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{{Short description|Phenomenon of marine life}}
{{Short description|Phenomenon of marine life}}
[[File:Sciadv.abh3732-f1.jpg|thumb|(A) The black mapped points are n = 226,405 sample locations for measurements of heterotrophic bacteria and zooplankton. Autotrophs were estimated from satellite imagery of surface chlorophyll and fish from global process models constrained by catch data. Marine mammals are estimated from species global population estimates, and their biomass is not included on the map. Biomass (g/m2; wet weight) of each group is summed over all groups in each 1° region of the ocean (only biomass in the upper 200 m is shown here). (B) Total ocean biomass (wet weight) is partitioned across relevant size classes (g, wet weight) for each group to estimate the global size spectrum. This is shown as the total number of individuals in each order of magnitude size class over the ocean’s epipelagic and continental shelves (upper ~200 m), giving an exponent of −1.04 (95% CI: −1.05 to −1.02). The gray confidence band includes biomass uncertainty in each size class and uncertainty in the size distribution of each group. Bin colors show the relative fraction of each group on a linear axis [no relation to y axis or to the biomass in (A)].]]
[[File:Sciadv.abh3732-f1.jpg|thumb|(A) The black mapped points are n = 226,405 sample locations for measurements of heterotrophic bacteria and zooplankton. Autotrophs were estimated from satellite imagery of surface chlorophyll and fish from global process models constrained by catch data. Marine mammals are estimated from species global population estimates, and their biomass is not included on the map. Biomass (g/m2; wet weight) of each group is summed over all groups in each 1° region of the ocean (only biomass in the upper 200 m is shown here). (B) Total ocean biomass (wet weight) is partitioned across relevant size classes (g, wet weight) for each group to estimate the global size spectrum. This is shown as the total number of individuals in each order of magnitude size class over the ocean’s epipelagic and continental shelves (upper ~200 m), giving an exponent of −1.04 (95% CI: −1.05 to −1.02). The gray confidence band includes biomass uncertainty in each size class and uncertainty in the size distribution of each group. Bin colors show the relative fraction of each group on a linear axis [no relation to y axis or to the biomass in (A)].]]
The '''Sheldon spectrum''' is an observed phenomenon of [[marine biology|marine life]] that demonstrates an inverse correlation between the size of an organism and its abundance in the ocean. The spectrum is named after Ray Sheldon, a marine ecologist at Canada’s [[Bedford Institute of Oceanography]] in [[Dartmouth, Nova Scotia|Dartmouth]], [[Nova Scotia]] who first reported on this finding in the late 1960s.
The '''Sheldon spectrum''' is an empirically-observed feature of [[marine biology|marine life]] by which the size of an organism is inversely correlated with its abundance in the ocean. The spectrum is named after Ray Sheldon, a marine ecologist at Canada’s [[Bedford Institute of Oceanography]] in [[Dartmouth, Nova Scotia|Dartmouth]], [[Nova Scotia]]. Sheldon and colleagues first suggested the existence of the inverse correlation based on seagoing measurements of [[plankton]] made with a [[Coulter counter]] in the late 1960s, most notably during the first circum-navigation of the Americas aboard the [[CCGS Hudson]] <ref>Sheldon et al., [https://doi.org/10.4319/lo.1972.17.3.0327 The size distribution of particles in the ocean], ''Limnology and Oceanography'' 1972, 17(3)</ref>.


The rule observed is that [[biomass]] density as a function of [[logarithmic scale|logarithmic]] body mass is approximately constant over many [[orders of magnitude]].<ref>Cuesta JA, Delius GW, Law R. [https://link.springer.com/article/10.1007/s00285-017-1132-7 Sheldon spectrum and the plankton paradox: two sides of the same coin—a trait-based plankton size-spectrum model], ''Journal of Mathematical Biology'' 2018;76:67-96</ref> For example, [[krill]] are a billion times smaller than [[tuna]], but they are a billion times more abundant in the ocean. When Sheldon and his colleagues analyzed their [[plankton]] samples by size, they observed that each size bracket contained the same mass of creatures. In a bucket of seawater, for example, one third of the plankton mass would be between 1 and 10 [[micrometre|micrometers]], another third would be between 10 and 100 micrometers, and a third would be between 100 micrometers and 1 millimeter. To make up for the discrepancy of size, there would be a remarkably accurate mathematically correlative increase in number of organisms, so that the biomass would remain constant.<ref>Matt Reynolds (November 23, 2021) [https://www.wired.com/story/humans-broken-fundamental-law-ocean/ Humans Have Broken a Fundamental Law of the Ocean], ''Wired'' Retrieved November 24, 2021</ref>
The inverse correlation implies that [[biomass]] density as a function of [[logarithmic scale|logarithmic]] body mass is approximately constant over many [[orders of magnitude]].<ref>Cuesta JA, Delius GW, Law R. [https://link.springer.com/article/10.1007/s00285-017-1132-7 Sheldon spectrum and the plankton paradox: two sides of the same coin—a trait-based plankton size-spectrum model], ''Journal of Mathematical Biology'' 2018;76:67-96</ref> For example, when Sheldon and his colleagues analyzed a plankton sample in a bucket of seawater, they would tend to find that one third of the plankton mass was between 1 and 10 [[micrometre|micrometers]], another third was between 10 and 100 micrometers, and a third was between 100 micrometers and 1 millimeter. To make up for the differences of size, there must be a remarkably accurate mathematically correlative decrease in number of organisms as they become larger, in order for the biomass to remain constant. Thus, the rule predicts that [[krill]] which are a million times smaller than [[tuna]] are a million times more abundant in the ocean, a prediction which appears to be true. <ref>Matt Reynolds (November 23, 2021) [https://www.wired.com/story/humans-broken-fundamental-law-ocean/ Humans Have Broken a Fundamental Law of the Ocean], ''Wired'' Retrieved November 24, 2021</ref>


There is concern that human behavior, such as [[overfishing]] and [[water pollution]] have modified the Sheldon spectrum for larger species, and it is unknown what long term effects such global alteration will have.<ref>Hatton IA, et al. [https://www.science.org/doi/10.1126/sciadv.abh3732 The global ocean size spectrum from bacteria to whales], ''Science Advances'' 2021;7(46)</ref>
There is strong evidence that human behavior, particularly [[overfishing]] and [[whaling]], have modified the Sheldon spectrum for larger species, and it is unknown what long term effects such global alteration may have.<ref>Hatton IA, et al. [https://www.science.org/doi/10.1126/sciadv.abh3732 The global ocean size spectrum from bacteria to whales], ''Science Advances'' 2021;7(46)</ref>


==References==
==References==

Revision as of 19:43, 25 September 2023

(A) The black mapped points are n = 226,405 sample locations for measurements of heterotrophic bacteria and zooplankton. Autotrophs were estimated from satellite imagery of surface chlorophyll and fish from global process models constrained by catch data. Marine mammals are estimated from species global population estimates, and their biomass is not included on the map. Biomass (g/m2; wet weight) of each group is summed over all groups in each 1° region of the ocean (only biomass in the upper 200 m is shown here). (B) Total ocean biomass (wet weight) is partitioned across relevant size classes (g, wet weight) for each group to estimate the global size spectrum. This is shown as the total number of individuals in each order of magnitude size class over the ocean’s epipelagic and continental shelves (upper ~200 m), giving an exponent of −1.04 (95% CI: −1.05 to −1.02). The gray confidence band includes biomass uncertainty in each size class and uncertainty in the size distribution of each group. Bin colors show the relative fraction of each group on a linear axis [no relation to y axis or to the biomass in (A)].

The Sheldon spectrum is an empirically-observed feature of marine life by which the size of an organism is inversely correlated with its abundance in the ocean. The spectrum is named after Ray Sheldon, a marine ecologist at Canada’s Bedford Institute of Oceanography in Dartmouth, Nova Scotia. Sheldon and colleagues first suggested the existence of the inverse correlation based on seagoing measurements of plankton made with a Coulter counter in the late 1960s, most notably during the first circum-navigation of the Americas aboard the CCGS Hudson [1].

The inverse correlation implies that biomass density as a function of logarithmic body mass is approximately constant over many orders of magnitude.[2] For example, when Sheldon and his colleagues analyzed a plankton sample in a bucket of seawater, they would tend to find that one third of the plankton mass was between 1 and 10 micrometers, another third was between 10 and 100 micrometers, and a third was between 100 micrometers and 1 millimeter. To make up for the differences of size, there must be a remarkably accurate mathematically correlative decrease in number of organisms as they become larger, in order for the biomass to remain constant. Thus, the rule predicts that krill which are a million times smaller than tuna are a million times more abundant in the ocean, a prediction which appears to be true. [3]

There is strong evidence that human behavior, particularly overfishing and whaling, have modified the Sheldon spectrum for larger species, and it is unknown what long term effects such global alteration may have.[4]

References

  1. ^ Sheldon et al., The size distribution of particles in the ocean, Limnology and Oceanography 1972, 17(3)
  2. ^ Cuesta JA, Delius GW, Law R. Sheldon spectrum and the plankton paradox: two sides of the same coin—a trait-based plankton size-spectrum model, Journal of Mathematical Biology 2018;76:67-96
  3. ^ Matt Reynolds (November 23, 2021) Humans Have Broken a Fundamental Law of the Ocean, Wired Retrieved November 24, 2021
  4. ^ Hatton IA, et al. The global ocean size spectrum from bacteria to whales, Science Advances 2021;7(46)