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Record W2288843383 · doi:10.2495/eco030111

The Use Of Taxonomic Diversity Indices In The Assessment OfPerturbed Community Recovery

2003· article· en· W2288843383 on OpenAlexaboutno aff
Rachelle E. Desrochers, Madhur Anand

Bibliographic record

VenueWIT Transactions on Ecology and the Environment · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEntropy (arrow of time)EcologyGamma diversitySpecies diversityDiversity indexMathematicsTaxonomic rankAlpha diversitySpecies richnessBiology

Abstract

fetched live from OpenAlex

The spatial dynamics of ecological diversity are studied in two regions (Sudbury, Canada and Harjavalta, Finland) damaged by air pollution from copper and nickel smelting. Perturbation from pollution is assumed to be most intense near the source and to decrease with distance. Monitoring sites were therefore selected to traverse these pollution gradients. Using Rhyi's generalized entropy as a measure of diversity, a monotonic pattern of increasing diversity is discovered at the recovering Canadian sites but not at the Finnish sites. Quadratic entropy and a related information-theoretical measure of taxonomic diversity, taxonomic entropy, were calculated in the hope that these diversity indices, which incorporate taxonomic distances, would provide a better understanding of these unexpected results. Quadratic entropy has the additional advantage of making use of pairwise taxonomic distances between species in a highly intuitive manner. Taxonomic has a clear information-theoretical meaning and can be calculated in the same units of measurement as Rknyi's generalized entropy thereby facilitating the comparison of classical diversity to taxonomic diversity. Quadratic entropy was found to contribute little insight as to the state of ecological recovery relative to taxonomic entropy.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.198
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
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 head0.024
GPT teacher head0.210
Teacher spread0.186 · 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.

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

Citations4
Published2003
Admission routes1
Has abstractyes

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