The potential of models and modeling for social-ecological systems research: the reference frame ModSES

Abstract

Dynamic models have long been a common tool to support management of ecological and economic systems and played a prominent role in the early days of resilience research. Model applications have largely focused on policy assessment, the development of optimal management strategies, or analysis of system stability. However, modeling can serve many other purposes such as understanding system responses that emerge from complex interactions of system components, supporting participatory processes, and analyzing consequences of human behavioral complexity. The diversity of purposes, types, and applications of models offers great potential for social-ecological systems (SESs) research, but has created much confusion because modeling approaches originate from different disciplines, are based on different assumptions, focus on different levels of analysis, and use different analytical methods. This diversity makes it difficult to identify which approach is most suitable for addressing a specific question. Here, our aims are: (1) to introduce the most common types of dynamic models used in SESs research and related fields, and (2) to align these models with SESs research aims to support the selection and communication of the most suitable approach for a given study. To this end, we organize modeling approaches into a reference scheme called "modelling for social-ecological systems research" (ModSES) along two dimensions: the degree of realism and the degree of knowledge integration. These two dimensions capture key challenges of SESs research related to the need to account for context dependence and the intertwined nature of SESs as systems of humans embedded in nature across multiple scales, as well as to acknowledge different problem framings, understandings, interests, and values. We highlight the need to be aware of the potentials, limitations, and conceptual backgrounds underlying the different approaches. Critical engagement with modeling for different aims of SESs research can contribute to developing integrative understanding and action toward enhanced resilience and sustainability.

Advancing landscape sustainability science: theoretical foundation and synergies with innovations in methodology, design, and application

“…ABMs, including cellular automata-based models, provide a disaggregated view, as they aim to incorporate the effect of human decision-making (along with its drivers) on the environment in a mechanistic and spatially explicit way, while considering social interaction and adaptation (Schlüter et al 2019). ABMs are capable of modeling individual entities and their interactions, incorporating overarching influences on decision-making, and dynamically integrating social and environmental processes (Brown et al 2005).…”

Resilience trinity: safeguarding ecosystem functioning and services across three different time horizons and decision contexts

“…This may, however, be at odds with various other goals such as biodiversity conservation, maintaining existing ecosystem functions, functionality of human infrastructures or human recreation (Minchin et al 2002). Policy makers and decision makers must explicitly recognize the tradeoffs in this situation and recognize that ecosystems are multi-scaled and nonlinear with inherent uncertainty and managing for one spatial or temporal context ignores reality and tends to reduce resilience at other spatial and temporal scales (see also Schlüter et al 2019). Table 1 and 2 can be used as a tool in this context: which resilience mechanisms are employed by the potential actions for increasing reactive, adjustive or provident resilience, that were discussed so far for this example?…”

How can social–ecological system models simulate the emergence of social–ecological crises?

“…Network modelling has recently been used to explore the ways in which individual and social characteristics affect responses to climate change (Barnes et al, 2020). A structured typology of social-ecological model types and the roles they can play in exploring system dynamics is provided by Schlüter, Müller, et al (2019), and can be related to more general existing frameworks for social-ecological systems modelling (Robinson et al, 2018) and analysis (e.g. Binder & Hinkel, 2013).…”