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Species richness and diversity in different functional groups across environmental stress gradients: a model for marine rocky shores

2010· article· en· W2113361237 on OpenAlexafffundabout
Ricardo A. Scrosati, Barbara van Genne, Christine Heaven, Cortney A. Watt

Bibliographic record

VenueEcography · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsSt. Francis Xavier University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsMcGill University
KeywordsSpecies richnessIntertidal zoneBiotaEcologyAbiotic componentRocky shoreBenthic zoneHabitatInvertebrateGeographyEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

We present a model predicting how the species richness and diversity within benthic functional groups should vary across the full environmental stress gradient across which a regional biota from marine rocky shores can occur. Built upon previous models, our model makes predictions for sessile species (macroalgae and filter feeders), herbivores, and carnivores. We tested some of its predictions by surveying vertical (intertidal elevation) and horizontal (wave exposure and ice scour) stress gradients in northern Nova Scotia, Canada. Because of harsh winter conditions, these coasts only depict approximately intermediate‐to‐high yearly levels of stress that the cold‐temperate, rocky intertidal biota from the northwestern Atlantic can experience. The observed trends matched predictions for sessile species in 75% of the studied gradients, and showed a moderate agreement for herbivores and carnivores only when they were combined as mobile consumers. Agreement meant that both richness and diversity increased from the most stressful to the most benign habitats that can be found in northern Nova Scotia. Also as predicted, sessile species generally showed a faster rate of increase in richness than mobile consumers. Our model also predicted a higher overall richness for sessile species than for mobile consumers, which was true by a factor of 3. Therefore, our model may constitute a useful tool to understanding community composition as a function of abiotic stress, which may in turn facilitate studies on community functioning. Model predictions for lower stress ranges could be tested on more southern shores where the same regional biota occurs.

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 score0.068
Threshold uncertainty score0.948

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)0.0010.000

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 head0.014
GPT teacher head0.180
Teacher spread0.166 · 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

Citations58
Published2010
Admission routes3
Has abstractyes

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