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Record W2621921890 · doi:10.3354/meps12222

Phenotypic plasticity in the marine angiosperm Halophila decipiens (Hydrocharitaceae, Streptophyta)

2017· article· en· W2621921890 on OpenAlexaboutno aff
Nadine Schubert, Kyle Demes

Bibliographic record

VenueMarine Ecology Progress Series · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyPhenotypic plasticityHydrocharitaceaeEcologySeagrassEcosystem

Abstract

fetched live from OpenAlex

MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 575:81-93 (2017) - DOI: https://doi.org/10.3354/meps12222 Phenotypic plasticity in the marine angiosperm Halophila decipiens (Hydrocharitaceae, Streptophyta) Nadine Schubert1,3,*,**, Kyle Demes2,* 1Unidad Académica de Sistemas Arrecifales Puerto Morelos, Instituto de Ciencias del Mar y Limnología, Universidad Autónoma de México, 77500 Cancún, Quintana Roo, México 2Office of the Vice-President Research, University of British Columbia, Vancouver, BC V6T1Z2, Canada 3Present address: Programa de Pós-Graduação em Oceanografia, Departamento de Geociências, Universidade Federal de Santa Catarina (UFSC), Campus Trindade, 88040-900 Florianópolis, Brazil *Both authors contributed equally to this work**Corresponding author: nadine_schubert@hotmail.com ABSTRACT: Light availability is a central determinant of seagrass physiology and therefore distributional patterns. While climax species usually inhabit areas with favorable light conditions, poor competitors like Halophila decipiens Ostenf. are often marginalized into areas of low and high light levels. Thus, their ecological success relies on the ability to withstand and quickly acclimate to contrasting light conditions. Here we determined the acclimation of H. decipiens to different light availabilities and its capacity to rapidly adjust to changing light environments. Morphological and physiological traits differed among depths, with deeper plants having longer, wider leaves and higher photosynthetic performance. This agreed with the reported shade-adapted nature of this species and suggests that the wide tolerance to different light environments of H. decipiens is accompanied by costs resulting in an optimal phenotype for high-light environments, but occasioning a decrease in fitness, most likely related to higher investments in photoprotection and photodamage repair. This species exhibits efficient photoprotective mechanisms, related to energy dissipation, but we also detected chloroplast movement in response to light intensity, which most likely protects the photosynthetic apparatus under high-light stress through minimizing light absorption. H. decipiens also showed high plasticity through quick morphological and physiological adjustments upon transplantation, within days exhibiting characteristics consistent with plants that had originated from the transplant site. This rapidly responding plasticity, in addition to the high sexual reproduction of this species and the formation of extensive seed banks, is likely one of the key features to understanding this species' broad distribution and persistence when outcompeted to the distributional limits of dominant climax species. KEY WORDS: Chloroplast movement · Halophila · Light stress · Photoacclimation · Photoprotection · Phenotypic plasticity · Seagrass · Transplants Full text in pdf format PreviousNextCite this article as: Schubert N, Demes K (2017) Phenotypic plasticity in the marine angiosperm Halophila decipiens (Hydrocharitaceae, Streptophyta). Mar Ecol Prog Ser 575:81-93. https://doi.org/10.3354/meps12222 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 575. Online publication date: July 20, 2017 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2017 Inter-Research.

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 score0.206
Threshold uncertainty score0.997

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.013
GPT teacher head0.221
Teacher spread0.209 · 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

Citations12
Published2017
Admission routes1
Has abstractyes

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