1. Complexity, individuation and function in ecology Part II, sec 2 Individuation of ecosystems, stability, resilience
Prof. John Collier
(Departamento de Filosofia, Universidade de Kwazulu-Natal, África do Sul. Pesquisador Visitante do Laboratório de Ensino, Filosofia e História das Ciências (LEFHBio), Programa Ciência sem Fronteiras)

2. Outline
Why we need individuation of ecosystems to understand ecosystem function.
Function is contribution to survival or achievement of something X.
We cannot determine the something X without criteria for individuation of X.
Properties that might underlie individuation in ecosystems.
Stability
Ecosystem health
Resilience
Ascendency
Overhead
Individuation of ecosystems as complex systems
Metamodels
Combining metamodels
Other issues in ecosystems

3. Why we need individuation of ecosystems to understand ecosystem function.
Function is always “for the sake of” something, meaning that it contributes to that something’s survival and/or achievement.
For ecosystems, functionality can only be related to issues like ecosystem stability and its growth and development.
Ecosystem functionality is anything that contributes to the ecosystem stability and growth and development.
So we need to be able to identify what it is that functionality contributes to in order to properly identify functionality.

4. What about parts of ecosystems?
The simplest parts of ecosystems are organisms, and we have a criterion for their functionality in terms of autonomy.
However there are smaller ecosystem units within larger ecosystems.
Sometimes these are other ecosystems, which then presents the same problem for individuation.
But there are also other factors that contribute to functionality indirectly through their contribution to larger but perhaps not distinct units.
Their functionality will therefore ultimately contribute to the larger ecosystem, but the mechanisms and constraints need to be examined and understood in order to understand the nature of their functionality.

5. Properties proposed to underlie individuation in ecosystems.
Stability – a very general property; we want to know the mechanisms that contribute to it. In ecosystem growth and development stability sometimes must be compromised for the capacity for growth and development.
Ecosystem health – too vague, same problem as stability.
Resilience – a widely used concept, this reflects the capacity of the ecosystem to resist perturbations, and is thus related to stability and ecosystem health. Definitions from C.S. (Bud) Holling
as the time required for an ecosystem to return to an equilibrium or steady-state following a perturbation (which is also defined as stability by some authors). This definition of resilience is used in other fields such as physics and engineering, and hence has been termed ‘engineering resilience’ by Holling.
as "the capacity of a system to absorb disturbance and reorganize while undergoing change so as to still retain essentially the same function, structure, identity, and feedbacks".

6. Ulanowicz’ dynamical account
Ulanowicz uses information theory to calculate the correlations among nodes in the ecosystem. This gives a measure of gross system organization.
He also uses other measures like energy dissipation and transfer.
He considers not just size, but also organization.
Size is like the Gross National Product. It measures the total system throughput (TST).
Size correlates with growth, and organization with development. He combines the two into a measure called ascendency, which can be used to estimate ecosystem stability under various conditions.

8. Overhead
There are processes in an ecosystem that don’t contribute to either growth or development. Some are involved in routine maintenance of parts of the system, but others aspects are available to be converted to ascendency either as organization or growth.
He calls this overhead.
If overhead goes to 0, then the system becomes very brittle, vulnerable to perturbations. It lacks resilience.

11. Stability and Health
On Ulanowicz’ account an ecosystem is stable at a time if it has high ascendency.
It is stable over time if it has both this as well as a good overhead.
Fortunately, both can increase together.
However, there are costs.
Overhead can be reduced, making the system brittle.
Organization increase can reduce efficiency and also introduce to much complexity, moving the system out of the “safe” area.

14. Comparison to other approaches
Time dependence, compare with Holling.
Mathematical model, so can make fairly precise predictions.
Dynamical model, so can be used to test some predictions.
Therefore more useful for management than vague resilience, stability and ecosystem health.

18. Ecosystem individuation
Ecosystems are complexly organized (Type IV) systems, so there is no complete model.
There are several popular models used in ecology, but they are preferred by specialists who don’t interact much. We call these metamodels.
Although some approaches work well for certain cases, other cases will involve cohesion from multiple sources (much like organisms and species).
What we need to look for is testable evidence that the cohesion is there and what its nature is.
Therefore, we need to look for closure of the processes.

19. Ecology metamodels
Metamodels are not hypotheses in the commonly used sense. They are not necessarily rigorous quantitative statements, although they must be supported by rigorous quantitative studies. Indeed, they are more a kind of specific metaphor: a way of thinking about things that serves as a powerful tool for the generation of specific hypotheses in specific cases.

20. Some metamodels Holling's adaptive cycle
Random walk: Under this model, complex systems wander randomly through a multivariate space.
Replacement
Succession
Dynamic limitation (external constraints and drivers)
Ecosystem evolution