Bibliographic record
Abstract
Sand Dunes are great fun. (Greely and Iverson, 1984) Introduction The dynamic nature of sand dunes over relatively short spatial and temporal scales makes them an ideal phenomenon from which to obtain a better understanding of the interactions between the geosciences and biological sciences. Most early studies of sand dunes focused on classification of dune forms, plant species composition on various dune types, plant succession, and the morphological adaptation of plants to sand burial, salt spray, and xeric conditions. In this chapter, the interaction of ecology and geomorphology in the development of coastal sand dunes will be discussed, from the origin of ecology in the 1800s through to the present. Underlying this history is a struggle by both disciplines to move from a mainly descriptive approach toward an understanding of how sand dunes and plants influence each other. The difficulty has always been how to couple the physical processes of sand transport with the influence of plants and, in turn, how to connect plants with different life histories to sand transport. This undertaking is still in its infancy. Physiography and Physiographic Ecology At the end of the 1800s, both physiography (as geomorphology was called at the time) and biology adopted a neo-Lamarckian evolutionary viewpoint (Johnson, 1979; Inkpen and Collier, 2007). Evolution, at this time, incorporated ideas of directional development that could take place at scales above the individual or population (today this idea is called group selection and is mostly rejected as having no valid mechanism (Williams, 1966)). Stages in this directional development were believed to facilitate further evolution. The result was a belief that many forms in biology developed in a progressive, integrated manner with an end-stage that would be in equilibrium. Herbert Spencer, a prolific but now largely forgotten philosopher, was a popular exponent of these ideas, combining both “evolutionary” and “quasi-thermodynamic” ideas in Principles of Biology (1864). He is best remembered for the teleological term “survival of the fittest.” These evolutionary viewpoints can be found in numerous scientific studies, such as the landscape cycles of Davis (1889; 1899) and in the ecology of communities and succession of Cowles (1899), Clements (1916), and Cooper (1926).
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".