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Record W2518642596 · doi:10.1080/iw-6.3.844

Absence of winter and spring monsoon changes water level and rapidly shifts metabolism in a subtropical lake

2016· article· en· W2518642596 on OpenAlexaff
Jeng‐Wei Tsai, Timothy K. Kratz, James A. Rusak, Wan-Yu Shih, Wen‐Cheng Liu, Sen-Lin Tang, Chih‐Yu Chiu

Bibliographic record

VenueInland Waters · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsMinistry of the Environment, Conservation and ParksQueen's University
FundersAcademia SinicaNational Science Foundation
KeywordsEnvironmental scienceEcosystem respirationEcosystemAutotrophPrimary productionThermoclineNutrientBiomass (ecology)Water levelStratification (seeds)SubtropicsWater columnOceanographyMonsoonHydrology (agriculture)EcologyGeologyBiologyAgronomyGeography

Abstract

fetched live from OpenAlex

We investigated how the lack of usual winter and spring monsoons, effectively representing consecutive drought events, affected the dynamics of ecosystem metabolism in a shallow mesotrophic seepage lake in northeastern Taiwan. An instrumented buoy provided high-frequency free-water dissolved oxygen measurements, water temperature profiles, and meteorological data, which we used to estimate daily values of gross primary production (GPP), ecosystem respiration (R), and net ecosystem production (NEP). Results revealed that the disappearance of monsoons decreased lake level and volume, concentrated dissolved nutrients, stimulated the development of algal biomass, promoted stratification, and resulted in a major shift in lake metabolism. Offshore GPP and R were both initially stimulated but then decreased due to shallower mixing depths in the water column. The lake rapidly shifted from a heterotrophic state to a highly autotrophic status when the water level dropped to the lowest level. A return to autotrophy was caused by a greater decline in R than an increase in GPP. This study demonstrates the dramatic effect that drought events can have on lake ecosystem function and suggests that nutrient control may be important in mitigating the effects of a predicted warmer and drier climate and increased water withdrawal in this region.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.177

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)0.0000.000

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 head0.201
Teacher spread0.188 · 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.

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

Citations11
Published2016
Admission routes1
Has abstractyes

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