Equity and modeling in sustainability science: Examples and opportunities throughout the process

Equity is core to sustainability, but current interventions to enhance sustainability often fall short in adequately addressing this linkage. Models are important tools for informing action, and their development and use present opportunities to center equity in process and outcomes. This Perspective highlights progress in integrating equity into systems modeling in sustainability science, as well as key challenges, tensions, and future directions. We present a conceptual framework for equity in systems modeling, focused on its distributional, procedural, and recognitional dimensions. We discuss examples of how modelers engage with these different dimensions throughout the modeling process and from across a range of modeling approaches and topics, including water resources, energy systems, air quality, and conservation. Synthesizing across these examples, we identify significant advances in enhancing procedural and recognitional equity by reframing models as tools to explore pluralism in worldviews and knowledge systems; enabling models to better represent distributional inequity through new computational techniques and data sources; investigating the dynamics that can drive inequities by linking different modeling approaches; and developing more nuanced metrics for assessing equity outcomes. We also identify important future directions, such as an increased focus on using models to identify pathways to transform underlying conditions that lead to inequities and move toward desired futures. By looking science, we argue that there are valuable opportunities for tools to support sustainable and equitable futures.urn:si:payload:6429386 multiple and intersecting dimensions of social stratification (4), as well as relationality between humans and nature (5), across multiple sites and scales (6). In short, sustainable development aspires to "leave no one behind" (7). To what extent have models of nature- society systems used to inform sustainable development supported the aim of equity, and what opportunities exist for improvement? Computational models are a core tool for exploring collective understanding of, and assessing interventions for, complex nature-society systems (8, 9). Models of these dynamic sys- tems-often, though not exclusively, mechanistic models-are frequently used to consolidate knowledge about a system into a single representation which is then used to predict system