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Record W6946450798 · doi:10.3389/fevo.2021.674792.s004

Image_3_Kelp Forests: Catastrophes, Resilience, and Management.tif

2021· other· en· W6946450798 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFigshare · 2021
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBioactive natural compounds
Canadian institutionsnot available
Fundersnot available
KeywordsKelp forestPopulationTipping point (physics)EcosystemSustainable yieldClimate changeSustainabilitySustainable managementRegime shiftHabitat

Abstract

fetched live from OpenAlex

<p>Resilient kelp forests provide foundation habitat for marine ecosystems and are indicators of the ecosystems’ sustainable natural capital. Loss of resilience and imperfectly reversible catastrophic shifts from kelp forests to urchin barrens, due to pollution or loss of a top predator, are part of an ecological tipping point phenomenon, and involve a loss in sustainable natural capital. Management controls to prevent or reverse these shifts and losses are classified in a number of ways. Systemic controls eliminate the cause of the problem. Symptomatic controls use leverage points for more direct control of the populations affected, urchin harvesting or culling, or kelp enhancement. There is a distinction between ongoing structural (press) controls versus temporary or intermittent perturbation (pulse) controls, and one between shift preventing versus shift reversing or restorative controls. Adaptive management and the options it creates both focus on reductions in uncertainty and control policies with the flexibility to take advantage of those reductions. The various management distinctions are most easily understood by modeling the predator-urchin-kelp marine ecosystem. This paper develops a mathematical model of the ecosystem that has the potential for two different catastrophic shifts between equilibria. Pulse disturbances, originating from exogenous abiotic factors or population dynamics elsewhere in the metacommunity, can activate shifts. A measure of probabilistic resilience is developed and used as part of an assessment of the ecosystem’s sustainable stock of natural capital. With perturbation outcomes clustered around the originating equilibrium, hysteresis is activated, resulting imperfect reversibility of catastrophic shifts, and a loss in natural capital. The difficulty of reversing a shift from kelp forest to urchin barren, with an associated loss in sustainable natural capital, is an example. Management controls are modeled. I find that systemic and symptomatic, and press and pulse, controls can be complementary. Restorative controls tend to be more difficult or costly than preventative ones. Adaptive management, favoring flexible, often preventative, controls, creates option value, lowering control costs and/or losses in sustainable natural capital. Two cases are used to illustrate, Tasmania, Australia and Haida Gwaii, Canada.</p>

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.239
Threshold uncertainty score0.944

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0570.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.252
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it