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Record W7017863156

Changing environmental conditions and the response and potential adaptability of freshwater whitefishes

2022· article· en· W7017863156 on OpenAlexaboutno aff

Bibliographic record

VenueScholarWorks -A service of University of Vermont Libraries (University of Vermont) · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIncubationPhenologyAdaptabilityEgg incubationClimate changeLight intensityIce formation
DOInot available

Abstract

fetched live from OpenAlex

Changes in winter conditions, such as increased temperatures and decreased ice coverage, have been observed worldwide. The responses of many lake fish populations to changing winters are projected to be inadequate to counter the speed and magnitude of climate change. Such environmental changes have been hypothesized to explain the low recruitment observed in freshwater whitefishes (Salmonidae Coregoninae). My research focused on measuring the impact changing winter conditions may have on coregonine reproductive phenology and developmental and morphological traits to better predict changes in coregonine populations as a result of climate change. I used experimental incubation methods and modeling to explore how climate-induced changes in water temperature and ice coverage may impact coregonine adults during spawning and early-life stages within and among species. First, I experimentally evaluated the response of embryonic development to increasing water temperature for cisco (Coregonus artedi) from lakes Superior and Ontario, and vendace (C. albula) and European whitefish (C. lavaretus) from Lake Southern Konnevesi, Finland. Embryo survival, incubation duration, and length-at-hatch were inversely related to temperature whereas yolk-sac volume increased with temperature within study groups. However, responses varied in magnitude among study groups suggesting differential levels of developmental plasticity. Next, I quantified how cisco embryos from lakes Superior and Ontario responded to simulated changes in incubation light conditions representing 0-10 (high light), 40-60 (medium light), and 90-100% (low light) ice coverage. Embryo survival was highest under medium light, and light intensity had no effect on incubation duration. Increasing light intensity decreased length-at-hatch in Lake Superior but had no effect in Lake Ontario. Yolk-sac volume was positively correlated with increasing light in Lake Superior and negatively correlated in Lake Ontario. Contrasting responses between lakes suggest populations’ response to light is flexible. Furthermore, I analyzed different embryo incubation temperatures on post-hatching survival, growth, and critical thermal maximum of larval cisco from lakes Superior and Ontario. Larval survival and critical thermal maximum were negatively related to temperature, and larval growth was positively related to temperature. The magnitude of change was greater in Lake Superior than Lake Ontario for all traits examined, suggesting Lake Superior larvae may possess a more limited ability to acclimate to and cope with environmental change. Lastly, I used simulation modeling to investigate changes in reproductive phenology under climatic-warming scenarios for coregonine populations across the Laurentian Great Lakes and Europe. Models predicted that climate-induced increases in water temperatures may cause delayed spawning, shorter embryo incubation lengths, and earlier larval hatching. I quantified how climate change could affect coregonine populations, including changes in embryo development traits, reduced physiological condition of larvae, and shifts in reproductive phenology. Climate-induced responses of coregonines to changing environmental conditions are likely to vary within and among species and with the magnitude of climate warming. Management strategies that maximize phenotypic variability could improve the ability of coregonines to cope with environmental change.

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)0.001
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 score0.182
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0000.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.004
GPT teacher head0.140
Teacher spread0.136 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueScholarWorks -A service of University of Vermont Libraries (University of Vermont)Same topicFish Ecology and Management StudiesFrench-language works237,207