Why is the world green? The interactions of top–down and bottom–up processes in terrestrial vegetation ecology
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A classic question in plant ecology is “why is the world green?” That is, if plants are food for animals why do not animals eat all the available food – changing a ‘green world’ into a ‘brown world’. We first reviewed this question in 2009 and now revisit our arguments in the light of new data and new thinking. Here we argue that (1) the top–down bottom–up dichotomy is probably too simple for understanding a complex system – such as vegetation – rich in feedback processes. (2) Nevertheless it appears that bottom–up processes are generally more important for maintaining the presence of some sort of vegetation while top–down control process are generally more important in determining the type of vegetation at a site. (3) Although this review mainly takes a qualitative and experimental approach to the question, we also argue that simple well-known mathematical models from population ecology can be very informative in thinking about the types of explanations for the green world phenomenon, and demonstrating that it is rarely a simple choice between one form of control or another.
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.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it