My understanding is that heritability is a measure of predictive ability. Meaning if a trait is 80% heritable and you want to guess whether or not Bob has that trait then you’ll be 80% more accurate if you know whether or not Bob’s parents have the trait than if you didn’t have that information. Likewise, for a very low heritability trait like having 2 legs, knowing whether or not Bob’s parents have two legs doesn’t improve your guess much if it improves it at all.
As you mentioned, environmental factors can at times subsume the genetic factors (e.g. heritability of height can be subsumed with very low nutrition). So if environmental factors for the dataset that you’re trying to predict from are significantly different from the factors which you used to determine heritability, then the heritability estimate may not be as accurate and it should be reassessed for the different factors.
You can still make very concrete predictions about traits based on heritability even though very different environmental circumstances could reduce how heritable the trait is. Heritability of IQ has been determined in an environment exceedingly similar to that faced by kids in the modern schooling system. Let’s say IQ has shown to be 80% heritable in circumstances not dissimilar to the US school system (as far as I am aware this is the current state of the art). Now if you want to predict the IQ of 20,000 parents of 10,000 US schoolchildren you’ll do 80% better if you know the kids IQ than if you were just guessing randomly. Similarly, if you know Bob is smart you should update your prior estimate that Bob’s parents are also smart significantly in favor of their intelligence.
if a trait is 80% heritable and you want to guess whether or not Bob has that trait then you’ll be 80% more accurate if you know whether or not Bob’s parents have the trait than if you didn’t have that information.
I think this is more or less correct for narrow-sense heritability (most commonly used when breeding animals) but not quite right for broad-sense heritability (most commonly used with humans). If you’re talking about broad-sense heritability, the problem is that you’d need to know not just if the parents have the trait, but also which genes Bob got or not from each parent, as well as the effect of dominant genes, epistatic interactions, etc.
Assuming you’re talking about broad-sense heritability, I think a better way of looking at it would be to say that you’ll be 80% more accurate if Bob has an identical twin raised by a random family and you know if that twin had the trait. This isn’t quite right either, but I think it’s valid if you assume that phenotypic traits are the sum of genetic effects and environmental effects and also that genetic effects are independent of environmental effects.
Of course, few people have identical twins raised by random families, and most phenotypes probably aren’t additive in genetic and environmental effects, and those effects probably aren’t independent! Which… is a lot of caveats if you want to know practical applications of heritability numbers.
My understanding is that heritability is a measure of predictive ability. Meaning if a trait is 80% heritable and you want to guess whether or not Bob has that trait then you’ll be 80% more accurate if you know whether or not Bob’s parents have the trait than if you didn’t have that information. Likewise, for a very low heritability trait like having 2 legs, knowing whether or not Bob’s parents have two legs doesn’t improve your guess much if it improves it at all.
As you mentioned, environmental factors can at times subsume the genetic factors (e.g. heritability of height can be subsumed with very low nutrition). So if environmental factors for the dataset that you’re trying to predict from are significantly different from the factors which you used to determine heritability, then the heritability estimate may not be as accurate and it should be reassessed for the different factors.
You can still make very concrete predictions about traits based on heritability even though very different environmental circumstances could reduce how heritable the trait is. Heritability of IQ has been determined in an environment exceedingly similar to that faced by kids in the modern schooling system. Let’s say IQ has shown to be 80% heritable in circumstances not dissimilar to the US school system (as far as I am aware this is the current state of the art). Now if you want to predict the IQ of 20,000 parents of 10,000 US schoolchildren you’ll do 80% better if you know the kids IQ than if you were just guessing randomly. Similarly, if you know Bob is smart you should update your prior estimate that Bob’s parents are also smart significantly in favor of their intelligence.
I think this is more or less correct for narrow-sense heritability (most commonly used when breeding animals) but not quite right for broad-sense heritability (most commonly used with humans). If you’re talking about broad-sense heritability, the problem is that you’d need to know not just if the parents have the trait, but also which genes Bob got or not from each parent, as well as the effect of dominant genes, epistatic interactions, etc.
Assuming you’re talking about broad-sense heritability, I think a better way of looking at it would be to say that you’ll be 80% more accurate if Bob has an identical twin raised by a random family and you know if that twin had the trait. This isn’t quite right either, but I think it’s valid if you assume that phenotypic traits are the sum of genetic effects and environmental effects and also that genetic effects are independent of environmental effects.
Of course, few people have identical twins raised by random families, and most phenotypes probably aren’t additive in genetic and environmental effects, and those effects probably aren’t independent! Which… is a lot of caveats if you want to know practical applications of heritability numbers.