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Record W2062430846 · doi:10.1111/ddi.12087

Unifying measures of biodiversity: understanding when richness and phylogenetic diversity should be congruent

2013· article· en· W2062430846 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueDiversity and Distributions · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSpecies richnessBiodiversityPhylogenetic diversityPhylogenetic treeEcologyBiogeographySpatial analysisGeographySpecies diversityBiologyEvolutionary biology

Abstract

fetched live from OpenAlex

Abstract Aim Biogeographical theory and conservation valuation schemes necessarily involve assessing how biodiversity is distributed through space and ‘biodiversity’ encapsulates many different aspects of biological organization and information. While biogeography may try to explain biodiversity patterns, successful conservation strategies should attempt to maximize different aspects of diversity. Ultimately, diversity patterns are the product of evolutionary history, and research and conservation efforts seek to understand the unequal distribution of evolutionary history. For conservation efforts, results have been inconsistent as to whether species richness ( SR ) provides sufficient surrogacy for evolutionary history. Here, we provide a conceptual framework allowing for the direct comparison of taxonomic richness and phylogenetic diversity ( PD ), both in terms of their mechanistic relationship and the relationship between their spatial distributions. Location Global. Methods We present a framework that relates regional SR , PD , biogeographically weighted evolutionary distinctiveness and biogeographically weighted SR . Further, we use simulations to illustrate how the size of the species pool, topological patterns within the phylogeny and autocorrelation in spatial distributions affect the correlation among metrics. Results In regions that include both recently diversified groups and ancient species poor lineages, large species pools and low spatial autocorrelation, the correlation between biodiversity measures is lower than regions with low richness, balanced phylogenetic trees and high spatial autocorrelation. Main conclusions We can now understand and predict when regional richness and PD should be strongly correlated. This congruency is the product of evolutionary and ecological processes that determine species pool membership and community assembly. Further, in regions where SR is not expected to be congruent with phylogenetic distinctiveness, re‐examining how existing reserve networks protect the multiple aspects of biodiversity is critically important.

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.

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 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 score0.008
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 studies0.0030.001
Scholarly communication0.0000.000
Open science0.0000.003
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 head0.101
GPT teacher head0.234
Teacher spread0.134 · 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