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Record W2110571187 · doi:10.1098/rsbl.2009.0311

Tree shrew lavatories: a novel nitrogen sequestration strategy in a tropical pitcher plant

2009· article· en· W2110571187 on OpenAlexaff
Charles Clarke, Ulrike Bauer, Ch'ien C. Lee, Andrew Alek Tuen, Katja Rembold, Jonathan A. Moran

Bibliographic record

VenueBiology Letters · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and Biological Electrophysiology Studies
Canadian institutionsRoyal Roads University
Fundersnot available
KeywordsBiologyPredationCarnivorous plantEcologyHabitatSympatric speciationMontane ecologyCecropiaBotany

Abstract

fetched live from OpenAlex

Nepenthes pitcher plants are typically carnivorous, producing pitchers with varying combinations of epicuticular wax crystals, viscoelastic fluids and slippery peristomes to trap arthropod prey, especially ants. However, ant densities are low in tropical montane habitats, thereby limiting the potential benefits of the carnivorous syndrome. Nepenthes lowii, a montane species from Borneo, produces two types of pitchers that differ greatly in form and function. Pitchers produced by immature plants conform to the 'typical' Nepenthes pattern, catching arthropod prey. However, pitchers produced by mature N. lowii plants lack the features associated with carnivory and are instead visited by tree shrews, which defaecate into them after feeding on exudates that accumulate on the pitcher lid. We tested the hypothesis that tree shrew faeces represent a significant nitrogen (N) source for N. lowii, finding that it accounts for between 57 and 100 per cent of foliar N in mature N. lowii plants. Thus, N. lowii employs a diversified N sequestration strategy, gaining access to a N source that is not available to sympatric congeners. The interaction between N. lowii and tree shrews appears to be a mutualism based on the exchange of food sources that are scarce in their montane habitat.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.028
GPT teacher head0.224
Teacher spread0.196 · 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 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

Citations110
Published2009
Admission routes1
Has abstractyes

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