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Gilioli G.,University of Brescia | Tikubet G.,African Institute for Capacity Development | Herren H.R.,Millennium Institute | Baumgartner J.,Global Center for the Analysis of Sustainable Agricultural Systems Global
International Journal of Agricultural Sustainability | Year: 2015

In a peri-urban poverty-stricken community in the outskirts of Addis Ababa, Ethiopia, 15 years of development efforts were undertaken by establishing an enterprise, which initially consisted of a horticultural farm and finally was composed of a multifunctional farm and a restaurant with a shop. The enterprise collaborated with BioEconomy Africa, which was charged with administrative, monitoring and facilitation tasks, and provided a training, demonstration and research facility. In the innovation process, the enterprise selected technologies and implemented them within the context of local economic and market conditions. The project benefitted from a flexible allocation of modest funds. This paper assesses the sustainability of the enterprise and the community on the basis of social–ecological system transformability and resilience. The scheme of the Food and Agriculture Organization is used to evaluate the transformability, while resilience is evaluated through self-organization capacity, disturbance absorption capacity, and learning and adaptability. The project period was divided into five Macro-phases. The transformability assessment of the enterprise revealed nonlinear and asynchronous dynamics of environmental sustainability, economic resilience, social well-being and governance that after reaching a minimum attained a maximum at the end of the period under observation. The resilience assessments showed that the self-organization capacity, the disturbance absorption capacity, and learning and adaptability slowly changed to reach a satisfactory level at the end of the observation period. The changes in transformability and resilience profoundly affected the livelihood of the community. The paper demonstrates the important role of agricultural in the development of poverty-stricken peri-urban communities and indicates that innovation processes and the efficiency of facilitation extension model implementation can be enhanced by applying adaptive project execution procedures. It can be concluded that the continuous monitoring and assessments of transformability and resilience are a prerequisite for efficiently moving the socio-ecological system on a smooth road towards a socially acceptable standard of living. © 2014 Taylor & Francis. Source

Gilioli G.,University of Brescia | Gilioli G.,Global Center for the Analysis of Sustainable Agricultural Systems Global | Pasquali S.,CNR Institute for Applied Mathematics and Information Technologies
Ecological Modelling | Year: 2016

Physiologically based demographic models are important tools for the development of sustainable pest management as they can realistically describe the spatio-temporal dynamics of population abundance as function of environmental forcing variables, e.g. temperature and resource availability. The physiological based model presented here is based on a stochastic demographic model for a stage-structured population that has application to a wide range of species across different taxa. The species life-history strategies are described in terms of a set of biodemographic rate functions dependent from the biological characteristics of the species and their environmental driver variables. Model application required parameter estimation of the biodemographic rate functions at two levels: assessing physiological responses at the per capita level and/or using population time series data for rate functions estimation. To explore the usefulness of the modelling framework in pest management, we consider the case study of the grape berry moth Lobesia botrana, a major pest in European vineyard. Most of the model parameters were estimated from data in the literature. An unpublished dataset of population dynamics collected in a vineyard in the Veneto region (Italy) over three years was used to estimate the mortality function. Model validation was performed with a set of independent data. Model simulations provided realistic trajectories of population dynamics obtained with a limited dataset of initial conditions. The suitability of the model as a tool for decision support for grape berry moth management is discussed. © 2015 Elsevier B.V. Source

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