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Record W6999793596

Development and Application of Periphyton-Based Biomonitoring Methods to Elucidate Aquatic Ecosystem Responses of Lakes in a Water-Rich Northern Landscape (Old Crow Flats, Yukon, Canada) to Climate Change

2022· dissertation· en· W6999793596 on OpenAlexaboutno aff

Bibliographic record

VenueUWSpace (University of Waterloo) · 2022
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsEcoregionSubarctic climateThermokarstWetlandClimate changePermafrostArcticEcosystemHabitatResource (disambiguation)
DOInot available

Abstract

fetched live from OpenAlex

Shallow freshwater lakes are abundant in Arctic and subarctic regions, where they provide important wildlife habitat and sustain the cultural heritage and traditional land use of Indigenous communities. Concern over effects of climate change on shallow northern lakes, including warming and associated increase of evaporation and shifts in precipitation, however, elicits a need for agency-led, long-term, biomonitoring programs to implement protocols applicable across large, remote landscapes. My research focuses on lakes of the Old Crow Flats (OCF), a 5,600 km2 lake-rich thermokarst landscape in northern Yukon recognized as a Ramsar Wetland of International Importance for ecosystem services provided to wildlife and the Vuntut Gwitchin First Nation (VGFN). There, climate warming has raised uncertainty about sustainability of traditional activities in the landscape and challenges natural resource stewardship. The research employs analysis of periphytic diatom community composition accrued on artificial-substrate samplers and water chemistry in lakes of the Old Crow Flats (Yukon Territory, Canada), where spatial and temporal variation in input water sources and water balance has been characterized using water isotope tracers, to explore the ability of diatoms to discern ecological responses to shifts in basin hydrology. The findings are reported in two data chapters. One chapter explores spatial variation across a set of lakes that span the hydrological gradients of OCF during ice-free seasons of 2008 and 2009. The other chapter assesses temporal variation at 14 lakes during a 12-year-long monitoring period (2008-2019) when water isotopes document increasing input of rainfall and possibly permafrost thaw on their water balance. \nResults of multivariate analyses based on the spatial data set (33 and 48 lakes sampled in 2008 and 2009, respectively) demonstrate that water chemistry and diatom community composition differ among three isotope-defined hydrological lake categories based on differences in input water sources (snowmelt-dominated, rainfall-dominated, intermediate). Some snowmelt-dominated lakes support moderate percent abundances of Rossithidium pusilla, Sellaphora laevissima, Tabellaria flocculosa str. III and T. fenestrata, associated with relatively high concentrations of major nutrients and dissolved organic carbon (DOC). Rainfall-dominated lakes have higher pH and ion content, yet diatom composition overlapped extensively with intermediate and snowmelt-dominated lakes. Water chemistry and diatom community composition did not differ between study years, despite almost four-fold greater snowfall in 2009. Overall, the results reveal that periphytic diatom communities on artificial-substrate samplers capture ecological differences across hydro-limnological gradients of Old Crow Flats, but longer time-series of data are required to assess their ability to track temporal responses to hydro-climatic variation. \nThe spatial dataset of OCF lakes sampled during 2008 and 2009 for analysis of periphytic diatom community composition and water chemistry was used to inform interpretations of temporal changes in diatom community composition that accrued on artificial substrate samplers deployed during thaw seasons of a 12-year period (2008-2019) at 14 long-term monitoring (LTM) lakes and infer shifts in water chemistry. Ordination by CCA reveals that periphytic diatom communities at 10 of the 14 LTM lakes (71.4%) converged towards composition typical of lakes with rainfall-dominated input waters by 2019 due to relatively high or rising percent abundance of the diatom taxa Achnanthidium minutissimum, Gomphonema angustum, G. capitatum, Diatoma tenuis, and/or Eunotia obscurum. These include 4 of the 5 lakes that were dominated by rainfall input water at the beginning of the monitoring period (OCF 29, 37, 38, 49), where diatom community composition remained relatively unchanged, as well as 5 of the 6 lakes that began in the intermediate category (OCF 19, 34, 35, 46, 48), and one of the 3 lakes that began in the snowmelt-dominated category (OCF 58). Four of the 14 LTM lakes reveal patterns of change that are not consistent with a shift towards diatom communities typical of rainfall-dominated lakes. These include two lakes (OCF 26, 55) where diatom community composition remained relatively constant during the entire monitoring period and indicative of conditions typical of lakes with snowmelt-dominated inflow. They also include a lake that recently drained (OCF 6) and a lake with a particularly large catchment area (OCF 11) where Cocconies lineata dominated diatom communities and where basin hydrology appears to be strongly influenced by both rainfall and snowmelt input. Overall, these findings suggest that composition of periphytic diatom communities on artificial-substrate samplers tracks aquatic ecosystem responses to temporal trends in climate-mediated hydrological 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 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)0.000
metaresearch head score (Gemma)0.000
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 score0.676
Threshold uncertainty score0.643

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.021
GPT teacher head0.242
Teacher spread0.222 · 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
Published2022
Admission routes1
Has abstractyes

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