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There are many sources of uncertainty in scenarios and models of socio-ecological systems, and understanding these uncertainties is critical in supporting informed decision-making about the management of natural resources. Here, we review uncertainty across the steps needed to create socio-ecological scenarios, from narrative storylines to the representation of human and biological processes in models and the estimation of scenario and model parameters. We find that socio-ecological scenarios and models would benefit from moving away from “stylized” approaches that do not consider a wide range of direct drivers and their dependency on indirect drivers. Indeed, a greater focus on the social phenomena is fundamental in understanding the functioning of nature on a human-dominated planet. There is no panacea for dealing with uncertainty, but several approaches to evaluating uncertainty are still not routinely applied in scenario modeling, and this is becoming increasingly unacceptable. However, it is important to avoid uncertainties becoming an excuse for inaction in decision-making when facing environmental challenges.

Controlling tick bites on farmers is important to the management of tick-borne diseases and occupational health risks in agriculture. Based on an extensive household survey conducted between June and August 2015 with 219 farmers from western Hungary where tick-borne diseases are endemic, we analysed the pattern of farmers' self-reported contacts with ticks and investigated the potential interactions between farmers, landscape and the risk of exposure to tick bites. We developed a lifestyle typology based on farmers' socioeconomic profiles, farming objectives and time use patterns, and a habitat typology describing different configurations of tick habitats and agricultural areas in place of farming. We found no relationship between tick exposure risk and self-prevention. The lifestyle typology could be used to classify the risk of tick bites and the adoption of prevention measures into different levels, the difference between which could further be modified by the habitat typology. Our results suggest that (i) farmers who are frequently engaged in outdoor recreations and (ii) part-time and inexperienced farmers who have lower rate of preventive actions are likely to experience greater exposure to tick bites either in less cultivated, semi-natural habitats or in agricultural landscape with highly diverse land uses. Future disease prevention practices should take into consideration the interaction of lifestyle and habitat and the need to associate different farmer groups with different landscape configurations.

Understanding uncertainties in land cover projections is critical to investigating land-based climate mitigation policies, assessing the potential of climate adaptation strategies and quantifying the impacts of land cover change on the climate system. Here, we identify and quantify uncertainties in global and European land cover projections over a diverse range of model types and scenarios, extending the analysis beyond the agro-economic models included in previous comparisons. The results from 75 simulations over 18 models are analysed and show a large range in land cover area projections, with the highest variability occurring in future cropland areas. We demonstrate systematic differences in land cover areas associated with the characteristics of the modelling approach, which is at least as great as the differences attributed to the scenario variations. The results lead us to conclude that a higher degree of uncertainty exists in land use projections than currently included in climate or earth system projections. To account for land use uncertainty, it is recommended to use a diverse set of models and approaches when assessing the potential impacts of land cover change on future climate. Additionally, further work is needed to better understand the assumptions driving land use model results and reveal the causes of uncertainty in more depth, to help reduce model uncertainty and improve the projections of land cover.

The nexus of population growth and changing diets has increased the demands placed on agriculture to supply food for human consumption, animal feed and fuel. Rising incomes lead to dietary changes, from staple crops, towards commodities with greater land requirements, e.g. meat and dairy products. Despite yield improvements partially offsetting increases in demand, agricultural land has still been expanding, causing potential harm to ecosystems, e.g. through deforestation. We use country-level panel data (1961–2011) to allocate the land areas used to produce food for human consumption, waste and biofuels, and to attribute the food production area changes to diet, population and yields drivers. The results show that the production of animal products dominates agricultural land use and land use change over the 50-year period, accounting for 65% of land use change. The rate of extensification of animal production was found to have reduced more recently, principally due to the smaller effect of population growth. The area used for bioenergy was shown to be relatively small, but formed a substantial contribution (36%) to net agricultural expansion in the most recent period. Nevertheless, in comparison to dietary shifts in animal products, bioenergy accounted for less than a tenth of the increase in demand for agricultural land. Population expansion has been the largest driver for agricultural land use change, but dietary changes are a significant and growing driver. China was a notable exception, where dietary transitions dominate food consumption changes, due to rapidly rising incomes. This suggests that future dietary changes will become the principal driver for land use change, pointing to the potential need for demand-side measures to regulate agricultural expansion.

Land exchange can be a major factor driving land-use change in regions with high pressure on land, but is generally not incorporated in land-use change models. Here we present an agent-based model to simulate land-use change arising from land exchange between multiple agent types representing farmers, nature organizations, and estate owners.

The globalisation of trade affects land use, food production and environments around the world. In principle, globalisation can maximise productivity and efficiency if competition prompts specialisation on the basis of productive capacity. In reality, however, such specialisation is often constrained by practical or political barriers, including those intended to ensure national or regional food security. These are likely to produce globally sub-optimal distributions of land uses. Both outcomes are subject to the responses of individual land managers to economic and environmental stimuli, and these responses are known to be variable and often (economically) irrational. We investigate the consequences of stylised food security policies and globalisation of agricultural markets on land use patterns under a variety of modelled forms of land manager behaviour, including variation in production levels, tenacity, land use intensity and multi-functionality. We find that a system entirely dedicated to regional food security is inferior to an entirely globalised system in terms of overall production levels, but that several forms of behaviour limit the difference between the two, and that variations in land use intensity and functionality can substantially increase the provision of food and other ecosystem services in both cases. We also find emergent behaviour that results in the abandonment of productive land, the slowing of rates of land use change and the fragmentation or, conversely, concentration of land uses following changes in demand levels.

This paper presents an assessment of land use changes and their impacts on the ecosystem in the Montado, a traditional agricultural landscape of Portugal in response to global environmental change. The assessment uses an agent- based model (ABM) of the adaptive decisions of farmers to simulate the influence on future land use patterns of socio-economic attributes such as social relationships and farmer reliance on subsidies and biophysical constraints. The application and development of the ABM are supported empirically using three categories of input data: 1) farmer types based on a cluster analysis of socio-economic attributes; 2) agricultural suitability based on regression analysis of historical land use maps and biophysical attributes; and 3) future trends in the economic and climatic environments based on the A1fi scenario of the Intergovernmental Panel on Climate Change. Model sensitivity and uncertainty analyses are carried out prior to the scenario analysis in order to verify the absence of systematic errors in the model structure. The results of the scenario analysis show that the area of Montado declines significantly by 2050, but it remains the dominant land use in the case study area, indicating some resilience to change. An important policy challenge arising from this assessment is how to encourage next generation of innovative farmers to conserve this traditional landscape for social and ecological values.

Traditional impact models combine exposure in the form of scenarios and sensitivity in the form of parameters, providing potential impacts of global change as model outputs. However, adaptive capacity is rarely addressed in these models. This paper presents the first spatially explicit scenario-driven model of adaptive capacity, which can be combined with impact models to support quantitative vulnerability assessment. The adaptive capacity model is based on twelve socio-economic indicators, each of which is projected into the future using four global environmental change scenarios, and then aggregated into an adaptive capacity index in a stepwise approach using fuzzy set theory. The adaptive capacity model provides insight into broad patterns of adaptive capacity across Europe, the relative importance of the various determinants of adaptive capacity, and how adaptive capacity changes over time under different social and economic assumptions. As such it provides a context for the implementation of specific adaptation measures. This could improve integrated assessment models and could be extended to other regions. However, there is a clear need for a better theoretical understanding of the adaptive capacity concept, and its relationship to the actual implementation of adaptation measures. This requires more empirical research and coordinated meta-analyses across regions and economic sectors, and the development of bottom-up modelling techniques that can incorporate human decision making.

Using a range of different methods including extensive reviews, workshops and an electronic conference, 70 key research recommendations and 12 priority research needs to integrate the ecosystem services approach into biodiversity conservation policy and funding were identified by a cross-disciplinary group of over 100 scientists and 50 stakeholders, including research funders and policy-makers. These recommendations focus on the ecological underpinning of ecosystem services, drivers that affect ecosystems and their services, biological traits and ecosystem services, the valuation of ecosystem services, spatial and temporal scales in ecosystem service assessment, indicators of ecosystem services, and habitat management, conservation policy and ecosystem services. The recommendations in this paper help steer the research agenda on ecosystem services into policy-relevant areas, agreed upon by funders, researchers and policy-makers. This research agenda will only succeed with increased collaboration between researchers across disciplines, thereby providing a challenge to the research community and research funders to work in new, interdisciplinary ways.

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 alternative plausible futures have been used extensively to explore the potential effects of socioeconomic and environmental change. The ultimate objective of any explorative scenario exercise is to assess the variation in possible futures to provide insights into the range of potential outcomes. These results provide stakeholders with guidance for policy development, planning, and management. We explore how personal judgment can influence scenario development. Scenarios for the future of European rural regions are used to explore alternative outcomes under a public interventionist future and a market liberalization oriented future. A transparent qualitative framework is used to identify differences in outcomes based on personal judgment. Results show that, for both scenarios, there are plausible mechanisms that can lead to similar positive or negative outcomes. Choosing a single process per scenario, based on personal judgment and interpretation, can therefore greatly influence scenario outcomes and limit the range of uncertainty that is covered by the scenarios. The exercise shows the importance of making these judgments explicit in scenario development, especially when exploring broad consequences of alternative policy directions that may be based in political worldviews.