Bioregionalisation part 3: clustering with Biodiverse

Biodiverse is a software for spatial analysis of biodiversity, in particular for calculating diversity scores for regions and for bioregionalisation. As mentioned in previous posts, the latter is done with clustering. Biodiverse is freely available and extremely powerful, just about the only minor issues are that the terminology used can sometimes be a bit confusing, and it is not always easy to intuit where to find a given function. As so often, a post like this might also help me to remember some detail when getting back to a program after a few months or so...

The following is about how to do bioregionalisation analysis in Biodiverse. First, the way I usually enter my spatial data is as one line per sample. So if you have coordinates, the relevant comma separated value file could look something like this:

species,lat,long
Planta vulgaris,-26.45,145.29
Planta vulgaris,-27.08,144.88
...

To use equal area grid cells you may have reprojected the data so that lat and long values are in meters, but the format is of course the same. Alternatively, you may have only one column for the spatial information if your cells are not going to be coordinate-based but, for example, political units or bioregions:

species,state
Planta vulgaris,Western Australia
Planta vulgaris,Northern Territory
...

Just for the sake of completeness, different formats such as a tsv would also work. Now to the program itself. You are running Biodiverse and choose 'Basedata -> Import' from the menus.

Navigate to your file and select it. Note where you can choose the format of the data file in the lower right corner. Then click 'next'.

The following dialogue can generally be ignored, click 'next' once more.

But the third dialogue box is crucial. Here you need to tell Biodiverse how to interpret the data. The species (or other taxa) need to be interpreted as 'label', which is Biodiversian for the things that are found in regions. The coordinates need to be interpreted as 'group', the Biodiversian term for information that defines regions. For the grouping information the software also needs to be told if it is dealing with degrees for example, and what the size of the cells is supposed to be. In this case we have degrees and want one degree squared cells, but we could just as well have meters and want 100,000 m x 100,000 m cells.

After this we find ourselves confronted with yet another dialogue box and learn that despite telling Biodiverse which column is lat and which one is long it still doesn't understand that the stuff we just identified as long is meant to be on the x axis of a map. Arrange the two on the right so that long is above lat, and you are ready to click OK.

The result should be something like this: under a tab called 'outputs' we now have our input, i.e. our imported spatial data.

Double-clicking on the name of this dataset will produce another tab in which we can examine it. Clicking on a species name will mark its distribution on the map below. Clicking onto a cell on the map will show how similar other cells are to it in their species content. This will, of course, be much less clear if your cells are just region names, because in that case they will not be plotted in a nice two-dimensional map.

Now it is time to start our clustering analysis. Select 'Analyses -> cluster' from the menu. A third tab will open where you can select analysis parameters. Here I have chosen S2 dissimilarity as the metric. If there are ties during clustering it makes sense to break them by maximising endemism (because that is the whole point of the analysis anyway), so I set it to use Corrected Weighted Endemism first and then Weighted Endemism next if the former still does not resolve the situation. One could use random tie-breaks, but that would mean an analysis is not reproducible. All other settings were left as defaults.

After the analysis is completed, you can have the results displayed immediately. Alternatively, you can always go back to the first tab, where you will now find the analysis listed, and double-click it to get the display.

As we can see there is a dendrogram on the right and a map on the left. There are two ways of exploring nested clusters: Either change the number of clusters in the box at the bottom, or drag the thick blue line into a different position on the dendrogram; I find the former preferable. Note that if you increase the number too much Biodiverse will at a certain point run out of colours to display the clusters.

The results map is good, but we you may want to use the cluster assignments of the cells for downstream analyses in different software or simply to produce a better map somewhere else. How do you export the results? Not from the display interface. Instead, go back to the outputs tab, click the relevant analysis name, and then click 'export' on the right.

You now have an interface where you can name your output file, navigate to the desired folder, and select the number of clusters to be recognised under the 'number of groups' parameter on the left.

The reward should be a csv file like the following, where 'ELEMENT' is the name of each cell and 'NAME' is the column indicating what cluster each cell belongs to.

Again, very powerful, only have to keep in mind that your bioregions, for example, are variously called clusters, groups, and NAME depending on what part of the program you are dealing with.

Bioregionalisation part 2: clustering

Already I think I should change the way I was going to do this. It seems more straightforward to keep the two approaches in separate posts. So for today: bioregionalisation using clustering methods.

A small example

As the term clustering suggests the approach is very simple. Let's start by considering a landscape of five cells A-E with five species occurring in them as follows:

Another way of expressing this information is as a matrix where the cells are rows and the species are columns, and presence of a species is indicated with "1" while absence is indicated with "0":

We now simply calculate a distance matrix. There are several possible dissimilarity metrics we can use for this. For this post I will use the S2 dissimilarity, which is defined as

S2 dissimilarity = 1 - ( number of shared species / ( number of shared species + minimum( species unique to first cell , species unique to second cell ) ) )

The resulting S2 dissimilarity matrix for our small dataset is consequently as follows:

Now we use a hierarchical clustering algorithm to produce a dendrogram. I have used R's hclust, and the result is:

We can now recognise clusters as bioregions, and we are done. The main remaining problem with hierarchical clustering is that there is no objective answer for the number of bioregions we should recognise. We could still accept anywhere between one and five, but at least we know that there should not be a region of e.g. only the cells C and E to the exclusion of D.

(This is of course the same problem as in phylogenetic systematics, where we would now know that CE to the exclusion of D is not an acceptable taxon, but it remains a subjective decision whether to recognise CD and E as separate genera or whether to have one genus CDE, for example.)

In our present, case it seems sensible to accept less than five regions but more than one, otherwise we would not have needed the analysis, so let's go with the two clusters AB and CDE:

These regions now show a fairly high level of endemism, as four of the five species are endemic to one region; only the blue species occurs across both.

Some R code

Although the proper software for this kind of work is Biodiverse, this post would get too long if I tried to do everything in one go. What is more, a simple analysis can just as well be run in R, which is what I have done in this case. First build a matrix of cells and the species in them, e.g.

occurs <- as.matrix(rbind(c(1,1,0,0,0), c(1,1,1,0,0), c(0,0,1,1,0), c(0,0,1,1,0), c(0,0,0,1,1)))
rownames(occurs) <- c("A", "B", "C", "D", "E")
colnames(occurs) <- c("red","brown","blue","orange","lilac")

The following loops will then produce a matrix of S2 dissimilarity scores.

mydm <- matrix(0, 5, 5)    # create empty matrix; could make it more flexible for future analyses by handing over square root of length(occurs) for the dimensions
rownames(mydm) <- c("A","B","C","D","E")    # same here, could use row names from occurs
colnames(mydm) <- c("A","B","C","D","E")     # and same here
for (i in 1:5)
{
  for (j in i:5)
  {
    if (i==j)
    {
      mydm[i,j] <- 0
    }
    else
    {
      shareds <- sum(occurs[i,] & occurs[j,])
      uniques_i <- sum(xor(occurs[i,], occurs[i,] & occurs[j,]))
      uniques_j <- sum(xor(occurs[j,], occurs[i,] & occurs[j,]))
      mydm[i,j] <- 1- (shareds / (shareds + min( uniques_i, uniques_j)))
      mydm[j,i] <- mydm[i,j]
    }
  }
}

Now finally do a cluster analysis and plot the resulting dendrogram:

mycl <- hclust(as.dist(mydm), method = "mcquitty")     # WPGMA
plot(mycl)

Done. For large numbers of cells we would want a decent visualisation, ideally as a map, and that is where Biodiverse works better. How to do the analysis in that software will be covered in the next post.

Bioregionalisation part 1: what's the idea?

This is the start of a little series of posts on bioregionalisation. I intend to divide the topic up as follows:

1. What I mean with bioregionalisation and what it is good for.
2. Comparison of two different quantitative approaches to defining bioregions, clustering and network analysis.
3. Practical how-to guide to inferring bioregions with clustering in the software Biodiverse.
4. Practical how-to guide to inferring bioregions with network analysis in R.
5. Beyond species presence and absence, i.e. using phylogenies for bioregionalisation.

Let's see if that works. So today:

What do I mean with bioregionalisation?

The idea is to divide a study region - perhaps a country, a continent or the whole world - into natural regions. There are obviously lots of different ways of doing so. A well-known one is climatic, where we would have arctic, temperate, subtropical, and tropical regions. Closer to what I am talking about are vegetation zones; in this case the general appearance of the natural vegetation and the life form of its constituent species are used to define zones such as tundra, boreal forest, mallee, or savanna.

But that still is not what this is going to be about. The bioregions I am going to discuss are defined by the taxa that occur in them. A very high-level classification is shown, for example, in the following map from earthonlinemedia.com:

As we can see there are no 'tropics', but instead the American tropics are separated from the African and South Asian ones. Why might that be the case? As a botanist I can immediately think of two important plant families that are very characteristic of the Neotropics but are (with the exception of one rather odd, small genus) entirely missing from the Paleotropics: the cactus family Cactaceae and the pineapple family Bromeliaceae.

This, then, is what bioregions as I will subsequently discuss them are: they are regions defined by the presence of (plant, animal, ...) taxa they do not share with other regions. Another way of putting it is that bioregionalisation aims to maximise the endemism of its regions. And this immediately suggests the possibility of quantitative, objective analyses as long as we can somehow quantify endemism.

But these approaches are for other posts. More importantly now:

Why do we care? What are these bioregions good for?

I can think of at least two use cases. The first is quite simply that we like to classify things, and climate and vegetation form do not capture all there is to natural regions. Specifically, the presence e.g. of bromeliads, leaf cutter ants and hummingbirds in the New World and their absence in the Old World is an accident of history that is orthogonal to the shared climate and to the fact that 'tropical rainforest' kind of looks the same from a distance in all continents. But it still matters because these groups of organisms have evolved unique characteristics, like the hummingbirds' high metabolic rate, that have an ecological impact. A neotropical cloud forest 'works' a bit differently than a southeast Asian one.

The second use case is that of finding objectively defensible regions for biogeographic analysis, a problem that still does not have a single widely accepted solution. For example, we may be interested in conducting an inference of ancestral areas and biogeographic processes using the R package BioGeoBears, because we want to know if our study group started evolving in the temperate part of our continent and then spread into the tropics or vice versa. For this analysis we need (a) a time-calibrated phylogeny and (b) a data table of taxa-by-regions showing for each region what taxa are naturally occurring in them.

Taking one step back, it is obvious then that we first need to define regions. This may be easy if we can simply use the islands of an island group, but taking a big blob of land like Australia as an example, how do we cut that up? States? Clearly political units are kind of iffy for biogeography, because they are human inventions. Climate or vegetation zones are more natural, but are they meaningful for our specific study group? How meaningful would a region be for my purposes that happens to have one of my study taxa scored as present because it comes in from the side into 5% of that region's extent?

To me at least it seems as if the solution is bioregionalisation by taxon content: take small units like 100 x 100 km cells or similar and use an objective bioregionalisation approach to group them into meaningful larger regions. As mentioned above this maximises endemism, which is precisely what I would want for the inference of ancestral areas and biogeographic history.

MCDA spam

Ye gods, I got an absolute gem of science spam yesterday.

We wish you a happy new year.

Well, at least no greetings of the day, so that is good.

It's so pleasant to communicate with eminent people like you through this email.

Is it brown-nose day already?  I had not noticed.

I believe that your efforts will create the good reputation for my Journal. Our MCDA journal is in shortfall of one article to accomplish the issue. So, we request you to submit any type of article towards our journal. I would be highly obliged with your swift submission process. Hope you will support us.

And this is where it all falls over. Why does this spammer think that I should care about the reputation of their journal? If they were a car dealer, would they say, I believe that your purchase will increase my profits, I need another sale to make my target? As opposed to, say, stressing the price to performance ratio of the car. If they were a university recruiter, would they say, I believe that your enrolment would create the good reputation for my university? As opposed to, say, claiming that the already good reputation of their university would transfer onto the prospective student?

Well, maybe that is what they would do. But that is not how it works. I am not in sales, but even I know that if you are selling something you have to convince the prospective buyer that buying is in their interest, not only in yours.

Await your article submission.
Regards,
Emma Wright Š Modern Concepts & Developments in Agronomy (MCDA)
LLC, Third Avenue, 2nd floor, New York - 10016, USA

If this message is the English of an Emma Wright in New York I will not only eat my hat but a whole stack of them.

Also, just as an aside, the message did not even contain a link to the journal website!

It displays a level of incompetence so profound, so all-encompassingly fractal, that there is truly no hope for this spammer. How can anybody who is able to write an eMail without trying to eat the keyboard look at this spam message and think, yes, this is going to convince people that I am running a serious scientific journal?

Cell phone with macro lens

Happy new year, everybody! Time to get back to blogging.

Lately I have been playing around with a macrolens that I bought for my smartphone. The idea was to be able to take pictures of small structures, in particular fruits or seeds, even when I do not have my proper camera with me. So far the results are mixed.

Here we have the fruit of Hypochaeris radicata (Asteraceae), one of the larger propagules I have tried so far. Not too bad, all in all, but I do not care about the shadow, and obviously the depth of field is an issue.

The above is a mericarp of Malva neglecta (Malvaceae). The surface structure looks nice, but again light conditions and shadows are problematic. I will have to do something about light and the texture of the background.

It works reasonably well for flowers in sunlight, however. Here a tomato flower. As this will likely be the use case for most people I guess one cannot complain. It would be a fair deal given that the lens package cost me only $20 (including wide angle and fish-eye lenses, which I don't really use).

No, the blockchain does not actually appear to be useful for anything much

Merry belated Christmas and a happy new year! For the following note that this is my personal opinion, which I present not as a professional statement and as not necessarily representative of the views of my employer, colleagues, friends and family. I am not a specialist in investment, nor in blockchain technology.

So it is fairly clear that the blockchain based crypto-"currency" Bitcoin is in a speculative bubble. Owning a Bitcoin is not like owning a useful commodity or the share of a company. The price of Bitcoin is entirely based on the assumption that others are willing to pay at least that price at some point in the future, which sounds like a good definition of speculative bubble thinking. (The same may well apply to some degree to the Australian housing market, but at least there you still have a house even if it is currently overvalued; with Bitcoin you will only have a bunch of electrons when the price is corrected to $0).

It is also fairly clear that the ICO (Initial Coin Offering) market is in a speculative bubble. I have been reading the finance section of Charles Mackay's Memoirs of Extraordinary Popular Delusions and the Madness of Crowds, and his descriptions of the various stock offerings during the English South Sea Bubble of 1720...

In the mean time, innumerable joint-stock companies started up every where. [...] Some of them lasted for a week or a fortnight, and were no more heard of, while others could not even live out that short span of existence. Every evening produced new schemes, and every morning new projects.
[...]
Some of these schemes were plausible enough, and, had they been undertaken at a time when the public mind was unexcited, might have been pursued with advantage to all concerned. But they were established merely with the view of raising the shares in the market. The projectors took the first opportunity of a rise to sell out, and next morning the scheme was at an end. Maitland, in his History of London, gravely informs us, that one of the projects which received great encouragement, was for the establishment of a company "to make deal boards out of saw-dust." This is no doubt intended as a joke; but there is abundance of evidence to shew that dozens of schemes, hardly a whit more reasonable, lived their little day, ruining hundreds ere they fell. One of them was for a wheel for perpetual motion--capital one million; another was "for encouraging the breed of horses in England, and improving of glebe and church lands, and repairing and rebuilding parsonage and vicarage houses." [...] But the most absurd and preposterous of all, and which shewed, more completely than any other, the utter madness of the people, was one started by an unknown adventurer, entitled "A company for carrying on an undertaking of great advantage, but nobody to know what it is." Were not the fact stated by scores of credible witnesses, it would be impossible to believe that any person could have been duped by such a project.

 ... read eerily similar to the current craze in ICOs. Check out this excerpt from David Gerard's book Attack of the 50 Foot Blockchain, which I can recommend, by the way. I am not an investment expert, but even I can tell that "whatever these people do, I'm going all in" is not so much a sophisticated investment strategy as mania.

Blockchain technology

It is amazing how often one will read from otherwise sensible people something to the effect of "clearly Bitcoin is worthless, and ICOs are a bubble, but the blockchain is an amazing technology". In fact I was shocked some weeks ago to be sitting in a meeting of taxonomists and hearing somebody say words to the effect of, "it would be great if we could somehow use blockchain in taxonomy", apparently just to be in on something newfangled.

Even without going into any details this seems kind of odd. Surely the rational way to go about one's business is to say, hey, here is a problem, does anybody know a solution?, as opposed to, hey, here is a supposed solution, can we all pretend that we have a problem that it solves?

But let's take a closer look nonetheless. What is a blockchain? And what could it be useful for, perhaps even in taxonomy?

I am going to simplify here, obviously, but to the best of my understanding a good mental model of a blockchain is as follows. Imagine you have a database or, even simpler, an Excel style table. In the realm of taxonomy, let's assume it is a big sheet showing, for each published species name in your country, what its type specimen is, where the name was published, and what the currently accepted name is. This latter piece of information may be a reference to a different line on your sheet if the name has been synonymised, and if the field is empty then the name is accepted. (Again, simplified assumptions.)

One way of managing this taxonomic database is to have one authoritative version of your sheet sitting on the computer of a trusted, central authority, where everybody can look it up and download it, for example like this one. When changes need to be made the central authority implements them on their master copy, done.

As I understand it, the blockchain way would be to have no central authority. Instead, the sheet is distributed in numerous identical copies across lots of different networked computers. The network needs some kind of process for deciding who gets to make a change to the sheet ever so often. Bitcoin uses a tremendously wasteful procedure, but it seems as if there are less wasteful ones that could be used instead. The point is still that instead of one central authority we have lots of copies that constantly need to be harmonised against each other.

Notice something? Of course you do. The whole affair can be made considerably more efficient by simply centralising it, by creating a central trusted authority that manages the one accepted copy, and by dispensing with all the equivalent copies that constantly have to be harmonised against each other. The blockchain approach is just a waste of storage space and computing power.

Really the only reason anybody ever seems to have thought that the decentralisation inherent in blockchain is a good idea is a pathologic distrust of central authority, and concerning crypto-currencies like Bitcoin specifically a pathological distrust of government.

(I am wondering a bit whether there is some kind of psychological projection at work. As an illustrative example take conservative, fundamentalist Christians. Why do they constantly fear that secularists are going to outlaw Christianity, including harmless things like saying "Merry Christmas"? Is it perhaps because outlawing every belief system except their own is what they would do the second they had the power to do so, and they cannot fathom that there are other people out there who are very different, people who genuinely believe that everybody else should be allowed to practice their religion as they see fit, even if they personally don't believe in it? Similarly here I wonder if the proprietarian-libertarian anarcho-capitalists who are constantly afraid that Evil Government Thugs will print so much money that inflation will be at 10,000% are so afraid because abusing government power to enrich themselves is what they would do the second they had such power. Maybe they simply cannot fathom that there are many other people out there who are very different; people who do not constantly obsess about Getting Rich Quick and gloating at the less fortunate but who are happy to live on a modest salary; craftspeople who are simply proud of making high-quality products; academics who simply enjoy figuring out how the world around us works; public servants who genuinely find satisfaction working for the common good; and central bankers who take serious their mandate of keeping inflation near 2%. Not a psychiatrist myself, but wondering.)

So again, nearly every system using a blockchain could immediately be improved by removing the blockchain. But there is another problem. One of the main selling points of the blockchain is that it is "tamper-proof" or in other words "immutable". Again this is an expression of pathological distrust, here the fear that others would tamper with a list of transactions or some other kind of valuable information. For Bitcoin, for example, one of the selling points is that all transactions are irreversible, the idea being that a merchant has the confidence that the customer cannot reverse a payment.

The problem should be immediately obvious: What if a mistake has happened? What if fraud has happened, and the result has already been written into the blockchain? In reality, there is simply close to no market for immutability and irreversibility. All human relationships and interactions have an element of trust, and trying to replace that with the blockchain is doomed to failure.

In financial transactions the merchant benefits more from customers having the confidence that they can reverse transactions with fraudsters than they would from customers becoming very hesitant to make any transactions at all. In other systems the same principle applies: If I were running a taxonomic database, for example, I would want the ability to reverse vandalism or mistakes. As far as I can tell blockchain technology is superfluous and wasteful, and most of its supposed selling points actually appear to be drawbacks.

For a more thorough examination of the issue I can recommend Kai Stinchcombe's essay Ten years in, nobody has come up with a use for blockchain, but of course he does not consider taxonomy :-).

Philosophy of mind: consider the children

'Thanks' to a post on Crooked Timber I had the misfortune of finding David Bentley Hart's review of Daniel Dennett's new book From Bacteria to Bach and Back.

Hart's 'review' is not so much a review as a meandering, bile-filled rant wrapped up in obscurantist terminology. I find it very hard to extract an actual argument from it, mostly because of the lack of a clear line of thought. But to the degree that there is a core to what he seems to be trying to say, he claims that (a) language and (b) our mind or consciousness are irreducibly complex. To quote only the perhaps most immediately relevant parts:

There is simply no causal narrative -- and probably never can be one -- capable of uniting the phenomenologically discontinuous regions of "third-person" electrochemical brain events and "first-person" experiences, nor any imaginable science logically capable of crossing that absolute qualitative chasm.

Then there is the irreducible unity of apprehension, without which there could be no coherent perception of anything at all, not even disjunctions within experience. As Kant among others realized, this probably poses an insuperable difficulty for materialism. It is a unity that certainly cannot be reduced to some executive material faculty of the brain, as this would itself be a composite reality in need of unification by some still-more-original faculty, and so on forever, and whatever lay at the "end" of that infinite regress would already have to possess an inexplicable prior understanding of the diversity of experience that it organizes. For, even if we accept that the mind merely represents the world to itself under an assortment of convenient fictions, this would involve a translation of sense data into specific perceptions and meanings; and translation requires a competence transcending the difference between the original "text" and its rendition.

This problem, moreover, points toward the far more capacious and crucial one of mental intentionality as such -- the mind's pure directedness (such that its thoughts are about things), its interpretation of sense experience under determinate aspects and meanings, its movement toward particular ends, its power to act according to rationales that would appear nowhere within any inventory of antecedent physical causes. All of these indicate an irreducibly teleological structure to thought incongruous with a closed physical order supposedly devoid of purposive causality.

Similarly, there is the problem of the semantic and syntactic structure of rational thought, whose logically determined sequences seem impossible to reconcile with any supposed sufficiency of the continuous stream of physical causes occurring in the brain.
[...]
In every case, most of his argument consists in a small set of simple logical errors. The most conspicuous is one I think of as the "pleonastic fallacy": the attempt to explain away an absolute qualitative difference -- such as that between third-person physical events and first-person consciousness -- by positing an indefinite number of minute quantitative steps, genetic or structural, supposedly sufficient to span the interval. Somewhere in the depths of phylogenic history something happened, and somewhere in the depths of our neurological machinery something happens, and both those somethings have accomplished within us an inversion of brute, mindless, physical causality into, at the very least, the appearance of unified intentional consciousness.
[...]
Everything in nature must for him be the result of a vast sequence of tiny steps. This is a fair enough position, but the burden of any narrative of emergence framed in those terms is that the stochastic logic of the tale must be guarded with untiring vigilance against any intrusion by "higher causes." But, where consciousness is concerned, this may very well be an impossible task.
[...]
So, for Dennett, language must have arisen out of social practices of communication, rooted in basic animal gestures and sounds in an initially accidental association with features of the environment. Only afterward could these elements have become words, spreading and combining and developing into complex structures of reference. There must then, he assumes, have been "proto-languages" that have since died away, liminal systems of communication filling up the interval between animal vocalizations and human semiotic and syntactic capacities.

Unfortunately, this simply cannot be. There is no trace in nature even of primitive languages, let alone proto-languages; all languages possess a full hierarchy of grammatical constraints and powers. And this is not merely an argument from absence, like the missing fossils of all those dragons or unicorns that must have once existed. It is logically impossible even to reverse-engineer anything that would qualify as a proto-language. Every attempt to do so will turn out secretly to rely on the syntactic and semiotic functions of fully developed human language. But Dennett is quite right about how immense an evolutionary saltation the sudden emergence of language would really be. Even the simple algorithm of Merge involves, for instance, a crucial disjunction between what linguists call "structural proximity" and "linear proximity" -- between, that is, a hypotactic or grammatical connection between parts of a sentence, regardless of their spatial and temporal proximity to one another, and the simple sequential ordering of signifiers in that sentence. Without such a disjunction, nothing resembling linguistic practice is possible; yet that disjunction can itself exist nowhere except in language.

And so on, believe it or not, in the same tone for a total of more than 5,400 words. I cannot for one moment image writing a book review of even half of that length.

Anyway, this is pretty much the same argument as always. A creationist would say, look, the eye is really complicated. Half an eye would not work, so how could an eye have evolved? And Hart says, look, language / consciousness is really complicated. There is no half-language or half-consciousness, so how could they have evolved?

Now unfortunately for the creationist, nature abounds in half-eyes, so to say. Extant animals show everything from single light-sensitive cells across groups of such cells arranged in a little depression of the skin across ocelli to vertebrate style camera eyes of varying degrees of sophistication. Hart has it a bit easier in that our ancestors who would have had half-languages are gone, so he finds it possible to claim that such intermediates are unthinkable.

It is less clear to me how the same claim can reasonably be made about consciousness given the obvious progression in mental capability from worms to chimpanzees, but let's assume for present purposes that there is a vast gulf between us and any other species on the planet. The problem is still that Hart's position falls apart the moment somebody vaguely gestures towards children. This idea is not original to me, indeed one of the commenters on the otherwise mostly distressingly woolly Crooked Timber thread soon made the same point.

Note what I am not saying. I am not saying that Dennett is right about everything he wrote in his book. I have not read it, nor do I have any intention of doing so anytime soon. More to the present point, I am not saying that human ontogeny recapitulates evolutionary history. I am not saying that a six month old human's mind is a very accurate model of a rodent mind or suchlike.

But it is nonetheless obviously and demonstrably the case that every human starts as one cell, clearly without a consciousness, and (if healthy and unharmed) develops gradually into an extremely complex being with what Hart calls consciousness*. Yes, somewhere during ontogeny "something happens", and as far as I can tell most of us would accept that it is gradual. This indicates that gradual evolution can well be assumed to have produced this outcome, no magic involved.

Likewise it is obviously and demonstrably the case that young humans do not suddenly acquire "a full hierarchy of grammatical constraints and powers" in one go. Has Hart actually ever communicated with a toddler? We acquire our language competence gradually, and again this indicates that humans can well be assumed to have acquired language competence gradually over the course of their evolution.

For language in particular it is indeed trivial to visualise how even very rudimentary language immediately confers an advantage. Forget grammar; merely being able to grunt a few words meaning "danger", "food", and "shelter" while pointing into the distance would have served our ancestors quite well at some point. Next they may have come up with a few verbs. Even without tenses and suchlike "you wait; me go" will convey useful information, and of course lots of tourists successfully communicate at this level in a local language.

Again, I do not know how good Dennett's book is. Nor do I claim to have all the answers. But sometimes it is quite easy to tell that a given answer must be wrong even if you don't know what the right answer is. And it is really fascinating to read with what a tone of condescension Hart argues that there cannot be a gradualist explanation for capabilities that are demonstrably acquired gradually during human ontogenetic development.

----

*) Another point potentially to be made here is that certain philosophers of mind frustratingly take terms that have been invented to give a name to an observed phenomenon and then mystify them to the point where they cannot imagine a non-magic explanation for the phenomenon.

Consciousness is a perfect example. When our ancestors came up with that word they would have done so to describe the difference between a sleeping, knocked-out, drugged or dead person on one side and an awake and aware person on the other. They would then at some point have observed that while for example a beetle may be kind of awake and aware it does not appear to have the same awareness of itself (~consciousness) as a human. Finally a certain type of philosopher of mind comes in, picks up the term consciousness, reinterprets this label slapped on an observed distinction into a mysterious substance sitting in human heads, and claims that such a mysterious substance cannot be explained scientifically.

I would take one step back and say, no, actually this is straightforward in principle (if not necessarily easy in practice): that person over there is sleeping, just study how the brain processes differ from when they are awake and you have your explanation. Of course this is not what the philosopher means, but it is what consciousness means! The same goes for qualia, experience, apprehension, intentionality, and a whole host of other buzzwords used by Hart. They all have been created to describe observed distinctions, and being observable they can be studied using empirical science.

Luckily most scientists and philosophers understand the difference between things and processes, the concept of emergent processes, and the fallacies of composition, division and reification. (The last of these seems particularly relevant to how Hart discusses the terms mentioned in the previous paragraph.)