Posts Tagged ‘Nature’


In 1959, Soviet scientists embarked on an audacious experiment to breed a population of tame foxes, a strain of animals that wouldn’t be aggressive or fearful of people.

Scientists painstakingly selected the friendliest foxes to start each new generation, and within 10 cycles they began to see differences from wild foxes – fox pups that wagged their tails eagerly at people or with ears that stayed folded like a dog’s.

This study in animal domestication, known as the Russian farm-fox experiment, might be just a fascinating historical footnote – a quirky corner in the otherwise fraught scientific heritage of Soviet Russia.

Instead, it spawned an ongoing area of research into how domestication, based purely on behavioral traits, can result in other changes – like curlier tails and changes to fur color.

Now, the tools of modern biology are revealing the genetic changes that underpin the taming of foxes of Siberia.

In a new study, published Monday in Nature Ecology & Evolution, scientists used genome sequencing to identify 103 stretches of the fox genome that appear to have been changed by breeding, a first pass at identifying the genes that make some foxes comfortable with humans and others wary and aggressive.

The scientists studied the genomes of 10 foxes from three different groups: the tame population, a strain that was bred to be aggressive toward people and a conventional group bred to live on a farm.

Having genetic information from all three groups allowed the researchers to identify regions of the genome that were likely to have changed due to the active selection of animals with different behaviors, rather than natural fluctuation over time.

Those regions offer starting points in efforts to probe the genetic basis and evolution of complex traits, such as sociability or aggressiveness.

“The experiment has been going on for decades and decades, and to finally have the genome information, you get to look and see where in the genome and what in the genome has been likely driving these changes that we’ve seen – it’s a very elegant experimental design,” said Adam Boyko, an associate professor of biomedical sciences at Cornell University, who was not involved in the study.

While some genetic traits are relatively simple to unravel, the underpinnings of social behaviors aren’t easy to dissect. Behavior is influenced by hundreds or thousands of genes, as well as the environment – and typically behaviors fall on a wide spectrum.

The existence of fox populations bred solely for how they interact with people offers a rare opportunity to strip away some of the other complexity – with possible implications for understanding such traits in people and other animals, too, since evolution may work on the same pathways or even the same genes.

“We’re interested to see what are the genes that make such a big difference in behavior. There are not so many animal models which are good to study genetics of social behavior, and in these foxes it’s such a big difference between tame foxes compared to conventional foxes, and those selected for aggressive behavior,” said Anna Kukekova, an assistant professor at the University of Illinois at Urbana-Champaign, who led the work.

Kukekova and colleagues began studying one very large gene that they think may be linked to tame behavior, called SorCS1. The gene plays a role in sorting proteins that allow brain cells to communicate.

Kukekova is interested in determining what happens if the gene is deleted in a mouse and to search for specific mutations that might contribute to differences in behavior.

Bridgett vonHoldt, an assistant professor of ecology and evolutionary biology at Princeton University, said changes that occurred in foxes “overlap extensively with those observed in the transition of gray wolves to modern domestic dogs.”

She said the study may help dog and fox biologists determine if there are complex behavioral traits under the control of just a few genes.

Recent fox evolution in a domesticated population may seem to have little to do with understanding the genetics of human behavior, but interest in domestication has grown as an area of scientific interest in part because genes involved in behavior in one animal may play a similar role in another.

“One reason why it is interesting is it gives us some insights about us. Humans are domesticated themselves, in a way,” Boyko said.

“We’re much more tolerant of being around other humans than probably we were as we were evolving; we’ve had to undergo a transformation, even relatively recently from the agricultural revolution.”


Researchers found the first known hybrid between a rough-toothed dolphin and a melon-headed whale near Kauai, Hawaii.

Rough-toothed dolphins.

Melon-headed whales.

By Jessie Yeung

Scientists from the Cascadia Research Collective have discovered a rare dolphin-whale hybrid off the coast of Kauai, Hawaii, according to a report published last week.

The marine mammal monitoring program, funded by the US Navy, first spotted the animal in August 2017. The team tagged various species, including commonly seen rough-toothed dolphins and rarer melon-headed whales.
However, researchers soon noticed that one tagged animal that looked a little odd. Although it had a typical melon-headed whale’s dorsal fin shape and dorsal cape, it was also blotchy in pigmentation and had a sloping forehead, more reminiscent of a rough-toothed dolphin.

A genetic sample soon confirmed their suspicions: it was a hybrid of the two species, the first to ever be found.The cross-species hybridization may seem bizarre, but is made possible by the fact that melon-headed whales aren’t actually whales. They belong to the Delphinidae family, otherwise known as oceanic dolphins, which also includes orcas and two species of pilot whales.

It also isn’t the first discovery of hybridization in the family
— there have also been cases of bottlenose dolphin/false killer whale (Pseudorca crassidens) hybrids, known as Wolphins, and common/bottlenose dolphin hybrids.

This is the first confirmed hybrid between rough-toothed dolphins and melon-headed whales. However, though it’s an exciting discovery, researchers point out it is not, as commonly thought, a new species.

“While hybridization can at times lead to new species, most of the time this does not happen,” Cascadia researcher Robin Baird told CNN, pointing that there was only a single hybrid found this time.

Some hybrid animals, such as the mule — a hybrid of a male donkey and female horse — are mostly sterile and therefore cannot propagate easily.

The dolphin-whale hybridization is especially surprising in this region, as a sighting of melon-headed whales had never before been confirmed near the Pacific Missile Range Facility (PMRF) navy base.

The hybrid was only traveling with one companion — a melon-headed whale. This, too was unusual, given that melon-headed whales typically travel in groups of 200-300. The solitary pair were “found associating with rough-toothed dolphins,” the report read.

The odd pair and their closeness to the other dolphins have led the researchers to speculate that the accompanying melon-headed whale is the hybrid’s mother.
The research team will return to Kauai next week, hoping to confirm their theory.

“If we were lucky enough to find the pair again, we would try to get a biopsy sample of the accompanying melon-headed whale, to see whether it might be the mother of the hybrid, as well as get underwater images of the hybrid to better assess morphological differences from the parent species,” said Baird.

The US Navy is required to monitor these species as part of the Marine Mammal Protection Act and the Endangered Species Act.

They do so through the Cascadia Research Collective, which conducts photo identification, genetic analyzes, and acoustic monitoring to determine the abundance of odontocetes, also known as toothed whales.

Motion sensor “camera traps” unobtrusively take pictures of animals in their natural environment, oftentimes yielding images not otherwise observable. The artificial intelligence system automatically processes such images, here correctly reporting this as a picture of two impala standing.

A new paper in the Proceedings of the National Academy of Sciences (PNAS) reports how a cutting-edge artificial intelligence technique called deep learning can automatically identify, count and describe animals in their natural habitats.

Photographs that are automatically collected by motion-sensor cameras can then be automatically described by deep neural networks. The result is a system that can automate animal identification for up to 99.3 percent of images while still performing at the same 96.6 percent accuracy rate of crowdsourced teams of human volunteers.

“This technology lets us accurately, unobtrusively and inexpensively collect wildlife data, which could help catalyze the transformation of many fields of ecology, wildlife biology, zoology, conservation biology and animal behavior into ‘big data’ sciences. This will dramatically improve our ability to both study and conserve wildlife and precious ecosystems,” says Jeff Clune, the senior author of the paper. He is the Harris Associate Professor at the University of Wyoming and a senior research manager at Uber’s Artificial Intelligence Labs.

The paper was written by Clune; his Ph.D. student Mohammad Sadegh Norouzzadeh; his former Ph.D. student Anh Nguyen (now at Auburn University); Margaret Kosmala (Harvard University); Ali Swanson (University of Oxford); and Meredith Palmer and Craig Packer (both from the University of Minnesota).

Deep neural networks are a form of computational intelligence loosely inspired by how animal brains see and understand the world. They require vast amounts of training data to work well, and the data must be accurately labeled (e.g., each image being correctly tagged with which species of animal is present, how many there are, etc.).

This study obtained the necessary data from Snapshot Serengeti, a citizen science project on the platform. Snapshot Serengeti has deployed a large number of “camera traps” (motion-sensor cameras) in Tanzania that collect millions of images of animals in their natural habitat, such as lions, leopards, cheetahs and elephants. The information in these photographs is only useful once it has been converted into text and numbers. For years, the best method for extracting such information was to ask crowdsourced teams of human volunteers to label each image manually. The study published today harnessed 3.2 million labeled images produced in this manner by more than 50,000 human volunteers over several years.

“When I told Jeff Clune we had 3.2 million labeled images, he stopped in his tracks,” says Packer, who heads the Snapshot Serengeti project. “We wanted to test whether we could use machine learning to automate the work of human volunteers. Our citizen scientists have done phenomenal work, but we needed to speed up the process to handle ever greater amounts of data. The deep learning algorithm is amazing and far surpassed my expectations. This is a game changer for wildlife ecology.”

Swanson, who founded Snapshot Serengeti, adds: “There are hundreds of camera-trap projects in the world, and very few of them are able to recruit large armies of human volunteers to extract their data. That means that much of the knowledge in these important data sets remains untapped. Although projects are increasingly turning to citizen science for image classification, we’re starting to see it take longer and longer to label each batch of images as the demand for volunteers grows. We believe deep learning will be key in alleviating the bottleneck for camera-trap projects: the effort of converting images into usable data.”

“Not only does the artificial intelligence system tell you which of 48 different species of animal is present, but it also tells you how many there are and what they are doing. It will tell you if they are eating, sleeping, if babies are present, etc.,” adds Kosmala, another Snapshot Serengeti leader. “We estimate that the deep learning technology pipeline we describe would save more than eight years of human labeling effort for each additional 3 million images. That is a lot of valuable volunteer time that can be redeployed to help other projects.”

First-author Sadegh Norouzzadeh points out that “Deep learning is still improving rapidly, and we expect that its performance will only get better in the coming years. Here, we wanted to demonstrate the value of the technology to the wildlife ecology community, but we expect that as more people research how to improve deep learning for this application and publish their datasets, the sky’s the limit. It is exciting to think of all the different ways this technology can help with our important scientific and conservation missions.”

The paper that in PNAS is titled, “Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning.”,-count,-describe-wild-animals.html

Honeybees can identify a piece of paper with zero dots as “less than” a paper with a few dots. Such a feat puts the insects in a select group—including the African grey parrot, nonhuman primates, and preschool children—that can understand the concept of zero, researchers report June 7 in Science.

“The fact that the bees generalized the rule ‘choose less’ to [blank paper] was consequently really surprising,” study coauthor Aurore Avarguès-Weber, a cognitive neuroscientist the University of Toulouse, tells The Scientist in an email. “It demonstrated that bees consider ‘nothing’ as a quantity below any number.”

In past studies, researchers have shown that bees can count up to five, but whether the insects could grasp more-complex ideas, such as addition or nothingness, has been unclear. In the latest study, Avarguès-Weber and her colleagues tested the bees’ ability to comprehend the absence of a stimulus by first training the insects to consistently choose sheets of paper either with fewer or more dots by landing on a tiny platform near the paper with the dots. If the bees chose correctly, they were rewarded with a sugary drink. The bees performed the task surprisingly well, Avarguès-Weber says. “The fact that they can do it while we were also controlling for potential confounding parameters confirms their capacity to discriminate numbers.”

The team then tested the bees’ ability to distinguish a blank piece of paper, or what the researchers call an empty set, from a sheet with one dot and found the insects chose correctly about 63 percent of the time. The behavior reveals “an understanding that an empty set is lower than one, which is challenging for some other animals,” the researchers write in the paper.

That bees can use the idea of “less than” to extrapolate that nothing has a quantitative nature is “very surprising,” says Andreas Nieder of the University of Tübingen in Germany who was not involved in the study. “Bees have minibrains compared with human brains—fewer than a million neurons compared with our 86 billion—yet they can understand the concept of an empty set.”

Nieder suggests honeybees, similar to humans, may have developed this ability to comprehend the absence of something as a survival advantage, to help with foraging, avoiding predation, and interacting with other bees of the same species. The absence of food or a mate is important to understand, he says.

Clint Perry, who studies bees at Queen Mary University of London and was not involved in the study, is a bit more cautious about the results. “I applaud these researchers. It is very difficult to test these types of cognitive abilities in bees,” he says. “But I don’t feel convinced that they were actually showing that the bees could understand the concept of zero or even the absence of information.” Perry suggests the bees might have selected where to land based solely on the total amount of black or white on each paper and that’s the choice that got rewarded, rather than distinguishing the number of dots or lack of them.

Avarguès-Weber and her colleagues argue, however, that the bees were always rewarded when shown dots. “In the test with zero (white paper) versus an image with a few dots, the bees chose the white picture without any previous experience with such stimulus. A choice based exclusively on learning would consist in choosing an image similar to the rewarded ones, ones presenting dots,” she says.

Perry says he’d like to see better control experiments to confirm the finding, while Nieder is interested in the underlying brain physiology that might drive the how the insects comprehend nothingness. How the absence of a stimulus is represented in the human brain hasn’t been well studied, though it has been explored in individual neurons in the brains of nonhuman primates. It could be even harder to study in bees, because they have much smaller brains, Nieder says. Setting up the experiments to test behavior and record brain activity would be challenging.

Avarguès-Weber and her colleagues propose a solution to that challenge—virtual reality. “We are developing a setup in which a tethered bee could learn a cognitive task as done in free-flying conditions so we could record brain activity in parallel,” she says. The team also plans to test the bees’ potential ability to perform simple addition or subtraction.

S. Howard et al., “Numerical ordering of zero in honey bees,” Science, doi:10.1126/science.aar4975, 2018.

The purpose and evolutionary origins of sleep are among the biggest mysteries in neuroscience. Every complex animal, from the humblest fruit fly to the largest blue whale, sleeps — yet scientists can’t explain why any organism would leave itself vulnerable to predators, and unable to eat or mate, for a large portion of the day. Now, researchers have demonstrated for the first time that even an organism without a brain — a kind of jellyfish — shows sleep-like behaviour, suggesting that the origins of sleep are more primitive than thought.

Researchers observed that the rate at which Cassiopea jellyfish pulsed their bell decreased by one-third at night, and the animals were much slower to respond to external stimuli such as food or movement during that time. When deprived of their night-time rest, the jellies were less active the next day.

“Everyone we talk to has an opinion about whether or not jellyfish sleep. It really forces them to grapple with the question of what sleep is,” says Ravi Nath, the paper’s first author and a molecular geneticist at the California Institute of Technology (Caltech) in Pasadena. The study was published in Current Biology.

“This work provides compelling evidence for how early in evolution a sleep-like state evolved,” says Dion Dickman, a neuroscientist at the University of Southern California in Los Angeles.

Mindless sleep
Nath is studying sleep in the worm Caenorhabditis elegans, but whenever he presented his work at research conferences, other scientists scoffed at the idea that such a simple animal could sleep. The question got Nath thinking: how minimal can an animal’s nervous system get before the creature lacks the ability to sleep? Nath’s obsession soon infected his friends and fellow Caltech PhD students Michael Abrams and Claire Bedbrook. Abrams works on jellyfish, and he suggested that one of these creatures would be a suitable model organism, because jellies have neurons but no central nervous system. Instead, their neurons connect in a decentralized neural net.

Cassiopea jellyfish, in particular, caught the trio’s attention. Nicknamed the upside-down jellyfish because of its habit of sitting on the sea floor on its bell, with its tentacles waving upwards, Cassiopea rarely moves on its own. This made it easier for the researchers to design an automated system that used video to track the activity of the pulsing bell. To provide evidence of sleep-like behaviour in Cassiopea (or any other organism), the researchers needed to show a rapidly reversible period of decreased activity, or quiescence, with decreased responsiveness to stimuli. The behaviour also had to be driven by a need to sleep that increased the longer the jellyfish was awake, so that a day of reduced sleep would be followed by increased rest.

Other researchers had already documented a nightly drop in activity in other species of jellyfish, but no jellyfish had been known to display the other aspects of sleep behaviour. In a 35-litre tank, Nath, Abrams and Bedbrook tracked the bell pulses of Cassiopea over six days and nights and found that the rate, which was an average of one pulse per second by day, dropped by almost one-third at night. They also documented night-time pulse-free periods of 10–15 seconds, which didn’t occur during the day.

Restless night
Without an established jellyfish alarm clock, the scientists used a snack of brine shrimp and oyster roe to try to rouse the snoozing Cassiopea. When they dropped food in the tank at night, Cassiopea responded to its treat by returning to a daytime pattern of activity. The team used the jellyfish’s preference for sitting on solid surfaces to test whether quiescent Cassiopea had a delayed response to external stimuli. They slowly lifted the jellyfish off the bottom of the tank using a screen, then pulled it out from under the animal, leaving the jelly floating in the water. It took longer for the creature to begin pulsing and to reorient itself when this happened at night than it did during the day. If the experiment was immediately repeated at night, the jellyfish responded as if it were daytime. Lastly, when the team forced Cassiopea to pull an all-nighter by keeping it awake with repeated pulses of water, they found a 17% drop in activity the following day.

“This work shows that sleep is much older than we thought. The simplicity of these organisms is a door opener to understand why sleep evolved and what it does,” says Thomas Bosch, an evolutionary biologist at Kiel University in Germany. “Sleep can be traced back to these little metazoans — how much further does it go?” he asks.

That’s what Nath, Abrams and Bedbrook want to find out. Amid the chaos of finishing their PhD theses, they have begun searching for ancient genes that might control sleep, in the hope that this might provide hints as to why sleep originally evolved.

By Sean Quinton

This is a tale of a rabbit, a fox and an eagle — but it’s no bedtime story.

An incredible display of nature unfolded Saturday on San Juan Island as a young fox quickly learned a valuable lesson about the pecking order in the Northwest wilderness.

A fox kit pranced along the prairie of San Juan Island National Historical Park with a rabbit clenched in its jaws, apparently pleased with its catch. Then the predator pauses abruptly, looks up and sees a bald eagle coming its way. The predator becomes the prey.

The fox tumbles and spins, and the eagle swoops to take hold of the rabbit. Both the rabbit and the fox are lifted into the air. The eagle flaps its wings. The fox doesn’t give up right away, flailing its young legs.

But the bird is too much for the red fox, which lets go of the rabbit and falls twirling back to the ground. The bird of prey won the battle.

The eight-second spectacle was captured on video.

Zachary Hartje was shooting photos when he anticipated what was about to happen in the prairie. He switched his camera to video mode.

“I was totally shocked,” he said. “No one I had ever talked to had ever seen anything like that.”

Hartje recently graduated from Gonzaga University and goes to the San Juan Islands several times a year to film and photograph the foxes there.

“It was a baby fox, so it might’ve been its first kill,” he said. “The fox just ran away into the den after. It looked pretty scared.”

Another photographer, Kevin Ebi, was also there to watch the fox kits.

“When I heard the bald eagle calling, I knew exactly what was going to happen,” Ebi said, who posted his photos to his blog, “I knew it wanted that rabbit.”

“After I saw the eagle finally drop the fox … I thought, ‘This is one of the most incredible things I’ve ever seen.’ “

Ebi said he has photographed eagles for years. He even published a book called “Year of the Eagle,” which chronicles the life of the Pacific Northwest birds. Even for him, the event was unprecedented.

Ebi said eagles don’t like to expend more calories than they need to get food, so when they see some other animal that’s already done the work of hunting, they might try to swoop in to steal a meal. The behavior is called kleptoparasitism.

Saturday’s confrontation was on another level. “This is the most difficult attempt I’ve ever seen and it’s extremely uncommon,” Ebi said.

The fox appeared to escape without injury, but next time it might think twice before taking its prey across the prairie.

Large boulders 2 metres across and weighing 10 tonnes could soon begin blasting out from Kilauea, the erupting volcano on Hawaii’s Big Island. But the biggest imminent threat to residents could arise if the volcano starts spewing ash to heights of 6000 metres or more.

The conditions are similar to those when Kilauea last erupted in 1924, which showered the island in ash for several months. “That’s what I would guess will happen next,” said Don Swanson of the Hawaiian Volcano Observatory, in a press conference video issued on 9 May.

Kilauea has been unusually active since late April. On 30 April, the floor of the lava lake at the volcano’s summit collapsed.

The lava has been draining ever since. By 9 May, and following a 6.9-magnitude earthquake on 3 May, it had already plunged almost 300 metres into the vertical shaft below. The lava is now below the level of water-saturated rock at 600 metres above sea level. “Since the earthquake, the lava lake has dropped in a very steady manner, at 2.2 metres per hour,” said Swanson.

Steam explosions

Because the lava has sunk so low, water is now draining into the empty shaft that it previously occupied. The walls of the crater are red hot, so the water is instantly turning to steam, which is now bellowing in white clouds from the volcano summit.

What happens next is difficult to predict, said Swanson. But there could be explosions. If large rocks fall from the unstable walls of the shaft, they could block it, in which case pressure from steam will build up underneath and cause an explosion.

Once the “plug” is blown out, the steam can escape again unimpeded, until the plug is restored by rock falls.

The result would be a series of explosions followed by hiatuses. That’s what happened in 1924: there were 60 explosions over the course of four months or so.

Boulders and ash

Any explosion can produce a variety of “ejecta”, said Swanson. “You can get rocks ejected like cannonballs, weighing up to 10 tonnes and 2 [metres] in diameter,” he said.

The good news is that these boulders should fall within about a kilometre of the summit. This area is deserted. Smaller rocks the size of softballs could impact a bit further away, albeit still not far enough to reach people’s homes. But tinier fragments a fraction of an inch wide could reach peopled areas. “They would sting, but not be lethal,” says Swanson.

The most important hazard is fine ash, which can block thoroughfares and accumulate on buildings. In 1924, ash landed on railway tracks and made them too slippery for trains to run on safely.

“It’s a nuisance, especially if it goes on for several weeks,” said Tina Neal of the Hawaiian Volcano Observatory at the press conference. “I’ve been in many ash falls myself, and the most difficult bit is keeping it out of your eyes.”

Meanwhile, lava fountains and steam continue to spew copiously from cracks on the island, reaching heights of 30 metres. By Monday, there were 19 fissures in total. So far, more than 30 properties have been destroyed by lava, and 2000 residents remain evacuated.