PubTalk 07/2019 — Taking the Pulse of Our Planet

Video Transcript

Detailed Description

Title: Taking the Pulse of our Planet: A 10-year status report from the USA National Phenology Network

• Plants and animals in your backyard are sensitive indicators of climate variation and change
• Understanding and predicting plant and animal seasonal activity, a science called phenology, helps humans adapt to a changing world
• Learn about a national network of volunteer and professional observers tracking plant and animal phenology, and find out how we get involved

Details

Image Dimensions: 1370 x 886

Date Taken:

Length: 01:26:01

Location Taken: Menlo Park, CA, US

Video Credits

Contact: Amelia Redhill - aredhill@usgs.gov

Transcript

… Geological Survey’s July 2019 public lecture. I’m Diane Garcia, and I’m with our Science Information Services. And I’m delighted to see such a full room. Thank you very much for attending. Before we get started, I always like to plug next month’s lecture. And we are going to have an August lecture on August 29th. And it is Pliocene World – Earth’s Climate 3 Million Years Ago and How it Relates to Our Future. So I hope you pick up a flier on the back table. And more importantly, I hope to see you here late August – August 29th. So, but what you’re here for is tonight’s lecture. And it’s Taking the Pulse of Our Planet – a 10-Year Status Report from the USA National Phenology Network. And it’s presented by Jake Weltzin. Jake assumed his position as executive director of the USA National Phenology Network in 2007. Jake’s interests in natural history developed as he grew up in Alaska and served as an exchange student in the Australian Outback. He obtained his bachelor of science from Colorado State University and his master’s from Texas A&M University and a Ph.D. from the University of Arizona. Following a postdoctoral fellowship at the University of Notre Dame, Jake went to the University of Tennessee where he served as assistant and then associate professor. Jake is interested in how the structure and function of plant communities and ecosystems might respond to global environmental change, including atmospheric chemistry, climate change, and biological invasions. His research spans temperate and tropical grasslands and savannahs, temperate woodlands, deciduous forest, and sub-boreal peatlands. His recent experience as a science administrator at the National Science Foundation underscored the need to foster large-scale science initiatives, such as the USA NPN, as its first executive director. Jake’s vision for the USA National Phenology Network is to develop a continental-scale instrument for integrative assessment of global change that simultaneously serves as an outreach and educational platform for citizens and educators. So the USGS monthly public lecture is pleased to bring you a program this evening about the National Phenology Network. I’m going to ask that you please hold your questions until the end. And now I’m going to ask for you to give Jake a warm round of applause to welcome him.

[Applause]

- Sierras.

[Applause]

- Thank you, Jake. I want to – we have time for questions, of course. And, of course, we’re going to ask you to please walk to the microphone to ask them so that our online viewers can hear the question.

- Thank you very much. I came with two other people who – we had a group of people who created our own monitoring site.

- Mm-hmm.

- In Palo Alto. And we monitored that site for a little over five years. And it’s a private site. And just wanted to come and offer, if anyone was interested in seeing how we set the site up, and we can take you over there and show you what it looks like.

- Is that through Nature’s Notebook? So you have a Nature’s Notebook site?

- Yes, we – yeah, we put all the data up on Nature’s Notebook for a little over five years.

- Oh. Great.

- And we had seven species of trees.

- Okay. Okay.

- And two samples of each.

- Excellent. Wow.

- Yeah.

- Thank you very much for your contribution. I feel a little bit bad. I should have done a little bit of research for, okay, who here might be participating in Nature’s Notebook, and what are the sites nearby? California has, I think, 3,000 registered sites, though. So got a lot of action here in California. So it’s really great to hear. I do know that, in the California Natural Reserve system, a number of the natural reserves are actually tracking blue oak and other taxa. So you’re not part of a natural reserve? One of the UC reserves? Okay. And that’s been fantastic. So that’s another kind of a network. It’s kind of a node of our network that really makes it a network as opposed to, you know, a small team of us from Tucson and Fort Collins. [chuckles] Thank you.

- So, first, thanks for coming out. I enjoyed your talk.

- Thank you.

- So, I’m a very heavy eBird user.

- Ah.

- And so some stuff with iNaturalist.

- Uh-huh.

- And I didn’t – you mentioned those, I heard, in your talk. But how much sharing of data goes on? Because, you know, I don’t …

- Yes.

- I don’t want to have to enter observations into six different systems.

- Yes.

- Right? And so there’s, like, the citizen scientist fatigue, you know …

- Yes.

- … in terms of recording data.

- [laughs] Yes.

- So just – can you talk to that a bit?

- Hi, Jake.

- Dr. Weiss.

- Yeah. Just – I was wondering, what’s your annual budget? And how much has been invested, specifically in your program, over the 10 years?

- Okay. Great. Thank you, Stu. I appreciate it. Well, this is us. I’m a USGS scientist. Everybody else on the team is [chuckles] from the University of Arizona. So I manage a cooperative agreement with the University of Arizona. The total budget is about $1.2 million a year. That’s my salary, the salaries that you see here, some overhead costs, and whatnot. So that’s today. It’s been stable for about the last five years or so. Resources come in a little bit from NASA. A couple of grants to the University of Arizona. Some money from Fish and Wildlife Service. So we don’t – can’t – they give us a little bit of money so we can accelerate their cool websites that we do for them. So the total is about – so far, the total investment is about$12 million. When I first started, we had a quarter of a million dollars, and I said, well, that sounds great. And they’re, like, well, that’s your salary too. Mm, okay. [laughter] That’s not so much. So, really, we’ve sort of built it through time. We’ve been successful. I’m not – you know, that was enough. It was the seed money. But that’s – so about \$12 million total. So it sounds like a lot. A dollar per record. [laughs] 15 million records. But we’re catching up. We’re catching up. Thanks, Stu.

- Any last questions?

- Usually in a room – in any situation, it takes about seven seconds to truly plumb the questions out there. So we wait seven seconds in our office if somebody has a question. [chuckles] Please, go ahead.

- Just a question. Do you know about Calflora? Because they have been acquiring phenology information on California flora for a bunch of years. So I’m sure there are many, many millions of records.

- Yeah. That’s a very good question. I’ve heard of Calflora, and I’m not familiar – well enough familiar with the nature of the data or the standardization. We have had a lot of involvement with a variety of different California organizations. So my thought, to be honest, is there might be some significant differences there, but it would be very good. So there are a lot of other organizations that do collect phenological data. In fact, if you work with iNat, you – in some species, you actually have a chance to go over and add the phenological data in – link it over to the National Phenology Network, and the data are actually shared back over. On eBird, we haven’t bridged the gulf yet. They’re producing the best-quality bird data set. At a global scale, we’re producing the – we’re trying to understand what the resources are. So Calflora might be a really good one for us to work with. There’s actually a lot of different kinds of data sets out there.

- Yeah.

- Botanical gardens, for example. Many of them have great phenology data sets. Some of the California natural reserves. Actually, many of the Fish and Wildlife refuges – the national wildlife refuge systems have phenological data. Everybody used a different protocol, a different way to count coots, you know, or whatever. And those data are all on cards and on paper, and so sometimes we call those shoebox data sets. My guess is there’s probably several of you who are sitting on shoebox data sets. Meaning, like, you know, that you have been keeping your own data, like, on a barn door. When did the – when the combines arrive, or when did the martins arrive, you know, et cetera. So there’s all kinds of different data sets that are out there. We found that – we started out thinking, okay, we’re just going to integrate all these different data sets together. It’s going to be great. And, like, oh my gosh. You know, we realized, even that, as we changed our protocols through time, that that could create confusion. Because we had to tweak them early on, and we didn’t know how to – you know, what’s the best way to track a fish, you know, in a stream? So we had to change things over time. We realized when we worked with New York Botanical Garden, it took several years just to get the data re-homogenized back into the current protocol. So now we build better versioning, and we work to not change our protocols. But just – data integration is a – is a huge job. And there’s so many different data sets out there, like the Thoreau data set, and the Leopold data set, and the various and sundry data sets. Rather than try to gather those together, we say, here’s what we have, and if you have a specific question, we’ll help you find those kinds of data sets that are out there. So you actually have a data set registry tool. So you can say, I’m from this place. And we try to create a community of practice so they can figure out, okay, I’m really interested in coots. Okay, what phenology data sets are coot – of coots are out there and, you know, help that. And then that’s a grad student who’s going to integrate all those data and maybe share them back or publish them. So, good question. Thank you.

- Mine’s similar. You have a real challenge with data and having quality data.

- Mm-hmm.

- And so I’m kind of curious about war stories about – you know, you got a changing climate. You have invasive species. And then things that show up that you never expected. So I imagine you have a couple of stories with respect to surprises that you had to deal with.

- Yeah. So, with data coming from so many different sources, some of them might be higher quality than others. Some of them might have a higher level of accuracy than others. And, when you put them together, there’s the potential to create – instead of something useful, just a big mess.

- Yes.

- So how do you work on that problem?

- That’s a great question. We have a whole page on our website devoted to data quality – descriptions of the processes that we use. And we developed a strategy to deal with data quality. You have two parts. We basically break it apart. We have quality assurance and quality control. Quality assurance is working to create systems to get – to prevent people from making mistakes or whatever before the data come in. Quality control is where, okay, now we have this piece of data. Do we know whether it’s any good or not? There actually might be a third part. I just sort of realized that we create tools after the fact that allow people to kind of post hoc go in and try to work with the data and slice it and determine which piece of data is not so good. Maybe that would be part of quality control. But we do that sort of not – we ourselves don’t do that actively. Rather, we provide information to others to be able to do that. So quality assurance might be things like pre-filled dates. So, for someone – for example, if someone said, oh, I saw this flower, and then I saw this leaf, as they’re entering data. What we know for that particular species, that actually the leaf comes on before the flower, then they’ll get a little flag. They’ll try to enter a date in the future. That won’t allow them to do that. Other kind of simple things that we can do to prevent mistakes from occurring. Those that might be mistakes. Or we could – we actually do a lot of training before people even go to the field, say, with our certified leader program, to try to improve data quality. So, before anybody even goes to the field to make an incorrect interpretation, perhaps, or enter the data incorrectly. So those are all quality assurance. Quality control then allows us to do some out-of-range testing, for example – pretty easy to do. Except for things like blue spruce, which is everywhere. Red maple is also everywhere. Except there is a red maple in Phoenix. I know it’s not Acer rubrum. It’s somebody’s red maple. It has red leaves on it. So it’s out of – so we flag it. Because we don’t know whether it’s actually really – someone could have planted a red maple there – truly Acer rubrum L – Linnaeus. Because, in Nunavut, which is what the old Northwest Territories, people started saying, what are these weird red-breasted birds doing out here all the sudden? They’re at the very northern end of Canada. It turns out it was robins. [laughter] Robins had actually started – they were – they were vagrants – or, what’s the word – on occasion, seen on occasion. But, because of the conditions changing, you actually had a shift in robins, where they’re becoming part of the – part of the natural history of the area, if you will. Relatively recently. So we don’t necessarily know whether something – if it’s out of place or whether or not it’s actually a good piece of data. So we flag it with some quality control flagging. There’s one more piece that I’ll tell you. So, if you have a piece of data, and it’s – the question is, did you see a flower on your lilac? We ask people to say yes or no, or I couldn’t tell, or I didn’t look, basically. And so, if you have – because that absence data. We ask them, tell us – did you look or not? They might say, no, I didn’t look today. Okay, good. So that means it – absent – you don’t – you can’t make – you don’t have to make inference as to whether it was or not. So if you have a piece of data that goes like this – someone’s watching it through time. Yes. That’s a lot different than somebody who’s going out weekly. No. No. No. No. No. Yes. Yes. Yes. Yes. No. No. No. That’s a – oooh, that’s a lovely set of data right there on, say, leafing or flowering of red maple. And so we actually – that’s how we collect the data. We distribute it that way. So that takes a lot of processing. So when I make a pretty map, we’ve had to deal with all of that. But it really allows someone to be able to kind of go out and parse all that out. It might go yes, yes, yes, yes, yes, no, yes, yes, yes, yes. Okay, what’s going on there? So the scientist who’s doing the data analysis can make inference based on a string of data. So those are a few examples of how we work to manage the data sort of up front once we have it, or how we process it after the fact. Thank you.

- One quick question. Looking 10 years in the future, say, the way the Apollo program did their 10-year within-the-decade moon shot idea, if you look 10 years in the future from today, what particular challenges or successes or things like landing people on the moon – that kind of out-there goal do you think is possible and that you’d like to see?