIFT Approach.
Main conclusion
Rice exudation patterns changed in response to P deficiency. Higher exudation rates were associated with lower biomass production. Total carboxylate exudation rates mostly decreased under P-limiting conditions.
Abstract
Within the rhizosphere, root exudates are believed to play an important role in plant phosphorus (P) acquisition. This could be particularly beneficial in upland rice production where P is often limited. However, knowledge gaps remain on how P deficiency shapes quality and quantity of root exudation in upland rice genotypes. We therefore investigated growth, plant P uptake, and root exudation patterns of two rice genotypes differing in P efficiency in semi-hydroponics at two P levels (low P = 1 µM, adequate P = 100 µM). Root exudates were collected hydroponically 28 and 40 days after germination to analyze total carbon (C), carbohydrates, amino acids, phenolic compounds spectrophotometrically and carboxylates using a targeted LC–MS approach. Despite their reported role in P solubilization, we observed that carboxylate exudation rates per unit root surface area were not increased under P deficiency. In contrast, exudation rates of total C, carbohydrates, amino acids and phenolics were mostly enhanced in response to low P supply. Overall, higher exudation rates were associated with lower biomass production in the P-inefficient genotype Nerica4, whereas the larger root system with lower C investment (per unit root surface area) in root exudates of the P-efficient DJ123 allowed for better plant growth under P deficiency. Our results reveal new insights into genotype-specific resource allocation in rice under P-limiting conditions that warrant follow-up research including more genotypes.
This article analyses the Buckets Revolution, an urban agroecological movement in a Brazilian favela that emerged to address waste management issues. We aim to explore the movement’s achievements in promoting socio-ecological justice in a vulnerable community of the Global South through agroecology, investigating: i) what socio-ecological problems and intersected demands for justice boosted the emergence of the Buckets Revolution? and ii) what demands for justice the BR has been dealing with to overcome the socio-ecological injustices borne by the Chico Mendes community? We apply the socio-ecological justice model as our theoretical framework, with a decolonial and feminist intersectional approach to embrace the complexity of the case study. The research methods focus on embracing the local reality and the community views, encompassing bibliographical research, a focus group, and semi-structured interviews. The findings reveal that this agroecological movement has effectively addressed organic waste management, food insecurity, and other socio-ecological issues, contributing to socio-ecological justice in the Chico Mendes community. The study emphasizes the importance of considering the a) interconnections of social and ecological problems, b) intersected dimensions of justice, and c) needs and views of the community when developing environmental urban policies to achieve social justice and ecological sustainability.
International, regional, and national organizations, alongside policymakers, are increasingly acknowledging the crucial connection between climate, peace, and security. However, there remains a notable gap in research methodologies capable of fully grasping the intricate dynamics of this relationship. This paper introduces the Integrated Climate Security Framework (ICSF), a comprehensive mixed-methods approach designed to unravel the complexities of climate-human security-conflict connections across various scales. By integrating traditional and innovative research methods, the ICSF aims to provide cutting-edge, policy-relevant insights to address five main measurement challenges of the climate security nexus: multiple pathways; context specificity; non-linearity; multiple actors and scales, and multiple geographic and time scales. By drawing on diverse epistemological perspectives and engaging directly with local communities, the framework offers a comprehensive evaluation of the complex social-ecological dynamics at play. Using Kenya as a case study—a country where climate and security risks frequently intersect and amplify each other—we demonstrate the comprehensive insights the framework offers to address the complex challenges at the nexus of climate, human security, and conflict.
Biological nitrogen fixation is a fundamental part of ecosystem functioning. Anthropogenic nitrogen deposition and climate change may, however, limit the competitive advantage of nitrogen-fixing plants, leading to reduced relative diversity of nitrogen-fixing plants. Yet, assessments of changes of nitrogen-fixing plant long-term community diversity are rare. Here, we examine temporal trends in the diversity of nitrogen-fixing plants and their relationships with anthropogenic nitrogen deposition while accounting for changes in temperature and aridity. We used forest-floor vegetation resurveys of temperate forests in Europe and the United States spanning multiple decades. Nitrogen-fixer richness declined as nitrogen deposition increased over time but did not respond to changes in climate. Phylogenetic diversity also declined, as distinct lineages of N-fixers were lost between surveys, but the “winners” and “losers” among nitrogen-fixing lineages varied among study sites, suggesting that losses are context dependent. Anthropogenic nitrogen deposition reduces nitrogen-fixing plant diversity in ways that may strongly affect natural nitrogen fixation.
Urbanization constitutes a major threat to biodiversity. Understanding its effects on insect communities is relevant because they are key elements of trophic interactions, and indicators and targets of conservation. Herein, we investigated the influence of meteorological and habitat factors on the soil entomofauna in three areas with distinct levels of urbanization at the Parque Estadual da Pedra Branca, Brazil. We investigated whether community structure differs among areas with different levels of urbanization, and how changes in the environment affect soil insect community composition and distribution. We systematically monitored communities for 12 months in three areas along a gradient of anthropogenic disturbance, representing preserved secondary forest, disturbed forest and peridomicile areas. The results revealed that the degree of urbanization affects insect communities, with a strong effect of habitat factors, such as canopy cover, presence of flooded areas, quantity of fallen trunks and mean temperature. Insect abundance did not show significant differences among areas, while biomass was higher in disturbed forest than in preserved forest and peridomicile areas. Additionally, insect richness and diversity were higher in preserved and disturbed forests than in peridomicile areas, with no significant difference between preserved and disturbed forests. Our results can be used to enhance the understanding of the effects of urbanization on taxonomically and functionally diverse groups of insects, and to advise residents and urban planners about the consequences of urbanization on biodiversity and ecosystem services in urban-sylvatic interface areas.
The increasing impacts of climate variability pose a challenge in understanding the dynamics of arid and semi-arid regions, especially in the context of desertification and land degradation. However, in South America, there is a lack of comprehensive studies on the spatial and temporal shifts in aridity zones, particularly using satellite-based indices. The present paper aimed at assessing the spatio-temporal distribution of the Satellite-based Aridity Index (SbAI) in Argentina to analyze possible shifts in the margins of desert and semi-desert regions during the period 2005–2022. Unsupervised classifications were carried out using K-means clustering algorithm taking into account SbAI, Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), Shuttle Radar Topography Mission (SRTM) digital elevation, Vegetation transpiration (Ec) and wetness tasseled caps classification variables. Five Aridity-related Classes associated with hyper-arid, arid, semi-arid, sub-humid and humid regions were identified. Between the 2005–2013 and 2014–2022 periods, the arid/semi-arid and the semi-arid/sub-humid boundaries shifted to the southwest of the country, i.e., arid and semi-arid areas have undergone a retreat. A discrete wavelet low-pass filtering to identify long-term cyclic dynamics along with a 1D unsupervised signal clustering was applied on the class changing pixels SbAI time series. The shifting aridity frontier seems to be associated with the El Niño Southern Oscillation. Additionally, a simplified model, based on SbAI-NDVI-Altitude thresholds, is proposed to map aridity in the region, improving the SbAI-based models previously developed.
The potato is the most important non-cereal food crop worldwide. Silicon (Si) fertilizers have been reported to improve potato growth and yield. We used results from two field experiments in the temperate zone to gain insight into silica accumulation in potato plants as well as corresponding long-term potato yield performance. We found relatively low Si contents in potato plants grown in soils with different concentrations of plant-available Si (field experiment 1). Moreover, potato yield was not correlated to plant-available Si concentrations in soils in the long term (1965-2015, field experiment 2). Based on our results, we ascribe the reported positive effects of Si fertilization on potatoes rather to effects of the used Si fertilizers than to silica accumulation in potato plants. While Si fertilizers applied directly to the leaves can prevent fungal infections, soil-applied Si fertilizers can enhance phosphorus and water availability in agricultural soils. With our study, we aim to inspire further research on Si fertilization-potato relationships. The corresponding results will help to derive practice-oriented recommendations for potato growers worldwide to cope with the challenges of climate change.
Climate change has substantially increased both the occurrence and intensity of flood events, particularly in the Indian subcontinent, exacerbating threats to human populations and economic infrastructure. The present research employed novel ML models—LR, SVM, RF, XGBoost, DNN, and Stacking Ensemble—developed in the Python environment and leveraged 18 flood-influencing factors to delineate flood-prone areas with precision. A comprehensive flood inventory, obtained from Sentinel-1 Synthetic Aperture Radar (SAR) data using the Google Earth Engine (GEE) platform, provided empirical data for entire model training and validation. Model performance was assessed using precision, recall, F1-score, accuracy, and ROC-AUC metrics. The results highlighted Stacking Ensemble’s superior predictive ability (0.965), followed closely by, XGBoost (0.934), DNN (0.929), RF (0.925), LR (0.921), and SVM (0.920) respectively, establishing the feasibility of ML applications in disaster management. The maps depicting susceptibility to flooding generated by the current research provide actionable insights for decision-makers, city planners, and authorities responsible for disaster management, guiding infrastructural and community resilience enhancements against flood risks.
'FraxForFuture' was an interdisciplinary project to study the devastating effects of ash dieback on the host, to characterize the associated ash microbiome, and to develop non-chemical and biological control strategies to combat the pathogen, Hymenoscyphus fraxineus. Bacteria and fungi as well as fungal secondary metabolites were identified, which have an antagonistic effect against the ash dieback pathogen or can be used for microbiome optimisation. Results, conclusions and an outlook are presented.
Expanding agriculture and unsustainable farming practices in Central Asia’s steppes may increase the risk of wind erosion and severe dust emissions. However, empirical data from field experiments to assess a potential severe dust source is lacking. Therefore, a mobile wind tunnel was used in northern Kazakhstan to investigate the potential wind-induced soil loss and dust emissions under real field conditions common in agricultural practices. Field experiments were carried out on typical surfaces that act as dust sources: seedbeds as they occur after cultivation, in-field tracks, and dirt roads. Measurements were conducted by sediment collection of total eroded material and optical particle counting for particulate matter ≤30 µm. The results of the wind tunnel experiments show that the same soil can emit significantly different amounts of dust depending on the mechanical stress to which the soil was previously exposed. Soil loss and dust emissions increased from seedbeds to dirt roads due to the intensifying effect of pulverization by tires. In order to assess an area as a dust source or for emission inventories, the total emissions must be adjusted separately to these shares. Further insights of the field experiments will be presented at the conference.
Climate change is commonly assumed to induce species’ range shifts toward the poles. Yet, other environmental changes may affect the geographical distribution of species in unexpected ways. Here, we quantify multidecadal shifts in the distribution of European forest plants and link these shifts to key drivers of forest biodiversity change: climate change, atmospheric deposition (nitrogen and sulfur), and forest canopy dynamics. Surprisingly, westward distribution shifts were 2.6 times more likely than northward ones. Not climate change, but nitrogen-mediated colonization events, possibly facilitated by the recovery from past acidifying deposition, best explain westward movements. Biodiversity redistribution patterns appear complex and are more likely driven by the interplay among several environmental changes than due to the exclusive effects of climate change alone.
Participatory modelling (PM) is a transdisciplinary research approach that involves stakeholder in a modelling process to develop or improve qualitative or quantitative models. To better understand the potential uses of PM in the emerging field of agroecology living lab research, I conducted a systematic search of the peer-reviewed literature and describe 78 participatory agri-environmental case studies in this dataset. Bibliographic data are included and each case study is described in terms of main goal(s), PM method(s) used, involved stakeholders and their contributions and the level of stakeholder participation in the project. I also extracted key metadata (if available), such as publication type and year, study location (country), funding source, project duration and outcomes beyond publications. This dataset adds value by revealing clusters and associations of methods and goals, by showing the dominating role of researchers in this type of participatory research, by pointing out the absence of PM in certain areas of agricultural production, such as hydroponic farming or viticulture and by providing a comprehensive foundation for the related research article. It also contained data not used in the related research article that could provide a basis for future research, such as linking methods, goals and stakeholder involvement with other metadata or comparing this agri-environmental research and other areas.
High-yielding traits can potentially improve yield performance under climate change. However, data for these traits are limited to specific field sites. Despite this limitation, field-scale calibrated crop models for high-yielding traits are being applied over large scales using gridded weather and soil datasets. This study investigates the implications of this practice. The SIMPLACE modeling platform was applied using field, 1 km, 25 km, and 50 km input data resolution and sources, with 1881 combinations of three traits [radiation use efficiency (RUE), light extinction coefficient (K), and fruiting efficiency (FE)] for the period 2001–2010 across Germany. Simulations at the grid level were aggregated to the administrative units, enabling the quantification of the aggregation effect. The simulated yield increased by between 1.4 and 3.1 t ha− 1 with a maximum RUE trait value, compared to a control cultivar. No significant yield improvement (< 0.4 t ha− 1) was observed with increases in K and FE alone. Utilizing field-scale input data showed the greatest yield improvement per unit increment in RUE. Resolution of water related inputs (soil characteristics and precipitation) had a notably higher impact on simulated yield than of temperature. However, it did not alter the effects of high-yielding traits on yield. Simulated yields were only slightly affected by data aggregation for the different trait combinations. Warm-dry conditions diminished the benefits of high-yielding traits, suggesting that benefits from high-yielding traits depend on environments. The current findings emphasize the critical role of input data resolution and source in quantifying a large-scale impact of high-yielding traits.
There is a general consensus among stakeholders about the benefits of sustainable soil management practices for soil health, yet their implementation lags behind expectations. The aim of this paper is to analyse factors supporting or hindering the implementation of sustainable soil management practices in conventional and organic farming systems. This is achieved using a Logit model, based on penalized maximum likelihood estimation on survey data by 76 farmers from 10 federal states in Germany. Affected factors were categorized in two main groups: agricultural soil management practices, and barriers to their implementation. The measures for soil improving agricultural management included (I) structural landscape elements, (II) organic fertilization, (III) diversified crop rotation, (IV) permanent soil cover (V) conservation tillage, (VI) reduced weight pressure, and (VII) optimized timing of wheeling. Results show differences in preferences between conventional and organic farmers for key sustainable soil management practices, including conservation tillage, optimized wheeling timing, reduced weight pressure, and diversified crop rotation. Economic constraints decrease crop rotation diversification in conventional systems by 14%. Conservation tillage raises the chance of a farm being conventional by 16%, while optimizing wheeling timing reduces it by 60%, highlighting soil compaction concerns among organic farmers. Marginal effects confirm that economic factors, not knowledge, are the main barriers to sustainable soil management. Inconsistent policies, lack of support, and insufficient financial incentives from government institutions can hinder the willingness of farmers to adopt these practices, further exacerbating the barriers to adoption.
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