This paper presents a framework to model future residential demand for housing in a polycentric region. The model, called HI-LIFE (Household Interactions through LIFE cycle stages), builds on ...Agent-Based Modelling (ABM) paradigms. In contrast to traditional equilibrium-based urban economics models that assume a homogenous population of rational actors, ABM focuses on the diversity of heterogeneous household agents and their behaviour in time and in space. The model simulates land-use patterns at the regional scale by integrating qualitative knowledge of agent location preferences with quantitative analysis of urban growth dynamics within a high resolution spatial modelling framework. The model was calibrated for the region of East Anglia in the UK using a semi-quantitative procedure. Simulation of urban dynamics for the future was undertaken for a 25 year period with the assumption of a continuation of baseline behavioural trends. The results demonstrated non-uniform, spatial patterns of urban sprawl with some locations experiencing greater urban development pressure than others. The town of Brundall, in particular, has a large potential demand for residential housing because of its proximity to the principle city, Norwich. As Brundall is also located close to a national park and a river, new housing development in this area would increase the risk of ecological impacts and flood damage. By modelling explicitly agent behaviour and interactions, ABM can simulate the response and adaptation strategies of a population to changing circumstances. This makes ABM especially well suited to the analysis of environmental change and landscape ecology pressures through scenario modelling.
Understanding cross-sectoral impacts is important in developing appropriate adaptation strategies to climate change, since such insight builds the capacity of decision-makers to understand the full ...extent of climate change vulnerability, rather than viewing single sectors in isolation. A regional integrated assessment model that captures interactions between six sectors (agriculture, forests, biodiversity, water, coasts and urban) was used to investigate impacts resulting from a wide range of climate and socio-economic scenarios. Results show that Europe will be significantly influenced by these possible future changes with between 79 and 91 % of indicator-scenario combinations found to be statistically significantly different from the baseline. Urban development increases in most scenarios across Europe due to increases in population and sometimes GDP. This has an indirect influence on the number of people affected by a 1 in 100 year flood which increases in western and northern Europe. Changes in other land uses (intensive farming, extensive farming, forests and unmanaged land) vary depending on the scenario, but food production generally increases across Europe at the expense of forest area and unmanaged land to satisfy increasing food demand. Biodiversity vulnerability and water exploitation both increase in southern and Eastern Europe due to direct effects from climate and indirect effects from changes in land use and irrigation water use. The results highlight the importance of considering non-climatic pressures and cross-sectoral interactions to fully capture climate change impacts at the regional scale.
Identifying and interpreting the heterogeneity of farmer behaviour is becoming increasingly important in support of policy- and decision-making goals. This paper explores whether observed differences ...in farming practices can be interpreted from the heterogeneity of farmer behaviour. Farmer attitudes and objectives were analysed using a combination of principal components and cluster analysis applied to responses to statements in a telephone-based survey. Respondents were classified into four profiles; business-oriented, lifestylers, multifunctionalists and traditionalists. Each profile differed in terms of farm management practices, the amount of land farmers either managed or owned, the existence of successors and the importance placed on household members in providing information. The results suggest that knowledge of farmer behavioural profiles could support more targeted policy development that accounts for alternative farmer goals. However, similarities were also found between the profiles, suggesting that farmer behaviour would be better interpreted as a dynamic set of identities, rather than as static profiles.
In this paper we present an uncertainty analysis of a cross-sectoral, regional-scale, Integrated Assessment Platform (IAP) for the assessment of climate change impacts, vulnerability and adaptation. ...The IAP couples simplified meta-models for a number of sectors (agriculture, forestry, urban development, biodiversity, flood and water resources management) within a user-friendly interface. Cross-sectoral interactions and feedbacks can be evaluated for a range of future scenarios with the aim of supporting a stakeholder dialogue and mutual learning. We present a method to address uncertainty in: i) future climate and socio-economic scenarios and ii) the interlinked network of meta-models that make up the IAP. A mixed-method approach is taken: formal numerical approaches, modeller interviews and network analysis are combined to provide a holistic uncertainty assessment that considers both quantifiable and un-quantifiable uncertainty. Results demonstrate that the combined quantitative-qualitative approach provides considerable advantages over traditional, validation-based uncertainty assessments. Combined fuzzy-set methods and network analysis methods allow maps of modeller certainty to be explored. The results indicate that validation statistics are not the only factors driving modeller certainty; a large range of other factors including the quality and availability of validation data, the meta-modelling process, inter-modeller trust, derivation methods, and pragmatic factors such as time, resources, skills and experience influence modeller certainty. We conclude that by identifying, classifying and exploring uncertainty in conjunction with the model developers, we can ensure not only that the modelling system itself improves, but that the decisions based on it can draw on the best available information: the projection itself, and a holistic understanding of the uncertainty associated with it.
Soil erosion negatively affects crop yields and may have contributed to the collapse of ancient civilizations. Whether erosion may have such an impact on modern societies as well, is subject to ...debate. In this paper we quantify the relationship between crop yields and soil water available to plants, the most important yield-determining factor affected by erosion, at the European scale. Using information on the spatial distribution of erosion rates we calculate the potential threat of erosion-induced productivity losses. We show that future reductions in productivity in Europe as a whole are relatively small and do not pose a substantial threat to crop production within the coming century. However, within Europe there is considerable variability, and although productivity in northern Europe is not likely to be significantly reduced by soil erosion, for the southern countries the threat of erosion-induced productivity declines is stronger.
Policy makers and stakeholders are increasingly demanding impact assessments which produce policy-relevant guidance on the local impacts of global climate change. The Regional Climate Change Impact ...and Response Studies in East Anglia and North West England (RegIS) study developed a methodology for stakeholder-led, regional climate change impact assessment that explicitly evaluated local and regional (sub-national) scale impacts and adaptation options, and cross-sectoral interactions between four major sectors driving landscape change (agriculture, biodiversity, coasts and floodplains and water resources). The Drivers-Pressure-State-Impact-Response (DPSIR) approach provided a structure for linking the modelling and scenario techniques. A 5 x 5 km grid was chosen for numerical modelling input (climate and socio-economic scenarios) and output, as a compromise between the climate scenario resolution (10 x 10 km) and the detailed spatial resolution output desired by stakeholders. Fundamental methodological issues have been raised by RegIS which reflect the difficulty of multi-sectoral modelling studies at local scales. In particular, the role of scenarios, error propagation in linked models, model validity, transparency and transportability as well as the use of integrated assessment to evaluate adaptation options to climate change are examined. Integrated assessments will provide new insights which will compliment those derived by more detailed sectoral assessments.PUBLICATION ABSTRACT
This paper reviews the relationships between land use and climate change. It explores how land use decisions will be affected by future changes in the climate, but also the feedbacks from land use ...change to the global climate system through greenhouse gas (GHG) fluxes. Past changes in land use were characterised by decreasing areas of agricultural use and increasing areas of forested and urbanised land. This has led to UK land use being a net sink for GHGs, mostly due to forestation. However, existing forests have on average passed their age for maximum net removals of carbon from the atmosphere. In the next decade at least, net removals from UK forests are likely to decrease significantly.
Longer term scenarios of future land use change are consistent in their expectation of further declines in the agricultural area used for food production – offset to some extent by increased bioenergy cropping – along with increases in forested and urban areas. These trends are broadly consistent with the observed past land use change, but are calculated from various assumptions about future changes in drivers rather than by extrapolation from the past. Socio-economic and technological changes are likely to be the most important drivers for land use, with climate change having a smaller influence. The land use changes represented in these scenarios would likely reduce GHG emissions and enhance carbon sinks. These trends would be reinforced by small future changes in the climate, but large climatic changes are likely to cause net GHG fluxes to switch from being a sink to a source. Land use change will also be moderated by potential policy goals that seek to reduce GHG emissions from land and/or increase the size of land-based sinks. This includes strategies to reduce carbon and nitrogen emissions through increased efficiency, afforestation and biofuel production.
This paper provides an overview of the development of the 'Regional Impact Simulator' - a user friendly software tool designed to allow stakeholders to perform integrated assessments of the effects ...of climate and/or socio-economic change on the important sectors and resources of two contrasting UK regions. This includes the assessment of agriculture, water resources, biodiversity and coastal and river flooding. The tool arose from the need to further develop the methods applied in the earlier RegIS project, which was the first local to regional integrated assessment in the UK. The limitations of RegIS included very long run times, a limited number of simulations, incomplete linkages between models and no allowance for scenario uncertainty. Based upon the stakeholder needs identified within RegIS, a series of guiding principles were developed with Steering Committee stakeholders, which informed the concept of the 'Regional Impact Simulator' including functionality, appearance and complexity. An Integrated Assessment Methodology based upon the Drivers-Pressure-State-Impact-Response (DPSIR) framework facilitated the integration of multiple models, scenarios and datasets within the software interface. The development of the 'Regional Impact Simulator' provides a test-bed for further studies of stakeholder-led, regional, integrated assessment, and provides an opportunity to learn the many lessons in undertaking such studies.
Agri-environment is one of the most widely supported rural development policy measures in Scotland in terms of number of participants and expenditure. It comprises 69 management options and ...sub-options that are delivered primarily through the competitive ‘Rural Priorities scheme’. Understanding the spatial determinants of uptake and expenditure would assist policy-makers in guiding future policy targeting efforts for the rural environment. This study is unique in examining the spatial dependency and determinants of Scotland's agri-environmental measures and categorised options uptake and payments at the parish level. Spatial econometrics is applied to test the influence of 40 explanatory variables on farming characteristics, land capability, designated sites, accessibility and population. Results identified spatial dependency for each of the dependent variables, which supported the use of spatially-explicit models. The goodness of fit of the spatial models was better than for the aspatial regression models. There was also notable improvement in the models for participation compared with the models for expenditure. Furthermore a range of expected explanatory variables were found to be significant and varied according to the dependent variable used. The majority of models for both payment and uptake showed a significant positive relationship with SSSI (Sites of Special Scientific Interest), which are designated sites prioritised in Scottish policy. These results indicate that environmental targeting efforts by the government for AEP uptake in designated sites can be effective. However habitats outside of SSSI, termed here the ‘wider countryside’ may not be sufficiently competitive to receive funding in the current policy system.
•Scotland's agri-environmental measure was examined using spatial econometrics.•A range of expected explanatory variables were found to be significant.•Spatial models had an improved output compared to aspatial.•Results indicate the effectiveness of policy targeting in designated areas.
A primary goal of Earth system modelling is to improve understanding of the interactions and feedbacks between human decision making and biophysical processes. The nexus of land use and land cover ...change (LULCC) and the climate system is an important example. LULCC contributes to global and regional climate change, while climate affects the functioning of terrestrial ecosystems and LULCC. However, at present, LULCC is poorly represented in global circulation models (GCMs). LULCC models that are explicit about human behaviour and decision-making processes have been developed at local to regional scales, but the principles of these approaches have not yet been applied to the global scale level in ways that deal adequately with both direct and indirect feedbacks from the climate system. In this article, we explore current knowledge about LULCC modelling and the interactions between LULCC, GCMs and dynamic global vegetation models (DGVMs). In doing so, we propose new ways forward for improving LULCC representations in Earth system models. We conclude that LULCC models need to better conceptualise the alternatives for upscaling from the local to global scale. This involves better representation of human agency, including processes such as learning, adaptation and agent evolution, formalising the role and emergence of governance structures, institutional arrangements and policy as endogenous processes and better theorising about the role of teleconnections and connectivity across global networks. Our analysis underlines the importance of observational data in global-scale assessments and the need for coordination in synthesising and assimilating available data.
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