In the eastern Democratic Republic of Congo, agriculture represents the most important economic sector, and land control can be considered a perpetual source of conflict. Knowledge of the existing production system distribution is fundamental for both informing national land tenure reforms and guiding more effective agricultural development interventions. The present paper focuses on existing agricultural production systems in Katoyi collectivity, Masisi territory, where returning Internally and Externally Displaced People are resettling. We aim to define a repeatable methodology for building evidence-based and updated knowledge concerning the spatial distribution of the two existing production systems: subsistence-oriented agriculture (SOA) and business-oriented agriculture (BOA). To this aim, we used a supervised object-based classification approach on remotely sensed Sentinel-2 imagery to classify land cover. To classify production systems further within the “agriculture” and “pasture” land use classes, binary classification based on an entropy value threshold was performed. An iterative approach was adopted to define the final H_NDVI threshold that minimised commission and omission errors and maximised overall accuracy and class separability. The methodology achieved acceptable observed accuracy (OA equal to 80–90% respectively for agricultural and pasture areas) in the assessment. SOA and BOA respectively covered 24.4 and 75.6% of the collectivity area (34,606 ha). The results conclude that land use and entropy analysis can draw an updated picture of existing land distribution among different production systems, supporting better-adapted intervention strategies in development cooperation and pro-poor agrarian land tenure reforms in conflict-ridden landscapes.

Agroforestry practices can play a key role in ecological transition and socio-territorial regeneration in peri-urban areas, particularly when designed and implemented according to agroecological principles and supported by robust public engagement. In this short communication, we illustrate how community-based agroforestry approaches—encompassing public plantings, self-building workshops, collaborative agroforestry management, training, and cultural events—are transforming an area located at the southeastern fringe of Milan. Drawing on a transdisciplinary methodology, we investigate how agroforestry increases ecological complexity, fosters participatory decision-making, and provides diverse cultural ecosystem services for local communities. Our results indicate that the establishment of multi-strata agroforestry systems, combined with initiatives such as ‘Adopt a Hen!’ and hands-on agroecological workshops, not only enhances biodiversity and soil health but also strengthens social cohesion and citizen engagement. Overall, this study highlights the potential of ‘farmscaping’— a concept borrowed from entomology and here adapted to the meaning of creating vibrant peri-urban landscapes that support both environmental resilience and communal well-being.

Agroforestry Systems are gaining attention as a sustainable alternative to conventional agriculture, yet there is a lack of practical methods to guide their design by integrating ex-ante participatory ecosystem services (ESs) assessment. This study addresses this gap through participatory action research in Northern Italy, aiming to co-design an innovative agroforestry system by comparing three distinct scenarios: a Successional Agroforestry System (i.e. a multilayered, evolutive agroforestry system based on biomimicry), a traditional mixed orchard, and a conventional hazelnut orchard. The research employed a mixed-method approach, engaging twelve stakeholders, including farmers, technicians, and residents, in a series of participatory workshops. Instrumental ESs, such as carbon sequestration and air pollutant removal, were quantified over a 30-year period using the i-Tree software. Intrinsic ESs, including biodiversity and cultural heritage, were assessed through an expert-based participatory process inspired by the Matrix Model Methodology. The results revealed a clear trade-off. The traditional mixed orchard demonstrated the highest provision of instrumental ES. However, the participatory evaluation highlighted the superior performance of the SAFS (Successional Agroforestry System) in delivering intrinsic and cultural ES, which is better aligned with the long-term ecological and educational objectives of the farm. Consequently, the stakeholders selected the SAFS for implementation.mail id This study demonstrates that integrating quantitative modeling with participatory assessment of intrinsic values provides a robust framework for designing sustainable agroforestry systems that reflect the holistic goals of landowners and local communities. This approach offers a replicable model for evidence-based, collaborative design of multifunctional agricultural landscapes.

The study compares the overall sustainability of two organic and two conventional rice farming systems during the 2022 drought. The research aimed to develop an experiment exploring the ability of an integrated methodological approach to identify tradeoffs and provide actionable insights for a sustainable agricultural transition under extreme climate stress. To this aim, the study employed economic analysis, Life Cycle Assessment (LCA) for environmental impact, and the OASIS framework for broader social and resilience indicators. The study revealed tradeoffs between the economic efficiency of conventional rice farming and the ecological resilience of organic systems, a conclusion made possible only through its integrated assessment methodology. By combining different methods, the research suggested that while conventional farms achieved clear financial superiority and greater efficiency per ton of rice, organic systems showcased superior ecological performance per hectare, greater biodiversity, and enhanced resilience. This highlights a crucial research frontier focused on designing hybrid systems or new economic models that can translate the environmental resilience of organic methods into tangible market value, effectively resolving the very tradeoffs this comprehensive assessment suggested.

Background Land-use change profoundly influences soil microbial communities, yet its impacts on richness and diversity remain incompletely resolved across taxa. Methods Here, we characterized fungal and bacterial communities in soils from four contrasting land-use types—including crop, reforested, agroforestry, and uncultivated land—located in the same pedoclimatic conditions, using high-throughput amplicon sequencing of Internal Transcribed Spacer (ITS) and 16S ribosomal RNA (rRNA) genes. We quantified species richness and Shannon diversity and examined their relationships with key physicochemical parameters. Results Our results reveal that fungal and bacterial communities responded differently to land-use management. Fungal richness was highest in reforested soils, whereas bacterial richness was more uniformly distributed across land uses. Shannon diversity showed greater sensitivity than richness, suggesting that differences in the distribution of relative abundances among taxa contributed substantially to the observed patterns. Multivariate ordinations and correlation analyses further demonstrated that soil properties such as pH, total nitrogen, and cation exchange capacity were significant drivers of microbial community composition and diversity patterns. Conclusions Our study provides new empirical evidence of how land management shapes biodiversity and informs strategies for enhancing soil health and ecosystem potential resilience.