A PhD student position is available in the lab of Heroen Verbruggen at the University of Melbourne to work on the evolution of ecological niches of marine algae.

You will study how ecological niches of marine algae change over evolutionary timescales and how the niche affinities of lineages influence their speciation-extinction dynamics. The project involves field work, DNA sequencing, molecular phylogenetics, ecological niche modeling and evolutionary modeling.

To be successful you will:

  • satisfy the requirements for a PhD degree at the University of Melbourne (http://goo.gl/VGRgQ)
  • have experience in generating and managing DNA sequences
  • have a strong interest in evolutionary biology and mathematical modeling
  • evidence strong oral and written communication skills

To find out more, follow these links:

To apply, send your CV, a representative piece of English writing (e.g. MSc thesis), and the names and contact information of two or more references (at least one previous supervisor) to heroen.verbruggen@unimelb.edu.au. Informal enquiries are welcome.

This position is now filled.


I’ve just uploaded new versions of OccurrenceThinner and RasterTools on my web site.

OccurrenceThinner is a tool that performs distance-based thinning of species occurrence data to reduce geographic sampling bias in niche modeling. It takes a set of species occurrence records and a kernel density grid file as input. It then filters out occurrence records using a probability-based procedure. More information is available on the software website. The new version 1.04 fixes a problem reading the header of certain ASCII files. Thanks to Diego Nieto-Lugilde for pointing out the problem. The option to round coordinates to a user-specified number of decimals is no longer included for reasons described below.

Within RasterTools, two minor updates were done.

The script moveCoordinatesToClosestDataPixel.jar was updated to version 1.03. The main update here is that this version includes the possibility to specify a distance threshold for moving coordinates. Many thanks to Niels Raes, who suggested this on the Maxent forum. In addition, it fixes the same issue mentioned above and it does not permit rounding the coordinates to a specified number of decimals anymore. In some cases, the rounding caused coordinates to move into no-data pixels, which is exactly the opposite of what this script is supposed to do. Thanks to Vanessa Marcelino for pointing out this problem.

The script extractDataForCoordinates.jar was updated to version 1.03, fixing the same issue with ASCII headers.

In the context of Vanessa Marcelino’s Msc thesis on the evolutionary dynamics of Halimeda seaweeds we were trying to visualize niche conservatism or the lack thereof across a whole bunch of species simultaneously.

As it turns out, making a heat map of niche model similarities gave a very satisfactory result. We calculated two niche overlap measures (Schoener’s D and Warren’s I) for the species’ Maxent models using ENM Tools. The resulting matrices were merged into one with Schoener’s D in the top right triangle and Warren’s I in the lower left triangle. Species were sorted in the matrix in the order that they appeared in the phylogeny, so related species are closer together in the matrix. The similarity values were then converted to colors along a green-yellow-red color gradient with MatrixGradients. The result looks like this (follow this link for PDF version):

heat map

Looks very cool. Well, mostly red and hot actually… The first striking pattern is that D values are on average lower than I values. The fact that almost the entire figure is red indicates that niches are highly conserved in Halimeda. There is also a green-yellowish cross going across the figure (as a horizontal and a vertical band of dissimilar niches). This band represents the species that have invaded colder water and these are related to one another, so they lie together in the matrix. The first column/row is also very dissimilar to all the rest. This is the sole Mediterranean species, which occurs in much colder water than all other species in the genus.

Here are the legend and the way the table was built, just to complete the picture:


I’ve just posted a new version of Maxent Model Surveyor on my web site (link).

Maxent Model Surveyor is a program that evaluates different sets of predictors and different model complexities for Maxent niche modeling. It automatically calculates the test AUC and the Akaike and Bayesian information criteria (AIC, BIC; Warren & Seifert 2011) under the various predictor sets and model complexities and suggests “suitable” sets of predictors and model complexities for your dataset.

Version 1.04 includes the option to specify a custom test dataset when exploring models based on test AUC. I’ve included this option because we wanted to identify a suitable set of predictors that would not bias analyses towards one or the other ocean basin (Atlantic vs. Indo-Pacific). We have many species that occur in one of both ocean basins and when comparing models between strictly Atlantic and strictly Indo-Pacific species, environmental differences between ocean basins could in theory bias the comparison. To avoid this, one could look for predictor sets that have good predictive power across ocean basins for species that do occur in both ocean basins and avoid those predictor sets that don’t.

In closing I want to mention that I’ve renamed this program to Maxent Model Surveyor (instead of the previous Maxent Model Selector) because “surveying” is a more appropriate description of what it does and I don’t want to encourage people to simply let the program “select” a predictor set and model complexity. Programs like this are no substitute for a good understanding of your organism’s physiology and serve as a guiding tool only.

I just came across a very interesting opinion paper titled “No name, no game” published in the European Journal of Taxonomy.

The paper was written by Yves Samyn of the “Belgian National Focal Point to the Global Taxonomy Initiative” (I think we all agree they need an acronym) and Olivier De Clerck of Ghent University. I’ve known Yves since we were both on a field trip in KwaZulu-Natal (South Africa) many years ago, and Oli is a great colleague and friend who I’ve worked with very closely for over ten years.

They argue that, in contrast to what Joppa et al. (2011) claim, today’s taxonomic workforce is not sufficiently large to describe the remaining pool of missing species within a reasonable amount of time. This is in the first place because much larger numbers of species remain to be described for many understudied taxa than for the well-studied groups of organisms that Joppa et al. (2011) included in their analysis. In addition, the massive numbers of unnamed species in the Genbank and BoLD databases suggest that there is another layer of undiscovered diversity remaining to be characterized (coined “dark taxa” by Rod Page). This is certainly relevant for algae as these unnamed species (e.g. “Rhodymenia sp. 1SA“) are discovered en masse when DNA barcodes are generated and “dark algal species” are accumulating rapidly in Genbank (see figure below; >75% dark taxa in the three main algal groups in 2011). The great majority of these discovered species remain without a proper name because formally describing them is much more laborious than discovering them.

algal dark taxa

Yves and Oli argue that this widening gap between the number of discovered and described species is problematic, focusing their argument on the fact that these newly discovered species do not have names. They argue that scientific names matter for society, for example because legislation (e.g. CITES) uses species names as currency.

While I agree with most of the paper, in particular the part about promoting an increasing role for developing countries in characterizing their biodiversity, I think that Yves and Oli fail to make a convincing case for their “no name, no game” statement. In my opinion, traditional binomials are not needed for legislation to work or for scientists and non-specialists to communicate about species. When the bird flu hit, the specialist as well as the greater audience knew and understood what H5N1 was. Just like professional and amateur astronomers have no trouble communicating about “55 Cancri e”. What would make biologists different? All one needs to communicate about a species is some sort of identifier, not necessarily a formally described species binomial.

When it comes to legislation and conservation, I agree that it is important to be able to pinpoint exactly what is being conserved. But once again, does it need a binomial? Not having to go through the process of describing a newly discovered species would permit that species to be conserved more rapidly. Furthermore, for legislative purposes, diagnosability of the species should be more important than the name of the species. And at least for algae, where DNA data have become the gold standard for species delimitation, DNA sequences are rapidly becoming much more reliable for species identification than morphological keys to named species. While the DNA vs. morphology contraposition should not play a major role in this discussion, it is relevant because the great majority of dark taxa are discovered through DNA sequencing and can future collections can easily be identified as the dark taxon in question with a DNA barcode. In other words, DNA sequencing has changed the game, and because of that I think we should think more along the lines of “no name, new game” instead of “no name, no game”.

Once again, I agree with what Yves and Oli wrote about the taxonomic workforce not being large enough to describe the remaining pool of species in understudied groups within a reasonable timeframe using traditional procedures. As do I agree with most other points made in the paper. But do we really need formal species binomials for all newly discovered taxa? Are there arguments that support the “no name, no game” statement that I have overlooked here? Or arguments in favor of the “no name, new game” alternative that I have not mentioned? I welcome your ideas in the comments.

Most of the projects that my coworkers and I work on involve analyses of big datasets with information about algal specimens. One of Tom Schils‘ projects that I’m helping out with aims to sketch an image of the geographical patterns of seaweed diversity using a combination of tools. Tom’s been accumulating floristic information that we are now trying to complement with DNA sequence data to characterize how species diversity and phylogenetic diversity are distributed on earth.

The Hawaiian Algal Database is a superb resource of information about — you guessed it — Hawaiian algae. The data were generated, compiled and put online by Alison Sherwood and Gernot Presting of the University of Hawaii at Manoa, and a report about the dataset was published in BMC Plant Biology. It’s a specimen-centered database that has all sorts of metadata including geographical coordinates, information about the collection site, and in many cases DNA sequences of up to 3 markers from different genomes (yes, algae have 3, at least).

Because the data are available only through the online HADB interface, Tom encouraged me to write a script to download the information we needed to integrate the Hawaiian data with ours. I wrote a Perl script that uses the LWP library to download and store the information in a more analysis-friendly format. In case anyone is interested, I’m linking the script here.

I downloaded information for the 221 specimens of brown algae, 238 of green algae and 2163 of red algae in the dataset. What’s absolutely great is that for the reds, 61% of the samples have been sequenced; that’s 1333 sequenced specimens belonging to 213 unambiguously named species! Unfortunately far fewer specimens of greens (43) and browns (25) were sequenced.

Stats for Hawaiian Algal Database specimens

So, HADB is a great addition to the data we have from Genbank and other sources and will no doubt help us understand the geographical distribution of algal phylogenetic diversity. Thanks to the Hawaii group for generating these data and making them available.

I’ve just started my new job at the University of Melbourne, in the School of Botany and thought that was enough of a reason to start a new blog.

I’m on a fellowship funded by the Australian Research Council and during the coming four years, I will be studying the evolutionary dynamics of algae. The project aims to characterize how ecological niches evolve and document how trace metal utilization changes over time and across the algal tree of life. If you’d like to read more about the project, have a look at the project page on the lab’s web site.

The purpose of this blog is to keep a record of ideas and activities as I’m making progress with this project. I look forward to receiving your reactions, especially if they can steer me in the right direction or just keep me sane while I tackle the challenges ahead of me.