The ecological dynamics of early and modern soft-bodied marine animal ecosystems
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".