Catálogo de publicaciones - revistas

<jats:title>Abstract</jats:title><jats:p>In response to the sustainability issues that agriculture faces in advanced economies, agroecology has gained increasing relevance in scientific, political, and social debates. This has promoted discussion about transitions to agroecology, which represents a significant advancement. Accordingly, it has become a growing field of research. We reviewed the literature on and in support of farm transitions to agroecology in advanced economies in order to identify key research challenges and suggest innovative research paths. Our findings can be summarized as follows: (1) Research that supports exploration and definition of desired futures, whether based on future-oriented modeling or expert-based foresight approaches, should more explicitly include the farm level. It should stimulate the creativity and design ability of farmers and other stakeholders, and also address issues of representation and power among them. (2) Research that creates awareness and assesses farms before, during or after transition requires more holistic and dynamic assessment frameworks. These frameworks need to be more flexible to adapt to the diversity of global and local challenges. Their assessment should explicitly include uncertainty due to the feedback loops and emergent properties of transitions. (3) Research that analyzes and supports farms during transition should focus more on the dynamics of change processes by valuing what happens on the farms. Research should especially give more credence to on-farm experiments conducted by farmers and develop new tools and methods (e.g., for strategic monitoring) to support these transitions. This is the first review of scientific studies of farm transitions to agroecology. Overall, the review indicates that these transitions challenge the system boundaries, temporal horizons, and sustainability dimensions that agricultural researchers usually consider. In this context, farm transitions to agroecology require changes in the current organization and funding of research in order to encourage longer term and more adaptive configurations.</jats:p>

<jats:title>Abstract</jats:title><jats:p>Organic mixed livestock farming offers a range of potential benefits for the environment. Due to the diversification of enterprises, this farming system can be associated with a high workload, which means that it could be socially unsustainable. The aim of this study was to understand and explain work satisfaction of farmers running an organic mixed livestock farm. Using a mixed-method approach, quantitative and qualitative data were collected from 102 farmers in seven European countries during face-to-face interviews. We showed for the first time that across Europe and different animal species and category combinations, organic mixed livestock farms can provide a high work satisfaction, despite a high workload. By using a mixed-method approach and a clear framework, we aimed at better understanding work satisfaction. Underlying reasons for work satisfaction included the diversity of tasks, opportunities to learn, autonomy in the work schedule, perceived acknowledgement by consumers, and the contribution to sustainable food production. Factors contributing to work satisfaction identified in the analysis of quantitative data included workload, number of livestock units, mental complexity, proportion of work peaks per year, and the match between wanted free time and time taken off work. The combination of qualitative and quantitative data allowed a deeper understanding of farmers’ work satisfaction and revealed consistent findings. Future research should investigate the relationship between farmers’ work satisfaction and capacity for innovation, flexibility, and adaptation potential.</jats:p>

<jats:title>Abstract</jats:title><jats:p>Long-term active restoration is often employed to restore degraded grasslands. The establishment of a viable soil seed bank is the key to successful restoration, as it enhances the resilience of vegetation. However, little is known of how the soil seed bank affects vegetation resilience following long-term active restoration of degraded grasslands. We determined seed abundance and species composition of the soil seed bank and soil properties and vegetation resilience of intact, degraded, and long-term (&gt;10 years) actively restored grasslands on the Tibetan plateau (3900–4200 m a.s.l.). The plant-soil-seed bank quality index and structural equation modelling (SEM) were used to assess the effect of the soil seed bank on vegetation resilience. After long-term (&gt;10 years) active restoration of degraded grasslands by sowing seeds of native plant species, the densities of transient and persistent seeds increased by 5%, but seed richness (number of species) decreased by 25% when compared with degraded grasslands. This occurred largely as a result of an increase in grass but decrease in forb seeds. Persistent seeds of grasses play an important role in the productivity of restored grasslands, while the density of persistent seeds serves as an indicator of the resilience of vegetation. A combination of the plant community and soil properties determined seed density. Here, we show for the first time that long-term active restoration enhances vegetation resilience of grasslands by altering the soil seed bank. A high seed density of sown Gramineae and a low seed density of forbs in the soil seed bank is a key to the successful active restoration of degraded grasslands.</jats:p>

<jats:title>Abstract </jats:title><jats:p>With the rapid growth of professional intra-urban agriculture (PIUA) projects in the Global North, sponsors, projects leaders, and experts developing these projects are seeking to evaluate their sustainability. As existing assessment tools are not adapted to PIUA projects, they establish their own assessment practices. Our study examines these practices to identify their original features, criteria, and indicators used. To this end, we analysed 19 case studies of different PIUA projects. We identified four dimensions underpinning sustainability assessment, namely, internal sustainability, external sustainability, the project leader’s credibility, and the innovative nature of the project. We also shed light on the wide diversity of the 67 assessment criteria identified, as well as the qualitative nature of 78% of indicators used. In addition, our study highlights that assessment practices evolve over time as the project progresses from ideation to implementation, according to the variety of assessment situations. Our study is the first to provide an in-depth exploration of PIUA stakeholders’ sustainability assessment practices and to shed light on their specific features. Our results afford a better understanding of the way the sustainability of PIUA projects is assessed and contribute to reflection on the design of a flexible assessment tool, considering the diverse criteria and practices used by stakeholders to assess the sustainability of PIUA.</jats:p>

<jats:title>Abstract</jats:title><jats:p>Cropping system models are deployed as valuable tools for informing agronomic decisions and advancing research. To meet this demand, early career scientists are increasingly tasked with building crop models to fit into these system modelling frameworks. Most, however, receive little to no guidance as to how to do this well. This paper is an introduction to building a crop model with a focus on how to avoid pitfalls, minimize uncertainty, and maximize value. We synthesized knowledge from experienced model builders and literature on various approaches to model building. We describe (1) what to look for in a model-building dataset, (2) how to overcome gaps in the dataset, (3) different approaches to fitting and testing the model, and (4) how to avoid common mistakes such as over-parameterization and over-fitting the model. The process behind building a crop model can be overwhelming, especially for a beginner, and so we propose a three-pronged approach: conceptualize the model, simplify the process, and fit the model for a purpose. We revisit these three macrothemes throughout the paper to instil the new model builder with the methodical mindset needed to maximize the performance and impact of their crop model.</jats:p>

<jats:title>Abstract</jats:title><jats:p>The need for better understanding and conservation of wild plant resources with potential for domestication or utilization in crop improvement has been highlighted in recent years. Botanical resources such as herbaria, databases, and floras offer an information-rich platform from which to select species of interest based on desirable traits. To demonstrate the potential of these resources, wild, native forage legumes were screened for inclusion in northern Swedish grassland agricultural systems (leys). The poor persistence of red clover in multi-year leys is a limitation to the current management strategy in the region. Wild, native forage legumes with the potential for longer persistence were considered for inclusion as minor components in leys to contribute to the system in later years of production. Using the Umeå University Herbarium, local floras, and both regional and international biodiversity databases, seven wild forage legume species were selected based on phenology, morphology, and native range. Particular focus was given to the potential for species to provide pollinator resources early in the season, leading to species with early flowering being preferred. Biodiversity databases were also used to locate wild populations of the selected species to facilitate seed collection for future cultivation, as additional study of the agronomic potential of the selected species is necessary. Here, we have shown that the rich biodiversity data stored in botanical institutions can jumpstart the selection of wild species for utilization in the agriculture sector based on various traits of interest.</jats:p>