An empirical investigation of why species–area relationships overestimate species losses
Bibliographic record
Abstract
It is generally assumed that, when natural habitat is converted to human-dominated land cover, such habitat is lost to its native species. Most literature assumes that species richness should vary as a function of remaining natural area, following the well-known species-area relationship (i.e., classic SAR). However, classic SARs have consistently overestimated species losses resulting from conversion of natural forested land cover to human-dominated landscapes. Moreover, richness is sometimes a peaked function of remaining natural habitat. Recent studies propose modified SAR models based on species' utilization of multiple habitat types, yet none fully explain a peaked species-area relationship. Here, we evaluate the responses of total avian richness, forest bird richness, and open-habitat bird richness to remaining natural land cover within 991 quadrats, each 100 km2, across southern Ontario, Canada. Total bird species richness peaks at roughly 50% natural land cover. Richness of forest birds varies as a classic power function of forested area. In contrast, richness of birds that prefer open habitats does not increase monotonically with either natural- or human-dominated land cover. Richness of open-habitat species can be predicted when we partition human-dominated land cover into an "available human-dominated" component and "lost" habitat. Disiinguishing three land-cover types (natural, available human-dominated, and lost) can thus permit accurate predictions of species richness in landscapes with differing levels of natural habitat conversion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".