This is really valuable work, and I look forward to seeing the discussion that it generates and to digging into it more closely myself. I did have one immediate question about the neuron count model specifically, though I recognize that it’s a a small contributor to the overall weights. I’d be curious to understand how you arrived at 13 million neurons as your estimate for salmon. The reference in the spreadsheet is:
The teleost brain is capable of adult neurogenesis, with neural proliferation zones in dozens of locations within the brain (e.g. Zupanc et al. 2005, Zupanc 2009). This makes a definitive count of total neurons within the brain difficult, since the number of neurons may be continuously in flux. For example, Zupanc (2009) summarizes: “the continuous production of new cells, together with the longterm persistence of a large portion of them, leads to a permanent growth of the brain and its individual structures… This growth by a net increase in the total number of brain cells is characteristic of at least some, but likely most, of the estimated 30,000 species of teleost fish.” Therefore, reports of total neuron counts for salmon and carp are rare, but Hinsch & Zupanc (2007) report that “By labeling S-phase cells with the thymidine analog 5-bromo-2-deoxyuridine (BrdU), quantitative analysis demonstrated that, on average, 6000 new cells were generated in the entire adult brain within any 30 min period. This corresponds to roughly 0.06% of the total number of brain cells” in an adult zebrafish (Danio rerio, a model cyprinid) brain. As part of their study, Hinsch & Zupanc (2007) report that, for adult zebrafish, the total number of brain cells varied between 0.8 x 107 and 1.3 x 107 (mean: 1.0 x 107 ± S.E.M. 8 x 105). They also report that “approximately 46% of the cells present at 10 days persisted in the adult zebrafish brain” meaning that “at least half of the cells generated in the adult zebrafish brain develop into neurons and are likely to persist for the rest of the fish’s life.” This pattern is reflected in other species of teleosts, for example in adult gymnotiform fish (Apteronotus leptorhynchus) who generate 100 000 new brain cells (corresponding to approximately 0.2% of the total population of cells in the brain) within a period of 2 hours (Zupanc & Horschke 1995). Thus the teleost brain is constantly growing and likely increasing in terms of total number of neurons, and counts are only representative of snapshots through time.
I don’t easily see how that translates to 13 million neurons. When I previously looked at this issue myself, I came away thinking it was possible that salmon had substantially more neurons than you’re estimating.
Thanks, MHR. Quick reply to say: Good question, but I don’t know the answer offhand, as I didn’t come up with that number myself. Many different people helped with the literature reviews. I’ll get in touch with the relevant person and get back to you.
Sorry for the delay, MHR! It took a bit to get to the bottom of this. In any case, the short version is that the 8-13M neuron count for both salmon and carp should be read as the lowest reasonable estimate, not our best guess. We got the number from the zebrafish literature—specifically, a study by Hinsch & Zupanc (2007) (cited in the table) who reported that the total number of brain cells for adult zebrafish varied between 8 and 13 million. In the notes associated with the Welfare Range Table, we had a caveat that neuron counts are very hard to come by in fish and, in any case, only represent a snapshot in time, because the teleost brain is constantly growing. Moreover, no one has done total neuron count estimates for salmon or carp, whereas zebrafish are often used as a model species and are well-studied; so, we simply used those values as a placeholder. Granted, then, the 8-13M number may well be an underestimate due to the size differences between zebrafish and salmon, and we do see the appeal of using Invincible Wellbeing’s curve fits to come up with a higher number. However, we tried to stick as close to the empirical literature as possible. And truth be told, because neuron counts are just one of several models we include, using a higher number wouldn’t make a major difference to our welfare range estimates for salmon or carp.
The upshot is that is one of many cases where our methodology is more conservative than many EAs have been when doing related projects (e.g., we were more inclined to default to “unknown,” we used lower-bound placeholder values in some cases, etc.). Advantages and disadvantages!
Just to see the magnitude of the change, I tried rerunning the model with a neuron count estimate of 100 million for salmon. That led to salmon’s 50th-percentile estimate increasing by 0.001 and 95th-percentile estimate increasing by 0.002. So you’re right that it’s not really a noticeable impact.
This is really valuable work, and I look forward to seeing the discussion that it generates and to digging into it more closely myself. I did have one immediate question about the neuron count model specifically, though I recognize that it’s a a small contributor to the overall weights. I’d be curious to understand how you arrived at 13 million neurons as your estimate for salmon. The reference in the spreadsheet is:
I don’t easily see how that translates to 13 million neurons. When I previously looked at this issue myself, I came away thinking it was possible that salmon had substantially more neurons than you’re estimating.
Thanks, MHR. Quick reply to say: Good question, but I don’t know the answer offhand, as I didn’t come up with that number myself. Many different people helped with the literature reviews. I’ll get in touch with the relevant person and get back to you.
Sorry for the delay, MHR! It took a bit to get to the bottom of this. In any case, the short version is that the 8-13M neuron count for both salmon and carp should be read as the lowest reasonable estimate, not our best guess. We got the number from the zebrafish literature—specifically, a study by Hinsch & Zupanc (2007) (cited in the table) who reported that the total number of brain cells for adult zebrafish varied between 8 and 13 million. In the notes associated with the Welfare Range Table, we had a caveat that neuron counts are very hard to come by in fish and, in any case, only represent a snapshot in time, because the teleost brain is constantly growing. Moreover, no one has done total neuron count estimates for salmon or carp, whereas zebrafish are often used as a model species and are well-studied; so, we simply used those values as a placeholder. Granted, then, the 8-13M number may well be an underestimate due to the size differences between zebrafish and salmon, and we do see the appeal of using Invincible Wellbeing’s curve fits to come up with a higher number. However, we tried to stick as close to the empirical literature as possible. And truth be told, because neuron counts are just one of several models we include, using a higher number wouldn’t make a major difference to our welfare range estimates for salmon or carp.
The upshot is that is one of many cases where our methodology is more conservative than many EAs have been when doing related projects (e.g., we were more inclined to default to “unknown,” we used lower-bound placeholder values in some cases, etc.). Advantages and disadvantages!
Thanks Bob, that makes sense!
Just to see the magnitude of the change, I tried rerunning the model with a neuron count estimate of 100 million for salmon. That led to salmon’s 50th-percentile estimate increasing by 0.001 and 95th-percentile estimate increasing by 0.002. So you’re right that it’s not really a noticeable impact.