We are Canadian scientists using new techniques to transform how we monitor and protect our freshwater lakes. Ask us anything…
We are researchers at IISD Experimental Lakes Area (or IISD-ELA to its friends), which is one of the very few places in the world where you can conduct big experiments on whole lakes long term, and where we have tracked the health of fresh water—and a changing climate—for over 50 years.
Over the last decade, we have been transforming how we monitor the health of our lakes, to make the results more accurate and easier to obtain, with less of an impact on wildlife.
This ranges from innovating new sampling techniques that avoid sacrificing animals—like scraping the mucus off a fish, then placing it back in the lake, to understand its health—to placing sensors across our lakes so we can keep track of them, in real time, from the comfort of our desks.
We have also been working hard to make our unparalleled dataset on the health of our lakes more available to researchers and the public. Oh, and we are now working on using the DNA that animals shrug off and leave behind as they make their way through the environment in order to estimate populations.
All of what we discover in these 58 lakes (and their watersheds) in a remote part of Ontario up in Canada becomes data we are excited to share with the world, which then influences the polices that governments and industries across the globe implement to protect fresh water for future generations.
We (Sonya Havens, Chris Hay, Scott Higgins, Michael Paterson and Thomas Saleh) have learned so much over the last ten years, and now we want to share what we have learned with you.
So, ask us anything*
*within reason, of course!
My Proof: https://twitter.com/IISD_ELA/status/1618311471196418048
There are a few questions to consider here.
One of the core mandates of IISD Experimental Lakes Area is to undertake large scale experiments/research to provide guidance for science/evidence-based policies. There remain many issues that require this type of science, from climate change effects to potentially harmful pollutants. A main challenge for undertaking this research, for us and for our collaborators, is access to science funding to undertake this research. With recent investments by the Government of Canada in our facilities’ infrastructure, we are well positioned to support these large experiments.
When it comes to threats to lake health, we are relatively unaffected since the lakes we study are intentionally remote and relatively pristine —far enough away from human influence to escape many of the problems other lakes are facing (except climate change and pollution that reaches the lakes through the air). Having said all of that, when thinking more broadly about lakes around the world, we should remember that IISD-ELA was originally established to investigate what causes algal blooms. Algal blooms occur when too many nutrients enter a water body (eutrophication), which results in the excessive growth of algae. Research at IISD-ELA revealed that phosphorus, rather than nitrogen or carbon, was the primary nutrient responsible for algal blooms. However, controlling phosphorus entering our waterways proves to be a difficult and expensive endeavor, and algal blooms are still a major issue affecting many lakes around the world.
What is the most surprising change you've seen at ELA over the years?
One of the things that has really surprised us—for the better—was going from being a government facility to an independent not for profit.
We are now much more flexible to look at a much broader range of scientific questions, but we are no longer constrained by governmental mandates, and can respond to any environmental issue that we consider to be a threat to our freshwater supplies.
This also means we can work with a broader range of collaborators.
When we moved status, it was definitely a leap of faith. I am not sure many of us expected for us to do even better than we ever had over our first forty years, but here we are—collaborating with more partners, working on a broader range of issues, using new techniques, monitoring with higher resolution.
Are you doing any research with constructed floating wetlands for reduction of excess nutrients and algal blooms?
Our team is using constructed floating wetlands primarily to assess their ability to remove contaminants like oil after a spill. We are exploring the use of floating wetlands and associated microorganisms on their roots to enhance biodegradation of freshwater oil spills. Researchers are working to explore changes to the microbial community upon exposure to oil to see if there are organisms that can degrade oil compounds.
There has been some work done by one of our scientists, Richard Groshans, using constructed floating wetlands on one of our long-running whole lake experiments on algal blooms to see how much phosphorus (the key ingredient in algal blooms) they can remove from the lake, though I believe this work has not yet been published (https://www.iisd.org/articles/video/how-build-floating-wetland, https://www.iisd.org/publications/guide/floating-treatment-wetlands-keeping-our-fresh-water-clean-and-healthy ).
Richard has also done considerable research on the harvesting of emergent macrophytes from ephemeral wetlands as an energy source, which has the added benefit of removing nutrients
What are your fave lakes at ELA and why?
Chris: Lake 227 for being fairly symmetrical and bowl-shaped. The bathymetry map looks beautiful – available publicly and free here, in the “Current Maps” section of our larger bathymetry data package.
Thomas: The curtain experiment on Lake 226 was one of the most impactful early experiments at ELA. The hourglass shape of the lake makes for nice aerial photos!
Scott: Lake 227...to our knowledge it is the longest running whole lake experiment in the world....and still providing excellent policy relevant scientific outputs. We are also adding phosphorus to two new lakes (Lakes 303 and L304) and are turning bright green with algal blooms.
Sonya: Lake 227 is probably my favorite lake as well for the same reasons stated above. It’s the lake most researchers and students want to visit since they learn about it in university. However, it is also my least favorite lake from an analytical standpoint; since it is experimentally eutrophic, it has high nutrient concentrations, which means we have to dilute the samples to be within our analytical range.
Mike: I like Lake 979. It’s a beautiful, small, diverse wetland with a gorgeous waterfall at the far end. I started my research at ELA there, so I have many great memories of it.
What can actually learn from fish mucus?
Fish secrete compounds in their mucus, and when you scrape mucus off a fish, we can analyze it to discover a whole host of things about that fish. You can look at genes, proteins, metabolites and hormones! Using that you can tell if a fish is stressed in general or diving into specific genes what they might be stressed by.
Working with fish mucus is part of a much broader endeavor at IISD-ELA to use more non-lethal sampling methods when we are testing fish health and fish populations. This means we have much less of an impact on the fish populations as a whole and ensure we inflict minimal harm on the fish in our lakes.
Do you have an example of an experiment or project where a whole lake study revealed the opposite of what you initially hypothesized?
The results of many experiments at ELA differed considerably from what we expected.
For example, in the early eutrophication experiments at ELA, many scientists predicted carbon would limit algal blooms. Later, many scientists predicted that nitrogen would also limit algal growth. The results from Lake 227 and Lake 226 clearly showed that phosphorus was the most important nutrient driving algal blooms and that variations in carbon and nitrogen inputs did not affect the outcomes for these boreal lakes. These results provided critical information about which nutrients we need to focus our management efforts on. Like many experiments at ELA, they demonstrated that predictions based on small-scale studies often do not do well at the ecosystem scale.
When we set out to research on the impact that nanosilver (very small particles of silver, found in clothing or hygiene products), we expected a much greater impact on the overall ecosystem. We had been expecting the biggest impacts to affect the lower food web (bacteria and phytoplankton) but the only impacts we saw were to fish.
Why should I care about lakes?
We use lakes directly for many things and lakes are also indicators of the quality of our fresh water, without which we could not live. We need freshwater for drinking and for food production (crops, livestock, fish).
Degradations of water quality affect our health.
Fresh water is critical for many industrial processes. Many forms of energy production depend on freshwater (often by turning turbines with water – like dams or by boiling water – nuclear, coal power for example). We use freshwater for waste and sewage disposal. Freshwater is also widely used for recreation, from sailing to cottaging.
In a nutshell, fresh water is critical to almost everything we do.
What will be the biggest areas/trends to watch out for in 2023 and coming next 5/10 years?
Freshwater science is undergoing rapid changes that are associated with increases in technology. For example, data collection has traditionally been limited by logistical capacity— the ability to get to the research site (sometimes by boat or float plane) and return to the laboratory with a water sample. While these types of activities still occur, they are now increasingly supplemented by automated sensors that can connect to satellites. These sensors often collect data at much higher frequencies than traditional methods and they can be available in ‘real time’ for decision makers. An example of this is for drinking water facilities that now monitor source water for algal blooms or high levels of suspended particles in real time, which allows them to adjust their processes like the amount of chlorination required. The large increase in data from sensors will mean that science disciplines like Machine Learning and Artificial Intelligence will become increasingly important.
Although it might seem like a small thing, there have already been large improvements in the accessibility of data (open data) which have led to an upsurge in global analyses of freshwater (for example, how climate change is affecting the properties of lakes at a global scale). We expect this trend to continue. Some additional advancements in the past 10 years, like the ability to reliably measure environmental DNA, are increasingly being incorporated into research and monitoring and hold great promise for our discipline. It may be that the use of eDNA becomes commonplace to measure biodiversity and the abundance of species not only present currently, but also back in time (through the evaluation of eDNA in sedimentary records).
What is the thickest ice you've seen on ELA lakes?
We have monitored the ice thickness on our main reference lake (Lake 239) since 1969.
The maximum ice thickness we have found on this lake was 82 cm, found in March 15th, 1999 (we can easily check our PostgreSQL master database). Lake 239, like many boreal lakes is fairly small (approx. 50 hectares).
From 2016 to 2019 we also undertook a study in collaboration with Natural Resources Canada that used Ground Penetrating Radar to examine how lake ice thickness was influenced by lake size. In general, our results indicated that as lake size increases, so does the maximum thickness of the ice. The difference from the smallest lake (4 hectares) to the largest lake (2400 hectares) in our study was approximately 40 cm. The apparent cause of the difference was the amount of snow cover. Larger lakes have less accumulation of snow on them due to the higher windspeeds that pushed the snow to the lake edges. The lack of snow meant these lakes were less insulated from the cold air temperatures... and more ice developed.
placing sensors across our lakes so we can keep track of them, in real time, from the comfort of our desks
What kind of sensors are those?
As we speak, we are investing in a suite of sensors that provide high resolution data (several measurements are taken each day) for our lakes. Sensors include temperature strings that provide thermal stratification data; sensors that test for everything from temperature, conductivity, dissolved oxygen to algal pigments, dissolved organic matter; and many more.
In the upcoming year, we will be testing out a relatively new type of sensor that can measure concentrations of nutrients like nitrogen and phosphorus that promote algal blooms; for instance, Systea WIZ probes that provide ammonia, total nitrogen, total phosphorus, and total organic carbon data.
For about a decade, our team has also been implanting some fish with transmitters that allow our researchers to determine which habitats they use, and which they avoid during different parts of the season.
Until recently, all of these measurements were made manually—by going out onto the lake to take samples and using handheld sondes. In some cases, it has been possible to leave an automated sensor in the lake and return at a later date to collect the data.
However, these new networked instruments allow us to gather much more information and to view it in real-time from anywhere—even the comfort of our desks.
Do you have a data scientist/ data science team working in your project? If yes, what methods did they use to offset the negative effects of small samples when it comes to ML? (You mentioned that the data from the samples do not scale well on an ecosystem level)
Yes, we have a small team of data scientists working specifically on our database, in collaboration and consultation with our broader group of scientists.
Our comment about 'scaling' concerned the transfer of results obtained using small scale approaches such as tests conducted in test tubes, bottles, or small enclosures to entire ecosystems. These small-scale approaches are widely used because there is a high degree of control, they are inexpensive, and easier to replicate.
While these approaches have considerable value as exploratory tools, there are often problems extrapolating their results to natural ecosystems. This is because small scale systems lack important elements of natural ecosystems such as contact of water with lake sediments and the atmosphere or the influence of soils and vegetation that surrounds natural lakes and streams. Natural ecosystems are also subject to immigration and emigration of organisms from surrounding areas and it may take years for changes to take effect.
Most small-scale approaches are short-term and do not allow for these effects. This is why the ability to conduct whole-lake experiments at IISD-ELA is so important. Here, we can directly test the influence of human activities at the scale that usually is most important to society – the ecosystem.
It is true that machine learning requires large volumes of data. So the benefits of ML are constrained to the size of the datasets we are working with. Fortunately, we have been around for over 50 years and includes dozens of lakes, so we have lots of data to work with already. With that said, the newer sensors we are deploying now will be able to provide us with a higher volume and resolution of data than we’ve ever had before, and we are excited about the possibilities that machine learning offers to make sense of it all.
How would I apply for a research position with IISD?
Check out the 'employment' page on our website!
What is the solution to keep any lakes water clean,beside chemical use?
To develop solutions to environmental problems, we need to understand how human activities affect the environment, especially freshwater. This is where research at IISD Experimental Lakes Area comes in. We conduct whole ecosystem experiments (in a real lake) to determine what pollutants, and at what concentrations, have harmful impacts on freshwater systems.
This helps direct policy and technological innovation to mitigate the extent of the impact.
The classic example is phosphorus – IISD-ELA helped determine phosphorus was the limiting factor for causing harmful algal blooms. Before that, it was not clearly known which nutrient was the main driver. Once that was determined, governmental regulations were put in place around the world to limit phosphorus going into freshwaters (e.g., requiring soap ingredients to be changed).
This can take many forms in practice.
Wastewater treatment facilities capture and treat wastewater and stormwater from our cities and from our industrial water uses. Some treatment methods are chemical, but others are physical, leaving no trace in the water. Physical water treatment methods can include UV disinfection and dissolved air flotation.
Natural systems can also be used to improve water quality. Natural infrastructures such as wetlands and riparian buffers (conserved vegetation along riverbanks) can capture pollutants from urban and agricultural runoff and improve water quality. This is also important for many small ‘cottage’ lakes, where protection of shoreline riparian areas limits the quantity of pollutants that can enter the lake.
What threats act as obstacles to maintaining fresh water in the lakes you study?
The location of the Experimental Lakes Area was intentionally chosen in a remote location of Northwestern Ontario, where most human activities are limited. The remote location limits the number of stressors that threaten the water quality and biota of these lakes. At our lakes the two biggest threats are climate change and the long-range deposition of pollutants.
When it comes to lakes around the world more broadly, eutrophication and harmful algal blooms resulting from excessive nutrient inputs, in particular phosphorus. Algal blooms are the leading cause of the degradation of freshwater ecosystems globally, and they are very expensive to fix once they become a problem. The best approach is to determine which factors drive blooms and work to prevent those through policy (e.g., regulations on wastewater effluent, or runoff from agriculture).
There are also many potentially harmful chemicals in wastewaters, that derive from a growing list of chemicals that we, the public, use in our everyday lives. Some of these chemicals do not naturally break down and are potentially toxic to plants and animals. These chemicals include microplastics, mercury, road salt, plastics, and the chemical released during oil spills.
Habitat destruction from flow modification (dams, irrigation, etc.) also has an impact, as does the physical alteration of shorelines.
And, as always, invasive species (such as zebra mussels in Lake Winnipeg) pose a risk to our lakes worldwide.
It's a beautiful area. I heard a few years back that funding might be ending, has that been sorted out, or is it still precarious? I think long-term studies like these are incredibly important.
Mike: The Experimental Lakes Area was established as federal government facility in 1968, and was then operated by Fisheries & Oceans Canada. In 2012-2013, the Government of Canada announced its intention to close ELA but after a considerable public outcry, ELA was instead transferred to the International Institute for Sustainable Development (IISD) with financial support from the Government of Ontario. Shortly afterwards, the federal government re-instated funding for ELA and this support has grown even more in recent years. IISD-ELA is now an independent not-for-profit charitable organization.
With the transfer to IISD, the site has grown and we are able to do even more than we did in the past. We are no longer limited by the departmental mandate of Fisheries and Oceans Canada, and we are able to work on a broader range of issues with a wider range of partners and collaborators. In recent years, we have conducted experiments and research on many environmental problems including microplastics, oil spills, several different pharmaceuticals, climate change, harmful algal blooms, and the effects of fish harvesting, to name a few.
Throughout the years, we have managed to maintain our long-term dataset, which is an incredibly valuable resource. For some lakes, we have up to 54 years of data on water quality, hydrology, climate, and all the major components of the food web including algae, invertebrates, and fish. Researchers from all around the world contact us on a regular basis to benefit from this unparalleled dataset.
Very interesting but it just so happens that I can't think of anything important right now. A simple question would be what to do about the "forever" chemicals in freshwater lakes? I have read it in some science news article.
Forever chemicals are a very real and serious problem.
For example, there are recent news reports about high levels of chemicals referred to as PFAS (perfluoroalkyl and polyfluoroalkyl substances) in fish across the United States (and likely across Canada too) that are very concerning, especially those who consume freshwater fish.
For the immediate future, the public needs to know about this issue and be provided guidance (e.g., fish consumption advisories) for the level of risk associated with eating fish from different geographic areas. For Canada, this means we need much better data on the level of these PFAS chemicals in fish from lakes and rivers across the country, especially in areas where local communities rely on fishing as part of their culture or livelihood.
However, this is not enough. These results indicate much more effort needs to go into reducing the input of these chemicals into our lakes and rivers. This will likely require much stricter regulation of the use of such chemicals in thousands of products (from cell phones to non-stick frying pans, from cosmetics to fast-food wrappers).
Do you find any evidence of heavy metals in any of your lakes? If so, are these metals naturally occurring, or suspected to be unwanted man made pollution?
Measurable concentrations of heavy metals occur in all our lakes and are derived from both natural and human sources.
Of particular concern are fairly high levels of mercury in fish (a topic on which we have conducted a whole-lake research project) which is a common occurrence in unproductive lakes in northern and eastern Canada.
Much of this mercury (approximately 50%) is estimated to have been derived from human activities, especially the burning of coal. Most of the mercury travels in the atmosphere and is deposited on lakes and their surrounding watershed in rain and the sources may come from as far away as the Midwest USA or even Asia.
Little late to the party... We use thousands of tons of salt mines from enormous reserves 2000' below the great lakes. Dumpling this locally on all roadways. What effect does this have as it eventually makes its way to all our fresh water lakes? I often wonder, but guess that the elevation means it ultimately drains to the oceans and is replaced by fresh spring waters. Is there any concern here?
Mike: There is considerable concern about the potential effect of road salts on freshwaters and this is an active area of research. There is substantial evidence that salt levels are increasing in lakes and waterways near roads and that increases in salt concentrations are affecting biota, especially small invertebrates that are critical components of all aquatic food webs. The greatest problems often arise in the spring following snowmelt when salts accumulated over the winter are washed into streams and lakes.
What are your findings, if any, and comment on the amount of salt that is used in the various cities around the great lakes whose storm water drains into them, untreated?
Growing up in Toronto, insemento notice that far more salt seems to be used today than ever before. On roads but particularly in plazas and parking lots.
I know the volume of water in the great lakes is immense but i have to imagine this is having a measurable effect.
Mike: Our group has not done research on salinization (at least to date!) but other researchers have documented that levels of road salt application are increasing. In general, road salts are washed into storm drains and the water is not treated before it enters lakes and streams.
What are the biggest threats/challenges you see in your research?
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