One of the useful ideas from ecosystem theory that seems to work well for
ecosocial systems (as specialized kinds of ecosystems, inheriting all their
properties, but more highly specified because of the additional new
emergent properties that they have) is that of 'mosaic organization'.
Ecosystems are inherently 'patchy' rather than uniform across their spatial
distributions. On each spatial scale, each local patch in an ecosystem is
different from the neighboring patches: it has a different average age of
species or level of development in terms of ecological succession (in a
mature ecosystem), different frequency distribution of numbers of organisms
of each species present in the overall system, different local soil and
water and sunlight conditions, etc. Differences breed more differences. The
differences, the patchiness exists on all scales, from several meters to
microscopic. This is part of the basis for the resilience of ecosystems to
local trauma (forest fires, oil spills, etc.). But for the ecosystem to
regenerate damaged patches, there still needs to be healthy ecosystem
around them on the larger scale.
This feature of 'fractal mosaic diversity' in ecosystems is also, I think,
an example of an old principle of complex adaptive systems: they do not
tend to uniformity or homogeneity, because the successful types are those
that retain residual lability to change, those which satisfy the
information principle of 'requisite variety' which says that in an
unpredictable environment, you must have the capability to mutate rapidly
to adapt to changing conditions (the more unpredictable the environment,
the less stable you have to be).
This starts to make the link to timescales. Complex adaptive systems like
living systems, of which possibly ecosystems are the highest form (organism
chauvinism aside!), cannot tend to ultrastability. They are instead
meta-stable; dynamically contingent. They resist final attractors of their
dynamics. How do they do this? an old conjecture of mine is that they work
against their own stability (counter-functional process I called this in
the late 70s; see the Postscript to Textual Politics, and also Chapter 5
there, or the precursor to the Gent paper -- which precedes the timescales
paper -- which is at:
http://academic.brooklyn.cuny.edu/education/jlemke/ecosoc.htm
(see the last two linked papers from that page, which tells the story).
How can a system work against its own stability? Recognizing that the
system operates on and across multiple timescales, dyssynchronies in N-1
scale processes can prevent stabilization (at least strong, or
ultra-stabilization, the kind that the system cannot deviate from without
destroying itself) of focal scale (level N) processes.
There are actually known mechanisms of this kind in ecosystems (see
references in the papers linked to above, esp. Hollings 1986, Schneider,
Odum), as for example when several different cyclical processes that result
from the mutual couplings among several species (trees, leafeaters,
leafeater eaters) are temporally incommensurable, so that there is never a
stable repeating cycle at a longer timescale. It is a kind of 'chaos'
behavior, though more like an indeterminate wandering path among cyclical
attractors in which there is no optimum solution, and relatively random
factors determine which attractor we get temporarily entrained by.
There is some kinship here to the 'principle of uneven development' whereby
cultural and economic systems are 'patchy' in time (like the uneven stages
of ecological succession in a mature forest where local fires have reset
the successional clock in some patches at different times). It is like
trying to define the age of a city by the age of its buildings; old ones
exist side by side with new ones; there is age-diversity at all scales
(districts, neighborhoods, buildings, parts of buildings, etc.) Faster
timescale processes (local construction vs. larger scale urban development)
are insuring age-patchiness.
But in time and development, optimal non-stabilization is achieved also by
the dyssynchonizations of rates of processes, and point-in-the-cycle (or
phase, technically) among processes with characteristic cycle times on the
same timescale.
So in Mike's example local conditions may lead some patches to be in a
go-slow phase, others in a go-fast phase. That diversity is useful to the
larger aggregate system. Depending on how tightly coupled the different
patches are to one another, a slow-phase patch may exert a braking effect
on a fast-phase one (and the reverse accelerating effect occurs), coupling
the different local cycles in ways that perhaps keep any patch from
stopping altogether or going so fast it self-destructs. There may
(hopefully) never be a full synchronization of the cycles of all the
patches; they keep each other a little off-balance, and therefore always
ready for a leap to something new.
Kinda like us here on xmca ....... JAY.
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JAY L. LEMKE
PROFESSOR OF EDUCATION
CITY UNIVERSITY OF NEW YORK
JLLBC who-is-at CUNYVM.CUNY.EDU
<http://academic.brooklyn.cuny.edu/education/jlemke/index.htm>
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