There are many things we take for granted in modern life, skills that humanity developed over literally hundreds of thousands of years, but also many modern conveniences that are fairly recent. One is food storage – saving food for later consumption.

We began as hunter-gatherers, a lifestyle that involves mostly consuming food right as it is acquired. This creates times of feast and famine, but little consistency or predictability. Without refrigeration and other techniques of food preservation, most foods would not last long. Cooked meat, gathered fruits might last a few days, while nuts and roots might last a bit longer. But that was about it.

Agriculture led to a significant increase in our control over our food supply. We could now store food as dried grains for months. As we cultivated crops, some were selected for storing well. Some hard-skinned squash, for example, can keep for several months. Cheese was a huge discovery, preserving milk calories also for months. Domesticated animals could be “preserved” indefinitely, and then slaughtered when needed. Salting, pickling, smoking, and curing were discovered over time as methods of preserving various foods. Industrialization eventually allowed for things like canning and, of course, refrigeration.

But what was the oldest and first example of humans preserving food for later consumption? Archaeologists think they have discovered it – researchers from Tel Aviv report the finding from Qesem Cave, a paleolithic human settlement from 400,000 years ago. They found evidence that the people living there would preserve deer and other bones for potentially up to 9 weeks, and then break them open to eat the marrow.

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Have you ever traveled with a large group of friends? When a group gets beyond a certain “critical mass” it becomes geometrically more difficult to make decisions. Even going to a restaurant or a movie become laborious. Decision making seems to break down in large groups, especially if there isn’t an established hierarchy or process in place. That’s why the “by committee” cliche exists – group decision making can be a highly flawed and problematic process.

I can’t escape the nagging sensation that the world is having this problem. We seem to be politically frozen and unable to take decisive timely action. We are metaphorically driving toward a cliff, and we can’t even take our foot off the accelerator, let alone apply the brakes.

I am talking, of course, about climate change. The World Meteorological Organization (WMO) compiled data in preparation for a UN summit on climate change in New York (which the US will not, ironically, be attending). They found:

• 2014-2019 are the hottest 5 years on record
• Global temperature have risen by 1.1 C since 1850, but  0.2 C between 2011-2015.
• CO2 release between 2014-2019 was 20% higher than the previous 5 years
• Sea level rise has been 3.2 mm per year on average since 1993, but is 5mm per year averaged over the last five years.
• Ice loss is accelerating. For example – “The amount of ice lost annually from the Antarctic ice sheet increased at least six-fold, from 40 Gt per year in 1979-1990 to 252 Gt per year in 2009-2017.”
• Heatwaves, wild fires, and extreme weather events are increasing and causing increasing damage and costs.

There is a decisive scientific consensus that these facts are basically accurate, that human activity is causing warming, and that the results are not going to be good. There is a growing consensus among economists that the costs of global warming will be huge, in the billions for the US alone. Even if there is still a little uncertainty, there is enough data and enough consensus to act. So what’s holding us back?

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There is an industry of misinformation fueling climate change denial. It is often fairly sophisticated, and because it is dealing with a highly complex technical area, it’s easy to create an argument that sounds compelling. This results (as if often evidenced right here in the comments) in people who are confident that they are good skeptics and climate fearmongering is all nonsense. Of course they have to simultaneously believe in a rather absurd conspiracy theory regarding the scientific community, but they make that work somehow too.

Here are a couple of recent examples, both of which involve some subtle cherry picking. The first has to do with electric cars, which are frequently opposed by the denialists, in that they oppose subsidies to help bootstrap the market. This involves the “solution aversion” aspect of climate change denial – deniers are really motivated by the proposed solutions to climate change, which goes against either their politics or other interests. The claim that is often made is that producing electric cars has a higher carbon footprint than gasoline cars, and that if you are charging your car off the grid you are probably getting that electricity from fossil fuels. Therefore – electric cars are worse for the environment.

At the very least, I see climate change deniers delight in how stupid this makes the climate change believers appear.  This is a great example of cherry picking, because the two basic facts are correct but they are not the whole picture. Here, for example, is an article posted by Breitbart claiming that batteries are not green, concluding:

One of the authors, Mats-Ola Larsson at IVL, has made a calculation of how long you have to drive a petrol or diesel before it has released as much carbon dioxide as battery manufacturing has caused.

“The result was 2.7 years for a battery of the same size as the Nissan Leaf and 8.2 years for a battery of the Tesla-size.”

Truly the enduring mystery of why Tesla is now more highly valued than such non-Potemkin U.S. car manufacturers as Ford and General Motors grows more mysterious by the hour.

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A 2015 Pew survey found that 88% of AAAS scientists believe that GMOs (genetically modified organisms) are generally safe to eat, while only 37% of the general public did. This was the biggest gap, 51%, of any science attitude they surveyed – greater than evolution or climate change. This hasn’t changed much since. A 2018 Pew survey found that 49% of US adults think that GMOs are worse for your health. These numbers are also similar in other countries.

An important underlying question for science communicators is – what is the source and therefore potential solution to this disconnect between experts and the public? In other words – what drives anti-scientific or pseudoscientific attitudes in the public? The classic answer is the knowledge deficit model, that people reject science because they don’t understand it. If true, then the answer is science education and fostering greater scientific literacy.

However, psychological research over the last two decades has called into question the knowledge deficit model. Studies have found that giving facts often has not result, or may even create a backfire effect (although to scope of this is still controversial). Some research suggests you have to confront a person’s explanatory narrative and replace it with another. Others indicate that ideological beliefs are remarkably resistant to alteration with facts alone.

But the knowledge deficit model is not dead yet. It seems that we have to take a more nuanced approach to unscientific beliefs in the public. This is a heterogeneous phenomenon, with multiple causes and therefore multiple potential solutions. For each topic we need to understand what is driving that particular belief, and then tailor an approach to it.

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The degree to which there is a scientific consensus in anthropogenic global warming (AGW) remains politically controversial, even though it is not scientifically controversial. Denial of the consensus remains a cornerstone of AGW denial, so let’s examine the science and the arguments used to deny it.

Much of the public discussion focusses on the 2013 Cook article which claimed that there is a 97% consensus among experts in AGW. This has become the poster child of the consensus argument, much in the way Mann’s original article has become the icon of the “hockey stick” of global temperatures. The denialist strategy here is the same – falsely present the situation as if all the scientific eggs are in one basket, and then attack that basket with everything you have.

So Cook has been vilified by the deniers as if that demolishes the evidence for a consensus. That strategy ignores, however, the many other studies that also look at the question of consensus. In fact, there is a consensus of studies on consensus. A 2016 review of 6 independent studies found the range of estimates of the consensus is from 90-100%, with the consensus clustering around 97%. The “everything depends on that one Cook study” strategy is just factually incorrect.

The other strategy used to deny the consensus is to misrepresent individual studies, again with the focus being on Cook. There is admittedly a lot of complexity here, and no one number will capture that. No individual study is perfect, because you always have to make some trade-offs. These papers are all estimates of the consensus, and had to make certain assumptions. But that is why multiple independent estimates are useful.

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A paper is making the rounds on climate denial sites that claims to debunk human-caused climate change in a single stroke. Predictably, the paper does nothing of the sort, but it does raise a complex issue regarding climate change that is worth reviewing. But first let’s get to the paper itself.

The paper, by J. Kauppinen and P. Malmi, is a pre-publication paper on the Arxiv. This means it is not peer-reviewed. Their central claim, from the abstract:

In this paper we will prove that GCM-models used in IPCC report AR5 fail to calculate the influences of the low cloud cover changes on the global temperature.

Right in the first sentence is a huge red flag – claiming to be able to “prove” that the IPCC report is false. That’s a bold claim, and suggests a less than rigorous intellectual approach. They also claim to rebuke a rather robust conclusion built on many lines of evidence with a single line of evidence – the single stroke approach. This is also a huge red flag.

The claim is built around one major line of reasoning, that if you compare low cloud cover with changes in global temperatures, you see a strong correlation. In fact, the authors argue, you can explain most of global warming as resulting from a decrease in low cloud cover, leaving almost nothing left for anthropogenic forcing. There is a great deal wrong with this claim. The site ClimateFeedback has helpfully curated much of the response from climate scientists, who eviscerate the Kauppinen paper, and I will give you a summary of their summary.

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There are bacteria and mold aboard the International Space Station (ISS). This should come as no surprise, as these organisms follow humans everywhere we go. In fact it’s claimed that the ISS astronauts spend several hours per week cleaning mold off the ISS and wiping everything down. However, this first hand report by ISS astronaut Clayton C. Anderson says he did his cleaning duty every Saturday, but not as thoroughly as requested.

Still, as we spread into space, we need to carefully consider the microscopic ecosystem we will bring with us. A space ship or station is a self-contained environment, and as we plan trips back to the Moon and on to Mars, there will be longer and longer missions. Something as simple as a fungus may threaten those missions. A recent study of the resilience of mold spores highlights how challenging this may be.

The study looked at the effects of ionizing radiation on mold. They looked at the two most common species of mold aboard the ISS,  Aspergillus and Pennicillium. They found:

The spores survived exposure to X-rays up to 1000 gray, exposure to heavy ions at 500 gray and exposure to ultraviolet light up to 3000 joules per meter squared. Gray is a measure of absorbed dose of ionizing radiation, or joules of radiation energy per kilogram of tissue. Five gray is enough to kill a person. Half a gray is the threshold for radiation sickness.

Those are some hardy fungi. For context a one-way trip to Mars is expected to expose travelers to 0.7 gray. That will be a problem for the humans aboard, not so much the molds.

As an aside, the exposure to radiation is a major limiting factor for space travel. The ISS is still within the Earth’s magnetic field, and so is somewhat protected. But anything beyond low earth orbit will be slowly fried by radiation. We need to figure out how to shield our ships and colonies if we are going to have a prolonged presence outside of low earth orbit. This, by the way, is why lava tubes may be the best location for stations on the Moon or Mars.

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I know this is two paleontological posts in a row, but I had intended to blog about this before the stunning KT discovery. Chinese paleontologists announce in the journal Science a new early Cambrian fossil bed in South China – the The Qingjiang biota.

This is now just the third major Cambrian find – the first being the famous Burgess shale, and the second the Chengjiang, also in China. This find is amazing for several reasons.

First, the Cambrian Explosion is an incredibly important period in the evolution of life. The Cambrian period lasted from 541 to 485 million years ago. This was the first appearance of the multicellular life that clearly lead to all subsequent plants and animals, including modern species. There was a previous period called the Ediacara fauna, but it is still unclear if this lead to the Cambrian life or was a side branch or even an independent origin of multicellular life that didn’t make it. Recent evidence suggests that some Ediacara life were animals, and therefore ancestors to some Cambrian life and not a total dead end. But this is still not fully resolved.

Either way, the massive diversification of multicellular life in the Cambrian period lead to all the modern phyla, and many additional phyla that did not survive the Cambrian. Our first real evidence of this diversification was from a famous fossil find in Canada, the Burgess Shale. Most of what we know about the Cambrian still comes from these fossils.

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“When I saw that, I knew this wasn’t just any flood deposit,” DePalma said. “We weren’t just near the KT boundary—this whole site is the KT boundary!”

Unless something really unexpected happens, this is likely to be the science news story of the year, and will be on everyone’s short list for the science news of the decade. It may be the paleontological news of the century. It’s easy to get excited when news like this breaks, and maybe I’m overcalling it, but you can decide once you hear the news, if you haven’t already.

A young PhD candidate, Robert DePalma, has found a massive fossil deposit that seems to have been laid down on the actual day the asteroid hit and wiped out 99.9999% of living things and 75% of species on Earth.

The New Yorker tells the whole story in great detail, and the whole thing is worth a read, but here is the quick version. It is now clearly established that 66 million years ago a several mile wide asteroid impacted the earth at 45 thousand miles per hour, impacting near the Gulf of Mexico creating what is now called the Chicxulub crater. The impact sent tons of debris into the air, into orbit, and even around the solar system. Hot rock rained back down onto the Earth, setting fire to most of the plant life, poisoning the atmosphere, and blocking out the sun plunging the Earth into a toxic deep freeze.

It’s hard to imagine anything surviving that day or the following weeks and months, but some life squeaked through and eventually evolved into the modern assemblage of life, including humans.

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A new paper published in Nature, and signed by over 800 researchers, adds to the growing backlash against overreliance on P-values and statistical significance. This one makes a compelling argument for getting rid of the concept of “statistical significance” altogether. I completely agree.

Statistical significance is now the primary way in which scientific results are recorded and reported. The primary problem is that it is a false dichotomy, and further it reduces a more thorough analysis of the results to a single number and encourages interpreting the results as all or nothing – either demonstrating an effect is real or not real.

The primary method for determining significance is the P-value – a measure of the probability that the results obtained would deviate as much as they do or more from a null result if the null hypothesis were true. This is not the same as the probability that the hypothesis is false, but it is often treated that way. Also, studies often assign a cutoff for “significance” (usually a p-value of 0.05) and if the p-value is equal to or less than the cutoff the results are significant, if not then the study is negative.

When you think about it, this makes no sense. Further, the p-value was never intended to be used this way. It is only the human penchant for simplicity that has elevated this one number to the ultimate arbiter of how to interpret the results of a study.

The consequences of this simplistic analysis is that the interpretation of study results are often misleading. The authors, for example, looked at 791 articles in 5 journals and found that half of them made wrong conclusions about the results based on overinterpreting the implication of “significance”.

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