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Broad‐scale environmental response and niche conservatism in lacustrine diatom communities

2010· article· en· W1484080307 on OpenAlexafffund
Joseph Bennett, Brian F. Cumming, Brian K. Ginn, John P. Smol

Bibliographic record

VenueGlobal Ecology and Biogeography · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsLake Simcoe Region Conservation AuthorityQueen's UniversityUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiological dispersalNicheEcological nicheEcologyGeographyConservatismMacroecologyDiatomPropaguleScale (ratio)Spatial ecologyCommunityPhysical geographyBiologyBiogeographyHabitatCartographyDemographyPopulation

Abstract

fetched live from OpenAlex

ABSTRACT Aim (1) To resolve theoretical debates regarding the role of environment versus dispersal limitation, the conservatism of niches across distances and the prevalence of environmental specialists in diatom communities. (2) To provide guidance on the use of diatom communities and other microbial analogues to analyse ecological response to environmental change. Location Eight hundred and ninety‐one lakes in five regional datasets from north‐western Europe and four regional datasets from north‐eastern North America. Methods Lacustrine diatom communities were analysed at three scales: inter‐continental, intra‐continental and regional. Nested partial redundancy analyses (RDAs) were used to determine spatial versus environmental components of community variation. Weighted‐averaging (WA) regression and calibration, as well as logistic and quadratic regressions, were used to detect niche conservatism and the prevalence of environmental specialists. Results Community patterns indicate that dispersal limitation acts predominantly at the inter‐continental scale, while at the regional (less than c. 1,000,000 km2) scale, a single environmental variable (pH) explains more than five times the community variation as spatial (dispersal‐related) variables. In addition, pH niche components appear to be conserved at the inter‐continental scale, and environmental specialization does not impose relative rarity, as specialists apparently readily disperse to suitable environments. Main conclusions Analysis at multiple scales is clearly important in determining the influences of community variation. For diatom communities, dispersal limitation acts most strongly at the broadest scales, giving way to environment at the scales considered by most analyses. The availability of a wide variety of propagules with consistent niches across regions indicates that diatom communities reflect the succession of taxa according to local environmental conditions, rather than disequilibrium with the environment or adaptation of local populations. While multi‐scale analyses must be undertaken for other groups to resolve debates over community drivers and determine appropriate scales for prediction, for diatoms (and probably other microbial communities), responses to environmental change can be inferred using analogue datasets from large geographic areas.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.007
GPT teacher head0.210
Teacher spread0.204 · 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

Citations102
Published2010
Admission routes2
Has abstractyes

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