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📈 Lesson 1 - essential variables matter! Agreeing on what should be measured and reported accomplishes two important goals at once: it helps standardize the work of data collection, and it provides a common language around which we can build a science/policy interface. (2/)

📂 Lesson 2 - data clearinghouse are key to capacity building Initiatives like @gbif.org do FAR more than storing and distributing data; they help establish best practices for curation, analysis, and citation. But they also encourage the use of data standards. (3/)

🌏 Lesson 3 - global actions don't mean ignoring local specificities Global efforts are easier to establish when they work by federating local initiatives. The idea of biodiversity observation networks is a powerful one, that is partially replicated by One Health networks. (4/)