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Record W2561768607 · doi:10.1002/ecs2.1617

Do novel ecosystems follow predictable trajectories? Testing the trophic surge hypothesis in reservoirs using fish

2016· article· en· W2561768607 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEcosphere · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversité du Québec à RimouskiMcGill University
FundersMitacs
KeywordsTrophic levelEcosystemEcologyEnvironmental scienceAbundance (ecology)Fish <Actinopterygii>BorealBiologyFishery

Abstract

fetched live from OpenAlex

Abstract Hydroelectric reservoirs are novel ecosystems that provide a variety of important services. To manage these ecosystems and their fish populations effectively, we need to develop conceptual frameworks for predicting their short‐ and long‐term responses. To advance this goal, we revisited and tested the “trophic surge hypothesis, TSH .” The TSH has been widely cited in the literature, but has not been empirically tested across numerous reservoirs. The TSH suggests that fish populations should show a hump‐shaped pattern (i.e., the non‐equilibrium phase) after river impoundment. As such, we assembled 40 recruitment and 109 adult fish abundance time series from 19 species distributed across seven reservoirs from temperate and boreal regions, and applied curve fitting analyses and model selection. We found that the hump‐shaped pattern was the predominant pattern across individual time series, providing moderate support for the TSH . Fish recruitment increased substantially during reservoir filling and was followed by an increase in adult fish lagging 3–4 years behind. The non‐equilibrium phase was transient and lasted roughly eight years for recruits, whereas it could be much longer for adults. When time series were combined across regions and sites, the support for the TSH was weaker. However, we observed significant variability in the duration, timing, and magnitude of the surge across individual time series and found that the total flooded area was the most influential predictor to explain this variability. In conclusion, the TSH and related metrics can be a useful and general predictive framework to understand how fish populations may respond to impoundment. In particular, long‐term management recommendations could be short‐sighted if formulated before convincing evidence has emerged to show that the reservoir reached its new trophic equilibrium.

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)0.001
metaresearch head score (Gemma)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0030.000

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 head0.044
GPT teacher head0.213
Teacher spread0.169 · 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