Species Interactions Limit the Predictability of Community Responses to Environmental Change
Bibliographic record
Abstract
AbstractPredicting how ecological communities will respond to environmental change is challenging but highly relevant in this era of global change. Ecologists commonly use current spatial relationships between species and environmental conditions to make predictions about the future. This assumes that species will track conditions by shifting their distributions. However, theory and experimental evidence suggest that species interactions prevent communities from predictably tracking temporal changes in environmental conditions on the basis of current spatial relationships between species and environmental gradients. We tested this hypothesis by assessing the dynamics of protist species in replicated two-patch microcosm landscapes that experienced different regimes of spatial and temporal environmental heterogeneity (light vs. dark). Populations were kept in monocultures or polycultures to assess the effect of species interactions. In monocultures, abundances were predictable on the basis of current environmental conditions, regardless of whether the populations had experienced temporal environmental change. But in polycultures, abundances also depended on the history of the environmental conditions experienced. This suggests that because of species interactions, communities should respond differently to spatial versus temporal environmental changes. Thus, species interactions likely reduce the accuracy of predictions about future communities that are based on current spatial relationships between species and the environment.
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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 | 0.000 |
| 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".