A duck is a duck is a duck, or is it? – Some notes on how to age Mallards in autumn.

Female head

2cy+ female, October. Adult females often show distinct blackish spots and a bright yellow-orange colour of the bill. [90A86379]

There are a lot of ducks on this blog – too many for some readers, perhaps – but it is not that surprising given that Mallards are our main model system for exploring disease ecology questions. Given their abundance, importance as game species, relationship with domestic ducks, synanthropic (yes, google that) behaviors, and propensity to carry interesting viruses and bacteria, it is not strange that ducks have rendered considerable research interest here and elsewhere. Ducks are also very beautiful animals, which helps.

You may think that a duck is a duck is a duck. But really this is not true; there is considerable individual variation in all measured traits in Mallards. The size differs, the plumage varies, as do migration patterns and immunocompetence, and so forth. As scientists, the variation is often what we are most interested in. The topic of today’s post is variation in plumage and the uncertainties of correctly ageing Mallards in the hand.

During our long-term studies of Mallards at Ottenby Bird Observatory in Sweden we have built up a large database of captures and recaptures of birds, which has allowed us to identify birds with known ages. For examples, if a bird was ringed in 2012 as juvenile and recaptured in 2016 we can be confident that this bird is adult at the second capture. Recently we published a study investigating different proposed plumage criteria for ageing Mallards by careful assessment of photos gathered over several years.

Generally, in birds, there is a difference between juvenile feathers (i.e. those attained directly after hatching) and feathers of older generations. In some bird species, this may include color differences, or special markings – such as spots or vermiculation; while in others differences are subtler, as in shape or wear. The key to age determination is the knowledge of in which sequence feathers are replaced (generally termed moult), and when in the year it takes place. In many passerines, birds have one complete moult of flight feathers per year and one or two partial moults of body feathers. Thus, knowing when, where and how birds moult you can search for the presence or absence of juvenile feathers. In non-passerines it becomes a bit messier, for instance with raptors where it may take several years to complete the moult of flight feathers. You could also look at other characters, such as the coloration of soft parts (bill, orbital ring, feet) and eye color, but generally those are less well known.

And what about Mallards? Let’s cite the paper (slightly edited):

“At the age of 2–4 months, juvenile mallards perform a partial moult of some feathers on the head, neck, mantle, scapulars, breast, and flanks in late summer (mainly July–September, correlated to hatching date). Both young and adults undergo pre-breeding moult from August–December, but the process may be prolonged during winter. This moult includes most body feathers, scapulars, tertial coverts, tertials, and tail, but very few lesser, middle, and greater coverts, and no primaries and secondaries. The retained feather groups allow determination of juveniles until replaced during the next year. Young females also retain at least some juvenile tertials and tertial coverts, whereas most males have moulted all tertials by late November. Males are thought to perform more extensive tertial moult due to sexual selection, and perhaps is sexual selection also responsible for the “extra” moult of mainly head and neck feathers noted in males in February–March.

In January–May, females perform a moult (of similar extent as the preceeding one) to acquire an even more cryptic plumage during nesting, brood-rearing, and moult of flight feathers, while males moult into a female-like eclipse plumage in May–July. Both sexes are flightless for about one month when all remiges (primaries and secondaries) are lost simultaneously during the summer (mainly late June–August), latest in successfully breeding females.”

For you non-birders, this may sound awfully complicated, but it is actually not that hard once you know your way around the anatomy of a bird and become familiar with the lingo of ornithology. The take-home message is that during autumn, birds will have a plumage comprised of feathers of different ages and knowing what you look for you should theoretically be able to correctly separate juvenile birds from adult birds.

1 cy Male tail

1cy male, November. Easily recognized as a young bird due to remaining juvenile RR being narrower (and shorter), worn, frayed, and with brown and buff colours. The outermost pair of feathers is often the last to be moulted, but sometimes the central pair is still retained when all the others are post-juvenile.

1 cy male tertials

1cy male, November. This bird has moulted T2 to T4, but still has juvenile T1. The four outer TC are worn and dull brownish, but note that even juvenile two outermost TC occasionally show warm brown tips. [90A88713]

However, in practice this is hard – even for experienced duckologists (see for example the figure just above). Using the photographs, we tested the validity of different criteria, either one by one, or combined, by presenting them to a panel of (mostly) volunteers experienced in age and sex determination of birds. Evaluating their scores compared to the known ages of the birds we found that no single criterion was conclusive (range 48-89% correct), but that when given access to photographs of all plumage tracts, 91 and 95% of male and female Mallards were correctly assigned, respectively. The latter setup is more similar to what is experienced in the field, but nevertheless we urge caution with ageing, especially in late autumn where many juvenile birds may have moulted tail and tertials in a pre-breeding moult and hence are very adult-like in appearance.

I am happy to send a pdf of the paper to those interested, just google my name at Linnaeus University. You could also visit the online Ringers’ DigiGuide at Ottenby Bird Observatory where we have provided quality photos and texts to use for the purpose of ageing and sexing of Mallards, as well as for other species.

The reference for the article is:

Andersson, S., Bengtsson, D., Hellström, M. & Waldenström, J. 2016. Age and sex determination of Mallards Anas platyrhynchos in autumn. Ornis Svecica 26: 61-81.

What lies ahead post-Brexit?

 

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A fridge magnet my daughter uses to tell that ‘she isn’t here’. The question is what fridge magnet we should use for science post-Brexit.

As all of you know, UK voted for Brexit.

In the local village sauna (yes, we have one of those) the reactions ranged from Brexit being stupidity in action, to quotes such as this was EU’s fault for not being on par with the people and that this could serve as a bloody needed wakeup call for the union. I sat mainly silent, stunned by the absoluteness of the decision. Because it is such a major decision, and a decision that have ramifications on so many levels for so many people.

As a scientist, I wonder what this will mean for UK and EU science? Truth is, no one knows. (And the elderly men in my sauna had no answer either). What we do know is that over the years, science and education have become more and more interconnected in the EU as a whole. And that’s a damn good thing. During my career it has become easier to study and conduct research outside Sweden, and for students from other countries to come to Sweden. Actually, after finishing a PhD, one of the most common ways of continuing in science is to apply for EU-funded postdocs (foremost via the Marie Skłodowska-Curie grant programs). I have many friends that have done that journey, and as PI I have had students applying for this funding to come to my lab. Also at the next level, where an aspiring scientist wants to develop his own research group, the EU provides means to do so via the ERC starting grants. Will these opportunities remain for young UK researchers? And what will happen with the opportunities for postdocs from the rest of the EU to do their work in the UK? The UK has been a magnet for talented Europeans for a long time, and it would be a terrible loss if that door, if not closed totally, would be harder to get through. Moreover, what will happen with European-wide calls, such as Horizon 2020 grants? At the moment I am participating on a grant proposal at the second stage where 2 out of the 6 partners are from the UK – will it be considered for funding anyway?

The interconnected science world is manifested also locally, even in a small university such as the one I work at. For instance, I have participated in EU-funded research, acted as an expert in EFSA (European Food Safety Authority) opinions, have had UK colleagues on shared grants, hosted postdocs with roots or training in the UK, and once I was close to actually move to the UK myself. I have met so many talented UK researchers at so many different levels. It is a shame if the ties connecting research between UK and EU will be weakened. It would be a great loss for EU and devastating for the upcoming research generation in the UK if they cannot participate at the same level as other European researchers.

You may say that is doom and gloom talk, that in fact not much will change, that either EU or the UK will make sure that funding and research opportunities will continue more or less as they are now. I hope you are right, but fear that you are wrong. For sure, there will be a backlash if article 50 is invoked, the question is how big and how long-lasting it will be. Because once you’re out, you cannot really continue business as usual. Simply put, why would EU-funds be used to support UK research and infrastructure in the future if not the UK is paying their share, or if EU-researchers cannot move freely to the UK?

It is still early on in the Brexit process, and we’ll have to wait and see what will come out of this mess. If my crowd in the sauna come up with a solution, I will let you know.

Seabirds and flu, a review

A small murre colony on Cabot Island, Canada.

[This post is by Michelle Wille, postdoctoral researcher at Uppsala University]

For those who have visited a seabird colony, you would know that it is a loud and crowded place, with large swaths of the colony covered in guano. It literally stinks of bird poo. If you were to imagine a good host for a virus that is transmitted by the fecal oral route, one could imagine that these conditions would be excellent for transmission. A virus, such as the influenza A virus (IAV).

 

This virus is one of the most important and well-studied avian viruses, especially in its reservoir hosts, the dabbling ducks. However, for seabirds – the majestic creatures that roam the oceans – no real synthesis has been published despite close to 50 years of surveillance. In fact, when I started working on IAV in seabirds, we knew very little about the presence and prevalence of influenza in this group of birds. What we did know was that seabirds were being sampled for influenza – in fact, most bird groups were being sampled for IAV following the highly pathogenic H5N1 outbreaks after 2005 – but we didn’t actually know how seabirds fit into the ecology of influenza. Are they infected? Are some seabirds more important than others? Do they follow similar patterns to ducks or gulls? Are their viruses unique, or more similar to duck or gulls?

 

Antarcric Tern

Antarctic tern

We set out to collate the existing knowledge on IAV in seabirds – a diverse collection of species and are best defined through their shared propensity to spend portions of their lives at sea – and pulled together as much surveillance data as possible from publications and influenza databases to try to evaluate sampling effort in seabirds, and which species play a role in IAV ecology. This review was just published in the journal Avian Diseases. It turns out, scientists have sampled a large number of seabirds over the last 50 years: 41,828 samples from 98 species, spanning 14 avian families in 6 orders. This may seem like a lot of samples, but if broken down it equals only 8.5 samples per species per year. To put it in perspective, from our sampling site in Sweden, 22,229 samples were collected from Mallards between 2002-2009, and it is samples sizes like these that allow us to make stronger inferences on IAV ecology.

 

While this illustrates the lack of effort overall, some seabirds have received more effort and attention. Terns as a group are heavily sampled, although sporadically rather than systematically. Terns are interesting as the first confirmed outbreak of highly pathogenic influenza in wild birds occurred in Common Terns (Sterna hirundo) in South Africa back in 1961. Despite very few isolations of viruses, serology suggests circulation of IAV in terns and noddies and a diversity of virus subtypes – most recently highlighted in the Indian Ocean system. Most interesting, perhaps is the compelling evidence suggesting that Murres/Guillemots (Uria sp.) are hosts for IAV. Research to investigate IAV in murres dates back to the 1970s, and interest in these birds has been renewed with increased sampling effort in the past 10 years. These birds are piscivorous, limited to the northern Holoarctic where they breed predominantly on islands, often on steep cliffs. Within all the seabird groups, the greatest number and diversity of viruses come from murres, with viruses isolated across their range – Russia, Sweden, Greenland, Newfoundland (Canada), Nunavut (Canada), Alaska (USA), and Oregon (USA). Unfortunately there is rather limited serological information in Common and Thick-billed Murre, which would provide a more long-term assessment of influenza dynamics.

 

 

COMU

A few other species/groups have large enough sample sizes to estimate IAV prevalence with confidence, but serology, despite small sample sizes, indicates IAV presence in most seabird species tested. However, more focused work is required to better assess these species as hosts. Regardless, if you are interested in the IAV status of the seabirds you work on – sampling effort and IAV results are presented for all 98 species.

 

concept

What is the role of seabirds in the epidemiology of low-pathogenic avian influenza?

What was a surprise for us, as we were completing this review, was how little we could say about the role of seabirds in the ecology of seabirds due to limitations in sampling. There is clearly a space to fill for an aspiring IAV researcher. If you want to sample for IAV and be able to draw some conclusions – here are some things to think about:

 

  1. Influenza A in birds is seasonal. Some months the prevalence is high (up to 30%) and some months it is low (>0.00001%). While seabirds are logistically hard to access, temporal and repeated sampling is key.

 

  1. Within an individual, the period of shedding live virus is very short. While longer periods have been detected (up to 14 days), usually birds shed viruses for less than 7 days. This highlights the importance of serology, or assessing the antibody prevalence in a population. This allows us to ascertain whether the population has been infected by IAV in the past, and therefore, whether it is a population to target (if positive).

 

  1. Seabird colonies may have many species, and it is tempting to take a few samples from each species present. Low sample size however limits the detection probability. For example, if prevalence of IAV is about 1% in the population, you need to take well over 100 samples to have a 95% probability of detecting the virus. Putative prevalence of IAV in seabirds is in this 1% range.

 

  1. Maintaining “cold chain” is key. Seabird colonies are logistically hard to sample, and dragging a -80C freezer or vapour shipper may just not seem to be worth the effort. But, RNA viruses degrade rather rapidly, and swaths of negative samples may be false negatives due to poor sampling handling. While it is speculation, perhaps the reason that we are starting to be more successful at isolating influenza from Antarctic Penguins is an improvement in cold chain (who would have through it would be difficult to keep samples at a constant temperature of -80C in Antarctic!).

 

I feel privileged to be writing this piece after recently spending a week working in a Murre colony in Sweden. Seabird colonies really are the best places to be – serene beauty on the steep, the smell of guano-ladened cliffs on (remote) islands, with the flutter of murre wings and peeping of recently hatched murre chicks.

Link to the article:

Andrew S. Lang, A.S., Lebarbenchon, C., Ramey, A.M., Robertson, G.J., Waldenström, J.& Wille, M. 2016. Assessing the Role of Seabirds in the Ecology of Influenza A Viruses. Avian Diseases 60(1s):378-386.

 

Penguins

Adelie and Gentoo penguins doing their thing.

Influenza A virus epidemiology – from individual disease histories to disease dynamics

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Mallards on the wing (Photo by Flickr user Bengt Nyman used under a CC-BY 2.0 license)

Wildlife disease studies are challenging. That’s a fact. If you want an easy science life you should choose another path with more instant results. However, challenging is also the opposite of boring, and the rewards of getting your results are even more exhilarating when lots of toil, sweat and tears have been invested. As readers of this blog are aware, wildlife disease studies are what we do, and I have repeatedly written about our ongoing work on influenza A virus ecology and epidemiology in wild migratory Mallards. This week another study from our study site was published, entitled Capturing individual-level parameters of influenza A virus dynamics in wild ducks using multistate models, which can be found on early view in the Journal of Applied Ecology.

The challenges of studying wildlife disease dynamics are that you want to capture a dynamic process influenced both by the host and the pathogen, which in turn is compounded by variation in the environment – both biotic factors, such as food abundance and the occurrence of other potential hosts, and abiotic factors, such as weather and climate. Disentangling these interconnected effects is a little like making a cube out of mercury. In most wildlife disease studies the available data is at the population level, usually in the form of prevalence rates at specific time points. This type of data is ‘fairly easy’ to collect – you head out into the field, sample all animals you can lay your hands on and then use this snapshot in time as a proxy for the true disease dynamic in your system. The more times you are out collecting data, the better your model becomes. However, disease is driven by factors operating at the level of individuals, such as infection risk and recovery rate, and that type of data can only be acquired by repeated sampling of individuals across a suitable timescale. This is rarely achieved because of logistical, practical and monetary reasons.

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Mallards on the wing (Photo by Flickr user Bengt Nyman used under a CC-BY 2.0 license)

We, however, sit on a huge collection of Mallard and flu data gathered at the same study site with similar methods over a period of close to 15 years. Our latest paper, headed by Alexis Avril and with collaboration with colleagues in France, utilizes this dataset to develop individual-based influenza A virus epidemiological models. This proved to a monumental task that stretched over several years and burned the processors of a good number of computers. Part of the difficulty can be attributed to the data itself – capture and disease histories for 3500 individuals collected over 7 seasons, where at each capture occasion axillary data on bird age, sex, condition, infection status and weather were included. But also the patchy nature of recapture probability and the short duration of most influenza virus infections contributed significantly to extensive data crunching.

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The conceptual framework in the multistate CMR model.

The method we used was multistate capture-mark-recapture models, which are extensions of models originally developed to investigate mortality rates from census data, but where one can include the infection state – i.e. infected or not with influenza virus – as a factor in the analyses. Interested readers should head over and read the publication, as I will spear the rest of you any hardcore statistics and model lingo. Parts of the abstract serves as a good summary:

 For most years, prevalence and risk of influenza A virus (IAV) infection peaked at a single time during the autumn migration season, but the timing, shape and intensity of the infection curve showed strong annual heterogeneity. In contrast, the seasonal pattern of recovery rate only varied in intensity across years. Adults and juveniles displayed similar seasonal patterns of infection and recovery each year. However, compared to adults, juveniles experienced twice the risk of becoming infected, whereas recovery rates were similar across age categories. Finally, we did not find evidence that infection influenced the timing of emigration from the stopover site.

Our study provides robust empirical estimates of epidemiological parameters for predicting IAV dynamics. However, the strong annual variation in infection curves makes forecasting difficult. Prevalence data can provide reliable surveillance indicators as long as they catch the variation in infection risk. However, individual-based monitoring of infection is required to verify this assumption in areas where surveillance occurs. In this context, monitoring of captive sentinel birds kept in close contact with wild birds is useful. The fact that infection does not impact the timing of migration underpins the potential for mallards to spread viruses rapidly over large geographical scales.

Our findings corroborate much of the earlier works done on IAV in birds from population level data or from infection experiments, but with higher robustness of the conclusions. Importantly, we provide estimates of the most crucial infection parameters and show how they vary in relation to age in different seasons and years. And from a model point of view, we show that MS-CMRs are a potent method for disease dynamic inferences. We hope this paper will be read and cited by people in the IAV field and in general disease dynamic research, and that it will be useful for stakeholders interested in the contribution of wild birds in the epidemiology of IAV in poultry.

Link to the paper:

Avril, A., Grosbois, V., Latorre-Margalef, N., Gaidet, N., Tolf, C., Olsen, B. & Waldenström, J. 2016. Capturing individual-level parameters of influenza A virus dynamics in wild ducks using multistate models. Journal of Applied Ecology, online early.

On the cover

In the Swedish academic system a PhD thesis is an actual printed book. Yes, a proper book-looking book. A kind of book you can shove in the hands of your family and say ‘here it is, the fruits of my labor, the sum of all my forsaken years, MY THESIS!’

The editions are small, usually between 100 and 200 copies, of which 30 go to specified libraries, kept safe in the hallways of science. One is nailed to an oak tree three weeks before the thesis defense, thereby symbolically presented to the public (and continuing a tradition dating back to Martin Luther’s nailed thesis to the church port of Wittenberg in 1517). Although it probably isn’t really necessary to print them on paper in this age of computers, it is a tradition worth honoring. More than anything it represents a closure of sorts, and a mark of something new.

I really like that feeling when the book gets back from the printers and the student finally sees the end of the wonderful but torturous path that is a PhD. The making of the book is sometimes also an act of procrastination, where the student can spend an inordinate time adjusting the colors on the cover, rather than finalizing that final chapter.

Below are the theses produced in our research group in Kalmar the last years. If you want to read them there are links to the online publications too.

Daniel Bengtsson

• Daniel Bengtsson, Linnaeus University, Stopover ecology of mallards – where, when and how to do what? 11 March 11 2015, ISBN 978-91-88357-00-7.

• Michelle Wille, Linnaeus University, Viruses on the wing: evolution and dynamics of influenza A virus in the Mallard reservoir, 8 May 2015. ISBN 978-91-87925-56-6.

Johan Stedt

• Johan Stedt, Linnaeus University, Wild birds as carriers of antibiotic resistant E. coli and Extended-Spectrum Beta-Lactamases, 13 June 2014. ISBN: 978-91-87427-93-0.

Petra Griekspoor Berglund

• Petra Griekspoor, Linnaeus University, Exploring the epidemiology and population structure of Campylobacter jejuni in humans, broilers and wild birds, 28 May 2013. ISBN 978-91-87427-83-1.

Neus Latorre-Maraglef

• Neus Latorre-Margalef, Linnaeus University, Ecology and epidemiology of influenza A virus in Mallards Anas platyrhynchos, 8 June 2012. ISBN 978-91-86983-61-1.

Jorge Hernandez

• Jorge Hernandez, Uppsala University, Human pathogens and antibiotic resistant bacteria in the Polar regions, 10 October 2014. ISBN 978-91-554-9016-4.

Jenny Olofssons avhandling

Jenny Olofsson, Uppsala University, Amoebae as hosts and vectors for spread of Campylobacter jejuni, 2015. ISBN: 978-91-554-9276-2.

Flu, ducks and the costs of being infected

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There was light snow this morning, but it has since melted away, leaving small puddles on the streets. Unfortunately, the sun seems to have lost today’s battle with the fog and the low clouds – it is, in essence, an ordinary wet, cold and gloomy February day. But if I peer out through the window, ignoring the construction works in the foreground, there is water on the horizon. And where there is water, there are ducks. And where there are ducks, there is flu. One cannot ask for more.

Over the years I have thought much about ducks and flu. (Some would say too much, but they don’t know what they miss). Although my research group has already produced four PhD theses on this topic, there is so much more that I would like to know. Some of it is  highly specialized knowledge, of interest for a limited set of like-minded scientists with  acquired duck disease tastes. Other things are quite basic, but hard to study, such as the question whether ducks infected with flu suffer from infection or not. That is a pretty important question also for a broader audience, as it has relevance for how well virus can spread with individuals in the environment; especially how ducks may spread virus long distances during migration. So, do they suffer from infections, or not?

Actually, there has been some controversy on this topic – partly stemming from different methods of quantifying disease effects. A field ecologist and a veterinarian have different scales in their toolboxes, one could say. In the latter case, disease signs are determined in  experimental infections in animal house facilities, where individuals can be followed over time. Such experiments in Mallards have not been associated with strong disease signs – as long as we consider the low-pathogenic avian influenza viruses that are naturally occurring in wild avian populations (highly pathogenic AI is a completely different story). Infected Mallards shed viruses, but are otherwise apparently healthy, or only display a very short increase in body temperature. But, the ecologist argues, the artificial environment with plenty of food, controlled temperature and absence of predators is not really mimicking the situation in the wild, where even small reductions in vigilance and movement capacity may end in the death from a raptor’s claw. Absence of overt disease is not equal to absence of ecological costs, the ecologist would conclude.

The field studies so far have been a mixed bag, ranging from large effects to negligible effects depending on study and the species considered. The largest effect was seen in a study of Bewick’s swans in the Netherlands, where infected birds had poorer condition and migrated slower than uninfected swans. Such large effects have not been seen in other species, and one can not conclusively rule out other underlying factors, as the swan study was based on a limited number of birds. When it comes to Mallards – the most glorious of all avian influenza reservoir species – previous population studies from our group have suggested infected birds to weigh on average less than uninfected birds at capture.

Averages and populations are all and well, but to get to a mechanistic understanding one is better off with experiment conducted on a set of individuals. However, a problem is that we can not infect birds and release them in the field; in fact, we are not allowed to do so – there is a reason infection experiments are conducted in biosafety labs, after all. What to do, then? Well, we approached this question via GPS and accelerometer loggers attached to two groups of birds caught during the ongoing surveillance at our study site: one group of 20 Mallards with natural avian influenza infection at the time of capture, and another group of 20 Mallards that were negative for influenza at the time of capture.

The benefit of these data loggers is that they record such a wealth of information. From the GPS fixes we can follow the birds in the landscape and quantify their movements at spatial and temporal scales; from the accelerometer we can get metrics that describe activity, defined as movements in the x, y, z-dimensions. We predicted that infection would significantly hamper movement, and that with time the difference between infected and uninfected birds would level off (see figure below); hence the analyses need to take time in to account, too.

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Theoretical predictions of the influence of infection on movement metrics. If infection affects spatial behaviour, infected (blue) and uninfected (red) birds should behave differently at the time of release. We postulate that, at this time, movement metrics for infected birds should be lower than for uninfected birds, which would be revealed as different intercepts of the regression of the movement metrics against time for uninfected (β0) and infected birds (β0+βInf). As infected birds recover with time, their movement metrics will approach and eventually meet the values for uninfected birds. This happens when the slope of the regression of the movement metrics against time for infected individuals (βT.aft.Rel*inf) reaches the slope for uninfected birds (βT.aft.Rel), which is expected to be null.

The full paper is freely accessible at Royal Society Open, and I hope readers with a more heavy interest in movement ecology download and read it. There is a lot of data crunching and statistics there that most of you are likely not that interested in – if you are, go read the original publication – but remember even easy questions may be hard to answer. Okay, with that said, what where the results?

Well. There were no effects of infection on the movement parameters measured, at all. Yes, there were differences among individuals, and between night and day, but infection status did not explain much of the variation in movement metrics. This means that under the natural situation in this study, conducted during stopover in autumn migration, infected ducks moved as much as uninfected ducks. This also means they likely are not impaired by infection during active migration, and could therefore carry LPAI viruses on the wing as they depart the stopover site.

Is this, then, the last nail in the ‘cost of infection’ coffin for low-pathogenic influenza in ducks? Probably not, because one could argue that non all viruses behave the same (in fact, there should be a variation for virulence), and that some viruses may have adapted to infect non-mallard-birds, and hence be spillover infections in Mallards (and then potentially be at less than optimal virulence). Moreover – and perhaps a stronger argument – there may be differences in outcome depending on whether it is a primary infection, or subsequent infection; where the first infection in a naïve bird could be believed to carry a larger cost. Or there may be effects seen only at certain environmental conditions.

All these ‘but, or, perhaps, mayhaps’ are classic scientist disclaimers… My personal belief, these days, is that also the ecological costs of infection are slim. But I am happy to be proven wrong – out you go now and study.

There is water at the horizon still. And questions aplenty.

 

Link to the article:

Bengtsson, D., Safi, K., Avril, A., Fiedler, W., Wikelski, M., Gunnarsson, G., Elmberg, J., Tolf, C., Olsen, B. & Waldenström, J. 2016. Does influenza A virus infection affect movement behaviour during stopover in its wild reservoir host? Royal Society Open Science 3: 150633.

 

Older ducks poop fewer viruses – a story of how to sell a story (and some science, too)

Flickr user ‘John K’ under a CC BY-NC-ND 2.0 license.

Flying Mallards – great shot by Flickr user ‘John K’ (distributed under CC BY-NC-ND 2.0 license).

Last Friday, we published a paper in Applied and Environmental Microbiology with the title ‘How does sampling methodology influence molecular detection and isolation success in influenza A virus field studies?’ The study is a thorough analysis of 26,586 samples collected for detection of influenza A viruses from Mallards over some 9-10 years. The aim was to tap from the knowledge base gained in our long-term studies and provide some advice on best field and lab practices for others that want to initiate similar surveillance schemes for this virus. Thus, this is an article with high relevance for a limited crowd of people in our field, but not one that will attract hordes of interested ecologists. But as a methods paper it will be widely cited and useful.

In the paper we show which type of sample methodology that gives the best results. Not surprisingly, molecular detection was more sensitive than isolation, and virus isolation success was proportional to the amount of RNA copies in the sample – e.g. the more virus the easier to grow them in eggs. Comparing the results from specific RRT-PCRs and from isolation it was clear that co-infections were very common in the investigated birds. The effect of sample type and detection methods warrants some caution for interpretation of results of surveillance data, which we discuss in the paper.

Publishing a paper is great, but ideally the work doesn’t end there. One can blog about it, like I often do here, or one can try to push for the results in conventional media. The latter is tricky, and not something we do for every paper. However, this time we had some time to spare, and drafted a press release and sent it merrily along to the university’s Communications Office. One would think that a methods paper is a hard sell, but no – it was picked up by roughly 40 Swedish newspapers (mainly in short electronic form). That is pretty amazing! The reason? A catchy headline, of course.

The press release lifted up a smaller part of the paper, namely that for a given Ct-value, the isolation success was lower in samples from adult birds than from juveniles. This could be interpreted as adult birds (having had exposure to virus in previous infections) being more adept in limiting infections, manifested as less shed functional/infectious virus per given Ct-value. This is an interesting result that has bearing on our view of the epidemiology of the virus in the wild reservoir – but it was a side issue, not the main focus of the article. Anyway, during a sampling trip to Ottenby, we came up with the headline ‘Older ducks poop fewer viruses’ (Äldre änder bajsar färre virus). And this, my friends, is a title that was catchy enough to carry through the noise.

Communicating your science is important for a bunch of reasons, plus it is a part of the job description of us academics. But it is quite hard, and rewards at times unpredictable. Over the years, our research on ‘what scary deadly bugs do‘ has received much media attention. This is partly because the topic as such is appealing, but more likely that we actually put an effort into it. And time with media is time well spent. Anyway, that was a story about how to sell a story. For the real story please read the original article:

Latorre-Margalef, N., Avril, A., Tolf, C., Olsen, B. & Waldenström, J. 2015. How does sampling methodology influence molecular detection and isolation success in influenza A virus field studies? Applied and Environmental Microbiology, ahead of print, doi: 10.1128/AEM.03283-15.