For me, the most surprising point in the article was this:
> Our analysis reveals that the global marine biomass pyramid contains more consumers than producers, thus an inverse food pyramid.
I didn't understand how such a thing was possible until I read the explanation further down:
> Such inverted biomass distributions can occur when primary producers have a rapid turnover of biomass [on the order of days], while consumer biomass turns over much more slowly [a few years in the case of mesopelagic fish]. Thus, the standing stock of consumers is larger, even though the productivity of producers is necessarily higher.
There's an analogy in the "human world": Farmers were 90% of labor force in the U.S. in 1790, but only 2.6% in 1990.[1] Farming has become so much more efficient that a small group can feed the whole country.
I would suspect that there's also some amount of refuse biomass from terrestrial sources that helps supply marine consumers, though it may be trivial in the grand scheme of things. I wonder how much biomass relies on sewage dumping as a food source?
Edit: And how are tide flats and their flora categorized?
I don’t know if the farmer anaolgy works. The majority of farming operations in the U.S.A are owned by corporations and use harmful farming practices. That trend needs to be reversed back to when local family farmers provided the majority of the food in their region.
Why is this being downvoted? Perhaps on its face it seems to be anti-technology and regressive, but there's plenty of data to suggest that the industrial efficiencies of modern farms have massive negative externalities in terms of depleted soil health in the form of the narrowing of both macrobiome and microbiome, depleted nutrient content in our plants, depleted health and nutrition of our animals, leading up to depleted health to those at the top of the food chain: humans.
it's being downvoted because it's not a relevant reply to the original comment, and has potential to provide a flamewar on a topic entirely different than the original article.
If you're willing to spend 40x+ more on labor per acre, you can vastly increase yields and entirely eliminate pesticides/non-organic fertilizer usage - potentially 20x+ yields in same area (depending on crop). But it takes a lot of expensive skilled labor to meet or exceed agroindustrial yields.
I think the biggest problem with our agricultural industry is commoditization of vegetables. We need 'celebrity/hipster' vegetable strains/growers that command significantly higher prices. If you grow vegetables that are twice as nutritious as found in the grocery store, you'd have a hard time finding a market at twice the price. Nutritional density of our vegetables has dropped something like 10% in the last 30 years as a result of agroindustrial farming methods.
Megacities are certainly problematic for the 'local' part. A city like Chicago that's more-or-less surrounded by farmland could be more plausible. Microgreens with imported seeds could be an interesting option: locally grown, fresh, short growing cycle of ~14 days, one warehouse full of growlights and you could provide greens for thousands year round.
Perennial grain research, such as Salish Blue 'Wheat', is also pretty exciting - would greatly simplify grain farming if the plant lived many years.
> The total wild mammal biomass before the Quaternary Megafauna Extinction event of ≈0.04 Gt C is about 6-fold higher than the ≈0.007 Gt C of extant wild mammal biomass. We cannot currently derive the uncertainty associated with the change in wild mammal biomass before and after human civilization, as we do not have a projection for the uncertainty associated with the pre-human wild land mammal biomass. ...
> At the same time that the biomass of wild megafauna collapsed, the biomass of humans gradually increased over the same period. Since the industrial revolution we have witnessed an exponential increase in human population, as well as a rapid increase in the domesticated livestock biomass. Today, the biomass of livestock (≈0.1 Gt) is an order of magnitude larger than that of all the terrestrial wild megafauna before the Quaternary Megafauna Extinction. Even the biomass of humans alone (≈0.05 Gt) is around twice the size of the biomass of all wild megafauna before the Quaternary Megafauna Extinction event.
Wow. I love analysis like this. Total biomass of viruses = 0.2 gigatons. Total humanity of all 7 billion souls only 0.06 gigatons. Did I understand correctly?
Basically yeah. Consider for this that viruses are also incredibly lightweight and tiny. Those 0.2 Gigatons cause the death of 40% of marine life each day (2.4 Gt of C).
I found a good antidote for an existential mood is that even if you consider that a human life is probably pretty meaningless, you can still have fun for yourself.
> Their findings, published in the International Society for Microbial Ecology Journal, showed that approximately 800 million viruses may be deposited per square meter of land.
As a counterpoint, I found it to be very helpful in understanding the information presented.
The animals breakdown (Chart B) contains 10 values, ranging from 1 Gt to 0.002 Gt. That's a difference of 500x. That's a bit hard to perceive in a one-dimensional chart.
The two-dimensionality of a Voronoi makes it easier to perceive, particularly in a small image (as is presented on a phone's screen), at least to me. I imagine this is mostly due to a 2D chart consuming far more physical pixels to convey the same information.
A stacked bar chart of the same information: [1]. Admittedly, I didn't take time sprucing up that chart, but I find it extremely hard to intuit from and can't even see the value for "wild birds".
I've rendered the data as a stacked bar chart; I think the reason a bar chart is ineffective here is clear. It would have to be logarithmic to deal with the wide range of values, and logarithmic charts make it extremely difficult to quickly compare values.
I was thinking it should be a stacked bar chart for the top-level categorization (e.g. plants, animals, fungi, etc.) with a separate stacked bar chart for proportions within each group of interest (e.g. humans, insects, etc.).
Not sure I understand. What would be stacked in the first chart you describe? If it's the sub-categories that are stacked, I believe that's what I've rendered here. If it's the top-level categories that are stacked, it's not really a bar chart at all; there'd be only one bar.
Either way, you'd still be comparing animals to viruses to plants with one-variable-dimension objects, and you'd have the same problem. The topmost categories simply vary too much in size.
I disagree. Comparing bar heights with large dynamic range requires vanishingly small bars or a graph that doesn't fit on one screen, both of which inhibit intuition about relative size.
I don't know that that would be the case with this particular data, but I can certainly imagine a dataset whose data would fit easily when expressed as two dimensional areas but would become too large for a screen or too small for a pixel when rendered as one dimensional objects.
>Comparing bar heights with large dynamic range requires vanishingly small bars
True. It is nice that the smallest parts don't have to all appear as similarly tiny slivers.
Comparing areas, though, is not a strength of human perception. It would be interesting to test a population of users, given a Voronoi diagram, to estimate the apparent percentage of each area.
And it is instructive that in the paper they still resort to a second, zoomed-in view that breaks down the smallest subsets. You'd want to do the same no matter the representation.
Heh. The obvious answer is "because Voronoi tesselations can convey a 2D location in addition to the data set size". But this doesn't use that. So... yeah, they're not.
I thought it did though. The centroid of the space relates the relative relatedness of the subsegment. I.e., animals are closer to plants than viruses.
When differences are vast, a linear bar chart becomes unreadable, and logarithmic bar charts make intuition about sizes difficult. Two dimensional spatial comparisons are intuitive and compact.
I think it’s at least partly about space efficiency. A bar chart with a few tall bars and many much shorter ones ends up wasting a large amount of space, while a Voronoi makes effective use of the whole graph area to represent data. This allows the area representing small ‘bars’ to be larger given constant graph size, and therefore more clearly represents them.
From the appendix, it sounds like amphibians at least may still outweigh humans. They guess 1 amphibian per square meter over the entire non-ice covered terrestrial surface to get .1 Gt C. Which puts the other weights into perspective...
For reptiles, different estimates range from 0.00005 Gt C to .5 Gt C. They say their best guess is .003 Gt C (compared to .007 Gt C for wild mammals).
Edit: I wonder if they might be somewhat underestimating the mass of rodents.
> Finally, we highlight that the mass of humans is an order of magnitude higher than that of all wild mammals combined
I sometimes wonder if the Earth is an egg and humanity is a kind of embryo and the other biomass is a yolk.
I don't believe it but it's the only hope I have that what we're doing is okay.
We're converting oil and the other living things on this planet into humans (and our meat animals) so voraciously. We're strip-mining the oceans of protein. If we invent e.g. antigravity and the bulk of humanity can leave that's one yet-fictional option. Realistically, we've already reached a tipping point to ecological collapse and we will be very fortunate if even 0.1% of humanity is still alive by the end of this century.
> Our analysis reveals that the global marine biomass pyramid contains more consumers than producers, thus an inverse food pyramid.
I didn't understand how such a thing was possible until I read the explanation further down:
> Such inverted biomass distributions can occur when primary producers have a rapid turnover of biomass [on the order of days], while consumer biomass turns over much more slowly [a few years in the case of mesopelagic fish]. Thus, the standing stock of consumers is larger, even though the productivity of producers is necessarily higher.
There's an analogy in the "human world": Farmers were 90% of labor force in the U.S. in 1790, but only 2.6% in 1990.[1] Farming has become so much more efficient that a small group can feed the whole country.
[1] https://www.agclassroom.org/gan/timeline/farmers_land.htm