Moth Diversity in a Fragmented Habitat: Importance of Functional Groups and Landscape Scale in the Boreal Forest
Bibliographic record
Abstract
One of the leading concerns for both conservation biology and forestry has been how forest fragmentation affects biodiversity, and how forestry practices can be altered to mitigate diversity losses. However, the effects of habitat fragmentation on ecological functional groups within diverse taxa such as Lepidoptera are poorly known, particularly in boreal forests. We assessed landscape-level changes in moth species richness and abundance in relation to forest fragmentation, measured at multiple scales. We assessed fragmentation effects on three functional groups: tree- and shrub-feeding species, grass- and forb-feeding species, and species that act as hosts for parasitoids of an important forest defoliator, Malacosoma disstria Hübner (Lepidoptera: Lasiocampidae). Total species richness showed a significant decline as a function of fragmentation at all measured spatial scales; both polynomial and threshold models tended to explain more variation than linear models, suggesting that there is little to no change in overall moth diversity between low and moderately fragmented stands. However, changes in diversity patterns within functional groups showed that total diversity measures may mask changes in community structure. Changes in overall diversity were driven largely by a decrease in species richness of tree- and shrub-feeding moths, although forb- and grass-feeding moths also showed marginally lower species richness at high fragmentation levels. Most species of the parasitoid host group decreased in abundance with increasing fragmentation. These findings show that overall diversity measures can mask important community changes, and that the optimal landscape scale at which these changes are measured is taxon dependent. Finally, the decrease in host availability to M. disstria parasitoids in fragmented forests may exacerbate population outbreaks of M. disstria.
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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) | 0.000 | 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".