Jule Schulze

Simple or complicated agent-based models? A complicated issue

Agent-based models (ABMs) are increasingly recognized as valuable tools in modelling human-environmental systems, but challenges and critics remain. One pressing challenge in the era of Big Data and given the flexibility of representation afforded by ABMs, is identifying the appropriate level of complicatedness in model structure for representing and investigating complex real-world systems. In this paper, we differentiate the concepts of complexity (model behaviour) and complicatedness (model structure), and illustrate the non-linear relationship between them. We then systematically evaluate the trade-offs between simple (often theoretical) models and complicated (often empirically-grounded) models. We propose using pattern-oriented modelling, stepwise approaches, and modular design to guide modellers in reaching an appropriate level of model complicatedness. While ABMs should be constructed as simple as possible but as complicated as necessary to address the predefined research questions, we also warn modellers of the pitfalls and risks of building mid-level models mixing stylized and empirical components. We clarify the terms complexity and complicated in the context of ABM.We comprehensively discuss pros and cons of simple and complicated ABMs.We identify challenges and pitfalls for simple and complicated ABMs.We provide recommendations and good practices for dealing with complicatedness.

Design, implementation and test of a serious online game for exploring complex relationships of sustainable land management and human well-being

Land is a limited resource providing various services. Decisions on land use shape the distribution of these life support functions and thus require understanding of complex feedbacks between decisions on land use and human resource appropriation. Due to multiple nonlinear feedbacks between management, productivity, environmental quality, and human well-being, complexity is an inherent property of land systems. We present an educational game, which aims at illustrating options of sustainable land management to the interested public, students and stakeholders. The game provides the opportunity to govern a country by exploring how contrasting dimensions of sustainability (economy, environment and social conditions), can be harmonized regionally, while continuously being threatened by global trade fluctuations. The game was tested by several groups of students from high schools and universities. The feedback shows that the game is a valuable tool in environmental education initiating learning the complexity of feedbacks in land use and resources appropriation. Display Omitted Land management requires understanding of nonlinear dynamic feedbacks in land systems.LandYOUs, a serious online game, explains various facets of sustainable land management.The player governs a country by means of land use, nature protection and education.The game was tested by several groups of students from high schools and universities.User feedback supports the potential for applications in environmental education.

Agent-Based Modelling of Social-Ecological Systems: Achievements, Challenges, and a Way Forward

Understanding social-ecological systems (SES) is crucial to supporting the sustainable management of resources. Agent-based modelling is a valuable tool to achieve this because it can represent the behaviour and interactions of organisms, human actors and institutions. Agent-based models (ABMs) have therefore already been widely used to study SES. However, ABMs of SES are by their very nature complex. They are therefore difficult to parameterize and analyse, which can limit their usefulness. It is time to critically reflect upon the current state-of-the-art to evaluate to what degree the potential of agent-based modelling for gaining general insights and supporting specific decision-making has already been utilized. We reviewed achievements and challenges by building upon developments in good modelling practice in the field of ecological modelling with its longer history. As a reference, we used the TRACE framework, which encompasses elements of model development, testing and analysis. We firstly reviewed achievements and challenges with regard to the elements of the TRACE framework addressed in reviews and method papers of social-ecological ABMs. Secondly, in a mini-review, we evaluated whether and to what degree the elements of the TRACE framework were addressed in publications on specific ABMs. We identified substantial gaps with regard to (1) communicating whether the models represented real systems well enough for their intended purpose and (2) analysing the models in a systematic and transparent way so that model output is not only observed but also understood. To fill these gaps, a joint effort of the modelling community is needed to foster the advancement and use of strategies such as participatory approaches, standard protocols for communication, sharing of source code, and tools and strategies for model design and analysis. Throughout our analyses, we provide specific recommendations and references for improving the state-of-the-art. We thereby hope to contribute to the establishment of a new advanced culture of agent-based modelling of SES that will allow us to better develop general theory and practical solutions.

Assessing Regional-Scale Impacts of Short Rotation Coppices on Ecosystem Services by Modeling Land-Use Decisions.

Meeting the world’s growing energy demand through bioenergy production involves extensive land-use change which could have severe environmental and social impacts. Second generation bioenergy feedstocks offer a possible solution to this problem. They have the potential to reduce land-use conflicts between food and bioenergy production as they can be grown on low quality land not suitable for food production. However, a comprehensive impact assessment that considers multiple ecosystem services (ESS) and biodiversity is needed to identify the environmentally best feedstock option, as trade-offs are inherent. In this study, we simulate the spatial distribution of short rotation coppices (SRCs) in the landscape of the Mulde watershed in Central Germany by modeling profit-maximizing farmers under different economic and policy-driven scenarios using a spatially explicit economic simulation model. This allows to derive general insights and a mechanistic understanding of regional-scale impacts on multiple ESS in the absence of large-scale implementation. The modeled distribution of SRCs, required to meet the regional demand of combined heat and power (CHP) plants for solid biomass, had little or no effect on the provided ESS. In the policy-driven scenario, placing SRCs on low or high quality soils to provide ecological focus areas, as required within the Common Agricultural Policy in the EU, had little effect on ESS. Only a substantial increase in the SRC production area, beyond the regional demand of CHP plants, had a relevant effect, namely a negative impact on food production as well as a positive impact on biodiversity and regulating ESS. Beneficial impacts occurred for single ESS. However, the number of sites with balanced ESS supply hardly increased due to larger shares of SRCs in the landscape. Regression analyses showed that the occurrence of sites with balanced ESS supply was more strongly driven by biophysical factors than by the SRC share in the landscape. This indicates that SRCs negligibly affect trade-offs between individual ESS. Coupling spatially explicit economic simulation models with environmental and ESS assessment models can contribute to a comprehensive impact assessment of bioenergy feedstocks that have not yet been planted.

Describing Human Decisions in Agent-Based Social-Ecological Models - ODD+D an Extension of the ODD Protocol

Multiple agent-based models (ABM) on social-ecological systems exist in parallel investigating similar research questions. However, the choice of a particular human decision model is often not sufficiently empirically or theoretically substantiated in the model documentation. Furthermore, model comparison is difficult because model descriptions are often incomplete, intransparent and difficult to understand. Therefore we expand and refine the ‘ODD’ (Overview, Design Concepts, and Details) protocol to establish a standard to describe ABMs which includes human decision making (ODD+D). Since the original ODD is mainly from an ecological perspective, some adaptations are necessary for the social-ecological context. We extended and rearranged the design concepts and related guiding questions to differentiate and describe decision making, adaptation and learning of the agents in a comprehensive and clearly structured way. Furthermore, ODD+D encompasses a section on ‘Theoretical and empirical background’ to encourage that model design and model assumptions are related more closely to theory. The application of ODD+D is illustrated with a description of a social-ecological ABM on water use. We believe that our expansions help to make the ODD protocol a most suitable protocol to describe social-ecological ABMs and may support the review process of related manuscripts. The ODD+D protocol does not only improve the quality of model descriptions but also improves our understanding of models and is an important necessary step forward developing theory respectively frameworks for social-ecological ABMs.