Impacts of fragmentation and neighbor influences on farmland conversion: A case study of the Edmonton-Calgary Corridor, Canada. (November 2015)

• Record Type: Journal Article
• Authors: Qiu, Feng; Laliberté, Larry; Swallow, Brent; Jeffrey, Scott
• Is Part Of: Land use policy. Volume 48(2015:Jul.)
• Page Start: 482
• Page End: 494
• Publication Date: 2015-11
• Subjects: Farmland conversion -- Fragmentation -- Neighbor influences -- Spatial regression; Land use -- Periodicals; Land use -- Government policy -- Periodicals; Sol, Utilisation du -- Périodiques; Sol, Utilisation du -- Politique gouvernementale -- Périodiques; Electronic journals; 333.7305
• DOI: 10.1016/j.landusepol.2015.06.024
• Languages: English
• ISSNs: 0264-8377

Abstract

Highlights: Quantify land fragmentation within the context of agriculture. Examine effects of fragmentation and neighboring influences on farmland conversion. Increases in fragmentation further encourage farmland conversion. Land-use activities and decisions have strong spillover effects on neighboring areas. To design and implement effective strategies, regional policy makers need to collaborate and cooperate with each other. Abstract: Under heavy development pressure, farmland is rapidly being converted to non-agricultural uses such as houses, roads, and industrial uses. A great deal of research has investigated these farmland losses and their associated drivers. However, the existing empirical studies have neglected two important issues related to farmland conversion: spillover effects from neighboring areas and the impacts of farmland fragmentation. This study incorporates fragmentation and neighboring impacts into the farmland conversion analysis and provides new insights for the land-use/cover change literature. Empirical results indicate that increases in fragmentation further encourage farmland conversion to urban uses, but the effects are not linear with decreasing marginal influences. Land-use activities and decisions have strong spillover effects on neighboring areas. Ignoring this externality could result in biased estimates and marginal effects and thus misleading policy decisions and recommendations.