Environmental and spatial influences upon species composition of a termite assemblage across neotropical forest islands
Why this work is in the frame
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Bibliographic record
Abstract
Patterns of species composition in a neotropical termite assemblage were studied in relation to early effects of forest fragmentation as well as other sources of environmental and spatial heterogeneity. Termite diversity surveys were carried out at three mainland forest sites, and 10 islands of varying size, in an area of lowland tropical forest that had been flooded 4 y earlier, during the creation of the Petit Saut hydroelectric project in French Guiana. The ‘ghost forest’ of dead emergent trees in the flooded zone was also studied for its influence on island termite assemblages. Results suggested that the effects of forest fragmentation upon the total assemblage, and upon soil-feeders in particular, were subordinate to the influence of forest understorey palm density, and the closely associated gradients of soil humus depth and soil pH. Moreover, gradients for these three variables were uncorrelated with forest fragmentation and probably reflected spatial environmental heterogeneity pre-dating inundation events. Nevertheless, factors associated with forest fragmentation appeared to have had a significant effect on changes in termite species composition across the study site, primarily in structuring the wood- and leaf-litter-feeder assemblage. Effects upon the latter were not apparently a result of influx of species from the ghost forest. Purely spatial variation also influenced β-diversity changes in species composition across the site. In conclusion, the effects of forest fragmentation upon termites appear to have been relatively mild compared with other faunal groups, 4 y after flooding. Nevertheless, we predict that the effects of fragmentation on termite assemblages will ultimately be negative. This study also points to the importance of Amazonian understorey palms in structuring a tropical forest termite assemblage.
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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 | 0.000 |
| 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 it