Looking around for a topic to write about, I found a recent paper in Nature that struck me for four reasons. The first is how it ties into my previous post about repeated patterns in evolution of sticklebacks in higher latitudes. This new paper uncovers a surprising pattern in marine fish biodiversity – the fastest rates of speciation occur in polar regions of the globe – not tropical waters. These results are paradoxical because polar regions also have the lowest species richness of fishes. The prevailing dogma is that lower latitudes harbor higher levels of biodiversity on land and in the sea and higher rates of marine species formation in the tropics have been inferred in fossil molluscs, plankton, and coral. However, the authors found the fastest overall rate of speciation occurs in the south polar seas within icefishes and their relatives. The mean speciation rate is over two times greater in the Southern Ocean around Antarctica than in the Coral Triangle in the Indo-Pacific, the marine region exhibiting the highest species richness. Though there is little overlap in species that occur in the southern and northern polar regions, the northern seas exhibit high speciation rates as well. Moreover, there is a high correlation between endemism and speciation rate. A notable exception is the Mediterranean Sea, which shows high endemism, but a low speciation rate. Clearly, there’s something about the high latitudes that’s conducive to high rates of evolution in marine fishes. How can it be that the tropical latitudes harbor the most number of species if the rate of species generation is so much higher in the polar regions? One obvious hypothesis is that the extinction rate is much higher at the poles as well. The authors were unable to examine extinction rates in this study, but mention elsewhere that their current work is exploring this avenue.
The second reason this paper grabbed me is the sheer amount of data and analysis effort that went into this study. First of all, the authors constructed a time calibrated phylogeny of all ray-finned fishes, including 31,526 tips, 11,638 with genetic data. The time calibration was achieved by surveying the palaeontological literature and museum collections to gather a 139-taxa fossil calibration set. They generated or downloaded from Genbank sequence data for those 11638 taxa for 27 genes. They distilled geographic distribution information for all marine fish species with data available, using AquaMaps, but incorporated expert opinions and museum records to refine distributions to estimate geographic ranges to 150 x 150 km grid cell resolution for 12,050 marine species. They also calculated mean speciation rates for 232 marine biogeographic ecoregions. All of this biogeographic data came from four major biodiversity occurrence aggregators (Global Biodiversity Information Facility, Ocean Biogeographic Information System, Fishnet2, and VertNet), which amounted to 13,322,575 marine fish occurrences. In addition, 132 institutions world-wide significantly contributed occurrence records to this study.
The authors estimated speciation rates in several ways, employing the diversification rate statistic, λDR, for each tip in the 31,526 taxon phylogenies, then averaged across the set of 100 trees generated with stochastic polytomy resolution and two Bayesian Analysis of Macroevolutionary Mixtures with and without time-varying rate regimes (λBAMM and λBAMM-TC). Finally, a simple node density estimate for a sequence of intervals between 0.25 and 50 Mya. Mean speciation rate was estimated by grid cell, by geographic region, and by latitudinal mid-point. There are nine extended data figures included with the otherwise brief paper that delve into how cell rates may change the results, taking into account depth of occurrence (in case the speciation rates are more of a deep sea phenomenon as opposed to a higher latitude one. It’s not.), endemism, and the temporal dimension of the rate heterogeneity, among others. Clearly, the museum, digital archivist, ecological, evolutionary, palaeontological, taxonomic, and bioinformatic expertise needed for this work is staggering.
The third reason I wanted to draw attention to this paper was its uncovering of errors in Genbank. When exploring the files deposited in Dryad, I came across a table called “sequence_blacklist” that lists all the sequences that were excluded from the analyses and why. Of the 577 records, 185 were excluded because they blasted to a different organism than what they were identified as, including two that blasted to Homo sapiens. I mention this because databases are only as good as their entries. It is up to us to provide Genbank with high quality submissions and to CORRECT ERRORS when they are uncovered. If you, dear reader, have deposited any sequences into Genbank from any fish species, I implore you to check the table mentioned above. It’s your open source scientific duty.
The final reason I wanted to highlight this paper is the glorious figure below. I confess that I often suffer from figure envy when I read papers. Constructing an elegant, visually captivating figure is a skill I do not have and would desperately like to cultivate. When I come across one like the one below, I immediately think of how I would go about making it on my own and I invariably come up short. I have so many questions for the authors. How long did this take? Was it originally more than one? How many different programs did you need to get the final version? Did anyone try to talk you out of a figure so complex? Were the fish drawn by hand, then scanned, or rendered in a graphics program? There is so much information packed into this figure, but it comes across clearly and completely considering the scads of data and analyses behind it. Truly a masterpiece.
References
Daniel L. Rabosky, Jonathan Chang, Pascal O. Title, Peter F. Cowman, Lauren Sallan, Matt Friedman, Kristin Kaschner, Cristina Garilao, Thomas J. Near, Marta Coll, Michael E. Alfaro. An inverse latitudinal gradient in speciation rate for marine fishes. Nature, 2018; DOI: 10.1038/s41586-018-0273-1