Experimental evidence does not support the Habitat Amount Hypothesis
Bibliographic record
Abstract
For a half century, habitat configuration – the arrangement of habitat patches within a landscape – has been central to theories of landscape ecology, population dynamics, and community assembly, in addition to conservation strategies. A recent hypothesis advanced by Fahrig (2013) would, if supported, greatly diminish the relevance of habitat configuration as a predictor of diversity. The Habitat Amount Hypothesis posits that the sample area effect overrides patch size and patch isolation effects of habitat fragmentation on species richness. It predicts that the amount of habitat in a local landscape, regardless of configuration, is the main landscape‐level determinant of species richness. If habitat amount is indeed the major, landscape‐level driver of species richness, the slopes of the species–area relationship (SAR) for otherwise similar fragmented and unfragmented landscapes should be indistinguishable. We tested the Habitat Amount Hypothesis with data from two replicated and controlled habitat fragmentation experiments that disentangle the effects of habitat amount and configuration. One experiment provided time‐series data on plant species richness and the other on micro‐arthropod species richness. We found that, relative to less fragmented habitats, the SARs for fragmented habitats have significantly higher slopes and that the magnitude of the difference in slopes increased over time. Relatively more species were lost in smaller areas when fragments were more isolated. In both experiments, the proportion of species lost due to increased habitat fragmentation was nearly identical to the proportion lost due to reduced habitat amount. Our results provide a direct and experimentally derived refutation of the Habitat Amount Hypothesis, supporting the long‐held view that in addition to area, patch isolation and configuration are important determinants of species richness. Differences in species richness between fragmented and non‐fragmented habitats increase over time, demonstrating that long‐term studies are needed to understand the effects of fragmentation, above and beyond the amount of habitat lost.
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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 | 0.009 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".