493
52.3 Divergent Ecological Modeling
One extremely interesting divergence has been recognition by ecological modelers
of an individual as a population. Hence, the “human brain” is described as “one of
the largest biological populations, consisting of approximately 10
11
neurons and
10
14
synapses.” Comparing the death of this complex system in terms of gauging
sub-population declines (polymorphism) as against an “immortal” population
model leads researchers to posit “internal population time”(s).
54
Even these, seemingly non-observable, remote, and independent variables, are unlikely (as far as can
be ascertained) to elude the so-called transient phenomena in ecology, which impart
distinct “important general lessons” within “the context of anthropogenic global
change,” such as a determination of just “when transients are likely to occur and
[their] various properties.” And this includes the recognition of new timeframes of
change, as well as “nonlinear interactions” that lead beyond mere idiosyncratic ecological events, but up to and beyond the bifurcation points, such that “transient
dynamics in ecological models” are now viewed soberly, in the spirit of attempting
to identify “appropriate responses to the possibility of sudden system changes”.
55
Such system behavioral shifts might refer to a virulent threshold, where a pathogen either kills its host and total metapopulation entire, or in part; where such
changes lead to total die-out of partial populations, or regain some new type of stability according to an entirely different set of fragmented population ratios, dynamics, metabolisms and energy/gene exchange; where eight generations of hunger in a
species, as studied by John Drake and Blaine Griffen, provided fundamental early
warning of a “critical slowing down” and then major transition.
56
And whether the
sum-total of such bifurcation points might (ecologically, medically), as opposed to
all out extinction, provide evolution sufficient informational cues to rescue certain
species according to, as yet ungrasped, transcendent regulatory mechanisms in
cat/web/newsroom/news-detail/mathematical-law-could-anticipate-the-possibility-of-mass-extinctions-in-ecosystems%2D%2D1345668003610.html?noticiaid=1345773475461,
Accessed
May 16, 2020. See also, “Mathematics predicts a sixth mass extinction,” by Jennifer Chu, MIT
News Office (based upon the work of MIT geophysics professor Daniel Rothman, who correlates
the abundance of carbon-12 and carbon-13 at the time of previous mass extinction events),
September 20, 2017, http://news.mit.edu/2017/mathematics-predicts-sixth-mass-extinction-0920,
Accessed May 16, 2020.
54 “Mathematical Modeling of Extinction of Inhomogeneous Populations,” G.P Karev and L. K.
areva, Bulletin of Mathematical Biology, April 2016, 78(4): 834–858, https://doi.org/10.1007/
s11538-016-0166-0, PMCID: PMC4877184, NIHMSID: NIHMS784225, PMID: 27090117,
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4877184/, HHS Public Access, Accessed May
16, 2020.
55 “Transient phenomena in ecology,” Alan Hastings, Karen C. Abbott, Kim Cuddington, Tessa
Francis, Gabriel Gellner, Ying-Cheng Lai, Andrew Morozov, Sergei Petrovskii, Katherine
Scranton, Mary Lou Zeeman, Science 07 Sep 2018: Vol. 361, Issue 6406, eaat6412, https://doi.
org/10.1126/science.aat6412, Accessed May 16, 2020.
56 John M Drake and Blaine D Griffen, “Early warning signals of extinction in deteriorating environments,” Nature 467, no. 7314 (2010): 456.
52.3 Divergent Ecological Modeling
52.3 Divergent Ecological Modeling
One extremely interesting divergence has been recognition by ecological modelers
of an individual as a population. Hence, the “human brain” is described as “one of
the largest biological populations, consisting of approximately 10
11
neurons and
10
14
synapses.” Comparing the death of this complex system in terms of gauging
sub-population declines (polymorphism) as against an “immortal” population
model leads researchers to posit “internal population time”(s).
54
Even these, seemingly non-observable, remote, and independent variables, are unlikely (as far as can
be ascertained) to elude the so-called transient phenomena in ecology, which impart
distinct “important general lessons” within “the context of anthropogenic global
change,” such as a determination of just “when transients are likely to occur and
[their] various properties.” And this includes the recognition of new timeframes of
change, as well as “nonlinear interactions” that lead beyond mere idiosyncratic ecological events, but up to and beyond the bifurcation points, such that “transient
dynamics in ecological models” are now viewed soberly, in the spirit of attempting
to identify “appropriate responses to the possibility of sudden system changes”.
55
Such system behavioral shifts might refer to a virulent threshold, where a pathogen either kills its host and total metapopulation entire, or in part; where such
changes lead to total die-out of partial populations, or regain some new type of stability according to an entirely different set of fragmented population ratios, dynamics, metabolisms and energy/gene exchange; where eight generations of hunger in a
species, as studied by John Drake and Blaine Griffen, provided fundamental early
warning of a “critical slowing down” and then major transition.
56
And whether the
sum-total of such bifurcation points might (ecologically, medically), as opposed to
all out extinction, provide evolution sufficient informational cues to rescue certain
species according to, as yet ungrasped, transcendent regulatory mechanisms in
cat/web/newsroom/news-detail/mathematical-law-could-anticipate-the-possibility-of-mass-extinctions-in-ecosystems%2D%2D1345668003610.html?noticiaid=1345773475461,
Accessed
May 16, 2020. See also, “Mathematics predicts a sixth mass extinction,” by Jennifer Chu, MIT
News Office (based upon the work of MIT geophysics professor Daniel Rothman, who correlates
the abundance of carbon-12 and carbon-13 at the time of previous mass extinction events),
September 20, 2017, http://news.mit.edu/2017/mathematics-predicts-sixth-mass-extinction-0920,
Accessed May 16, 2020.
54 “Mathematical Modeling of Extinction of Inhomogeneous Populations,” G.P Karev and L. K.
areva, Bulletin of Mathematical Biology, April 2016, 78(4): 834–858, https://doi.org/10.1007/
s11538-016-0166-0, PMCID: PMC4877184, NIHMSID: NIHMS784225, PMID: 27090117,
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4877184/, HHS Public Access, Accessed May
16, 2020.
55 “Transient phenomena in ecology,” Alan Hastings, Karen C. Abbott, Kim Cuddington, Tessa
Francis, Gabriel Gellner, Ying-Cheng Lai, Andrew Morozov, Sergei Petrovskii, Katherine
Scranton, Mary Lou Zeeman, Science 07 Sep 2018: Vol. 361, Issue 6406, eaat6412, https://doi.
org/10.1126/science.aat6412, Accessed May 16, 2020.
56 John M Drake and Blaine D Griffen, “Early warning signals of extinction in deteriorating environments,” Nature 467, no. 7314 (2010): 456.
52.3 Divergent Ecological Modeling