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Record W2970023557 · doi:10.1002/ecy.2874

Intraguild predation enables coexistence of competing phytoplankton in a well‐mixed water column

2019· article· en· W2970023557 on OpenAlexaff
Holly V. Moeller, Michael G. Neubert, Matthew D. Johnson

Bibliographic record

VenueEcology · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsUniversity of British Columbia
FundersInstitute for Collaborative BiotechnologiesSimons Foundation Autism Research InitiativeWoods Hole Oceanographic InstitutionArmy Research OfficeSimons FoundationNational Science Foundation
KeywordsIntraguild predationPhototrophCompetition (biology)EcologyPredationLimitingEcosystemCompetitive exclusionBiologyResource (disambiguation)PhytoplanktonMixotrophInterspecific competitionHeterotrophPredatorPhotosynthesisNutrient

Abstract

fetched live from OpenAlex

Resource competition theory predicts that when two species compete for a single, finite resource, the better competitor should exclude the other. However, in some cases, weaker competitors can persist through intraguild predation, that is, by eating their stronger competitor. Mixotrophs, species that meet their carbon demand by combining photosynthesis and phagotrophic heterotrophy, may function as intraguild predators when they consume the phototrophs with which they compete for light. Thus, theory predicts that mixotrophy may allow for coexistence of two species on a single limiting resource. We tested this prediction by developing a new mathematical model for a unicellular mixotroph and phytoplankter that compete for light, and comparing the model's predictions with a laboratory experimental system. We find that, like other intraguild predators, mixotrophs can persist when an ecosystem is sufficiently productive (i.e., the supply of the limiting resource, light, is relatively high), or when species interactions are strong (i.e., attack rates and conversion efficiencies are high). Both our mathematical and laboratory models show that, depending upon the environment and species traits, a variety of equilibrium outcomes, ranging from competitive exclusion to coexistence, are possible.

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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.995

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)0.0060.001

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 head0.007
GPT teacher head0.183
Teacher spread0.176 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations30
Published2019
Admission routes1
Has abstractyes

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