Mathematical Models of Pattern Formation in Planktonic Predation-Diffusion Systems: A Review
Bibliographic record
Abstract
Plankton form the basis of aquatic food webs. The mathematical modelling of plankton dynamics was initiated by fisheries in the early 20th century. Today, the significant role of plankton in the global carbon cycle and, hence, in climate control has been recognized. The main aim of modelling is to improve understanding of the functioning of food chains and webs and their dependence on internal and external conditions. Population-dynamical models have not only to account for growth and interactions but also for spatial processes like random or directed and joint or relative motion of species as well as the variability of the environment. Early attempts began with exponential growth, Lotka-Volterra type interactions and physico-chemical diffusion. These approaches have been continuously refined to more realistic descriptions of the development of natural populations. The aim of this paper is to give an introduction to the subject of equation-based modelling and the corresponding bibliography, based on and extending previous reviews [1]–[5]. The fascinating variety of temporal, spatial and spatio-temporal patterns in such systems and the governing mechanisms of their generation and further evolution are described and related to plankton dynamics.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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 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".