|Feature Article - October 2019|
|by Do-While Jones|
From cold-blooded lizards to hot-blooded birds.
You can just imagine my joy when I saw an article titled, “The decoupled nature of basal metabolic rate and body temperature in endotherm evolution” in the journal, Nature. Well, maybe you can’t imagine my joy—so you will have to take my word for it. I was really excited!
The abstract of the article said,
The origins of endothermy [warm-bloodedness] in birds and mammals are important events in vertebrate evolution. Endotherms can maintain their body temperature (Tb) over a wide range of ambient temperatures primarily using the heat that is generated continuously by their high basal metabolic rate (BMR). There is also an important positive feedback loop as Tb influences BMR. Owing to this interplay between BMRs and Tb, many ecologists and evolutionary physiologists posit that the evolution of BMR and Tb must have been coupled during the radiation of endotherms, changing with similar trends. However, colder historical environments might have imposed strong selective pressures on BMR to compensate for increased rates of heat loss and to keep Tb constant. Thus, adaptation to cold ambient temperatures through increases in BMR could have decoupled BMR from Tb and caused different evolutionary routes to the modern diversity in these traits. Here we show that BMR and Tb were decoupled in approximately 90% of mammalian phylogenetic branches and 36% of avian phylogenetic branches. Mammalian BMRs evolved with rapid bursts but without a long-term directional trend, whereas Tb evolved mostly at a constant rate and towards colder bodies from a warmer-bodied common ancestor. Avian BMRs evolved predominantly at a constant rate and without a long-term directional trend, whereas Tb evolved with much greater rate heterogeneity and with adaptive evolution towards colder bodies. Furthermore, rapid shifts that lead to both increases and decreases in BMRs were linked to abrupt changes towards colder ambient temperatures—although only in mammals. Our results suggest that natural selection effectively exploited the diversity in mammalian BMRs under diverse, often-adverse historical thermal environments. 1
Their results are absolutely absurd. How do they know, “Mammalian BMRs evolved with rapid bursts,” but “Avian BMRs evolved predominantly at a constant rate?”
They claim to have discovered “an important positive feedback loop.” Temperature regulation is a negative feedback loop, so they clearly don’t understand anything about feedback loops, and their conclusions are ridiculous. However, it gives us an excuse to explain to you the difference between open-loop and closed-loop systems, the difference between positive and negative feedback, and why a cold-blooded creature could not evolve into a warm-blooded creature by natural selection.
The difference between an open-loop system and a closed-loop system is what makes a lawn sprinkler different from a toilet. Here in the Mojave Desert, if you want to have a lawn, you have to have an underground sprinkling system. You set the timer to turn the sprinkler on at a certain time, and then turn the sprinkler off after a certain amount of time. If you set the timer to water for 1 minute, then your lawn won’t get enough water, and the grass will die. If you set it to water for 1 hour, your lawn will get too much water, and the water police will give you a ticket. The trick is to set the timer to run long enough to give your lawn enough water to survive, but not so long that it wastes water. Since the timer has no way of knowing how hot it is, and how dry it is, the length of time the sprinkler runs is really just a guess.
If your toilet worked the same way, a timer would put a fixed amount of water in your toilet tank at specific times of day, regardless of how many times the toilet had been flushed.
The difference between a sprinkler system and a toilet is feedback. The float in the toilet tank tells the valve when it needs to turn on and off. The control loop is “closed” because the command goes out and a sensor feeds back status information to the controller, closing the loop. The lawn sprinkler gets no feedback as to how much water is needed. The control loop is “open” because there isn’t a complete circle. The command goes out, but no status information comes back.
The problem with a closed-loop system is that it can become unstable. For example, driving a car is a closed-loop system. You turn the steering wheel, see where the car goes, and make corrections based on the visual feedback. Suppose your car starts to drift off to the right. You turn left a little bit; but if you turn left too much, the car starts to go toward the left lane. Then, if you then turn the wheel back to the right and over-correct, the car veers right too much, and rolls the car over, into a ditch. The car became unstable.
There are two things that determine if a closed-loop system is stable. They are gain margin and phase margin. In the hypothetical example above, the car rolled because of improper gain and phase. You turned the wheel too far to the left or right. There was too much amplitude (gain) in your response. You exceeded the gain margin of a stable system. You also turned the steering wheel too late, so the phase lag exceeded the phase margin. In real life, you can keep the car on the road because you don’t turn too much, and realize when you need to turn quickly enough. You stay safely below the gain and phase margins.
Once upon a time, designing a stable control system was an art. Then, in 1932, Harry Nyquist discovered some stability criteria which turned that art into a science. 2 That science is now a required part of every college engineering curriculum. I hated taking the Linear Control Systems course in college because it is really hard to design a stable control system. When I graduated, I wound up having to design an incredibly fast and accurate control system for the AIM-95 Agile missile, and I needed everything I learned in that class (and more) to do it.
I began this essay by asking you to imagine how excited I was to read an article about metabolic control systems. That’s because, although I hated control systems in college, my experience with the Agile missile deepened my appreciation for how carefully a closed-loop system has to be designed. It became my area of expertise. I presented a paper titled “Linear Control System Pitfalls” 3 at the Fifth Annual Embedded Systems Conference, in 1993. It was so well received that it was published in Embedded Systems Programming magazine 4 the next month, and I was asked to present the paper again at the next three Embedded Systems Conferences. The point of bragging about this is that I know a lot about designing closed-loop control systems in analog and digital systems, which makes me qualified to discuss biological closed-loop temperature control systems.
In common speech, “positive” usually means good, and “negative” means bad—but not always. In control systems, positive feedback is as bad as testing positive for cancer. At some time in your life you no doubt have been in an auditorium and heard an ear-piercing squeal which was caused by positive feedback. The microphone heard a faint noise. The amplifier made it louder. The speaker reproduced the sound. The microphone heard the louder sound. The amplifier amplified it even more, and so on until the amplifier maxed out. It was a closed-loop (microphone to amplifier to speaker to microphone) with positive feedback which caused the system to go unstable. The gain exceeded the gain margin. The fix was to turn the volume control down.
The statement, “There is also an important positive feedback loop as Tb influences BMR,” showed right off the bat that the authors of that article had no clue as to what they were talking about. If body temperature (Tb) had a positive influence on basal metabolic rate (BMR), then the warmer a bird got, the more internal heat it would produce, which would make the bird warmer, which would make it produce more internal heat, and so on, until it cooked itself.
The title of the article said it was about the “decoupled nature of basal metabolic rate and body temperature.” “Decoupled” means “not connected.” The article title claims there is no connection between metabolic rate and body temperature, making it an open-loop system which has no feedback at all. That’s really ridiculous. If you get cold, your metabolic rate goes up to warm you up. If you get too hot, you sweat to cool down. Your body temperature is coupled to your metabolism.
The statement, “adaptation to cold ambient temperatures through increases in BMR could have decoupled BMR from Tb and caused different evolutionary routes to the modern diversity in these traits” makes no sense at all. If, as they claim, cold temperatures caused an increased metabolism to evolve through any route, the two are definitely coupled!
You don’t need to be much of a scientist to have observed that warm-blooded creatures have a closed-loop temperature control system which uses negative feedback to maintain a stable body temperature. This brings us to these important questions: “What are the necessary components of a closed-loop temperature control system, how did those parts originate, and how did they become coupled to create a functional system?”
Here is the amusing beginning of their explanation:
Phylogenetic statistical methods provide us with the opportunity to formally test whether BMR has been linked to Tb or ambient temperature (Ta) throughout the evolution of birds and mammals. By accommodating for and identifying heterogeneity in the rate of phenotypic evolution, these methods can detect and reconstruct accurate historical evolutionary processes. Evaluation of the evolutionary coupling between BMR and Tb has direct consequences for several longstanding ecological and evolutionary theories (including the metabolic theory of ecology) that assume coupling between BMR and Tb.
We first quantified and compared rates of evolution for BMR and Tb along each branch of the time-calibrated phylogenetic trees of birds and mammals (hereafter, branch-wise rates (r)). r is a rate scalar by which the background rate of evolution (σ2b) is multiplied to increase or decrease the pace of evolution; it measures how fast a trait evolved along an individual phylogenetic branch. 5
That is complete nonsense! There are no “accurate historical evolutionary processes.” In order to quantify and compare rates of evolution, you have to measure the rates of evolution. Where did they get the “rates of evolution for BMR and Tb along each branch of the time-calibrated phylogenetic trees of birds and mammals?” You have to skip down to the last two sentences of the report to get the biggest laugh of all.
No new data were generated for this study. The data used for this paper are available from the original sources cited in the Methods and Supplementary Information. 6
They didn’t measure any evolution at all! They just took some previously reported results and did some bogus analysis of them. There are no real “time-calibrated phylogenetic trees of birds and mammals” which show the rates of evolution. There are just stories that evolutionists have made up and published.
If BMR and Tb were coupled during the evolution of endotherms, the amount of change along phylogenetic branches for both traits should be positively associated—in cases in which rBMR is high, we expect it to be high for rTbrTb (Fig. 1 b). We tested this prediction against alternative evolutionary scenarios. First, we cannot make any inferences about coupling or decoupling in cases in which there is no rate heterogeneity for both BMR and Tb (r = 1 for all branches in the tree for both traits) (Fig. 1a). Second, we infer decoupled evolution if both traits show rate heterogeneity, for which the magnitudes of r values are negatively correlated (that is, branches that evolve at a high rate for BMR but a low rate for Tb, and vice versa) (Fig. 1c). We suggest this scenario indicates decoupled evolution because a negative correlation most probably indicates that one trait tends to be conserved while the other evolved rapidly. Third, we infer decoupled evolution if only one trait shows rate heterogeneity while the other evolved at a constant rate (Fig. 1d, e) or if both traits show heterogeneity but the branch-wise rates are not associated (Fig. 1f). 7
Here’s what they said in plain English: “No rate heterogeneity” means there was no difference in the rates of evolution because the rates were the same. If the rates of evolution were the same, they say they could not make any inferences about any connection. If two things increase at the same rate, or decrease at the same rate, one might reasonably infer some sort of connection—but, unexplainably, they could not.
Second, in cases where one increased while the other decreased, they inferred that there was no connection. That is like saying, when the number of police officers in a neighborhood is increased, and the crime in that neighborhood decreases, there is no logical connection.
Third, in cases where the evolutionary rates were different, they assumed there was no connection. That isn’t an unreasonable conclusion—but it isn’t necessarily correct, either.
No matter what happened, they inferred no connection. If they both increased at the same rate, there was no connection. If they both decreased at the same rate, there was no connection. If one increased while the other decreased, there was no connection. If one changed while the other stayed the same, there was no connection. What’s left? What set of conditions would have led them to the conclusion that there is a connection between body temperature and metabolism? They covered every possible scenario, and every one led to the same stupid conclusion.
The body of the report was filled with absurd data like this:
When the branch-wise rates for BMR and Tb were compared, we found that in mammals both traits evolved at a constant rate in 10.6% of branches (Fig. 3a, consistent with Fig. 1a). In 60.2% of branches, only one trait evolved at faster rates while the other trait diverged at a constant rate. This indicates that BMR and Tb evolved in a decoupled manner along these branches (Fig. 3a, consistent with Fig. 1d, e). 8
There’s no real data here. How do they know that in 10.6% of all branches of mammals, body temperature evolved at a constant rate? How do they know that in 60.2% of all branches of mammals, body temperature and metabolism evolved at different rates? They didn’t measure the body temperatures of extinct elephants and compare those temperatures to modern elephant temperatures, and neither did the researchers who published the data they used.
We’ve spent enough time on this stupid letter to Nature, which somehow managed to pass a peer review. Let’s take our own reasonable look at the problem.
Let’s start with cold-blooded animals.
Reptiles, such as lizards and snakes, are cold-blooded. They have no internal mechanism for regulating their body temperature. They have to bask in the sun to warm up, or seek shade or a hole to cool down. This means that conscious thought is involved. The reptile has to realize that it is too cold, and move its body into the sun, or it has to realize that it is too hot, and find shade.
Just think about all that involves. The reptile needs a temperature sensor. The reptile needs a brain that knows what the ideal temperature is. The reptile needs to process the data from its temperature sensor and determine if it is too hot or too cold. The reptile needs to know that it is warm in the sunlight and cool in the shade. The reptile then needs to decide where to go and how to get there.
If you want to win first prize at a science fair, design a Lego robot which moves (on uneven terrain) closer to, or farther from, a lamp to keep itself at 98.6 degrees. If you can’t do it on purpose, just write some random instructions and hope that it works!
Now, let’s consider warm-blooded animals.
The temperature regulation in warm-blooded mammals and birds is slightly different from cold-blooded reptiles. They still need a temperature sensor to determine body temperature—but the conscious part of the brain isn’t necessarily involved. Mammals and birds might realize they are cold and move to a warmer place—but even if they don’t do anything consciously to solve the problem, subconsciously, they change their metabolism to generate heat internally. If you are hot, you might choose to take a dip in a pool; but if that isn’t an option you just have to sweat it out—and you will, automatically. Subconsciously, sweat glands will produce moisture which cools your body as it evaporates.
For a cold-blooded reptile to evolve into a warm-blooded mammal, sweat glands must evolve from nothing by chance. Then, the brain has to evolve a closed-loop control system algorithm which will make the mammal sweat just enough to cool off when it is too hot. If it is too cold, a warm-blooded creature’s temperature control algorithm needs to burn enough calories to warm up, without overheating.
Try to imagine what a biological temperature control system needs to function. There must be multiple sensors to regulate the temperature in all parts of the body—otherwise it would be like my furnace (which keeps the hall much too warm even though the bedroom is too cold). There are different ways animals control temperature. Birds don’t cool their bodies by pumping more blood through their ears (like elephants do). Hormones must be involved in humans because women sometimes complain about hot and cold flashes (which is evidence that their temperature control system becomes underdamped as they age).
The point is that closed-loop control systems, from air conditioners to automobile cruise controls to missile guidance systems are notoriously hard to design. You even have to set the float in your toilet tank correctly to make your toilet function properly. For a cold-blooded reptile to accidentally evolve an endothermic metabolism which is controlled by an algorithm that just happens to write itself in the subconscious part of the brain is just nonsense.
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Jorge Avaria-Llautureo, et al., Nature, 29 August 2019, “The decoupled nature of basal metabolic rate and body temperature in endotherm evolution”, pp. 651-654, https://www.nature.com/articles/s41586-019-1476-9
3 Do-While Jones, Fifth Annual Embedded Systems Conference, October 5-8 1993, "Linear Control System Pitfalls"
4 Do-While Jones, Embedded Systems Programming, November 1993, "Avoiding Control System Pitfalls"
5 Jorge Avaria-Llautureo, et al., Nature, 29 August 2019, “The decoupled nature of basal metabolic rate and body temperature in endotherm evolution”, pp. 651-654, https://www.nature.com/articles/s41586-019-1476-9