Mark Rounsevell

Ecosystem service supply and vulnerability to global change in Europe

Global change will alter the supply of ecosystem services that are vital for human well-being. To investigate ecosystem service supply during the 21st century, we used a range of ecosystem models and scenarios of climate and land-use change to conduct a Europe-wide assessment. Large changes in climate and land use typically resulted in large changes in ecosystem service supply. Some of these trends may be positive (for example, increases in forest area and productivity) or offer opportunities (for example, “surplus land” for agricultural extensification and bioenergy production). However, many changes increase vulnerability as a result of a decreasing supply of ecosystem services (for example, declining soil fertility, declining water availability, increasing risk of forest fires), especially in the Mediterranean and mountain regions.

Are agricultural land-use models able to predict changes in land-use intensity?

Land-use and land-cover change research needs to pay more attention to processes of land-cover modification, and especially to agricultural land intensification. The objective of this paper is to review the different modelling approaches that have been used in land-use/land-cover change research from the perspective of their utility for the study and prediction of changes in land-use intensification. After clarifying the main concepts used, the different modelling approaches that have been used to study land-use change are examined, case study evidence on processes and drivers of land-use intensification are discussed, and a conclusion is provided on the present ability to predict changes in land-use intensity. The analysis suggests there are differences in the capability of different modelling approaches to assess changing levels of intensification: dynamic, process-based simulation models appear to be better suited to predict changes in land-use intensity than empirical, stochastic or static optimisation models. However, some stochastic and optimisation methods may be useful in describing the decision-making processes that drive land management. Case study evidence highlight the uncertainties and surprises inherent in the processes of land-use intensification. This can both inform model development and reveal a wider range of possible futures than is evident from modelling alone. Case studies also highlight the importance of decision-making by land managers when facing a range of response options. Thus, the ability to model decision-making processes is probably more important in land-use intensification studies then the broad category of model used. For this reason, landscape change models operating at an aggregated level have not been used to predict intensification. In the future, an integrated approach to modelling - that is multidisciplinary and cross-sectoral combining elements of different modelling techniques - will probably best serve the objective of improving understanding of land-use change processes including intensification. This is because intensification is a function of the management of physical resources, within the context of the prevailing social and economic drivers. Some of the factors that should be considered when developing future land-use change models are: the geographic and socio-economic context of a particular study, the spatial scale and its influence on the modelling approach, temporal issues such as dynamic versus equilibrium models, thresholds and surprises associated with rapid changes, and system feedbacks. In industrialised regions, predicting land-use intensification requires a better handling of the links between the agriculture and forestry sectors to the energy sector, of technological innovation, and of the impact of agri-environment policies. For developing countries, better representation of urbanisation and its various impacts on land-use changes at rural-urban interfaces, of transport infrastructure and market change will be required. Given the impossibility of specific predictions of these driving forces, most of the modelling work will be aimed at scenario analysis

Competition for land.

A key challenge for humanity is how a future global population of 9 billion can all be fed healthily and sustainably. Here, we review how competition for land is influenced by other drivers and pressures, examine land-use change over the past 20 years and consider future changes over the next 40 years. Competition for land, in itself, is not a driver affecting food and farming in the future, but is an emergent property of other drivers and pressures. Modelling studies suggest that future policy decisions in the agriculture, forestry, energy and conservation sectors could have profound effects, with different demands for land to supply multiple ecosystem services usually intensifying competition for land in the future. In addition to policies addressing agriculture and food production, further policies addressing the primary drivers of competition for land (population growth, dietary preference, protected areas, forest policy) could have significant impacts in reducing competition for land. Technologies for increasing per-area productivity of agricultural land will also be necessary. Key uncertainties in our projections of competition for land in the future relate predominantly to uncertainties in the drivers and pressures within the scenarios, in the models and data used in the projections and in the policy interventions assumed to affect the drivers and pressures in the future.

Quantifying the Contribution of Organisms to the Provision of Ecosystem Services

Research on ecosystem services has grown rapidly over the last decade. Two conceptual frameworks have been published to guide ecological assessments of organisms that deliver services—the concepts of service-providing units (SPUs) and ecosystem service providers (ESPs). Here, we unite these frameworks and present an SPU-ESP continuum that offers a coherent conceptual approach for synthesizing the latest developments in ecosystem service research, and can direct future studies at all levels of organization. In particular, we show how the service-provider concept can be applied at the population, functional group, and community levels. We strongly emphasize the need to identify and quantify the organisms and their characteristics (e.g., functional traits) that provide services, and to assess service provision relative to the demands of human beneficiaries. We use key examples from the literature to illustrate the new approach and to highlight gaps in knowledge, particularly in relation to the impact of species interactions and ecosystem dynamics on service provision.

Modelling the spatial distribution of agricultural land use at the regional scale

Agriculture is the most important land use in Europe in geographic terms and because of this it plays a central role in the quality of the wider environment. Whilst the spatial patterns of agricultural land use have changed considerably in recent times, further changes are likely as a result of the influences of policy reform, socio-economics and climate change. Understanding, therefore, how agricultural land use might respond to global environmental change drivers is a research question of considerable importance. The first step, however, in projecting potential future changes in agricultural land use is to be able to understand and represent in models both the socio-economic and physical processes that control current land use distributions. Thus, this paper presents an approach to modelling the spatial distribution of agricultural land use at the regional scale. The approach is based on the simulation of farm-scale decision making processes (based on optimisation) and the response of crops to their physical environment. Regional scale applications of the model are undertaken through the use of spatially-variable, geographic data sets (soils, climate and topography) combined with economic data. Examples of the application of the model are given for two regions of England: the north-west and east Anglia. These regions were selected to give examples of contrasting land use systems within the context of northern European agriculture. The model results are compared statistically with observed distributions of agricultural land use for the same regions in a quasi-validation exercise. The comparison suggests that the model is very good at representing land use that is aggregated at the regional level, and at representing general spatial trends in land use patterns. Some differences were observed, however, in land use densities between the modelled and observed data. The results suggest that the basic hypothesis of the model: that farmers are risk averse, profit maximisers, is a reasonable assumption for the regions studied. However, further study of decision making processes would be likely to improve our ability to model agricultural land use distributions. This includes, for example, the role of farmer attitudes to risk, differing views on future prices and profitability, and the effect of time lags in the decision process.

A conceptual framework to assess the effects of environmental change on ecosystem services

A new conceptual framework is presented for the assessment of the impacts of environmental change drivers on ecosystem service provision and the policy and management responses that would derive from the valuation of these impacts. The Framework for Ecosystem Service Provision (FESP), is based on an interpretation of the widely-used Drivers-Pressures-State-Impact-Response (DPSIR) framework. FESP differs from the DPSIR by offering clarity in the definitions of the various DPSIR components as well as introducing novel elements of relevance to the ecosystem service approach. The value of a common framework lies in making the comparison across competing services accessible and clear as well as highlighting the conflicts and trade-offs between not only multiple ecosystem services, but also multiple service beneficiaries. The framework is explicit, for example, in recognising as state variables not only the attributes of the Ecosystem Service Providers (ESPs), but also the attributes of the Ecosystem Service Beneficiaries (ESBs). That a service depends as much on the attributes of the people whose well-being benefits from the service as on the attributes of the biology providing the service is an important step in integrated social-ecological thinking. FESP also identifies the mechanisms of either mitigation or adaptation to the environmental change problem through the effect of these response strategies on specific pressure or state variables. In this way, FESP can contribute to the policies and strategies that are used to support conservation management. This paper describes the principles of FESP and presents some indicative examples of its practical implementation.

Projected changes in mineral soil carbon of European forests, 1990-2100

Forests are a major land use in Europe, and European forest soils contain about the same amount of carbon as is found in tree biomass. Changes in the size of the forest soil carbon pool could have significant impacts on the European carbon budget. We present the first assessment of future changes in European forest soil organic carbon (SOC) stocks using a dedicated process-based SOC model and state-of-the-art databases of driving variables. Soil carbon change was calculated for Europe using the Rothamsted Carbon model using climate data from four climate models, forced by four Intergovernmental Panel on Climate Change (IPCC) emissions scenarios (SRES). Changes in litter input to the soil due to forest management, projected changes in net primary production (NPP), forest age-class structure, and changes in forest area were taken into account. Results are presented for mineral soil only. Under some climate scenarios carbon in forest soils will increase slightly (0.1 to 4.6 Pg) in Europe over the 21st Century, whilst for one scenario, forest SOC stocks are predicted to decrease by 0.3 Pg. Different trends are seen in different regions. Climate change will tend to speed decomposition, whereas increases in litter input due to increasing NPP and changing age-class structure will slow the loss of SOC. Increases in forest area could further enhance the total soil carbon stock of European forests. Whilst climate change will be a key driver of change in forest soil carbon, changes in age-class structure and land-use change are estimated to have greater effects.

From actors to agents in socio-ecological systems models

The ecosystem service concept has emphasized the role of people within socio-ecological systems (SESs). In this paper, we review and discuss alternative ways of representing people, their behaviour and decision-making processes in SES models using an agent-based modelling (ABM) approach. We also explore how ABM can be empirically grounded using information from social survey. The capacity for ABM to be generalized beyond case studies represents a crucial next step in modelling SESs, although this comes with considerable intellectual challenges. We propose the notion of human functional types, as an analogy of plant functional types, to support the expansion (scaling) of ABM to larger areas. The expansion of scope also implies the need to represent institutional agents in SES models in order to account for alternative governance structures and policy feedbacks. Further development in the coupling of human-environment systems would contribute considerably to better application and use of the ecosystem service concept.

Ecosystem services and biodiversity conservation: concepts and a glossary.

The RUBICODE project draws on expertise from a range of disciplines to develop and integrate frameworks for assessing the impacts of environmental change on ecosystem service provision, and for rationalising biodiversity conservation in that light. With such diverse expertise and concepts involved, interested parties will not be familiar with all the key terminology. This paper defines the terms as used within the project and, where useful, discusses some reasoning behind the definitions. Terms are grouped by concept rather than being listed alphabetically.

Scenarios of future urban land use in Europe

The objective of this paper is to present the development of quantitative, spatially explicit, and alternative scenarios of future urban land use in Europe. The scenario-construction methodology is based on three steps: (1) an interpretation of four global-scale storylines describing in qualitative terms alternative urban-development pathways, (2) the development and application of a simple statistical model to estimate the future demand for urban land, and (3) the development of rules to allocate this urban demand geographically through the consideration of land-use planning goals. The qualitative part of the analysis is based on an interpretation of the four storylines of the Special Report on Emission Scenarios by the Intergovernmental Panel on Climate Change. This interpretation describes the principal driving forces that are specific to the European region and to the urban sector on the basis of the theoretical principles of urban economy. The urban-demand model includes two driving forces: (a) the population, representing demographic trends and the demand for housing; and (b) the gross domestic product, reflecting the economic level and dynamism. A further three variables are used as drivers of spatial patterns: (c) accessibility to the transport network; (d) the degree of restriction arising from land-use planning policy, and (e) the relative attractiveness (in terms of residential-location choice) of small, medium, and large cities. Thus, the urban-land-use change model is based on a multilevel analysis, which integrates theory and empirical evidence. The results are original urban-land-use maps of Europe for each of the four scenarios on the basis of a 10′ (latitude and longitude) geographic grid. The comparison of these alternative views of the future and the transparency of the development of these views provide a rich and consistent method for understanding the relationships between driving forces, their intensity, and their consequence for geographic space. Scenario analysis is a useful tool to test incentives, measures, or planning regulations according to different policy objectives.