Antarctic video gallery
Ocean waves following sea ice loss trigger Antarctic ice shelf collapse
The deep sea dwellers of the Southern Ocean
What the krill microbiome can tell us about Southern Ocean ecosystems
What the krill microbiome can tell us about Southern Ocean ecosystems
Bruce: Thank you everybody for coming today! I’ll just do an introduction of today’s speaker while we wait for the last people to show up. Today’s speaker – the third speaker in the AAD seminar series – Laurence Clarke who is an ACE-CRC [Antarctic Climate and Ecosystem Cooperate Research Centre] postdoc and he is based here at the AAD in the Ecological Genetics group. He did a PhD – he finished it in 2008 – at the University of Woollongong; he was actually working on the reserves of Antarctic moss on climate change. After his PhD, he was a research fellow at the University of Adelaide on a couple of different projects working in terrestrial ecology and he also started to get more into genetics and ended up working at the Australian Centre for Ancient DNA. After that position, he applied for a research fellow position at the ACE-CRC and that was in 2015 so he’s been here since then. He’s done work on a whole pile of projects one about which you will hear today. He’s worked on biofilm in the Free Ocean Carbon Enrichment experiment – the FOCE experiment. He was looking at biofilm communities, he has looked at biodiversity of proteists on the K-Axis voyage and he went on the K-Axis trip a couple of years ago. He has also looked at biodiversity in fish stomachs, so looking at fish diet and recently published a paper on that. And if that’s not enough, he has also recently become a father and bravely agreed to give a talk in his sleep-deprived state… So I let Laurence go ahead.
Laurence: Thanks for that introduction, Bruce. My first slide is an introduction slide but I reckon Bruce has covered pretty much everything on here. The only one he missed was work that Bruce did more of than me so I can’t really blame him, and that was applying genetics to look at the samples from the Continuous Plankton Recorder. Other than that he pretty much covered it. What I am here today to talk to you about are some quite fresh results looking at krill-associated bacteria or the krill microbiome.
Today I’ll give you a bit of an introduction about microbiomes and why they are important. Then I shall give you a bit of rundown on how we do it. Then I’ll take you through three results. The first one is the bacteria that we found in the krill stomachs, then the bacteria that we found on the krill surface or the krill moults, and finally how these microbial communities or microbiomes influence nutrient cycling in the Southern Ocean.
So let’s take it away! Chances are that by now you’ve heard of the human microbiome. Basically it’s… we’re a little bit less human than we like to think. There are three times as many bacterial cells in our bodies than human cells for starters. Now these cells are very small so it’s a bit of an abstract thing to think about. But what drove this point home to me was that finding out that each one of our poos a third of it is food, a third of it is water and the other third is bacteria. So these cells are tiny and that is a lot of bacteria.
Our genome is made up of genes and best guesses are that we’ve got about 20,000 genes. Now in the human biome, we’ve got all these little environments on us - our mouth, our skin, our guts – and each of these have different bacterial communities and these communities are made up of many bacterial species. All these species have genomes of their own. So compared to the human genome, our microbiome is actually made up of 2 million or more genes. So 99% of our genes by numbers are bacterial genes. We are getting an increased understanding in the last 10 years of how important our microbiome actually is to us. It’s now being linked to everything from obesity to depression. The list is ever growing.
Now a quick introduction to everyone’s favourite crustacean, the Antarctic krill or Euphausia superba. Best guesses is there are around 380 million tonnes of krill in the Southern Ocean. It’s a massive population. They’ve got a circumpolar distribution – they are found all around Antarctica. Partially because of this huge population – when we look at the genes or genomes of krill, there is no genetic structure. What that means is if you take a krill from the West Antarctic Peninsula and a krill off Mawson station in East Antarctica, just by looking at their DNA you couldn’t tell that they are from those two different areas. As far as their genome is concerned, it looks like one big population. Now because there are huge numbers of krill, chances are there are huge numbers of krill-associated bacteria. If we do a back-of-the-napkin calculation, say that 0.1% of each krill is bacterial biomass that still gives you 380,000 tonnes of krill-associated bacteria in the Southern Ocean. So chances are that they are fairly important. This has pretty much been overlooked until now. I figured it’s about time to get in there and figure out what’s happening.
I am just going to give you a quick rundown on the different parts of krill that I’ll talk about today. The first one is their moults, also known as their carapaces. It’s kind of the equivalent of our skin. They shed that on average every 15 to 30 days in summer. It’s made of chiton; I’ll come back to that near the end. Just like us they also poo. The krill faeces are those tiny green threads in here, and – just like us – I suspect that they are full of bacteria from their gut. As far as their digestive tract goes, they’ve got two main parts. The first one is their stomach, this kind of half-moon shape… hopefully can you see what the stomach is. Behind the stomach, there is the digestive gland, much bigger and green from all the phytoplankton they’ve been eating.
How do you go about sampling a krill microbiome? This is where I love the krill group! They have a growth experiment that they’ve set up. So they make use of the fact that they [the krill] moult every 15 to 30 days, and by comparing the moults with the actual krill they can work out a growth rate. To do this, they jar up the krill; that means from each individual krill you can collect the moult and the faeces, but also the stomach and digestive gland and whatever else from that one individual.
Let’s go through step by step; how does one get a krill microbiome. First, you’re out on a ship, in this case the Aurora Australis on the Southern Ocean. You wait for the acoustics to show up a big blob that is a krill swarm. You put your net in and hopefully you come up with some krill. At the same time, I took a seawater sample and filtered that so that I could look at the bacteria in the seawater, and I could compare that with the bacteria that I found on the krill. Once you’ve got your krill trawl, you set up your krill IGR experiment. You jar up about 300 individual krill and pop them into a tank on the back of the Aurora Australis, and you wait for six to twelve of them to moult. That takes 24 to 48 h hours. Once they moult, you collect that moult and also the krill and then you bring it back to the Australia. You can dissect them to get the stomach and digestive gland and whatever else you’re after.
Once you’ve got your samples, you know want to extract the DNA and sequence it. What’s made all this microbiome research possible in the last ten years has been the invention of high-throughput DNA sequencing. Just as an indication of how far we have come, the draft human genome took about ten years to finish. It started in the 1990s and the draft was finished in 2000. A massive international collaboration! They were using machines that would sequence one piece of DNA at a time. Now high-throughput DNA sequencers sequence literally millions of pieces of DNA in parallel in a single run. You can put hundreds of samples on one run, you get tens of thousands of samples per sample. A high-throughput sequencer can now give you the equivalent of 48 human genomes in one run that takes about two days. It was a major leap forward there.
That’s where the headaches come in. The final step is the bioinformatics and the analysis. Just in this dataset that I talk to you about today, 14.8 million sequences and that is after getting rid of any low quality DNA sequences, errors and things like that. Within that let’s call it 15 million sequences there were 6000 unique sequences, and as far as bacteria are concerned, we call them Operational Taxonomic Units or OTUs, basically the equivalent of bacterial species. That’s our best way to tell them apart.
To start with I had 24 krill from four trawls on the K-Axis voyage. This plot – and there will be a few of them – basically shows firstly the seawater and the jar water, which is the jars they were in – is very distinct from the krill-associated bacteria, the krill microbiome. Just to walk you through this plot, points that are closer together have more similar bacterial communities. Hopefully you can see that sea water and the jar water at the very top of the plot are quite separate from our four different krill tissues, and hopefully you can also see that the four different krill tissues are also quite distinct. So the moults are quite distinct from all the digestive samples.
Getting on to the gut bacteria, the bulk of our microbiome resides in our guts. But the diversity in the krill gut was much lower than that in the sea water or on their moults. Sea water and moults have 4000 or more of these OTUs or species whereas the stomach and the digestive gland somewhere between 50 to a 100, so much, much lower.
This is another complex graph. What was cool was we could kind of see something that is highly likely to be a symbiont that is helping the krill to survive. Each of the vertical bars in this graph represents a different one of our samples, and the different colours represent different bacterial phyla. The light grey that dominates most of the samples across there is Proteobacteria, and the blue that you can see in the digestive samples is Actinobacteria. Though what is most interesting to me is that hot pink number at the top. That’s in a phylum called Tenericutes, but that phylum was made up of one bacterium called Candidatus hepatoplasma. This bacterium is interesting because in other crustaceans it’s been shown to basically give an improved fitness. The crustaceans that have this bacterium are better able to survive on low quality diet. So there is every chance that krill with this bacterium, well, basically this bacterium is helping the krill to absorb nutrients that otherwise wouldn’t be available. We can also see is that the distribution of this bacterium is fairly random. It wasn’t in krill from a particular trawl, it wasn’t just in adult krill or juveniles, wasn’t in males or females. It was quite stochastic as to whether any given krill had this bacterium or not. So there is a question of how did it end up here?
I am going to duck over to the humans for a moment as a possible explanation. Now that we are getting a better understanding of how important the human microbiome is, a key question is: can we restore a healthy gut microbiome in people that have microbiome related diseases. One way you can potentially do this is by faecal transplant and without going into the details, you basically want to get a sample from a healthy donor and use it re-seed the gut microbiome of your unhealthy recipient. This has been shown to have some pretty amazing success rates. C. difficile is a particularly nasty gut bacterium that often can’t be resolved with antibiotics. So people have this incredibly long-lasting debilitating reaction that is difficult to treat. Faecal transplants have had a 90% success rate in resolving C. difficile infections which is pretty amazing.
Now, marine snow could be the faecal transplant for krill. You may or may not know, marine snow is quite different from the pure white stuff that us terrestrial folks are used to. It’s actually made of a lot of detritus, dead cells but also plenty of faecal matter. Krill are fairly indiscriminant feeders; anything that is in the right size range is going down the hatch. So it might be that the krill is able to ingest this Candidatus hepatoplasma basically to re-seed its own guts. Marine snow might be the answer for the random distribution of this bacterium in the krill.
Now moving on to the moults… As I said before we started out with four trawls and looking at the moults – effectively the skin microbiome of the krill – we got this pretty amazing result that those four trawls, those four different populations, all had completely distinct bacterial communities. You can see on the plot that they are perfectly cluster together. You don’t often see that kind of resolution in this kind of studies. So that was pretty amazing.
To sort of crank this up and figure out what was going on here, we wanted to ramp it up. So we took a total of 17 populations – or trawls – from both the K-Axis and Totten voyages. These trawls were anywhere from 4 km to 3500 km apart. They were also in different water masses, what I figured would be different environment, so south of the boundary of the Antarctic Circumpolar Current, as well as a bit further north.
And sure enough, moults from different trawls were quite distinct. Interestingly, the further apart your krill swarm was the more distinct your bacterial population was.
I wanted to get to the bottom of this. Is this an environmental effect, is it something else? One way to try and tease this apart is to look at krill that is presumably living in identical environments. One thing that was handy was that on the Kerguelen Axis voyage, we did a krill box; we sampled quite a few krill swarms within quite a narrow size range - sorry, distant apart. In this case, we had three swarms that were four to eleven kilometres apart. As far as the Southern Ocean is concerned this is a pretty tiny distance. Rob King did make the very good point though you wouldn’t want to through a cricket ball between them. Hopefully you can see on this plot, even though these populations were much more similar than what we saw in the other plot, but statistically speaking they are still very much distinct. Basically they are in the same environment but they still have distinct bacterial communities.
One other way we can look at this is in the krill aquarium. I don’t know how Rob ended up doing this – thank goodness he did! – basically they took one swarm from the Totten voyage , one single trawl, and split it across four tanks in the krill aquarium. These krill were getting the same food, the same light environment, and the same water for nine months but importantly that water was being filtered and sterilized between tanks. So it was the same water but the bacteria shouldn’t have been transferred between them. After nine months, we took a few krill out of each tank, 12 krill in this case, and we swabbed them. This was a different way of getting the moult microbiome; we didn’t really know if it would work but luckily enough it did. It felt like giving the krill a little massage; it’s quite cute. Sure enough, four different tanks, once again totally distinct bacterial communities had developed over nine months in the krill aquarium. You start off with what was presumably a homogenous swarm; over nine months time they ended up with distinct communities.
How is this happening? One answer could be roller derby. Doesn’t make much sense… Before I get into how this might help us understand, I give you a quick intro into what roller derby is. [video playing] Alright. Now that you all know what roller derby is - and probably woken up those two sleeping babies at the back of the room – bit of an explanation. There was a very cool study in the US looking at the skin microbiomes of roller derby players. They started off with three different teams from different parts of the States and each team at the start had a distinct skin microbiome, same as the krill. But they found that after each bout, and this is obviously a contact sport, that the microbiomes of the different teams has started to converge. The contact is having a homogenizing effect on the skin microbiomes of the roller derby players. If you want to see some roller derby action, I’ve got a little plug here for the Convict City Rollers, that is the local Hobart roller derby association.
So, krill roller derby. Krill swarms can contain 1000 up to 2000 individuals per cubic metre. They are constantly swimming into their friends and relatives and into their bacteria as well. So there is every chance that like a roller derby this is having a homogenizing effect.
That explains why a swarm ends up with a homogenous moult microbiome. But why do the different swarms end up with different microbiomes? It doesn’t seem like it’s environment based on the krill aquarium and the krill box populations. Maybe it’s what is called ‘ecological drift’. This is basically random changes in the population that accumulate over time. If you imagine in the krill aquarium that they’d been in there for nine months, if the krill bacteria are reproducing say at one generation per day, that is 270 generations over that nine month period. That is quite a bit of time to accumulate differences potentially. This might be incredibly handy for krill fishery management. We’ve seen from the genomics that we couldn’t tell the different krill populations apart from their own DNA. But it might be that the moult microbiome gives us a chance to look at the mixing of different krill populations, whether we are looking at different stocks in different parts of Antarctica.
Just before I move on, there was one time when we did see an environmental effect. This was an experiment where krill in two tanks in the krill aquarium were put on a winter diet for six months. Those krill were fed once a week instead of six times a week for that six month period and then they went back to a standard diet for four months after that. We swabbed them just like the other krill and what we ended up with – the krill from tanks H2 and 5 are the two in the top of the graph – so they are totally distinct from all the other tanks, and they are also slightly distinct from each other. Because of that diet they seem to have converged on that some microbiome. Now it turns out that these communities were particularly enriched in a species called Arenicella – this was Leonie Suter’s experiment to look at regression of krill sexual regression in winter – and she also managed to find out that these Arenicella are associated with diseases of lobster shells. So the picture down the bottom is actual bacterial lesions that appear on lobsters that are infected with this Arenicella species. So it likes environment can alter microbiomes as long as that environmental effect is strong enough.
Moving on to the last part of my talk, now that we know the community, we know the bacteria that are present. If we know their genomes, we can also know the genes that are present and we can use that to look at the function of these communities in the different krill populations. There is a computer program with an incredibly awkward acronym – it’s called PICRUSt – stands for Phylogenetic Investigation of Communities by Reconstruction of Unobserved States – I’m kind of glad that they do have the acronym. We start off with our OTU table of different bacterial species of our different samples. We then take all the known bacterial genomes – about 61,000 bacterial genomes have been sequenced by now. It’s quite a bit of information out there. All the bacteria in our samples that have already their genome sequenced we now know the genes that are present. For all the bacteria that don’t have genome sequence we can predict the genomes based on the closest relative. After that we end up with a table of genes by samples.
When you do that for the krill microbiome, you end up with 7000 genes. And for me, I don’t do that much of this genomic work, it is very easy to get lost in this genomic space. It’s tricky to get anything sensible out of this. So I decided to focus on one particular gene that was probably going to be important for the krill and their bacteria, and that was the chitinase genes. Chitin is the second most abundant compound on Earth after cellulose. They reckon there is about 1 billion tonnes produced each year. Krill moults are pretty much entirely made of chitin and each krill is on average about 7 per cent chitin. It’s a really important carbon source both for krill-associated bacteria and the Southern Ocean in general.
These are really preliminary results. Looking at these different moult microbiomes, it did seem the different communities did have different levels of this chitinase gene. But was particularly interesting – I am not really sure what it means yet – is that we had four trawl that were more northerly than the others, and all four of these trawls had low chitinase gene content whereas the southern trawls had a much broader range. Some of them much higher chitinase gene contents. So the different bacterial communities do effect the gene presence and the function of these communities. It will be interesting when we get into it and can figure out more of what this means.
Just to wrap up… Hopefully you’ve got a new appreciation of how many krill-associated bacteria are in the Southern Ocean and how important they might be for the krill and Southern Ocean ecosystems. We found a krill gut bacterium that is potentially helping them to survive on a low quality diet and to absorb nutrients. It could be important for their survival over winter. We’ve also seen that the moult microbiomes could be very useful markers for the krill fisheries to see whether we are looking at different effective stocks in different parts of Antarctica, and lastly by looking at the genes we can see that different communities potentially have different functional traits that could influence carbon and nutrient cycling in the Southern Ocean.
Thanks very much for listening and special thanks to Rob, Jessica Melvin, Leonie Suter, Andrew Bissett at CSIRO, all the K-Axis expeditioners, Bruce Deagle and also the krill STS folk who I haven’t stuck on the slide but they definitely deserve a thank-you, too. Thanks very much.
Year-round access to Antarctica: New Davis runway
Listening to the deep water soundscape off East Antarctica
Listening to the deep water soundscape off East Antarctica
Video transcriptMike: Welcome to the AAD seminar series. Today we’ve got Brian Miller who will give our seminar. Brian did his undergrad at Boston University and graduated in 2003 – so you can to the maths. He did a Bachelor of Science in biomedical engineering and he also did a Bachelor of Arts in biology. I don’t know what to say about that… maybe it’s about how the US think about science, I don’t know. He then went on to complete a PhD at Otago University and it was titled “Acoustically derived growth rates and three-dimensional localization of sperm whales in Kaikuora”. Brian joined the AAD in 2011 as our cetacean acoustician replacing Jason Gedamke, who many of you will know. Brian almost immediate became an integral member of the whales team and has led acoustic teams on domestic and three Antarctic voyages and will lead another team in January 2019 on AAD’s RV Investigator’s voyage down to East Antarctica. He’s also a leader of the Southern Ocean Hydrophone Network group which is an initiative of the International Whaling Commission’s Southern Ocean Research Partnership. Brian’s talk today is title ‘Listening to the deep water soundscape of East Antarctica’.
Brian: Thanks, Mike. Okay, everyone can hear me okay? I’m really happy to be here today, to be able to share this talk with you.
Just want to talk a little about AAD’s passive acoustics program. It’s literally sound science so passive acoustics means listening to sounds and we focus on underwater sounds. Our stakeholders are government, industry and the science community, and as Mike mentioned, one of the primary stakeholders is the International Whaling Commission and we deliver our results through the Southern Ocean Research Partnership. Early this year, our group joined the Southern Ocean Observing System [SOOS] as well. So we’ve now created a technical working group – a capability working group – for the SOOS. Of course our work is delivered through the Australian Antarctic Science Program. There are a couple of common themes that keep arising with passive acoustics work. The most basic theme is simply passive acoustic surveys. This is listening for and counting animals and determining where they are. It doesn’t have to be animals; passive acoustics originally, I believe, started more as a military discipline monitoring for submarines. And geologists for a long time listened to the sounds of the Earth. All of those things could be considered passive acoustics. Animal communication and behavior is a really important aspect of passive acoustics. The more you understand about why the animals produce the sounds the more use you can get out of listening. A more recent topic that has become prevalent in this community is the effect of sound, of man-made sounds, on marine animals.
So what are the sounds, the underwater sounds, in the Antarctic? As I mentioned in the previous slide there are physical sounds, there are man-made sounds and there are biological sounds. Physical sounds can be sound from wind, precipitation, whether rain or snow, the sound of sea ice, as well as earth quakes. Man-made noise can come from ships whether that’s the propulsion, cavitation from the propellers, or sounds of machinery onboard the ship that are transmitted through the hull, or instruments that go ping or make other noises. But the sounds that I like to focus on are the biological sounds. A lot of different types of animals make noise; in the Antarctic the main sounds we are listening for are sounds from seals, but predominantly sounds from whales and dolphins were the sounds that really drove the conception and the bread and butter of our program. There are four seals in the Antarctic that make noise underwater regularly. These are crabeater, leopard, Weddell and Ross seals and there are about a dozen whale species that make sounds. So all baleen and toothed whales make underwater sounds and the instruments we are putting out at the moment can record sounds from blue, fin, humpback, Antarctic minke, southern right, sperm whales and killer whales.
This slide is just to illustrate the variety of different platforms that we can use to collect passive acoustic data. Passive acoustics, the main sensor that we use is called a hydrophone and it’s essentially an underwater microphone; it records the pressure wave form of sound underwater. In the top left corner, we have a simple directional hydrophone. It’s just a handheld device with some headphones. Here in the top right we have a more complex device which is AAD’s moored acoustic recorder. Some of you may be familiar with that or even helped to create or deploy that. At the bottom left we have sonar buoys; sonar buoys are directional listening devices that can be deployed from a ship and send their sounds back to the ship via radio link. And in the bottom right we have a towed radiophone array. These are devices that can be towed behind the ship for thousands of kilometers to listen for sounds while the ship is underway. So all of these include hydrophones, all of these are different forms of passive acoustic monitoring.
It’s a great time to be developing small sensors! In addition to the traditional forms of acoustic monitoring that I showed, there is a whole variety of platforms that we can put hydrophones on as well. These include autonomous underwater vehicles, profiling floats, autonomous surface vehicles and even on suction-cup tags that can be deployed on animals directly. So it’s an exciting time to be in this field.
What is it that we can learn from passive acoustics? Well, the main thing that we can learn is what species of animals are present and calling. We don’t learn anything about animals that are silent but we can about what species are present and calling. Most platforms allow us some idea about where those calling animals are located. For certain species or certain populations, we can also learn what those animals are doing. Perhaps there are sounds that are associated with feeding or with mating. Certain populations within a species might have distinct vocalization. So might learn about the population or the sex of the animal that is making these sounds. Males might make different sounds to females perhaps and if we know enough about the biology of the animals and what drives this sound production, we can learn about the abundance of those animals as well.
For the rest of the talk I’m going to focus on long-term acoustic recordings that have been made by the Australian Antarctic Division. The small map in the corner there is showing the location of sites where AAD has conducted long-term acoustic recording. This table is showing years for which we have long-term acoustic recordings. So in this table, a black X indicates a recording site that has approximately one year of data, the empty spaces indicate years when we didn’t attempt to collect data, and the little red sad faces there are unfortunately years we attempted to collect data but weren’t successful for some reason or another. Leaving instruments in the ocean for a year is always an activity that’s – leaving anything in the ocean for a year – is an activity that is fraught. Over the years we’ve used a variety of different instruments to collect these sorts of data. In the early years, we borrow instruments from SCRIPS Institute of Oceanography. This instrument is called and ARP or acoustic recording pack and these were deployed from 2004 to 2006. From 2006 to 2009, a device called a CMST Logger from Curtin University was deployed, and in 2013 the AAD deployed its first AAD moored acoustic recorder. Now these moored acoustic recorders were developed, they were basically conceived, designed and developed and operated entirely by the AAD and at this point I just like to thank the AAD’s STS group for their role in doing all of that. So we’re really, really lucky to have the STS group here. We’re able to take an idea, design precision-engineered instruments to do this job. The instruments that the AAD has designed allow us to record with better fidelity, longer duration than any of the instruments that came before.
Our project, our work here at the AAD is part of a bigger picture and you see here the filled circles showing the AAD recording sites that were the sites from that previous map. The open circles show all of the other recording sites that have been conducted in the Antarctic south of 60 [degrees latitude] by other nations. This map is showing all of the recording sites. The first Antarctic recorders were deployed in 2001. The AAD started in 2004, so we are just a few years behind there. This is part of what Mike mentioned already, the Southern Ocean Hydrophone Network or the SOHN and this is an initiative of the International Whaling Commission’s Southern Ocean Research Partnership and also the Southern Ocean Observing System. So the SOHN has a really long-term focus. We’re really aiming to characterize changes over long time periods. We’re looking at recording sound for more than a decade at each of these sites where we’re able to. It has a circumpolar focus; we’re building up to that circumpolar focus. You can see there are regions on this map that have no recording sites and we are keen to engage partners to fill in those gaps. International collaboration for the SOHN is absolutely important to deliver on these goals and the sorts of data we aim to collect with the SOHN are baseline ocean noise data to see how the ambient ocean noise changes over time. But as I already mentioned many of the group members focus on the distribution, occupancy and abundance of marine mammals or at least marine mammal sounds that we hear.
These lovely people are the IWC-SORP Acoustic Trends Working Group. These are the members who collect data and analyse data for the SOHN, and the goal of the working group is to use passive acoustics – this is the overarching goal – to use passive acoustics to deliver cost-effective information on Southern Ocean whales. The specific tasks that the group has been undertaking in recent years have involved coordinating, trying to match people who have ship-time to deploy instruments with people who have instruments, people who have analytical capacity to analyse the data. The group has also been working towards standardizing the data collection and analysis of these data. Each nation can potentially develop their own instruments and have slightly different standards and slightly different analytical approaches. That can frustrate a more holistic circumpolar approach to that analysis. The group also aims to develop novel systems, new instruments, new software, new analytical techniques to facilitate the collection and analysis of the data. And lastly the group has been working to provide advice and build international capacity to expand the network of recording sites.
Getting back towards the sound we hear in East Antarctica, marine mammals produce a wide variety of underwater sounds and I know in the abstract I promised we’ll play some sounds and we’re just about there. We can identify distinctive sounds from different species. There are a lot of sounds that are difficult to classify to species. So some species sound similar to each other but for the most part, every species that we have recorded has some sort of distinctive sound that we are able to identify and distinguish them. We’re not typically – this is a real common question so I just get out in front of it – we not typically able to identify individual singers. We can say that’s blue whale, that’s a fin whale, that’s a humpback whale but we can’t at this point say that’s Bobby, that’s Franky, that’s Harry. For some species passive acoustics can be a really, really cost-effective means of studying them and unsurprisingly the species that are most cost effective are the species that are rarely seen by other methods and that are highly vocal. So animals that make a lot of noise are perfectly amenable to passive acoustics, especially if they are rare and rarely seen from ships. In the Antarctic, these species pretty much are sperm whales, fin whales and blue whales. Alright, that’s enough background information, why don’t we have a listen to some of these animals. I’m going to play these sounds. There’s going to be a little animation called a spectrogram that shows a visual representation of the sounds and see if you can guess what animals are making these sounds.
[sound playing, spectrogram showing but sound difficult to hear] I started with an easy one. Any guesses? Just shout it out… Yeah, that’s right, that’s a humpback whale
[next sound playing…] Not a thunderstorm… it’s actually noise from ice. Ice can be really, really noisy, especially when it’s crushing into other ice or breaking up.
[next sound playing…] So you can see I had to play the sound that faster than it was originally recorded because it wouldn’t be audible otherwise. So it’s a very low frequency sound. Any guesses? These are 20 Hertz pulses produced by fin whales.
[next sound playing…] That went on a bit longer than I remembered. Any guesses? [audience: a seal of some sort?] It’s not a seal… it’s a big dolphin, it’s a killer whale. They’re just big dolphins.
[next sound playing…] It is mechanical, absolutely. These are the bow thrusters of the Akademik Treshnikov, a Russian ice breaker that I was on during the Antarctic circumnavigation expedition last year.
[next sound playing…] Anyone recognize that? Those are echo location clicks of sperm whales.
[next sound playing…] No guesses? This funny sound is called the bio-duck produced by Antarctic minke whales. The bio-duck was only recently linked to Antarctic minke whales due to an acoustic suction-cup tag being placed on a minke whale four years ago. The sound had been recorded by submariners for decades and they were never really sure what it was. They thought it might have even been some sort of Russian communication system but it turns out that it was Antarctic minke whales.
[next sound playing…] That was produced by a leopard seal.
[next sound playing…] That’s one I have played many times before in seminars. Anyone remember? No? It’s a blue whale, of course. It’s an Antarctic blue whale, that’s the song of Antarctic blue whales; they repeat the same units again and again and again for hours on end.
So I mentioned with passive acoustics we can learn what species is calling; they’re all sound quite different and distinctive from each other and we can learn about the occupancy and the temporal and spatial distribution. I said we wanted to focus on long-term recording sites and the figure at the bottom is what we call a long-term spectral average. It’s a way of visualizing an entire year of sound and all at once. This is a long-term spectral average from our site at the southern Kerguelen Plateau. We’ve got time on this x-axis here and we’ve got the frequency of sound on the y-axis. So it’s like looking at one of those spectrograms, one of those visualizations that I just showed but it’s quite compressed and it’s showing the average. Each vertical pixel corresponds to one hour of sound. So there is a lot of compression going on because the resolution of the display is far less than the number of hours in a year. But it gives us a good sense of what’s making noise. These horizontal bands of sound are tonal calls from animals, and the vertical bands are sounds, increased background noise, from elevated wind and waves. Just to illustrate the effect of wind, these moored acoustic recorders, they sit deep in the ocean - they are two to three kilometres deep – but we still pick up the effects of storms that pass overhead. The top graph is now showing the average wind speed at this site in six hour increments and the wind speed was measured from remotely sensed data. So it’s a product that gives us sort of two and half degrees spatial resolution and six hour temporal resolution. If you look closely, you can see some of these peaks in the wind speed correspond to some of the peaks in the long-term spectral average. If you don’t want to correlate it by eye, we can actually plot it up here now we have wind speed on the x-axis and we have the sound energy on the y-axis and you can see that there is a positive relationship there.
So where to the animals fit in? Antarctic blue whales, the low frequency sounds – we had to speed them up – so these come in at the bottom of the spectrogram here. Fin whales actually have a lot of overlap with blue whales; you can see these low frequency pulses also show up on the long-term spectral average towards the bottom. But if you see this little blip up here, this also shows up on the long-term spectral average as that narrow, yellow band from April to about July. So this is the season for blue and fin whale song.
Leopard seal sounds. We really mainly detect them throughout December and early January and if I recall correctly, this is during their breeding season. So these are highly seasonal calls.
Antarctic minke whale, the bio-duck sound, is kind of the odd one out. They are the only species really making noise throughout the winter.
Our ice noise. You can hear ice throughout the year in the Antarctic whether it’s frozen solid or whether it’s being broken up. But what I really like to illustrate with this is that during the months when the recorder is not covered by ice, we actually have a real increase in low frequency background noise, and during the months when the recorder is covered by solid ice we have a real decrease in that low frequency noise level. The ice is a really important part of the soundscape in East Antarctica. So putting it all together, we can look at this long-term spectral average and this can basically be considered the soundscape of East Antarctica. We can kind of work out when and where species are based on simply comparing these long-term spectral averages. The top figure is showing the spectral average for the Casey site, a site along the Casey resupply route, and the bottom figure is showing the spectral average of the southern Kerguelen Plateau and one of the main things that seems to be different between these two figures is the colour of this band down here. This is representing find whale calls; these seem to be absent at the Casey site. Both of these spectral averages are showing the calendar year 2014. There was a little bit of an offset; the Casey recording was put in first, the one on the Kerguelen Plateau was set up a little bit later but otherwise there is a lot of overlap here. Another thing that seems to be more present on the south Kerguelen Plateau is the minke whales. They are a lot fainter at our Casey site.
We can also compare multiple years of recording within the same site. Now we’re looking at three years of long-term spectral averages, all from the southern Kerguelen Plateau, from 2014 to 2016, and you can see the intensity of the fin whale band seems to be quite variable throughout the year. Minke whales were very present in 2014 and 2015 but they seemed to be a little bit fainter in 2016. And the leopard seals, you can see again really producing sound during that breeding season and all of the sounds seem to be quite seasonal when they are present.
So I’ve been talking for a while now, and I’ve got a bit more to go but I try to get through this quickly. Some of the species that are really dominant in the soundscape we’ve had a listen to and looked at, and these long-term spectral averages are really a synoptic picture of a recording site for a year. But really, fully make use of the data we actually have to … we might be interested in sounds that are produced less frequently, that are intermittent or possibly rare. A lot of species don’t make noise as frequently as the ones that dominate the soundscape. Some species do make noise quite frequently but because of the characteristics of the sound they produce, they don’t show up on these long-term spectral averages. So other analytical techniques are required.
The sort of techniques we like to employ are often called Detection, Classification, Localisation and Density Estimation. That’s a lot to say so it does get abbreviated to DCLDE which is still a lot to say. Just conceptually, Detection can be thought of as separating out signals of interest from the background noise. Classification can be thought of as identifying different types of sound. Localisation is simply the determination of a sound source, and potentially the movement and tracking of a sound source, and Density Estimation is just a fancy way of counting, saying that we want to quantify the number of sounds or animals that we hear.
This suite of techniques is really a multi-disciplinary endeavor and it draws from engineering, computer and data science, physics, biology and statistics. You really can’t focus on any one of these fields and get anywhere in terms of actually understanding passive acoustics. You have to involve all of them to some degree. I won’t talk too much about this but happy to talk afterwards. Just wanted to show it’s truly a multi-disciplinary endeavor and it’s not purely a biological study, it’s not purely physics, it’s not purely engineering but it’s a combination of all of these things.
Just to give a quick illustration of an example, you know sperm whales are a very, very vocal animal. But they weren’t present in that long-term spectral average. There is no indication that there were sperm whales in that long-term spectral average. Here are sperm whale clicks, here’s a spectrogram of sperm whale clicks showing 10 seconds of data, ten seconds of audio and the clicks are these vertical bands. So the majority of time there is no signal and for very brief instances these echo location clicks are present. So we can create a detector by looking at the energy in these vertical bands. We can think of the energy in the clicks as a detection function. The bottom is now showing our detection function and we can apply a threshold to that detection function – represented by that red line – and where the detection function exceeds that threshold we can call that a sperm whale click. We can extract those clicks and we can basically detection and classification can be thought of as transforming the audio into a signal that is more friendly. So it’s signal processing and data science.
Once we have perhaps detected the clicks, we can perform this feature extraction – so additional transformations – to separate out clicks, any sort of clicks, so our energy detector will not just detect sperm whale clicks but it might detect clicks that come from ice or other species. So we can take the extracted clicks, the detected clicks, and transform them yet again, in order to try to better represent the signal of interest. So here we’ve got our long-term spectral average again. The pink X shows a time period that has been manually inspected and has been determined by an analyst to have sperm whales present. The red cross indicates a time period when there are no sperm whales present. we can extract features from the audio for each of those times to separate out these signals better and then transform the audio into these features and – low and behold – after transformation we’ve got a dark spot on here that gives a good indication that sperm whales were present in this time period but not in that [points to empty space] time period. I don’t want to go into the details but happy to talk afterwards. If we apply these methods to the entire data set we can start to answer questions about the presence of sperm whales. So now top figure is showing, the blue line is showing the proportion of hours per day for which our detector and classifier have determined sperm whales are indeed present and the grey boxes are showing the proportion of days per month for which our classifier detected sperm whales. There is a faint red line in here that shows the proportion of ice cover and you can see that sperm whales are really not detected in the winter at all.
So this is just an example of detection and classification. If we actually want to count animals, we move beyond just detecting the presence of animals. We have to start localizing animals. A conceptually simple way to think about localization is just what is the detection range of these sounds. It’s conceptually simply to think about but actually to answer this question is really involved. It requires understanding the characteristic of the signal, the noise and you have to understand how sound travels through the environment, and you have to have good models for all of these things.
Just to illustrate how challenging this can be, this is a figure from a recent publication by
Benda-Beckmann and colleagues. This is illustrating two different models and two different thresholds for the detection of sperm whale clicks in an effort to determine the range. You’ve got the range of the clicks on the x-axis and the probability of detection on the y-axis and you can see that the worst performing model detects sperm whales out to about four kilometres, and the best performing model detects sperm whales out to about twelve kilometres. This is assuming a fixed signal, fixed noise and a fixed environment. In reality, the noise, signal and environment all change over time. So this can get quite challenging.
Finally, if we want to estimate the density of animals and not just the number of calls we detect we actually have to have some behavioural information about the animals. Just over here we have our density estimation equation. It says that the density is equal to the number of calls divided by the time, area and cue rate. So we can define the time span as one hour. Let’s assume that we can measure the detection range – not something that’s very easy but let’s assume that on average the detection range is ten kilometres. That gives us a detection area of pi r squared which is about 314 kilometres [squared]. From previous studies, people have determined that the click rate of an individual sperm whale is about 1.27 clicks per second. Each animals clicks at that rate, but they don’t click all of the time. In fact, each animal clicks only about 60 percent of the time. So with that individual click rate and duty cycle we can calculate what the cue rate is and we now have all of the information we need to estimate the density of animals. Assuming from our example that there were 2600 sperm whale clicks detected in an hour, a random given hour, we can put that into our density equation and estimate that this works out to three animals per 1000 square kilometres per hour. Now we have to be a little bit careful. We might think that we can estimate from that the total number of sperm whales that visit our site. However, if we want to extrapolate over that entire three year time period, we really need to be careful. And the situation we are trying to avoid is – I think I could explain it – but I think it’s really well expressed by this cartoon which has been hanging up in the science tea room for as long as I’ve been here. That’s the situation we have to avoid when we are trying to extrapolate density estimates over time. We can’t identify individuals, we don’t know whether we’re counting the same whale multiple times.
That’s probably a good place to end. Just to sum up, there is an increasing amount of acoustic data available. There is an exciting number of platforms and sensors and as sensors get smaller and computers get faster, more power efficient and data storage gets better we are only going to improve in that regard. There’s a suit of analytical methods available for analyzing these data but very few of these are general purpose methods or are standardized. So a lot of the work involves developing detectors that are specific to a species, classifiers that can distinguish between different species and we can do density estimation and abundance using acoustics but there is a really severe limitation because to do density estimation effectively we need to know a lot about the acoustic behavior of the animals that we’re listening to. We can conduct dedicated behavioral studies to better understand the acoustic behavior of animals. You can put acoustic tags on animals; that gives you a great source of information about their behavior but also sighting survey, simultaneous visual and acoustic surveys and focal follows of animals can be a real good source of information. This might still require some dedicated ship time but not necessarily entire dedicated voyages. This is the sum of the information we are hoping to collect on the upcoming voyage on the Investigator in January.
That’s all I’ve got. Thank you very much for listening and I am happy to try and answer any of your questions.
Marine Ecosystem Assessment for the Southern Ocean
Marine Ecosystem Assessment for the Southern Ocean
Video transcriptRowan: G’day everyone, I think we might get started. Thanks for coming along; I'm recognising a lot of faces in the audience and realised that most of you already know Andrew and what he does. But I keep this brief as some of you may not Andrew [know him]. Andrew is a Section Leader at the AAD and a program leader at the Antarctic Climate and Ecosystems CRC. He recently led the Marine Ecosystem Assessment of the Southern Ocean conference which happened last month here in Hobart which is what this talk is about and MEASO – as it is abbreviated to – has been in planning at least since 2013 is starting to come to fruition with the conference. You may have heard that the conference is widely regarded as a great success and also quite unique in several aspects notably the inclusiveness of it in terms of the wider scientific community. It had a strong international flavour and a strong emphasis on inclusion of early career researcher voices but also more generally in terms of stakeholders and interest groups through the policy forum. So I am looking forward to hearing what Andrew has to report.
Andrew: Thanks very much, Rowan. I had to run away to get my talk as it was not coming up on the screen. Thank you all for coming. It’s quite a pleasure sharing the stage with a Christmas tree. I remember some 14 years ago I was at a conference, an interesting conference in the US. It was looking at a similar sort of topic as this. One of the people who got up was quite a reputable ecosystem modeller and his introductory remark was: “Well if you thought your Christmases had not yet come, they are all going to come now.” And he still has not yet fulfilled this promise. The reason why I make this point is that this work is very hard and people have been talking about doing things like this for many, many years and I want to draw on that and the flavour of this talk – because I know that many of you were at the conference and participated in one thing or another – many of you will be familiar with the material and what I want to do really is to talk about is what brought us to the conference and where are we going now, and how do we deal with such a large problem. There are many aspects to this problem and that is what I really want to talk to you about in this talk. I am sharing this talk with Rowan, with Jess Melbourne Thomas and Mike Sumner because the four of us have been working for some time now in the background to determine what constitutes an ecosystem assessment. Rowan has a paper under review which looks at one aspect of that which relates to habitat. The other part of the conference had to do with evaluating species, and evaluating food webs and ecosystems generally. Why the name? The name that I started with was really long. Miso is in fact a soup if you look it up. It is a very easily digestible soup - as is this title - and it is very enjoyable. You can have it before breakfast, breakfast, lunch, dinner, after dinner … you can have it at any time. It is a nice savoury soup, quite filling and energizing. I like to think that this was like this conference was, and that its name will progress in that manner. It came from Jess when we were brainstorming potential titles and I think it has gravitated quite nicely to the acronym of MEASO.
So who was involved in this conference? There were two parts to it; the local organising committee which is on the left. We had our last meeting on Tuesday. The Wrap Up is more or less what I am going to talk about now. By in large the committee was a great success, pulling things together, bringing the expertise together, having ideas for the conference, formatting the conference and having it proceed very nicely. You see on this list that we have a diversity of representatives from our community and they were all very helpful in providing support; and as I did on Tuesday I want to give specific recognition to Wenneke ten Hout from the ACE-CRC who really should become a conference organiser because it went smoothly and it was an organisational success because of what she did. She was not there for the conference but all her preparatory work was great. - On the right hand side you'll see the international steering committee. They helped organise the general proceedings of the conference, particularly the talks, the structure of the talks and the posters. We thank them as well. That group is going to be very important as we are going through the production of the first MEASO. These are representatives from a variety of and Arctic research groups that are involved in marine ecosystem research.
These are our sponsors. I thought I am going to show you this just to indicate that we had a diverse group of sponsors across our stakeholders. So it wasn't just conservation or fisheries or particular agencies and so on. We had quite a diversity of sponsors and we thank them for that. Without them we would not have been able to have the key notes and the attention to the detail.
So why have a MEASO? Where did it all come from? What we are interested in when undertaking a marine ecosystem assessment in all its guises was really trying to assess some of those key questions that people are addressing in many forums nowadays. People call them ecosystems services and all sorts of things but I like to think of them as managing risks to our condition, our physical condition, here we are physically, and what is around us is our social condition - so it's our society - and it's our psychological condition. There are all sorts of ways one might look at psychology in the importance of ecosystems. I summarise it in these three terms. Of course there are many other things you might place on that list but from an individual point of view that is what we are going to be interested in. I also like to think that one of the important risks that we are trying to manage is what happens when we change our priorities in future. How much are we going to diminish our future amenities so that we can pursue what we might decide in the future to be important. I think that is also part of what we are trying to do. These days this is called intergenerational equity and all sorts of other terms. So that is what we are trying to do with the MEASO. What might it look like to help manage risk? And of course this is not going to play now… I had an audio… anyway it was a fire alarm. That is why I put up the sign don't panic. It's a test. So just imagine beep beep beep… when you hear that you all know what to do, and in order to manage risk that's what a fire alarm is for; it’s to manage the risk of fire destroying you. You know how to respond to that. I like to come back to that but just think about this as we go through the talk. How do we make something that is a satisfactory alarm for action?
One thing about a MEASO is that. Kathryn Woodthorpe who is the chair of the CRC, she put This one up as one of her first slides: “At the start of every disaster movie there is a scientist who is being ignored”. There are many ways that scientists can be ignored and one of the things we are trying to do with MEASO is trying to overcome the issue of the scientist being ignored and that there is no foundation to ignore them. How might we achieve that? This is a really important question when we start to think about it.
So here is another way of looking at Why a MEASO? On the left-hand side is a series of scales of science. We could do molecular science, we could do science on individual species, we do science on the ecosystem, we could science on a region which may have a number of ‘ecosystems’, and we might look at the Earth system. And as scientists we tend to choose a scale at which we work and one of the points of the last decade of discussions in many forums, many science forums under the International Council of Science, has been consideration about not only how do we get discussions amongst scientists across disciplines but also across scales of interest so that we get a much better fusion of knowledge across different scales. If we start to map then the scales at which people are operating, we can map that as the kind of impact they have on decision making or on the population. So you can see at the bottom scale of our interest in organisms, the ecology of organisms - we like to sit and watch whales - and you can see at the very top we might have the whole of the global population needs to have an interest in what we are achieving. Between that there are sort of different scales of interest and decision making and particularly focusing on the United Nations which are trying to engage all 196 countries that are involved in the United Nations, or just a few countries 26 countries, or 26 members I should say, involved in CCAMLR, for example. And there are more that are involved in the wider Antarctic Treaty System. On the bottom axis you see I have labelled that effort. How much effort in terms of science does it take to get consensus at those different scales? Think about the recent climate wars, and ongoing climate war, chances to get the whole public to agree on a prognosis for the future and who caused it is impossible. You get to the point when as much effort as you like is really not going to change the day. But how can you get consensus? That is that even if people don’t agree to the proposition they will still agree to actions being taken. That’s the important thing behind the MEASO; how can we get everybody to agree to proceed and the start of that is how do we get scientist to agree with a central estimation of risk rather than being in disagreement. That is one of the important issues to face.
Coming back to my fire alarm, Don’t Panic! The fire alarm is there for a reason. What does it actually mean in terms of managing risk? One of the great successes of fire alarms is universally it’s agreed what you do when you hear it. When people hear an alarm of one sort or another they know that they need to do something. They need to be vigilant and they need to act in response to a fire. Quite often the alarms will go off even if there is no fire. So there is a risk of something happening when you hear an alarm but there is also the alternative which is something is not going to happen but you are going to act anyway just in case. That’s what we are trying to do with the marine ecosystem assessment. Can we identify those risks to the things we hold dear and then take action in suitable time for us to make sure that if there is a problem then it’s not really going to arise.
So what is a MEASO? This was a definition we put up early in the meeting. We had a discussion paper at the conference – you are all welcome to the discussion paper if you like it; just let me know, and there is an appendix to this as well – and it was the centre point in the discussions in the margins. Even though there wasn’t a lot of time for broad discussions there was still a lot of discussion in the margins about what a marine ecosystem assessment should be and how might we progress towards that. Towards the end of this talk I will be talking about how we will progress it but this was an idea of an objective. The aim of a MEASO then is to provide policy makers with estimates of change relative to a baseline. An estimate of change may be fully quantitative. We can state precisely what the abundance of something might be relative to an initial abundance, or it might simply be that we are pretty confident that something changed into this direction and not that direction. So it becomes almost a binary type conclusion, but nevertheless we can provide policy makers with that sense of change and whether or not they need to take action. We would imagine then that this assessment will be a consensus amongst the scientific body that is interested in a region, a consensus on the estimate of change that will facilitate adapting to future ecosystem change. We can add to that to take also action on apparent change. But this was the focus for the conference. What we are trying to do is to facilitate adaptation in order to maintain a low risk of adverse impacts into the future. In the Southern Ocean, the most common point of discussion is to deal with fisheries but there are other factors going on globally that are worthwhile advertising that they will generate a risk of adverse impacts into the future. Human induced climate change and ocean acidification is part of that. We need to be able to develop that consensus on the basis of those estimates but also taking count of the uncertainties in the scientific information. This is not new. What I like to do now is to talk briefly about what where has this actually come from and even though there is a lot of new language and new thoughts around this problem, it has been going on for a long time. In the marine space, I had the great fortune of being involved in my early years with people, such as Bill, and one of Bill’s early mentors, Sydney Holt. In the two models of the IWC in its early days, particularly through the 1960s and 1970s, there was recognition that we were damaging the environment, in this case whales, and what do we need to do about it. How do we arrest the decline of the great whales and ensure their recovery given the uncertainties. Sydney and Bill, and Justin Cook and others were very formative in the approaches we can now look upon as risk assessment at a system level. These kind of discussions have been very formative not only in the IWC but when those ideas then were brought into CCAMLR, in fact in 1986 – I’m now just going to say a few words about what Bill has done in CCAMLR – in 1986, Bill handed in his PhD and at the same time he instituted the program of work that became known as the Working Group on Developing Approaches to Conservation or WGDAC for short. In 1987, those discussions began and that was the instigation of risk assessments to the system and what might you do about that. One of the great outcomes of that particular work was between Bill - and there were others in the area, Doug Butterworth, M. Voison, Andre Punt and others – were talking in the working group of krill we don’t have an estimate on the abundance of krill – well, we have some but they are not very good – but how might we use those to come up with a precautionary catch limit and take account of these risks. That was really important because what that meant was that by the time it got adopted in 1991, there was a rule in place that the Commission agreed as a whole that they, whatever the outcome of the application of that rule given the data, that would be the accepted catch limit. That made decision making in CCAMLR a breeze compared to other bodies that manage fisheries because the same method is applied to toothfish, to icefish, as well as krill, and that means that with the acquisition of the data and the processes of using the data and then applying the decision rule the catch limits are set and there is no argy-bargy, well… mostly no argy-bargy in the Commission. And that’s really important because it means that the scientists might disagree about the value of the different kinds of data but once you put it through the mill, and you have an answer, then you get a consensus outcome for action. That’s what we are trying to do in the marine ecosystem assessment. How can you actually pull together a lot of disparate data about the effects of climate change, the effects of fishing, the effects of tourism, the effects of stations and so on. How can you pull all of that together into a way that would mean that the decision then is an easy one to take. One of the great impediments of Sydney and Bill and Justin and others was at the time way back in the 1980s is the computational power wasn’t there. In fact when Sydney wrote the book, the bible for fisheries way back in the 1940s and early1950s, when they wrote that book with Ray Bevon, the Bevon Holt bible, they didn’t have computers. So they were coming up with ideas to try and work out how to do this. Fortunately now we do have the computing power. We do have statistical power. Even in though it’s in its infancy we have the capability to start bringing those ideas together in complex system ways. So how do we do that? That’s what we are trying to discuss.
One of the things that is really important in these discussions is how do we actually harmonise expressions of change? One of the things you may remember from an earlier slide is that we can go all the way from the UN down to the person on the cliff watching whales, and they’ll be talking different languages depending on the people they are amongst and the languages that they inherited. In fact, in fisheries it’s exactly the same; do you have an IWC pedigree or do you have a pedigree that emerges from stock assessments on coasts. You’ll have a different language even of stock assessments. We need to try and harmonise what we mean. Biodiversity means everything under the CBD and in other organisation biodiversity just means species richness. It’s trying to be very clear what we mean and what managers need to know. One of our tasks it to come up with a set of metrics that articulate in a simple way what is the state of the ecosystem in the various ways that managers might be thinking about them. We were discussing six; there may be others. There may be different language to this but each of these six expressions of change of six ecosystem dimensions have some sort of provenance from different conventions and different regulatory frameworks that we know about. So the physical environment, for many who work in system models if you know about the physics, then everything else will follow even though we are starting to know that biology can play a big part in physics at various scales. So it’s not entirely true that physics will carry through and govern everything else but nevertheless knowing about the physical environment is an important foundation. The second thing is what is the species pool that you might have present? And how do you do that in a way that you are choosing a species pool or you’re giving access to all species that are living in a place, just are they there? For example, one way of looking at species is what is the kind of environment that they might like to live in? And if you look at it that way, penguins could live in the Arctic and polar bears could live in the Antarctic. But they’re not there. How much do you deal with that? Not only are you dealing with species richness but you are looking at the effectiveness of – or the realisation of - a species being able to be present. And that can deal with in a continuous way, deal with endemic species, invasive species, globally distributed species and so on. The third dimension is about the structure and the function of the food web in the ecosystem as a whole. That is going to be important if you are looking at a variety of things in relation to say the krill-based food web or the fish-based food web. The next dimension is about energetics and production. How much is there? How much is going to be produced, how much biomass is going to be produced? That’s important from a global carbon cycle perspective and the extraction of carbon from the atmosphere which will help reduce human-induced climate change. But it’s also important to fisheries, it’s also going to be important to iconic species that we like to see and we like to conserve and we like to be able to understand. It’s also important to those; how much energy is left over for them. And the last two is something that is becoming much more important in our consideration of natural systems. The first one is about the frequency of extreme events that might be game changers. So in the first four quite often we think about it in average terms, we’ll think it’s like this and like this. But it may be that extreme events cause a system to change irreparably. We are starting to see that on the Great Barrier Reef. The last one is about human forces. I use the term ‘human forces’ deliberately here because for many people we’re now seeing in many science programs a fusion not only between the physics, chemistry and biology but also the social sciences. They are all part of that. There has been an image since the early 2000s that people are part of the ecosystem and therefore the requirements for people should be considered as part of the ecosystem outcome. That came from the Food and Agricultural Organisation in their ecosystem-based fisheries management discussions. But for me, if people are really part of the ecosystem, then there should have been some sort of co-evolutionary processes going on so that there has been some adaptation to people being in the system. There are very places around the world where I would say that the current human activities are such that the ecosystem has co-evolved so to account for those kinds of behaviours. I think people still stand above that but the idea for looking at what are the human forces on the system, and how might these human forces actually affect the risks to the things we hold dear which is where I started. It is not necessarily requiring that the ecosystem has co-evolved to adapt to those responses. So there are our considerations to our six dimensions that managers might be interested in. Those six dimensions are obviously interrelated. So if one changes, so if energetics goes up, then the food web / assemblage structure might change if the production has gone up only in a particular way. We need to think about that but to summarise the statements for managers is going to be important.
The MEASO framework aims to try and provide an assessment method. I stated at the outset that a lot of people don’t like this approach as a presentational approach but I’m using it here because I haven’t come up with something different. We have a group of people now, not formally a group of people, but a number of people thinking about what’s the best way of communicating these summaries of change on those six dimensions. On the left hand side you see the six dimensions represented. Each of these triangles, the apex of these triangles, its height above the apex is meant to indicate the magnitude of change, and the black bars indicate the uncertainty. For some things in some areas you might not have much uncertainty but for some other things there might be considerable uncertainty. So things like the species composition, invasive species might be important. If that is highly uncertain, then we might need to give attention to that and I come back to that later in the talk. But the aim is trying to have a simple graphic that could convey current change might be useful in the way it is displayed on the right so that you can start to see which area around the Southern Ocean might be most vulnerable to change and which areas we might have to concentrate on further. So each one of these plots that you see on the left, we could do one for now compared to say a hundred years ago. We could do one for 50 years time compared to now or we could do something for 100 years time compared to now. One of the points of attention we’re asking for people to think about is what’s going to happen in the next 20 to 30 years, because it takes about that long to change the direction in any international body. It’s not something that can be done overnight; it’s a long haul. So thinking about 20 to 30 years time is a good time frame to think about future change.
What are the gaps to fill? We have an idea about what things we want to measure, make statements about to help managers at a system level. What do we know now? On the left is a diagram of a food web with benthic-pelagic coupling; it’s primarily a pelagic food web that links to the benthos, and on the left hand side you see a krill pathway; in the middle you have a pathway going from the phytoplankton through copepods through fish to the higher predators, and then on the right you see the pathway that links the pelagic with the benthos – and there is dashed line around toothfish because it sit between the benthic environment and the pelagic environment feeding on both. What is interesting about those pathways for CCAMLR, for example, the Commission for the Conservation of Antarctic Marine Living Resources, is that this left hand pathway is the krill pathway, and that right pathway is the toothfish pathway. So if the krill side goes down for whatever reason leaving more production for the right, then toothfish might go up. Or if the toothfish side goes down, the krill side might go up. Maybe. Or there may be partitioning between the pathways that we need to know about. The circles are intended to indicate what part of this very simple food web do we have estimates of abundance for. I like to thank Nat for giving me a summary on quick notice on the estimates for whales, and one of the key groups of species that we are interested in here in the Antarctic Division is the productivity and population dynamics of whales. We’re seeking to conserve whales into the long term and not prejudice their recovery yet their estimates of abundance date longer than a decade ago and there are many uncertainties about those estimates from around the Southern Ocean. That is one of the groups of species that we are interested in and there’s been a lot of work on. We are also interested in krill. The status of estimates for krill are less than 10 years for some areas but mostly they are 10, 20 years old already. So we don’t have any global estimates of krill abundance at present and for many for many places we don’t have much knowledge about what they are doing over time either. Toothfish are in a similar situation. We’ve got the areas around the sub-Antarctic islands where we have good estimates of abundance but for other areas they are not so good. For the higher predators we’ve got recent estimates of abundance of penguins but seal abundances are quite dated now and we need to start thinking about that. Everything else we really don’t know what they are doing… If we look on the right, this is a map out of a paper that Rowan has under review and the red dots indicate areas where we’ve got individual taxa with estimates of abundance and we are monitoring those over time. That might be zooplankton out in the Indian Ocean through CPR, maybe seals on sub-Antarctic islands, penguins on sub-Antarctic islands – not necessarily both – penguins at land-based stations, seals at land-based stations, flying birds, and so on. So you see that for most of the Southern Ocean we are just tracking individual taxa; we’re not getting a good look at the system overall. On the western Antarctic Peninsula and the Scotia Arc the story is a little bit different and we have not tried to pull that together yet as an ecosystem assessment but that is a place where we can start. But you can see it’s mostly patchy. It’s interesting that if you did see Stacy McCormick’s talk at the conference it’s quite clear that the krill-based system is found on the west Antarctic Peninsula, the typical system you would read about in books and it’s not found anywhere else as a dominant part of the system. It has also got other things going on, fish and the like become important prey species. So there are lots of gaps to fill. (I skip that slide…)
One of the things that Jess raised in her talk to the policy forum which was on the Wednesday was this idea of deep uncertainty. We all talk about uncertainty and there are people going out to estimate uncertainty, which is an interesting concept. Identifying uncertainty and trying to resolve it, trying to resolve the errors in our estimation is difficult. But when there is disagreement about the processes by which those errors might even be estimated, then it causes great consternation and great difficulties. In CCAMLR, for example, it’s a very different environment to the Antarctic Treaty Consultative Meeting in that in CCAMLR each year they have to decide on catch limits for species and management actions that will appropriately conserve the Antarctic marine living resources. That’s a different type of environment where many nations are after the same species in the same locations; that means that you can have quite a lot of national conflict. Whereas in the Antarctic Treaty Consultative Meeting quite often the management relates to individual stations where it’s managed by a nation and the opportunities for conflict if you like between nations become much less. It’s more at the higher level than what occurs at CCAMLR. And that’s good to know about; it’s good to know what the political environment might be in order to try and tailer how the information gets managed.
But taken into account deep uncertainty is one of the things we need to talk about. One of the key messages out of Jess’s talk – and out of this particular slide - was that having systems that can adapt to change is going to be important. We need to add to that we need systems then that can adapt to prospective change. In other words that change is upon us, how are we going to adapt to that before it arrives because if we wait for the change to have happened and try to react, it’s probably the case that it’ll be too late to be able to do something about it or something that is effective and we end up chasing our tails. That’s why the 20 to 30 year horizon is a good one for the Southern Ocean because it is in that 20 to 30 time that we would expect to see a lot of dramatic changes in Southern Ocean ecosystems as a result of warming and ocean acidification.
What is a MEASO in practice? We have our map, we try to divide the map up into regions where the behaviour of the physics is likely to be consistent but different then between regions. So we got four of these. They are most aligned with the way various disciplines look at these areas. We can extract data out of a particular area that we might be interested in. This diagram comes out of Stacy McCormack’s work on food webs and the circles were put there by me to indicate that these are the parts of the food web where we got most data. You can see that there is a lot of the food web say out of the South Atlantic where we don’t have a lot of data. So we need to try and come up with a system assessment and start to look to the future about how the system will behave, and we need to take account of the fact that we don’t have a lot of data for most species that are present. So the aim of the MEASO is to suck in all the data that we can to look at the ecology of the system as best we can and then start to use the data with our understanding of ecology to deliver to the end users. Then we summarise that information into the various dimensions as to what is the state of that dimension and how is that state changing over time. As a result of that - given the uncertainties and risks that might be associated with those summaries of status and trends – we might set up a set of priorities that would alter management measures, we’ll generate some adaptation responses or we focus our research and observations to help fill the gaps. It’s a very typical adaptive system, the likes of what Bill and Sydney and Justin have worked on in the past and what we use in CCAMLR, except at a larger scale and in an individual fishery. What is important here is that this kind of process is well established in the physical sciences. We don’t have to think that this is new; we can look to see where it was successful. In the physical sciences, they ended up with a Nobel prize after the fourth assessment review at the Intergovernmental Panel for Climate Change. That was a fantastic result but that was after many, many decades of bickering and carrying on in the early decades. Coming through with a very coordinated response, coordinated approach to their field work, and each assessment cycle came up with the next set of priorities to work on for the next cycle. That’s a very smooth cycle, now to the extent that the modelling processes that feed into the assessments now have a regular cycle as well for looking at how well they do.
For ecology, let’s just blow that up, that’s what we are trying to do. In the middle, we have a computer – that’s where all the work is. We use the computing grunt that we have; we need appropriate assessment methods and ecosystem models and we suck in our field observations. These may be lots of different things; direct sightings, acoustics, isotopic signatures, satellite data, all sorts of things and we are trying to match them together. It’s great when they are taken coincidentally but if they weren’t, then we need to try and work out ways we can pull them together. We do that by looking at the ecology of the system; that’s a food web diagram up there, a very simple one that we work with but understanding the responses of species to physical variables is very important. Looking at how species co-vary over time may be all we have but how much do we expect that from a theoretical perspective. Some of the modelling that Bill is doing more recently on the individual base modelling for whales, and he’s worked it up with So on krill, there is work that Louise is doing on penguins, and so on. All that feeds into a better understanding of how we link all this data together. That is one of the big tasks we have ahead of us because that is modelling efforts are still at a rudimentary level. And then at the right hand side is well what to the end users need to know about. There are the six dimensions I mentioned before but the reporting on the six dimensions is something that we need to think about. One of the important aspects of a MEASO is that can we do something where we’re getting consensus among the scientific community. We’re not just getting a part of the community we’re getting the whole of the community to sign off on a report like the IPCC reports. Then that report can be what feeds into the different end users, feeds into CCAMLR, feeds into IWC, feeds into the IPCC, feeds into the UN, and various other bodies that are trying to do these assessments. There are a lot of these groups trying to do these assessments. So can we come up with one report rather than ending up with five, six, ten or more science reports that are all saying that they do the same thing but they have different outcomes. In the end, these bodies that are on the right, the end users, have to synthesise all those reports into a single document. So why don’t we do that for them because it is better the scientists synthesise the science than it is for policymakers to try and interpret and then synthesise after that. Quite often they won’t have the capability. So THAT’S the aim of the MEASO in practice. It is trying to that across all the variety of groups, not just those that are specifically in the Antarctic but also those that are coming out of the other ICSU processes, International Council of Science Unions, say through future Earth and other things, there are a lot of biogeochemical groups now as well.
So the conference, that’s all the background, that’s what we are trying to do, that’s the philosophy that we are trying to have. The conference was … initially we would have been happy with 40 people and in the end we ended up with 180. We had to change the idea from a working conference to a conference but with the idea to come out with a work program afterwards. Our earliest career researcher was Eila, Jess’s young bub, who was a great participant in the conference. As Rowan said one of the really neat things coming out of this conference was the engagement of early career researchers and mid-career researchers in trying to generate an agenda for their research futures. In summary, we’ve had 175 attendees, 23 different countries, I am not a Twitter follower but somebody sent me this, we had 164 users of Twitter so that means most of the attendees were twittering – I wasn’t one of them – and we had 591 reports but in the end we had over ¾ mill messages being read around the world. That was I think a pretty good outcome for the conference just knowing we were making so kind of connections. One of the great things that came out of the conference for me was the number of people that are interested in trying to make this kind of work happen and I think it does provide the opportunities for us to work together in an apolitical environment so we can freely talk about the biology and the requirements for conservation and so on. It is one of the things we are trying to have in CCAMLR for many years, a working group that would be able to deal with generally looking at these issues but that was never possible and so doing it externally is quite helpful.
Our journey at the conference was along four themes. The first theme was the MEASO itself, the assessment, but critically the – as you would have seen from the earlier slide – we had themes to talk about how do we get observations, sustained observations over time to better understand the dynamics of the system over time. How do we improve upon the responses of biota to change – they were two separate themes, and then we had a theme which was about the statistical and dynamic modelling we might to do facilitate assessments, not only assessments of change right now but also particularly assessments of change that we might foresee over the next 20 to 30 years. And in the middle we had a policy forum. The policy forum was important because it aimed to have end users and scientist be able to talk together about what their requirements were and the people that were invited to the policy forum weren’t there because of their organisational representation but more there because of the specific experiences that they might bring to the discussions. A lot of people were very appreciative of this opportunity. It doesn’t happen very often.
I am not going to go through these slides; they will be made available generally. What we also had an engagement of the association of Polar Early Career Scientists or APECS. We engaged APCES early on in the planning and we had a number of volunteers that would help with the organisation of the conference but we specifically had volunteers that help with the policy forum and with the four different themes. So they were providing summaries for us about what they thought were the important outcomes with respect to their themes. So they were listening around, talking around, and coming up with these summaries. What was really interesting is that – there is Alexa Hasselman here who did the Theme one on assessments;
we had Jilda Caccavo on responses,
we had Jennifer Freer on modelling and
then we had Juan Höfer on the observing systems. They came up with some interesting perspectives which weren’t the perspectives we would normally bring to these themes but clearly we could identify how they could see agendas for their future research on the back of what they were hearing what was most important. So they are going to form the corner stone for discussions about how we are going to maintain MEASO in the long term.
We are using the Southern Ocean Information Wiki – SOKi – to compile the information for MEASO and we are going to try and undertake the first MEASO over the course of this year.
So the requirements for a MEASO are firstly to identify the policy needs, and then what are the kinds of summaries that policy makers need not in general – this is on the left hand side – but also in specific components and how might we review and integrate the work. One of the other parts of the MEASO requirements is what additional work might there need to be in order to make the synthesis work in the end. So it’s not just reviewing what’s in the literature but it’s also instigating work to fulfil these needs. So our work program then is to do that work and the integration and any of the other work that we identify as important and then come up with a set of summaries - so the summaries of individual components – and they might be species, they might be physical parameters, and so on. We summarise those in terms of trends and then how do we synthesise that into those six dimensions or whatever dimensions we decide that – simple dimensions - that policy makers can understand, and we need to deliver that. The dashed line is a very important line. In the early parts of the discussions, we were discussing what would be the level of the assessment. And there was one definition which was being brought to the discussion which was an assessment which was the equivalent of how well are the policy makers and the different forums doing in terms of management and their uptake of science at a very high level. In the original foundation of MEASO discussions assessment was meant to mean estimation like a stock assessment. Can we start to estimate these things and can we deliver that to policy? And it became very clear from some of our scientists from around the world that there are some countries where they can’t step into the policy domain. There is a point to which they will engage but as soon as we start having an orientation which is specifically around the policy outcomes that should arise from the science they now withdraw. In order to get the scientific consensus, in other words that we don’t have another body here giving a different view of the science of change, status and trends, in order to have consensus across all the bodies we need to make sure that all bodies are able to engage, and we don’t exclude bodies that could then cause a confrontation later and the policy makers have to choose between the science. Bill can tell you many stories about when that happens – and it happened in CCAMLR for the first ten years – when that happens you make no progress because the science gets ignored. So how can we make sure that the scientists aren’t ignored? We need to build our consensus around that. So that dashed line is very important and we’re feeling our way as to where that actually resides. But I would suggest that it falls short of being able to advise the policy makers that they are falling short of their objectives.
So what’s our proposed time table for this year is that we need to develop our summaries of the data we have. That is already underway. One of the good things about MEASO was that there is recognition that this is a good next step after SCAR’s biogeographic atlas of the Southern Ocean. That went part way to where they wanted to go and the MEASO will go that extra step and will form a strong foundation for the Antarctic climate change and environment report which is managed by SCAR and it’s intended that this work will be the marine ecosystem component of that report. In October we’ll do a report for the Scientific Committee of CAMLR and hopefully get some feedback as to whether or not they find it useful and then we’ll go through a review process in November, so that is external review, peer review, and then revise and hopefully publish it in March next year in time for the assessment review number six of the IPCC.
So you’re not going to hear the animation on the right but that’s okay. Just coming back to where we are, we need to make sure that our science that delivers into policy has consensus so that it’s then not the policy makers that are choosing between the science. And it is up to us, I think, to put forward as best as we can the estimates of change in habitat species and the system as a whole and we give an idea about those uncertainties that can then form a strong basis for consensus in policy. We need to be able to communicate this in the best way. Lisa Roberts has been an associate of the Antarctic Division for many years, has been doing art work in one form or another and she does terrific graphics, graphic design, to help communicate very complex science. We certainly encourage more artists and communicators to get involved with this process. So at that point perhaps, if we ask questions, there is Rowan and Jess is here to also answer questions, and if you would like to participate in MEASO, there are many things that can be done. The aim is that a lot of people do a little, not a few people do a lot and the aim for it is to be ongoing. It is not just something that will happen every seven years; it is as we can update assessments, we will and it’s only every six or seven years in a cycle that we would then update the summaries for policy makers. Thank you!
Deep field ice core provides snapshot of Antarctic climate history
Deep field ice core provides snapshot of Antarctic climate history
Mount Brown South Field Leader, Sharon Labudda
Hi my name's Sharon Labudda and I am the Field Leader for the Mount Brown South camp, this year in 2017-18 season.
Mount Brown South Chief Investigator, Dr Tessa Vance
And my name's Dr. Tessa Vance and I'm the Chief Investigator for the Mount Brown South camp. We're drilling an ice core to 350 metres this year, which should give us a 1200 year climate history of the Indian Ocean.
Mount Brown South Field Leader, Sharon Labudda
My job is pretty much to look after everyone, keep everyone safe, make sure we get planes in and out, we get all the gear home, get the ice cores home safely. And yeah pretty much just look after everyone.
Mount Brown South Chief Investigator, Dr Tessa Vance
And my job to make sure that we achieve the science objectives for the
project, which is to get the ice core back home and analysed and make some cool science out of it. And also to hopefully keep some of the scientists in line, so Sharon doesn't have too hard a job.
Mount Brown South Field Leader, Dr Sharon Labudda
That'd be great (laughs).
Spying on penguins
Australian Antarctic Media Program open for applications
Anzac Day Casey research station 2018
Anzac Day Casey research station 2018
Casey Station Leader - Commander Rebecca Jeffcoat
On the 25th of April Australians and New Zealanders mark Anzac Day the anniversary of the 1915 landing of British-led troops at Gallipoli.
It's very special to me to be commemorating Anzac Day in Antarctica.
There's a great tradition of Antarctic explorers who have served in Defence Forces in times of conflict including Mawson and Wilkins and Hurley, and we'll remember those men today.
And in turn the qualities of Anzacs who served and who we remember today such as teamwork and mateship, courage, self-sacrifice and self-discipline.
They are all qualities that I see in the expeditioners who are with me in Antarctica at the moment and it's a great honour to be spending Anzac Day with those Australians and New Zealanders so far from home.