Assessing the adaptation of arable farmers to climate change using DEA and bio-economic modelling

The objective of this article is to assess the impact of climate change on arable farming systems in Flevoland (the Netherlands) and to explore the adoption of different adaptation strategies. Data Envelopment Analysis (DEA) is applied that uses empirical data from individual farms to identify “best” current farm practices and derive relationships regarding current farm managemen

Integrated assessment of farm level adaptation in Flevoland, the Netherlands: what did we learn from multiple methods and model chains

Climate change impact assessment requires farming systems analysis and integrated assessment. However, multiple models can be used to assess changes in drivers. In addition, farms are complex systems and many assumptions need to be made regarding objectives and constraints. Here, we evaluate the impact of different models and assumptions on impacts of climate change on arable agriculture in Flevoland, the Netherlands. We performed three studies. Firstly, we used the crop model WOFOST, market model CAPRI, and bio-economic farm model FSSIM. Secondly, we used the crop model SIMPLACE, an adapted version of CAPRI, and a different set up of FSSIM. Thirdly, we used the crop model WOFOST, estimates of impacts of extreme events by the Agro Climate Calender, and the bio-economic farm model FarmDesign. In general, climate change is projected to have positive impacts. The first two studies however showed that impacts of technology and price changes are larger. But while changes in gross margins are more influenced by results from crop and market models, changes in farm plans are more influenced by assumptions regarding resources and constraints. Assumptions regarding the available land for rent largely influence results. The third study showed that when policy constraints are neglected, impacts on gross margin are more positive. Positive impacts of average climate change may however be counterbalanced by negative impacts of extreme events, but adaptation measures are available. When considering soil quality as important objective, adaptation at farm level will be different: instead of more potato or sugar beet, farms will grow more wheat. We conclude that climate change impacts depend on assumptions, but when making this transparent, it can inform adaptation

Intelligent multimedia indexing and retrieval through multi-source information extraction and merging

This paper reports work on automated meta-data\ud creation for multimedia content. The approach results\ud in the generation of a conceptual index of\ud the content which may then be searched via semantic\ud categories instead of keywords. The novelty\ud of the work is to exploit multiple sources of\ud information relating to video content (in this case\ud the rich range of sources covering important sports\ud events). News, commentaries and web reports covering\ud international football games in multiple languages\ud and multiple modalities is analysed and the\ud resultant data merged. This merging process leads\ud to increased accuracy relative to individual sources

Adapting agriculture in 2050 in Flevoland; perspectives from stakeholders

Although recently more research has gone into farm level studies, little attention has been given to the variety of responses of farmers, considering their characteristics, objectives and the socio-economic, technological and political contexts (Reidsma et al, 2010). In the Agri-Adapt project we focus on farm level adaptation within an agricultural region considering the socio-economic context of 2050

Climate change adaptation in agriculture; the use of multi-scale modelling and stakeholder participation in the Netherlands

Abstract about a research project to develop a methodology to assess adaptation of agriculture to climatic and socio-economic changes at multiple scales, with a first application in the Province of Flevoland, the Netherlands

Tailoring information about climate change and its impacts

Resultaten van onderzoek naar klimaatverandering en de mogelijke effecten zijn vaak niet beschikbaar in een vorm waarin ze direct door anderen gebruikt kunnen worden. Gebruikers van klimaat- en impactinformatie hebben vaak ook geen goed overzicht over de beschikbare gegevens van alle sectoren en resultaten zijn soms inconsistent