Planktonic biomass size spectra: an emergent property of size-dependent physiological rates, food web dynamics, and nutrient regimes
Bibliographic record
Abstract
The systematic change in a trait with size is a concise means of representing the diversity and organization of planktonic organisms. Using this simplifying principle, we investigated how interactions between trophic levels, resource concentration, and physiological rates structure the planktonic community. Specifically, we used 3 size-structured nutrient-phytoplankton-zooplankton models differing in their trophic interactions, ranging from herbivorous grazing on one size class to omnivorous grazing on multiple size classes. We parameterized our models based on an extensive review of the literature. The maximum phytoplankton growth, maximum microzooplankton grazing, and phytoplankton half-saturation constant were found to vary inversely with size, and the nutrient half-saturation constant scaled positively with size. We examined the emergent community structure in our models under 4 nutrient regimes: 10, 20, 25, and 30 M total N. In all models under all nutrient conditions, the normalized biomass of both phytoplankton and microzooplankton decreased with increasing size. As nutrients were in creased, phytoplankton biomass was added to larger size classes with little change in the extant smaller size classes; for microzooplankton, spectra elongated and biomass was added to all size classes. The different grazing behaviors among models led to more subtle changes in the community structure. Overall, we found that phytoplankton are top-down controlled and microzooplankton are largely bottomup controlled. Sensitivity analyses showed that both phytoplankton and microzooplankton biomass vary strongly with the size-dependence of the maximum grazing rate. Therefore, this parameter must be known with the greatest accuracy, given its large influence on the emergent community spectra.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".