How did the Ice Ages affect three Scrubwrens in the highlands of Papua New Guinea?

Genomic study looks for signatures of population expansion or contraction.

For many bird species, their evolutionary history is a series of population expansions and contractions. This is especially apparent during the Pleistocene (between 2.5 million and 11,000 years ago) when the climate fluctuated between cold and warm periods. As the climate warmed, certain vegetation types expanded, followed by the bird species that reside within them. These expansion and contraction dynamics leave traces in the genetic make-up of the bird populations. Several population genetic statistics have been developed to detect the signatures of these processes.

In 1989, for example, the Japanese researcher Fumio Tajima introduced a statistic to discriminate between population expansion and contraction: Tajima’s D. I will not go into the mathematical details (you can check out the excellent video by Mohamed Noor below), but in general you can interpret this statistic as follows: a negative Tajima’s D points to population expansion, while a positive Tajima’s D suggests population contraction. However, similar patterns can also arise due to different selection events (e.g., balancing selection or selective sweeps). That is why it is important to calculate other population genetic statistics to tease these processes apart. Or you could take a modelling approach where you compare different demographic models and see which one explains the data best. And that is exactly what researchers in a recent study in the journal BMC Evolutionary Biology did.


ABC Models

Kritika Garg and her colleagues focused on three scrubwren species on Mt. Wilhelm, the highest mountain of Papua New Guinea. These small passerines occur at different altitudes along this mountain. The buff-faced scrubwren (Aethomys perspicillatus) is restricted to lower montane forest at 1500–2450 meters, while the Papuan scrubwren (A. papuensis) can be observed in the upper montane habitat above 2000 meters. The third species – the large scrubwren (Sericornis nouhuysi) – can be found across the widest range, from 1500 to over 2000 meters. The researchers sequenced the DNA of 74 individuals and applied Approximate Bayesian Computation (ABC) analyses to the data. This computational method allows you to estimate the likelihood of several parameters under particular demographic models. In this case, we are interested in the population sizes over time.

A topographical map of Papua New Guinea indicating the sampling locations in black and red dots. The inset shows the area around Mt. Wilhelm. From: Garg et al. (2020) BMC Evolutionary Biology.


Ålesund Interstadial

The demographic analyses revealed that all three species experienced a population expansion between 27,000 and 29,000 years ago. This timeframe coincides with the Ålesund Interstadial that occurred about 30,000 years ago when a drop in global temperatures impacted the distribution of vegetation on Mt. Wilhelm.

The strong cooling would have shifted elevational belts down the slope, expanding the area of habitat available to montane forest birds such as the three scrubwrens, and sometimes even connecting populations that would have previously been stranded on separate mountain ranges.

The genetic consequences of these population expansions are also reflected in the lack of population genetic structure in the three species. As individuals expanded their range and potentially interbred with other populations, any differences between subpopulations would be erased. The researchers also calculated Tajima’s D for the three scrubwren species and unsurprisingly it was negative in all species. Hence, all the evidence clearly points to population expansions.

For all three species, Tajima’s D was clearly negative, suggesting population expansions. From: Garg et al. (2020) BMC Evolutionary Biology.



Garg, K. M., Chattopadhyay, B., Koane, B., Sam, K., & Rheindt, F. E. (2020). Last Glacial Maximum led to community-wide population expansion in a montane songbird radiation in highland Papua New Guinea. BMC evolutionary biology20(1), 1-10.

Featured image: Large Scrubwren (Sericornis nouhuysi) © Katerina Tvardikova

Genomic study unveils the true identity of Brewster’s and Lawrence’s Warbler

Are they first generation hybrids, backcrosses or something else?

Some bird hybrids were initially described as distinct species. I have covered some notable examples on this blog, such as Rawnsley’s Bowerbird (Ptilonorhynchus rawnsleyi) and Argus Bare-eye (Phlegopsis barringeri). In most cases, the species name disappears when the hybrid identity of the bird has been revealed, but sometimes the name stays around. In papers on hybridization dynamics between Golden-winged Warbler (Vermivora chrysoptera) and Blue-winged Warbler (V. pinus), you often come across Brewster’s Warblers and Lawrence’s Warblers. The latter two “species” turned out to be hybrids. In 1893, Sage already expressed his doubt by stating that ‘I am not inclined to believe leucobronchialis [i.e. Brewster’s Warbler] a hybrid, but hope to have more to say on this subject at another time.” However, the names are still used to indicate the characteristics of these birds.

“Lawrence’s” hybrids are similar to Blue-winged Warblers (i.e. yellow overall, with 2 narrow white wing bars) but have the black throat patch and face mask, similar to Golden-winged Warblers. “Brewster’s” hybrids, by contrast, lack a black throat patch, have little to no yellow on the underparts, and commonly have partially separated yellowish wing bars.

Based on these traits, Nichols (1908) and Parkes (1951) speculated that first generation hybrids would look like Brewster’s Warblers, while second generation hybrids and backcrosses would resemble Lawrence’s Warblers. With the advent of genomic data, we can put these hypotheses to the test. In a recent study in the journal The Auk, Marcella Baiz and her colleagues examined the genetic make-up of nine Vermivora warblers.

The different species and hybrids of Vermivora Warblers. From: Baiz et al. (2020) The Auk.


Hybrid Triangles

To figure out whether Nichols and Parkes were right, the researchers used triangle plots. Based on two statistics – heterozygosity and hybrid index – you can deduce what kind of hybrid or backcross you are dealing with. Pure individuals are located in the lower corners, while first generation hybrids are at the top. The sides of the triangles (D1 and D2) indicate backcrosses. You would thus expect that Brewster’s Warblers (F1) end up at the top and Lawrence’s Warblers at the sides (backcrosses) of these triangles.

This was, however, not the case. The sequenced individuals were scattered across the triangle and did not follow the predictions by Nichols and Parkes. The Lawrence’s Warbler in this study is not a backcross, but probably a multigenerational hybrid with mostly Blue-winged Warbler ancestry. Similarly, the Brewster’s hybrids are not F1 hybrid, but can trace the majority of their ancestry to either parental species. It thus seems that these hybrid types are quite variable and that F1 hybrids and backcrosses are not easy to distinguish based on the coloration of their underparts.

An example of a triangle plot (left, adapted from Pulido-Santacruz et al. 2018). In this case, you would expect Brewster’s Warblers (F1) at the top and Lawrence’s Warblers at the sides (backcrosses) of these triangles. The results show a different picture, indicating that the hybrids are quite variable (right, from Baiz et al. 2020).


Black Throat Patch

The story of the black throat patch is very different. Previous work by David Toews and his colleagues uncovered high genetic differentiation between Golden-winged and Blue-winged Warblers near the gene ASIP. This candidate gene has been linked to plumage differences in other bird species, such as Sporophila Seedeaters, Setophaga Warblers and Lonchura Munias. In this study, the researchers could zoom in on the genomic region where this gene resides. They found genetic variants in front of ASIP, suggesting that mutations in the regulatory sequences – the on-and-off switches – are responsible for the presence or absence of a black throat patch. Gene expression studies are needed to confirm this prediction. So, we moved on from one set of predictions (by Nichols and Parkes) to the next one. In science, we call that progress!

A clear signal of genetic differentiation at the ASIP gene (highlighted in grey). From: Baiz et al. (2020) The Auk.



Baiz, M. D., Kramer, G. R., Streby, H. M., Taylor, S. A., Lovette, I. J., & Toews, D. P. (2020). Genomic and plumage variation in Vermivora hybrids. The Auk, 137(3), ukaa027.

Featured image: Golden-winged Warbler (Vermivora chrysoptera) © Caleb Putnam | Wikimedia Commons


This paper has been added to the Parulidae page.

Isolated Icterids: Unraveling the evolutionary history of the Altamira Oriole

What processes explain the genetic and morphological variation in this neotropical species?

Speciation involves the build-up of genetic differences between populations in isolation. But this “isolation” can take many forms. Populations might be separated over large distances, preventing the exchange of genetic material (isolation by distance). Or populations might become isolated by historical processes that affect topographic features, such as rivers and mountain ranges (isolation by history). Or populations might adapt to different environmental conditions in a heterogenous landscape, lowering the chances of interbreeding (isolation by environment). These types of isolation are not mutually exclusive and can interact. Not an easy knot to disentangle. A recent study in the journal Molecular Ecology, however, rose up to the challenge and attempted to figure out what isolating factors can explain the evolution of the Altamira oriole (Icterus gularis).


Genetic Patterns

The Altamira oriole is a brightly colored songbird from Central America. Taxonomists recognize three subspecies based on body size: the large gularis, the small mentalis, and the intermediate flavescens. Lucas Moreira and his colleagues studied populations from all subspecies, using molecular and morphological methods.

The genetic analyses revealed two distinct clusters, divided by the Chivela Pass, a narrow mountain gap separating three mountain chains in southern Mexico. The split between these populations occurred about 150,000 years ago, but the populations remained connected by occasional gene flow. It seems that the Chivela Pass functioned as a kind of funnel that limited dispersal between the northern and southern populations. Within both populations, the researchers detected signatures of isolation by distance, but no effect of environmental factors. Hence, the genetic data point to isolation by history and isolation by distance.

The genetic data suggested two main cluster (one in blue and one in red/green) separated by the Chivela Pass. From: Moreira et al. (2020) Molecular Ecology.


Morphological Measurements

The morphological data tell a completely different story. Measurements of wing, bill and tarsus length indicated two main groups, representing small and large individuals. These differences in body size were best explained by climatic variables, such as precipitation and temperature. In general, Altamira orioles are larger in hotter and drier areas. Whether these morphological differences have a genetic basis or are due to phenotypic plasticity remains to be determined. Nonetheless, morphological variation can best be explained by isolation by environment.

Morphological variation (here: wing length) correlates with environmental factors, such as (a) temperature and (b) precipitation. From: Moreira et al. (2020) Molecular Ecology.


Discrepancy Explained

The fact that genetic and morphological patterns are driven by different isolation mechanisms makes sense from a genomic point of view. Isolation by history and isolation by distance tend to affect the entire genome, and it is thus easier to pick up these patterns with molecular markers that cover the whole genome (RADseq in this study). The morphological differences are often the outcome of natural selection, which tends to target small genomic regions and is thus more difficult to detect without whole genome data. A genomic study of the Altamira oriole might thus uncover some contribution of isolation by history to the morphological differences.

In addition, the different processes underlying genetic and morphological variation also explain the disagreement in taxonomic studies where genetically focused ornithologists clash with morphologically minded ones. This study again highlights that it is more insightful to understand the evolutionary and ecological processes behind speciation instead of having endless discussions about species status based on every small genetic difference or morphological detail.



Moreira, L. R., Hernandez_Ba_os, B. E., & Smith, B. T. (2020). Spatial predictors of genomic and phenotypic variation differ in a lowland Middle American bird (Icterus gularis). Molecular Ecology, 29(16), 3084-3101.

Featured image: Altamira Oriole (Icterus gularis) © Kati Fleming | Wikimedia Commons

The complex interplay between tRNA genes and transposable elements in bird genomes

New tRNA genes can emerge through multiplication by transposable elements.

Transfer RNAs (tRNAs) are an underappreciated group of molecules. Apart from transporting the amino acids to the protein-synthesizing ribosomes, they fulfil are range of other important functions in the cell (nicely summarized in this review). During a six-month postdoc at the Karolinska Institute (Stockholm, Sweden), I entered the wonderful world of tRNA genes under the expert guidance of Claudia Kutter. The tRNA-team further consisted of PhD-student Keyi Geng and transposon-guru Alexander Suh. Taking advantage of the increasing number of available bird genomes, we explored the evolutionary dynamics of tRNA genes in our feathered friends. And we were in for some surprises! But before we dive into the results, let’s refresh some basic molecular biology.


The Genetic Code

DNA contains the instructions to make proteins. But the DNA alphabet consists of four letters (A, T, G and C), while the language of the proteins has twenty letters (i.e. amino acids). How does the cell translate DNA language into protein language? The Russian physicist George Gamow looked at the problem through a mathematical lens. How can you combine four letters so that each of the twenty amino acids has a unique DNA code? A code based on two DNA letters does not work, because it only yields sixteen combinations. Not enough for the twenty amino acids. But a code with three DNA letters is possible. That code results in 64 different letter combinations, more than enough for twenty amino acids.

However, this solution led to another problem. Which combination of three DNA letters codes for which amino acid? In 1954 the American biologist James Watson founded the RNA Tie Club with Gamow to crack this genetic code. This club had twenty members (one for each amino acid) and four honorary members. Each member was given a woolen tie with the double helix embroidered on it. One of its members, South African biologist Sydney Brenner, suggested the term “codon” to refer to a combination of three DNA letters. Sixty-four codons and twenty amino acids. Who could solve this puzzle?

The first codons were deciphered with simple experiments. Scientists made long strands containing one DNA letter in the lab. These strands were then translated by a cell into a chain of amino acids. When one strand of As was used, a long chain of the amino acid lysine was formed. And if a strand of C’s was translated, the chain consisted only of the amino acid proline. The conclusion was crystal clear: AAA codes for lysine and CCC codes for proline. With further experiments, researchers deciphered the entire genetic code. The code even turned out to contain start and stop signs. The codon ATG – which codes for methionine – marks the starting point of a protein, while the codons TAA, TGA and TAG signal the end.

The genetic code. Notice that the DNA-letter T (thymine) has been replaced with the RNA-letter U (uracil).


Redundancy and Wobbling

With sixty-four codons and twenty amino acids, it is obvious that multiple codons code for the same amino acid. For example, AAT and AAC both refer to asparagine. This phenomenon, known as the redundancy of the genetic code, provides the cell with some protection against mutations. A mutation in a codon can lead to a different amino acid or stop character in the protein chain. Suppose the codon AAA (which codes for lysine) mutates into TAA (a stop codon). This mutation puts a stop codon in the wrong place in the protein and the production of that protein is stopped prematurely with possible negative consequences for the cell. A detailed look at the genetic code shows that many mutations, however, have no harmful effect. Take the amino acid alanine, which is encoded by the codons GCT, GCC, GCA and GCG. A mutation at the third position of these codons, for example from GCT to GCC, does not lead to a change in amino acid, as both GCT and GCC refer to alanine. After this mutation, the cell still produces the same protein.

Each organism has a certain number of tRNAs per codon available. For example, humans have 44 tRNAs for lysine: 24 for the codon AAG and 20 for the codon AAA. Certain tRNAs are also missing in the human genome. You will not encounter any tRNAs for GGT (glycine), CGC (arginine) or CAT (histidine). Fortunately, there are other tRNAs that provide these amino acids. The absence of certain isoacceptors is explained by wobble base pairing, in which the third anticodon position can deviate from the standard Watson-Crick base pairing, allowing for the translation of multiple synonymous codons by a single tRNA. In addition, modifications at certain positions in the anticodon loop can improve translational efficiency. For example, in the G34 anticodon sparing strategy, an enzyme converts adenine-34 to inosine-34 in specific isoacceptors. This conversion enables position 34 to wobble with adenine, cytosine and uridine. One tRNA molecule can thus be used for multiple codons in the mRNA.

The third position in the anticodon can wobble, allowing it to bind with both C and U on the mRNA molecule. Hence, multiple codons can be translated by a single tRNA.


Genome Size Reduction

Now that we have refreshed our knowledge about the genetic code, we can finally dive in to the results of the paper, which appeared in Genome Biology and Evolution. Comparing the total number of tRNA genes between avian genomes and other vertebrates revealed a striking pattern. On average, birds have about 169 tRNA genes which is significantly less than reptiles (466), amphibians (1229), mammals (579) and fish (813). This reduction could be a by-product of an evolutionary trend towards smaller genomes in birds through deletions of non-coding DNA. Interestingly, the tRNA gene repertoire in birds still contains all necessary tRNA genes that code for all twenty amino acids. Moreover, when we investigated the expression of tRNA genes in chicken (Gallus gallus) and zebra finch (Taeniopygia guttata), we found that all twenty amino acids were represented by at least one tRNA gene. Hence, the reduction in tRNA gene number and complexity in birds occurred within the functional constraints on efficient protein translation mechanisms.

An overview of the total number of tRNA genes in the genomes of birds (brown), reptiles (green), mammals (orange), amphibians (yellow), fish (blue) and yeast (black). From: Ottenburghs et al. (2021) Genome Biology and Evolution.


Transposable Elements

At the very start of the project, we noticed that some bird species had a overrepresentation of certain tRNA genes when we did not apply a quality filter. Why would the Dalmatian pelican (Pelecanus crispus) need almost 600 tRNA genes for isoleucine? And what does the bar-tailed trogon (Apaloderma vittatum) do with 2750 valine tRNA genes? Close inspection of these tRNA genes uncovered the presence of transposable elements: SINEs (short interspersed elements) to be precise. These selfish and highly active genetic elements incorporate themselves into genomes by a copy-paste mechanism, continuously giving rise to new genomic loci. If a tRNA gene is associated with such a transposable element, it can quickly increase in frequency. Our detailed analyses of these SINEs pointed to several known elements, such as TguSINE1 in Eupasseres (i.e. all passerines except the New Zealand wrens) and ManaSINE1 in manakins. But we also discovered some new SINEs, including PeleSINE1 in the Dalmatian pelican and ApalSINE1 in bar-tailed trogon.

And now for my personal favorite fact in our paper: the evolutionary dynamics of transposable elements in the golden-collared manakin (Manacus vitellinus) genome. This small songbird houses two SINEs that have been active at different times during its evolution: TguSINE1 was jumping around about 30 million years ago, while the activity of ManaSINE1 is more recent (about 5 million years ago). When these transposable elements become inactivated by the cell, they get “stuck” in a genomic location and start accumulating mutations. Because TguSINE1 was active millions of years before ManaSINE1, we expected that copies of this transposable element have accumulated more mutations.

We could test this prediction by using the Cove score which is calculated by the tRNAscan-SE progam. This score is based on the ability of a given sequence to form tRNA stem-loop structures and the presence of particular promoter and terminator sequences. Active tRNA genes will have high Cove scores, whereas inactive tRNA genes might be decaying into pseudogenes, leading to lower Cove scores. So, our prediction was straightforward: TguSINEs should have lower Cove scores compared to ManaSINEs. And that is exactly what we found (see figure below)! Isn’t it great when you find support for a hypothesis?

The evolution of transposable elements in the golden-collared manakin genome. Based on past activity patterns, we expected that TguSINEs would have lower quality scores compared to ManaSINEs. And that is exactly what we see. From: Ottenburghs et al. (2021) Genome Biology and Evolution.



Based on the findings of our work (and there is much more that I did not cover in this blog post), we formulated a model for the coevolution of tRNA genes and transposable elements. Some parts of this model are strongly supported by our results, while others still need to be investigated further.

The model consists of three phases. First, a TE recruits a copy of a tRNA gene for its own mobilization and increases its copy number in the genome. Second, the TE is silenced by epigenetic control mechanisms. Third, some TE-associated tRNA genes decay into pseudogenes, while others remain transcriptionally active and become coopted for their original tRNA function.

The last phase in the model – transposable elements that become active tRNA genes – is difficult to prove because the activity of these genes can be due to functioning as an actual tRNA gene or simply as an active TE. In zebra finch, we noticed that the correlation between codon usage in proteins and the available tRNA genes improved if we included transposable elements. This suggests that the activity of transposable elements can help shape the tRNA gene repertoire of an individual and potentially improve the efficiency of protein translation.

The correlation between codon usage and tRNA genes in the zebra finch genome improved if we included transposable elements (notice how rho increases and the p-value decreases). From: Ottenburghs et al. (2021) Genome Biology and Evolution.


An Extra Acknowledgement

I would like to end this long blog post with a personal note. The story behind this paper already starts in January 2016 when I attended the Plant and Animal Genomics (PAG) conference in San Diego. I was invited to give a talk at the “Avian Genomics” workshop (organized by Robert Kraus) where I met another invited speaker: Alexander Suh. Fast-forward to the spring of 2017: I was getting ready to move to Uppsala to start a postdoc, studying the genomics of hybridization in geese. I had already signed the contract and secured an apartment when my postdoc supervisor informed me that the sequencing of the samples was delayed. He wanted me to start a few months later so that I could work on the data during my entire postdoc. I tried to convince him that I could work on other projects while I waited for the goose data, but he would not give in. To fill the unexpected gap in my schedule, I contacted several people that might need help with a small project. Alex replied quickly and told me about a potential collaboration with Claudia Kutter in Stockholm. We discussed the project over Skype and a few weeks later I was on a plane to Sweden. I thoroughly enjoyed my six months in Claudia’s group and I am happy that we managed to turn my work into a nice paper. But more importantly, I made countless new friends during my Swedish adventures.

All invited speakers at the Avian Genomics workshop in San Diego where I (third from the left) met Alexander Suh (second from the left). The workshop was organized by Robert Kraus (right).



Ottenburghs, J., Geng, K., Suh, A. & Kutter C. (2021) Genome size reduction and transposon activity impact tRNA gene diversity while ensuring translational stability in birds. Genome Biology and Evolution. Early Online

Featured image © Claudia Kutter.

Unusually low genetic diversity in the Red-billed Tropicbird

“This,” said I at length, to the old man—“this can be nothing else than the great whirlpool of the Maelström.”

Edgar Allen Poe (Descent into the Maelstrom)


One of the key concepts in conservation biology is the extinction vortex, a model that shows how small populations get sucked in a maelstrom of genetic and demographic misery that culminates in their extinction. The reasoning behind is model is straightforward: small populations are more vulnerable to genetic drift and inbreeding, leading to a loss of genetic diversity. This genetic decline might prevent organisms from adapting to rapidly changing environments which translates into lower survival and reproduction rates. The result is an even smaller population that is again more vulnerable to the diversity-reducing forces of genetic drift and inbreeding. This negative cycle continues until the population disappears. An extinction event. A recent study in the Journal of Field Ornithology examined whether the Red-billed Tropicbird (Phaethon aethereus) should worry about descending into this treacherous vortex.

A graphical representation of the extinction vortex. © Pearson Education.


Low Genetic Diversity

At first glance, the Red-billed Tropicbird seems to be doing fine. This seabird species is considered “Least Concern” by the IUCN, although populations are declining due to competition with invasive species and habitat degradation. On local levels, however, Red-billed Tropicbirds are listed as threatened. In Mexico, for example, there are only 14 confirmed and six potential breeding colonies that vary in size from two to 1600 pairs. Absolute numbers only tell you so much, what about the genetic diversity of these colonies?

José Alfredo Castillo‐Guerrero and his colleagues sequenced one mitochondrial gene and 10 microsatellites from Red-billed Tropicbirds in the Mexican Pacific. The genetic data revealed surprisingly low levels of genetic diversity. The researchers found that 85 individuals all carried the same mitochondrial variant. For comparison, similar studies on other seabirds reported 47 variants for 55 Sooty Terns (Onichoprion fuscata) and 106 variants in 292 Masked Boobies (Sula dactylatra). The lack of genetic diversity in the mitochondrial DNA of Red-billed Tropicbirds was also reflected in the microsatellites: 7 out of ten markers showed no variation.

Genetic diversity in 3 microsatellites (P3A4, P4G1 and P3C1) for 8 Red-billed Tropicbird colonies in Mexico. From: Castillo‐Guerrero et al. (2020) Journal of Field Ornithology


Should we worry?

The extremely low genetic diversity suggests that Mexican Red-billed Tropicbirds have been sucked into the extinction vortex and might be more vulnerable than we think. But is that really the case? From a theoretical point of view, the extinction vortex makes sense: smaller populations continue to lose genetic diversity which leads to even smaller populations that continue to lose genetic diversity, and so on. But several genomic studies have reported species with extremely low genetic diversity that seem to be doing just fine. For example, reconstructing the historical demography of the vaquita porpoise (Phocoena sinus) indicated an effective population size of less than 5000 for over 200,000 years. One potential benefit of small population sizes is genetic purging. In this process, deleterious variants appear more often due to inbreeding and get expelled from the population because individuals carrying these variants fail to survive or reproduce. This probably allowed the vaquita porpoise to maintain a healthy level of genetic diversity.

Another aspect to consider is the distribution of genetic diversity across the genome. There might be particular genomic regions with high levels of genetic diversity that can provide the raw material for rapid adaptation to changing conditions. Just because 10 microsatellites are not very diverse does not necessarily mean that the entire genome is deprived of useful genetic variants. It is therefore important to carefully quantify genetic variation across the genome and understand the functional contents of regions of high and low genetic diversity.

The extinction vortex is certainly a useful concept, but we should be careful not to follow it blindly. It is important to take into account other potentially positive processes, such as genetic purging. This does, however, not mean that we should not protect the Red-billed Tropicbirds in Mexico. Their low genetic diversity does set some alarm bells ringing and we need to take proper conservation actions.



Castillo‐Guerrero, J. A., Piña‐Ortiz, A., Enríquez‐Paredes, L., van der Heiden, A. M., Hernández‐Vázquez, S., Saavedra‐Sotelo, N. C., & Fernández, G. (2020). Low genetic structure and diversity of Red‐billed Tropicbirds in the Mexican Pacific. Journal of Field Ornithology91(2), 142-155.

Featured image: Red-billed Tropicbird © Dominic Sherony | Wikimedia Commons

The magic of Fairywren hybrids

Chance always looks like fate in the taillights.”

– Colleen Wing (Iron Fist)

Working as a scientist trains you to wary about coincidences. Just because two events occur in quick succession does not mean they are related. Think of the common warning that correlation does necessarily imply causation (you check these spurious correlations). However, people tend to focus on the hits and ignore the misses. Remember that time you thought about someone and a few moments later they texted you. That cannot be a coincidence! But what about all the times you thought about that person, but they did not text you? Or when someone that is not on your mind sends you a message?

I found myself in a similar situation a few days ago. I was finalizing the internship of a student, who studied the behavior of Superb Fairywrens (Malurus cyaneus) in Australia,  when I received an e-mail about hybrid Fairywrens. In the e-mail, Joe Welklin – who runs a citizen science project on Fairywrens with Allison Johnson – turned my attention to two papers on putative hybrid Fairywrens that were not included in the Avian Hybrids Project. This nice coincidence provides the perfect opportunity to have a look at these cute passerines.

A Superb Fairywren © J.J. Harrison | Wikimedia Commons


Superb or Variegated?

The first possible hybrid was seen in south-east Queensland in 1980. Neil McKilligan observed a male that looked like a cross between a Red-backed Fairywren (M. melanocephalus) and a Superb Fairy-wren. Other birdwatchers managed to observe the bird as well and provide a detailed description of its plumage. A paper in the ornithological journal Sunbird contains the following account (unfortunately there are no pictures):

The bird’s plumage was bright and boldly patterned. It can be most easily visualised if one imagines a bird with the head of a Superb Fairy-wren and the body of a Red-backed Fairy-wren, except that the apparent hybrid had two shoulder patches of orange-gold.

It was obvious that one parent was a Red-backed Fairywren, but the identity of the second species was unclear: either a Superb Fairywren or a Variegated Fairywren (M. lamberti). A point by point comparison of several plumage traits could not solve the mystery, because “each species had five points of resemblance with the hybrid out of the fourteen body parts compared.” In the end, the birdwatchers turned to the distribution of the species. There were no records of Variegated Fairywren in the area, so the most likely second species in this cross was the Superb Fairywren.

A Red-backed Fairywren © Nevil Lazarus | Wikimedia Commons


“White” Wings

The second putative Fairywren hybrid was reported in the South Australian Ornithologist. Peter Haines discovered the peculiar bird at the Hart Lagoon, a lake northwest of Waikerie. The colors and markings pointed to a Splendid Fairywren, but the shoulder patches were atypical. Was this an individual with aberrant plumage or a hybrid? A consultation round with several ornithologists led to the conclusion that it was probably a cross between a White- winged Fairywren (M. leucopterus) and a Superb Fairywren. The plumage patterns were clearly a combination of both species.

The appearance of the head, including the face, approximating that of the Superb Fairywren and the body (including throat) and wings being like those of the White-winged Fairywren.

Another possible candidate for the cross – the black-backed subspecies of the Splendid Fairywren – was ruled out because it does not occur in the region around the lake.

A putative hybrid between Superb Fairywren and White-winged Fairywren. © Peter Haines | South Australian Ornithologist.



These two examples nicely illustrate how to check whether you are dealing with a hybrid. First, you compare the plumage patterns with other species to narrow down the number of possible parental species. Next, you check which of these species are present in the area. This approach mostly leads to a preliminary conclusion. Genetic analyses can provide the decisive evidence. In one cases described above, one of the parental species turned out to be a Superb Fairywren. Exactly the species that my student was working on. What a coincidence…



Haines, P. (2014). Hybrid Fairywren at Hart Lagoon, River Murray, South Australia. South Australian Ornithologist39, 2..

Wilson, M. (1983). Apparent Hybridisation between two species of Fairy-wren. Sunbird, 13(2): 38-39.


These papers have been added to the Maluridae page.