Plant species composition across several natural edge types in Nova Scotia
Bibliographic record
Abstract
Forest edges, anthropogenic and natural, experience edge effects which influence the surrounding species and abiotic factors.The amount of effect on the forest depends on a variety of factors including how the edge was made (or if it exists naturally), severity of contrast between adjacent habitat and forest, forest type and age.Many studies have looked in depth on anthropogenic edges but there is a lack of knowledge about natural edges, specifically looking at multiple natural edges and comparing them.My objectives were 1) to compare different edge types in Nova Scotia and 2) look at differences in species composition between the edge, forested and non-forested areas of each study.The data set used in this study spans a ten-year period and includes lakeshore, bog, barren, coastal, insect and fire edges.Cover estimates of vascular plants were taken within quadrats along a transects perpendicular to the edges and varied in length from 100 to 200m.I conducted a correspondence analysis to compare species composition.The bog, lakeshore and barren edges had patterns of distinction between the edge, forested and non-forested categories.The coastal, insect and fire sites had a lack of distinction in species composition at these three distance categories.This was related to disturbance with coastal, insect and fire being frequently/previously disturbed and thus with less complex species composition.Overlap in species composition were seen between forest and edge at all six edge types and there was also overlap with the edge and non-forested area, less so.The natural inherent sites shared more similarities to each other.The naturally created sites were not like each other nor to the naturally inherent sites.The edge and forested sites had similar species composition, as did non-forested and edge sites.The non-forested and forested species composition was distinct from each other.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".