Category Archives: science

Biodiversity for heretics

Epistemic status: Not very confident in my conclusions here. Could be missing big things. Information gained through many hours of reading about somewhat-related topics, and a small few hours of direct research.

Summary: Biodiversity research is popular, but interpretations of it are probably flawed, in that they’re liable to confuse causation and correlation. Biodiversity can be associated with lots of variables that are rarely studied themselves, and one of these, not “biodiversity” in general, might cause an effect. (For example, more biodiverse ecosystems are more likely to include a particular species that has significant effects on its own.) I think “biodiversity” is likely overstudied compared to abundance, biomass, etc., because it’s A) easier to measure and B) holds special and perhaps undue moral consideration.


From what I was told, biodiversity – the number of species present in an environment – always seemed to be kind of magical. Biodiverse ecosystems are more productive, more stable over time, produce higher crop yields, and are more resistant to parasites and invaders. Having biodiversity in one place increases diversity in nearby places, even though diversity isn’t even one thing (forgive me for losing my citation here). Biodiverse microbiomes are healthier for humans. Biodiversity is itself the most important metric of ecosystem health. The property “having a suite of different organisms living in the same place” just seems to have really incredible effects.

First of all – quickly – some of what I was told isn’t actually true. More diverse microbiomes in bodies aren’t always healthier for humans or more stable. The effects of losing species in ecosystems varies a ton. More biodiverse ecosystems don’t necessarily produce more biomass.

That said, there’s still plenty of evidence that biodiversity correlates with something.

But: biodiversity research and its interpretations have problems. Huston (1997) introduced me to a few very concrete ways this can turn up misleading or downright inaccurate results.

Our knowledge about biodiversity’s effects on ecosystems comes from either experiments, in which biodiversity is manipulated in a controlled setting; or in observations of existing ecosystems. Huston identifies a few ways that these have, historically, given us bad or misleading data:

  1. Biotic or abiotic conditions, either in observations or experiments, are altered between groups. (E.g. you pick some sites to study that are less and more biodiverse, but the more-biodiverse sites are that way because they get more rainfall – which obviously is going to have other impacts)
  2. Species representing the “additional biodiversity” in experiments aren’t chosen randomly, they’re known to have some ecosystem function.
  3. Increasing the number of species increases the chance that one or a few of the added species will have some notable ecosystem effect on their own.

I’m really concerned about (3).


To show why, let’s imagine aliens who come to earth and want to study how humans work. They abduct random humans from across the world and put them in groups of various sizes.

Building walls

The aliens notice that the human civilizations have walls. They give their groups of abducted humans blocks and instruct them to build simple walls.

It turns out that larger groups of humans can build, on average, proportionally longer walls. The aliens conclude that wall-building is a property of larger groups of humans.

Building radios

The aliens also notice that human civilizations have radios. They give their groups of abducted humans spare electronic parts, and instruct them to build a radio.

Once again, it turns out that larger groups of humans are proportionally more likely to be able to build a radio. The aliens conclude that radio-building, too, is a property of large groups of humans.


The mistake the aliens are making is in assuming that wall- and radio-building are functions of “the number of humans you have in one place”. More people can build a longer simple wall, because there’s more hands to lift and help. But when it comes to building radios, a larger group just increases the chance that at least one human in the group will be an engineer.

To the aliens, who don’t know about engineers, “number of humans” kind of relates to the thing they’re interested in – they will notice a correlation – but they’re making a mistake by just waving their hands and saying that mostly only large groups of humans possess the intelligence needed to build a radio, perhaps some sort of hivemind.

Similarly, we’d make a mistake by looking at all the strange things that happen in diverse ecosystems, and saying that these are a magical effect that appears whenever you get large numbers of different plants in the same field. I wonder how often we notice that something correlates with “biodiversity” and completely miss the actual mechanism.

Aside from a specific species or couple of species in combination that have a particular powerful effect on ecosystems, what else might biodiversity correlate to that’s more directly relevant? How about abundance (the number of certain organisms of some kind present)? Or biomass (the combined weight of organisms)? Or environmental conditions, like the input of energy? Or the amount of biomass turnover, or the amount of predation, etc., etc.?

I started wondering about this while doing one of my several projects that relate to abundance in nature. We should still study biodiversity, sure. But the degree to which biodiversity has been studied compared to, say, abundance, has lead us to a world where we know there are 6,399 species of mammals, but nobody has any idea – even very roughly – how many mammals there are. Or how we’re pretty sure that there are about 7.7 million species of animals, plus or minus a few hundred thousand, which is a refinement of many previous estimates of the same thing – and then we have about two people (one of whom is wildly underqualified) trying to figure out how many animals there are at all.

It’s improving. A lot of recent work focuses on functional biodiversity. This is the diversity of properties of organisms in an environment. Instead of just recording the number of algae species in a coastal marine shelf, you might notice that some algae crusts on rocks, some forms a tall canopy, some forms a low canopy, and some grows as a mat. It’s a way of separating organisms into niches and into their interactions with the environment.

Functional diversity seems to better describe ecosystem effects than diversity alone (as described e.g. here). That said, it still leaves the door open for (3) – looking at functional diversity means you must know something about the ecosystem, but it’s not enough to tell you what’s causing the effect in and of itself.


To illustrate why:

Every species has some functional properties that separate it from other species – some different interactions, some different niche or physical properties, etc. We can imagine increasing biodiversity, then, as “a big pile of random variables.”

It turns out that when you start with a certain environment and slowly add or remove “a big pile of random variables”, that changes the environment’s properties. Who would have thought?


So is biodiversity instrumentally relevant to humans?

  1. There are sometimes solid explanations for why biodiversity itself might be relevant to ecosystems, e.g. the increased selection for species complementary over time theory.
  2. Biodiversity probably correlates to the things that studies claim it correlates to, including the ones that find significant environmental effects. I just claim that often, biodiversity is plausibly falsely described as the controlling variable rather than one of its correlates. (That said, there are reasons we might expect people to overstate its benefits – read on.)

If this is true, and biodiversity itself isn’t the driving force we make it out to be, why does everyone study it?

Firstly, I think biodiversity is easier to measure than, say, individual properties, or abundance. Looking at the individual properties and traits of each species in the environment is its whole own science, specific to that particular species and that particular environment. It would be a ridiculous amount of work.

But when we try to get the measure of an ecosystem without this really deep knowledge, we turn into the alien scientists – replacing a precise and intricate interaction with a separate but easier-to-measure variable that sort of corresponds with the real one.

What about studying one of the other ecosystem properties, like abundance? I’m guessing that in the modern research environment, you’d basically have to be collecting biodiversity data anyways.

Researcher: We found 255 beetles in this quadrant!

PI: What kind?

Researcher: You know. Beetles.

…And if you’re identifying everything you find in an environment anyways, it’s easier to just keep track of how many different things you find, rather than do that plus exhaustively search for every individual.

This is just speculation, though.

Secondly, a lot of people believe that species and ecosystems are a special moral unit (independent of any effects or benefits they might have on humans). That’s why people worry about losing the parasites of endangered species, or wonder if we shouldn’t damage biodiversity by eradicating diseases.

And… it’s hard to explain why this seems wrong to me, but I’ll try. I get it. Environmentalism is compelling and widespread. It was the background radiation of virtually almost every interaction with nature I had growing up. It was taken for granted that every drop of biodiversity was a jewel with value beyond measure, that endangered species were inherently worth going to great lengths to protect and preserve, that ecosystems are precariously balanced configurations that should be defended as much as possible from encroachment by humans. Under this lens, of course the number of species present is the default measurement – the more biodiversity preserved from human destruction, the more intricate and elaborate the ecosystem (introduced species excepted), the better.

And… doesn’t that seem a little limited? Doesn’t that seem like a sort of arbitrary way to look at huge parts of the world we live in? It’s not worth throwing out, but perhaps it deserves a little questioning. Where else could we draw the moral lines?

Personally, I realized my morality required me to treat animals as moral patients. This started with animals directly used by humans, but then got me re-examining the wild animals I’d been so fond of for so long.

Currently, I put individual animals and species in mostly-separated mental buckets. A species, a particular pattern instantiated by evolution acting on rocks and water over time, is important – but it’s important because it’s beautiful, like a fantastic painting made over decades by a long-dead artist. We value aesthetics, and interpretations, and certainly the world would be worse off without a piece of beauty like this one.

But an individual matters morally because it feels. It cares, it thinks, it feels joy, it suffers. We know because we are one, and because the same circuits and incentives that run in our brains also run in the brains of the cats, chickens, songbirds, insects, earthworms, whale sharks, and bristlemouths that we share this lonely earth with.

We might say that a species “suffers” or “is in pain”, the same way that a city “is in pain”, and we might mean several different things by that. We might say many of the individuals in the collective suffer. Or we might mean that the species is degraded somehow the way art is degraded – lessened in quantity, less likely to survive into the future, changing rapidly, etc. But it seems like a stretch to call that pain, in the way that being eaten alive is pain.

Obviously, at some point, you have to make trade-offs over what you care about. I don’t have my answers worked out yet, but for now, I put a lot more value on the welfare of individual animals than I used to, and I care less about species.

I don’t expect this viewpoint to become widespread any time soon. But I think it’s possible that the important things in nature aren’t the ones we’ve expected, and that under other values, properties like abundance and interactions deserve much more attention (compared to biodiversity) than they have now.


This blog has a Patreon. If you like what you’ve read, consider giving it your support so I can make more of it.

Are viruses alive?

Whether viruses are alive or not is a silly question. Here’s why.

(I make a handful of specific claims here that I expect are not universally agreed upon. In the spirit of tagging claims and also as a TL;DR, I’ll list them.)

  • Whether things are alive or not is a categorization issue.
  • The criteria that living organisms should be made of cells is a bad one, even excluding viruses.
  • Some viruses process energy.
  • A virus alone may not process energy, but a virus-infected cell does, and meets all criteria for life.
  • Viruses are not an edge case in biology, they’re central to it.
  • The current criteria for life seem to be specifically set up to exclude viruses.
phage

Bacteriophage infecting a cell. || Electron micrograph by Dr. Graham Beards, CC BY-SA 3.0

What does it mean to be alive?

Whether viruses are alive is a semantic issue. It isn’t a question about reality, in the same way that “how many viruses are there?” or “do viruses have RNA?” are questions about reality. It’s a definitional question, and whether they fall in the territory of “alive” or not depends on where you draw the borders.

Fortunately, scientists tentatively use a standard set of borders. This is not exactly set in stone, but it’s an outset. In intro biology in college, I learned the following 7 characteristics (here, copied from Wikipedia)*:

  1. Homeostasis: regulation of the internal environment to maintain a constant state; for example, sweating to reduce temperature

  2. Organization: being structurally composed of one or more cells — the basic units of life

  3. Metabolism: transformation of energy by converting chemicals and energy into cellular components (anabolism) and decomposing organic matter (catabolism). Living things require energy to maintain internal organization (homeostasis) and to produce the other phenomena associated with life.

  4. Growth: maintenance of a higher rate of anabolism than catabolism. A growing organism increases in size in all of its parts, rather than simply accumulating matter.

  5. Adaptation: the ability to change over time in response to the environment. This ability is fundamental to the process of evolution and is determined by the organism’s heredity, diet, and external factors.

  6. Response to stimuli: a response can take many forms, from the contraction of a unicellular organism to external chemicals, to complex reactions involving all the senses of multicellular organisms. A response is often expressed by motion; for example, the leaves of a plant turning toward the sun (phototropism), and chemotaxis.

  7. Reproduction: the ability to produce new individual organisms, either asexually from a single parent organism or sexually from two parent organisms.

The simple answer

Viruses meet all of the criteria for living things, except 2) and maybe 3).

The complicated answer

For the complicated answer, let’s go a level deeper.

Simply put, criterion 2) states that living things must be made of cells.

Criterion 3) states that living things must metabolize chemical energy in order to power their processes.

Are viruses made of cells?

Definitely not.

Okay, here’s what I’ve got. I think 2) is a bad criterion. I think that criteria for living things should not be restricted to earth *, and therefore not restricted to our phylogenetic history. Cells are a popular structure on earth, but if we go to space and find large friendly aliens that are made of proteins, reproduce, evolve, and have languages, we’re not just going to call them “non-living” because they run on something other than cells. Even if that definition is useful up until that point, we’d change it after we found those aliens, suggesting that it wasn’t a good criterion in the first place either.

(Could large aliens not be made out of cells? Difficult to say – multicellularity has been a really, really popular strategy here on earth, having evolved convergently at least 25 times. But cells as we know them only evolved once or twice. Also, it’s not clear to what degree convergent evolution applies to things outside of our particular evolutionary history, because n=1.)

So no, viruses don’t meet criterion 2), although the importance of criterion 2) is debatable.

Do viruses process energy?

What about criterion 3)? Do viruses process energy? Kind of.

Let’s unpack “processing energy.” Converting one kind of chemical energy to another is pretty generic. In bacteria and eukaryotes, what does that look like?

metabolicpathways

Some metabolic pathways used by cellular life. Large version.

Go ahead. Enlarge it. Look around. Contemplate going into biochemistry. Here’s where it starts to get complicated.

One of the major energy sources in cells is converting adenosine triphosphate (ATP) into adenosine diphosphate (ADP). This transformation powers so much cellular processes in all different organisms that it’s called the currency of life.

Bacteriophage T4 encodes an ATP→ADP-powered motor. It’s used during the virus’ reproduction, to package DNA inside nascent virus heads.

Some viruses of marine cyanobacteria encode various parts of the electron transport chain, the series of motors that pump protons across membranes and create a gradient that results in the synthesis of ATP. They encode these as a sort of improvement on the ones already present in the hosts.

Do those viruses process chemical energy? Yes. If you’re not convinced, ask yourself: Is there some other pathway you’d need to see before you consider a virus to encode a metabolism? If so, are you absolutely certain that we will never find such a virus? I don’t think I would be.

Wait, you may say. Sure, the viruses encode those and do those when infecting a host. But the viruses themselves don’t do them.

To which I would respond: A pathogenic bacterial spore is, basically, metabolically inert. If it nestles into a warm, nutrient-rich host, it blossoms into life. Our understanding of living things includes a lot of affordance for stasis.

By the same token, a virus is a spore in stasis. A virus-infected cell meets all the criteria of life.

(I think I heard this idea from Lindsay Black’s talk at the 2015 Evergreen Bacteriophage meeting, but I might be misremembering. The scientists there seemed very on-board with the idea, and they certainly have another incentive to claim that their subjects are alive, which is that studying living things sounds cooler than studying non-living things – but I think the point is still sound.)

Do we really want only some viruses count as alive?

To summarize, cells infected by T4 or some marine cyanophages – and probably other viruses – meets all of the criteria of life.

It seems ridiculous to include only those viruses in the domain of ‘life’, and not others that don’t include those chemical processes. Viruses have phylogeny. Separating off some viruses that are alive and some that aren’t is pruning branches off of the the evolutionary tree. We want a category of life that carves nature at its joints, and picking only some viruses does the opposite of that.

Wait, it gets more complicated. Some researchers have proposed giant viruses as a fourth domain of life (alongside the standard prokaryotes, eukaryotes, and archaea.) You’ll note that it’s giant viruses, and not all the viruses. That’s because viruses probably aren’t monophyletic. Hyperthermophilic crenarchaea phages, in addition to being a great name for your baby, share literally no genes with any other virus. Some other viruses have only extremely distant genetic similarities to others, which may have been swapped in by accident during past infections. This is not terribly surprising – we know that parasites have convergently evolved perhaps thousands of times. But it certainly complicates the issue of where to put viruses in the tree.

Viruses are not just an edge case

When people talk about the criteria of life, they tend to consider viruses as an edge case, a weird outlier. This is misleading.

standardview

The standard view of life

cosmopolitanview

A more cosmopolitan view.

Worldwide, viruses outnumber cells 10 times over. They’re not an edge case in biology – by number of individuals, or amount of ongoing evolution, they’re most of biology. And it’s rather suspicious that the standard criteria for life seem to be set up to include every DNA-containing evolving organism except for viruses. If we took out criteria 2) and 3), what else would that fold in? Maybe prions? Anything else?

Accepting that ‘life’ is a word that tries to draw out a category in reality, why do we care about that category? When we ask “is something alive?”, here are some questions we might mean instead.

  • Is something worth moral consideration? (Less than a bacteria, if any.)
  • Should biologists study something? (A biologist is much more suited to study viruses than a chemist is.)
  • Does something fit into the tree of life? (Yes.)
  • If we find something like it on another planet, should we celebrate? (Yes, especially because a parasite has to have a host nearby.)

When we think of viruses – fast moving, promiscuous gene-swappers, picking up genes from both each other and their hosts, polyphyletic, here from the beginning  – I think of a parasitic vine weaving around the tree of life. It’s not exactly an answer, but it’s a metaphor that’s closer to the truth.


* Carl Sagan’s definition of life, presented to and accepted by a committee at NASA, is “a self-sustaining chemical system capable of Darwinian evolution.” This nicer, neater definition folds in viruses, prions, and aliens. The 7-point system is the one I was taught in college, though, so I’m writing about that.

Triptych in Global Agriculture

As I write this, it’s 4:24 PM in 2016, twelve days before the darkest day of the year. The sun has just set, but you’d be hard-pressed to tell behind the heavy layer of marbled gray cloud. There’s a dusting of snow on the lawns and the trees, and clumps on roofs, already melted off the roads by a day of rain. From my window, I can see lights glimmering in Seattle’s International District, and buildings of downtown are starting to glow with flashing reds, neon bands on the Colombia Tower, and soft yellow on a thousand office windows. I’m starting to wonder what to eat for dinner.

It’s the eve before Seattle Effective Altruism’s Secular Solstice, a somewhat magical humanist celebration of our dark universe and the light in it. This year, our theme is global agriculture – our age-old answer to the question of “what are we, as a civilization, collectively going to eat for dinner?” We have not always had good answers to this question.

Civilization, culture, and the super-colony of humanity, the city, started getting really big when agriculture was invented, when we could concentrate a bunch of people in one place and specialize. It wasn’t much specialization, at first. Farmers or hunter-gatherers were the vast majority of the population and the population of Ur, the largest city on earth, was around 65,000 people in 3000 BC. Today, farmers are 40% of the global population, and 2% in the US. In the 1890’s, the city of Shanghai had half a million people. Today, it’s the world’s largest city, with 34 million residents.

What happened in those 120 years, or even the last 5000?

Progress, motherfuckers.

I’m a scientist, so the people I know of are scientists, and science is what’s shaped a lot of our agriculture in the last hundred years. When I think of the legacy of science and global agriculture, of people trying to figure out how we feed everyone, I think of three people, and I’ll talk about them here. I’ll go in chronological order, because it’s the order things go in already.

Fritz Haber, 1868-1934

Fritz.jpg

Fritz Haber in his laboratory.

Haber was raised in a Jewish family in Prussia, but converted to Lutheranism after getting his doctorate in chemistry – possibly to improve his odds of getting high-ranking academic or military careers. At the University of Kulroch in Germany, Haber and his assistant Robert Le Rossignol did the work that won them a Nobel prize: they invented the Haber-Bosch process.

The chemistry of this reaction is pretty simple – it was a fact of chemistry at the time that if you added ammonia to a nickel catalyst, the ammonia decomposed into hydrogen and nitrogen. Haber’s twist was to reverse it – by adding enough hydrogen and nitrogen gas at a high pressure and temperature, the catalyst operates in reverse and combines the two into ammonia. Hydrogen is made from natural gas (CH4, or methane), and nitrogen gas is already 80% of the atmosphere.

Here’s the thing – plants love nitrogen. Nitrogen is, largely, the limiting factor in land plants’ growth – when you see that plants aren’t growing like mad, it’s because they don’t have sufficient nitrogen to make new proteins. When you give a plant nitrogen in a form it can assimilate, like ammonia, it grows like mad. The world’s natural solid ammonia deposits were being stripped away to nothing, applied to crops to feed a growing population.

When Haber invented his process in 1909, ammonia became cheap. A tide was turning. The limiting factor of the world’s agriculture was suddenly no longer limiting.

Other tides were turning too. In 1914, Germany went to war, and Haber went to work on chemical weapons.

During peace time a scientist belongs to the World, but during war time he belongs to his country. – Fritz Haber

He studied deploying chlorine gas, thinking that it would shorten the war. Its effect is described as “drowning on dry land”. After its first use on the battlefield, he received a promotion on the same night his wife killed herself. Clara Immerwahr, a fellow chemist, was a pacifist, and had shot herself with Haber’s military pistol. Haber continued his work. Scientists in his employ also eventually invented Zykkon B. First designed as a pesticide, after his death, the gas would be used to murder his extended family (along with many others) in the Nazi gas chambers.

Anti-Jewish sentiment was growing in the last few years of his life. In 1933, he wasn’t allowed through the doors of his institute. The same year, his friend, and fellow German Jewish scientist, Albert Einstein, went to the German Consulate in Belgium and gave them back his passport – renouncing his citizenship of the Nazi-controlled government. Haber left the country, and then died of a heart attack, in the next year.

I don’t know if Fritz Haber’s story has a moral. Einstein wrote about his colleague that “Haber’s life was the tragedy of the German Jew – the tragedy of unrequited love.” Haber was said to ‘make bread from air’ and said to be the father of chemical weapons. He certainly created horrors. What I might take from it more generally is that the future isn’t determined by whether people are good or bad, or altruistic or not, but by what they do, as well as what happens to the work that they do.

Nikolai Vavilov – 1887-1943

Nikolai.jpg

Vavilov in 1935.

We shall go into the pyre, we shall burn… But we shall not abandon our convictions. – Nikolai Vavilov

As a young but wildly talented agronomist in Russia, the director of the  Lenin All-Union Academy of Agricultural Sciences for over a decade, the shrewd and charismatic Nikolai Vavilov, wanted to make Russia unprecedented experts in agriculture. He went on a series of trips to travel the globe and retrieve samples. He observed that in certain parts of the world, one would find a much greater variety of a given crop species, with a wider range of characteristics and traits not seen elsewhere. This lead to his breakthrough theory, his Vavilov centers of diversity, that the greatest genetic diversity could be found where a species originated.

What has this told us about agriculture? This morning for breakfast, I had coffee (originally from Ethiopia) with soy milk (soybeans originally from China), toast (wheat from the Middle East) with margarine (soy oil, China, palm oil, West and Southwest Africa), and chickpeas (Central Asia) with black bean sauce (central or possibly South America) and pepper (India). One fairly typical vegan breakfast, seven centers of diversity.

He traveled to twelve Vavilov centers, regions where the world’s food species were originally cultivated. He traveled in remote regions of the world, gathering unique wheat and rye in the Hindu Kush, Spain, and Portugal, teff in Somalia, sugar beet and flax in the Mediterranean, potatoes in Peru, fava beans and pomegranates and hemp in Herat. He was robbed by bandits in Eritrea, and nearly died riding horseback along deep ravines in the Pamirs. The seeds he gathered were studied carefully back in Russia, tested in fields, and most importantly, cataloged and stored – by gathering a library of genetic diversity, Vavilov knew he was creating a resource that could be used to grow plants that would suit the country’s needs for decades to come. If a pest decimates one crop, you can find a resistant crop and plant it instead. If drought kills your rice, all you need to do is find a drought-tolerant strain of rice. At the Pavlovsk Experimental Research Station, Vavilov was building the world’s first seed bank.

vavilov centers.png

Vavilov Centers of the world. Image from Humanity Development Library of the NZDL.

In Afghanistan, he saw wild rye intermingled with wheat in the fields, and used this as evidence of the origin of cultivated rye: that it wasn’t originally grown intentionally the way wheat or barley had been, but that it was a wheat mimic that had slipped into farms and taken advantage of the nurturing protection of human farmers, and had, almost accidentally, become popular food plants  at the same time. Other Vavilovian mimics are oats and Camelina sativa.

While he travelled the world and became famous around the burgeoning global scientific community, Russia was changing. Stalin had taken over the government. He was collectivizing the farms of the country, and in the scientific academies, were dismissing staff based on bourgeois origin and increasing the focus on practical importance of work for the good of the people. A former peasant was working his way up through agricultural institutions: Trofim Lysenko, whose claimed that his theory of ‘vernalization’, or adapting winter crops to behave more like summer crops by treating the seeds with heat, would grow impossible quantities of food and solve hunger in Russia. Agricultural science was politicized in a way that it never had been – Mendelian genetics and the existence of chromosomes were seen as unacceptably reactionary and foreign. Instead, a sort of bastardized Lamarckism was popular – aside from being used by Lysenko to justify outrageous promises of future harvests that never quite came in, it said that every organism could improve its own position – a politically popular implication, but one which failed to hold up to experimental evidence.

Vavilov’s requests to leave the country were denied. His fervent Mendelianism and the way he fraternized with Western scientists were deeply suspicious to the ruling party. As his more resistant colleagues were arrested around him, his institute filled up with Lysenkoists, and his work was gutted. Vavilov refused to denounce Darwinism. Crops around Russia were failing under the new farming plans, and people starved as Germany invaded.

Vavilov’s devoted colleagues and students kept up his work. In 1941, the German Army reached the Pavlovsk Experimental Research Station, interested in seizing the valuable samples within – only to find it barren.

Vavilov’s colleagues had taken all 250,000 seeds in the collection by train into Leningrad. There, they hid them in the basement of an art museum and watched them in shifts all throughout the Siege of Leningrad. They saw themselves as protecting Russia’s future in agriculture. When the siege lifted in 1944, twelve of Vavilov’s scientists had starved to death rather than eat the edible seeds they guarded. Vavilov’s collection survived the war.

Gardening has many saints, but few martyrs. – T. Kingfisher

In 1940, Vavilov was arrested, and tortured in prison until he confessed to a variety of crimes against the state that he certainly never committed.

He survived for three years in the gulag. The German army advanced on Russia and terrorized the state. Vavilov, the man who had dreamed of feeding Russia, starved to death in prison in the spring of 1943. His seed bank still exists.

Vavilov’s moral, to me, is this: Science can’t be allowed to become politicized. Whatever the facts are, we have to build our beliefs around them, never the other way around.

Norman Borlaug, 1914-2009

Norman.jpg

Norman Borlaug in 1996. From Bill Meeks, AP Photo.

Borlaug was raised on a family farm to Norwegian immigrants in Iowa. He studied crop pests, and had to take regular breaks from his education to work: He worked in the Civilian Conservation Corps during the dustbowl alongside starving men, and for the Forest Service in remote parts of the country. In World War 2, he worked on adhesives and other compounds for the US MIlitary. In 1944, he worked on a project sponsored by the Rockefeller Foundation and the Mexican Ministry of Agriculture to improve Mexico’s wheat yields and stop it from having to import most of its grain. The project faced opposition from local farmers, mostly because wheat rust had been killing their crops. This wasn’t an entirely unique problem – populations were growing globally. Biologist Paul Erlich wrote in 1968, “The battle to feed all of humanity is over … In the 1970s and 1980s hundreds of millions of people will starve to death in spite of any crash programs embarked upon now.”

Borlaug realized that by harvesting seeds in one part of the country and quickly moving them to another, the government could take advantage of the country’s two growing seasons and double the harvest.

By breeding many wheat strains together, farmers could make crops resistant to many more diseases.

He spread the use of Haber’s ammonia fertilizers, and bred special semi-dwarf strains of wheat that held up to heavy wheat heads without bending, and grew better in nitrogen fertilizers.

Nine years later, Mexico’s wheat harvest was six times larger than it had been in 1944, and it had enough wheat to export.

Borlaug was sent to India in 1962, and along with Mankombu S. Swaminathan, they did it again. India was at war, dealing with famine and starvation, and was importing necessary grain for survival. They used Borlaug’s strains, and by 1968, were growing so much wheat that the infrastructure couldn’t handle it. Schoolhouses were converted into granaries.

His techniques spread. Wheat yields doubled in Pakistan. Wheat yields in the world’s least developed countries doubled. Borlaug’s colleagues used the same process on rice, and created cultivars that were used all over Asia. Borlaug saw a world devastated by starvation, recognized it for what it was, and treated it as a solvable problem. He took Haber’s mixed legacy and put it to work for humanity. Today, he’s known as the father of the Green Revolution, and his work is estimated to have saved a billion lives.

We would like his life to be a model for making a difference in the lives of others and to bring about efforts to end human misery for all mankind. – Statement from Borlaug’s children following his death


What’s next?

When I think of modern global agriculture, this is who I think of. I’ve been trying to find something connecting Vavilov and the Green Revolution, and haven’t turned up much – although it’s quite conceivable there is, given Vavilov’s inspirational presence and the way he shared his samples throughout the globe. Borlaug’s prize wheat strain that saved those billion lives, Norin 10-Brevor 14, was a cross between Japanese and Washingtonian wheat. Past that, who knows?

One of the organizations protecting crop diversity today is the Consultative Group for International Agricultural Research (CGIAR), which was founded in 1971 by the Rockefeller Foundation as the Green Revolution was in full swing. They operate a variety of research stations worldwide, mostly at Vavilov Centers in the global south where crop diversity is highest. Their mission is to reduce global poverty, improve health, manage natural resources, and increase food security.

They must have been inspired by Vavilov’s conviction that crop diversity is essential for a secure food supply. If a legacy that’s saved literally a billion human lives can be said to have a downside, it’s that diets were probably more diverse before, and now 12 species make up 75% of our food plant supply. Monocultures are fragile, and if conditions change, a single disease is more likely to take out all of a crop.

glamox

The Svalbard Seed Bank. Image from Glamox.

In 2008, CGIAR brought the first seed samples into the Svalbard Seed Vault – a concrete structure buried in the permafrost. It’s constructed as a refuge against whatever the world might throw. If electricity goes out, the permafrost will keep the seeds cool. If sea levels rise, the vault is built on a hill. The land it’s on is geologically stable and very remote. And it stores 1,500,000 seeds – six times more than Vavilov’s 250,000 – at no cost to countries that use it.

WorldHungerGraph.png

Let it be known: starvation is on its last legs. We have a good thing going here. Still, with global warming and worse things still looming over the shoulder of this tentative victory, let’s give thanks to the movers and shakers of global agriculture for tomorrow: the people ensuring that whatever happens next, we are going to be fed.

We are going to be eating dinner, dammit.

Happy Solstice, everyone.

Science for Non-Scientists: How to read a journal article

Scientific journal writing has a problem:

  1. It’s the main way scientists communicate their findings to the world, in some ways making it the carrier of humanity’s entire accumulated knowledge and understanding of the universe.
  2. It’s terrible.

It’s terrible for two reasons: accessibility and approachability. This first post in this series discussed accessibility: how to find papers that will answer a particular question, or help you explore a particular subject.

This post discusses approachability: how to read a standard scientific journal article.


Scientific papers are written for scientists in whatever field the journal they’re published in caters to. Fortunately, most journal articles are also written in such a way that you can figure out what they’re saying even if you’re a layperson.

(Except for maybe math or organic chemistry synthesis. But if you’re reading about math or organic chemistry as a layperson, you’re in God’s hands now and I can’t help you.)

Okay, so you’ve got your 22-page stack of paper on moose feeding habits, or the effects of bacteriophage on ocean acidification, or gravitational waves, or whatever. What now? There are two cardinal rules of journal articles:

  1. You usually don’t have to read all of it.
  2. Don’t read it page by page.

Journal articles are conveniently broken into sections. (They often use the names given, or close synonyms.) I almost always read them in the following order:

20160705_110250

1. Abstract

The abstract is the TL;DR of the article, the summary of what the studies found. Conveniently, it’s first. The abstract is very useful for determining if you actually want to read the rest of the article or not. Abstracts often have very dense, technical language, so if you don’t understand what’s going on in the abstract, don’t sweat it.

2. Introduction

As a layperson, the introduction is your best friend. It’s designed to bring the reader from only a loose understanding of the field, to “zoom in” to the actual study. It’s supposed to build the context you need to understand the experiment itself. It gives a background to the field, what we already know about the topic at hand, historical context, why the researchers did what they did, and why it’s important. It’ll define terms and acronyms that will be crucial to the rest of the paper.

It may not actually be easy language. At this point, if you encounter a term or concept that’s unfamiliar (and that the researchers don’t describe in the introduction), start looking it up. Just type it into Wikipedia or Google, and if what you get seems to be relevant, that’s probably it.

3. Conclusions

In a novel, skipping to the end to see how the suspense plays out is considered “bad form” and “not the point.” When reading papers, it’s a sanity-saving measure. In this part of the paper, the researchers write about what conclusions they’re drawing from their studies,and its implications. This is also done in fairly broad strokes that put it in context of the rest of scientific understanding.

4. Figures

Next, go to the figures that are strewn around the results section, just before the conclusions. (Some papers don’t have figures – in that case, just read the results.) Figures will give you a good sense of the actual results of the experiments. Also read the captions – captions on figures are designed to be somewhat stand-alone, as in that you don’t have to read everything else in the paper to tell what’s going on in the figures.

Depending on your paper, you might also get actual pictures of the subject that illustrate some result. Definitely look at these. Figure out what you’re looking at and what the pictures are supposed to be telling you. Google anything you don’t understand, including how the images were obtained if it’s relevant.

In trying to interpret figures, look at the labels and axes – what’s being compared, and what they’re being measured by. Lots of graphs include measurements taken over time, but not all. Some figures include error measurements – each data point on a graph might have been the average of several different data points in individual experiments, and error measures how different those data points were from each other. A large percent error (or error bar, or number of standard deviations, etc) means the original data points were far apart from each other, small error means that they were all close to the average value. If you see a type of graph that you’re not sure how to read, Google it.

5. Results

The section that contains figures also contains written information about the researchers actually observed in the experiments they ran. They also usually include statistics, IE, how statistically significant a given result is in the context of the study. The results are what the conclusions were interpreting. They may also describe results or observations that didn’t show up in figures.

Maybe read:

Methods

Methods are the machinery of the paper – the nuts-and-bolts, nitty-gritty of how the experiments were done, what was combine, where the samples came from, how it was quantified. It’s critical to science because it’s the instructions for how other researchers can check what you did and see if they can replicate the results – but I’d also rather read Youtube comments on political debates than read methods all day. I’ll read the methods section under the following circumstances:

  • I’m curious about how the study was done. (You do sometimes get good stuff, like in this study where they anesthetized snakes and slid them down ramps, then compared them to snakes who slid down ramps while wearing little snake socks to compare scale friction.)
  • I think the methodology might have been flawed.
  • I’m trying to do a similar experiment myself.
snakes on a plane.gif

Snakes on a plane! || Gif from this video.

Works cited

Papers cite their sources throughout the paper, especially in the introduction. If I want to know where a particular fact came from, I’ll look at the citation in the works cited section, and look up that paper.

Acknowledgement/Conflicts of Interest

Science is objective, but humans aren’t. If your paper on “how dairy cows are super happy on farms” was sponsored by the American Dairy Association and Dairy Council, consider that the researchers would be very biased to come to a particular conclusion and keep receiving funding. If the researchers were employed by the American Dairy Association and Dairy Council, I’d be very tempted to just throw out the study.

Science for Non-Scientists: How to find scientific literature

Scientific journal writing has a problem:

  1. It’s the major way scientists communicate their findings to the world, in some ways making it the carrier of humanity’s entire accumulated knowledge and understanding of the universe.
  2. It’s terrible.

This has two factors: Accessibility and approachability. Scientific literature isn’t easy to find, and much of it is locked behind paywalls. Also, most scientific writing is dense, dull, and nigh-incomprehensible if you’re not already an expert. It’s like those authors who write beautiful works of literature and poetry, and then keep it under their bed until they die – only the poetry could literally be used to save lives.  There are systematic issues with the way we deal with scientific literature, but in the mean time, there are also some techniques that make it easier to deal with.

This first post in this series will discuss accessibility: how to find papers that will answer a particular question or help you explore a subject.

The second post in this series discusses approachability: how to read a standard scientific journal article.


How to Find Articles

Most scientific papers come from a small group of researchers who do a series of experiments on a common theme or premise, then write about what they learned. If your goal is to learn more about a broad subject, ask yourself if a paper is actually what you want. Lots of quality, scientifically rigorous information can be obtained in other ways – textbooks, classes, summaries, Wikipedia, science journalism.

 

blog science stack

The great food web of “where does scientific knowledge come from anyways?”

When might you want to turn to the primary literature? If you’re looking at very new research, if you’re looking at a contentious topic, if you’re trying to find a specific number or fact that just isn’t coming up anywhere else, if you’re trying to fact-check some science journalism, or if you’re already familiar enough with the field that you know what’s on Wikipedia already.

You can look at the citations of a journal article you already like. Or, find who the experts in a field are (maybe by looking at leaders of professional organizations or Wikipedia) and read what they’ve written. Most science journalism is also reporting on a single new study, which should be linked in the article’s text.

If you have access to a university library, ask them about tools to search databases of journal articles. Universities subscribe to many reliable journals and get their articles for free. Your public library may also have some.

Google Scholar is a search engine for academic writing. It has both recent and very old papers, and a variety of search tools. It pulls both reliable and less reliable sources, and both full-text and abstract-only articles (IE, articles where the rest is behind a paywall.) Clicking “All # Versions” at the bottom of each result will often lead you to a PDF of the full text.

If you’ve found the perfect paper but it’s behind a paywall- well, welcome to academia. Don’t give up. First up, put the full name of the article, in quotes, into Google. Click on the results, especially on PDFs. It’ll often just be floating around, in full, on a different site.

If that doesn’t work, and you don’t have access through a library, well… Most journals will ask you to pay them a one-time fee to read a single article without subscribing. It’s often ridiculous, like forty dollars. (Show of hands, has anyone reading this ever actually paid this?)

But this is the modern age, and there are other options. “Isn’t that illegal?” you may ask. Well, yes. Don’t do illegal things. However, journals follow two models:

  1. Open content access, researchers pay to submit articles
  2. Content behind paywalls, researchers can submit articles for free

As you can see, fees associated with journals don’t actually go to researchers in either model. There are probably some reasonable ethical objections to downloading paywalled-articles for free, but there are also very reasonable ethical objections to putting research behind paywalls in general.

How good is my source?

Surprise! There’s good science and bad science. This is a thorny issue that might be beyond my scope to cover in a single blog post, and certainly beyond my capacity to speak to every field on. I can’t just leave you here without a road map, so here are some guidelines. You’ll probably have two goals: avoiding complete bullshit and finding significant results.

Tips for avoiding complete bullshit

  • Some journals are more reliable than others. Science and Nature are the behemoths of science and biology (respectively), and have extremely high standards for content submission. There are also other well-known journals in each field.
  • Well-known journals are unlikely to publish complete bullshit. (Unless they’re well known for being pseudoscience journals.)
  • You can check a journal’s impact score, or how well-cited their work tends to be, which is sort of a metric for how robust and interesting the papers they publish are. This is a weird ouroboros: researchers want to submit to journals with high impact scores, and journals want to attract articles that are likely to be cited more often – so it’s not a perfect metric. If a journal has no impact score at all, proceed with extreme caution.
  • Watch out for predatory journals and publishers. Avoid these like the plague, since they will publish anything that gets sent to them. (What is a predatory journal?)
  • Make sure the journal hasn’t issued a retraction for the study you’re reading.

Once you’ve distinguished “complete bullshit” from “actual data”, you have to distinguish “significant data” from “misleading data” or “fluke data”. Finding significant results is much tougher than ruling out total bullshit – scientists themselves aren’t always great at it – and varies depending on the field.

Tips for finding significant results

  • Large sample sizes are better than small sample sizes. (IE, a lot of data was gathered.)
  • If the result appears in a top-level journal, or other scientists are praising it, it’s more likely to be a real finding.
  • Or if it’s been replicated by other researchers. Theoretically, all research is expected to replicate. In practice, it sometimes doesn’t, and I have no idea how to check if a study has been replicated.
  • If a result runs counter to common understanding, is extremely surprising, and is very new, proceed with caution before accepting the study’s conclusions as truth.
  • Apply some common sense. Can you think of some other factor that would explain the results, that the authors didn’t mention? Did the experiment run for a long enough amount of time? Could the causation implied in the paper run other ways (EG, if a paper claims that anxiety causes low grades: could it also be that low grades cause anxiety, or that the same thing causes both anxiety and low grades?), and did the paper make any attempt to distinguish this? Is anything missing?
  • Learn statistics.

If you’re examining an article on a controversial topic, familiarize yourself with the current scientific consensus and why scientists think that, then go in with a skeptical eye and an open mind. If your paper gets an opposite result from what most similar studies say, try to find what they did differently.

Scott Alexander writes some fantastic articles on how scientists misuse statistics. Here are two: The Control Group is Out of Control, and Two Dark Side Statistical Papers. These are recommended reading, especially if your subject is contentious, and uses lots of statistics to make its point.


Review articles and why they’re great

The review article (including literature reviews, meta-analyses, and more) is the summary of a bunch of papers around a single subject. They’re written by scientists, for scientists, and published in scientific journals, but they’ll cover a subject in broader strokes. If you want to read about something in more detail than Wikipedia, but broader than a journal article – like known links between mental illness and gut bacteria – review articles are a goldmine. Authors sometimes also use review articles to link together their own ideas or concepts, and these are often quite interesting.

If an article looks like a normal paper, and it came from a journal, but it doesn’t follow the normal abstract-introduction-methods-discussion-conclusion format, and subject headings are descriptive rather than outlining parts of an experiment, it might be a review article. (Sometimes they’re clearly labelled, sometimes not.) You can read these the same way you’d read a book chapter – front to back – or search anywhere in it for whatever you need.

What if you can’t find review articles about what you want, or you need more specificity? In that case, buckle up. It’s time to learn how to read an article.