Congruence of community thresholds in response to anthropogenic stress in Great Lakes coastal wetlands
Bibliographic record
Abstract
Biological attributes of ecosystems often change nonlinearly as a function of anthropogenic and natural stress. Plant and animal communities may exhibit zones of change along a stressor gradient that are disproportionate relative to the incremental change in the stressor. The ability to predict such transitions is essential for effective management intervention because they may indicate irreversible changes in ecological processes. Despite the importance of recognizing transition zones along a stressor gradient, few, if any, investigators have examined these responses across multiple taxa, and no community threshold studies have been reported at large geographic scales. We surveyed benthic macroinvertebrate, fish, bird, diatom, and plant communities in coastal wetlands across a geospatially referenced gradient of anthropogenic stress in the Laurentian Great Lakes. We used Threshold Indicator Taxon Analysis (Baker and King 2010) to analyze each community’s response to identify potential zones of disproportionate change in community structure along gradients of major watershed-scale stress: agriculture and urban/suburban development. Our results show surprising congruence in community thresholds among different taxonomic groups, particularly with respect to % developed land in the watershed. We also analyzed uncertainty associated with the community-specific thresholds to understand the ability of different assemblages to predict stress. The high and congruent sensitivity of assemblages to development demonstrates that watershed-scale stress has discernible effects on all biological communities, with increasing potential for ecosystem-scale functional changes. These findings have important implications for identifying reference-condition boundaries and for informing management and policy decisions, in particular, for selecting freshwater protected areas.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".