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Record W2086130177 · doi:10.1086/587520

Scale Dependence of Species‐Energy Relationships: Evidence from Fishes in Thousands of Lakes

2008· article· en· W2086130177 on OpenAlexafffund
Tariq Gardezi, Andrew Gonzalez

Bibliographic record

VenueThe American Naturalist · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsMcGill University
FundersCanada Research ChairsMinistry of Natural Resources
KeywordsSpecies richnessEcologyOccupancyAbundance (ecology)Spatial ecologyScale (ratio)MacroecologyBeta diversitySpecies diversitySpatial variabilityBiologyGeographyStatisticsCartography

Abstract

fetched live from OpenAlex

Variation in the shape of relationships between species richness and different measures of energy may be linked to variation in the spatial scale on which such relationships are measured. We examine scale dependence in the relationship between potential evapotranspiration and the species richness of fishes in 7,885 postglacial lakes. The strength of this relationship is weak across lake communities but strong and positive across groups of lakes or regions. In addition, the strength and slope of this relationship increase significantly as the regional scale of analysis is increased. We interpret the observed patterns in terms of a simple model whereby energy influences the linear character of the species-energy relationship through its influence on spatial turnover in the species composition (beta diversity). Our results suggest that if energy is strongly tied to patterns of site occupancy or abundance, the parameters of species-energy relationships will depend, to a considerable extent, on the scale of measurement. Furthermore, the ability of high-energy regions to accommodate relatively large numbers of rare or infrequent species may underlie any general tendency for the strength or shape of species-energy relationships to change with scale.

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 score0.028
Threshold uncertainty score0.998

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 studies0.0000.002
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 head0.028
GPT teacher head0.234
Teacher spread0.206 · 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

Citations31
Published2008
Admission routes2
Has abstractyes

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