The influence of geomorphic processes on plant distribution and abundance as reflected in plant tolerance curves
Bibliographic record
Abstract
Ecologists describe plant distribution using direct gradient analysis, by which a tolerance curve of species abundance is described along an environmental gradient (any environmental variable that affects plant distribution). Soil moisture is generally the gradient in low‐relief areas that explains the most variation. Traditional direct gradient analyses have used terrain structure (i.e., transects up or down hillslopes) as a correlate to soil moisture. Here we use a numerical tectonic and geomorphic process‐based landscape development model to create two landscapes with different geomorphic characteristics: (1) to demonstrate the influence of geomorphic processes on soil moisture patterns and plant distribution and (2) to evaluate the effectiveness of transects in describing moisture gradients and tolerance curves on landscapes dominated by creep or overland flow. We use a topographic index to approximate the distribution of soil moisture as it is determined by the shape of these different landscapes. Transects are placed on hillslopes in each model landscape and used to construct tolerance curves. Results show that transect methods that use the distance from the channel to the ridgeline as an approximation of soil moisture create variable tolerance curves for the same plant both within a single landscape and between different landscapes. The reason for these differences is that transects do not take into account the three‐dimensional landscape form that explains water movement. Landscapes have regions of convexity and flow path divergence and regions of concavity and flow path convergence that, along with hillslope length, determine contributing area. In addition, hillslope curvature results in varying capacities to retain water. However, when the topographic index is used instead of hillslope transect position, tolerance curves from the same and different landscapes reflect the differences the topographic structure has on soil moisture. We thus show that traditional methods of direct gradient analysis are not always adequate as they do not tend to consider that soil moisture depends on hillslope length, curvature, and slope. Furthermore, we show that within and between landscapes there are differences in spatial distributions of soil moisture that are reflections of the geomorphic processes that created them.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".