Deforestation alters species interactions
Bibliographic record
Abstract
Abstract Interspecific interactions are a major determinant of stability in ecological communities and are known to vary with biotic and abiotic conditions. Deforestation is the primary driver of the ongoing sixth mass extinction, yet its effect on species interactions remains largely unexplored. We investigate how deforestation affects species interactions using a complex systems model and a co‐occurrence dataset of 363 bird species, observed across 134 sites, from 5 regions across the Brazilian Atlantic Forest totalling 27,226 interactions. Both theoretical and empirical results show that interspecific interactions vary non‐monotonically with forest cover and are more positive than average in areas with higher forest cover, and to a lesser extent in highly deforested areas. Observed differences in interactions reflect both species turnover and changes in pairwise interactions. Our results point to changes in stability across the gradient of deforestation that may lead to varying community resilience to environmental perturbations. Key Interdisciplinary Aspects Species interactions are expected to vary due to the biological, chemical and physical changes caused by deforestation on their local environment. We use a mathematical complex systems approach, as well as ecological data, to show that species interactions are more positive in highly forested areas. We propose that the alteration of species interactions caused by deforestation will affect the stability of communities and their resilience to future perturbations (e.g. climate change).
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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 | 0.001 |
| Science and technology studies | 0.001 | 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 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".