[00:00] Chapter 1: The Measurement Paradox
What if I told you that the most widely used measurement for assessing lake health is not only inaccurate—but gets more inaccurate precisely when your lake is in the most danger?
What if the monitoring system being used to protect your lake from toxic blooms is actually blind to them?
And what if I told you this isn’t speculation – it’s been proven and confirmed by the EPA’s own scientists using a decade of data from the Great Lakes?
I’m Dave Shackleton. For years, communities have been spending millions on lake management, guided by reports that tell them everything is under control. But their lakes keep getting worse and more and more people are asking why.
I’ve spoken about the importance of measuring what matters in previous videos and said that chlorophyll-a is a misleading metric. We’ve had a tremendous response – many of you asking for more detail, wanting to understand more about the science behind it. This video is for you.
So today, we’re going to simplify the science behind measuring chlorophyll-a, show you why it’s dangerously misleading.
[01:21] Chapter 2: The Flawed History of the Trophic State Index
So, what is chlorophyll-a? Simply put, it’s the green pigment found in all plants and algae. Think of it as nature’s solar panel – it’s the engine that captures sunlight and converts it to energy through photosynthesis.
About sixty years ago, in the 1960s when scientists first started studying the process of eutrophication – the process that degrades our lakes, they noticed a simple correlation: more nutrients like phosphorus led to more algae, which meant more chlorophyll-a. It was a logical connection. So if you measure chlorophyll-a you get a quick and easy measurement of algae.
That logic led to the creation of the Trophic State Index, or TSI. It was a simple way to categorize how eutrophic a lake was – measure three things—total phosphorus, water clarity, and chlorophyll-a as a proxy measure for algae – and you get a score that tells you where your lake stands. For its time, this was good science.
The problem isn’t that the original science was bad. The problem is that our understanding of eutrophication has changed dramatically since then, but the way we measure lakes hasn’t. The Trophic State Index was built on a fundamental assumption: that for monitoring purposes, all phytoplankton are basically the same and measuring chlorophyll-a measured all phytoplankton.
As we’re about to see, that assumption is fatally flawed.
[03:05] Chapter 3: Algae vs. Toxic Cyanobacteria
About ten years after the TSI was developed, a mystery emerged. Veterinarians started reporting that animals were being found dead around farm ponds and watering holes that were full of bright green algae.
That was a puzzle, because we know that algae cannot produce toxins. But then came the breakthrough. In the 1980s, Professor Wayne Carmichael discovered it wasn’t algae killing the animals – it was a completely different type of phytoplankton called cyanobacteria.
Here’s the difference. Cyanobacteria are ancient bacteria that learned to photosynthesize, but some of them retained the ability that pathogenic bacteria have to produce potent toxins. Algae, on the other hand, are more evolved, and are the precursors to all the plants we have on Earth today, and they cannot produce toxins.
So when I say our understanding of eutrophication has changed dramatically, I mean this: It’s no longer just about aesthetics – reduced water clarity from too much algae. Professor Carmichael showed us that the eutrophication process continues beyond that point and becomes a public health threat – a toxic takeover that could shut down your lake, kill your pets, and threaten your drinking water supply.
This should have triggered a complete overhaul of how we monitor our lakes. But it didn’t. We kept using the same old tools, designed for a different, non-toxic problem.
And we are paying the price for that now.
[06:53] Chapter 5: The Fluorometer Failure (The Traffic Analogy)
So that is the first part of the measurement problem if you are relying on chlorophyll-a to understand what is happening with the phytoplankton in your lake.
Here’s the second measurement problem. The fluorometers used to measure chlorophyll-a are tuned to its specific fluorescence wavelengths. But those other pigments in cyanobacteria interfere with the signal, causing the instrument to under-read the amount of chlorophyll-a that’s actually there.
Imagine if you invented a device in the 1960s that measured the level of noise from a gasoline engine to calculate the volume of traffic on a highway.
And for years it worked so well that it was adopted as the standard for measuring highway traffic.
Then someone invents electric cars, and they make a different noise to a gasoline engine and your device doesn’t detect that noise.
So what happens?
At first your device doesn’t detect the increase in traffic volumes on the highway even though there are more vehicles on the road. That’s bad enough, if your job is to manage road infrastructure and traffic flow.
But as the number of electric cars on the roads continues to go up, your device starts to report that there’s less traffic on the road. And the bigger the proportion of electric cars on the road the bigger the error.
If you ever got to 100% electric cars on the road your device is going to tell you there’s no traffic – nobody ever uses that road anymore.
Your device is actually blind to the increase in the number of cars and the type of cars on the road.
You’re missing a huge part of the picture. And you are going to make some really bad decisions.
Well that is a pretty good analogy for what has been happening for people who rely on measuring chlorophyll-a to understand what is happening with the phytoplankton in their lake.
[09:01] Chapter 6: Real-World Examples of Flawed Lake Reports
This creates a dangerous and deeply ironic paradox. As a lake gets worse – as beneficial algae die off and are replaced by toxic cyanobacteria – the chlorophyll-a readings may stay the same or may actually go down. A lake manager looking at that report would think, “Great! Everything is under control” But in reality, the lake is collapsing into a toxic state.
Here are two examples of where we have seen exactly that error has been made.
Indian Hills Lake in Missouri was monitored by the Statewide Lake Assessment Program for over 40 years.
By 2020 the residents knew their lake was in a bad state, but the head of the State program stated “From 1978 to 2020 there was no long-term trend in Chlorophyll-a concentrations (a proxy for phytoplankton biomass), Secchi disk depth (a proxy for water transparency), Total Phosphorus (TP), . . . . the lake was not getting worse in terms of water quality – it was staying the same.”
Yet in 2020 toxin tests were done and every single kind of cyanotoxin was found in the lake in virtually every single test done.
In 2021 the lake committee got serious – they began doing detailed phytoplankton analysis and over 33 different samples – throughout the summer of 2021 not one single sample showed one single cell of phytoplankton that wasn’t toxic cyanobacteria.
If you are relying on chlorophyll-a you are flying blind.
Another lake was shut down because of toxic HABs for 4 out of 5 years in a row. So they applied for a permit to remediate the lake and prevent HABs, and to get the permit they had to measure chlorophyll-a for a year to prove that the lake had a problem that needed to be fixed.
A review of the permit application stated “The water quality numbers on this lake are interesting. . . . the levels of chlorophyll-a they measured were relatively low and put this lake in a mesotrophic category. This is strange since the main complaint is harmful algae blooms – you’d expect high chlorophyll-a levels.”
No you wouldn’t! – and its that level of confusion that is at the heart of the problem.
[11:45] Chapter 7: The EPA Study Proves the Flaw
Now, you might be thinking, “This guy sounds like he is talking sense, but is there independent scientific proof?”
Absolutely! And it comes from the most authoritative source possible.
In January 2026, a group of EPA-affiliated and funded scientists published a landmark paper in the journal Limnology and Oceanography: Methods. They analyzed ten years of data from 72 monitoring stations across all five Great Lakes – 978 samples in total – comparing fluorometer readings to actual microscopy-based identification of exactly what phytoplankton were present and in what quantities.
What they found was unequivocal.
Now scientists have known for a while that fluorometers are not particularly reliable and chlorophyll-a is not a reliable metric – and so have the manufacturers of these devices. They know about the flaws I’ve told you about so they have made every effort to try to develop more sophisticated equipment to overcome these limitations.
So for this study they used one of the most sophisticated fluorometers – a multi-wavelength fluorometer that uses 5 different detectors at five different wavelengths to detect different phytoplankton groups. It has a dedicated cyanobacteria channel. It tries to to specifically detect phycocyanin fluorescence.
So if this sophisticated technology – specifically designed to detect cyanobacteria – fails… what chance do simple chlorophyll-a probes have? Keep that question in mind as we look at the data.
Before we look at the data let me try to give you a simple easy to understand explanation of what these charts aim to show.
So the study is looking to see what correlation there is between measuring chlorophyll-a with a fluorometer to estimate the phytoplankton and actually looking at a sample under a microscope to see the true situation so that we can understand whether these fluorometers give meaningful information.
So you end up with a chart like this – on the X axis, along the horizontal you put the true measured biovolume of a sample, and on the Y axis – the vertical you put what the fluorometer reading was.
So if you had 100% correlation, every dot would sit right on this diagonal line. Fluorometer says this, microscopy says this. Fluorometer says this, microscopy says this. Perfect agreement and accurate, meaningful information from the fluorometer.
But if the fluorometer says this when microscopy says it is actually this—or says this when the microscopy say this—the dots scatter all over the place. Low correlation. Unreliable.
In statistics, we use something called an R-squared value to measure how well two things correlate. An R-squared of 1.0 means perfect 100% correlation. An R-squared near zero means no correlation at all – you’d be much better off flipping a coin, taking a wild guess or just making something up.
Now let me walk you through their four key findings.
[15:33] Chapter 8: Finding #1 – Blind to Cyanobacteria
First, they found that fluorescence-based measurements systematically fail to detect cyanobacteria.
So here’s the chart showing the correlation between what the probe said and what the true value was.
The chart is a little bit difficult to see, but the light blue dots show springtime readings and the darker dots are summer.
This would be the 100% correlation line.
Here is the correlation line for the springtime data.
And here is the correlation line for the summer data.
Nowhere near the 45 degree line you would see if correlation was good and the fluorometer readings were meaningful.
Basically – if the real amount is low, the fluorometer says low, but if the real amount is high, the fluorometer still says low. All the dots are clustered along the bottom here – where the fluorometer readings are low regardless of the true situation. It is blind to the cyanobacteria.
In fact for cyanobacteria, the R-squared was .06. That means the measurement could explain only 6% of the variation in cyanobacteria biovolume. The other 94%? Unexplained. Undetected. The measurement does not detect actual cyanobacteria levels.
The authors put it politely: “Only weak correlations were observed for cyanobacteria.”
Think about that. The very organisms responsible for toxic blooms—the ones that can shut down your lake, kill your pets, contaminate your drinking water—are essentially invisible to the monitoring system we’re using to try to track them.
[17:38] Chapter 9: Finding #2 – Failing When You Need It Most
But here’s where it gets truly alarming. The failure isn’t uniform. It gets worse precisely as the danger is rises—during high-density toxic blooms.
Listen to this finding carefully. In half of the samples where microscopy detected the highest cyanobacteria concentrations, meaning significant blooms, the fluorometer registered a median reading of 0.01 micrograms per liter.
Look at this cluster of dots in the bottom-right part of the chart. Microscopy detected cyanobacteria at levels of 6, 7, 8 – these are massive blooms. But the fluoroprobe readings are all stuck down here at 0.01. Essentially zero.
High actual concentrations. Near-zero readings or detection. The equipment is blind when you need it most.
Let me say that again. In 50% of the samples with the highest bloom concentrations, the monitoring equipment said there was almost nothing there.
Imagine a smoke detector that works great and does nothing when there’s no fire, but also stays silent and does nothing when your house is actually burning. That’s what we’re dealing with.
This isn’t just inaccurate. It’s catastrophically misleading. A lake could be experiencing a severe toxic bloom while the monitoring system reports safe conditions.
And the fact of the matter is – on most American lakes it’s only when we visually see a bloom that we test for toxins to confirm it’s too late – a toxic takeover has occurred, the water is toxic, shut the lake down.
[19:39] Chapter 10: Finding #3 – Biased Toward Good News
Now, you might be thinking, “Maybe fluorometers just don’t work very well in general?”
That’s no true. And this is the third critical finding. The technology works perfectly fine – for other types of phytoplankton.
Here is the chart for diatoms, which are a type of beneficial algae. You can see the dots form a clear diagonal pattern—low on the left, high on the right. The fluorometer is giving a much more accurate representation of what’s there.
Here is the lighter colored springtime correlation line – pretty good. Not so good in summer, but for diatoms the R-squared was 0.65. That’s a strong, pretty reliable correlation.
Now, the summer dots are a bit more scattered than spring—that’s because summer communities are more complex – but 65% correlation certainly beats 6% for cyanobacteria and that chronic blind spot.
But here’s what makes this even more dangerous. The fluorometer accurately measures the beneficial algae – in this case the diatoms. But it’s blind to the toxic cyanobacteria.
So when you look at your monitoring data, you’re seeing all of the good and almost none of the bad.
It’s like having security cameras that clearly show everyone entering the front of your building but fail to record anyone sneaking out through the back door. You think you know who’s coming and going, but you’re only seeing half the picture—and it’s the half that makes everything look fine.
The measurement isn’t just inaccurate. It’s systematically biased toward good news. In relative terms, it overrepresents the beneficial algae and underrepresents the toxic cyanobacteria. So the lake is reported to be healthier than it actually is.
So the technology isn’t flawed. The problem is that we’re using a tool designed to measure one thing – chlorophyll-rich algae – and expecting it to accurately measure something fundamentally different – toxic cyanobacteria.
It’s like trying to use a metal detector to find plastic. The metal detector works great for coins and jewelry. But if you’re looking for plastic bottles or credit cards, it’s the wrong tool. That doesn’t mean the metal detector is broken it means you’re using it for the wrong job.
[20:18] Chapter 11: Finding #4 – Urgent Public Health Warning
The fourth finding is really a warning. The authors – who, remember, include EPA-affiliated and funded scientists – explicitly call out the danger of what’s happening all across the country right now.
They wrote: “The similarly low correlation between the two approaches observed for cyanobacteria in the current study is particularly consequential because field fluorometry has been increasingly used to monitor harmful phytoplankton blooms.”
Let me translate that from scientific language: We’ve proven that measuring chlorophyll-a with fluorometers doesn’t work for cyanobacteria. And the problem is that more and more agencies, consultants and lake management companies are using chlorophyll-a measurements in an attempt to monitor lake health and warn of impending toxic HAB events.
Everyone is making the same mistake.
The paper is a direct indictment of current monitoring protocols. It’s another call for a complete paradigm shift—away from relying on chlorophyll-a measurements, and the TSI – toward detailed, taxonomy-based assessments of phytoplankton demographics that can actually tell you what’s in your water and what your level of risk is.
This echoes exactly what the Government Accountability Office report said. The way we monitor lakes and reservoirs is misleading and blind to reality. The GAO told us we need to manage the risks associated with hypoxia and toxic harmful algal blooms. But what this research proves is that you cannot achieve that if you’re measuring chlorophyll-a as a key part of your lake management plan.
[24:17] Chapter 12: The Dog That Doesn’t Bark
There’s a famous Sherlock Holmes story where someone is killed at the dead of night at a place with a big aggressive guard dog. Holmes comments to the police detective on the case about “the curious incident of the dog in the night time”.
The detective says “the dog didn’t do anything that night” and Holmes says “That was the curious incident”
He solves the mystery by noting that the dog didn’t bark in the night. The dog should have barked at the intruder, but it didn’t. That silence told Holmes everything he needed to know – the intruder wasn’t a stranger to the dog.
Chlorophyll-a is our dog that isn’t barking.
The National Lake Assessment – the EPA’s comprehensive survey of lakes across America – showed that in 2017 they detected microcystin toxin in 20% of lakes. By 2022 that had gone up to 50%.
If chlorophyll-a was a reliable indicator of the cyanobacteria crisis, the National Lake Assessments show it should be going berserk barking at us all across the country. But it’s not.
And that silence should tell any thinking person that something is fundamentally wrong with the measurement.
The GAO figured it out. In less than 2 years they produced a report that said: What you are monitoring is not giving you any forward looking insight into HAB risk. That’s why you have to resort to testing for toxins after HABs occur and by then its too late. You have to change how you monitor our lakes.
[26:12] Chapter 13: The Algaecide Trap
The other point the GAO report made was that using algaecides just makes things worse and not enough attention has been paid to that either.
Now failing to detect the problem is one thing – being duped into actively making it worse is another.
Chlorophyll-a doesn’t just fail to detect the problem – too often it is used to actively justify practices that make it worse.
Chlorophyll-a levels are reported to be high, so your vendor says he’ll deal with it by applying algaecide. So he applies the algaecide and measures chlorophyll-a again and confirms that it has gone down because all the algae have been killed.
But scientific research has shown that algaecides are more effective against beneficial algae than cyanobacteria and that cyanobacteria recover faster and develop resistance.
So over time, as the phytoplankton recover from the algaecide, the proportion of cyanobacteria is higher, but the chlorophyll-a level is a little lower. So the vendor says “the algaecide is working, chlorophyll-a levels aren’t as high as before, I’ll apply some more and get things under control again” – so he does.
You can see where this is leading right?
The chlorophyll-a readings are suckering you into actively helping cyanobacteria take over by wiping out their competition with algaecides.
It’s the old algaecide trick or treatment question again. The magician distracts your attention by sleight of hand, look at how green the chlorophyll-a is – then he does his algaecide trick and wow – the chlorophyll-a has gone right down! Amazing, the water is blue again.
It’s a good trick. Until it isn’t – and then its too late.
[28:08] Chapter 14: How to Demand Better Monitoring
So the science is clear. The policy warnings from the GAO are clear.
For us, this isn’t new. The scientists who developed the technology that we use to eliminate hypoxia, prevent HABs and restore lake health realized all this over a decade ago.
That’s why the starting point is to Measure What Matters – there’s a link below for you to download an e-Book that explains it.
Now, there are people in the industry who’ve been doing things the same way for years – and I understand that. Change is difficult – people who’ve been doing things the same way for years and want to stick with what they know.
But as we’ve seen, and as these scientists who did the research and wrote this paper have shown – it’s what they don’t know that’s dangerous. It’s the dog that isn’t barking.
This scientific report from the EPA’s own researchers provides the conclusive, independent evidence that lake communities need to demand better monitoring from their vendors.
We’ve had several lake committees from around the country send us their annual management plans for us to review for them – and what we’re seeing is concerning – communities paying a lot of money to get a completely flawed picture of their lake’s health —and often paying for treatments that are actually making things worse.
So if you are on a lake committee, and your annual report is focused on the Trophic State Index and a chlorophyll-a – you are not getting the full picture. You need to ask your consultant, “Please can you provide a taxonomic and biovolume analysis of our phytoplankton?” If they can’t, or won’t, you need to find someone who can.
If you want to learn more about what to measure to really understand what is happening with the phytoplankton in your lake we have a video dedicated to explaining that called “Is Chlorophyll-a Lying About Your Lake”, if you click on the thumbnail up here, you can watch that next.
I hope this has answered your questions and provided the proof you need to demand change.
There’s a link below if you have questions that you would like us to answer in one of our videos.
There’s a lot more to come, so if you found this useful, hit subscribe—that way you’ll be notified when we upload the next video. Share this video if you know someone else who would find it useful, and give us a like, because YouTube likes that.
lake management, cyanobacteria, harmful algal blooms, HABs, water quality, chlorophyll a, trophic state index, eutrophication, lake restoration, EPA study, algae vs cyanobacteria, lake toxins, environmental science, lake health
