Darwin's feathers: Eco-evolutionary biology, predictions and policy.
Adv Mar Biol
; 95: 91-111, 2023.
Article
in En
| MEDLINE
| ID: mdl-37923540
ABSTRACT
The scientific community is often asked to predict the future state of the environment and, to do so, the structure (biodiversity) and the functions (ecosystem functioning) of the investigated systems must be described and understood. In his "handful of feathers" metaphor, Charles Darwin explained the difference between simple and predictable systems, obeying definite laws, and complex (and unpredictable) systems, featured by innumerable components and interactions among them. In order not to waste efforts in impossible enterprises, it is crucial to ascertain if accurate predictions are possible in a given domain, and to what extent they might be reliable. Since ecology and evolution (together forming "natural history") deal with complex historical systems that are extremely sensitive to initial conditions and to contingencies or 'black swans', it is inherently impossible to accurately predict their future states. Notwithstanding this impossibility, policy makers are asking the community of ecological and evolutionary biologists to predict the future. The struggle for funding induces many supposed naturalists to do so, also because other types of scientists (from engineers to modellers) are keen to sell predictions (usually in form of solutions) to policy makers that are willing to pay for them. This paper is a plea for bio-ecological realism. The "mission" of ecologists and evolutionary biologists (natural historians) is not to predict the future state of inherently unpredictable systems, but to convince policy makers that we must live with uncertainties. Natural history, however, can provide knowledge-based wisdom to face the uncertainties about the future. Natural historians produce scenarios that are of great help in figuring out how to manage our relationship with the rest of nature.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Ecosystem
/
Biological Evolution
Limits:
Animals
Language:
En
Journal:
Adv Mar Biol
Year:
2023
Type:
Article