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Indigenous Peoples across the Arctic have adapted to environmental change since time immemorial, yet recent climate change has imposed unprecedented and abrupt changes that affect the land and sea upon which communities rely. Co-created community-based observing programs offer an opportunity to harness the holistic breadth of knowledge in communities with the goal of tracking Arctic change while simultaneously supporting community priorities and local-scale needs. The Alaska Arctic Observatory and Knowledge Hub (AAOKH) is a network of Iñupiaq observers from northern Alaska coastal communities working in partnership with academic researchers. Here, we describe five core functions that have emerged through AAOKH, which include tracking long-term environmental changes; communicating Indigenous-led observations of the environment and their meaning; place-based and culturally relevant education; enabling scientific and Indigenous Knowledge exchange; and supporting community-led responses to environmental change. We outline and discuss specific actions and opportunities that have been used to increase knowledge exchange of AAOKH observations, make space for the next generation of Indigenous scholars, and create locally relevant data products and syntheses that can inform resource management and community planning. We also discuss our ongoing efforts to increasingly shift toward a knowledge coproduction framework as we plan to sustain AAOKH into the future. 

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 at examples across the diverse fields within sustainability science, we argue that there are valuable opportunities for mutual learning on how to use models more effectively as tools to support sustainable and equitable futures.