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Record W2559274089 · doi:10.1007/s00442-016-3786-z

Body size drives allochthony in food webs of tropical rivers

2016· article· en· W2559274089 on OpenAlexaff
Timothy D. Jardine, Thomas S. Rayner, Neil E. Pettit, Dominic Valdez, Douglas P. Ward, Garry Lindner, Michael M. Douglas, Stuart E. Bunn

Bibliographic record

VenueOecologia · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of Saskatchewan
FundersAustralian Government
KeywordsBiologyMacrophyteFood webEcologyFloodplainPredationDry seasonPeriphytonBiomass (ecology)InvertebrateTropicsHabitatWet season

Abstract

fetched live from OpenAlex

Food web subsidies from external sources ("allochthony") can support rich biological diversity and high secondary and tertiary production in aquatic systems, even those with low rates of primary production. However, animals vary in their degree of dependence on these subsidies. We examined dietary sources for aquatic animals restricted to refugial habitats (waterholes) during the dry season in Australia's wet-dry tropics, and show that allochthony is strongly size dependent. While small-bodied fishes and invertebrates derived a large proportion of their diet from autochthonous sources within the waterhole (phytoplankton, periphyton, or macrophytes), larger animals, including predatory fishes and crocodiles, demonstrated allochthony from seasonally inundated floodplains, coastal zones or the surrounding savanna. Autochthony declined roughly 10% for each order of magnitude increase in body size. The largest animals in the food web, estuarine crocodiles (Crocodylus porosus), derived ~80% of their diet from allochthonous sources. Allochthony enables crocodiles and large predatory fish to achieve high biomass, countering empirically derived expectations for negative density vs. body size relationships. These results highlight the strong degree of connectivity that exists between rivers and their floodplains in systems largely unaffected by river regulation or dams and levees, and how large iconic predators could be disproportionately affected by these human activities.

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 score0.031
Threshold uncertainty score0.996

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)0.0050.000

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 head0.006
GPT teacher head0.204
Teacher spread0.198 · 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

Citations43
Published2016
Admission routes1
Has abstractno

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