Scenario development to explore the future of Europe's rural areas

Westhoek, H.; Berg, M. van den; Bakkes, Jan

doi:10.1016/j.agee.2005.11.005

Cited by 173 publications

(112 citation statements)

References 13 publications

Supporting

Mentioning

107

Contrasting

Unclassified

Order By: Relevance

“…To account for possible future trends in socio-economic developments, we used scenarios A1 Global Economy and B2 Regional Communities from the commonly used Dutch WLO scenarios (van Drunen and Berkhout 2008). These scenarios are adapted from Westhoek et al (2006) for the situation in The Netherlands, and are similar to the IPCC SRES scenarios (Nakicenovic and Swart 2000). Following suggestions of Henseler et al (2009) we assume that the more economically and globally oriented A1 scenario goes with a significant temperature increase of 2°C by 2050, i.e.…”

Section: Scenariosmentioning

confidence: 99%

Scenarios of long-term farm structural change for application in climate change impact assessment

2012

View full text Add to dashboard Cite

Towards 2050, climate change is one of the possible drivers that will change the farming landscape, but market, policy and technological development may be at least equally important. In the last decade, many studies assessed impacts of climate change and specific adaptation strategies. However, adaptation to climate change must be considered in the context of other driving forces that will cause farms of the future to look differently from today's farms. In this paper we use a historical analysis of the influence of different drivers on farm structure, complemented with literature and stakeholder consultations, to assess future structural change of farms in a region under different plausible futures. As climate change is one of the drivers considered, this study thus puts climate change impact and adaptation into the context of other drivers. The province of Flevoland in the north of The Netherlands was used as case study, with arable farming as the main activity. To account for the heterogeneity of farms and to indicate possible directions of farm structural change, a farm typology was developed. Trends in past developments in farm types were analyzed with data from the Dutch agricultural census. The historical analysis allowed to detect the relative importance of driving forces that contributed to farm structural changes. Simultaneously, scenario assumptions about changes in these driving forces elaborated at global and European levels, were downscaled for Flevoland, to regional and farm type level in order to project impacts of drivers on farm structural change towards 2050. Input from stakeholders was also used to detail the downscaled scenarios and to derive historical and future relationships between drivers and farm structural change. These downscaled scenarios and future driver-farm structural change relationships were used to derive quantitative estimations of farm structural change at regional and farm type level in Flevoland. In addition, stakeholder input was used to also derive images of future farms in Flevoland. The estimated farm structural changes differed substantially between the two scenarios. Our estimations of farm structural change provide a proper context for assessing impacts of and adaptation to climate change in 2050 at crop and farm level.

show abstract

Section: Scenariosmentioning

confidence: 99%

Scenarios of long-term farm structural change for application in climate change impact assessment

2012

View full text Add to dashboard Cite

show abstract

“…The role of such scenarios is to make explicit what the alternative assumptions, beliefs and attitudes are and the role of simulation models to show the various contrasting and even surprising outcomes that can confirm or deny the various expectations. That aspect, the correspondence between what should be and what will be may fuel discussions and self-reflection (Klijn et al 2005;Westhoek et al 2006). Characteristic for such scenario studies is the focus on medium to long-term development.…”

Section: Introductionmentioning

confidence: 99%

A multi-scale, multi-model approach for analyzing the future dynamics of European land use

2007

View full text Add to dashboard Cite

Europe's rural areas are expected to witness massive and rapid changes in land use due to changes in demography, global trade, technology and enlargement of the European Union. Changes in demand for agricultural products and agrarian production structure are likely to have a large impact on landscape quality and the value of natural areas. Most studies address these changes either from a macro-economic perspective focusing on changes in the agricultural sector or from a local perspective by analyzing recent changes in landscapes for small case studies. This paper describes a methodology in which a series of models has been used to link global level developments influencing land use to local level impacts. It is argued that such an approach is needed to properly address the processes at different scales that give rise to the land use dynamics in Europe. An extended version of the global economic model (GTAP) and an integrated assessment model (IMAGE) are used to calculate changes in demand for agricultural areas at the country level while a spatially explicit land use change model (CLUE-s) was used to translate these demands to land use patterns at 1 km 2 resolution. The global economic model ensures an appropriate treatment of macro-economic, demographic and technology developments and changes in agricultural and trade policies influencing the demand and supply for land use related products while the integrated assessment model accounts for changes in productivity as result of climate change and global land allocation. The land use change simulations at a high spatial resolution make use of country specific driving factors that influence the spatial patterns of land use, accounting for the spatial variation in the biophysical and socio-economic environment. Results indicate the large impact abandonment of agricultural land and urbanization may have on future European landscapes. Such results have the potential to support discussions on the future of the rural area and identify hot-spots of landscape change that need specific consideration. The high spatial and thematic resolution of the results allows the assessment of impacts of these changes on different environmental indicators, such as carbon sequestration and biodiversity. The global assessment allows, at the same time, to account for the tradeoffs between impacts in Europe and effects outside Europe. JEL Classification

show abstract

“…Renwick et al (2013) combined the Common Agricultural Policy Regionalized Impact (CAPRI) modelling system and Dyna-CLUE models to examine the potential impact of agricultural land-use conversion and trade policy reform on land use across the European Union (EU). Verburg, Eickhout, and Meijl (2008) presented a scenario-based modelling approach to support policy discussions as developed in the Eururalis project (Westhoek, van den Berg, and Bakkes 2006), and to link global level developments influencing land use to local level impacts; three models are linked together: an extended version of the global economic model GTAP (Global Trade Analysis Project), the IMAGE (Integrated Model to Assess the Global Environment) model, and CLUE-s.…”

Section: Introductionmentioning

confidence: 99%

Historical and future land-cover changes in the Upper Ganges basin of India

Tsarouchi

Mijic

Moulds

et al. 2014

International Journal of Remote Sensing

View full text Add to dashboard Cite

The green revolution represents one of the greatest environmental changes in India over the last century. The Upper Ganges (UG) basin is experiencing rapid rates of change of land cover and irrigation practices. In this study, we investigated the historical rate of change and created future scenario projections by means of 30 m-resolution multitemporal Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper Plus data of the UG basin. Post-classification change analysis methods were applied to Landsat images in order to detect and quantify land-cover changes in the UG basin. Subsequently, Markov chain analysis was applied to project future scenarios of land-cover change. Fifteen different scenarios were generated based on historic land-cover change. These scenarios diverged in terms of future projections, highlighting the dynamic nature of the changes. This study has shown that between the years 1984 and 2010 the main land-cover change trends are conversion from shrubs to forest (+4.7%), urbanization (+5.8%), agricultural expansion (+1.3%), and loss of barren land (-9.5%). The land-cover change patterns in the UG basin were mapped and quantified, showing the capability of Landsat data in providing accurate land-cover maps. These results, in combination with those derived from the Markov model, provide the necessary evidence base to support regional land-use planning and develop future-proof water resource management strategies.

show abstract

Scenario development to explore the future of Europe's rural areas

Cited by 173 publications

References 13 publications

Scenarios of long-term farm structural change for application in climate change impact assessment

Scenarios of long-term farm structural change for application in climate change impact assessment

A multi-scale, multi-model approach for analyzing the future dynamics of European land use

Historical and future land-cover changes in the Upper Ganges basin of India

Contact Info

Product

Resources

About