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Record W2766452046 · doi:10.1111/fwb.13043

Increased risk of cyanobacterial blooms in northern high‐latitude lakes through climate warming and phosphorus enrichment

2017· article· en· W2766452046 on OpenAlexafffundabout
Anna Przytulska, Maciej Bartosiewicz, Warwick F. Vincent

Bibliographic record

VenueFreshwater Biology · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsUniversité LavalCenter for Northern Studies
FundersFonds de recherche du Québec – Nature et technologiesNetworks of Centres of Excellence of CanadaNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for Innovation
KeywordsPhytoplanktonEnvironmental scienceDominance (genetics)PermafrostSubarctic climateEcologyOceanographyBloomClimate changeChlorophyll aBiomass (ecology)Water columnNutrientGeologyBiology

Abstract

fetched live from OpenAlex

Abstract Harmful cyanobacterial blooms are an increasing problem at many locations throughout the world but are rarely reported in aquatic habitats at high latitudes. Shallow lakes are a major feature of northern permafrost landscapes and are likely to experience large‐scale changes in their limnological properties in the future as a consequence of climate warming. In the present study, we addressed the question of what preconditions would be necessary to stimulate the growth and dominance of bloom‐forming cyanobacteria in northern fresh waters. We analysed the summer phytoplankton of 18 lakes on eroding permafrost (thaw lakes) and on glacier‐scoured rock (rock basin lakes) in subarctic Quebec, Canada, to determine their phytoplankton community structure and the biomass contribution of cyanobacteria. This survey was complemented with an incubation experiment to evaluate the direct warming and indirect phosphorus (P) enrichment effects of climate change on cyanobacterial bloom development. All lakes contained diverse phytoplankton communities, often dominated by chrysophytes, dinoflagellates and chlorophytes. Cyanobacteria were present in all waterbodies, but their contribution to the total community biovolume was highly variable (mean of 8.7%, range 0.1%–47%). Cyanobacterial community biovolumes correlated positively with surface water temperatures, and negatively with dissolved organic carbon, soluble reactive phosphorus, iron and manganese concentrations in the surface waters. Phosphorus enrichment of water from a thaw lake resulted in a fourfold increase of chlorophyll a (Chl‐ a ) and an increase in the cyanobacterial pigments echinenone and zeaxanthin. The phytoplankton counts showed that there was a sharp decrease in diversity (expressed as decline of the Shannon–Wiener index from 1.69 to 0.16), accompanied by a shift to cyanobacterial dominance, notably by the heterocystous, potentially toxic species Dolichospermum cf. planctonicum . Increased temperature led to an initial doubling of cyanobacterial biovolume, followed by the development of a chrysophyte bloom. Combined warming and P enrichment led to reduced phytoplankton biodiversity, with a community composed of cyanobacteria and chrysophytes. There was also a pronounced response by the picophytoplankton community; picocyanobacteria were strongly stimulated by P enrichment, while picoeukaryotes increased in response to warming. The current inoculum levels of cyanobacteria in subarctic lakes and their responsiveness to temperature and phosphorus indicate the potential for an abrupt increase in their abundance, accompanied by a decrease in phytoplankton diversity. Ongoing climate change will increase the risk of noxious cyanobacterial blooms in northern lakes and ponds, with potentially negative consequences for higher trophic levels.

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 score0.430
Threshold uncertainty score0.837

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 head0.009
GPT teacher head0.212
Teacher spread0.203 · 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

Citations67
Published2017
Admission routes3
Has abstractyes

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