In situ resistance, not immigration, supports invertebrate community resilience to drought intensification in a Neotropical ecosystem
Bibliographic record
Abstract
While future climate scenarios predict declines in precipitations in many regions of the world, little is known of the mechanisms underlying community resilience to prolonged dry seasons, especially in “naïve” Neotropical rainforests. Predictions of community resilience to intensifying drought are complicated by the fact that the underlying mechanisms are mediated by species’ tolerance and resistance traits, as well as rescue through dispersal from source patches. We examined the contribution of in situ tolerance-resistance and immigration to community resilience, following drought events that ranged from the ambient norm to IPCC scenarios and extreme events. We used rainshelters above rainwater-filled bromeliads of French Guiana to emulate a gradient of drought intensity (from 1 to 6 times the current number of consecutive days without rainfall), and we analyzed the post-drought dynamics of the taxonomic and functional community structure of aquatic invertebrates to these treatments when immigration is excluded (by netting bromeliads) or permitted (no nets). Drought intensity negatively affected invertebrate community resistance, but had a positive influence on community recovery during the post-drought phase. After droughts of 1 to 1.4 times the current intensities, the overall invertebrate abundance recovered within invertebrate life cycle durations (up to 2 months). Shifts in taxonomic composition were more important after longer droughts, but overall, community composition showed recovery towards baseline states. The non-random patterns of changes in functional community structure indicated that deterministic processes like environmental filtering of traits drive community re-assembly patterns after a drought event. Community resilience mostly relied on in situ tolerance-resistance traits. A rescue effect of immigration after a drought event was weak and mostly apparent under extreme droughts. Under climate change scenarios of drought intensification in Neotropical regions, community and ecosystem resilience could primarily depend on the persistence of suitable habitats and on the resistance traits of species, while metacommunity dynamics could make a minor contribution to ecosystem recovery. Climate change adaptation should thus aim at identifying and preserving local conditions that foster in situ resistance and the buffering effects of habitat features.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".