Factors affecting meiofaunal colonization and assemblage structure in marine soft sediments
Bibliographic record
Abstract
Meiofauna are an abundant, diverse and important component of the marine biota, however, much of their ecology has been neglected. Despite their high densities, meiofaunal abundance is often patchy. Meiofauna present in high numbers at one site will often be less abundant in seemingly similar adjacent sites. What factors govern this variability? How readily do these animals colonize new patches? How do various biological and environmental factors affect meiofaunal colonization rate and resulting assemblage structure? The response of meiofauna to changes in abiotic factors, including sediment grain size, depth, exposure and distance from the ocean floor, was quite variable. Often one factor would affect certain taxa and not others. Even slight increases in depth resulted in drastic declines of harpacticoid copepods while nematodes were unaffected. Meiofauna were also fewer in sediments with large interstitial spaces. Some meiofauna were most abundant in sediments placed closer to the ocean floor. Other taxa colonized distant substrata as rapidly as they did substrate located closer to the ocean floor. This suggested differences between taxa in their rates of active dispersal. The effects of macrofauna on meiofauna have been debated. In particular, how do clams affect the colonization and assemblage structure of meiofauna? Certain characteristics of clams were isolated and evaluated: feeding behaviour, bioturbation rate/depth and metabolic byproducts. Clams that caused the greatest meiofauna declines were shallow burrowing deposit-feeders. Constant disturbance to the upper sediment by these clams was likely responsible for meiofaunal impact. Conversely, suspensionfeeding clams that passed quickly to deeper sediment and remained stationary had little impact on meiofauna. Finally, a survey of local marine nematodes added nine genera new to Canada and 24 genera new to British Columbia. A review was also compiled that shows nematodes and other meiofauna have been neglected for much of Canada. Although these small and abundant animals are quick to colonize even distant habitats they are quite sensitive to cues from the surrounding biotic and abiotic environment. This sensitivity combined with their ease of collection make meiofauna a valuable asset to any number of ecological investigations.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".