Determinants of savanna vegetation structure: Insights from <i>Colophospermum mopane</i>
Bibliographic record
Abstract
Abstract Savannas are structurally heterogeneous at the local, community‐level scale due to fine‐scale floristic heterogeneity as well as the responses of individual species to underlying environmental variation. The structure of mopane woodland, an arid savanna of southern Africa, is dictated largely by local variation in the relative dominance of tall, single‐stemmed and shorter, multi‐stemmed forms of the dominant tree species, Colophospermum mopane (Kirk ex Benth) Léonhard. Here we evaluate the hypothesis that the existence of these alternative forms of C. mopane, as well as the factors that dictate their distribution at a local scale, are driven by fine‐scale environmental variability in available water. We surveyed trees at four sites in the Kruger National Park of South Africa, in each instance surveying both forms of the species, from both riparian and non‐riparian zones. A survey of genetic variation across our sample (n = 80 individuals), using inter‐simple sequence repeat (ISSR) amplification profiles, indicates that the two forms are not genetically distinct, instead being environmentally determined. While measurements of xylem pressure potentials, determined using a Scholander pressure chamber, show a significant difference between riparian and non‐riparian zones, there is no significant difference between the two growth forms. Although this seems paradoxical in view of the prevalence of tree and shrub form mopane at riparian and non‐riparian sites, respectively, we speculate that such a pattern may emerge through the interaction of moisture stress and top‐down controls, such as those imposed by large mammal browsing and fire.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".