| Records |
| Author |
Podhora, A.; Helming, K.; Adenäuer, L.; Heckelei, T.; Kautto, P.; Reidsma, P.; Rennings, K.; Turnpenny, J.; Jansen, J. |
| Title |
The policy-relevancy of impact assessment tools: Evaluating nine years of European research funding |
Type |
Journal Article |
| Year |
2013 |
Publication |
Environmental Science & Policy |
Abbreviated Journal |
Environmental Science & Policy |
| Volume |
31 |
Issue |
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Pages |
85-95 |
| Keywords |
impact assessment tools; policy appraisal; science policy interface; sustainable development; european commission; affecting land-use; of-the-art; integrated assessment; sustainable development; agricultural systems; analytical framework; union; part |
| Abstract |
Since 2002, the European Commission has employed the instrument of ex-ante impact assessments (IA) to help focus its policy-making process on implementing sustainable development. Scientific tools should play an essential role of providing the evidence base to assess the impacts of alternative policy options. To identify the contribution of research funding for IA tool development, this paper analysed the variety of IA tools designed in projects funded by European Framework Programmes (FPs) 6 and 7. The paper is based on project information available on the European Cordis website, individual project websites and a verification of the results by the project coordinators. We analysed the projects from the interests of IA practitioners as tool users (European policy and impact areas addressed by the tools, jurisdictional application levels and tool categories). Out of the 7.781 projects funded in FP6 and FP7, 203 could be identified that designed tools for the IA process. Nearly half of them applied to environmental, agricultural and transport policy areas. Within these areas, the tools primarily addressed environmental impact areas, less economic and least social impact areas. The IA tools focused on European policies. Models represented the largest tool category, whereas approximately half of the tools could not be clearly categorized. Concerning our analysis criteria, the tool descriptions available on the internet were often unclear and thus may limit the application potential of the tools because of a mismatch of technical terms and categorisation criteria between tool providers and tool users. Future IA tools require a joint political and scientific typology and a narrowing of the gaps, e.g., with view to multi-jurisdictional application and a clear reference to the steps of the IA process. (C) 2013 Elsevier Ltd. All rights reserved. |
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1462-9011 |
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TradeM |
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MA @ admin @ |
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4500 |
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| Author |
Dietrich, J.P.; Popp, A.; Lotze-Campen, H. |
| Title |
Reducing the loss of information and gaining accuracy with clustering methods in a global land-use model |
Type |
Journal Article |
| Year |
2013 |
Publication |
Ecological Modelling |
Abbreviated Journal |
Ecol. Model. |
| Volume |
263 |
Issue |
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Pages |
233-243 |
| Keywords |
aggregation; downscaling; clustering; information conservation; land use model; scale; scales; agriculture; simulation; dynamics; pattern |
| Abstract |
Global land-use models have to deal with processes on several spatial scales, ranging from the global scale down to the farm level. The increasing complexity of modern land-use models combined with the problem of limited computational resources represents a challenge to modelers. One solution of this problem is to perform spatial aggregation based on a regular grid or administrative units such as countries. Unfortunately this type of aggregation flattens many regional differences and produces a homogenized map of the world. In this paper we present an alternative aggregation approach using clustering methods. Clustering reduces the loss of information due to aggregation by choosing an appropriate aggregation pattern. We investigate different clustering methods, examining their quality in terms of information conservation. Our results indicate that clustering is always a good choice and preferable compared to grid-based aggregation. Although all the clustering methods we tested delivered a higher degree of information conservation than grid-based aggregation, the choice of clustering method is not arbitrary. Comparing outputs of a model fed with original data and a model fed with aggregated data, bottom-up clustering delivered the best results for the whole range of numbers of clusters tested. (C) 2013 Elsevier B.V. All rights reserved. |
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0304-3800 |
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MA @ admin @ |
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4488 |
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Dono, G.; Cortignani, R.; Doro, L.; Giraldo, L.; Ledda, L.; Pasqui, M.; Roggero, P.P. |
| Title |
An integrated assessment of the impacts of changing climate variability on agricultural productivity and profitability in an irrigated Mediterranean catchment |
Type |
Journal Article |
| Year |
2013 |
Publication |
Water Resource Management |
Abbreviated Journal |
Water Resource Manage. |
| Volume |
27 |
Issue |
10 |
Pages |
3607-3622 |
| Keywords |
discrete stochastic programming; climate change variability; adaptation to climate change; net evapotranspiration and irrigation requirements; water availability; epic crops model; economic impact of climate change; precipitation; uncertainty; region; series; yield; model; scale; wheat; gis |
| Abstract |
Climate change is likely to have a profound effect on many agricultural variables, although the extent of its influence will vary over the course of the annual farm management cycle. Consequently, the effect of different and interconnected physical, technical and economic factors must be modeled in order to estimate the effects of climate change on agricultural productivity. Such modeling commonly makes use of indicators that summarize the among environmental factors that are considered when farmers plan their activities. This study uses net evapotranspiration (ETN), estimated using EPIC, as a proxy index for the physical factors considered by farmers when managing irrigation. Recent trends suggest that the probability distribution function of ETN may continue to change in the near future due to changes in the irrigation needs of crops. Also, water availability may continue to vary due to changes in the rainfall regime. The impacts of the uncertainties related to these changes on costs are evaluated using a Discrete Stochastic Programming model representing an irrigable Mediterranean area where limited water is supplied from a reservoir. In this context, adaptation to climate change can be best supported by improvements to the collective irrigation systems, rather than by measures aimed at individual farms such as those contained within the rural development policy. |
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0920-4741 |
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TradeM |
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MA @ admin @ |
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4487 |
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König, H.J.; Uthes, S.; Schuler, J.; Zhen, L.; Purushothaman, S.; Suarma, U.; Sghaier, M.; Makokha, S.; Helming, K.; Sieber, S.; Chen, L.; Brouwer, F.; Morris, J.; Wiggering, H. |
| Title |
Regional impact assessment of land use scenarios in developing countries using the FoPIA approach: findings from five case studies |
Type |
Journal Article |
| Year |
2013 |
Publication |
Journal of Environmental Management |
Abbreviated Journal |
J. Environ. Manage. |
| Volume |
127 Suppl |
Issue |
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Pages |
S56-S64 |
| Keywords |
Conservation of Natural Resources; Developing Countries; Environmental Monitoring/*methods; (Ex-ante) impact assessment; Indicators; Land use change; Scenario study; Stakeholder participation; Sustainable development |
| Abstract |
The impact of land use changes on sustainable development is of increasing interest in many regions of the world. This study aimed to test the transferability of the Framework for Participatory Impact Assessment (FoPIA), which was originally developed in the European context, to developing countries, in which lack of data often prevents the use of data-driven impact assessment methods. The core aspect of FoPIA is the stakeholder-based assessment of alternative land use scenarios. Scenario impacts on regional sustainability are assessed by using a set of nine regional land use functions (LUFs), which equally cover the economic, social and environmental dimensions of sustainability. The cases analysed in this study include (1) the alternative spatial planning policies around the Merapi volcano and surrounding areas of Yogyakarta City, Indonesia; (2) the large-scale afforestation of agricultural areas to reduce soil erosion in Guyuan, China; (3) the expansion of soil and water conservation measures in the Oum Zessar watershed, Tunisia; (4) the agricultural intensification and the potential for organic agriculture in Bijapur, India; and (5) the land degradation and land conflicts resulting from land division and privatisation in Narok, Kenya. All five regions are characterised by population growth, partially combined with considerable economic development, environmental degradation problems and social conflicts. Implications of the regional scenario impacts as well as methodological aspects are discussed. Overall, FoPIA proved to be a useful tool for diagnosing regional human-environment interactions and for supporting the communication and social learning process among different stakeholder groups. |
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0301-4797 |
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TradeM |
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no |
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MA @ admin @ |
Serial |
4474 |
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| Author |
Below, T.B.; Mutabazi, K.D.; Kirschke, D.; Franke, C.; Sieber, S.; Siebert, R.; Tscherning, K. |
| Title |
Can farmers’ adaptation to climate change be explained by socio-economic household-level variables |
Type |
Journal Article |
| Year |
2012 |
Publication |
Global Environmental Change |
Abbreviated Journal |
Glob. Environ. Change |
| Volume |
22 |
Issue |
1 |
Pages |
223-235 |
| Keywords |
Sub-Saharan Africa; Tanzania; Adaptive capacity; Index; Vulnerability; Adaptation; adaptive capacity; environmental-change; south-africa; vulnerability; variability; resilience; tanzania; framework; drought; policy |
| Abstract |
A better understanding of processes that shape farmers’ adaptation to climate change is critical to identify vulnerable entities and to develop well-targeted adaptation policies. However, it is currently poorly understood what determines farmers’ adaptation and how to measure it. In this study, we develop an activity-based adaptation index (AAI) and explore the relationship between socioeconomic variables and farmers’ adaptation behavior by means of an explanatory factor analysis and a multiple linear regression model using latent variables. The model was tested in six villages situated in two administrative wards in the Morogoro region of Tanzania. The Mlali ward represents a system of relatively high agricultural potential, whereas the Gairo ward represents a system of low agricultural potential. A household survey, a rapid rural appraisal and, a stakeholder workshop were used for data collection. The data were analyzed using factor analysis, multiple linear regression, descriptive statistical methods and qualitative content analysis. The empirical results are discussed in the context of theoretical concepts of adaptation and the sustainable livelihood approach. We found that public investment in rural infrastructure, in the availability and technically efficient use of inputs, in a good education system that provides equal chances for women, and in the strengthening of social capital, agricultural extension and, microcredit services are the best means of improving the adaptation of the farmers from the six villages in Gairo and Mlali. We conclude that the newly developed AAI is a simple but promising way to capture the complexity of adaptation processes that addresses a number of shortcomings of previous index studies. |
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0959-3780 |
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TradeM |
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no |
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MA @ admin @ |
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4467 |
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