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Record W2062156766 · doi:10.1890/11-0505.1

Incorporating temporally dynamic baselines in isotopic mixing models

2011· review· en· W2062156766 on OpenAlexafffundabout
Ryan J. Woodland, Marco A. Rodríguez, Pierre Magnan, Hélène Glémet, Gilbert Cabana

Bibliographic record

VenueEcology · 2011
Typereview
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsEcologyMixing (physics)Environmental scienceBiologyPhysics

Abstract

fetched live from OpenAlex

Stable isotopes (particularly C and N) are widely used to make inferences regarding food web structure and the phenology of consumer diet shifts, applications that require accurate isotopic characterization of trophic resources to avoid biased inferences of feeding relationships. For example, most isotope mixing models require that endmembers be adequately represented by a single probability distribution; yet, there is mounting evidence that the isotopic composition of aquatic organisms often used as mixing model endmembers can change over periods of weeks to months. A review of the literature indicated that the delta13C values of five aquatic primary consumer taxa, commonly used as proxies of carbon production sources (i.e., trophic baselines), express seasonally dynamic cycles characterized by an oscillation between summer maxima and winter minima. Based on these results, we built a dynamic baseline mixing model that allows a growing consumer to track temporal gradients in the isotopic baselines of a food web. Simulations showed that the ability of a consumer to maintain or approach isotopic equilibrium with its diet over a realistic growth season was strongly affected by both the rate of change of the isotopic baseline and equilibration rate of the consumer. In an empirical application, mixing models of varying complexity were used to estimate the relative contribution of benthic vs. pelagic carbon sources to nine species of juvenile fish in a fluvial lake of the St. Lawrence River system (Québec, Canada). Estimates of p (proportion of carbon derived from benthic sources) derived from a static mixing model indicated broad interspecific variation in trophic niche, ranging from complete benthivory to > 95% reliance on pelagic food webs. Output from the more realistic dynamic baseline mixing model increased estimated benthivory by an average of 36% among species. Taken together, our results demonstrate that failing to identify dynamic baselines when present, and (or) matching consumers with baseline taxa that possess substantially different equilibration rates can seriously bias interpretation of stable isotope data. Additionally, by providing a formalized framework that allows both resources and consumers to shift their isotopic value through time, our model demonstrates a feasible approach for incorporating temporally dynamic isotope conditions in trophic studies of higher consumers.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.289
Teacher spread0.254 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations44
Published2011
Admission routes3
Has abstractyes

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