Ants as ecological indicators of rainforest restoration: Community convergence and the development of an Ant Forest Indicator Index in the Australian wet tropics
Bibliographic record
Abstract
Ecosystem restoration can help reverse biodiversity loss, but whether faunal communities of forests undergoing restoration converge with those of primary forest over time remains contentious. There is a need to develop faunal indicators of restoration success that more comprehensively reflect changes in biodiversity and ecosystem function. Ants are an ecologically dominant faunal group and are widely advocated as ecological indicators. We examine ant species and functional group responses on a chronosequence of rainforest restoration in northern Australia, and develop a novel method for selecting and using indicator species. Four sampling techniques were used to survey ants at 48 sites, from grassland, through various ages (1-24 years) of restoration plantings, to mature forest. From principal components analysis of seven vegetation metrics, we derived a Forest Development Index (FDI) of vegetation change along the chronosequence. A novel Ant Forest Indicator Index (AFII), based on the occurrences of ten key indicator species associated with either grassland or mature forest, was used to assess ant community change with forest restoration. Grasslands and mature forests supported compositionally distinct ant communities at both species and functional levels. The AFII was strongly correlated with forest development (FDI). At forest restoration sites older than 5-10 years that had a relatively closed canopy, ant communities converged on those of mature rainforest, indicating a promising restoration trajectory for fauna as well as plants. Our findings reinforce the utility of ants as ecological indicators and emphasize the importance of restoration methods that achieve rapid closed-canopy conditions. The novel AFII assessed restoration status from diverse and patchily distributed species, closely tracking ant community succession using comprehensive species-level data. It has wide applicability for assessing forest restoration in a way that is relatively independent of sampling methodology and intensity, and without a need for new comparative data from reference sites.
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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 | 0.001 | 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 | 0.001 | 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".