Karen Tscherning

Ex Ante Impact Assessment of Policies Affecting Land Use, Part A: Analytical Framework

Contemporary policy making calls for scientific support to anticipate the possible consequences of optional policy decisions on sustainable development. This paper presents an analytical framework for ex ante assessment of economic, social, and environmental impacts of policy driven land use changes that can be used as an aid to policy making. The tasks were to (1) link policy scenarios with land use change simulations, (2) link land use change simulations with environmental, social, and economic impacts through indicators, and (3) valuate the impacts in the context of sustainable development. The outcome was a basis for dialogue at the science-policy interface in the process of developing new policies on the European level that impact on land and land use. The analytical approach provides a logical thread for ex ante impact assessment within the context of sustainable development, land use multifunctionality, and land use change and it provides a thorough discussion of achievements and open challenges related to the framework. It concludes with considerations on the potential for using evidence based ex ante assessments in the process of policy development. The paper is complemented by a B-paper providing exemplary results from two applications of the framework: a financial reform scenario of the Common Agricultural Policy of the European Union, and a bioenergy policy scenario for the case of Poland (Helming et al. 2011).

Ex ante impact assessment of land use changes in European regions: the SENSOR approach

Land use includes those human activities that exhibit a spatial dimension and that change the bio-geophysical conditions of land. Land use policy making at European level aims at fostering sustainability pathways of natural resource use and rural development through the decoupling of economic growth from environmental degradation while supporting social cohesion in rural areas. Targeted policy making requires tools for the ex ante assessment of impacts of policy driven land use changes on sustainable development opportunities in European regions. These tools have to cover all relevant land use sectors and impact issues including their interrelations. They have to be spatially explicit, allow scenario analysis of possible future developments, be based on reproducible analyses, and be transparent and easy to use. The European Commission funded Integrated Project SENSOR is dedicated to develop such ex-ante Sustainability Impact Assessment Tools (SIAT) for land use in European regions. SIAT is designed as a meta modelling toolkit, in which global economic trend and policy scenarios are translated into land use changes at 1km2 grid resolution for the area of Europe. Based on qualitative and quantitative indicator analyses, impacts of simulated land use changes on social, environmental and economic sustainability issues are assessed at regional (NUTS2/3) scale. Valuation of these impacts is based on the concept of multifunctionality of land use. It is conducted through expert and stakeholder valuations leading to the determination of sustainability choice spaces for European regions. This paper presents the analytical approach in SENSOR and describes the impact assessment framework.

Transfer into decision support: The Sustainability Impact Assessment Tool (SIAT)

This paper focuses on the development process and performance of the integrated meta-model Sustainability Impact Assessment Tool (SIAT), whose appropriateness for Sustainability Impact Assessment is finally discussed.

Ex-ante Impact Assessments (IA) in the European Commission — an overview

Ex-ante Impact Assessment (IA) was officially introduced into European Commission (EC) policy making in 2002. It is understood as a formal procedure to analyse potential effects of new policies before their adoption. The two main drivers behind this EC initiative are the EU Sustainable Development Strategy and the Better Regulation agenda. IA is carried out on policy level by the Secretariat General of the EC.

Assessing the determinants of poverty and vulnerability of smallholder farmers in a changing climate: the case of Morogoro region, Tanzania

Abstract This paper analyses the determinants of poverty and vulnerability of smallholder farmers in the rural areas in the face of climate change. The data were collected through a cross-sectional survey conducted between December 2009 and January 2010 covering 240 households in six villages of Morogoro region, Tanzania. Descriptive and the econometric approaches involving three-stage least squares (3SLS) and generalized methods of moments (GMM) regressions were used to analyse poverty and vulnerability. Results indicate that income poverty was prevalent in the study area—based on a daily income per capita poverty line of US

Food security in the context of climate change and bioenergy production in Tanzania: methods, tools and applications

1.25. The income poverty was relatively higher in agro-climatically less-favourable area than in favoured areas. Over three quarters of the sample households were vulnerable. The pattern of future vulnerability tended to overlap with poverty rates. Ageing of the household head tended to increase the level of vulnerability. Large-sized households were more income-poor than their counterpart small-sized households. Farming experience reduced the probability of future vulnerability. Increased farm size enhanced the level of income, and further increase in farm size reduced future vulnerability. Higher income contributed to wealth formation through improved access to assets and housing amenities. Farmers who perceived that climate change is human-induced tended to have significantly higher income than otherwise. The following conclusions with policy implications are drawn from the findings: (1) addressing poverty and vulnerability of farmers is critical particularly in relatively agro-ecologically less-favoured areas that are prone to climate change impacts, (2) old-age-related vulnerability must be addressed through dedicated policies and programmes, (3) increasing farm size would enhance smallholder farm income, (4) awareness creation among farmers on climate change drivers and processes by highlighting anthropogenic contribution is important in order to influence local adaptation and mitigation practices, and (5) improving rural income will advance wealth creation and foster local livelihood resilience to shocks including climate change.

Meta-Modelling for cross-sectoral Land Use Policy Impact Analysis: A Model requirements analysis of the SIAT

A dramatic population growth is projected for the least developed countries of the world (United Nations 2013), which will also suffer disproportionally from ongoing and predicted climate disruptions (IPCC 2013). More frequently occurring extreme weather events have led to yield losses and decreasing cattle populations—aggravating an already precarious situation and leading to critical food shortages. Food security is a function of food availability, food accessibility, food stability and food utilisation (FAO 2002; Ziervogel and Ericksen 2010). Climate change and population growth are seen as key drivers of food insecurity severely affecting farming systems (Muller et al. 2011; Haberl et al. 2011, Strengers et al. 2010), as well as the global energy demand and therefore induced biofuel production (Von Braun 2007a), changing trade patterns through liberalisation and globalisation (Von Braun 2007b; Lotze-Campen et al. 2010), and the state of health of the population (10–20 % AIDS rate in East Africa). Cause– effect chains, in which food security is involved (droughts– diseases–health–human capital), are also drivers over large regions (Ziervogel and Ericksen 2010). Most of these drivers do not only lead to a productivity decline, but also often result in a degraded natural resource base and declining soil fertility (Graef et al. 2000). Rapidly changing framework conditions (Muller 2011) require a thorough understanding of integrated food systems and targeted incorporation of region-specific innovations. However, creating a sustainable road map for the future is a huge challenge for a variety of reasons. Mainly rainfed, subsistence-oriented smallholder farming systems are not only extremely vulnerable to a changing and unpredictable climate, but often also lack access to external inputs, institutional support and adaptive capacity. Moreover, food insecurity is often regarded as insufficient food availability which is only part of the picture. Instead of solely focussing on boosting crop yields, the highly complex state of vulnerability needs to be addressed encompassing economic and sociopolitical factors (Misselhorn 2004; Pretty et al. 2006). Also, increased bioenergy production has fuelled land use conflicts and lead to largescale deforestation due to the growing international demand for biofuels. Biomass is still the primary source of energy in developing countries—important for income, energy supply, poverty reduction and self-sufficiency of rural communities (Harvey and Pilgrim 2011; Mitchell 2011; Tilman et al. 2009). Effective climate change adaptation and food security intervention strategies need to pursue a holistic approach and an array of objectives: social and economic viability, soil health, minimum use of scarce water and fossil energy, affordable and low external inputs, improvement in infrastructure and market access, as well as conservation of natural resources and biodiversity. To achieve positive impacts and sustainable solutions, international research projects increasingly focus on integrated in-depth analysis of the food system itself and its core elements: (a) natural and human resources, (b) the use of Disclaimer The views expressed are purely those of the authors and may not in any circumstances be regarded as stating an official position of the European Commission.

Can farmers’ adaptation to climate change be explained by socio-economic household-level variables?

The Integrated Project SENSOR developed the meta-model Sustainability Impact Assessment Tools (SIAT) to support decision making at the EU level (Sieber et al. 2008). First, this paper illustrates the concept on the functionality and methodology of the meta-model SIAT. Based on the development process and applied methods of software prototyping major model requirements have been elaborated. Four major requirement fields have been revealed. They can be subsumed into the categories of (1) performance, (2) integration, (3) institution and (4) quality (IIPQ), whereas point (1) is classified (a) spatial scales, (b) sectors and (c) indicator variables, (d) dynamic viability over time, (e) flexible system to select the level of implicit and explicit knowledge; point (2) is classified in (a) model response time (b) diversity of visualization results, (c) advanced technologies and system compatibility; point (3) on reliability information is structured in the three fields of (a) quality criteria on results, (b) assumptions and (c) back tracing. The point (4) on institutional embedment links the institutions; either trough stakeholder participation or expert consultations. The SIAT is finally classified according to the given criteria. The paper concludes on further requirements to maintain the model beyond project lifetime. Mainly funding issues, complementary further institutional embedment, flexibility towards new scopes of analysis, quality assurance and scientific publications have been described as major future challenges.