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Record W2080374247 · doi:10.1666/08024.1

Fidelity of variation in species composition and diversity partitioning by death assemblages: time-averaging transfers diversity from beta to alpha levels

2009· article· en· W2080374247 on OpenAlexfundno aff
Adam Tomášových, Susan M. Kidwell

Bibliographic record

VenuePaleobiology · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
FundersMcGill UniversityNational Oceanic and Atmospheric AdministrationUniversity of Chicago
KeywordsBeta diversityAbundance (ecology)Composition (language)EcologyVariation (astronomy)BiologyAlpha diversityGamma diversitySpatial ecologySpatial variabilitySpecies diversityBiodiversityStatisticsMathematics

Abstract

fetched live from OpenAlex

Despite extensive paleoecological analyses of spatial and temporal turnover in species composition, the fidelity with which time-averaged death assemblages capture variation in species composition and diversity partitioning of living communities remains unexplored. Do death assemblages vary in composition between sites to a lesser degree than do living assemblages, as would be predicted from time-averaging? And is the higher number of species observed in death relative to living assemblages reduced with increasing spatial scale? We quantify the preservation of spatial and temporal variation in species composition using 11 regional data sets based on samples of living molluscan communities and their co-occurring time-averaged death assemblages. (1) Compositional dissimilarities among living assemblages (LA) within data sets are significantly positively rank-correlated to dissimilarities among counterpart pairs of death assemblages (DA), demonstrating that pairwise dissimilarity within a study area has a good preservation potential in the fossil record. Dissimilarity indices that downplay the abundance of dominant species return the highest live-dead agreement of variation in species composition. (2) The average variation in species composition (average dissimilarity) is consistently smaller in DAs than in LAs (9 of 11 data sets). This damping of variation might arise from DAs generally having a larger sample size, but the reduction by ∼10–20% mostly persists even in size-standardized analyses (4 to 7 of 11 data sets, depending on metric). Beta diversity expressed by the number of compositionally distinct communities is also significantly reduced in death assemblages in size-standardized analyses (by ∼25%). This damping of variation and reduction in beta diversity is in accord with the loss of temporal resolution expected from time-averaging, without invoking taphonomic bias (from differential preservation or postmortem transportation) or sample-size effects. The loss of temporal resolution should directly reduce temporal variation, and assuming time-for-space substitution owing to random walk within one habitat and/or temporal habitat shifting, it also decreases spatial variation in species composition. (3) DAs are more diverse than LAs at the alpha scale, but the difference is reduced at gamma scales because partitioning of alpha and beta components differs significantly between LAs and DAs. This indicates that the effects of time-averaging are reduced with increasing spatial scale. Thus, overall, time-averaged molluscan DAs do capture variation among samples of the living assemblage, but they tend to damp the magnitude of variation, making them a conservative means of inferring change over time or variation among regions in species composition and diversity. Rates of temporal and spatial species turnover documented in the fossil record are thus expected to be depressed relative to the turnover rates that are predicted by models of community dynamics, which assume higher temporal resolution. Finally, the capture by DAs of underlying variation in the LA implies little variation in the net preservation potential of death assemblages across environments, despite the different taphonomic pathways suggested by taphofacies studies.

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)0.007
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
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 head0.031
GPT teacher head0.237
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 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

Citations124
Published2009
Admission routes1
Has abstractyes

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