Still Life with Eels

 kw: book reviews, nonfiction, ecology, fisheries, eels, poaching

When I was a child we visited tide pools in southern California, where my brothers and I would collect not only shells but a few living starfish, which we salted and dried for display. Sometimes we saw people using a putty knife to pry abalones off the rocks, which they would take home and cook to eat. I remember my mother telling us, "Don't take too many things. Leave some for others. If everyone takes these things, one day there will be none left." At the time I couldn't imagine that.

That was more than sixty years ago. About twenty years later the tide pools bore signs forbidding collecting. A few years after that they were closed; visiting was prohibited. Too much had been taken, and the sea life needed to recover. To date, the pools haven't been re-opened.

Now, living near the east coast, primarily the shores of New Jersey and Delaware, I find precious few seashells when we go to the ocean. Not being a fisherman, I don't notice the prevalence of fish, but others tell me that catching your limit takes longer than it used to. In certain seasons we do see fish in the rivers, but one thing I have never seen: eels. They migrate at night, and only in certain seasons. Anyway, if I am out at night, it is to do astronomy, not to look for animals. I am told that, during the seasons of migration, there are a great many eels, an uncountable multitude. Yet, fisheries reports indicate that what we see today is a tiny fraction of the numbers seen just one or two generations ago.

So, there are still eels. After reading Slippery Beast: A True Crime Natural History, with Eels by Ellen Ruppel Shell, I wonder, how close are we to exterminating them? The title of this image is the title of this review: Still Life with Eels. For the time being.

The fashion for eating eels comes and goes. Right now unagi (the Japanese word for Eel, and the currently popular name for eels-for-eating, particularly in sushi) is wildly popular. So popular that around half the unagi eaten around the world, particularly in Japan and America, originated with poached elvers.

Why do I say "originated with"? Eels have an astounding life cycle, more like a butterfly than a vertebrate. In early works of natural history, several different species were named, but they were all eventually found to be stages in the life of the eel.

This diagram, from ResearchGate, is worth considering in detail:

Begin at upper right, with spawning. This has never been seen, so the drawing is speculative. For American and European eels, spawning takes place in the Sargasso Sea. The eel larva is at first a tiny transparent thing a lot like a flatworm, called a leptocephalus, which means "small head". Nobody knows what they eat. Once they get a little bigger they become rounder but remain transparent, so they are called "glass eels". In this form they migrate from somewhere in the Sargasso Sea to the mouth of a river, a distance of 2,000 to 4,000 miles. Near the end of this journey they transform into elvers and begin to migrate upstream. Whether they go fully into freshwater or remain in an estuarine environment, they transform again into yellow eels. After a few years, for males, or up to thirty years for females, they become adults as silver eels and begin to migrate downstream. From this time they do not eat until they reach the Sargasso Sea to spawn. After spawning, the emaciated adults presumably die and sink to the ocean floor, or get snarfed up by carnivorous fish on the way down.

American and European eels haven't been successfully induced to spawn in captivity. Hormone treatments have rarely made a female produce eggs, and the eggs can be fertilized by suitably treated males, but the larvae don't live more than a matter of hours or a few days. However, the Chinese have perfected methods for raising river-caught elvers to adult size. This has led to a still-growing trade in elvers. The price has followed a roller-coaster as the market has shifted over the decades. The price of elvers is in the thousands of dollars per pound range at present. Eel dealers carefully, but very quickly!, send them to the Chinese eel farms. The adult eels are re-imported to America or Europe.

Elver prices are so high that poaching abounds. The Fish & Wildlife Service in America have been able to make a little dent in the trade, but are nowhere near stopping it. This is complicated by treaties with Native American tribes, which assert their rights over the fisheries in their territories. However, in Maine in particular, where the book is focused, the quantity of elvers fished by non-Natives, under licensed quotas, is many times greater than the Native American fishery. The fact remains that the biomass of American eels is probably less than 1/10th what it was thirty or forty years ago, and much, much less than it was in pre-Colonial times. Like nearly every fish stock worldwide, only a few percent remains. Humans love to eat fish, and we are loving them to extinction.

Ms Shell writes of the actions and attitudes of many players and stakeholders in this drama, including an American who is usually just known as "Sara", who has succeeded in setting up an eel farm in America, where many had failed in the past. Also including some of the eel experts who happen to also be leading poachers…or they were, prior to being prosecuted and in some cases, jailed. There are still too many prominent folks who say there are more than enough eels. To anyone who isn't profiting from the trade in elvers and eels, this is clearly not so. The book ends in ambiguity and hope.

Before closing, I need to correct a misapprehension by the author about sushi. Like many Americans, she thinks of sushi as raw fish. That is actually sashimi. Sushi, broadly speaking, is "rice plus seaweed plus lots of other things, served cold." Some of those "other things" include a few kinds of sashimi. At a sashimi restaurant they don't usually serve sushi, just a few kinds of fish with rice on the side and other side ingredients. Even there, eel is not served raw. Very few kinds of fish are served raw, and shellfish such as shrimp, and also octopus and squid, are always cooked. 

At a sushi restaurant, the raw fish is usually one of several species of tuna, and in American sushi restaurants salmon may also be served raw. I haven't seen salmon served raw in Japan (but I haven't been there for several years, so maybe that has changed). The reason for this care is parasites. Tuna and other predatory fish may have parasitic worms in them, but they are large enough for the sashimi chef to see and to remove. Many kinds of fish have smaller parasites that are harder, or economically impossible, to remove (it's usually done with a hook similar to a crochet hook). Still, the process isn't always perfect. At an Asian buffet restaurant in America that includes sushi, I never take the pieces with raw fish; I don't want to need to be dewormed! Finally, the kinds of sushi called "rolls" usually include vegetables and strips of scrambled eggs, and often contain no fish. A "California roll" has eggs, carrots, avocado, and mushrooms. No fish. So, while unagi sushi is very popular, not many know that the eel is always cooked. It isn't safe to eat raw.

Greenland was once green

 kw: book reviews, nonfiction, geoscience, ice science, ice drilling, ice coring, greenland, ice caps, climate change

This is the rig
That drilled the ice
Down into the soil
That proved the land
Was free of ice,
Less than a million years ago.

The climate then
Was like today's
But CO₂
Was half so much.
It shows that it
Could happen again:
It's really up to us.

When the Ice is Gone: What the Greenland Ice Core Reveals About Earth's Tumultuous History and Perilous Future by Paul Bierman concludes with a prognosis for human civilization: Get ready for tremendous upheavals, no matter what we do; we can easily make things worse, or with effort mitigate the pain but not eliminate it.

Dr. Bierman has worked in Greenland and around the world. He brings us the history of Greenland, and particularly the US/Danish military efforts to establish DEW-Line-extension radar stations and under-ice military encampments during the Cold War.

Don't know what is/was the Distant Early Warning Line? I grew up knowing about it, plus the two Lines closer in, that were intended to detect ballistic missiles coming over the polar regions from Russia. We also had periodic tests of the radio warning system that a DEW Line alert would trigger. We would then have 15 or so minutes to prepare for nuclear hell to rain down. We practiced in school, to duck under our desks and hold our legs ("and kiss your ass goodbye," we said under our breaths).

Ice is hard to live on or in. A light touch is necessary, so the Inuit and other northern peoples manage it. A military is not known for having a light touch. Ice at any temperature above -40° (either C or F; that's the crossover temperature) slowly flows under pressure. The warmer it is, the faster it flows. The tunnels and other under-ice structures needed to be maintained by crews of ice trimmers because the walls close in at least several inches yearly, and the floor heaves, etc., etc. The Army put a lot of effort and buckets of money into studying the properties of Greenland ice (and ice in other places, though they are not the focus of the book). One effort was deep drilling.

It took a few decades to learn how to drill into the ice and extract a core. Drilling makes friction which causes heating, so there needs to be a "drill fluid" that is at least as dense as ice, to keep the drill hole from closing around the drill shaft and capturing the drill string and bit. If that happens all you can do is move over and start a new hole, with new equipment. Various drill fluids were used. The most effective were based on diesel oil with various additives to make it more dense and less corrosive to the equipment. To this day, if you go to one of the ice core storage facilities, such as the one in Copenhagen, the cores stink of diesel oil and other noxious materials.

Camp Century, situated atop almost a mile of ice, housed the first drill rig, shown above, to extract ice cores, not only to the base of the ice, but tens of feet into the sediment beneath, which at the time was a type of permafrost called "permacrete": just as hard to drill as concrete, but with ice binding everything together. The story is told in loving detail, and it was a truly heroic effort. The hole was completed in early July 1966.

Here a mystery intervenes. For several decades, a dog-in-the-manger scientist stingily parceled out bits of ice core to scientists he favored, and the below-the-ice material was ignored. Finally that material was discovered among some odds-and-ends sent to an ice laboratory in Copenhagen, and in 2019 the author and a large collaboration of scientific teams were able to get portions to study. One finding in particular shook them up.

One of the researchers working with Dr. Bierman noticed dark bits that didn't look like mineral grains. Under a microscope, they were seen to be plant matter. Gathering more was easy. Melt a few grams of permacrete, centrifuge, and wait. Little dark bits will float to the top. Botanists were able to identify some of the species represented. It proved that the land had once been ice free, not nearly as long ago as everyone thought. A lot more work finally demonstrated that the ice-free period ended a bit less than half a million years ago. Other measurements, such as isotope ratios from the water in the permacrete, showed that the average temperature during the ice-free time was similar to what it is today on the coast of Greenland at that latitude, but that atmospheric CO₂ was about 280 ppm; it is 420 ppm now. Camp Century is more than 100 miles inland of the present edge of the ice.

There are multitudes of other findings, but this is the smoking gun. The ice cap of Greenland is more fragile than we thought, and at least 2/3 of it melted away for some period before snow and ice accumulated again. If all of the ice in Greenland were to melt, that alone would add 24 feet, or about 7.5 m, to the depth of the ocean. Two-thirds of that would result in 16 feet, or 5 m.

The last chapter of the book describes some consequences of the sea rising by 5 m. The timeline is instructive, though. That sea level rise will take at least a couple of decades. A lot depends on politics and business, as the author acknowledges. Here's my take on that.

Nearly all of the leaders in Washington are at one extreme or the other. Genuine Democrats and Republicans rarely rise to national leadership. An often-misquoted Bible verse begins, "The love of money is a root of all evils…" (1 Tim 6:10). Note that it says "a root" not "the root." There are other roots. A close second root is the lust for power and control. Whether far Right or far Left, the Totalitarians of both political parties want to exert control. Over us. Mitigating the climate crisis is not in the interest of either of them. The situation itself, and exaggerating its direness, is their weapon against us. The more moderate national leaders are utterly swamped by the control-mongers. In the world, the top five carbon emitters are:

1. China, 34% of total, 9.24 Ton/y/person
2. USA, 12% of total, 13.8 Ton/y/person
3. India, 7.6% of total, 2.07 Ton/y/person
4. Russia, 5.3% of total, 14.5 Ton/y/person
5. Japan, 2.4% of total, 7.54 Ton/y/person

Those five add up to 61.3%. If China could "catch down" with Japan on a per person basis, its percentage would go from 34% to just under 28% of the current total, or 29.6% of a total amount that is 93.7% of today's total. That difference would be nearly half of total US emission. China is the elephant in the room.

I wanted to go into much more detail, but I decided this is not where that belongs. I would add only this: our only bridge to a future without fossil fuels, or nearly so, is nuclear fission. Nuclear fusion is too far in the future to be of any help. As it happens, I've recently learned that China is building experimental Thorium reactors, perhaps hoping to replace Uranium. Apparently Thorium "burning" produces less (or less dangerous?) radioactive waste. Similar research is starting up here also. I need to do more research, but it is a hopeful sign.

All these things have long lead times. Part of the problem is regulatory. With control freaks in charge of both sides of Congress, I am not sure they will be any help. I hate to end this review on a downer, but at present, I see a long tunnel ahead before any light might appear.

This book is required reading for everyone, particularly voters.

Re-visiting the Jabberwock

 kw: ai experiments, artificial intelligence, generated art, poems, illustrations, photo essays

A little more than two years ago I used Dall-E2 to illustrate the poem "Jabberwocky" by Lewis Carroll. Now that there are four high quality generative art sites that I use, I experimented with bringing just the Jabberwock itself up to date. In nearly all cases the programs relied on dragon imagery.

This is a wide-view redraw by Dall-E3 of one result of my second prompt. It's a little less sinister than the results of the first prompt. Here is how it went:

Dall-E3: "The Jabberwock"

All are fierce dragons in near-silhouette. All but one are shown against the Moon.

Dall-E3: "The Jabberwock as a pastel painting"

The word "pastel" has evoked a less sinister atmosphere. We find flowers and butterflies and in one case the dragon is actually smiling. Now that Dall-E3 can recast a square image into one with a wider aspect ratio I had it re-do the second image, on upper right. Note that the wide image at the top of the post has elements from all four images. By experimentation I found that, while re-formatting each image produces a different result, repeating the re-format step on a particular square image yields exactly the same wider image as the prior re-formatting on that image. The re-formatting offerings are square and 4:3, but the resulting wide format images are actually 1792x1024, with a ratio of 1.75:1 or 7:4. That's close enough to 16:9 (HD) that it takes just a little cropping to produce a 16:9 image (1792x1008), which can be put through Upscayl to make it big enough to use for an HD wallpaper.

I went on to try Gemini (formerly Bard), which now uses Imagen 3 to make images, and only one at a time. The 3-panel pasteup here is from three prompts:

• An image of the Jabberwock from the poem Jabberwocky
• An image of the Jabberwock from the poem Jabberwocky as a pastel painting
• A full-body image of the Jabberwock from the poem Jabberwocky as a pastel painting

Adding "pastel" definitely produces a less fierce result. The third item is the least dragonlike. Unfortunately for much of what I do, one cannot outpaint with Gemini, and asking for "wide format" or "HD ratio" gets ignored.. Maybe such options are available with Gemini Plus, but I haven't yet signed up for that.

I looked next to Leonardo AI, which is the most recent tool I've used. It has many options and variations. Here I'll present four sets of results. Leo produces images in a horizontal string. I rearranged these as 2x2 rectangular arrays. The original images are 1368x768 pixels, not quite a 16:9 ratio (though it's labeled as such in the menu), but 171:96.

Leonardo: "The Jabberwock from the poem Jabberwocky as a pastel painting", Portrait, Cinematic

The "eye" in each image is a flag that indicates it is public. One needs a paid subscription to make private images. Though these are all dragonoid, some of them have no wings. This prompt without "pastel painting" produced much darker and fiercer results.

Leonardo: "The Jabberwock from the poem Jabberwocky", Concept Art, Stylistic Illustration

These were the most colorful results of all my experiments with Leo. The "Concept Art" setting pushes such limits. Though these have fierce expressions, they are rather cute.

Leonardo: "The Jabberwock from the poem Jabberwocky", Graphic Design, 3D

These are quite dark and sinister, but not as dark as some results.

Leonardo: "The Jabberwock from the poem Jabberwocky as a pastel painting", Graphic Design, 3D

The addition of "pastel" has lightened things up a lot, both in visual and emotional tone. It's interesting to note that these critters all have multiple tails. I count lavender as the least threatening hue.

Finally, I turned to Playground, which was once the most flexible of the tools. Since they shut down Canvas mode in mid-September, it has been harder to use all the filters and other options. The free version is slow, and sometimes times out. Playground also presents a horizontal string of four images, which I rearranged as a 2x2 matrix. I set aspect ratio to 4:3 mode, which one would expect to yield 1.333:1 images; the actual images are 1216x832, about 1.46:1 or 19:13. For the two Playground mode where this was possible I used the Watercolor filter, considering it similar to saying "pastel painting". Playground has three image engines available.

Playground: "The Jabberwock from the poem Jabberwocky", Stable Diffusion XL, Watercolor filter

The background architecture in items 1 and 4 adds interest. SDXL is now considered a "traditional" or even "retro" engine. I also had the option to set a "faithfulness to prompt" setting, and used 4 ("more free").

Playground: "The Jabberwock from the poem Jabberwocky", Playground v2.5, Watercolor filter

As I've frequently observed, PG25 is edgier and typically a bit darker.

Playground: "The Jabberwock from the poem Jabberwocky", Playground v3.0, no filter

Wow! What a difference from all the others. PG30 is apparently more attuned to "poem". It even tried to write one (second image), though the character strings are illegible. The third image looks like it could be a bookplate. PG30 is now the most colorful and creative engine Playground has to offer; it was introduced earlier this year.

I must say a word about limits and conditions in the free versions I use.

• Dall-E3 lets you run 15 prompts daily, and each prompt yields four images. There appears to be no charge for re-formatting an image.
• Gemini has no explicit limit, but when I asked, it told me that sending many image requests in rapid sequence could slow things down.
• Leonardo AI gives you 150 points to use in a day. However, that doesn't mean 150 images. There are about ten (the number occasionally varies) Presets. Two of them "charge" 10 points per prompt, and in the free version, you always get four images per prompt. One of them is 24 points (on a few occasions I saw it was 104 points). The rest are 14 points. So it is possible to generate fifteen 10-pointers, or ten 14-pointers plus one 10-pointer, or six 24-pointers (with 6 unusable points) per day. A "day" resets to the time you created your account, which is 8PM for me. You can outpaint and inpaint with Leonardo, for variable numbers of points per action.
• Playground originally let me generate 150 images daily, up to four at a time. More recently the limit has been 50, and at present I don't see an indication of how many images I have left in a session.

Paying for a subscription to Playground or Leonardo AI opens up greatly expanded limits, and added functionality. I haven't tried all the combinations of either of these programs, but one day I may pick one of them to subscribe to. I have lots else going on in my life, so I don't see much need to do so at the moment.

An interplanetary thriller

 kw: book reviews, science fiction, space fiction, moon, mars, mysteries

The Oxygen Farmer by Colin Holmes is an upgrade from the Space Opera subgenre of science fiction. It is set in space, mostly on or near the Moon, and there is plenty of opera, of the dysfunctional-family kind. The novel is a thrilling mystery that I can't say much about without being a spoiler. I'll confine myself to some of the ideas that interested me. 

This image is the fruit of a long negotiation with LeonardoAI. It's intended to evoke generic "space opera".

The setting is in late 2077, plus about a year; things happen fast in scifi spacetime. The first time I saw children using cell phones (flip phones in the late 1990's) I remarked, "Give it another generation or so, and they'll install a phone in the bone behind the ear of everyone, that is biologically powered and voice activated." The year 2077 is closer to two generations future, and everyone wears a "wristy", a souped up smart watch. It is used for "everything", the way smart phones/watches are used today in China and much of Europe…the US has some catching up to do. If you ask Ray Kurzweil, he would say that such a device will be long out of date by 2077.

There's an interesting dichotomy of thought. The protagonist/hero, Mil, (he really does some heroic stuff) was born 1/1/2000, so he's pushing eighty. Living and working on the Moon for half his life already, he thinks of himself as superannuated, too old to know better than to keep working. Yet the norm on Earth is to live to around the age of 140, and while it isn't stated, there's the implication that retirement before age 100 is unusual.

Chemical rockets are still used, but seem to be more efficient, shortening trips between Earth and Moon, and soon enough, Mars. Someone remarks that visiting the Moon is getting too much like visiting Cleveland; considering it's roughly a full day of travel, that would be starting from Melbourne, perhaps.

The super-rich guy behind a lot of what goes on is named Amon Neff. He's apparently the first trillionaire; the author trusts us to recognize that monetary amounts can be thought of in 2024 terms, even though inflation in the coming 53 years is likely to make today's trillion into 5-10 trillion (or much more) in the currency of 2077. I found it interesting that Neff's age in 2077 places his birth year near that of a modern near-trillionaire with two 4-letter names. But "our" super-rich guy isn't much like what Neff turns out to be.

Space and radiation medicine has apparently advanced a lot. Mil, even after a long lifetime of more-than-ordinary radiation exposure, survives an event that doses him with 4 Grays. A Gray is a unit of acute radiation absorbed, and for reference, 5 Grays leads to death within two weeks about half the time…for an initially healthy person. When a fella already has one foot and three toes in the grave, it takes a lot to keep his ticker ticking.

I like the concept of oxygen farming. The infrastructure needed to make practical use of such a resource is well thought out. The electrochemistry, and solar energy harvesting to run it all, are presented sketchily at best, which makes sense because they aren't on the plotline, but are stagecraft.

The author surrounds his characters with lots of equipment in various stages of wearing out, usually for dramatic effect. Set aside the Moon as the environment, and it is a lot like the life of  ranchers I know, who excel at keeping old trucks and tractors working decades past the expiration of their warranties.

The book's a fun read.

Had a good chat with your houseplant today?

 kw: book reviews, nonfiction, science, botany, research, plant consciousness, communication, signaling, plant movement, plant intelligence

In the human realm, "talking to the animals" like Dr. Doolittle is fictional. In the plant realm, it may be commonplace. What constitutes "communication"? There is more philosophy than science wrapped up in any attempt to answer that question. Even more so for the words "consciousness" and "intelligence". We may not have definitive answers in the next few decades, and perhaps we never will. In The Light Eaters: How the Unseen World of Plant Intelligence Offers a New Understanding of Life on Earth, author Zoë Schlanger doesn't provide the answers, though some of those she interviewed offered nascent attempts at doing so.

The eleven chapters of Light Eaters delve into several strains of research that are on the verge of redefining what a "plant" really is and re-settling our understanding of the rôles plants play in the biosphere. As we find from numerous lines of research, plants have several routes of plant-to-plant signaling: chemical, electrical, acoustic, and possibly bacterio-genetic. Plants discriminate. They are found to send differing signals to siblings versus non-siblings of the same species; plants of one species can also "eavesdrop" on signals of another species. Furthermore, plants send signals intended for animal species! An example of the latter is the plants that emit a pheromone that attracts a certain species of parasitic wasp when a caterpillar that the wasp parasitizes begins chewing on the plant's leaves. It's rather like a youngster who gets attacked and calls on his older brother for help, but in this case the "older brother" is a different species. Plants getting chewed on also emit other volatile chemicals that alert nearby plants, which respond by altering the chemistry of their leaves to be distasteful or even toxic to the caterpillar.

These are examples of chemical signaling. Other stressors such as drought result in plants making tiny clicking noises as low-pressure bubbles collapse; it is similar to the popping knuckles most people engage in. It's hard for me to determine what kind of research showed other plants responding to these barely audible sounds, but Chapter 5, "An Ear to the Ground" presents the evidence. 

What about electrical signals? Within a plant, it has been found that cutting a leaf initiates a wave of electrical activity that sweeps through the plant. These images of a small plant leaf, taken just before a scissor cut, then one second after, and then seven more seconds later. The plant had been grown from seed containing engineered genes that cause the calcium channels (every cell has them) to trigger Green Fluorescent Protein (GFP) when they emit or pass an electrical signal. The electrochemical signal moves as a wave through the whole plant. These images were clipped from this video. If the video doesn't work (they can be ephemeral), search for "gfp plant signaling". This is just one of several.

As the narrator in the video explains, the signal moves through the whole plant in about a minute along the veins, and spreads from the veins throughout all the plant's tissues at a slower rate.

This got me thinking. We know that while an electrical signal in a metallic wire is very fast, roughly the speed of light, the electrochemical signals in animal nerves are much slower. I had the neural conduction speed measured in my arm one time, after an injury. It was 60 m/s, which is normal. The fastest neural conduction speed in mammals is about twice this, and some nerves, where speed is less critical, are as slow as the range 2-5 m/s. Plants don't have nerves; at least none that we can recognize. But the veins seem to have a similar function, albeit slower, in the range of about 1 mm/s. That is between 2,000 and 120,000 times slower than animal neurons.

Put that together with a statement later in the book. The author had a hint of an idea (one I was toying with as I read): What if we think of the entire plant as a brain? She asked one scientist, who said, "I think you're right. I just don't talk about it." Let's speculate a bit. If you get jabbed in the leg with a pin, you'll react within about a quarter of a second. In the little plant shown in the video, which is about 10 cm across, the signal "I've been cut!" reaches the whole plant in less than two minutes. The "reaction" of the plant is to begin to synthesize noxious chemicals in the leaves, which takes a few hours. From this we can extract a couple of ratios:

1. We can infer the signaling time between your leg and brain as about 1/30 second. If signaling through the plant took 100 seconds, the ratio is 3,000:1.
2. Your physical flinch and "Ouch!" begin after about 1/4 second, while chemical synthesis in the plant gets underway in an hour (3,600 sec), for a ratio of 14,400:1.

If, then, the whole plant is, or contains, a distributed brain, it runs several thousand times more slowly than an animal brain. This is in accord with the rate that twigs grow on many woody plants, compared with the rate of animal motions. Animals move at about "the speed of gravity", by which I mean that rapid animal motions, such as swatting at a fly, happen at speeds similar to that of an object dropped a meter or so. Time-lapse videos of plants either growing or "doing" various things, such as the "reaching" of bean tendrils for something to cling to, show their motions to be hundreds to thousands of times slower than animal motions. It seems plausible that, if plants "think", they do so correspondingly slowly. While we cannot consider plants to have a nervous system, perhaps a term such as "signal conduction system" or "signal transduction system" can be used.

Do they think? Plant "intelligence" has been a fiercely contentious issue for decades, and that doesn't seem to be slowing down. Focusing on just three things: speed of motion, speed of communication, and speed of reaction, I (and, I think, Ms Schlanger) consider plants to be doing most things animals do, but on a time scale around 10,000 times slower. If we learn to talk to plants, and to hearken and understand what they are saying, we'll need enormous patience. Perhaps a translating SI (simulated intelligence) application can craft a signal at a rate the plant can accept, patiently receive its reply, and signal a human (who is doing something else in the meantime, because it could be hours) to come "read" the response. Even if the human then requires several minutes to decide what to say next, to the plant, the signal coming back, through the app, seems to begin almost instantly.

Finally, do plants see? Plants that mimic neighboring species hint that this is so. How can a South American vine Boquila take on the appearance of at least a few dozen other plants, just by growing in the vicinity? Moreso, if part of this vine is near one kind of plant, and another part is near another, it mimics both! To a lesser extent Mistletoe plants do something similar. One researcher believes the "signal" received by a Boquila plant is not visual, but bacterio-genetic, some kind of genetic signal from the neighboring plant's cloud of symbiont bacteria. All animals and all plants are inhabited by and surrounded by their own microbiome. Each breath we exhale contains members of our microbiome. Your own bacterial "envelope" changes every time you make a new friend and begin spending lots of time with him or her. The author finds a visual hypothesis more parsimonious, and I agree. Plants do have photoreceptors; they are chloroplasts. There are also other colored bodies in plants, in colors other than green. They may also receive light as well as reflect it, or they may provide color filters for chloroplasts to detect colored light. The author points out that this is similar to cuttlefish, which have color-blind eyes, yet they can still mimic the patterns and colors of the surface they are sitting on, probably because their whole skin surface is covered with photoreceptors that must provide the color signal.

I suggest a "red hat" experiment. Start with a number (12 at least) of plants that are wired to detect stress. Once they have recovered from being wired the experiment begins. Whenever the person who cares for the plants wears a red hat, that person also takes a snip from the end of one leaf of half the plants, chosen by a prearranged formula, and let some of the plants never be snipped. Let the interval between snipping incidents be a few days. I conjecture that after a few weeks at most, the plants will all react whenever the caretaker enters wearing the hat, before any snipping is done. This should indicate something visual on the part of the plants. It is likely that the never-snipped plants will react differently from the others. However, it is always possible that the caretaker is in a different mental state on "snipping days", and this causes an airborne chemical signal that the plants can detect and react to. I am not sure how to control for that.

Plants are fascinating, even more so now to me, after reading this book. What a great read!

-----------------------

A couple of quibbles and contentions:

1. On p 39 the author coined the adjective "Descartian", referring to René Descartes. The adjective "Cartesian" already exists and is easier to say.
2. On p 156 we read, "In the United States alone, as many as 11,000 farmworkers are fatally poisoned by pesticides each year, and another 385 million are severely poisoned…". 'Scuse me, but the entire US population is about 360 million, of whom two million are farmworkers. The CDC states 10,000-20,000 "poisonings" without saying how many are fatal. Sundry reports are all over the place. One appears to be the author's source for 11,000 fatalities yearly, while another states that 60,000 nonfatal incidents occurred in five years, or 12,000 per year. The author needs to dig a bit deeper.

American spiders now?

 kw: blogs, blogging, spider scanning

In recent weeks the number of daily views of this blog settled back to fewer than 100, typically 70-80. Today I noticed a big bump. Checking the 24-hour view, I see that whatever is going on is continuing:

It's about 10pm just now. Things started taking off at 4am. Here are the locations:

The top source is the US! How about that!! For the past year or so, when views skyrocketed, either Singapore or Hong Kong led the charge. Not this time. I wonder if the spider source is using a VPN…

Readable science writing

 kw: book reviews, nonfiction, science, nature, science writing, nature writing, anthologies

Science and technical writing are notable for being unreadable. Fortunately, some articles are well written and readable. Some. For The Best American Science and Nature Writing 2023, edited by Carl Zimmer, the editor and his helpers managed to find twenty articles and essays that are readable and informative, in a range of technical disciplines.

I don't intend to survey the whole book. This is more of an accolade than a full review. I used Dall-E3 to generate a number of images intended to evoke "science writer." I like this one best. For the sake of this volume, I chose a female writer because 13 of the 20 articles are by females, although one is amidst a transition to outward maleness.

In the Foreword the editor makes note that more and more of modern science and nature writing has a political flavor. This is not surprising. Many of the articles in this volume are based in research related to climate change, which has been overly politicized to the point that few granting entities are willing to fund work that is not explicitly supportive of the "mainstream view," no matter that it is very far from being the "settled science" that certain loud voices claim. While I am at it, I must say that two of the articles are not about science at all but are personal testimonies regarding the consequences of the political climate, related primarily to issues of gender and morality. While they are voices that deserve to be heard, they have no place in this volume.

My second favorite generated image is this one, of a naturalist in the field. Boots on the ground are sorely needed to winkle out all the effects of the increase of both temperature and atmospheric volatility. Articles about the changing populations of certain butterfly or frog species evoke the scientific spirit: "Why has this changed? and how?" 

Science is conservative, in the sense that new things, new ideas, new hypotheses must prove themselves. It is unscientific to accept a new "explanation" that lacks solid evidence. Environmental stewardship is also a conservative value. Social conservatism is different from political conservatism. Let us remember that prior to the Twentieth Century the conservatives (for example, the Tories in England and the Democrats in the US) were pro-royalty, pro-aristocracy, pro-feudalism, and pro-slavery. The constitutional liberals (who these days are called "conservatives" by leftists), particularly the leading Christians, led the way to abolish slavery. Their contention that all the "races" were equally human was based on scientific studies, on scientific conservatism, as much as on religious grounds. We are amidst a struggle to determine where the boundaries lie between scientific study of climate and political proclamations based on sketchy understanding of science.

Scientists would do well to learn better writing. For the moment, those who write well deserve appreciation, and this volume provides a little of that.

Not exactly a poison primer

 kw: book reviews, nonfiction, poisons, poisoners, women, history, short biographies

After reading The League of Lady Poisoners: Illustrated True Stories of Dangerous Women, written and illustrated by Lisa Perrin, I've become a little leery of having tea with a new acquaintance. These days there are more toxins than ever before that are odorless and tasteless, and some have long-delayed effects.

This book is a Wild Card selection. Although I usually peruse the Science section and a few others, including Science Fiction and Short Stories, I'll often poke around other Nonfiction areas of the library to see what might be interesting. I couldn't pass this one up.

Poison is considered a woman's weapon, but more poisonings are actually committed by men. However, since by far the most murders are committed by men, it stands to reason that even a less-common method men use would outnumber the primary method women use to be rid of an abusive spouse, terrifying neighbor, or inconvenient relative.

Most of the women presented here can be counted as serial killers. Having succeeded in one murder, a person finds that a line has been crossed, and follow-on killings result, often to cover up the first. One of the earliest was Cleopatra, who poisoned one of her brothers, and who tested poisons' effects on prisoners. She eventually poisoned herself and her two handmaids (the asp story is a fabrication; death by snakebite is agonizing. She would have mixed a poison containing lots of opium, to die painlessly).

Much more recently, possibly the most prolific poisoner was "Jolly Jane" Toppan. She confessed to 34 killings, but it is likely the total number of her victims exceeds 100. She worked as a nurse, which gave her access to her favorite toxins. She was almost unique in her obsession with watching others die by poisoning. Others were prolific as providers of poisons to others, such as a midwife in Nagyrév, Hungary; in the early 1900's she supplied arsenic to abused women, who collectively were called the Angel-Makers in later news accounts. Forty men are known to have died, making this practically an epidemic in the village. There may have been more.

Modern forensic methods can detect almost all known toxins. Arsenic is easy to test for. Fortunately, so is Fentanyl, which is taking tens of thousands of lives yearly in the US, nearly all by overdose. It is not known (and hardly anyone is looking) how many Fentanyl deaths are more deliberate.

Although one section describes common poisons and common poisonous plants and animals, nobody will gain knowledge how to use poisons from this book. The author's aim is the stories of the women themselves, and the sociology of their surroundings. In many cases it is easy to conclude, "Yes, so-and-so deserved to be killed." All too frequently, however, a first killing led to others. Killing is the ultimate slippery slope.

The author is a gifted illustrator. I've included just one random bit of her art. The main color used throughout is a sickly green color, the classical hue of poison. Most of the stories are illustrated by a full-page portrait. These are large and detailed (the pages are 7"x10"), so reproducing one here would probably violate the principle of fair use.

You can see much more of her art at her website.

As good as the writing is, and as fascinating as the stories are, with time I expect the lingering dread to fade. I don't want to go through life fearing new acquaintances.

Will our children become cyborgs?

 kw: book reviews, nonfiction, futurism, artificial intelligence, the singularity

I started these book reviews just after The Singularity is Near, by Ray Kurzweil, was published. I am not sure I read the book; I think I read some reviews, and an article or two by Kurzweil about the subject. Nineteen years have passed, and Ray Kurzweil has doubled down on his forecasts with The Singularity is Nearer: When We Merge With AI.

As I recall, in 2005 The Singularity referred to a time when the author expected certain technological and sociological trends to force a merging of human and machine intelligences, and he forecast this to occur about the year 2045. The new book tinkers with the dates a bit, but not by much. One notable change: in 2005 he considered the compute capacity of the human brain to be 10¹⁶ calculations per second, with memory about 10¹³ bits (~100 GBytes: woefully small by modern estimates). His current estimate is 10¹⁴ calculations per second, and I don't recall that he mentioned memory capacity at all.

I am encouraged that Kurzweil doesn't see us at odds with AI, or AI at odds with us, but as eternal collaborators. I'll be 98 in 2045, and I am likely to be still alive. Time will tell.

I am an algorithmicist. I built much of my career on improving the efficiency of computer code to squeeze out maximum calculations-per-second from a piece of hardware. But a "calculation" is a pretty slippery item. In the 1960's and 1970's mainframe computers were rated in MIPS, Millions of Instructions Per Second. Various benchmark programs were used to "exercise" a machine to measure this, because it doesn't correlate cleanly with cycle time. Some instructions (e.g., "Move Word#348762 to Register 1") might consume one clock cycle, while others (e.g., "Add Register 1 to Register 2 and store the result in Register 3") might require six cycles; and the calculation wasn't really finished until another instruction put the result from the Register back in a memory location. The 1970's saw a changeover from MIPS to MFLOPS, or Millions of FLoating-point Operations Per Second, to measure machine power. Supercomputers of the day, such as the CDC Cyber 6600 and the Cray-1, could perform "math" operations such as addition, in a single cycle, so a machine with a cycle time of 1 MHz could approach a rate of 1 MFLOPS (Note: The Cray-1 and later Cray machines used "pipeline processors", a limited kind of parallel processing, to finesse a rate of 1-FLOP-per-cycle. The Cray-1 achieved 100 MFLOPS).

The middle of the book is filled with little charts explaining all the trends that Kurzweil sees coming together. This is the central chart:

This is from page 165. Note that the vertical scale is logarithmic; each scale division is 10x as great at the one below. The units are FLOPS/$, but spelled out longer, because before 1970 the FLOPS rate had to be estimated from MIPS ratings. Also, the last two points are for the Google TPU (Tensor Processing Unit), a takeoff of the GPU (Graphics Processing Unit), which is specialized for extremely broad-scale massively parallel learning needed to train programs such as ChatGPT or Gemini. One cannot own a TPU, they can only be leased, so some figuration had to be done to make the data points "sit" in a reasonable spot on the chart. The dollars are all normalized to 2023.

The trend I get from these points (an exponential line from the second point through the next-to-last), is 52.23 doublings in 80 years, or a doubling each 18.4 months. It is also a factor of ten each five years plus a month (61 months). Of course, the jitter of the charted line indicates that progress isn't all that smooth, but the idea is clear. Whatever is happening today, can be done about ten times as fast in five years, or one can do ten times as much in the same time, five years from now.

When I was in graduate school, about 1980 (I was several years older than my classmates) we were asked to write an essay on how we would determine the progress of plate tectonics back in time "about 2 billion years", and whether computer modeling could help. I outlined the scale of simulation that would be needed, and stated that running the model to simulate Earth history for a couple billion years would take at least ten years of computer time on the best processors of the day. I suggested that it would be best to take our time to prepare a good piece of simulation software, but to "wait ten years, until a machine will be available that is able to run 100 times as fast for an economical cost". I didn't get a good grade. As it turned out, from 1978 to 1988 the trend of "fastest machine" is seen to be flat on the chart above! It took another five or six years for the trend to catch up after that period of doldrums. Now you can view a video of the motions of tectonic plates around the globe over the past 1.8 billion years, and the simulation can be run on most laptops.

So, I get Kurzweil's point. Machines are getting faster and cheaper and perhaps one day there will be a computer system that is smaller than the average Target store, which can hold, not just the simulation of one person's brain, but the whole human race. However, as I said, I am an algorithmicist. What is the algorithm of consciousness? Kurzweil says at least a couple of times that if 10¹⁴ calculations per second per brain turn out not to be enough, "soon" after that there will be enough compute capacity to simulate the protein activity in every neuron in a brain, and later on enough to simulate all of humanity, so that the whole human race could become a brain in a box.

Of course, that isn't the future he envisions for us. He prefers that we not be replaced by hardware, but augmented. Brain-to-machine interfaces are coming. He has no more clue than I do what scale of intervention is needed in a brain so it can handle the bandwidth of data transfer needed to, say, double the "native" compute capacity of a person, let along increase it by a factor of 10, 100, ... or a billion. At what point does the presence of a human brain in the machine even matter? I suspect even a doubling of our compute capacity is not possible.

Let's step back a bit. In an early chapter we learn a little about the cerebellum, which contains 3/4 of our neurons and more than 3/4 of the neuron-to-neuron connectivity of the total brain, all in 10% of its volume. With hardly a by-your-leave, Kurzweil goes on to other things, but I think this is utterly critical. The cerebellum allows our brain to interact with the world. It runs the body and mediates all our senses. Not just the "classic 5", but all of the 20 or more senses that are needed to keep a human body running smoothly. Further, I see nothing about the limbic system; it's only 1% of the brain, but without it we cannot decide anything. It is the core of what it "feels like to be human," among other crucial functions. Everything we do and everything we experience has an emotional component.

Until we fully understand what the 10% and the 1% are doing, it makes little sense to model the other 89% of the brain's mass. Can AI help us understand consciousness? I claim, no, Hell no, never in a million years. It will take a lot of HUMAN work to crack that nut. AI is just a tool. It cannot transcend its training databank.

At this point, I'll end by saying, I find Ray Kurzweil's writing very engaging but not compelling. I enjoyed reading the book, and not just so I could pooh-pooh things. His ideas are worth considering, and taking note of. Some of his forecasts could be right on. But I suspect the ultimate one, of actually merging with AI, of all of us becoming effectively cyborgs?… No way.

If it is artificial, is it intelligence?

 kw: book reviews, nonfiction, computer science, artificial intelligence, simulated intelligence, surveys

Before "hacker" meant "computer-using criminal", it meant "enthusiast". Many early hackers spent their time obsessively doing one of two things: either writing a new operating system, or trying to write software to do "human stuff". I have been hearing about "AI", "artificial intelligence" since the term was coined by Claude Shannon when I was nine years old. Two years later the third book in the Danny Dunn series was Danny Dunn and the Homework Machine (by Abrashkin and Williams). It featured a desk-sized computer with a novel design, created by a family friend, Professor Bullfinch. A decade later (1968) I had the chance to learn FORTRAN, which kicked off a lifelong hobby-turned-profession. The computer I learned on was the first desk-sized "minicomputer", the IBM 1130.

ENIAC and other early "elephants" were called "electronic brains" almost from the beginning. I learned how CPU's (central processing units) worked, and even though the operation of biological brains was not so well known yet, it was clear to me that computers worked in an utterly different way.

Fast-forward a few decades. Some 20 years ago a "last page" article in Scientific American described the newest supercomputer, claiming that it was equivalent to a human brain, in memory size, component count, and computing speed. Where it did not match the brain was the amount of power it needed: three million watts. Our brains use about 20 watts. It soon became evident that the metric of brain complexity is not the number of neurons, but the number of synapses, plus other connections between the neurons and the glia and other "support cells". In this, that supercomputer was woefully lacking. This is still true.

Tell me, does this illustration show one being or two?

My generation and all those following have been influenced by I, Robot, and by Forbidden Planet, and by other popular depictions of brainy machines. We think of a "robot" as a mechanical man, a humanoid mechanism that is self-contained.

In order to behave and respond the way one of the robots in I, Robot does, a humanoid mechanism would need an intimate connection with a room full of equipment like the supercomputer in the background of the image (that part of the image is real). When the Watson supercomputer played Jeopardy (and won) a few years ago, what the audience didn't see was the roomful of equipment offstage. And that was just what was running the trained "model" and its databases and the voice interface. The equipment used for training Watson was much larger, and kept a couple of hundred computer scientists, linguists, and other experts occupied for many months.

Assuming Moore's Law continues to double circuit complexity (per cubic cm) each two years, it will take sixteen doublings, or 32 years, to get the supercomputer shown into a unit that fits inside a robot of the size shown. And power requirements will have to drop from millions of watts to 100 watts or less. And this is still not a machine that has the brain power of a human. We don't know what that would take.

All this is to introduce a fascinating book, The Mind's Mirror: Risk and Reward in the Age of AI, by Daniela Rus and Gregory Mone. While Professor Rus is a strong proponent of AI and of its further development, she is more clear-headed than the authors of most books on the subject. In particular, she sees more clearly than most the risks, the dangers, of faddish over-promotion and of rushing blindly into an "AI Future".

At the outset, in Chapter 1, "Speed", she clearly emphasizes that products such as ChatGPT, DALL-E, and Gemini are tools, and particularly that their "expertise" is confined to the material that was used to train them. She writes that it might have been possible to get one of the LLM's (large language models) to write a chapter of the book, but it "would not really represent my ideas. It would be a carefully selected string of text modeled on trillions of words spread across the web. My goal is to share my knowledge, expertise, passion, and fears with regard to AI, not the global average of all such ideas. And if I want to do that, I cannot rely on an AI chat assistant." (p. 11) In a number of places she calls AI software "intelligent tools."

She continues the theme, writing of knowledge, insight, and creativity (Chapters 2 – 4), saying at one point, "They are masters of cliché." (p. 60) Critical analysis skills that we used to learn were based on following the progression from Data to Information to Knowledge, and then to Insight and Wisdom (does any school still teach this?) All of these together add up to comprehension. Does anyone have the slightest idea how to bring about Artificial Comprehension?

None of the software tools has shown the slightest ability to step outside the bounds of their training data. If ChatGPT "hallucinates", it is not rendering new knowledge, but remixing biased or deceptive content from its poorly curated training set, perhaps with a dollop of truthful "old news" in the mix. This illustration of a LinkedIn post I wrote last year shows the point.

The colors are significant:

• Green = correct or true
• Lighter orange = incomplete or outdated
• Darker orange and red = false to malicious, even evil
• Blue = AI training data, partly "good", partly "poor", partly "evil"—we hope not too evil

The three lavender blobs at right are varieties of human experience, including someone creating new "good stuff", poking out to the right and increasing the store of published knowledge. I kept those blobs far from the training data on purpose. Training is typically done with "old hat" material.

This book has a rare admission that "it's essential to remember that the nature and function of AI parameters and human synapses are vastly different." (p. 106) We don't know all that well the amount of processing going on within a neuron, nor even if a synapse is more than just a signal-passing "gate" or is something more capable. 

And though the matter of embodiment is touched upon, I was disappointed that there wasn't more on this. Perhaps you've heard that the human brain has "100 billion neurons". The actual number is 85-90 billion, and 80% of them are in the cerebellum, the "little brain" at the back, above the brain stem. We have a little inkling that the sorts of processing that cerebellar neurons perform are different from those in the cerebral neurons (the famous "gray matter"). Clearly, when 80% of the neurons make up only 10% of the brain's total volume, these neurons are smaller. The cerebellum "runs the body", and handles the traffic between the body and the cerebral cortex, the "upper brain", where thinking (most likely) occurs. Embodiment is clearly extremely important for a brain to function properly. It's being glossed over by most workers in AI.

A special chapter between 11 and 12 is "A Business Interlude: The AI Implementation Playbook". An entrepreneur or business leader who wants either to initiate a venture that strongly relies on these tools, or who wants to add them to the company bag of tricks would do well to extract these 19 pages from the book and dig into them. They include the key steps to take and the crucial questions to ask (including "Will AI be cost-effective compared to what I am doing now?"). A key component of any team tasked with making or transitioning a business to use AI is "bilinguals", people who are well versed in the business and also in computer science and AI in particular. This is analogous to a key period in my career (not with AI, though): Because I had studied all the sciences in college, and had a few degrees, and I also was a highly competent coder, I was a valued "bilingual", getting scientific software to work well for the scientists at the research facility where I worked. Bottom line: You need the right people to make appropriate use of AI tools in your company.

The book includes a major section on risks and the defenses we need. Whether some future AI system will "take over" or subjugate us is a far-off threat. It is not to be ignored, but the front-burner issues are what humans will do with AI tools that we need to be wary of. Something my mother said comes back to me. I was about to go into a new area of the desert for a solo hike. She said she was worried for my safety. I said, "Oh, I know how to avoid rattlesnakes." She replied, "I am worried about rattle-people!"

Let's keep that in mind. In my experience, rattle-people are a big risk whenever any new tool is created. What's one of the biggest uses of generative art-AI? Coupling it with Photoshop to produce deep fake pictures. Deep fake movies are a bit more difficult and costly just now, but just wait…and not very long! Soon, it will take a powerful AI tool to detect deep fake pix and vids, and how will we know that the AI detective tool is reliable and truthful?

A proverb from my coding days, "If we built houses the way most software is written, the next woodpecker to come along could destroy civilization." Most of us old-timers know a dozen ways to hack into a system, but the easiest is "social engineering," finding someone to trick into revealing login credentials or other information to help the hacker get into the system. Now social engineers are using AI tools to help them write convincing scripts to use to fool people, whether through scam phone calls, phishing emails or smishing SMS (or WhatsApp or Line or FB, etc.) messages.

[You can take this to the voting booth: Effective right now, any TV or radio political ad, particularly the attack ads, will have AI-generated content. If you want to know a candidate, go to the candidate's web site and look for actual policy statements (NOT promises!).]

A final matter I wish Professor Rus had included: Human decision making requires emotion. Persons who have suffered the kind of brain damage that "disconnects" their emotions become unable to make a decision. Somehow, we have to like something in order to choose it. Where "liking" comes from, we haven't a clue. But it is essential!

There is much more I could go into, but this is enough, I hope, to whet your appetite to get the book and read it.

A final word, that I didn't want to bring into the earlier discussions. I don't like the term Artificial Intelligence, nor AI. I much prefer Simulated Intelligence, abbreviated SI. It is unfortunate that, in the world of science, SI refers to System Internationale, the system of units such as meter, kilogram and second, used to define quantities in mathematical physics. Perhaps someone who reads this can come up with another moniker that makes it clear that machine intelligence isn't really intelligent yet.

The not-so-silent seas

 kw: book reviews, nonfiction, science, oceanography, acoustics, bioacoustics, sound, noise pollution

A number of years ago at the beach at Cape Henlopen, Delaware, a pod of porpoises came by, a hundred yards or so offshore, as they usually do in the afternoon. This particular day a couple of busloads of Amish people from the Lancaster, PA area had been brought for a day at the beach, and I was standing about chest-deep in the water among a dozen or so Amish teenagers. As I like to do when the porpoises swim by, I ducked my head under water to listen to them whistle and chirp. It is a sound I love. I liken it to the social honking of a V of geese flying overhead.

I said to the nearest Amish boy, "Try putting your head under water. You'll hear the porpoises." He tried it, and then shouted something in German to the other kids. Soon they all were bobbing up and down and chattering among themselves about this novel experience.

As a teen I often watched the Flipper TV show, centered on a bottlenose dolphin (the "poster child" of porpoises). I was familiar with the chatty noises the animal could make. A few years later I was enthralled to listen to the album Songs of the Humpback Whale. As an avid reader of science articles and books, I've kept up in a general way with the findings of bioacoustics about the whole range of animals that make sounds under water, from snapping shrimp and mantis shrimp to the fish called Grunts—and many others that do more than grunt—to the mammals, particularly whales (I count porpoises as small whales).

The title Sing Like a Fish: How Sound Rules Life Under Water was a slam-dunk for me. The reading was as enjoyable as I'd anticipated. The author, Amorina Kingdon, muses in the Epilog whether it was worthwhile to devote two years of her life to the book and its research. She concludes a resounding Yes, and I agree. Who else could do this? Another might write on the same subject, but Ms Kingdon's voice is unique: heartfelt, lyrical and eloquent.

Early in the book we learn why we've ignored the underwater soundscape for so long. Our ears don't hear that well under water. In the age of sail, many sounds were heard by sailors trying to sleep below decks. When there is little wind, a sailing ship is so silent, the sounds of the sea that make their way through the wooden hull are quite evident. These days, professional sailors would be hard pressed to hear anything coming through the hull of a noisy, engine-driven ship. Those who never go to sea, who experience it only from above, have no idea how sound-filled it is. Early SCUBA divers, with Jacques Cousteau in the lead, hampered by air-adapted ears and the noisy SCUBA apparatus, heard so little that they produced a documentary film about the ocean titled The Silent World, about ten years before the first episode of Flipper aired. As I recall, the main sound heard under water in that film is the noise of the SCUBA. I wonder if Cousteau ever learned that fish have songs.

Although I wanted to learn SCUBA diving, I wasn't willing to pony up for expensive diving lessons and equipment. I snorkeled instead; I could surface dive to 40 feet without much trouble, and once went 60 feet. Snorkeling can also be noisy if you never leave the surface; we breathe rather loudly. But if you pop a surface dive down even 10 feet and just hang there, gradually the sounds will become evident. In my case, though, I dove offshore of tide pools, to see what animals were on the rocks. Most of the sound was wave noise, but I did hear a little of the fishy chorus around me: clicks, squeaks, and mournful groans. Better equipment has helped us realize that fish sing! Not just whales.

Once the hydrophone was invented, the soundscapes of the seas came into sharper focus (Hmm, bit of a mixed metaphor there; I guess you can figure it out anyway). Much of the book is devoted to surveying the breadth of underwater animal species that detect sound, hear sound (different senses), and communicate using sound. In one place it is stated that a catalog of fish sounds contained around 900 species. Compare that to the 94 species of cetaceans (whales of all varieties), all of which can vocalize. Though there are about 34,000 species of fish, the 900 "cataloged" to be vocal simply reflects the very early stage of "auditioning" the world's census of fish. I don't recall reading about any fish that were tested, that they were unconditionally silent, so perhaps I can fairly conclude that most, or nearly all, fish will be found to not just receive sound but to use it.

Certain invertebrates also make sounds intentionally. Snapping shrimp and mantis shrimp make noises loud enough to be weapons, though a mantis shrimp mainly relies on the fastest punch in the animal kingdom as its primary weapon. Considering the wide range of insects that make noises to communicate and court, it's reasonable to assume that many of the active invertebrates also use sound. I immediately thought of scallops, which make a clapping sound when fleeing danger, but in their case I think the sound is incidental to the "jet propulsion" their clapping produces.

Sadly, there is a new player on the soundscape. Us. Ship engines are noisy. The propellers ("screws") are noisier. Sonar is noisy. Seismic surveying is incredibly noisy. The racket of pile driving to install offshore wind turbines drives whales and fish crazy and can kill them. The low rumble of the turbines once they are operating is a chronic noise that drives migrating animals to change migration routes, and hinders the feeding activities of many animals that need to hear their prey. So does the persistent growl of ships' propellers and the hammering of depth-finding Sonar. A couple of chapters are devoted to describing all the problems that sea animals are having with the sounds we make while we use the oceans for commerce and entertainment.

The book ends on a hopeful note regarding the confluence of regulation and public attitudes that can result from wise use of scientific data being collected right now. We know we can't protect everything, but if we know certain areas that are most sensitive—such as a special bay where certain whales raise their calves—we can focus our efforts where they are more effective.

Just in case you're wondering: This sonogram illustrates why we call the sounds made by humpback whales "songs":

For reference, middle C on a piano has a frequency of 261 Hz. 200 on these diagrams would then be near the G below middle C, and it happens to be the natural frequency of my speaking voice. To sing along with this whale, just follow the lowest, darkest line of each group. The highest blip on the second track (~700 Hz) is almost an octave higher than the highest note I can sing, which is an A with a frequency of 440 Hz. Most women can just reach the next A at 880 Hz, so a woman can sing with this whale, but not even a low-voiced man can reach the low tones near 50 Hz seen in much of the second track. This whale has a very wide vocal range!

But why are these a song rather than tuneless noises such as some people make when concentrating on whittling or something similar? In a word, structure. Phrases and shorter elements (words?) repeat and are sometimes repeated with variations. There is something intentional going on. One verse of a typical popular (human) song lasts from half a minute to a minute. Most song tracks on your playlist are 3-4 minutes in length. A typical section (verse?) of a humpback song lasts a couple of minutes, and such verses are grouped into soliloquies lasting on average 8 minutes, but the whale may sing the song, over and over again, with variations, for an hour, or even a day. Maybe a whale is a philosopher, and this is his way (only males sing) of thinking out loud. Or maybe these are courting songs, which the whale will repeat until a female responds, perhaps from miles away, and joins him.

A book like this reminds us of what we don't know, and hints at the level of effort we'll need to exert to find out what the natural world contains, while it is still there. That's the author's aim. The fish are singing, for their own reasons. But now we are able to hear. Will we value their songs enough to preserve them, not just as recordings, but by preserving the singers?

More Octo-fun

 kw: book reviews, nonfiction, zoology, cephalopods, octopus, octopuses

Almost a year ago I reviewed Soul of an Octopus by Sy Montgomery. She has followed up with a delightful, small book Secrets of the Octopus. Even more than the prior book, this one is replete with amazing pictures of these astounding creatures. The core of Soul is the relationship Dr. Montgomery had with four Giant Pacific Octopus individuals, during the short time (just a few years) that each resided in the aquarium at Monterey Bay. In Secrets we find a number of newer discoveries about octopuses.

At present we know of about 300 species of octopus. The largest is the Giant Pacific Octopus, Enteroctopus dofleini, which can reach twice the size of a man and weigh between 100-250 pounds. The first octopus I saw was one of these, at Marineland of the Pacific, when it was still open. I was about ten years old. The large female was plastered to the glass, and I had to look in from the side to see her mantle (which many people mistake for the head; it is behind the head).

I remember at the time being told that red color for an octopus meant anger, but that is wrong. It means interest or excitement. An angry octopus will instead blacken, particularly when it rises up to intimidate an opponent. The animal in this photo is excited from interacting with the diver. Many species of octopus quickly learn to enjoy human company.

Octopuses are cephalopods, the "brainy" order of mollusks, which also includes squids, cuttlefish, argonauts (which produce lovely, featherweight shells), nautiluses (with coiled, heavier shells), and sepiolids (often called "dumbo octopuses"). All cephalopods have arms, which most people call "tentacles", but to a biologist, the tentacles are the two long, extensible members that shoot out to capture prey, and only have suckers at their ends, the part often called a club. Arms typically have suckers all long their length. Also, all cephalopods have color-shifting skin, and many have skin that can dramatically change shape. Almost any octopus can mimic a rock or patch of seaweed in both color and shape.

The smallest octopus is the Hairy Octopus, which was discovered only a couple of years ago. It is so new a scientific binomial name hasn't been chosen yet. These lovely little critters, only 5 cm long (2 inches, or the size of a large paper clip), exhibit the shape-shifting skill almost all the time, looking mostly like drifting bits of seaweed. Depending on the screen you are using, this picture is probably twice as large as the actual animal.

It was once thought that octopuses are strictly solitary, only meeting to mate or fight or eat one another. This is also out of date. A lot depends on the density or scarcity of food. In abundant circumstances, some (perhaps many) species can be quite social, as seen with a few "octo-cities" such as Octopolis near Australia. While no large settlements of Giant Pacific Octopuses are known, their apparent enjoyment of human association indicates that they also can be quite sociable.

Some octopuses use tools. The Coconut Octopus, Amphioctopus marginatus, is just the right size to fit into a coconut shell. When an individual finds either a coconut shell portion (or two), or a similarly-sized shell of a clam or scallop, it will typically begin to carry it around to use as an impromptu shelter. This is a good strategy for an orange-sized, tasty morsel in an ocean full of predators.

This species is also one that "walks". Holding a shell with up to six arms, it uses two to stride along the ocean floor like a bellhop with a heavy suitcase. This image is two clips from a video of an octopus that wraps six arms around its body while walking on the other two. Starting about 10 seconds into this video, we see another species "stand up and walk away" from the photographer.

This is the video link, in case the one above doesn't work right: https://www.youtube.com/watch?v=kHwUW1inDCs.

These are just a few of the recent learnings about various species of octopus. The last part of the book, "Octoprofiles" by Warren K. Carlyle IV, presents brief descriptions of sixteen cephalopod species to give us a taste of their variety. Reading this book and gazing at the terrific pictures is pure enjoyment.