Impacts of anthropogenic land transformation on habitat amount, fragmentation, and connectivity in the Adirondack-to-Laurentians (A2L) transboundary wildlife linkage: Implications for conservation and ecological restoration
Bibliographic record
Abstract
Habitat loss and fragmentation, due to anthropogenic land transformation, is the leading cause of species declines and biodiversity loss worldwide. Habitat loss and fragmentation transform landscapes into a heterogeneous array of habitat fragments of smaller total habitat area, isolated from each other by a human-dominated matrix. This results in long-term changes in ecosystem structure and function, and an overall reduction in species abundance and movement ability between fragments. Globally, 56% of all terrestrial mammals have transboundary geographic ranges. In contrast, most conservation initiatives do not cross political boundaries. The Adirondack-to-Laurentians (A2L) transboundary wildlife linkage connects wilderness areas in the northeastern United States with southeastern Canada. Although the region contains many habitats of high ecological integrity and biodiversity, ceaseless anthropogenic land transformation within the A2L may be putting transboundary connectivity at risk. Changes in landscape structure, due to anthropogenic land transformation, that occurred within the A2L between 1992 and 2018 were quantified, and priority areas for conservation and restoration were identified. The results suggest that to achieve long-term functionality of the A2L, collaborative and coordinated measures will be necessary to preserve the integrity of the Québec portion, restore extensive habitat in eastern Ontario, and reestablish or maintain connectivity throughout the linkage. The results can be used to inform conservation policy and land-use planning throughout the region. Left unaddressed, continued anthropogenic land transformation is likely to have additional detrimental effects on the ability of the A2L to function as a transboundary wildlife linkage.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".