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Record W7109680352 · doi:10.26108/0pj9-9j44

The physical limnology of two shallow organic lakes in Nova Scotia : vulnerability and senstivity [sic] to short-term climate change

2004· article· en· W7109680352 on OpenAlexaboutno aff

Bibliographic record

VenueAcadiaU-DEV · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsProfundal zoneLittoral zoneClimate changeLimnologyStructural basinHydrology (agriculture)Water quality

Abstract

fetched live from OpenAlex

To interpret lake sediment records in terms of fluctuating climate it is necessary to understand contemporary processes operating in shallow lakes and within their catchments. Although these lakes comprise significant habitat for a wide variety of species, very little is understood about how climate change will affect their physical state. Canoran Lake, Lunenburg Co. and Sandy Lake, Annaopolis Co. have similar volumes, areas, and elevations but have unique basin morphometries. Datalogged thermistor strings were placed in the littoral zones, profundal zones and the canopy of both lakes from May — August, 2003. The water quality characteristics were determined using a wide variety of standard analyses. Canoran Lake is a complex basin with two profundal zones and a discontinuous, vegetated littoral zone. Sandy Lake has one profundal basin and a continuous, largely unvegetated littoral zone. Thermal results indicated that these two lakes reacted uniquely to both daily and longer term thermal variation. Profundal lake temperatures remained nearly constant in Canoran Lake but increased consistently in Sandy Lake. At both sites, profundal temperatures were unaffected by short-term thermal variation. These results indicate that Sandy Lake is more sensitive to summer air mass circulation changes, possibly as a result of its simple basin shape which simplifies the transfer of heat through the water column, but Canoran Lake is more vulnerable to climate change because the sill separating the two basins impedes heat transfer. Though these changes are subtle, they are anticipated to have a significant affect on productivity. Thermal sensitivity models based on these data will allow ecologists to better understand how the lake (as habitat) will evolve and are essential to the implementation of species monitoring and conservation programs.

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 score0.111
Threshold uncertainty score0.904

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 head0.020
GPT teacher head0.274
Teacher spread0.254 · 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

Citations0
Published2004
Admission routes1
Has abstractyes

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