 Well, thank you all for attending this science seminar. These seminars are presented by the National Science Foundation's National Ecological Observatory Network, operated by Patel. Our goal with this monthly series of talks is to build community among researchers at the intersection of ecology, environmental science, and neon. Today, we're very excited to have Teresa Cremins and Alyssa Rose-Martin from the University of Arizona to present on the USA National Phenology Network. But before we turn it over to the speakers, a few logistics. We have enabled optional closed captioning for today's talk. And if you'd like to use this closed captioning option, please find the closed captioning button in your menu bar. The webinar will consist of a presentation followed by a question and answer period. As you think of questions, please add them to the Q&A box. Moderators will facilitate the discussion at the end. I'm one of the moderators. During this time, there should be an opportunity to ask questions over audio. Neon welcomes contributions from everyone who shares our values of unity, creativity, collaboration, excellence, and appreciation. This is outlined in our Code of Conduct. These guidelines apply to neon staff as well as participants external to the neon program. Please review our Code of Conduct, which can be found on the DEI page of the neon website. This talk will be recorded and made available for later viewing on the Neon Science Seminar webpage. And finally, to compliment these monthly seminar series, we're hosting related data skills webinars where you can learn more about how to access and use neon data. These monthly science seminars are held kind of in every two weeks alternating with the data science seminars. So the next data skills seminar will be on November 29th and will focus on working with neon plant phenology data. And so for those who'd like to register for the data skills webinars, you can do it on the same page as the science seminars. So now it's my pleasure to introduce today's speakers, Dr. Teresa Crimmins and Alyssa Rosemarten. Teresa is a faculty member in the Integrated Climate Research Ecosystems, Water, and Weather Vertically Integrated Project at the University of Arizona. Teresa's research addresses patterns of drivers and drivers of phenology as well as facets of citizen science and engaging non-scientists documenting the plant animal life around us. Teresa is also the director of the USA National Phenology Network, which we're gonna hear about much more about during this today's talk. I'd also like to introduce Alyssa Rosemarten. Alyssa is an application specialist with the USA National Phenology Network and coordinator of research collaborations at the University of Arizona. So thank you, Teresa and Alyssa. We'll pass it on to you now. Super, thank you so much. Let me just, of course. Does the slides look good? Look great. Okay, super. So yes, Teresa and I are very excited to be here today. It gave us this, preparing for this presentation gave us a great opportunity to reflect back on, you know, 15 years of collaborations between the USA National Phenology Network and NEON and we've really just worked together in so many cool ways. And so it's exciting to get to share this with you and have a conversation about it as well. So in case you're not already sold that phenology is the coolest thing since sliced bread, we are into it because it is a great way to understand climate impacts. It offers feedbacks to climate connections to hydrologic cycles, carbon cycling, ecosystems and many aspects of global change. And we're also perhaps more in the last five or six years really focused on the use of phenology in decision support like invasive species control, agricultural applications, human health like pollen and allergies and then cultural events like flowering festivals. I mean, how those are changing with changing seasonal temperatures and preset patterns. So our organization, the USA National Phenology Network exists to collect, store and share phenology data and information with an overall purpose of advancing the science of phenology, supporting decision-making, communicating and connecting, bringing new audiences to observe and connect to and understand patterns in the seasons as they're changing around us. And then we're also focused on growing an equitable and inclusive network and ensuring that we're delivering benefit equitably to all demographics in the U.S. And we can really trace our origin story to a neon connection that we hear from the people who wrote the original research coordination network for the USA NPN that it was envisioned as a complimentary network to neon at some early neon planning meetings where neon's work would be intensive with all the amazing co-located sensors and the USA NPN would be only phenology focused but extensive across the country. And indeed, I think we have been really complimentary over the years. We've had many long and rich collaborations with many people on the neon staff but especially with Katie Jones and Sarah Elmendorf. And then on our side, it's been Ellen Denny, Kathy Gerst, myself and Teresa who have been particularly involved in fostering the collaboration with neon. We started working on shared protocols early on so which I'll talk about a little bit more in a minute. Approaches to data quality, sharing ideas and code and approaches for data quality. We've worked a bunch on data integration and access to make it easier to use both data sets together. We've collaborated on the development of novel analytical methods and then on indigenous approaches to phenology as well as data equity. So I'll talk in depth a little bit more about most of these. The shared protocols, I'm not sure how familiar everyone is but essentially what the USA National Phenology Network and NEON do is status monitoring. So instead of saying the date of the first milkweed bloom was June 15th, we say on June 15th, there were blooms on the milkweed. So it's presence or absence of a phenophase on a given date. And then we also have carefully worded definitions when we say there's leaves on a plant, we all mean the same thing by that. It's unfolded, you see the leaf base and it doesn't include dead leaves for the example that I've put here. And if you want the further resource, the Elmendorf et al paper from 2016 has the full monitoring design for NEON for phenology. So for us at the National Phenology Network, we've implemented those protocols through our Nature's Notebook program. So we have over 1600 species of plants and animals. We have extensive training materials and support for observers. So we have people, volunteers across the country collecting phenology data, people in the parks, backyards, natural areas, volunteers as well as park staff, refuge staff who collect data as part of specific projects or part of their work. We also have local phenology projects which are locally or regionally organized efforts where there might be a particular question like when are the mesquite pods ripe because the extension master gardeners want to grind the mesquite flower and they want to know when that's ready. So there's usually like a specific set of species and a local question that drives these local phenology projects. And then the middle part of the slide is a screenshot from the mobile app where people can download and submit data either on their own or as part of one of these groups. And then in NEON, which I'm not sure how if everyone on the call is already like, oh yeah, we totally know how the NEON phenology design works. But at each NEON terrestrial site, there are a series of phenology plots that are co-located with the productivity and biomass areas and in the tower air shed. And so this is in contrast to our program, this is like highly designed in terms of a sampling design around the questions that NEON is getting at, whereas our observers tend to be more opportunistic or organized around a local or regional question. NEON's program in phase one focused on, or is focusing, I think the transition is, Katie can speak to this more, but I think it's happening now, but in phase one, three species, 30 individuals of the sort of dominant species at each NEON site. And then phase two, which some sites are transitioning to now, is the community phonology. So up to 20 species at each location with a minimum of five individuals and selected based on abundance, as well as the science priorities, so species of management concern or species targeted by other sampling programs. So the NEON phonology program so far has 4 million records, 16,000 observation amounts for 541 species at 93 plots and 47 sites. And these records, because everything's compatible, because we've worked together for so long to make the protocols and the data structure compatible, these are served concurrently through the NEON and USA NPN data portals. So when we step back and look at the nature's notebook data and the NEON data combined, we see we have 30 million records across the country with 25,000 observers and 18,000 sites. And so I didn't double check this, it's very likely that a number of those bigger bluer circles are NEON location. So we're getting what we sort of dreamed of, right? Like deep intensive, well-sampled phonology for dominant species at NEON sites and extensive covering area in between those sites with the nature's notebook data. And then because we have integrated the data, that means that you can look at both NEON and nature's notebook data combined in our visualization tools, as well as our download and other tools. So this is an example of an activity curve where we look at the total, this is for milkweed, how many open flowers there were and for the monarchs, how many active individuals there were. Or this is the total number of, sorry, this is the total number of plants with positive observations for flowering over the course of the season. So it enables cool data exploration by having the two datasets combined. And then this was a specific NASA funded project that we collaborated on with NEON and other partners to develop a publicly available repository of source code workflows and APIs that could enable people to get at multi-scale data. So one of the great things about NEON is that there's the in-situ data camera, phenocam data, and we also have MODIS data from NASA for the same locations. And so how can researchers that want to use all three of those get access to them more readily and integrate them more readily? So that was the idea with this project and it resulted in a series of our packages which are shown here at the bottom. One of these is the phenocent project which shows you a phenocam view shed and allows you to visually select what pixel might be the best pixel to use to be for comparing phenocam and MODIS-based phenology as well as ground-based phenology. So it helps you both select the data that you might be interested in using and then also download it all together. And that's covered in the more set at all ecological informatics paper for more detail. And then another dimension of our collaboration that has been really meaningful to me, especially is that our work in the Indigenous Phenology Network. So also I think actually sort of transitions from the prior slide, it was Jeff Morris that originally invited me to a Rising Voices meeting in 2014. And I met Katie, no, I must have already known Katie but we got to, we're here in this picture, right? Like this is me and oops, and Katie next to Kalani who led the network for many years. So this group formed out of the Rising Voices as an NCAR-UCAR-led effort to bring together Western and Indigenous scientists in a way that is equitable and respects and values multiple Indigenous approaches to phenology, recognizes Indigenous community members and scholars as the first phenologists on this continent. And so Katie and I have learned and built so many relationships with others and many great collaborations have come out of this group. The core focus, like everything keeps coming back to relationships, to being responsible, to being a reciprocal, good relationships with each other, to engaging equitably. One of the Katie and I co-organize a symposium at ESA in 2020 called Indigenous Phenology, New Mindsets for Working Among Worldviews with Thal Small and others to really bring to the fore some of the amazing Indigenous scholars who are doing work in phenology. It's just also been a really great connection point because many tribes and Indigenous communities see, think deeply about phenology and close observation of the natural world through the season. So it's been, I've learned so much through this. This is some of Katie Jones' work following on, I think the growth that we've both been through through the Indigenous Phenology Network and the Sensing the Earth Tribal Climate Science Partnership Summit. There was a workshop in June and there's another one this month with the idea to build partnerships between tribal college faculty and our science institutions to support data-skilled curriculum and climate research. And then there's also that, she's also working on the NSF-funded Earth Data Relations Working Group, which advises on exercising Indigenous data governance in open data repositories. So those are two of the things that Neon is bringing forward in terms of data equity and working with tribal partners. And then for us at the National Phenology Network, we have a few things going on. One is the use of our protocols, but without our data management system. In the Great Lakes Fish and Wildlife, Indian, Great Lakes Indian Fish and Wildlife Commission is doing a study on important, traditionally important species that they harvest, including the wild leeks shown here. But the locations of those plants are often, they're in seeded territory where they have hunting and gathering rights. And so they often don't want to show the specific location of the plants that they're gathering. So to respect data sovereignty, we sort of explored this. We thought maybe we could make a protected data system, but ran up against the Freedom of Information Act. And feeling like since we have federal funding, we would likely would be obligated to share locations if requested. So they're managing their own data. And then sort of, but another example where they are using Nature's Notebook because the location is at College of Menominee Nation in Kashina, Wisconsin, where they have a knowledge learning path that's open to the public. The location of the plants is not an issue. And so they're using our data management system as well as our protocols as well as traditional protocols for observing and names for observing those plants. And then on the right side, there's just two more recent Climate Adaptation Science Center funded projects. One about returning cycles of renewal, returning good fire to the Shumash homelands in Southern California. And so the phenology dimension of this is focused on the timing of when to burn and the ecosystem response in terms of basketry materials and how phenology post fire. And then time to restore is in the South Central US looking at the timing of eight species that are important to pollinators and working with tribes and others to collect, store and share that information in ways that respect indigenous data sovereignty and help inform management for pollinator restoration. And I'll just a quick pitch for the Foundations of Data Equity class that I took through. We all count was really a powerful set of tools and lenses for thinking about equity in data collection and use and storage and interpretation. And I think with that, I will pass it over to Teresa. Thank you, Alyssa. That was fantastic. It was like a total whirlwind blast through what the NPN is and our longstanding history with neon and it's really cool to reflect on. As Alyssa indicated, because of the very intensive sampling efforts at neon, the data set that we manage and host at the USA NPN is progressively larger with every day that passes. And I was estimating today, I think that that neon's responsible for about a quarter of the data that's coming in on any given year these days, which is pretty exciting. And as Alyssa described too, they're so complimentary because we've got the deep, really static data sets that are being collected there at the neon stations contrasted with the broad scale observations that are being collected by observers across the country. And that has enabled all sorts of cool science and management advances to be undertaken. And so I'll just talk about a couple of these really quickly to kind of give you a sample, but by my count, and I am certain that it is far from comprehensive because we have, it's challenging to keep track of every time someone uses the data for sure. By our account though, it's well over 100 papers approaching now 150 papers that have used the phenology data contributed to one or both of these systems. And that's just the peer reviewed literature. Really, there's lots more outside of the peer reviewed literature too. So I'll just highlight a couple of examples here for fun here to be inspirational, hopefully. Alyssa, are you gonna advance? Okay, great. So the first one I wanted to mention is, it's tricky to make a slide to support this because it's just not a very visually appealing effort, but this is a manuscript that emerged from collaborative effort with Sarah Elmendorf who is someone that Alyssa mentioned earlier in the presentation. She had been a staff scientist with NEON several years ago and we undertook this analysis collaboratively, several of us prior to the establishment of the connections between our two databases. So she actually had to pull the phenology data from the two separate databases in order to analyze them together. But the aim with this particular effort was to try to apply hierarchical modeling or Bayesian approaches to see if we could establish drivers to leaf out and leaf color change in the observations that have been contributed to both datasets. That may seem like a funny question because there are so many papers that have addressed the drivers to leaf out and leaf color change, but in truth, there's still a lot we don't know about what the specific drivers are to these phenological events and especially when you get down to the species level and especially to once you drift away from temperate forests. Eastern temperate forests we have dialed in reasonably well but once you start getting into water-limited systems it really becomes a lot more challenging to know specifically what the conditions are that plants need to be exposed to in order to trigger either leaf out or leaf color change or any other phenological event. And so this effort was novel at the time that it was undertaken because it took advantage of all of the observations that we had for leaf out and flowering for over a hundred species in the two databases combined across 15 different eco-regions. And the approach that we used, the hierarchical modeling was undertaken because it can tolerate messy data basically, situations where you maybe don't have a prior no preceding the first time that someone says yes to yes I see open flowers or in this case leaf out. It also can tolerate infrequent and irregular sampling which again is less of an issue of course in neon observations but definitely an issue in the observations contributed through nature's notebook. And by pooling all those data together you can draw strengths on that larger dataset to try to basically address the gaps and I'll be honest I'm not the mastermind behind the Sarah was that's my limited understanding of the why we undertook it. We really wanted to see whether this technique could perform better than the more traditional model building techniques. And it was interesting. I will say that there weren't any massive surprises that emerged. What you see on the left are the variables that emerged as having the greatest influence on leaf out and then on the right it's the variables that had the greatest influence on leaf color change. And so it really didn't come as a surprise to us that growing degree days or accumulated warmth in the spring and day length had the greatest impact on promoting leaf out and then it varied by species but frost and precip kind of had a suppressing effect. And then when we looked at the fall chill degree days which is basically the accumulation of cool temperatures after the peak of the summer season had the strongest effect on driving leaf color change. But though I think we kind of were a little disappointed because we didn't feel like we solved the problem of being able to identify drivers to these phenomena. It was a first attempt and in truth the database has grown significantly substantially probably doubled since the time that we did this. And so it's certainly an open opportunity for anybody who may have an inklinger and any enthusiasm around taking this further because we really it would be much easier to do now since the data are combined and there are lots more data. Next slide please. Okay, another cool, I really wanted to draw out papers like the last one where it was very obvious that neon data were front and center. In truth, a lot of people that use the phenology data that were there especially when they're pulling it from our site, I think it's fairly transparent to them that some of the data originates from neon sites. However, I think it's transparent at the point of pulling the data. I think it emerges in the analyses because suddenly you start to see there are particular sites that have very good regular sampling and don't seem to miss events where again, and persist year on year which is definitely something that varies with volunteer observers. That said, there are so many cool examples of analyses where researchers have endeavored to capitalize on the breadth of all of the data. And so absolutely it may be not so much that in the manuscript the people called out neon but absolutely it's embedded in here and it was part of the story. And so in this particular recent paper that I really think is fascinating the investigators explored whether urbanization has an impact on fall phenology. And so the motivation for this question is really what's the effect of urban heat islands on phenology? So we saw in the previous slide that temperature really is important for driving phenology in the spring again warmth. The presence of warmth is so important to initiate activity. And then at the end of the season, the accumulation of chill plays a pretty significant role in driving the senescence and abscission. So leave color change and drop in species. We know too that urban areas tend to be warmer than their surrounding less developed locations. And so these researchers just said let's take advantage of all of those observations that have been contributed on leaf color change and leaf drop and see if the timing of these events vary based on whether the location where the trees were sampled was urban or not urban. Next slide please, thank you. And so this map shows the all of the different locations and I'm sure there's some neon sites in here where leaf senescence observations were drawn from over a basically a 10 year period and there were over almost 200,000 observations here that these researchers pulled on. Go ahead and go to the next slide please. And this is just a quick summary of the results. On the X axis of this graph here, we have effectively urbanization, the degree of urbanization. They used human population density as a proxy but and it's long transformed here but on the left of the axis it's low. And as you move to the right, it's increasingly more developed. And on the Y axis we have the day of year that the leaves senest. And then the color of the lines that we have graphed here reflect the annual average temperature. And so the purple line on the bottom, it reflects locations at the highest latitudes or elevations where the annual average temperature is the coolest. And we see a really clear positive relationship here where as locations become progressively more developed, we see that onset of leaf senescence or when leaves are senescing, moving toward later in the year. And then as we move basically to locations with increasingly warmer average temperatures, which also equates to further south or lower in latitude, we see the slope of that line flatten out eventually. And eventually at the end, it actually reflects the inverse relationship. The locations with that yellow line are actually the most southern most parts of the Conturminus United States. So we're looking at Southern Florida and Southern Texas there. But in truth, we actually start to see an inverse effect there. Go ahead. And so I wanted to bring in this next study that just came out earlier this year because it's also related, this particular study investigated the influence of artificial light now. So the kind of addressing that day length control on both the start of the season, again, represented by leaf out and the end of the season reflected in leaf color change and leaf drop. So what we know, what's really well documented in the literature, again, talking about temperate forests here, just nice, well-behaved deciduous plants. And I say that because I'm in Arizona and things don't behave here well at all. We have many bouts of flowering within a single season and it's very hard to model and predict. So sticking with these nice Gaussian curve seasons where things progress through clearly leaf on, leaf off. Basically, we know that temperature is a major control. And as temperatures warm, that springtime is advancing earlier and delaying things later in the season. However, there is anticipated that eventually there's a limit on that. And for many species, it's day length where the species require a certain number of hours of daylight in the springtime to actually be able to respond to those warmer temperatures. And so it's been predicted that we'll see an advancement in the onset of spring activity up until we run into that limiting factor and then we will cease to see things advance. However, what happens when we start throwing a bunch of extra light into the mix? And we actually are doing that because we have so many artificial lights on all night long and that it's quite concentrated and it's broad spectrum in many cases and it's not just pointed down at the ground but they're pointed up into the air. And we have cars driving around with lights on. And so all those extra sources of light can have a interactive effect here as well. Go to the next slide please. And so what these researchers did was pull on a satellite product and I'm forgetting the name of it but it is specifically aimed toward documenting where it's light in the night basically. You can see that imagery in the background where there are clear hotspots of artificial light and it reflects our cities of course. And then what we have layered on top of this are observations of breaking leaf buds on the left and colored leaves on the right. And again, I'm certain that there's some neon sites reflected in here. And what these researchers did was then evaluate what's the relationship here? What's the, is there, does the presence of the artificial light have an influence on the timing of leaf out and leaf color change? So basically in the locations where those observations are being collected if they happen to fall in pixels where we have bright white there, do we see a different timing of the event relative to similar latitudes but not so developed? And it was a very clear yes. It was very clear yes for the leaf out. It was a little more mixed for colored leaves but absolutely the take home message was artificial light does have a effect on the timing. And so therefore this kind of changes our story about whether we're gonna see a limit to how long the growing season can be extended in either direction because we are kind of, what's the right word? We're kind of supplementing that limit. We're subsidizing it, I guess I'll say with the artificial light. And so removing that control on the lengthening of the growing season. Next slide please. Okay, so I only put a couple of examples in here but we have a page on our website and I believe Neon does too where you can explore all of the different papers that have been published using the data. And if you're fishing around for a research question or inspiration, I strongly encourage you to check it out because there's really cool stuff on there and there's more stuff coming online just about every week. And I could easily fill hours talking about all these different examples. It's really pretty cool. But shifting gears a little bit because it seems worthwhile to mention these things too. We here at the USA NPN also develop our developing and delivering a several suites of raster gridded data products too. And these are real time and forecasted products as well as products that have been calculated back into the previous century, previous two centuries actually in some cases. And so those are additional data sources that are readily available and can be combined with the observational data being collected on the ground at both neon sites and other sites through Nature's Notebook for further analyses. One of those products is what we refer to as our spring leaf index or our start of spring maps. This is an example of that map as it was collected from April 18th of this year. And what it is indicating is the color represents the day of year that conditions that are associated with the start of biological activity in the Eastern US really were met. And so it's effectively accumulated temperature from the start of the year that and these particular temperature thresholds were established using observations of flowering, leaf-out and flowering in lilacs and honeysuckles. We have a long historical data set for those that goes extends back into the 1950s. And those plants are among the first to actually undergo activity in the springtime. And so this doesn't necessarily reflect the day of year that all species put on their leaves. It's an index, but it is an index that reflects conditions that are consistent with some activity in particular species in the spring. And so in this map, the color reflects the day of year that occurred. And then what resonates a lot more with folks is the slide, the next slide, the map on the next slide. What we do here is difference that current year map to the recent three full decades. So this is actually incorrect. My label at the bottom says difference from normal 81 to 2010. We actually updated the maps now where we're using the most recent climate normal period. So we difference the current year from the day of year that the event was reached in 1991 through 2020, the average over those 30 years. And then what the map indicates is was this year earlier than when it occurred on average those past 30 years or later and by how much? And so the red tones indicate locations where the onset of that spring activity occurred earlier than it did on average in the last 30 years and the blue tones indicate locations where it occurred later than average. And we find that these maps really get folks engaged because it's kind of a pretty clear distillation of information packaged in a way that makes sense to them. They can just simply look at the map and determine is spring happening earlier or later. It's absolutely not a comprehensive story but it's a starting point for a conversation. And so what we also find is in years where the southern states are shaded blue, meaning spring started later than average, we don't get very much media attention. But if those states like Georgia and Alabama and Texas and Florida are red, then we will get a lot of phone calls from the media because everybody wants to know a spring coming earlier and what does that mean for the allergy season and for the cherry blossom festival and for the crops that we just put in the ground and for mosquitoes and for all the reasons why we care about phenology and the timing of seasonal events. Next slide, please. And so here's a couple of examples of where folks have leveraged those maps in kind of storytelling and engaging with the public. One of the things we do is make those maps readily available in KML format, which is the format that most TV weather folks use. They can grab that file and pull it straight into their software that they use to make their online broadcasts or on air broadcasts. And so the map on the left is a screen capture of where someone did that and they just kind of reshaded it and re-labeled it but it is the data set from us. And they were using it to tell the story about allergies in particular. And then on the right was a similar story where folks were fretting that the cherry blossoms were going to be done blossoming before the actual big event occurred down in the tidal basin area. Next slide, please. Parallel to those, we also offer and deliver a couple of suites of accumulated growing degree day products. And so that's, it's fairly similar to the spring indices but we make these available on a couple of different, with a couple of different parameters. So different base temperatures and different, I guess that's it for now. So the map on the left is indicating how much heat, basically how much warmth has accumulated since January 1st in particular pixels across the country. And these maps are available at two and a half kilometer resolution in the current year. And we also have tools that enable you to go in and pull a time series within a pixel as well. And then on the right, we deliver anomaly maps. So again, similar to the previous slides I showed, this indicates whether we're ahead of schedule or behind schedule in terms of heat accumulation on a given day. And so these maps were from 2020, which was an early warm spring. And so you can see the impact of that across those Southern States where those are, those locations are many hundreds of growing degree day units ahead of schedule. And basically what that means is just the, those locations have been exposed to a lot more springtime warms than typically occurs in the early months of the year. Next slide. Those maps are also, those are, those are useful in and of themselves for sure to kind of tell a story about how the year has been unfolding. But then another way in which they are used and that we make use of them is in, especially in agricultural applications and integrated pest management, it's been established by field research or growth chamber experiments, other experimental approaches, exactly how much warmth in an organism needs to be exposed to in order for it to undergo a phenological transition. And so what we've done is in cases where we've been able to identify a species where it would be helpful to know when something's going to happen, when we can identify that and it's already been established how much warmth needs to be accumulated in order for that event to occur. We operationalize that as a real time forecast by just taking that, that growing degree day threshold that amount of heat that needs to be accumulated and using that as a way for how we deliver and present the maps. And so in this case, emerald ash borers are insects that bore into the heartwood of trees, ash trees in particular and do a whole lot of damage, I'm sure you're aware. And they're fairly hard to control for because they spend most of their life cycles under the barks of the tree. But when they become adults, they emerge from the bark and they fly around for about two weeks and then they lay eggs. And that is a prime opportunity to try to control their spread to additional trees. You wanna really prevent those adults from laying eggs on uninfected trees. And so managers have indicated it's helpful to know, it's helpful to be able to anticipate when is that gonna occur because then we can get traps out there and try to get crews out there to control their spread. It's been established by others that adult emerald ash borers emerge around 450 growing degree days. And so what we simply do is on any given day, shade the map based on how many growing degree days have been accumulated relative to that threshold of 450. And so in this case, the locations that are shaded yellow are locations where that threshold has been met recently. And so we predict that emerald ash borer adults are flying around in those locations at this time. And if you happen to be in the green or the blue tones, you're in locations where you're getting close to reaching that threshold. If you're in the purple tones, you can hang tight, it's not time yet. And if you're in the brown, you're past your threshold, you missed your window. Next, well, just go ahead and click it. One of the things we offer is folks can sign up to receive email based notifications based on their location. And so these maps are available on our website, real time and six days out. And so anybody can come at any point and explore the maps looking now and into the future and even into the past. Not everybody always wants to do that. They want a reminder delivered to them. And so you go in and you type in your location and then it'll prompt, you can sign up and then you'll receive these quick notifications when you're approaching. I think it's three weeks out, two weeks out and one week out, something like that. To try to help folks take most advantage of the information that's available. Next slide, please. The one other, I did want to make mention too because Alyssa mentioned early on in our strategic themes. One of the things we also try to do is just engage beyond just science and management but to ideally everybody who lives in the country to help them understand what phonology is and why it matters and how it's relevant. And so we do that by engaging via various podcasts and with the media and other opportunities whenever we can to help try to demystify what that old fashioned word is. Next slide. So with that, Alyssa and I will be happy to take questions and we invite you to get involved if you're inspired. At a minimum, please explore the data that are, I should have said, neon and NPN data. We have a wealth of curriculum material available for both K through 12 and post graduate instructors. We have the maps and forecasts that I mentioned. We also have several different newsletters that you can sign up for to stay in the loop on all of the great developments that are occurring. And we also always invite collaborations. We love working with data users or data collectors or anyone along that spectrum to just increase the reach and the impact of what we're able to do. So thank you. Thank you, Teresa and Alyssa. That was a magnificent presentation, really interesting. I'd like to remind everyone that you can ask your questions in the Q and A chat. There should be a button at the bottom of the screen where you can enter your questions and we will also take some live questions. I'd actually like to kick this off perhaps. This is a fascinating subject and really, really interesting presentation. As I understand it, there are different partners and stakeholders that are contributing data to the NPN. Is data quality control a challenge given the fact that you have multiple sources of information as part of the network? That's a really fair question, absolutely. Alyssa, do you want to do that or do you want me to? Yeah, either way, you can take it. It's definitely something we think a lot about. Pardon? It's definitely something we think a lot about. I guess I can say a few things that Theresa can time in. Yes, we think a lot about that and we sort of do the QAQC, so quality assurance, like what can we do on the front end to make sure the good data's going in? And so that's a lot about having really clear interfaces, really clear definitions, photographs where we can and then training happening locally. So like for the species that people are watching, like what does that look like? We have a new and updated observer certification course on our website. So, and then I think soon you will be able to know whether your observations came from a certified observer or someone who's not gone through that certification. And then we do stuff on the back end as well, the quality control where we're looking for observations that are in conflict with each other or that are logically inconsistent and either removing those when it makes sense or flagging them. And yeah, I was, I think, some of those we have in common with Neon, like Katie and Sarah and Kathy and Ellen and like we sort of came up with some of those together that are in the Neon workflow. And some of those, like there were problems that happened for Neon data that don't happen for us and vice versa. So there was, we could make a, we perhaps should make a little slide or flow chart that shows like where we have, where we do quality control measures together and where, and what our separate ones are. Do you miss anything, Teresa? No, there's been a couple of studies that have looked at that and have generally found really good concordance between professional and amateur observers, especially after the beginning of the season or the first few months of participating. Is the, are the Neon sites, the Neon phenology observations used as part of that kind of quality control assessment? Like in the publications? I don't know actually, I don't think so because those were done before the integration, right? And we couldn't unmute Katie anytime too if she wants to chime in. Yeah, but certainly when the neon ops come into our system they go through the same checks that the rest of the, that our data go through. Great, I think people can also raise their hand to ask questions live. I'm not certain how that actually works, but perhaps Samantha or Darcy can page them in once one of the questions are, when there's available time to ask those questions. I do see a question in the chat. Question is from Xian Wang, Wang. Could we potentially identify species based on the phenology variability for example, can we identify annuals and perennials? How much potential is there in doing that? Yeah, I'm happy to try and answer that. So I think the question is asking do we have good representation among these different functional types? And if so, is there the opportunity could we leverage that and see what phenology the variability in phenology might be across those different functional types or growth forms? Yeah, definitely, yes. I don't know off the top of my head what the breakdown is among the different growth forms or functional types. But I know just last week we were asked what's the representation of herbaceous species because there's an effort in an international effort with focus on herbaceous plants because traditionally trees, overstory canopy trees have been dominantly the focus of phenological investigations and studies. And so we quick and dirty during the call calculated it and it's about half and half among our plants where trees versus herbaceous. So it would then be a matter of looking among those which were perennials versus annuals. And then it would also be a matter of that's just the breakdown of the species available for observing in the program. The breakdown then would be how many observations do we have from represented for those different species? And that I don't know but it's absolutely a question worth pursuing and an opportunity, an open opportunity. Cool, I can ask one if no one else has one right now. So looking at your maps, obviously amazing spatial coverage so many hundreds of thousands of records but there are some white faces in there. It's interesting even with the citizen science observers there are areas that seem to be more or less covered. And so I wonder if you think is that something that you kind of actively try to do something about to sort of reach out to people that are more rural or don't live in population centers or don't live near university or you talked about like tribal partners maybe in certain jurisdictions or isn't it just sort of like you take whoever's interested comes to the network and they offer what it is or is there sort of more active from the network outward to kind of fill in the geography of observations? Alyssa, do you wanna jump in or would you like me to? Yeah, no, go for it. Okay, so I would say the answer is both really. Absolutely the way that nature's notebook is set up is that anybody and everybody is encouraged to participate for as long as they would like to participate but you're right that. So right now the way it stands is that you sign up you register yourself, you register your location where you're gonna observe you register either individual plants to make repeated observations or animals for that site. And then it's a big ask we really hope for observations on at least a weekly basis maybe more frequently when things are changing rapidly so you can really catch the start and the end of those events with high precision and then ideally to keep it going for years on end so we can have a really fantastic temporal record they're a good time series and it's a lot to ask for and so we recognize that it's a lot to ask and so therefore we say pick a site that's very convenient like right outside your door make it even such that maybe you don't even have to walk outside to make an observation you just stand at the window and so then that definitely leads towards a bias toward more developed more population density it just ends up following population density. We have definitely through particular campaigns and efforts put focus on particular geographic areas or species and that has grown data in some of those less data dense areas but that's of course limited by both available funds and staff and that kind of thing. One thing that we are trying to investigate right now is can we lower that barrier to participation to invite more observations? Recognizing that, just recognizing that what we're asking folks to do is such a heavy lift and we're really only going to get a pretty narrow slice of the population stick with us for a long time and so we've been kind of inspired by some of the other programs it's more like iNaturalist where you can make a very quick incidental observation you really it's very quick and easy to do it on your smartphone while you're out and about could we maybe do something like that for phenology as another way to kind of shore up what we've got in terms of the long-term observations and depending on the type of question that you're pursuing and the analysis that you wanna invoke those observational scattering just random yeses or noes that aren't part of a longer time series at a particular location may be indeed fine and well and good and so that's actually a pretty major shift to the database and the data model and the whole approach that we've evolved over all these years but we're exploring it as a way to kind of grow and really do a better job at trying to fill in some of those gaps. Is there anything you wanna add, Alyssa? Okay, we have a couple of questions from the audience from our own Katie Jones. Thank you so much for your presentation. One aspect of the NPN protocols that I think is very cool is the intensity data, not just whether phenophase is occurring but the extent to which a phenophase is occurring on an individual. Can ask questions about trends and rate of transition across years, species, et cetera, but this is still an underused aspect of both the NEON and the NPN phenology data. How can we promote opportunities to leverage these underutilized data in analysis? Alyssa, you should answer that one. You should definitely talk about the recovery. Katie's teeing me up but I don't even know if we've talked about this. So yes, we have been over the summer with a wonderful undergraduate student. I think the main barrier for people to use the intensity data from our data output tools is that it's been, so how many flowers you see 11 to 100, 100 to 1,000 and then what percent of those are open, five to 25, 25 to 50% and you have to track flowering through time. You have to do a bunch of data formatting and processing to get that information to identify start and end of peak. So we have a new product. We have both hopefully a publication and a new product, a peak phenometric product coming. I don't want to say anything about timeline. It could take years for us to get there but we'll at least be prototyping it and so that you could readily download information on, like this is when peak started for this species, this site, even maybe this region and this is when peak ended and use that data more readily. So I would love to talk to others who are interested in that and definitely something we're thinking about. I think that's the main barrier to usage is just the people understanding the kind of convolutedness of how it is right now and it just needs to be formatted more readily. Great. We have one more question but unfortunately we've run out of time. So I would ask that the person who asked the question stick around for a few more minutes so that we can ask the panelists. But I would, thank you so much for an extraordinary presentation and we really look forward to working very closely with the NPN as we move forward and hopefully everyone got as much out of this presentation as I did and I'd like everyone to, I'd like to open the invitation to our next presentation which will be in one month's time. January. January, okay. We're skipping December, have a great holiday but we will see you back in January. Okay, great. Well, again, thank you both for a terrific presentation and thank everybody for coming.