‘Shocking’ die-off of Africa’s oldest baobabs

AFP reports:

Some of Africa’s oldest and biggest baobab trees — a few dating all the way back to the ancient Greeks — have abruptly died, wholly or in part, in the past decade, researchers said Monday.

The trees, aged between 1,100 and 2,500 years and some as wide as a bus is long, may have fallen victim to climate change, the team speculated.

“We report that nine of the 13 oldest… individuals have died, or at least their oldest parts/stems have collapsed and died, over the past 12 years,” they wrote in the scientific journal Nature Plants, describing “an event of an unprecedented magnitude.”

“It is definitely shocking and dramatic to experience during our lifetime the demise of so many trees with millennial ages,” said the study’s co-author Adrian Patrut of the Babes-Bolyai University in Romania.

Among the nine were four of the largest African baobabs.

While the cause of the die-off remains unclear, the researchers “suspect that the demise of monumental baobabs may be associated at least in part with significant modifications of climate conditions that affect southern Africa in particular.” [Continue reading…]

Bees may understand zero, a concept that took humans millennia to grasp

Kate Keller writes:

As a mathematical concept, the idea of zero is relatively new in human society—and indisputably revolutionary. It’s allowed humans to develop algebra, calculus and Cartesian coordinates; questions about its properties continue to incite mathematical debate today. So it may sound unlikely that bees—complex and community-based insects to be sure, but insects nonetheless—seem to have mastered their own numerical concept of nothingness.

Despite their sesame-seed-sized brains, honey bees have proven themselves the prodigies of the insect world. Researcher has found that they can count up to about four, distinguish abstract patterns, and communicate locations with other bees. Now, Australian scientists have found what may be their most impressive cognitive ability yet: “zero processing,” or the ability to conceptualize nothingness as a numerical value that can be compared with more tangible quantities like one and two.

While seemingly intuitive, the ability to understand zero is actually quite rare across species—and unheard of in invertebrates. In a press release, the authors of a paper published June 8 in the journal Science called species with this ability an “elite club” that consists of species we generally consider quite intelligent, including primates, dolphins and parrots. Even humans haven’t always been in that club: The concept of zero first appeared in India around 458 A.D, and didn’t enter the West until 1200, when Italian mathematician Fibonacci brought it and a host of other Arabic numerals over with him.

But animal cognition researchers at the RMIT University of Melbourne, Monash University in Clayton, Australia and Toulouse University in France had a hunch that honey bees might just be one of the few species able to grasp the concept. Despite the fact that they have fewer than one million neurons in their brain—compared to 86,000 million in a human brain—the team recognized their cognitive potential. [Continue reading…]

What enabled animal life to get more complex and diverse during the Cambrian explosion?

Jordana Cepelewicz writes:

When Emma Hammarlund of Lund University in Sweden first reached out to her colleague Sven Påhlman for help with her research, he was skeptical he’d have much insight to offer. He was a tumor biologist, after all, and she was a geobiologist, someone who studied the interplay between living organisms and their environment. Påhlman didn’t see how his work could possibly inform her search for answers about the rapid proliferation and diversification of animal life that, half a billion years ago, forever changed Earth’s evolutionary landscape.

In spite of Påhlman’s initial reservations, however, the pair has collaborated over the past four years to put forth a new interdisciplinary hypothesis, published in Nature Ecology & Evolution earlier this year, explaining why it took so long for animals to burst onto the scene.

For most of its 4.5-billion-year history, Earth has sustained life — but that life was largely limited to microbial organisms: bacteria, plankton, algae. Not until about 540 million years ago did larger, more complex species begin to dominate the oceans, but within just a few tens of millions of years (a blip on the evolutionary timescale), the planet had filled up with all kinds of animals. The fossil record from that period shows the beginnings of almost all modern animal lineages: animals with shells and animals with spines, animals that swam and animals that burrowed, animals that could hunt and animals that could defend themselves from predators.

Like many biologists, Hammarlund wondered why it took so long for complex animals to emerge — and why, when they finally did, it happened so suddenly. One of the leading theories about this hotly debated question holds that a skyrocketing rise in atmospheric oxygen around that time triggered what’s known as the Cambrian explosion. Earlier, when oxygen was scarce, the simple animals in the seas had anaerobic metabolisms that did not depend on it, and they even found oxygen problematic if not toxic. By shifting to aerobic respiration, however, animals gained an enormous metabolic advantage because the amount of energy that cells could produce per respiration cycle increased nearly twentyfold. That extra energy may have been what powered the greater complexity witnessed during the Cambrian period: increased biomass, improvements in their cellular systems, more complex body structures, and the capacity for energy-intensive movement and predation. [Continue reading…]

Theory of predictive brain as important as evolution — an interview with Lars Muckli

Our brains make sense of the world by predicting what we will see and then updating these predictions as the situation demands, according to Lars Muckli, professor of neuroscience at the Centre for Cognitive Neuroimaging in Glasgow, Scotland. He says that this predictive processing framework theory is as important to brain science as evolution is to biology.

Horizon magazine: You have used advanced brain imaging techniques to come up with a model of how the brain processes vision – and it says that instead of just sorting through what we see, our brains actually anticipate what we will see next. Could you tell us a bit more?

Lars Muckli: ‘We are interested to understand how the brain supports vision. A classical view had been that the brain is responding to visual information in a cascade of hierarchical visual areas with increasing complexity, but a more modern way is to realise that, actually, the brain is not meeting every situation with a clean sheet, but with lots of predictions.’

How does that work?

‘The main purpose of the brain, as we understand it today, is it is basically a prediction machine that is optimising its own predictions of the environment it is navigating through. So, vision starts with an expectation of what is around the corner. Once you turn around the corner, you are then negotiating potential inputs to your predictions – and then responding differently to surprise and to fulfilment of expectations.

‘So that’s what’s called the predictive processing framework, and it’s a proposed unifying theory of the brain. It’s basically creating an internal model of what’s going to happen next.’

Why does this happen?

‘First of all, the outside world is not in our brain so somehow we need to get something into our brain that is a useful description of what’s happening – and that’s a challenge.

‘We become painfully aware of this challenge if we try to simulate this in a computer model – how do we get information about the outside world into a computer model? The brain does that in an unsupervised way. It segments the visual input into object, background, foreground, context, people and so on, and no one ever gives the brain any kind of supervision to do so.

‘To have meaningful models of the world, you need to have something like a supervisor in your brain that says: “This is Object A. This is another object, and you need to find a name for this.” We don’t have a supervisor, but we have something – and that’s the currency of surprise. (The need) to minimise surprise is used as a supervisor.’

[Read more…]

China-backed Sumatran dam threatens the rarest ape in the world

By Bill Laurance, James Cook University

The plan to build a massive hydropower dam in Sumatra as part of China’s immense Belt and Road Initiative threatens the habitat of the rarest ape in the world, which has only 800 remaining members.

This is merely the beginning of an avalanche of environmental crises and broader social and economic risks that will be provoked by the BRI scheme.

Read more:
How we discovered a new species of orangutan in northern Sumatra

The orangutan’s story began in November 2017, when scientists made a stunning announcement: they had discovered a seventh species of Great Ape, called the Tapanuli Orangutan, in a remote corner of Sumatra, Indonesia.

In an article published in Current Biology today, my colleagues and I show that this ape is perilously close to extinction – and that a Chinese-sponsored megaproject could be the final nail in its coffin.

Forest clearing for the Chinese-funded development has already begun.
Sumatran Orangutan Society

[Read more…]

We reconstructed the genome of the ‘first animal’

File 20180502 153908 1choet4.jpg?ixlib=rb 1.1


By Jordi Paps, University of Essex

The first animals emerged on Earth at least 541m years ago, according to the fossil record. What they looked like is the subject of an ongoing debate, but they’re traditionally thought to have been similar to sponges.

Like today’s animals, they were made up of many, many different cells doing different jobs, programmed by thousands of different genes. But where did all these genes come from? Was the emergence of animals a small step in evolution, or did it represent a big leap in the DNA that carries the instructions for life?

To answer these questions and more, my colleague and I have reconstructed the set of genetic instructions (a minimal genome) present in the last common ancestor of all animals. By comparing this ancestral animal genome to those of other ancient lifeforms, we’ve shown that the emergence of animals involved a lot of very novel changes in DNA. What’s more, some of these changes were so essential to the biology of animals that they are still found in most modern animals after more than 500m years of independent evolution. In fact, most of our own genes are descended from this “first animal”.

Previous research on lifeforms that are closely related to animals – single-celled organisms such as choanoflagellates, filastereans and ichthyosporeans – has shown they share many genes with their animal cousins. This means that these genes are older than animals themselves and date back to some common ancestor of all these creatures. So the recycling of old genes into new functions, a kind of genome tinkering, must have been an important force in the origin of animals.

But Professor Peter Holland and I wanted to find out which new genes emerged when animals evolved. We used sophisticated computer programs to compare 1.5m proteins (the molecules that genes contain the instructions for) across 62 living genomes, making a total of 2.25 trillion comparisons to find out which genes are shared between different organisms today.

[Read more…]

Person of the forest

Why the human brain is so efficient

Liqun Luo writes:

An important difference between the computer and the brain is the mode by which information is processed within each system. Computer tasks are performed largely in serial steps. This can be seen by the way engineers program computers by creating a sequential flow of instructions. For this sequential cascade of operations, high precision is necessary at each step, as errors accumulate and amplify in successive steps. The brain also uses serial steps for information processing. In the tennis return example, information flows from the eye to the brain and then to the spinal cord to control muscle contraction in the legs, trunk, arms, and wrist.

But the brain also employs massively parallel processing, taking advantage of the large number of neurons and large number of connections each neuron makes. For instance, the moving tennis ball activates many cells in the retina called photoreceptors, whose job is to convert light into electrical signals. These signals are then transmitted to many different kinds of neurons in the retina in parallel. By the time signals originating in the photoreceptor cells have passed through two to three synaptic connections in the retina, information regarding the location, direction, and speed of the ball has been extracted by parallel neuronal circuits and is transmitted in parallel to the brain. Likewise, the motor cortex (part of the cerebral cortex that is responsible for volitional motor control) sends commands in parallel to control muscle contraction in the legs, the trunk, the arms, and the wrist, such that the body and the arms are simultaneously well positioned to receiving the incoming ball.

This massively parallel strategy is possible because each neuron collects inputs from and sends output to many other neurons—on the order of 1,000 on average for both input and output for a mammalian neuron. (By contrast, each transistor has only three nodes for input and output all together.) [Continue reading…]

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Only a tiny fraction of the genes inside our bodies are human

James Gallagher writes:

Prof Rob Knight, from University of California San Diego, told the BBC: “You’re more microbe than you are human.”

Originally it was thought our cells were outnumbered 10 to one.

“That’s been refined much closer to one-to-one, so the current estimate is you’re about 43% human if you’re counting up all the cells,” he says.

But genetically we’re even more outgunned.

The human genome – the full set of genetic instructions for a human being – is made up of 20,000 instructions called genes.

But add all the genes in our microbiome together and the figure comes out between two and 20 million microbial genes.

Prof Sarkis Mazmanian, a microbiologist from Caltech, argues: “We don’t have just one genome, the genes of our microbiome present essentially a second genome which augment the activity of our own.

“What makes us human is, in my opinion, the combination of our own DNA, plus the DNA of our gut microbes.” [Continue reading…]

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Burning coal may have caused Earth’s worst mass extinction

Dana Nuccitelli writes:

Recently, geologist Dr Benjamin Burger identified a rock layer in Utah that he believed might have formed during the Permian and subsequent Triassic period that could shed light on the cause of the Great Dying [the Earth’s deadliest mass extinction 252 million years ago].

During the Permian, Earth’s continents were still combined as one Pangea, and modern day Utah was on the supercontinent’s west coast. Samples from the end-Permian have been collected from rock layers in Asia, near the volcanic eruptions, but Utah was on the other side of Pangaea. Burger’s samples could thus provide a unique perspective of what was happening on the other side of the world from the eruptions. Burger collected and analyzed samples from the rock layer, and documented the whole process in a fascinating video:


Burger’s samples painted a grim picture of Earth’s environment at the end of the Permian period. A sharp drop in calcium carbonate levels indicated that the oceans had become acidic. A similar decline in organic content matched up with the immense loss of life in the oceans during this period. The presence of pyrite pointed to an anoxic ocean (without oxygen), meaning the oceans were effectively one massive dead zone.

Bacteria ate the oversupply of dead bodies, producing hydrogen sulfide gas, creating a toxic atmosphere. The hydrogen sulfide oxidized in the atmosphere to form sulfur dioxide, creating acid rain, which killed much of the plant life on Earth. Elevated barium levels in the samples had likely been carried up from the ocean depths by a massive release of methane.

Levels of various metals in the rock samples were critical in identifying the culprit of this mass extinction event. As in end-Permian samples collected from other locations around the world, Burger didn’t find the kinds of rare metals that are associated with asteroid impacts. There simply isn’t evidence that an asteroid struck at the right time to cause the Great Dying.

However, Burger did find high levels of mercury and lead in his samples, coinciding with the end of the Permian period. Mercury has also been identified in end-Permian samples from other sites. Lead and mercury aren’t associated with volcanic ash, but they are a byproduct of burning coal. [Continue reading…]

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