 We're going to have a really quick report back session. I don't know if we have our reporter from session one. All right, Ted. So these are, we asked each session to come up with big ideas, three to five. Some have more, some may have less, but that's OK. We're reporting them out now. In about a week, you guys are going to get some materials that are sort of all the ideas that came out of the meeting with some requests for you to start prioritizing them. And so these are ideas that are going to go into that later on. OK, we had a lively discussion in the population genomics session, and we spent a lot of time talking about sample collection, sample archiving, and in standards across samples. Thinking about the ecological context and recording phenotypes associated with the samples that we are sequencing and archiving, and pointing out throughout the session that there's a lot of resources that already exist that we can leverage in the population genomics realm and for how it is that we're connecting the phenotypic data and the archived samples. We also talked a fair amount about in this sampling the international context of sampling, funding for this, the training and in leveraging local populations in terms of how it is that we use citizen science and citizen scientists and in aligning our interests with those of local populations. We also spent a good deal of time talking about prioritization of what gets sequenced and whether or not in the need for a good phylogenetic context and whether or not we need to do low-pass sequencing or high-pass sequencing initially to just connect the population genomics with the phylogenetic context. And the point was raised and agreed upon by many that one is not enough and that we need to think about how many is enough when we're thinking about population genomics. And then we also talked a fair amount about this idea of the extended specimen and that the importance of collecting phenotypic and ecological information on the samples that we use. And then as we were talking about these different data types with population genomics, there were a number of insightful comments from data scientists in the room that noted that we don't have to reinvent the wheel for a lot of these things in terms of how it is that we connect this data that this is being done through resources that already exist. So those were the things that sort of came out of the population genomics session.