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Record W7006490470

Understanding How Northern North American Freshwater Fishes are Responding to Rapid Environmental Change

2021· other· en· W7006490470 on OpenAlexaboutno aff

Bibliographic record

VenueYork University Digital Library (York University) · 2021
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsSubarctic climateEnvironmental changeAbundance (ecology)Climate changeFreshwater fishFreshwater ecosystemBiodiversitySTREAMSRelative species abundanceSpatial ecology
DOInot available

Abstract

fetched live from OpenAlex

Many northern fishes are experiencing unprecedented environmental changes across their ranges. However, limited empirical evidence exists for understanding how these changes may combine and potentially interact to influence fish diversity, individual species loss and gains, and overall productivity at broad spatial scales relevant for informing evidence-based conservation and management efforts. \n \nThis dissertation investigated how northern fishes are being impacted by cumulative and potentially interacting environmental changes across broad spatial scales including climate change, water quality, and land use. I examined two main research questions including 1) what are the key environmental variables currently influencing northern freshwater fishes? And 2) how is climate interacting with other variables to produce non-additive effects (i.e., antagonistic or synergistic interactions). To do this, I used fish community data from small streams across relatively intact regions of Alaska, small boreal streams in a more developed region of Alberta, Canada, and subarctic lakes in a rapidly changing permafrost region in the lower Mackenzie River basin. \n \nWarming temperatures were linked to increased community diversity and abundance in small streams. However, this trend was not observed for fish communities in small subarctic lakes, where water quality degradation appeared to have a stronger role in regulating fish community health than direct warming. In all three chapters, there was evidence for localized gains and losses of individual fish species presence or relative abundance in association with mounting environmental changes that included warming, changes in precipitation, and land use. Some species may be temporarily benefiting from warmer conditions across their northern ranges, for example, Pacific salmon species including Coho Oncorhynchus kisutch, Chinook Oncorhynchus tshawytscha, and Sockeye Oncorhynchus nerka appeared to be experiencing a net distribution gain possibly due to warmer and longer growing seasons. In contrast, species declines associated with environmental changes were more likely to occur for Arctic specialists, species intolerant to environmental degradation, and large-bodied benthic species. Interactions between climate warming and land use were synergistic (i.e., the combined effect of both stressors was greater than the sum of their individual effects), highlighting the potential for amplified species declines under future warming and land use scenarios. Together, these results provide new information that can be used to inform improved northern conservation planning amid rapid environmental changes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.941
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
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 head0.046
GPT teacher head0.167
Teacher spread0.121 · 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 source (direct Gemma or distilled Codex), 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
Published2021
Admission routes1
Has abstractyes

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