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Record W7140129827 · doi:10.17863/cam.128633

The ecological dynamics of early and modern soft-bodied marine animal ecosystems

2025· dissertation· en· W7140129827 on OpenAlexaboutno aff
Nile P. Stephenson

Bibliographic record

VenueApollo (University of Cambridge) · 2025
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Stratigraphy of Fossils
Canadian institutionsnot available
Fundersnot available
KeywordsEcosystemBiodiversityBiological dispersalCoral reefReefBiotaEnvironmental changePopulation

Abstract

fetched live from OpenAlex

Summary The first widespread animals constitute the Avalon assemblage (574–560 million years ago), largely preserved in the late Ediacaran rocks of Newfoundland, Canada, and Charnwood Forest, Leicestershire, UK. The Avalon assemblage represents the pivotal shift from the microbially-dominated Neoproterozoic world to the complex, animal-mediated ecosystems of the Phanerozoic. Using these fossils to understand the evolution of animals is challenging because of few homologies with extant organisms. However, these soft bodied, enigmatic animals were preserved in exceptional settings as in situ, near-census communities, allowing the study of their population and community ecology, and thus their evolutionary drivers. Modern ecosystems are also navigating a critical transition; in the past century, anthropogenic changes imposed on the Earth system have caused a biodiversity crisis. Few ecosystems are as impacted by anthropogenic change as tropical coral reefs which are important because they provide key services to humans (provision of food stocks, protection from storms) and support ~25% of all marine biodiversity. Reefs are changing in composition with changing climate. In particular, besides algae, soft corals are also increasing in prevalence, but little is known about how soft corals impact the ecological dynamics, and thus the services and biodiversity, of coral reefs. Crucially, both the Avalon biota and the soft corals are potentially key players in transitional moments in the extinct and modern Earth system, respectively. In Chapter 1, I investigated ecological succession in the Avalon and found that community assembly is dependent on dispersal processes leading to distinct “community types” which do not change as the communities mature, and that epifaunal tiering is present depending on the morphology of dominant taxa. However, I also found that the taxa that underpin tiering processes are the first to go extinct, indicating over-specialisation in the Avalon. In Chapter 2, I interrogated the role of secondary successions and disturbance-adaptation in community assembly in the Avalon. I found that fragmentary reproductive modes provided a successful post-disturbance re-colonisation strategy, but that survival of disturbance events by exceptionally large organisms did not pose local recolonisation advantages. Together, these chapters highlight the importance of long-distance dispersal and disturbance in early animal communities. In Chapter 3, I investigated the population ecology of a soft coral-dominated reef in Fiji and found that depth, dispersal limitation, and small-scale habitat variations were the key drivers of population dynamics. In Chapter 4, I elucidated the impacts of soft corals on the ecosystem dynamics of Fijian reefs. I found that the dominance of soft corals versus scleractinians was largely driven by depth, and that ecosystem dynamics are markedly different on reefs where soft corals are dominant. I also found that soft coral systems had significantly lower biodiversity than scleractinian systems, highlighting the potential impact of increasing soft corals in future climate change scenarios. In Chapter 5, I synthesised a comparison of these extinct and extant systems, highlighting the importance of ecological innovation at the dawn of animal life and the incipient regression of ecological actors in benthic ecosystems driven to collapse by anthropogenic climate change.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.023
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.187
Teacher spread0.180 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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