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The Invasive Species That Couldn’t Invade

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Wikimedia Commons

The red shiner is just a few inches long, and has no big scary fangs, no claws, no stinger, and no poisonous spines. The little minnow probably isn’t an animal that would ever strike fear in anyone’s heart, but it’s a fierce conqueror. 

In fact, on paper, they seem like the perfect invasive species. They can live and reproduce almost anywhere, tolerate extreme conditions like high-temperature and low-oxygen water, eat almost anything, grow rapidly, and produce large numbers of young. And sure enough, after accidental releases from bait farms, they’re now found in a dozen states outside their native range. In their conquered territory, shiners are considered a serious threat to native species because they displace and outcompete them, prey on their young, introduce tapeworms and other parasites, and dilute gene pools through hybridization. 

All this suggests that red shiners should be able to go wherever they please. But for some reason, they can’t go back home. 

The shiner is native to a broad swath of the Mississippi River basin and, for almost half a century, was abundant in the creeks that fed into Lake Texoma in southern Oklahoma. Over the last few decades, though, they’ve all but disappeared there. Populations that used to number in the hundreds in the 1980s dropped to just single digits in the late '90s and early 2000s. 

This doesn’t seem to be for lack of effort on the minnows' part, though, and surveys from recent years showed a mysterious pattern of reappearance and disappearance. After severe flooding in the area in the summer of 2007, previously impassable stretches of dry land were re-watered and the minnows re-colonized their old stomping grounds. In June 2009, researchers found 81 shiners in one of the creeks. Two months later, there were only four. By November, there was just one. Then that was gone, too. Just as quickly as they settled in, the fish disappeared again. 

The minnows were still abundant in other nearby streams, though, so the problem didn’t appear to be a total loss of the species in the area. It was just this handful of creeks that they couldn’t get a foothold in. 

They say you can never go home again, and it looked like the shiners would agree. The little minnow that couldn’t presented scientists with a natural paradox, one that turned the standard invasive species narrative on its head. Why, biologists wondered, despite their abundance, tolerance of harsh conditions and invasiveness, couldn’t the fish re-invade the creeks they’d come from?

To find out what had locked the shiners out, University of Oklahoma zoologists Edie Marsh-Matthews, William Matthews, and Nathan Franssen decided to watch a shiner homecoming unfold. They built an artificial stream that mimicked the conditions and native fish populations of Brier Creek, where the shiners were losing the most ground after re-invasion. 

After the other fish—which included stonerollers, bigeye shiners, blackstripe topminnows and green sunfish—had time to establish themselves, the shiners were thrown into the mix in a mock invasion. At first, they seemed right at home. They were healthy, they ate well and the males chased and circled the females in the shiner equivalent of courting. By the end of the experiments, though, only 20 percent of the invaders survived. Even in a fake stream, they’d failed again. 

The three scientists searched for reasons for the die-off, but couldn’t find anything. They’d stocked enough shiners at the start of the experiment. The water chemistry looked fine. The filters were clean. The algae cover was ideal. Shiners had successfully reproduced and raised young and thrived in similar experiments when housed alone, so maybe the problem was one of the other fish. 

The researchers found that the more adult sunfish there were in the stream during the experiments, the fewer shiners they wound up with in the end. The sunfish didn’t seem like likely suspects at first glance. They’d been stocked at the start of the experiment as small juveniles, hardly anything to worry about, and no one directly saw them preying on the shiners. But sunfish grow quickly, and by the end of the study, they were significantly larger and could pose a serious threat to the invaders.

Death-by-sunfish fit the timeline for what was happening in the wild, too. A group of invading red shiners, swimming into the creeks during spring and summer floods, would encounter juvenile sunfish that primarily eat insects. Given a summer to grow, the larger sunfish would start mixing small fish into their diet right around the time when the survey noted the shiners disappearing. 

The shiners’ failure to reinvade looks like just a matter of being in the wrong place at the wrong time. They’d come home again just before they would get added to their neighbors’ menu. Their behavior doesn’t help, either. In the experiments, the shiners tended to swim at midwater where sunfish hunt, and engaged in less defensive behavior in the face of danger. The small native fish like the bigeye shiners, on the other hand, mostly swam closer to the surface and stayed in parts of the stream that were too shallow for the larger predators. 

As destructive as invasive species can be, the shiners show that even an invader can sometimes be an underdog.

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iStock // Ekaterina Minaeva
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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
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iStock // Ekaterina Minaeva

Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

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iStock
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Here's How to Change Your Name on Facebook
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iStock

Whether you want to change your legal name, adopt a new nickname, or simply reinvent your online persona, it's helpful to know the process of resetting your name on Facebook. The social media site isn't a fan of fake accounts, and as a result changing your name is a little more complicated than updating your profile picture or relationship status. Luckily, Daily Dot laid out the steps.

Start by going to the blue bar at the top of the page in desktop view and clicking the down arrow to the far right. From here, go to Settings. This should take you to the General Account Settings page. Find your name as it appears on your profile and click the Edit link to the right of it. Now, you can input your preferred first and last name, and if you’d like, your middle name.

The steps are similar in Facebook mobile. To find Settings, tap the More option in the bottom right corner. Go to Account Settings, then General, then hit your name to change it.

Whatever you type should adhere to Facebook's guidelines, which prohibit symbols, numbers, unusual capitalization, and honorifics like Mr., Ms., and Dr. Before landing on a name, make sure you’re ready to commit to it: Facebook won’t let you update it again for 60 days. If you aren’t happy with these restrictions, adding a secondary name or a name pronunciation might better suit your needs. You can do this by going to the Details About You heading under the About page of your profile.

[h/t Daily Dot]

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