Factors driving structure of natural and anthropogenic forest edges from temperate to boreal ecosystems
Bibliographic record
Abstract
Abstract Questions What factors control broad‐scale variation in edge length and three‐dimensional boundary structure for a large region extending across two biomes? What is the difference in structure between natural and anthropogenic edges? Location Temperate and boreal forests across all of Sweden, spanning latitudes 55–69° N. Methods We sampled more than 2000 forest edges using line intersect sampling in a monitoring programme (National Inventory of Landscapes in Sweden). We compared edge length, ecosystem attributes (width of adjacent ecosystem, canopy cover, canopy height, patch contrast in canopy height, forest type) and boundary attributes (profile, abruptness, shape) of natural edges (lakeshore, wetland) with anthropogenic edges (clear‐cut, agricultural, linear disturbance) in five regions. Results Anthropogenic edges were nearly twice as abundant as natural edges. Length of anthropogenic edges was largest in southern regions, while the abundance of natural edges increased towards the north. Edge types displayed unique spectrums of boundary structures, but abrupt edges dominated, constituting 72% of edge length. Anthropogenic edges were more abrupt than natural edges; wetland edges had the most gradual and sinuous boundaries. Canopy cover, canopy height, patch contrast and forest type depended on region, whereas overall boundary abruptness and shape showed no regional pattern. Patch contrast was related to temperature sum (degree days ≥ 5 °C), suggesting that regional variability can be predicted from climate‐controlled forest productivity. Boundary abruptness was coupled with the underlying environmental gradient, land use and forest type, with higher variability in deciduous than in conifer forest. Conclusions Edge origin, land use, climate and tree species are main drivers of broad‐scale variability in forest edge structure. Our findings have important implications for developing ecological theory that can explain and predict how different factors affect forest edge structure, and help to understand how land use and climate change affect biodiversity at forest edges.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".