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Record W2156079526 · doi:10.4319/lo.2008.53.4.1319

Typhoons initiate predictable change in aquatic bacterial communities

2008· article· en· W2156079526 on OpenAlexfundno aff
Stuart E. Jones, Chih‐Yu Chiu, Timothy K. Kratz, Jiunn‐Tzong Wu, Ashley Shade, Katherine D. McMahon

Bibliographic record

VenueLimnology and Oceanography · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsnot available
FundersAcademia SinicaNational Science CouncilUniversity of Wisconsin-MadisonGlobal Lake Ecological Observatory NetworkGordon and Betty Moore FoundationNational Science Foundation
KeywordsTyphoonBacterioplanktonEpilimnionHypolimnionEnvironmental scienceWater columnPhytoplanktonEcologyEcological successionOceanographyBiologyGeologyNutrient

Abstract

fetched live from OpenAlex

We explored patterns of change in bacterioplankton and phytoplankton community composition in response to typhoons in a subtropical, subalpine freshwater humic lake in Taiwan. Thermal profiles with depth, nearsurface dissolved oxygen, and meteorological conditions were measured at high temporal resolution using an instrumented buoy. We collected samples across a time series spanning two typhoon seasons and assessed bacterial community composition at each time point using a fingerprinting technique targeting the internal transcribed spacer region of the ribosomal RNA operon. Wind and rain associated with the typhoons mixed the otherwise stably stratified water column. After each of six typhoon‐induced mixing events, the bacterial community composition was reset to similar conditions, revealing a surprisingly deterministic pattern of recovery that was reminiscent of secondary succession following large infrequent disturbances in terrestrial ecosystems. Distinct bacterial assemblages were associated with epilimnion and hypolimnion samples collected more than 80 d after a mixing event. These assemblages were also distinct from the communities observed in the generally unstratified water column within 7 d after a typhoon. Our results were surprising since bacterial communities are not expected to respond in such predictable ways because of their immense complexity and diversity. In contrast, phytoplankton communities did not recover in a predictable way after typhoons.

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 score0.011
Threshold uncertainty score0.998

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.032
GPT teacher head0.223
Teacher spread0.192 · 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

Citations86
Published2008
Admission routes1
Has abstractyes

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