Effects of slope aspect and topographic position on environmental variables, disturbance regime and tree community attributes in a seasonal tropical dry forest
Bibliographic record
Abstract
Abstract Questions What is the magnitude of the differences in environment and chronic human disturbance between contrasting slope aspects and topographic positions in a seasonally dry tropical forest? What is the effect of such topography‐related differences on composition, structure and diversity attributes of the tree community of this forest? Location Tziritzícuaro, Michoacán State, southern Mexico. Methods Vegetation was sampled in 36 100‐m 2 plots evenly distributed among three topographic positions (lower, middle and upper parts of a slope) and two slope aspects (N‐ and S‐facing). Environment at these sites was described through modelling incoming solar radiation and in situ recording of temperature during 1 yr. Disturbance was visually assessed in the field to calculate a Chronic Disturbance Index. Vegetation structure and diversity were compared among the resulting combinations of slope and topographic position. PERMANOVA and CCA were used to examine the multivariate relationship among vegetation, topography and disturbance. Results Slope aspects and topographic positions differed in terms of annual mean temperature, potential energy income and evapotranspiration. Conversely, disturbance was not so clearly related to topography. Regarding vegetation structure, significant differences were only found for individual sizes and abundance; these values increased towards the upper portion of S‐facing slopes, but decreased with elevation in N‐facing slopes. Species diversity (S, Jacknife 1 and Fisherʼs α) was higher in S‐facing slopes and increased from lower to upper topographic positions. PERMANOVA showed that vegetation structure and diversity were influenced by topographic position (12.9%) and the interaction between soil moisture and chronic disturbance with slope aspect (8.2% and 8.3%, respectively). CCA showed that a modest proportion (21%) of variation in species composition is explained by the combination of environmental and disturbance variables. Conclusions Slope aspect and topographic position represent axes of environmental and disturbance differentiation. Although vegetation attributes respond to these ecological factors, they do not show homogeneous responses. Floristic composition is clearly linked to environmental heterogeneity, while structural attributes and α‐diversity appear to be more closely related to human disturbance and soil moisture, particularly on S‐facing slopes. Integrating environmental heterogeneity and human disturbance with topographic variability enhances our understanding of large variation in tree community attributes in seasonal dry tropical forests.
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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 | 0.000 | 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) | 0.001 | 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".