Integrated assessment of future CAP policies: land use changes, spatial patterns and targeting

Piorr, Annette; Ungaro, Fabrizio; Ciancaglini, Arianna; Happe, Kathrin; Sahrbacher, Amanda; Sattler, Claudia; Uthes, Sandra; Zander, Peter

doi:10.1016/j.envsci.2009.01.001

Cited by 90 publications

(52 citation statements)

References 9 publications

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“…Such behavioral validations are still a challenge in ABM [69,70,72]. In contrast to other ABM studies addressing farmland abandonment [40][41][42]45], however, we do not model individual farms and remain within the structure of traditional normative farm sector supply modeling approaches [56]. One key challenge in such normative approaches is that corner solutions emerge and these only change if input parameters vary considerably or additional restrictions are introduced into the model structure [56].…”

Section: Discussionmentioning

confidence: 99%

“…Existing ABM studies that address farmland abandonment and that consider individual farm decision-making underline the importance of a spatially explicit examination of the linkage between social behavior and environmental factors, and consequently the dynamic heterogeneity of land abandonment and re-forestation [40][41][42][43][44][45]. None of these studies, however, explicitly discusses the consequences of implementing a particular representation of decision-making and the associated short or long term perspective into their model structure.…”

Section: Introductionmentioning

confidence: 99%

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Sensitivity Analysis of a Land-Use Change Model with and without Agents to Assess Land Abandonment and Long-Term Re-Forestation in a Swiss Mountain Region

Brändle

Langendijk

Peter³

et al. 2015

Land

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Land abandonment and the subsequent re-forestation are important drivers behind the loss of ecosystem services in mountain regions. Agent-based models can help to identify global change impacts on farmland abandonment and can test policy and management options to counteract this development. Realigning the representation of human decision making with time scales of ecological processes such as reforestation presents a major challenge in this context. Models either focus on the agent-specific behavior anchored in the current generation of farmers at the expense of representing longer scale environmental processes or they emphasize the simulation of long-term economic and forest developments OPEN ACCESSLand 2015, 4 476 where representation of human behavior is simplified in time and space. In this context, we compare the representation of individual and aggregated decision-making in the same model structure and by doing so address some implications of choosing short or long term time horizons in land-use modeling. Based on survey data, we integrate dynamic agents into a comparative static economic sector supply model in a Swiss mountain region. The results from an extensive sensitivity analysis show that this agent-based land-use change model can reproduce observed data correctly and that both model versions are sensitive to the same model parameters. In particular, in both models the specification of opportunity costs determines the extent of production activities and land-use changes by restricting the output space. Our results point out that the agent-based model can capture short and medium term developments in land abandonment better than the aggregated version without losing its sensitivity to important socio-economic drivers. For comparative static approaches, extensive sensitivity analysis with respect to opportunity costs, i.e., the measure of benefits forgone due to alternative uses of labor is essential for the assessment of the impact of climate change on land abandonment and re-forestation in mountain regions.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Sensitivity Analysis of a Land-Use Change Model with and without Agents to Assess Land Abandonment and Long-Term Re-Forestation in a Swiss Mountain Region

Brändle

Langendijk

Peter³

et al. 2015

Land

View full text Add to dashboard Cite

show abstract

“…The most common quantitative method to study farm structural change is using econometric models, as shown in the review by Zimmermann et al (2009), or agent-based models as applied by Piorr et al (2009). However, nearly all of the past studies had short time horizons.…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, a long time horizon brings many uncertainties as to how future farm development will unfold in the context of multiple drivers of change acting at different levels. Agent-based models may provide a more realistic approach, but also in these models decisions are often based on profit maximization (Piorr et al 2009). Valbuena et al (2010) developed rules reflecting current farmers' behavior, but their study focused on specific decisions.…”

Section: Introductionmentioning

confidence: 99%

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

2012

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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.

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“…Nitrate leakage was assessed using an indicator-based, fuzzy-logic method (Zander and Kächele 1999;Mertens and Huwe 2002;Zander 2003;Piorr et al 2009). Fuzzy logic is based on the idea that the boundary between suitability and unsuitability (or acceptance and rejection) of an agricultural practice is not clear, but rather blurred or 'fuzzy' (Phillis and Andriantiatsaholiniaina 2001).…”

Section: Introductionmentioning

confidence: 99%

Assessment of nitrate leakage and N2O emission from five environmental-friendly agricultural practices using fuzzy logic method and empirical formula

Qin

Wang

et al. 2015

Environ Monit Assess

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Agricultural nonpoint source pollution in China has been the major environmental problem, so environmental-friendly agricultural practices (EAPs) must be promoted to improve environmental quality. However, the most suitable practices for each agricultural region must first be identified. Thus, in the presented study a fuzzy-logic method and a revised empirical formula were used to assess nitrate leakage and N 2 O emissions, respectively, and to compare five EAPs in Xinxiang, a major grain-producing county in Henan Province, China. The required information was collected in face-to-face interviews with 10 extension service experts from the county, using a questionnaire to explore their opinions of the EAPs currently adopted by smallholder farmers, as well as the amounts, frequencies, varieties and proportions of nitrogen fertilizers applied annually. The results indicate that reduced tillage, soil testing and fertilizer recommendations would be the most appropriate practices to initially promote on a large scale in Xinxiang.

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Integrated assessment of future CAP policies: land use changes, spatial patterns and targeting

Cited by 90 publications

References 9 publications

Sensitivity Analysis of a Land-Use Change Model with and without Agents to Assess Land Abandonment and Long-Term Re-Forestation in a Swiss Mountain Region

Sensitivity Analysis of a Land-Use Change Model with and without Agents to Assess Land Abandonment and Long-Term Re-Forestation in a Swiss Mountain Region

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

Assessment of nitrate leakage and N2O emission from five environmental-friendly agricultural practices using fuzzy logic method and empirical formula

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