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Record W3019494316 · doi:10.1007/s10750-020-04258-2

Local and regional environmental factors drive the spatial distribution of phototrophic biofilm assemblages in Mediterranean streams

2020· article· en· W3019494316 on OpenAlexfundno aff
Nina H. Witteveen, Anna Freixa, Sergi Sabater

Bibliographic record

VenueHydrobiologia · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicFreshwater macroinvertebrate diversity and ecology
Canadian institutionsnot available
FundersAgencia Estatal de InvestigaciónMinisterio de Ciencia e InnovaciónUniversiteit van AmsterdamErasmus+Centres de Recerca de CatalunyaCanadian Institute for Advanced ResearchEuropean CommissionMinistry of Science and Technology
KeywordsEcologySTREAMSPhototrophEnvironmental scienceCyanobacteriaHabitatMediterranean climateAlgaeRiffleBiologyPhotosynthesisBotany

Abstract

fetched live from OpenAlex

Abstract Temporary streams are submitted to high seasonal hydrological variations which induce habitat fragmentation. Global change promotes longer non-flow periods, affecting hydrological continuity and the distribution of biological assemblages in river networks. We aimed to investigate the effects of hydrological discontinuity on phototrophic biofilm assemblages in a Mediterranean stream, at both network and habitat scales. At the network scale during basal flow conditions, mostly nitrate and DOC concentrations were associated to the taxonomical and trait distribution of algae and cyanobacterial assemblages. Cyanobacteria dominated at the upstream and downstream sites of the network, while green algae and diatoms were abundant in its middle part. At the habitat scale, hydrological discontinuity promoted large changes in biofilm composition between riffles and pools, where pools were inhabited preferentially by green algae and riffle habitats by cyanobacteria. Our findings emphasize the myriad of factors affecting the spatial distribution of phototrophic biofilms, which become more heterogeneous according to water flow interruption. Under the predicted climate change scenarios, spatial heterogeneity in temporary streams may increase, which will lead to change phototrophic biofilm assemblages.

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 score0.099
Threshold uncertainty score0.857

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.183
Teacher spread0.167 · 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

Citations20
Published2020
Admission routes1
Has abstractyes

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