nucleation

LIT-1235: What can ecosystems learn? Expanding evolutionary ecology with learning theory

1 min read

Properties4
StatusActive — read 2026-10-29 (NOTE-1368) in full, from the publisher's version in PubMed Central (PMC4672551) with its erratum; worth reading as the model in which individual selection on competitive interactions acts like Hebbian learning, so that a community with no community-level selection comes to hold and recall several past compositions. Read it knowing that the memory needs an imposed trade-off that fixes each species' total competition, that simulations keep interactions symmetric, that the two-memory state collapses in the long run, and that its printed equations (1) and (10)–(11) are wrong as printed.
Version2
Tagsecology, complex-systems, learning-theory
Cited as “paper” byNOTE-1368 — Power et al. — What can ecosystems learn?

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Power, D. A., Watson, R. A., Szathmáry, E., Mills, R., Powers, S. T., Doncaster, C. P. & Czapp, B. (2015). What can ecosystems learn? Expanding evolutionary ecology with learning theory. Biology Direct 10: 69. doi:10.1186/s13062-015-0094-1. arXiv:1506.06374. Erratum: doi:10.1186/s13062-016-0132-7.

Read in full on 2026-10-29 (NOTE-1368).

Why this is here

The synthesis the owner relayed on 2026-10-18, connecting the record’s distributed-agency line to statistical feature learning and ecological coexistence theory, recommended it for reading. It is the one work in the batch that argues from the learning side: an ecological community without a selected-for whole can still learn, which is the organization-without-a-coded-governor that QUESTION-083 asks about.

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