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Variation of population and community ecology over large spatial scales in Ediacaran early animal communities

2025· article· en· W4408996777 on OpenAlexaboutno aff
Emily G. Mitchell, Nile P. Stephenson, Princess A. Buma-at, Lucy Roberts, S Dennis, Charlotte G. Kenchington

Bibliographic record

VenueGlobal and Planetary Change · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicEvolution and Paleontology Studies
Canadian institutionsnot available
FundersBritish Geological SurveyNatural Environment Research CouncilLeverhulme Trust
KeywordsVariation (astronomy)EcologySpatial variabilityGeographyPopulationTemporal scalesSpatial ecologyBiologySociologyDemography

Abstract

fetched live from OpenAlex

The Ediacaran strata of Newfoundland, Canada (580–560 Ma) record some of the first animal communities. The in-situ preservation of these sessile organisms means that the positions and sizes of specimens on the bedding planes encapsulate their life-histories, enabling spatial analyses to reconstruct their ecological dynamics. However, it is not known how these Ediacaran ecological dynamics vary across large spatial scales. Fortunately, the E and G surfaces at Mistaken Point, Newfoundland (∼565 Ma) crop out at multiple locations, providing the opportunity to compare ecological dynamics between communities separated by large spatial scales (∼800 m). In this study, we collected data from two outcrops each of E and G surfaces using a combination of laser-line probe, LiDAR and photogrammetry. We mapped out Mistaken Point G surface over 7.22 m 2 , finding 9 frondose taxa across 158 specimens Watern Cove East G surface across 154 m 2 (93 m 2 when fractures are excluded) finding 19 frondose taxa across 1320 specimens; and Watern Cove West E Surface across 20.02 m 2 , finding 11 frondose taxa across 734 specimens. We compared the Watern Cove West E surface with previously collected data from Mistaken Point E Surface, which had 2977 specimens over 85.42 m 2 . The two G outcrops exhibited remarkably similar community compositions, both dominated by Bradgatia with high proportions of frondose rangeomorphs and arboreomorphs. In contrast, the compositions between the E surfaces were notably different, with Watern Cove West E surface showing relatively higher proportions of Fractofusus and Bradgatia and lower proportions of frondose taxa . For comparisons of population ecology between the outcrops, only Bradgatia (G) and Fractofusus (E) populations occurred in sufficient numbers to enable spatial analyses. We quantified the spatial distributions using spatial point process analyses, finding for E surfaces that the Fractofusus populations showed significantly similar spatial patterns, which indicated reproductive events. In contrast, on G surface, the Bradgatia populations show remarkably different underlying processes, with the Watern Cove East population showing reproductive clusters on a background environmental heterogeneity, whereas the Mistaken Point population shows spatial segregation, indicating intra-specific competition. The Watern Cove East Bradgatia have a much lower density than those on Mistaken Point, suggesting that the increased density leads to competition due to insufficient resources to maintain this higher density. In modern deep-sea benthic communities, increased population densities occur within communities when different areas are subject to different flow regimes, and so different nutrient flux. Our results suggest that the Ediacaran communities of Mistaken Point show variability in ecological dynamics, even while composition of these communities remain remarkably similar. • Multiple Ediacaran surfaces enable analysis of large-scale community ecology. • Biological differences in community composition are distinguishable from PFPs. • Density and community dynamics can differ even if community composition is consistent. • The only taxon with small-scale intra-specific competition has a large wake. • Ediacaran community but not regional ecology are comparable to modern.

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 score0.601
Threshold uncertainty score0.652

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)0.0000.000

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 head0.023
GPT teacher head0.242
Teacher spread0.219 · 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

Citations4
Published2025
Admission routes1
Has abstractyes

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