Incorporating habitat suitability into community projections: Ant responses to climate change in the Australian Wet Tropics
Bibliographic record
Abstract
Abstract Aim Studies of climate change impacts on animal distributions typically consider only the direct impacts of a changing climate, under the assumption that future areas of suitable climate will otherwise remain ecologically suitable. Here we assess both the direct and indirect impacts of climate change on rain forest ant communities, where substantial shifts are projected to occur for both climate and habitat types. Location Australian Wet Tropics (AWT). Methods Generalized Dissimilarity Modelling was used to model turnover in the composition of ~300 rain forest ant species sampled at 150 sites across six mountains spanning five degrees of latitude. Ants were sampled within the leaf litter, on the litter surface and on tree trunks. By modelling the rate of turnover among sites, we determined the current effective area of similar ecological environments (SEE) for ant communities and consequently the expected change in species persistence when habitat shifts under two climate projections for the years 2035, 2055 and 2085. We compared results when SEE considered only the direct effects of a changing climate, with those when changes in habitat were also included. Results The rain forest ant communities modelled will lose a substantial proportion of SEE under both climate change scenarios. Under combined direct (changes in climate) and indirect (changes in rain forest habitat) impacts of climate change, >90% of the communities in the region were predicted to lose up to half their similar habitats compared with 50%–60% when only considering direct climate change impacts. The highest risk of reduction in area of SEE is projected in drier inland areas of the AWT, where profound compositional turnover is linked to dramatic changes in rain forest vegetation, including extensive conversion into savanna. Main conclusions Our findings emphasize the importance of incorporating habitat suitability into future projections of species turnover under a changing climate, particularly for habitats where vegetation structure is projected to undergo profound change.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".