Steps towards understanding comparative methods

Using phylogenetic comparative methods warrants a basic understanding of the history and progress of this field.  Working with some of the more recent tools for comparative evolutionary biology, I feel compelled to find out how current methods were devised, whom to credit for the methods I use, and what assumptions I am making by using them.  Below is a list of some of the landmark papers in comparative methods, with comments and synopses (written by me and Tomomi).

Felsenstein (1981) describes the basics for creating a maximum likelihood tree from a set of nucleotide sequences. One step elaborated from his 1973 paper is Felsenstein’s pruning algorithm for calculating the likelihood of a phylogenetic tree given branch lengths and tip values.  This algorithm makes likelihood calculations more computationally efficient by eliminating redundant calculations.  The paper also describes the Markov process for finding the maximum likelihood tree from nucleotide data.  Felsenstein uses a substitution model for molecular phylogenetics in which each nucleotide has a different stationary frequency (A, C, G, and T are not expected to be equally represented at any given site on DNA sequences).  Methods for searching tree space have been improved, and Bayesian theory has since permeated phylogenetic analyses, but the pruning algorithm continues to be an important subroutine in phylogenetic computations.

Possibly the most cited paper in phylogenetic comparative methods, Felsenstein (1985) describes with clear examples why species trait values may not be statistically independent and what might be done to compensate.  Felsenstein elaborates on his method of calculating standardized contrasts (phylogenetically independent contrasts) to help overcome the non-independence of character traits.  These contrasts are basically the differences between trait values of species pairs weighted by the evolutionary change separating them; they are estimates of the rate of change over time. A common use of standardized contrasts is to look for correlation in this rate between two traits; if standardized contrasts of traits X and Y are compared in a regression analysis, a linear trend suggests correlated rates of evolution between the traits.

Schluter et al. (1997) discuss the need for error estimates on ancestral state reconstructions. The paper introduces maximum likelihood ancestral state reconstructions of both discrete and continuous characters.   Responding to Schluter et al.’s call to account for error in tree construction, Huelsenbeck et al. (2003) describe a Bayesian method for mapping the change in character states onto a phylogeny.  The introduction reiterates the importance of having an alternative to parsimony methods when tackling character change; as with maximum likelihood, the new methods allow for more than one change along a given branch in the tree.  While the Huelsenbeck et al. paper is a landmark for evolutionary analysis, it also contains a very coherent introduction to the instantaneous rate matrix, substitution model, and likelihood calculations for finding the probabilities of evolutionary histories.

Although Brownian motion is often used to model quantitative character evolution, the Ornstein-Uhlenbeck (OU) process can also be used to develop informative evolutionary models.  OU models incorporate selection as a selective optima, or adaptive peak.  OU and Brownian motion are not entirely unrelated as OU collapses to Brownian motion in the absence of selection.  Butler and King (2004) use OU to test which of several evolutionary models has the best fit to several example data sets involving anoles.  They use likelihood ratio tests to determine how various OU-based models perform against Brownian motion, observing that biological information is important in determining what models to consider.  They also stress that stasis, although positive support for stabilizing selection, is often disregarded and can lead to underestimation of evolutionary drift.  However, although they state that Brownian motion is a pure drift process, Brownian motion can provide a good fit to selective schemes under fluctuating directional selection (O’Meara et al. 2006).

While Grafen (1989) first describes a generalized least squares model for phylogenetic regressions, Chris O. from our lab pointed out the appendix of a paper on mammal intestines (Lavin et al. 2008) as a nice summary of PGLS.  This appendix describes both the history and the methods of phylogenetic regression analysis.  PGLS can be performed not only under a Brownian motion model, but also with OU and several other transformations of the variance-covariance matrix used in the mixed model approach.

 

These are just a handful of important papers; feel free to add to the list via comments with other references and their contributions.

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Size, Scales and Sceloporus

This weeks blog (also posted on my blog) is a departure from fish, but is about a recent paper of mine that uses phylogenetic comparative methods to test hypotheses for body size and scale evolution among Sceloporus lizards.

Oufiero, C.E.$, G.E.A. Gartner$, S.C. Adolph,  and T. Garland Jr. 2011. Latitudinal and climatic variation in scale counts and body size in Sceloporus lizards:  a phylogenetic perspective. In press  Evolution. DOI: 10.1111/j.1558-5646.2011.01405.x
$ These authors contributed equally

This summer the lab has a reading group on phylogenetic comparative methods, where we are reading through some of the classic phylogenetic papers discussing the various methods. This past week we focused our attention on phylogenetic generalized least squares methods or PGLS. This method was introduced by Grafen in 1989, and although it wasn’t initially a common phylogenetic comparative approach, has seen more use in recent years. For those not familiar with this method, it utilizes a regression approach to account for phylogenetic relationships. In this method the phylogeny is converted to a variance-covariance matrix, where the diagonals in the matrix represent the “summed length of the path from the root of the tree to the species node in question (Grafen 1992).” That is, how far each tip is from the root; in an ultrametric tree the diagonals in the variance-covariance matrix will all be the same. The off diagonals represent the “shared path length in the paths from the root to the two species (Grafen 1992)”. In other words, the off diagonals are the distance from the root to the last common ancestor for the two species. Similar to independent contrasts, this method assumes Brownian motion evolution; however, unlike independent contrasts PGLS assumes the residual traits are undergoing Brownian motion evolution, whereas independent contrasts assumes the characters themselves are undergoing Brownian motion evolution. The other main difference  in PGLS is the use of raw data instead of computing independent contrasts. In short, the PGLS approach is similar to a weighted regression, where the weighted matrix is the variance-covairnace matrix based on the phylogeny of the group, and assuming the same phylogeny will produce the same results as independent contrasts.

So what does this have to do with size, scales and Sceloporus? Well, in a recent study we used a PGLS approach to examine patterns of body size and scale evolution in relation to latitude and climate among Sceloporus lizards. Sceloporus (fence and spiny lizards) are a group of more than 90 species of lizards found from Central America up to Washington State in the U.S. Throughout their range they experience a diversity of habitats, from deserts to tropical forests to temperate forests; and have been used in many studies examining physiological ecology, life history evolution and thermal biology. In our study we used Sceloporus to test two hypotheses for the evolution of morphology. 1) Lizards  exhibit an inverse Bergmann’s Rule, with larger individuals found at lower latitudes and/or warmer climates. 2) Lizards from hotter environments will exhibit fewer and thus larger scales to aid in heat dissipation; whereas lizards from colder environments will exhibit more/smaller scales to aid in heat retention. There has been conflicting results for these hypotheses in the literature, and latitude has often been used as a proxy for climate. However, one of the unique things about our study is the incorporation of multivariate techniques to describe habitat. We use latitude as a predictor as well as climatic variables (temperatures, precipitation and a composite aridity index Q), and also utilize principal component analysis to characterize habitat. We therefore can test for specific climate predictors of these traits without assuming that higher latitudes necessarily equate to colder environments.

To test our hypotheses we gathered data on 106 species and populations of Sceloporus from the literature and museum specimens. We obtained latitude from the literature and source maps, and climate date from the International Water Management Institute’s World Water and Climate Atlas (http://www.iwmi.cgiar.org/WAtlas/Default.aspx). Using a recent phylogenetic hypothesis for Sceloporus (Wiens et al. 2010) we examined the relationship between maximum snout-vent length with latitude and 5 climatic predictors under three models of evolution (no phylogenetic relationships (OLS), Brownian motion (PGLS) and a model in which the branch lengths are transformed in an Ornstein-Uhlenbeck process (RegOU). To examine hypothesis 2 we examined a multiple regression with dorsal scale rows as the dependent, body size as a covariate and latitude or one of the 5 climatic predictors as independents. We also compared results with principal components 1-3 as predictors of dorsal scale counts.

So what did we find? First, we found that phylogenetic models (PGLS or RegOU) were always better fit than non-phylogenetic (OLS) based on likelihood ratio tests and AICc scores. We also found that as latitude increases mean and minimum temperatures decrease, as well as precipitation and aridity, but maximum temperature tends to increase. Thus, lizards from this group found at higher latitudes may be experiencing more desert like environments. 

For hypothesis 1, we found support for the inverse of Bergmann’s Rule when viewed from a climatic perspective; larger lizards were found in areas with higher maximum temperatures, but not at lower latitudes. We also found that larger lizards were found in more arid environments.

Photo copyright Mark Chappell

Our results for hypothesis 2 were a little more complex. We did not find support for the first part of hypothesis 2, lizards with fewer scales were not found in hotter environments. We did find support for the second part of hypothesis 2, lizards with more scales are found in environments with lower minimum temperatures. We also found a positive effect of latitude, and a significant negative effect of aridity (with lizards with more scales inhabiting more arid environments). Results with principal components were also consistent, with PC1  (a latitude/temperature axis) having a significant negative effect on scale count; and PC2 (a maximum temperature/precipitation axis) having a significant positive effect.

Our results suggest several things. First, latitude alone may not be an accurate description of the environment organisms face, particularly at the finer spatial scales over which an individual species may exist. Second, we found support for the inverse of Bergmann’s Rule at the inter-specific level, which has also been found to be a consistent trend intra-specifically in some ectotherms (see Ashton and Feldman 2003). Finally, our analyses suggest that both temperature and precipitation (hence aridity) are important to the evolution of scale counts in this group. These findings also suggest that scale size may be important for other physiological processes, such as evaporative water loss (lizards in more arid environments may have more/smaller scales to reduce rates of evaporation through the skin as has been suggested by Soulé and Kerfoot 1972 ). Examining the relationship of morphological traits that may function in physiological processes may provide insight into how these organisms may respond to global of climate change.

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Stickleback attack (part 1)

Since our last video posting, many of the videos on our lab’s Youtube channel have gone viral. As of this blog post, the video of Inermia vitatta has accrued over 120,000 hits and has been featured on TV programs and newspaper articles around the globe. Not bad for a small fish!

Today’s video features the threespine stickleback, Gasterosteus aculeatus, feeding on a cladoceran (Daphnia pulex). If you have a short attention span like me, one of the first things you’ll notice from the video is how shiny the fish is. The reflective armor plates and large spines are a clue that this is a threespine stickleback from an anadromous population. Anadromous stickleback have a life history similar to a miniature salmon – they are born in freshwater, travel to the ocean, then return to freshwater to breed. Unlike salmon, anadromous stickleback do not necessarily return to their home stream to breed. Anadromous stickleback also look very similar to each other – an Alaska anadromous fish looks very similar to a California anadromous fish.

Sometimes, these anadromous stickleback will travel to a newly-formed lake or river, and instead of returning to the ocean, some fish will stay in freshwater, founding a new population of freshwater stickleback. Over time, this freshwater population will evolve to better match its new freshwater habitat.

These anadromous and freshwater populations are one of the reasons stickleback are such a good system for studying evolutionary biology. We can study the result of rapid evolution in the freshwater populations, and then turn around and study the anadromous fish that resemble the fish that founded the freshwater population. Studying ancestral and derived populations is one of the few ways – short of a time machine – that we can learn the dynamics of adaptation in natural populations.

If we study how this anadromous stickleback captures prey, and then study how freshwater stickleback catch prey, we can learn a lot about the process of adaptation. I’ve devoted much of my PhD work to studying this system, and I’ll be talking more about it in future posts.

Posted in adaptation, armor plates, high speed video, Research, stickleback, sticklematt, Uncategorized | Leave a comment

Showcasing the latest phylogenetic methods: AUTEUR

While high-speed fish feeding videos may be the signature of the lab, dig a bit deeper and you’ll find a wealth of comparative phylogenetic methods sneaking in.  It’s a natural union — expert functional morphology is the key to good comparative methods, just as phylogenies hold the key to untangling the evolutionary origins of that morphology.  The lab’s own former graduate, Brian O’Meara, made a revolutionary step forward in the land of phylogenetic methods when he unveiled Brownie in 2006, allowing researchers to identify major shifts in trait diversification rates across the tree.  This work spurred not only a flood of empirical applications but also methodological innovations, such as Liam’s brownie-lite, and today’s focus: Jon Eastman et al.‘s auteur package.

Auteur, short for “Accommodating uncertainty in trait evolution using R,” is the grown-up Bayesian RJMCMC version of that original idea in Brownie.  Diversification rates can change along the phylogenetic tree — only this time, you don’t have to specify where those changes could have occurred, or how many there may have been — auteur simply tries them all.

If you want the details, definitely go read the paper — it’s all there, clear and thorough.  Meanwhile, what we really want to do, is take it out for a test drive.

The package isn’t up on CRAN yet, so you can grab the development version from Jon’s github page, or click here.  Put that package in a working directory and fire up R in that directory.  Let’s go for a spin.

install.packages("auteur_0.11.0612.tar.gz", repos=NULL)
library(auteur)

Great, the package installed and loaded successfully. Looks like Jon’s put all 73 functions into the NAMESPACE, but it’s not hard to guess which one looks like the right one to start with.  rjmcmc.bm.  Yeah, that looks good.  It has a nice help file, with — praise the fish — example code.  Looks like we’re gonna run a simulation, where we know the answer, and see how it does:


## generate tree
n=24
while(1) {
phy=prunelastsplit(birthdeath.tree(b=1,d=0,taxa.stop=n+1))
phy$tip.label=paste("sp",1:n,sep="")
rphy=reorder(phy,"pruningwise")

# find an internal edge
anc=get.desc.of.node(Ntip(phy)+1,phy)
branches=phy$edge[,2]
branches=branches[branches>Ntip(phy) & branches!=anc]
branch=branches[sample(1:length(branches),1)]
desc=get.descendants.of.node(branch,phy)
if(length(desc)>=4) break()
}
rphy=phy
rphy$edge.length[match(desc,phy$edge[,2])]=phy$edge.length[match(desc,phy$edge[,2])]*64

e=numeric(nrow(phy$edge))
e[match(c(branch,desc),phy$edge[,2])]=1
cols=c("red","gray")
dev.new()
plot(phy,edge.col=ifelse(e==1,cols[1],cols[2]), edge.width=2)
mtext("expected pattern of rates")

## simulate data on the 'rate-shifted' tree
dat=rTraitCont(phy=rphy, model="BM", sigma=sqrt(0.1))

That creates this beautiful example (sorry, no random generator seed, you’re results may vary but that’s ok) tree:


Okay, so that’s the target, showing where the shift occurred.  Note the last line got us some data on this tree.  We’re ready to run the software.  It looks super easy:

## run two short reversible-jump Markov chains
 r=paste(sample(letters,9,replace=TRUE),collapse="")
 lapply(1:2, function(x) rjmcmc.bm(phy=phy, dat=dat, ngen=10000, sample.freq=10, prob.mergesplit=0.1, simplestart=TRUE, prop.width=1, fileBase=paste(r,x,sep=".")))

The data is going in as “phy” and “dat”, just as expected.  We won’t worry about the optional parameters that follow for the moment.  Note that because we use lapply to run multiple chains, it would be super easy to run this on multiple processors.

Note that Jon’s creating a bunch of directories to store parameters, etc.  This can be important for MCMC methods where chains get too cumbersome to handle in memory.  Enough technical rambling, let’s merge and load those files in now, and plot what we got:

# collect directories
dirs=dir("./",pattern=paste("BM",r,sep="."))
pool.rjmcmcsamples(base.dirs=dirs, lab=r)

## view contents of .rda
load(paste(paste(r,"combined.rjmcmc",sep="."),paste(r,"posteriorsamples.rda",sep="."),sep="/"))
print(head(posteriorsamples$rates))
print(head(posteriorsamples$rate.shifts))

## plot Markov sampled rates
dev.new()
shifts.plot(phy=phy, base.dir=paste(r,"combined.rjmcmc",sep="."), burnin=0.5, legend=TRUE, edge.width=2)

# clean-up: unlink those directories
 unlink(dir(pattern=paste(r)),recursive=TRUE)

Not only is that a beautiful plot, but it’s nailed the shift in species 12-16.  How’d your example do?

Auteur comes with three beautiful large data sets described in the paper.  Check them out, but expect longer run times than our simple example!


data(chelonia)
# take a look at this data
> chelonia
$phy
Phylogenetic tree with 226 tips and 225 internal nodes.

Tip labels:
Elseya_latisternum, Chelodina_longicollis, Phrynops_gibbus, Acanthochelys_radiolata, Acanthochelys_macrocephala, Acanthochelys_pallidipectoris, ...

Rooted; includes branch lengths.

$dat
Pelomedusa_subrufa                   Pelusios_williamsi
2.995732                             3.218876
...
dat <- chelonia$dat
phy <- chelonia$phy
## ready to run as above
 

Thanks Jon and the rest of the Harmon Lab for a fantastic package. This is really just a tip of the iceberg, but should help get you started. See the paper for a good example of posterior analyses requisite after running any kind of MCMC, or stay tuned for a later post.

Posted in blogging on peer-reviewed research, phylogenetics, software | 1 Comment

Inermia vittata: Camera Debut

Below is one of the first ever recorded high-speed video sequences of Inermia vittata, a zooplanktivore from the tropical western Atlantic.  We are using its first live appearance in the lab to see how the feeding kinematics of Inermia compare with that of other reef fishes.  Watch how far that upper jaw projects forward!

One common name for this fish is the bonnetmouth, named after the appearance of the protruded mouth.  Like other reef zooplanktivores, Inermia appears qualitatively to be specialized at picking prey from the water column.  As you can see in the video, the mouth reaches forward, closing the distance to the prey while preparing to pull the prey closer with suction.

The evolutionary relationship of Inermia to other species has been tricky to resolve because it is very similar in appearance and behavior to other zooplanktivores such as fusiliers (Lutjanidae).  However, molecular analysis shows Inermia to be nested within the grunts (Haemulidae), which typically feed on benthic invertebrates.  A look at the pictures below will show how much different Inermia appears from a typical grunt and how similar it looks to the distantly-related fusilier.

boga boga bonnetmouth boga

Our new star, Inermia vittata (Photo by Patrick Fuller)

Doubleline fusilier

A fusilier, close relatives of snappers (Lutjanidae) (Photo by Erik Schlögl)

French grunt

A close relative of Inermia (Photo by Brian Gratwicke)

Why does Inermia look so different from a typical grunt, and why does it look so similar to a distantly related species?  Perhaps the feeding mechanisms captured in these videos can help to resolve this evolutionary anomaly.

Posted in adaptation, coral reef fish, fish feeding, high speed video | Leave a comment

Stickleback camouflage

This week, the Wainwright blog returns to a topic of perennial interest, the threespine stickleback. I will discuss a recent paper from the Schluter lab at UBC on color plasticity and background matching in stickleback.

To set the stage, it’s important to realize that from a stickleback’s perspective, “bird” is a four-letter word. Predation by diving birds like grebes and coots is commonplace in many freshwater stickleback populations. Unlike predatory dragonfly larva, which detect prey by vision and by water movement, diving birds generally detect their prey by sight alone. In other words, if you’re a freshwater stickleback, it’s very important that the top of your body blends in with your surroundings.

This stickleback didn't get the memo. (http://www.lifeontheslea.co.uk )

In this paper, Jason Clarke and Dolph Schluter tried to assay background matching capability between limnetic and benthic sticklebacks in Paxton Lake, British Columbia. First, they used a spectrometer to record the background color in the limnetic and benthic habitats. The open-water limnetic habitat was a bluish color, but the benthic habitat, which has more aquatic vegetation, tended to be more greenish. Additionally, the benthic habitat showed much more variation in color than the limnetic habitat.

After checking the background color, the authors painted two sets of cups, one designed to look like the limnetic background, and one designed to look like the benthic background. Then they put benthic and limnetic sticklebacks on each background, let them adjust their color for 15 minutes, photographed each fish, then measured how well each fish matched its background. They also did the same experiment again, but this time taking pictures every 20 seconds.

What did they find? Limnetic fish and benthic fish were equally good at matching the blue limnetic background, but limnetic fish were not as good at matching the green benthic background as benthics were. The time trial experiment helped to clear up what was going on: benthics rapidly adapted their colors to match the background, but limnetics were doing something different. Limnetic fish were cycling through different colors instead of fixing a particular color. Limnetics were more variable in color when viewed with a benthic background, but even on their “home turf” in the limnetic background, they still showed variation in color, but to a lesser degree.

The authors suggest that the patterns of color chance exhibited by benthics and limnetics are probably adaptive. Their spectrometer data indicates that the benthic habitat is more variable in color, and their background experiments show that benthics are better at rapidly changing their colors to match the background. The limnetic habitat, on the other hand, is much more uniform, so there would be little incentive for limnetics to evolve rapid color matching. However, limnetics may be adapting to their light environment in an entirely different way:  the  “flickering” exhibited by limnetics could be an adaptation to fluctuating light intensity in open water.

After reading this paper, I’m particularly curious what the color-matching abilities of the ancestral marine sticklebacks are like. If they resemble the limnetic, then this color matching ability will be another interesting benthic stickleback adaptation. It will be cool to see if it is possible to discern the genetic basis for this shift in plasticity.

Clark JM, Schluter D. Colour plasticity and background matching in a threespine stickleback species pair. Biological Journal of the Linnean Society. DOI: 10.1111/j.1095-8312.2011.01623.x

Posted in benthic, ecology, limnetic, plasticity, stickleback, sticklematt, Uncategorized | Leave a comment

An optical illusion?

Zooplanktivory is one of the most distinct feeding niches in coral reef fish and many morphological traits have been interpreted as adaptations to feeding on plankton in the water column above the reef. One of these traditional hypotheses is that zooplanktivorous fish have larger eyes for sharper visual acuity. A larger eye usually has a longer focal length and thus is expected to produce a better-resolved image.

Peter and I tested this hypothesis with a data set on eye morphology of labrids (wrasses and parrot fishes):

Schmitz, L. & P.C. Wainwright (2011). Ecomorphology of the eyes and skull in zooplanktivorous labrid fishes. Coral Reefs, 30: 415-428. reprint.

Labrids are a species-rich clade of reef fish with enormous morphological and ecological diversity. We sampled a total of 21 species, with three independent origins of zooplanktivory: Clepticus parrae, the Creole Wrasse (photo: fishbase.org), Halichoeres pictus, the Rainbow Wrasse (photo: wetwebmedia.com), and Cirrhilabrus solorensis, the Red-eyed Fairy Wrasse (photo: fishbase.org).

To our surprise we failed to find any indication of larger eyes in zooplanktivores. We tried several methods, including phylogenetic residuals of eye diameter on body mass and evolutionary changes in eye size along branches leading to zooplanktivores, but zooplanktivorous labrids did not show any signs of having larger eyes than other trophic specialists. Instead, we suspect that the notion of large eyes in zooplanktivorous labrids is an optical illusion evoked by a size reduction of the anterior facial region, which makes the eye look bigger.

However, we did find other features interpreted as adaptations to zooplanktivory in labrids. Both Clepticus parrae and Halichoeres pictus have a large lens for given axial length of the eye, related to better visual acuity, a round pupil, possibly an adaptation to search a three-dimensional body of water for food, and longer gill rakers to help retain captured prey.

Our results are quite interesting in that they highlight the importance of many-to-one-mapping in form-function relations. There often is more than one possible pathway to perform a function. In labrids, increase in eye size to improve visual acuity apparently is not part of the evolutionary response. But, let’s see what we can find in other groups!

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Evolution Meeting 2011, Norman, OK

A majority of the lab is presenting at the Evolution Meetings in Norman, OK this weekend.  Almost all of our talks use a group of fish as a model system (Labrids, Haemulids, pupfish, sticklebacks, Xiphophorus, and reef fish), but our topics are very broad;  including sexual selection, morphological diversity, ecological novelty, nocturnality, phylogenetic comparative methods and ecological speciation. Below is a list of our talks at the meeting. Bold indicates presenting author. Hope to see you there.

Chris Martin and Peter Wainwright
Beyond ecological opportunity: adaptive radiation and the origins of novel ecological niches.
Sunday, June 19th, 1:45 pm, in room Oklahoma D, Ecological Speciation session.

Matt McGee
Functional morphology and kinematics of feeding in stickleback: implications for ecological
speciation.
Sunday, June 19th, 2:00 pm, in room Oklahoma D, Ecological Speciation session.

Lars Schmitz and Peter Wainwright
The effect of diel activity pattern on eye shape in reef fishes.
Monday, June 20th, 11:00 am, in room University C, Morphological Evolution II session.

Samantha Price, Peter Wainwright, Roi Holzman, Jose Tavera, Thomas Near
Reef habitats promote the evolution of morphological diversity in fishes.
Monday, June 20th, 11:15 am, in room University C, Morphological Evolution II session.

Carl Boettiger
A new phylogenetic comparative method to estimate key evolutionary transitions involving a release of constraint. (slides)
Monday, June 20th,  4:00 pm, in room Oklahoma A, Phylogenetic Methods V session

Chris Oufiero, Kristine Jugo, Mark Chappell, Theodore Garland, Jr.

Does the evolution of a sexually selected trait compromise sprint and endurance performance in Xiphophorus swordtails and their close relatives?
Tuesday, June 21st, 9:15 am, in room University A, Sexual Selection & Behavior session.

Posted in Meetings, Presentations | Tagged , | Leave a comment

Is this fish crazy?

This post is cross-posted with my personal website’s Blog.

We recently got some new fish in the lab, Butis butis, commonly called the crazy fish or Duckbill Sleeper. This is a fresh water fish, originating from East Africa to Fiji and belongs to the Eliotridae. These fish get to a maximum size of about 15 cm total length, live in brackish mangrove swamps and estuaries, feeding on small fish and crustacean, and is commonly found in the hobby industry.

The question is, are these fish in fact crazy? These fish tend to be unique because they can be seen swimming, floating, and even eating upside down. This behavior has been noted in nature and in aquariums, where they will also be seen pressed up the glass. They tend to be ambush predators and are often found floating among plants, in any position. Having them in the lab, we have begun filming them and have been able to capture their feeding right-side up and upside down. What will be interesting to see is if the kinematics of their feeding differs between the orientations, as well as if one orientation is better than the other at eliciting successful strikes. In the meantime, enjoy the videos of these crazy fish feeding in the two orientations.

Upside down filmed at 1000 frames per second, played back at 10 frames per second.

Right-side up filmed at 1000 frames per second, played back at 10 frames per second.

Posted in fish feeding, high speed video, Research | Tagged , , , | 1 Comment

Explosive evolution in pupfish

Pupfish are indeed the only group of fish named after puppy dogs for their playful behavior. They’re best known for their ability to survive in extreme environments, like desert hot springs. However, for my dissertation research, I have focused on understanding their evolution and diversification.

Pupfish show a remarkable pattern of adaptive diversification: in only two small lake systems throughout their entire range, pupfishes are evolving from 50 – 130 times faster than all other pupfish species. Truly ‘explosive evolution‘ – the fastest morphological diversification rates measured so far in fishes, and one of the fastest rates documented among all organisms. Further, other pupfish groups of similar young age do not show such extreme rates.

Figure 3 in paper. The pupfish heat map. Colors indicate the rate of evolution for 16 traits relative to other pupfishes in a: Lake Chichancanab pupfishes and b: San Salvador Island pupfishes.

What is going on here? The short answer is the evolution of novel ecological niches. Cyprinodon pupfishes occur throughout the Caribbean and along the Atlantic coast from Massachusetts to Venezuela and as far inland as isolated springs in California and Mexico. Throughout their entire range, pupfishes are ecological generalists: they eat mostly algae, decaying vegetation, and whatever insects or crustaceans they can catch. Yumm! Although different species can often be distinguished by differences in male coloration, or subtle differences in body or fin shape, pupfish species on the whole are anatomically very similar, particularly in jaw shape. Further, multiple pupfish species never coexist in the same habitat.

Except in two places. These are the only two places throughout their entire range where multiple pupfish species coexist and specialize on entirely new resources. On the tiny island of San Salvador in the Bahamas (only 11 miles long!), three pupfish species coexist in the inland salty lakes. Incredibly, one of these has evolved to feed almost entirely on the scales of other pupfishes! While scale-eating has evolved at least 14 times in other groups of fishes, within the 1,500 species of atherinimorphs, to which pupfish belong, this undescribed pupfish species is the only known scale-eater! While previous researchers speculated that it may eat scales or other fish, I was stunned to find only scales and no whole fish when I began examining the guts of this species (n = 60). This behavior is easy to watch in the field – the scale-eater stalks any nearby pupfish, quickly orienting perpendicular to its prey, striking and biting off scales, then stealthily moving on to the next target, just like a pup-tiger.

Cyprinodon sp. ‘scale-eater’: Males in full breeding coloration photographed in their natural habitat on San Salvador Island.

There is a second ecologically specialized species in these San Salvador lakes. This species has shortened jaws for crushing its diet of snails and ostracods. Moreover, it has a nose! This is one of the few fish species that tucks its jaw underneath protruding nasal tissue surrounding protruding bones (maxilla and nasal) on the face of the fish.

Cyprinodon sp. ‘nose’ What looks like an upper lip in this photo is actually the fish’s nose protruding outward above the fish’s tucked upper jaw.

The function of this peculiar fish nose is so far unknown (or any fish nose, for that matter). I do have a couple guesses: perhaps it helps stabilize the fish’s jaw while crushing hard shells. Or, it may help with species recognition, as males gently nudge females when trying to entice them to spawn.

The second remarkable place for pupfish diversification is Lake Chichancanab, Mexico, a large, brackish lake in the center of the Yucatan peninsula (Chichancanab is Mayan for “little lake” or “little girl lake”, whichever you prefer). Chichancanab contained at least five coexisting species of pupfishes, including four ecological specialists. One of these, Cyprinodon maya, is the largest pupfish species known and also the only pupfish to eat other fish. A second species, Cyprinodon simus, is the second smallest pupfish species, and was observed feeding on zooplankton in large shoals in open water. Piscivory and zooplanktivory are unique pupfish niches found only in Lake Chichancanab.

Terribly, these descriptions of Chichancanab species are in past tense. In the early 1990’s, invasive African tilapia (probably Oreochromis mossambicus) were introduced to Lake Chichancanab. In addition, the native Mexican tetra, Astyanax sp., was also introduced. All specialized pupfish species promptly declined in abundance and frequency over the next 10 years. I visited the lake in 2009 and after surveying thousands and thousands of fish from several different basins of the large lake, I observed zero Cyprinodon maya and only one putative hybrid Cyprinodon simus. These specialized species are now functionally extinct in the lake. Thankfully, they have survived in home aquaria and backyard fish ponds in the US thanks to the efforts of dedicated aquarium hobbyists in the American Killifish Association. I am now maintaining these extinct-in-the-wild species in the lab as well.


Cleared and stained specimenof Cyprinodon maya (top), the only piscivore pupfish.

Cleared and stained specimen of Cyprinodon simus (bottom), the only zooplanktivore pupfish. Note the dramatic difference in the thickness of their lower and upper jaws. These specimens were collected in the wild before invasive species were introduced and generously loaned for this research by the University of Michigan Museum of Zoology.

Thus, in only two remarkable lake systems throughout their entire range, pupfish are speciating and adapting to novel trophic resources, like scales, snails, other fish, and plankton. These two groups of pupfishes also happen to be showing the fastest rates of evolution among all pupfishes. Probably not a coincidence: invasion of these novel ecological niches is driving incredible rates of morphological change, particularly in jaw shape.

It is particularly remarkable to see this pattern within pupfish, a group of fishes that has repeatedly been isolated in new, extreme environments and also probably has repeatedly adapted to these new environments. Several other groups of pupfishes were also evolving fast in my analysis – around 5 – 10 times faster than average, such as the groups containing the Devil’s Hole pupfish, a tiny species restricted to the smallest habitat of any known organism, a tiny cave shaft in Death Valley, shown here:

Devil’s Hole, Death Valley National Park, Nevada. This vertical shaft of water stays a balmy 94 degrees F year-round and divers have not yet found the bottom (at least 400 feet deep). Cyprinodon diabolis is restricted to eating scarce algae off a tiny rock shelf near the surface and its population size has fluctuated between 37 and around 400 fish.

Cyprinodon pachycephalus also belongs to a quickly evolving group. This is the pupfish species that lives and breeds in the hottest waters of any known vertebrate, 114 degrees Fahrenheit year-round!

These are incredibly extreme environments that would be expected to drive rapid rates of morphological evolution. Indeed, these species are changing quickly, but the Devil’s hole pupfish and C. pachycephalus are both generalist detritivores, just like their relatives.

However, to really see explosive evolution appears to require that pupfish start dabbling in entirely new ways of life, to go where no pupfish has ever gone before. (this wouldn’t be blogging without Star Trek!)

But, I haven’t yet fully answered the question I originally posed. Why have novel trophic niches evolved in these two places and nowhere else across their entire range? Certainly, the size of these two lakes and lack of competitors (except native mosquitofishes) plays a role. But, there may be many similar lakes with similar fish communities throughout the Caribbean. What is going on here? This remains an outstanding research question, one I am actively pursuing.

For the full story and contact information, please see the paper:

Martin and Wainwright. In press. Trophic novelty is linked to extremes rates of morphological diversification in two adaptive radiations of Cyprinodon pupfishes. Evolution. 

Posted in adaptation, blogging on peer-reviewed research, diversification, ecological novelty, phylogenetics, pupfish | Leave a comment