Bibliographic record
Abstract
Predicting how gradual changes in abiotic conditions affect ecosystem functioning is a key challenge in ecology and environmental science. For many ecosystems, the response to gradual changes may not be smooth, but rapid and almost irreversible shifts in ecosystem states may occur. Early warning signals for such catastrophic shifts are difficult to obtain. Recent research suggests that so-called self-organized patchiness (regular spatial vegetation patterning) can serve as an indicator for such sudden changes. Self-organized patchiness has been observed in a variety of ecosystems, including peatlands. Most research has focused on linear patterns along the contours of peatland slopes. More recently, aerial photographs from relatively flat ground in Siberia revealed peatlands with so-called maze-patterning, because this type of patchiness somewhat resembles the corridors of a maze. The striking self-organized patchiness has amazed many peatland scientists and has lead to considerable attention for peatland patterning in the literature. Until now, however, the driving mechanisms of peatland patchiness still remain elusive, despite more than a century of research on this phenomenon. This thesis investigates underlying mechanisms that explain self-organized patchiness in peatlands, and whether this patchiness could serve as an indicator for proximity to catastrophic shifts in peatland ecosystem states. A combination of theoretical and empirical approaches is used. We conclude that the potential importance of different driving mechanisms for peatland patterning depends on climatic conditions. Increased evapotranspiration in vegetation patches with high density may be particularly important in peatlands where most water leaves the system through evapotranspiration. Alternatively, in peatlands where water is lost via drainage or overland flow, a positive feedback between the thickness of the upper aerobic peat layer and the rate of peat formation the peat accumulation mechanism may be more important. Global climate models project for most peatland regions an increasing importance of evapotranspiration during the coming century, with the strongest increases being projected for Siberia and Canada. Based on the results in this thesis, we speculate that evapotranspiration may become the main driver of pattern formation in parts of these regions. We also conclude that a shift from an unpatterned state without hummocks and hollows toward a patterned state with hummocks and hollows already comprises a catastrophic shift in ecosystem functioning that is difficult to reverse. This means that a pattern cannot be used as an indicator of proximity to a catastrophic shift, but rather indicates that the shift has already happened. Moreover, the very slow development of peatlands calls for caution when applying equilibrium concepts, which are used in most mathematical models of pattern formation, to peatland dynamics. Investigation of the mechanisms that drive self-organized patchiness in ecosystems is a promising approach to increase our understanding of ecosystem functioning, and the response of ecosystems to changing abiotic conditions. This thesis exemplifies that studies on pattern formation need to include both theoretical and empirical approaches, because the driving mechanisms of self-organized patchiness may change with climatic regions and may therefore be site-specific.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".