Spaghetti Towers

Here’s a pattern I’d like to be able to talk about. It might be known under a certain name somewhere, but if it is, I don’t know it. I call it a Spaghetti Tower. It shows up in large complex systems that are built haphazardly.

Someone or somethdesidesigning builds the first Part A.

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Later, someone wants to put a second Part B on top of Part A, either out of convenience (a common function, just somewhere to put it) or as a refinement to Part A.

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Now, suppose you want to tweak Part A. If you do that, you might break Part B, since it interacts with bits of Part A. So you might instead build Part C on top of the previous ones.

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And by the time your system looks like this, it’s much harder to tell what changes you can make to an earlier part without crashing some component, so you’re basically relegated to throwing another part on top of the pile.

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I call these spaghetti towers for two reasons: One, because they tend to quickly take on circuitous knotty tangled structures, like what programmers call “spaghetti code”. (Part of the problem with spaghetti code is that it can lead to spaghetti towers.)

Especially since they’re usually interwoven in multiple dimensions, and thus look more like this:

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“Can you just straighten out the yellow one without touching any of the others? Thanks.”

Second, because shortsightedness in the design process is a crucial part of spaghetti machines. In order to design a spaghetti system, you throw spaghetti against a wall and see if it sticks. Then, when you want to add another part, you throw more spaghetti until it sticks to that spaghetti. And later, you throw more spaghetti. So it goes. And if you decide that you want to tweak the bottom layer to make it a little more useful – which you might want to do because, say, it was built out of spaghetti – without damaging the next layers of gummy partially-dried spaghetti, well then, good luck.

Note that all systems have load-bearing, structural pieces. This does not make them spaghetti towers. The distinction about spaghetti towers is that they have a lot of shoddily-built structural components that are completely unintentional. A bridge has major load-bearing components – they’re pretty obvious, strong, elegant, and efficiently support the rest of the structure. A spaghetti tower is more like this.

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The motto of the spaghetti tower is “Sure, it works fine, as long as you never run lukewarm water through it and turn off the washing machine during thunderstorms.” || Image from the always-delightful r/DiWHY.

Where do spaghetti towers appear?

  • Basically all of biology works like this. Absolutely all of evolution is made by throwing spaghetti against walls and seeing what sticks. (More accurately, throwing nucleic acid against harsh reality and seeing what successfully makes more nucleic acid.) We are 3.5 billion years of hacks in fragile trench coats.
    • Scott Star Codex describes the phenomenon in neurotransmitters, but it’s true for all of molecular biology:

You know those stories about clueless old people who get to their Gmail account by typing “Google” into Bing, clicking on Google in the Bing search results, typing “Gmail” into Google, and then clicking on Gmail in the Google search results?

I am reading about serotonin transmission now, and everything in the human brain works on this principle. If your brain needs to downregulate a neurotransmitter, it’ll start by upregulating a completely different neurotransmitter, which upregulates the first neurotransmitter, which hits autoreceptors that downregulate the first neurotransmitter, which then cancel the upregulation, and eventually the neurotransmitter gets downregulated.

Meanwhile, my patients are all like “How come this drug that was supposed to cure my depression is giving me vision problems?” and at least on some level the answer is “how come when Bing is down your grandfather can’t access Gmail?

  • My programming friends tell me that spaghetti towers are near-universal in the codebases of large companies. Where it would theoretically be nice if every function was neatly ordered, but actually, the thing you’re working on has three different dependencies, two of which are unmaintained and were abandoned when the guy who built them went to work at Google, and you can never be 100% certain that your code tweak won’t crash the site.
  • I think this also explains some of why bureaucracies look and act the way they do, and are so hard to change.

I think there are probably a lot of examples of spaghetti towers, and they probably have big ramifications for things like, for instance, what systems evolution can and can’t build.

I want to do a much deeper and more thoughtful analysis about what exactly the implications here are, but this has been kicking around my brain for long enough and all I want to do is get the concept out there.

Does this feel like a meaningful concept? Where do you see spaghetti towers?

Crossposted to LessWrong.


Happy solstice from Eukaryote Writes Blog. Here’s a playlist for you (or listen to Raymond Arnold’s Secular Solstice music.)

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Tip: use a digital packing list

Photo by Jean-Philippe Boulet, under a CC BY-SA 3.0 license.

I have a Google spreadsheet I’ve used for the past three and a half years when travelling. It has everything I regularly need on multi-day trips, space for extra items to add on specific trips, and checkboxes.

To pack, I lay out my suitcase and backpack, and throw things into them while referring to my list. Once everything on the spreadsheet is ticked off, I zip up my suitcases and am ready to go.

It’s very straightforward. You can add or remove items to the spreadsheet over time, and just clear off the extra items for each new trip.

Here’s my spreadsheet. You probably don’t need exactly the same things as me, so feel free to save your own copy and change the lists. Happy trails, friends.

The funnel of human experience

[EDIT: Previous version of this post had some errors. Thanks for jeff8765 for pinpointing the error and esrogs in the comments for bringing it to my attention as well. This has been fixed. Also, I wrote FHI when I meant FLI.]

The graph of the human population over time is also a map of human experience. Think of each year as being “amount of human lived experience that happened this year.” On the left, we see the approximate dawn of the modern human species in 50,000 BC. On the right, the population exploding in the present day.

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It turns out that if you add up all these years, 50% of human experience has happened after 1309 AD. 15% of all experience has been experienced by people who are alive right now.

I call this “the funnel of human experience” – the fact that because of a tiny initial population blossoming out into a huge modern population, more of human experience has happened recently than time would suggest.

50,000 years is a long time, but 8,000,000,000 people is a lot of people.

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Early human experience: casts of the skulls of the earliest modern humans found in various  continents. Display at the Smithsonian Museum of National History.

 


If you want to expand on this, you can start doing some Fermi estimates. We as a species have spent…

  • 1,650,000,000,000 total “human experience years”
    • See my dataset linked at the bottom of this post.
  • 7,450,000,000 human years spent having sex
    • Humans spend 0.45% of our lives having sex. 0.45% * [total human experience years] = 7E9 years
  • 52,000,000,000 years spent drinking coffee
    • 500 billion cups of coffee drunk this year x 15 minutes to drink each cup x 100 years* = 5E10 years
      • *Coffee consumption has likely been much higher recently than historically, but it does have a long history. I’m estimating about a hundred years of current consumption for total global consumption ever.
  • 1,000,000,000 years spent in labor
    • 110,000,000,000 billion humans ever x ½ women x 12 pregnancies* x 15 hours apiece = 1.1E9 years
      • *Infant mortality, yo. H/t Ellie and Shaw for this estimate.
  • 417,000,000 years spent worshipping the Greek gods
    • 1000 years* x 10,000,000 people** x 365 days a year x 1 hour a day*** = 4E8 years

      • *Some googling suggested that people worshipped the Greek/Roman Gods in some capacity from roughly 500 BC to 500 AD.
      • **There were about 10 million people in Ancient Greece. This probably tapered a lot to the beginning and end of that period, but on the other hand worship must have been more widespread than just Greece, and there have been pagans and Hellenists worshiping since then.
      • ***Worshiping generally took about an hour a day on average, figuring in priests and festivals? Sure.
  • 30,000,000 years spent watching Netflix
    • 14,000,000 hours/day* x 365 days x 5 years** = 2.92E7 years
      • * Netflix users watched an average of 14 million hours of content a day in 2017.
      • **Netflix the company has been around for 10 years, but has gotten bigger recently.
  • 50,000 years spent drinking coffee in Waffle House

So humanity in aggregate has spent about ten times as long worshiping the Greek gods as we’ve spent watching Netflix.

We’ve spent another ten times as long having sex as we’ve spent worshipping the Greek gods.

And we’ve spent ten times as long drinking coffee as we’ve spent having sex.


I’m not sure what this implies. Here are a few things I gathered from this:

1) I used to be annoyed at my high school world history classes for spending so much time on medieval history and after, when there was, you know, all of history before that too. Obviously there are other reasons for this – Eurocentrism, the fact that more recent events have clearer ramifications today – but to some degree this is in fact accurately reflecting how much history there is.

On the other hand, I spent a bunch of time in school learning about the Greek Gods, a tiny chunk of time learning about labor, and virtually no time learning about coffee. This is another disappointing trend in the way history is approached and taught, focusing on a series of major events rather than the day-to-day life of people.

2) The Funnel gets more stark the closer you move to the present day. Look at science. FLI reports that 90% of PhDs that have ever lived are alive right now. That means most of all scientific thought is happening in parallel rather than sequentially.

3) You can’t use the Funnel to reason about everything. For instance, you can’t use it to reason about extended evolutionary processes. Evolution is necessarily cumulative. It works on the unit of generations, not individuals. (You can make some inferences about evolution – for instance, the likelihood of any particular mutation occurring increases when there are more individuals to mutate – but evolution still has the same number of generations to work with, no matter how large each generation is.)

4) This made me think about the phrase “living memory”. The world’s oldest living person is Kane Tanaka, who was born in 1903. 28% of the entirety of human experience has happened since her birth. As mentioned above, 15% has been directly experienced by living people. We have writing and communication and memory, so we have a flawed channel by which to inherit information, and experiences in a sense. But humans as a species can only directly remember as far back as 1903.


Here’s my dataset. The population data comes from the Population Review Bureau and their report on how many humans ever lived, and from Our World In Data. Let me know if you get anything from this.

Fun fact: The average living human is 30.4 years old.

Wait But Why’s explanation of the real revolution of artificial intelligence is relevant and worth reading. See also Luke Muehlhauser’s conclusions on the Industrial Revolution: Part One and Part Two.


Crossposted to LessWrong.

From the Month of Halloween – The Devil’s Hoofprints

UPDATE: I actually posted this to the wrong blog. But I’ll leave it up as a reminder that October has started, and as a taste of what’s happening over at the Month of Halloween 2018 for the rest of the month.  Thanks for your patience!


The story tells of a chilly February morning in 1855. Smoke from the night’s fires puffing up through chimneys. Villagers across the countryside of Southern England woke up to a strange sight: trails of large hoofprints in the thick snow, in single file. These trails crossed the county back and forth, making about a hundred mile journey. The tracks crossed rivers, wound through cities, and most disconcertingly were seen going straight up houses, across the roofs, and going down the other side, without a break. What or who would have left this one-legged gait?

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This text and image is reproduced from Mysteries of the Unexplained, a 1982 publication of The Reader’s Digest Association

This is the first of a few Month of Halloween treats you’ll see drawn from Mysteries of the Unexplained. An early childhood staple of mine (originally making its appearance in my elementary school library), it contains a vast variety of mysterious news reports and anecdotes on a variety of subjects. The concept and some of the entries were borrowed wholesale from Charles Fort, a 1930’s writer who collected such stories as well and knit them together with his own bizarre philosophies. Mysteries of the Unexplained may be less original, but it at least pretends to maintain some objectivity, so there’s that.

(I’ve skimmed over some snippets of Fort’s writing and it reads like 1910’s newspaper journalism mixed with an advertisement for a salt lamp that purifies WiFi – which is to say, delightful.)

So as per everything that comes out of Fort and Mysteries of the Unexplained, I must clarify that this story possibly isn’t real. All of these accounts in this book came from someone and are written down as if infallible, and probably a large number of them were invented wholesale. Or are at least garbled versions of something real. We know that drawings and a description of the event were published in a London newspaper in 1855, and evidence was collected by a vicar in the area around the same time.

It was certainly enough to scare me in middle school. And it’s a good story, right?

Seattle-Oxford Petrov Day 2018

My friend Finan wrote up an account of the 2018 Seattle and Oxford Petrov Day Faux Nuclear Crisis.

Recognizing this, a couple of community members in Seattle whipped up a program to have mutually assured party destruction for Petrov Day. In the game you are told if the other party has launched and given time to retaliate if you so choose. Both parties successfully made it through several false alarms without nuking each other. It could be a testament to our general feelings of well being towards each other, and to lack of real incentive to nuke the other party–aside from protecting your own.

[…]

One of the partygoers in Seattle pressed the launch button at -1 seconds. 1 second past the end time, they were assuming the game was over and enjoying the humor of an actually quite low stakes game. The server and the Seattle computer were slightly out of sync, so although the game appeared over from the Seattle end, it was not according to the server.

“If our extinction proceeds slowly enough to allow a moment of horrified realization, the doers of the deed will likely be quite taken aback on realizing that they have actually destroyed the world. Therefore I suggest that if the Earth is destroyed, it will probably be by mistake. ” – Eliezer Yudkowsky


The “Big Red Button” approach to the day has only been around for the last 3 years, but it’s seen some adoption since. This is notably the first time that the button has been pressed at a party.

Further reading:

More on Petrov Day

There Is A Button

Book review: The Doomsday Machine

This book and the movie Dr. Strangelove are my two recommendations for learning about why you should still be concerned about nuclear war. The Dr. Strangelove post is coming soon. For now, The Doomsday Machine by Daniel Ellsberg:

…is a book about designing the end of the world as we know it, chronologically through Daniel Ellsberg’s career as a nuclear war planner. It’s well written, and Ellsberg makes a compelling hero.

He’s most famous for leaking the Pentagon Papers, government documents on the Vietnam War that contributed to Nixon’s resignation. This book came out of a second set of documents he photocopied and intended to release after his trial for the Pentagon Papers, but lost in an act of nature. Early on, he describes this second planned leak as the one that he fully expected to put him in jail for the rest of his life, and how he felt the loss of those documents as both a tragedy for the nation, and a blessing that allowed him to spend the following decades beside his wife. It’s the kind of thing that makes you glad you’re driving alone when your audiobook is making you tear up in the desert along the Washington-Idaho border.

But all this just helps – the real meat of the book is in the systems he describes.


Let’s talk about nuclear winter real quick. (My favorite line on dates.) Ellsberg puts this at the end, which makes sense chronologically, but it’d be burying the lede for an x-risk focused blog, so let’s get it out there now:

All of our plans for cold war were decided before anyone knew about nuclear winter. I feel like I should capitalize that – Nuclear Winter. It’s the hypothesized event where nuclear explosions cause fired in cities that launch so much ash into the stratosphere that it blots out the sun for months and makes it impossible for plants to grow, killing most human and large animal life. There’s uncertainty around the specifics, but its existence is generally agreed upon in the scientific community.

All US strategy during the early Cold War hinged on this idea of “general war”, an all-out nuclear exchange with Russia and China. General War included dropping enormous nuclear weapons on literally every single city in both Russia and China. Obviously, this is atrocious enough – this level of calamity was expected to kill something like 20% of the world’s population at the time, mostly from fallout.

But every time general war was mentioned, a little voice in my head yelled “nuclear winter!” – that the death toll is actually >90% of humanity, Americans, Russians, Chinese, and everyone else alike, unbeknownst to everybody at the time. My loose impression is that there’s not substantial reason to believe that nuclear war planning policy ever shifted to account for this fact.


Another quick takeaway: the US planned on making the first nuclear strike on Russia and China throughout the Cold War. Today we have a perception that the US only plans for using a second strike, but almost the entirety of planning material is based on the supposition of the US using nuclear weapons first. Again, there’s little reason to suspect this has changed now.


Through this book, I was repeatedly reminded of the Litany of Jai: Almost nobody is evil, almost everything is broken. The problems described in the book aren’t the result of insanity or complete carelessness, but instead a horrifying spider web of incentives, laid unwittingly by people with limited goals and limited knowledge. It’s a sinister net of multipolar traps. If you follow this web down, as Ellsberg does, you find yourself looking into the yawning chasm of a nuclear apocalypse – not built on purpose, but built nonetheless.

Let’s look at how some of these tangled incentives lead us there.


  • Branches of the military want high budgets.
  • Budget decisions are made based on intelligence from those branches.
  • Branches compete with each other for funding from Congress and other officials.

  • Various branches hugely overestimate enemy capacities.
  • E.g. the army reports extremely high Soviet ground force numbers.
  • The Air Force reports extremely high Soviet ICBM capacity.
  • Inter-branch coordination gets trampled.
  • There is no incentive for estimates or behavior that aligns with strategy or reality.

  • All military branches want to get in all-out war if/when it happens.

  • The Pacific Navy basically insists on attacking Asia alongside Russia in all cases, because they want to be involved and don’t just want to attack minor Siberian targets “on the sidelines” of The Big War.
  • Nuclear plans have Moscow area getting blanketed with hundreds of nuclear bombs from all sides. “Hundreds of nuclear bombs” is a phrase that here and elsewhere means “calamitous overkill”.

  • Military branches don’t want to listen to civilian politicians.
  • Civilian politicians are powerful decision-makers.

  • Information is concealed, including from the president (for instance, the JSCP, which is the detailed plan for all-out war).
  • Military leaders just don’t listen to civilians who outrank them (e.g. in moving ships with nuclear warheads illegally stationed in Japanese ports).
  • Civilian President Kennedy is politically obliged not to override poor decisions made by President Eisenhower, the famous military general.

  • Nuclear bomber pilots need to receive an authorized signal to enact plans for bombing Russian and Asian targets.
  • Air force planners want as little delay as possible in executing war plans once they get the order.
  • Air Force planners want to save time and effort.

  • Authorization codes are stored in plaintext in envelopes in each plane, are the same between every plane, and are rarely changed.
  • Any pilot who realized this could easily lead their base in a nuclear strike, and almost certainly trigger all-out nuclear war.
  • There’s no way in the target database to easily distinguish Russian and Chinese targets, so everyone at Air Force bases assumes that if they get the war order, they’ll just drop nuclear weapons on everyone. All Chinese cities were going to be destroyed under every nuclear attack plan, throughout the entire early Cold War.

  • Communications systems with Washington DC might be destroyed if Russia attacks the US with nuclear weapons first.
  • Communication systems between bases might be destroyed during a Russian attack.
  • Communications in general are pretty unreliable.
  • Everyone in the military chain of command, including the President, wants the US to be able to respond as quickly as possible to a Russian first strike.

  • Ability to initiate a nuclear war is secretly delegated down the chain of command in cases where bases are not in touch with Washington DC.
  • Contact with Washington DC is often unreliable – for hours every day on some bases in the Pacific.
  • Basically anyone in the chain of command is not just capable of, but entirely authorized to, declare total nuclear war most of the time.

This are not even every example. A story retold in many different forms throughout the entire book goes like this:

  1. Daniel Ellsberg learns about one of these outcomes.
  2. Ellsberg talks to some relevant officials and outlines a possible catastrophe.
  3. The officials go still, think about it, and say with concern, “That seems entirely possible.”
  4. Nothing changes, ever.

A possible solution for most of these spiraling incentives is a countervailing force, balancing the dynamic back away from “total catastrophe”. An actor, or an incentive, or something. Often, that does not exist – in the veil of secrecy surrounding nuclear war, any party with an incentive to care about the implied risk isn’t aware of the entire situation, and can’t unilaterally fix it if it exists. Ellsberg tries to repair these flawed systems when he notices them, but has little power to do so.

He talks about how he suspects that some leaders, including President Kennedy, never had real intentions of using nuclear weapons, but even if that’s true, the scenarios above suggest that presidential intent may have had little to do with the outcome.

Ellsberg’s knowledge of the situation drops off in the 70’s or so when he started doing other work. Are all of these nuclear war and control systems still like this?? Maybe??!! Certainly nobody was rushing to reform them throughout his long tenure with the government.

I don’t know what to do about any of this. This book illuminates the number of needles we somehow threaded in avoiding catastrophe since the start of the Cold War. Here’s where you can get it.

Nemesis club

[Cover photo taken by T. R. Shankar Raman, under a CC BY-SA 4.0 license.]

College season is starting soon and many, including me, will be returning to school soon. In that spirit, I thought I’d try and pitch the Eukaryotes Read Blog collective on an idea I never tried out in undergrad.*

On undergrad campuses, fall is a magical time. A lot of energetic new students have found themselves joining together, bereft of their previous friends and social networks, away from their family, drastically changing their lifestyles, and making it on their own in the world.

University campuses are well-equipped to help you make friends. There are plenty of campus-organized bonding opportunities in the first few weeks, and, if you’re like most people, you’ll end up making friends with roommates, classmates, other people on your floor, people you eat with in the cafeteria, etc.

What university campuses do not help you make are enemies.

Enemies are an important and time-honored form of human relationship. Beowulf had Grendel, Batman had Catwoman, St. Patrick had the snakes. But forming and nurturing early-stage enemyships can be difficult. Sometimes your enemy has killed your son and you’ve come to exact retribution, or you’re investigating the same murder, or you’re driving your enemy out of Ireland. But these opportunities are few and far between.

Don’t get me wrong. True nemesis relationships can happen early on in the college career. Maybe you were in a conversation with them about land management during your “get acquainted” circle in Orientation Week, and their opinions were so bad you wanted to punch them, and now they’re dating your roommate. But most people aren’t looking to make nemeses off the bat, and the stifling atmosphere of today’s college campuses – rife with memes like “be good to each other” – is simply not fertile ground for real adversarial relationships.

Without this release valve early on, nemeses tend to form painfully and explosively at random points throughout your college career, when you’ve already signed a 12-month lease with them. Eventually, they get increasingly awful, and you have to kick them out and suffer through a massive screaming fit that goes on all night when you have a six-hour O-chem lab the next day. Go fuck yourself, Amy.

I don’t want that. None of us want that. Enter Nemesis Club.

Upon joining Nemesis Club, you fill out a form. It asks for your name and class standing, and goes into what you’re looking for in a nemesis.

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A sample nemesis-matching survey.

Over the next week, organizers match you with another participant with similar needs and desires. Congratulations! You now have a nemesis. While you make friends, reorient your life, and try to ace your classes, this friendly face will be there to curse, shake your fist at, and plot against.

There’s a tricky balance here – society has poorly equipped us for the nuances of the comradversarial relationship, so the club has to be ready to help members navigate this. What if two nemeses have different assumptions about the seriousness of the enemyship? What if people are unhappy in their nemesis bonds?

It’s important that these bonds be navigated carefully. Ideally, these relationships will be satisfying. Maybe they’ll lead to academic success, grudging friendship, or romance. Maybe at the end of the college career, both nemeses will set aside their grudges and continue their lives as pals. Or maybe, if we’re lucky, these connections will blossom into life-long rivalries.

If anyone starts a nemesis club, or some variation of it, do let me know.


  • My ex did actually briefly try to start this. I declined to participate because he refused to take out “physical violence” as a club-endorsed nemesis activity (between willing participants). I admire his commitment to the aesthetic, but have to disrecommend this approach if you’re planning on starting your own, for reasons both of legitimacy and of gaining members that really don’t want to be involved with something that includes physical violence (which is to say: most people).

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.


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Eukaryote Writes Blog resource pages

The same way I sometimes get interested in a topic and go learn a bunch about it, I tend to collect useful links and resources.  So I’ve put some of those collections here. (The meta-resource page is linked on the sidebar.)

Current resource pages are: