Ghost of land-use past in the context of current land cover: evidence from salamander communities in streams of Blue Ridge and Piedmont ecoregions
Bibliographic record
Abstract
The Blue Ridge and Piedmont of the southeastern United States are rich in biodiversity and have undergone centuries of extensive deforestation and subsequent urbanization resulting in geomorphic landscape changes. To investigate the impacts of past and present land uses on stream salamander communities across both ecoregions, we surveyed streams associated with different land uses at the riparian zone and watershed. Using the USGS land-cover data set (2006) and aerial photographs (1940), we assessed the current and historical percent land cover (urban, agriculture, and forests) at local and landscape scales for each sampling site. Using percent land cover as predictors and diversity indices (species richness, Simpson’s index, and relative abundance) as response variables, we developed a stepwise multiple regression model and a redundancy analysis. Both analyses indicated the negative impacts of historical land uses, particularly row-crop agriculture, on stream salamander diversity and community structure rendering streams unsuitable for all but the most tolerant species. Legacy effects were prominent in the Piedmont where protected areas with agricultural history were species-deprived (70% decline) compared with stream habitats that had sustained a continuous forest cover through time. Our findings suggested that landscape processes resulting in historical forest cover loss may persist over 50 years during forest recovery.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".