Data and the Bees
We use data to identify and solve problems all the time. In truth, this is nothing new. When wheelwrights were making wagon wheels, they paid attention to what went into a wheel that lasted longer than another. How many spokes, what kind of wood to use, and whether or not it was worth putting a metal hoop around the wheel. The Roman Legions paid attention to the most effective shield formations and used that data to build a massive empire. Farmers learned that cross-pollinating different varieties of the same plants could create whole new varieties by promoting desired characteristics. They just needed the right mix of plants and bees to help in the process.
For a while now, there has been concern about the number of bees dying off around the world. Whole colonies have been collapsing. Already, the bee population has dropped sufficiently that some beekeepers are actually driving their colonies around to different farms to make sure the crops are pollinated. Given the role they play in the food chain – pollinating all sorts of flora to keep the bottom of the chain going – people have been looking feverishly to find the cause.
Researchers from Penn State’s Ecology Program recently made some headway in this area. A recent study looked at the combined effect of habitat loss and a changing climate on the bee population. Habitat loss is of course fairly obvious. The more people spread out, the less room there is for a natural bee colony. Especially in the big cities where there is little grass to be had, to say nothing of the lack of forests and fields full of flowers. A changing climate is naturally more difficult to quantify as one has to take into account a number of factors such as day-to-day weather and longer term cycles that exist both in the earth’s orbit and the sun’s sunspot cycle. However, it was found that the warmer winters and increased rains in the northeastern part of the United States had a definite negative effect on the bee population.
The researchers relied heavily on data from the United States Geological Survey in conjunction with spatial maps and predictive models to reach their conclusions. One of these conclusions is that different species of bees are affected by different kinds of environmental changes. One species may be heavily affected by sunlight, another by the amount of precipitation. So, what affected the bees more in general? Loss of habitat or climate?
Bees are pretty adaptable as it turns out. Unless you suddenly build a massive industrial complex where there was nothing before, the bees will work around it for the most part. However, the climate is tougher for them to handle. That’s because changes in rainfall and temperature don’t just affect the bees directly, they affect their food supply. If it is hot or cold enough to knock out a weaker bee colony, it’s also bad enough to knock out a lot of the flowers they fed on. That means another colony can’t just move in and take over. There is literally nothing to take over.
How will this research help us come up with solutions to the bee problem? It’s too early to say. Yet, these Penn State researchers have taken an important step in getting us to a solution. They identified the problem at hand and used data to better define it. With this new research others can pick up the baton and keep things moving in the right direction. That’s how things get done, by collecting, refining, and analyzing the data again and again until the solution to the problem finally becomes clear.
That’s why TARTLE puts so much emphasis on data privacy and sharing. In sharing our data to support important work like the above we are helping to solve problems that are bigger than any one of us, but collectively should be well within our grasp.
What’s your data worth?
Farmers learned that cross-pollinating different varieties of the same plants could create whole new varieties by promoting desired characteristics. They just needed the right mix of plants and bees to help in the process.
Speaker 1 (00:07):
Welcome to TARTLE Cast with your hosts, Alexander McCaig and Jason Rigby, where humanities steps into the future and source data defines the path. The path.
Alexander McCaig (00:24):
Well how's data going to define the path for a bumblebee? I don't know, but we'll tell you soon. But the first thing you got to do is you got to go to TARTLE's YouTube. You don't have to, but I would suggest so you can hear what all the buzz is about. If you like listening to us, you can also see what we look like. We're not that fantastic to look at, but we are on here, and you can see what it's like in the studio to move yourself out of the audio version. But yeah, we'd love your support on YouTube. And that's a big sharing platform. A lot of people use it all over the globe and we put a lot of work into getting this stuff produced. We're not asking for any sort of payback on it, but we'd love for you guys to share and comment and interact because interaction brings us all to life here.
Jason Rigby (01:08):
Yes. And we have 135 subscribers right now.
Alexander McCaig (01:13):
135.
Jason Rigby (01:14):
And so we need to get that to at least one million.
Alexander McCaig (01:17):
How are we in 80 plus countries, and we have a hundred and something people subscribed to our YouTube?
Jason Rigby (01:22):
It's because we're producing shit content, Alex. No one likes us.
Alexander McCaig (01:30):
No, it's funny, we found that a lot more people are just listening in an audio format.
Jason Rigby (01:35):
Yes.
Alexander McCaig (01:35):
Substantially more.
Jason Rigby (01:37):
Oh, yeah. Substantially more. Yeah.
Alexander McCaig (01:38):
So that's been kind of nice, but like all things in life, good things take time. It'll steam roll. And when someone finds it there like, "Oh, this is a lot of content."
Jason Rigby (01:47):
Yeah, exactly.
Alexander McCaig (01:48):
Yeah. That's the point and we're here to educate.
Jason Rigby (01:50):
And Google's number one search engine, YouTube is number two, for search engines.
Alexander McCaig (01:54):
Yeah. That's why you've got to be on both.
Jason Rigby (01:54):
So most people when they watch our stuff, it's they've looked something up on YouTube and then we popped up.
Alexander McCaig (02:00):
Yeah.
Jason Rigby (02:02):
Let's talk about climate change. Number one in our-
Alexander McCaig (02:06):
Buzz. Buzz.
Jason Rigby (02:06):
... Best seven is climate stability. And let's talk about wild bees.
Alexander McCaig (02:10):
Bees are fun. Are not all bees wild? How do you domesticate a bee? Put a leash on it?
Jason Rigby (02:16):
You put it in a... I guess if you have your own hives, then they're domesticated.
Alexander McCaig (02:22):
Do I have feed it a bowl of food, when it's whining at me?
Jason Rigby (02:26):
Have you seen those hives that collect the honey automatically in a jar?
Alexander McCaig (02:30):
I love that. And you twist the thing and it doesn't upset the hive.
Jason Rigby (02:33):
Yeah.
Alexander McCaig (02:33):
So cool.
Jason Rigby (02:34):
Yeah. So I love stuff like that.
Alexander McCaig (02:35):
We don't have to pull them out and disturb them. It literally just shifts the hexagonal structure slightly so that the honey can move through.
Jason Rigby (02:41):
We need to buy one of those and stick it somewhere.
Alexander McCaig (02:43):
Right in here.
Jason Rigby (02:44):
Yeah. Stick it through our window. Have you seen those? They have a square-
Alexander McCaig (02:46):
Well listen, if the bees' undisturbed, I'll keep them in the house.
Jason Rigby (02:48):
Yeah. Yeah. They're not, it's not that big of a-
Alexander McCaig (02:51):
Studio bees.
Jason Rigby (02:52):
Studio bees. Yeah.
Alexander McCaig (02:55):
Beegay. Beegay. Where did our bees go?
Jason Rigby (02:57):
We're watching them?
Alexander McCaig (02:58):
This is the climate beegay. Where are the bees going?
Jason Rigby (03:01):
Wild bees are more effected by climate change than by disturbances to their habitats. According to a team of researchers led by Penn State.
Alexander McCaig (03:09):
Yeah. What does that mean? So if I'm going to, in the middle of a nicely forested area with a bunch of flowers and I'm going to slam down like a 55 plus aging community, retirement community, it's not really going to upset the bees.
Jason Rigby (03:25):
No.
Alexander McCaig (03:26):
What's going to upset the bees is precipitation. What's going to upset the bees is too much sunlight, too much heat, trapping all that in there because that's going to affect actually the flora and fauna that allowed them to thrive. Putting a house in the way the bee flies around it. But physically crippling the system itself, not displacing flowers, but you can change their concentration, whatever it might be. What you're looking at is really the rain and the sun. So let's talk about how our climate, I guess in all senses, us affecting these things, regardless how you say, if you put a house there your still affecting it, right? And if the earth's getting too hot, it's still affecting the bees. So either way you rub, this change in climate is not positive for the outcome of the bee ecosystem.
Jason Rigby (04:21):
Yeah. And I want people to understand the way that researchers work with data. This is interesting, every problem that's in the world will be solved by data.
Alexander McCaig (04:33):
All of it.
Jason Rigby (04:35):
And go ahead and speak to that because I want people to understand this is why your data is so important.
Alexander McCaig (04:41):
Yeah. So what's a really good old school example for data?
Jason Rigby (04:48):
For data? Oh, I saw a biography from Hershey, the guy that invented Mr. Hershey.
Alexander McCaig (04:55):
Oh, I was going very scientific. But yeah, tell me about the Hershey one. Yeah.
Jason Rigby (04:58):
So you have a lot of variables to make a Hershey's milk chocolate bar. There's a lot of different ingredients in there. There's cocoa, and so now you have a [crosstalk 00:05:10].
Alexander McCaig (05:10):
And all this other stuff. Yeah.
Jason Rigby (05:11):
Yeah, exactly. Yeah, unique fats. And everybody loves chocolate, but you have a... It's a complex system to get that bar to the grocery store or convenience store.
Alexander McCaig (05:23):
Yeah, without it melting and losing form.
Jason Rigby (05:25):
And the more data that they have in these process, the more efficient that they can be. Because like Kroger and all these other Walmart, they're running on razor thin margins.
Alexander McCaig (05:36):
Yeah.
Jason Rigby (05:37):
So it's the same way with candy.
Alexander McCaig (05:39):
You don't have any loss in the things that you're purchasing and having to store on a shelf, where it's stored, temperature in the store, all of this other stuff, how it affects your product, what that shelf life looks like. And then that's one thing you can solve with data, right? Is from that economic sense. Another one just as a local example, is when they were doing the first nuclear testing here, at the Trinity test site, which is further West of Socorro here in New Mexico, near Pie Town.
Jason Rigby (06:05):
I love that.
Alexander McCaig (06:06):
Yeah. So they really didn't have any data when they were going to drop this thing. They said, "Listen, when this blows up, it can either be a, essentially a concentrated chain reaction where it stops at a specific point, when we split these atoms, or this thing just keeps going and we literally rip a hole in the universe." Because it just starts splitting atoms and then just like everything just turns into one super nuke, right? Earth is a super nuke, the solar system turns into a super nuke. You know what I mean? If you can picture that.
Jason Rigby (06:38):
This is a risk.
Alexander McCaig (06:40):
It was a risk. And there was an unknown that needed to be solved. And the only way they could solve it was with data. And so they had all these different recording instruments that are sitting around here. So most of us operate on a hunch and these guys are operating on a hunch in doing the Manhattan Project with a nuclear bomb. They were totally unsure about the science. So when they were moving into a new future, a new way of science of nuclear technology, it's like, okay, well, the only way to solve for that unknown is to test, to acquire as much data as possible. So that when we come back, we can refine our processes and we don't have to be insane about this super nuke idea that we're ripping a hole in the universe.
Alexander McCaig (07:20):
So the bomb goes off and they're like, "Well, that was a plus. It was way bigger than we expected, but it was a sustained a chain reaction." It stopped at a specific point. It didn't just become critical and stay critical forever. And so through that, they acquired telemetry data, ground readings, air quality, light, heat, everything that was going on in the environment and things that were disturbed within that environment.
Alexander McCaig (07:48):
And then, then they went back through their scientific process and solved how they were going to expand upon that technology. And it's really interesting that they did make something, abit negative, a bomb, but from that, a lot of great things were learned.
Jason Rigby (08:01):
It's always that way.
Alexander McCaig (08:01):
There's been huge developments in technology. It'd be nice if we had the inverse, we were just making good things with it rather than-
Jason Rigby (08:06):
Yeah, lets make some clean energy.
Alexander McCaig (08:08):
Rather than a weapon first.
Jason Rigby (08:09):
Right.
Alexander McCaig (08:11):
But there's this, it's really interesting... And climate models. There are some incredible climate models that have been developed because of nuclear testing for above ground explosions. I had a professor that specialized that back in the day and it was quite interesting to learn about how they actually do those readings when you don't have... You have the surface of the earth.
Alexander McCaig (08:26):
So there's a couple of ways you can blow a nuke up. Okay. You can blow it up in the air, you can blow it up when it hits the surface, or you can blow it up underground. And all those are going to have different sort of reactions. And what have you, I'm not a nuclear physicist here. But the general idea is that there's different data inputs and outputs that are happening. Okay, here's our bomb. This is how much stuff we put into it with our data. What's our proposed outcome going to be? And through the analysis of a greater amount of data, they created efficiencies in their processes and they could solve for what was going on to make sure that, "Okay, now we know what our safety measure is."
Alexander McCaig (08:58):
So whether or not you're building a Hershey's bar or building a nuke, the data is going to help you understand what those margins of safety might be. Margins of economics, margins of the effect, especially systemic effects when you're talking about something like a nuclear chain reaction. So if you're saying, why is data so important for solving these problems? Well, data is absolutely fundamental to solving everything and they were doing this really before anything was really digital, at quite analog readings that they have, the clicking Geiger counter and stuff like that.
Alexander McCaig (09:23):
That's stuff's not digital. It's just a little bar that's moving back and forth. And it's telling you the reading as like these radioactive particles are moving through this metal rod, because that's what they do. But that stuff was all analog. Nothing's really changed. Go back to early war wartime commanders, right, during the Greco-Roman period, they had a board on a table and they're like moving huge chess pieces, but that's their data.
Alexander McCaig (09:44):
They send a scout out, but today we have GPS stuff or we can go ask someone through our decentralized systems or send them a message on WhatsApp to get an idea of what's happening somewhere else. Nothing has really changed, it's just the medium change. And now we have the ability to exchange that data quicker, assimilate it in a better format, and then analyze it more efficiently, more so than we could have ever done in some sort of analog format. So when we fundamentally look at this, whether it's bees, Hershey's kisses, nuclear bombs, or you're a Greco-Roman soldier, data is fundamental to the success of just about everything.
Jason Rigby (10:16):
Yeah. And these researchers, they analyzed 14 years of United States Geological Survey data to find the set of wild bees concurrences. And they did it in more than a thousand locations in Maryland, Delaware and Washington D.C.
Alexander McCaig (10:32):
And thank you for letting me rant.
Jason Rigby (10:34):
No.
Alexander McCaig (10:34):
And so for these-
Jason Rigby (10:35):
I always enjoy those.
Alexander McCaig (10:36):
For these models, here specifically what they're trying to do is they're trying to get the most amount of data. So it's like, what is the historical track record? So we need a huge time value, and then we need the highest volume possible within that time.
Jason Rigby (10:50):
Right.
Alexander McCaig (10:50):
Because then you start to get frequency. And through that frequency, you can be like, "Okay, now I have now have indicators across time and volume." And so it's anything, it's like analyzing the stock market at that point, because that's how linear time is. They're trying to take these linear things, put them together and put it into our three-dimensional world, which doesn't really make much sense. But anyway, that is the focus here and for a great period of time, because our big data models have lacked.
Alexander McCaig (11:15):
And the fundamental idea of how we do research has lacked kind of that primary source value in the ability to take data right now, very up-to-date data, we rely on historical things to kind of say, "Well, how do we extrapolate that to see what our future looks like?" But so many things are different every day. If someone was watching our podcast, right? We used to sit at a little tiny table, no TV, no bookshelves, no nothing, no cameras, and then all of a sudden you would have had no historical data from all the episodes we had. And then all of a sudden, the table shows up, beautiful arms, new microphones, TV, all this other stuff, like what's going on? It's a complete outlier.
Alexander McCaig (11:52):
So the ability for us to tell with our big data there's so many errors because you don't really know at the fundamental level, especially whether the bee has consciousness, right? You're strictly observing. So when it comes to data research and you're doing it from only an observational format, as like a third party and not getting primary data, you're just going to do whatever you can to get the most amount of information possible, because they think that's what's going to normalize that curve.
Jason Rigby (12:18):
Yeah. And one of the things that they found, and you brought this up, was more, and so this is why it's so important to have the right data and not be dogma about the data.
Alexander McCaig (12:30):
Dogmatic?
Jason Rigby (12:30):
Dogmatic. Because we could push it and say, "You just got to stop building houses." But like you had said, the houses are no concern. The spring bees, the issue is, too much rain. So we don't create enough spring bees. And then you raise the temperature of course, you're going to have less flowers.
Alexander McCaig (12:48):
Consider, in the cities how they do those green roofs?
Jason Rigby (12:50):
Mm-hmm (affirmative).
Alexander McCaig (12:51):
Well, okay. Now if you replace somewhat of that green scape that hadn't been there or it was totally nonexistent with something, but that doesn't help the bees, because it's still too damn hot for them to be up there.
Jason Rigby (13:02):
Yeah.
Alexander McCaig (13:03):
The flowers are crippled by the albedo and the heat coming off the ground and it causes their flowers to wilt, there's nothing of value. Or maybe it's in an area like Seattle where it's just too much perpetual rain, nothing can grow. It's damning everything down. It's like a farm field that gets flooded in India. Like what are you going to do? I had a great crop season, but people are like, "Oh, you could have watered your crops." Well, too much water inhibits growth.
Alexander McCaig (13:26):
When you step out of that world of balanced Jason, which is what we talk about, that climate stability, not so much climate change, but when you move out of that state of stability, that's when things get out of whack and what may seem positive, is really, it needs a little bit more of the negative, right? So if it's too hot, you actually need more cold, because you got to level it out, because that's better than the equilibrium of the flora and fauna within that local ecosystem from Washington DC, the rest of Maryland, and I don't know where else they did that study.
Jason Rigby (13:57):
Yeah. Whenever you look at climate stability, and so we're looking at here, we see warmer winters, hotter summers.
Alexander McCaig (14:05):
Yeah.
Jason Rigby (14:06):
And now we're, as we see global warming continue to wreak havoc on the world, and it's kind of like, you can boil a frog, and you just slowly start turning up the heat. And the next thing you know, he's boiled.
Alexander McCaig (14:20):
I've never pulled a frog.
Jason Rigby (14:21):
I never have either.
Alexander McCaig (14:21):
I boiled a lobster.
Jason Rigby (14:22):
But analogy is that way. Yeah.
Alexander McCaig (14:24):
I boiled a lobster.
Jason Rigby (14:24):
And you just go slow, slow, slow, slow. And then next thing you know, boom, they're cooked. And I think because in this world of fast food and quick, quick, quick, we don't see dramatic changes, but 40 years from now, 50 years from now, 70 years from now, now we have a world that is beyond repair.
Alexander McCaig (14:43):
Yeah. And you don't want to get to that point, because then you're screwed.
Jason Rigby (14:48):
Yeah. I don't want to leave my grandkids with a world that is apocalyptic.
Alexander McCaig (14:54):
What is the word I came up with? And I'm going to submit to Merriam Webster? Kyrosis.
Jason Rigby (14:59):
Yes.
Alexander McCaig (15:00):
So I just want to explain, I'm going to bring this up because I thought this was pretty good. So Kyrosis, is an adjective. Mind you, you're not going to find this online, I created this word. Hopefully it comes online sometime. And I said, it's a state of dis-ease, when an individual or collective of individuals are faced with a moment of difficult decision and look back in wanting to of choosing an earlier moment in time to solve their eminent problem, after a realization that it is too late. We don't want that.
Jason Rigby (15:30):
No.
Alexander McCaig (15:30):
We don't want to say... We don't want to look at the oblivion when the earth is like so hot, so dry, lacking its moisture, lacking the ability to support us. And that's when we wake up, because we're only at that short-sighted chance of moment, when you're only 15 feet from oblivion. I'd rather be 70 years away from it, a thousand years away from oblivion and pay attention then, rather than stand here 15 feet away and look back and like, "Oh, you guys remember that moment that passed when we should have done this?" Crap. And that's what that state... And then you become in a state of dis-ease.
Jason Rigby (16:03):
Right.
Alexander McCaig (16:04):
Because you're only focusing on the anxiety and the fear of what's very eminent and absolutely going to happen. We don't want to get there.
Jason Rigby (16:11):
No.
Alexander McCaig (16:11):
Okay. And that's why it's so important for us to focus on these things and talk about them to remove the bullshit, remove the bias, remove the dogmas, remove the untruths, and just look at the data for what it is and accept that truthful data, because that's the thing that's going to solve that problem. I don't want us to be a Kyrosis office of human society. All right, this is very important. So talking about a bumblebee or figuring out whether or not someone's going to have fast food tomorrow and understanding what that effect is systemically, that's going to be solved with data. And it's important that we come together and solve that by sharing that information.
Jason Rigby (16:50):
And it's important to share that information. How would an individual, whether they're in India, whether they're in Russia, Australia, how can they help with using their data to help solve these issues?
Alexander McCaig (17:03):
Yeah. So if you're on TARTLE and you're populating this data towards your preferences, and habits, and identifiable information, and other systems you use online, and talking about what you purchase, all of these things can be collectively analyzed by these people that have these huge resources to analyze these large datasets, these big decision makers so that you with your data are essentially telling them this is where the issue is set. And this is where the solve is. This is how we focus on it. And it's not for you to directly tell them that, "Oh, hey, this is what you should be looking at." It's a function of, now we're giving you the data so you know exactly what to look at.
Jason Rigby (17:44):
Yes.
Alexander McCaig (17:44):
When before they didn't have any of it. So regardless of where you are across the globe, using the TARTLE marketplace, you can share your data towards these specific things, whatever they are, towards a specific business or a specific cause, you name it. Or anonymously, you just want to share as much as possible. All of that is of great benefit because the more and truthful information that is shared globally, the more truthful our society becomes. And the more we move away from things that are untruthful that hinder our evolution and drive us closer to that point of oblivion. Not to get dark on it, but-
Jason Rigby (18:14):
Yeah. Let's get dark, dark mode. YouTube, go to TARTLE on YouTube and subscribe.
Speaker 1 (18:28):
Thank you for listening to TARTLE Cast with your hosts, Alexander McCaig and Jason Rigby, where humanity steps into the future, and source data defines the path, the path. What's your data worth?
