The Surales, Self-Organized Earth-Mound Landscapes Made by Earthworms in a Seasonal Tropical Wetland
Bibliographic record
Abstract
The formation, functioning and emergent properties of patterned landscapes have recently drawn increased attention, notably in semi-arid ecosystems. We describe and analyze a set of similarly spectacular landforms in seasonal tropical wetlands. Surales landscapes, comprised of densely packed, regularly spaced mounds, cover large areas of the Orinoco Llanos. Although descriptions of surales date back to the 1940's, their ecology is virtually unknown. From data on soil physical and chemical properties, soil macrofauna, vegetation and aerial imagery, we provide evidence of the spatial extent of surales and how they form and develop. Mounds are largely comprised of earthworm casts. Recognizable, recently produced casts account for up to one-half of total soil mass. Locally, mounds are relatively constant in size, but vary greatly across sites in diameter (0.5-5 m) and height (from 0.3 m to over 2 m). This variation appears to reflect a chronosequence of surales formation and growth. Mound shape (round to labyrinth) varies across elevational gradients. Mounds are initiated when large earthworms feed in shallowly flooded soils, depositing casts that form 'towers' above water level. Using permanent galleries, each earthworm returns repeatedly to the same spot to deposit casts and to respire. Over time, the tower becomes a mound. Because each earthworm has a restricted foraging radius, there is net movement of soil to the mound from the surrounding area. As the mound grows, its basin thus becomes deeper, making initiation of a new mound nearby more difficult. When mounds already initiated are situated close together, the basin between them is filled and mounds coalesce to form larger composite mounds. Over time, this process produces mounds up to 5 m in diameter and 2 m tall. Our results suggest that one earthworm species drives self-organizing processes that produce keystone structures determining ecosystem functioning and development.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".