Building a sensory screening tool for the European green crab

The European green crab (Carcinus maenas) is unusual among invasive species in being a classic laboratory animal. That makes it a good test of a question worth asking about any organism: how much of its sensory front end can be computed rather than assumed?

The thing I built is not a simulator. A simulator implies you can turn a crank and get behaviour out the other end. What this does is narrower and, I think, more useful: for a given stimulus it answers how much arrives at a receptor, in what format that receptor passes it on, and where it goes — and it refuses to answer when the number underneath does not exist. Calling it a screening tool is more honest than calling it a simulator, and the difference matters, because the most common output is a refusal.

The design rule: every number carries where it came from

Each constant in the tool is tagged with its provenance — measured in this species, measured in a surrogate species, derived from physics, or assumed. That sounds like bookkeeping. It turned out to be the part that did the work.

Over the course of building it, the tags caught six errors that had already made it into the model, every one of them from reading a summary instead of a source. Two examples, because they are the kind of thing that is invisible without the discipline:

• A trap statistic entered the model as “entry success rises from 16% to 59%.” Those are two different measurements — one is the fraction of attempts that succeed¹, the other is a percentage increase in catch from a modification². The second does not continue the first, and the best modification was not the one being quoted.
• A receptor threshold was carried in the model as a single value when the underlying study reports a range³. The single number was the low end of it.

The rule that generates the rest: an abstract is not a paper. A source read only at abstract can be cited as existing, but nothing may be said about what it measured. That constraint is load-bearing in what follows, and I have marked where it bites.

The mechanical senses — the part that is genuinely measured

The strongest ground is mechanoreception, because there is a real transfer function for this species. Recordings from the mouthpart setae give displacement thresholds in micrometres, and — more useful — the coding: spike count scales with displacement amplitude, interspike interval with velocity, and roughly half the cells are directionally sensitive⁴.

That last detail is what made the first version of the tool wrong. Those setae are tactile receptors for handling prey, not distance detectors, and I had been scoring far-field stimuli against them. The tool now raises a scope flag on any far-field verdict from that row, because the answer it would give is meaningless.

The receptor that is for water motion is a different one: sensory hairs on the chelae, studied in crayfish⁵. A joint organ in the walking leg has been described in green crab itself⁶, the behavioural response of intact animals to substrate vibration has been tested directly⁷, and decapod acoustic detection has been reviewed as a field⁸. An evoked-potential study in the American lobster asks which organ is actually responsible⁹, and a consolidated review of green crab sensory biology exists¹⁰.

Where the abstract-only rule bites, and it bites here: of the seven sources in this section I have read two at full text. For the other five I can tell you they exist and what question they asked — not what they found. So the surrogate threshold the tool actually uses for the water-motion channel is a number I am not in a position to attribute, and the tool carries it tagged as a surrogate for exactly that reason.

The physics that decides most of it

Two pieces of arithmetic ended up governing nearly every conclusion.

Near-field falloff. A small oscillating body in water produces a field that falls off as 1/r³ if it oscillates back and forth, or 1/r² if it changes volume. The cube law is brutal: a thousand times more source amplitude buys ten times the range. Working through plausible prey sources, ordinary prey turns out to be a centimetre-scale cue; only a large struggling animal or another crab reaches decimetres.

Displacement is not pressure. Particle displacement equals velocity divided by 2πf, so for a given sound pressure a kilohertz signal carries far less displacement than a hundred-hertz one. High-frequency sound is displacement-poor, and crabs detect displacement.

Those two together explain why the acoustic route keeps failing, and they are also why the chemical route keeps winning: a plume falls off as 1/r and the olfactory threshold is low.

What prey actually emit

Having built the receiver side, the obvious next question is what is available to receive.

The reference dataset for benthic invertebrate sound gives calibrated source levels for scallops, limpets, urchins and crustaceans¹¹. Converting each to particle displacement and solving for the crab’s threshold, none of it reaches a crab at more than millimetres — and every sound in that dataset peaks between 5 and 49 kHz, while the analysis band was filtered from 2 kHz upward. The corpus was built for hydrophone monitoring, not for prey detection, and the crab’s band was removed before analysis. A null there is unavailable, not absent.

The cue that does look promising is not a sound at all. Porewater pressure signals generated by infaunal activity have been recorded directly in sediment¹², and the irrigation timing of three tellinid bivalves — including a Pacific Northwest clam that is real green crab prey — has been measured in detail¹³. That is a slow hydraulic signal, not an acoustic one, and it is the only prey cue in this review with a field detection range measured on relevant species.

Chemistry, which out-ranges everything

Modelled as a plume, chemical detection spans roughly three orders of magnitude more distance than any mechanical cue. The receptor side has two anatomically separate systems doing different jobs — olfaction on the antennules, and contact chemoreception on the dactyls, where the gustatory organs of this species have been characterised electrophysiologically³. I have that paper at abstract only, so the threshold separation between the two — which is what the tool actually runs on — is stated in the model as a sourced parameter and is not stated here.

The tool refuses one thing here, deliberately. A chemical stimulus is not a scalar. You cannot hand it a single “concentration” and get a receptor response, because mixtures cross-adapt and receptors encode a ratio against background rather than an absolute. Single-compound dose-response is enabled; mixtures raise an exception.

The female sex pheromone in this species has been the subject of an identification study¹⁴, and later work using it produced the single most interesting behavioural result in this review: males presented with a pheromone-treated dummy female showed a mating response 87% of the time under ambient conditions and 40% under ship-noise playback, a significant drop — while the time taken to respond to the pheromone did not change significantly¹⁵. Noise interfered with completing the behaviour, not with detecting the signal. That dissociation is worth more than either number alone.

Electric and magnetic — where the tool says no

These are the two channels the tool refuses outright, and the refusals are the highest-confidence outputs in it.

Electric. No electroreceptor has been identified in any crustacean, and none has been sought in this species. That is not a modelling gap; it is the state of the field. The physics side is unambiguous: prey bioelectric fields were measured at microvolt scale with the electrode less than a millimetre from the tissue, and the authors state plainly that the voltage from invertebrates was too weak to record away from the source¹⁶. A behavioural sensitivity figure exists for a freshwater crayfish¹⁷ — a surrogate, from a different order, in fresh water. The tool will quote named surrogates and will not produce a crab number.

Magnetic. There is a directly relevant result: juvenile green crabs were exposed to static magnetic fields at strengths relevant to submarine power cables, and females spent substantially more time in the exposed zones while males showed no consistent preference¹⁸. That is a real, sex-specific response in this species — and it is a static-field spatial preference, not a compass, and not a receptor. Nobody has located the transducer.

And there is a confound worth stating plainly, because it is the obvious one. Helmholtz coils dissipate heat, and crabs are thermotactic. Working the published coil geometry through a thermal model gives, at the strongest field over the exposure period, roughly 20 W dissipated, a 0.58 K gradient across the tank and a 0.30 K bulk rise — small, but not obviously below what an animal can detect, and I could not find a behavioural thermal-discrimination threshold for this species to compare it against. So the model returns a number and refuses a verdict.

One thing does argue against the thermal explanation, weakly: ohmic heating scales with the square of the current, so the confound is about ten times larger at the strongest field than at the intermediate one — while the reported attraction was strongest at the intermediate field. The confound and the effect run in opposite directions. A thermocouple in the tank would settle it, and that is the cheapest experiment anywhere in this review.

The usual comparison is the spiny lobster, which is the standard invertebrate magnetoreception system¹⁹²⁰²¹. Here the abstract-only rule bites hardest: I have read those three at abstract, so I will not characterise their results. What I will say is a statement about the shape of the literature rather than its contents — the receptor cells themselves have not been located and characterised in that animal either. Mapping a mechanism from one order of crustaceans onto another, across more than two hundred million years of divergence, when the source species’ anatomy is itself unresolved, produces a hypothesis wearing borrowed credibility. The tool returns unavailable and says why.

How the native crabs compare

Comparing green crab to the Pacific Northwest natives was the point at which the exercise became most informative, because the comparison cannot be run.

Across eight receptor channels and five species, the green crab has measured values in five channels and a described-but-unmeasured organ in two. For Dungeness crab, red rock crab, graceful rock crab and yellow shore crab, I found two measured thresholds, both in Dungeness. One establishes a behavioural detection threshold for a prey extract²⁴; the other, behavioural salinity detection measured by antennular flicking²⁵. I have both at abstract only, so those are descriptions of what was measured, not of what was found — the model carries the values with the same tag. (A third record sits off this matrix entirely: dactyl chemo- and mechanoreceptor recordings in the kelp crab, a species not among the five.)

Two filled cells out of thirty-two, and the comparison still cannot be run — but for a different and much smaller reason than an empty literature. Those are behavioural thresholds, in grams per litre and parts per thousand. Every green crab value is single-unit electrophysiology, in micrometres or molar. They are not the same quantity, so putting them in one row would be a category error rather than a comparison.

That is the state of the literature, not a gap in the modelling. Green crab is a classic laboratory animal; the natives are commercially and ecologically important animals whose sensory physiology has largely not been measured.

What can be compared is everything except the senses — and there the differences are substantial and well documented²²: salinity tolerance, depth and zonation, body size, moult timing, and tolerance of emersion and hypoxia. Subadult Dungeness use the littoral zone in ways that matter for any comparison drawn from trap data²³, red rock crab emersion physiology has been measured in situ²⁶, settlement and emigration behaviour has been studied in green crab²⁷, predatory capability has been compared directly between green crab and red rock crab on a native clam²⁸, and the effect of a recovering apex predator on green crab abundance has been examined²⁹.

I have read the first of those at full text and the rest at abstract, which is why this paragraph names questions rather than answers.

The genetics, and what is actually there

I went looking for a genetic basis for the green crab’s reproductive advantage — some identified difference that would explain why it out-reproduces the natives. There isn’t one, and the absence is informative.

The adaptive-genomics literature for this species is real and substantial. What it is about is temperature: cold tolerance, thermal adaptation, a chromosomal inversion, and the relationship between genotype and thermal plasticity³⁰³¹³². I have read these at abstract only and will not characterise their findings. But the observation that the surveyed literature concerns thermal physiology and not reproduction or sensory biology is an observation about the literature, and I can make it.

So the honest account of why green crab out-reproduce the natives is life-history and tolerance, not a gene: a longer breeding season, earlier maturity at smaller size, two broods a year where conditions allow, and sperm storage such that one fertilisation can serve more than one clutch²². Note also that reproducing more is not the same as mating more — with sperm storage, the two can move in opposite directions.

What the tool is for

The most-used outputs are refusals: no electric readout, no magnetic readout, no mixture readout, no cross-species comparison, no sex difference in transduction. Sex enters the model in exactly one place — body size — because no measured threshold in this species differs by sex, and the tool will not invent one.

That is a strange thing to build on purpose, and it is the part I would defend. The value is not in the numbers it produces. It is that the numbers cannot drift: every constant is pinned by a test that fails if the figure is misquoted, and in one working session those tests caught four errors that had entered the model from secondary summaries of paywalled sources — which is exactly how this literature is normally read.

The most instructive failure, though, was mine and not the literature’s. The claim above — that no native species had a single measured sensory channel — was a strong negative drawn from a shallow search, and it was wrong; a deeper search turned up the two Dungeness thresholds immediately. A test had been pinning the wrong number in place, with a comment beside it admitting the value was known to be stale. That is worse than an unchecked number, because it looks checked.

And correcting it nearly introduced a new error. The function answering which channels are comparable across species tested only whether a cell was marked measured. Filling the two Dungeness cells would have made two channels report as comparable when the underlying quantities are not the same thing. It compares units now. A test that counts statuses will happily certify a category error, and the correction is what exposed it.

What would make it wrong: if a measured audiogram for Carcinus maenas, Dungeness and red rock crab on one rig showed the receptor bands to be substantially different from the surrogate values used here, most of the mechanical conclusions would need redoing. That measurement does not exist, and it is the single experiment that would change the most.

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Corrections

2026-09-06. Three changes, none of which erase anything above.

• The native-comparison section originally said I had found “two measured chemosensory thresholds in a single species and nothing else.” The two are now cited by key²⁴²⁵, one of them is a salinity threshold rather than a prey-odour one, and “nothing else” was an overreach — a third native record exists off the matrix. Both are held at abstract only, so the post names what they measured and not what they measured it to be. The count of filled cells is unchanged at two of thirty-two, and the comparison remains un-runnable.
• The “What the tool is for” section gains the account of how that error survived a test, and of the second defect that correcting it exposed.
• The correction has been applied to the model itself, not only to this post.