Over the last few years, wildlife damages to the agricultural sector have shown an increasing trend at the global scale. Fragile rural areas are more likely to suffer because marginal lands, which have little potential for profit, are being increasingly abandoned. Moreover, public administrations have difficulties to meet the growing requests for crop damage compensations. There is therefore a need to identify appropriate measures to control this growing trend. The specific aim of this research is to understand this phenomenon and define specific and effective action tools. In particular, the proposed research involves different steps that start from the historic analysis of damages and result in the mapping of risk levels using different tests (ANOVA, PCA and spatial correlation) and spatial models (MCE-OWA). The subsequent possibility to cluster risk results ensures greater effectiveness of public actions. The results obtained and the statistical consistency of applied parameters ensure the strength of the analysis and of costeffectiveness parameters.
Wildlife Agriculture Interactions, Spatial Analysis and Trade-Off Between Environmental Sustainability and Risk of Economic Damage
COZZI, Mario;ROMANO, Severino;VICCARO, MAURO;
2015-01-01
Abstract
Over the last few years, wildlife damages to the agricultural sector have shown an increasing trend at the global scale. Fragile rural areas are more likely to suffer because marginal lands, which have little potential for profit, are being increasingly abandoned. Moreover, public administrations have difficulties to meet the growing requests for crop damage compensations. There is therefore a need to identify appropriate measures to control this growing trend. The specific aim of this research is to understand this phenomenon and define specific and effective action tools. In particular, the proposed research involves different steps that start from the historic analysis of damages and result in the mapping of risk levels using different tests (ANOVA, PCA and spatial correlation) and spatial models (MCE-OWA). The subsequent possibility to cluster risk results ensures greater effectiveness of public actions. The results obtained and the statistical consistency of applied parameters ensure the strength of the analysis and of costeffectiveness parameters.File | Dimensione | Formato | |
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