Quantifying mortality of modular organisms: a comparison of partial and whole‐colony mortality in a colonial bryozoan
Bibliographic record
Abstract
Abstract Comprehensive studies on the population dynamics of colonial organisms require estimates of mortality from the level of the individual module (partial mortality) to the entire colony (whole‐colony mortality), as well as determining the factors that affect mortality at each level of organization. However, accurate measurements of whole‐colony and partial mortality of modular organisms can be difficult to obtain, and few studies involve concurrent measurements of modular and colony mortality. We implemented multiple approaches to measure whole‐colony and partial mortality of modular species using the colonial bryozoan Membranipora membranacea as a model organism. M. membranacea is a cosmopolitan species and of particular ecological significance in the northwest Atlantic, where it is the dominant epiphyte on laminarian kelps and the main driver for the defoliation of kelp beds. Rates of whole‐colony mortality were measured in the field (1) indirectly through repeated subsampling cohort analyses and (2) directly by tagging colonies in situ. Partial mortality of colonies was measured (1) in the field by quantifying the proportion of degenerated zooids per colony and (2) in the laboratory by monitoring loss of colony surface area during seasonal senescence of colonies over winter. Temporal patterns differed substantially between partial and whole‐colony mortality, suggesting that factors affecting mortality of individual modules differ from those affecting whole colonies. Our study indicated that the accuracy of common methods for measuring mortality of modular organisms depends on the species‐specific life‐history characteristics. However, we suggest that rates and mechanisms of whole‐colony and partial mortality can be most accurately quantified by revisiting tagged individuals in situ and recording loss of entire colonies (whole‐colony mortality) and loss of living colony area (partial mortality) between successive sampling times. For M. membranacea, measuring whole‐colony or partial mortality in isolation would overestimate important demographic rates and underestimate the influence of temperature on mortality, respectively. This study demonstrates the need to include mortality measurements from the level of the individual module to the entire colony when quantifying population dynamics of colonial organisms.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".