Landscape size affects the relative importance of habitat amount, habitat fragmentation, and matrix quality on forest birds
Bibliographic record
Abstract
It is important to understand the relative effects of landscape habitat loss, habitat fragmentation, and matrix quality on biodiversity, so that potential management options can be appropriately ranked. However, their effects and relative importance may change with the size of the landscape considered because the multiple (and potentially conflicting) ecological processes that are influenced by landscape structure occur at different spatial scales (e.g. dispersal, predation, foraging). We estimated the relative effects of habitat loss, habitat fragmentation, and matrix quality (measured as the amount of forest, the proportion of forest area contained in large core forests, and the density of roads respectively) on fragmentation‐sensitive forest birds in southern Ontario, Canada using a range of landscape sizes (0.8–310 km 2 ). We used three complementary statistical approaches to estimate relative effects of these correlated landscape factors – 1) multiple regression, 2) information theoretic (AIC) estimates of the most parsimonious model, and 3) multi‐model inference to average effects across all supported models. We controlled for spatial autocorrelation, local habitat, roadside sampling bias, time of day, season, habitat heterogeneity, and the interaction between the effects of habitat amount and fragmentation. We found that relative effects of habitat amount and fragmentation were scale dependent; habitat amount had a consistently positive effect that was consistent over more than two orders of magnitude in landscape area (~1–300 km 2 ). In contrast, the effects of habitat fragmentation depended on the size of the landscape considered. Indeed, for veery Catharus fuscescens , habitat fragmentation had positive effects at one scale and negative effects at another. The effects of matrix quality were generally weak and changed little with scale. For the number of fragmentation sensitive species and the presence of veery, habitat amount was most important in large landscapes and habitat fragmentation in small landscapes but for the presence of ovenbird Seiurus aurocapilla , habitat amount was most important at all scales.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".