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Environmental scientists, land managers, and policy actors are increasingly presented with high-stakes high-uncertainty problems stemming from human-ecosystem interactions. These interactions exacerbate already challenging issues associated with environmental policy and natural resource management. To address these problems, scientists and managers frequently use models that produce enormous geospatial and temporal datasets that are constantly modified. To help make sense of this complex and changing data, we are immersed in a co-production effort where software engineers and environmental scientists collaborate on the development of visualization software. We report on this on-going research, and find that visualization is critical not only for communicating science, but integral to many aspects of the science production pipeline and evolving data science field. We also find evidence among our collaborators that this software co-production process helps build legitimacy for the information it produces, with potential implications for generating actionable science for policy and governance.