Environmental filtering of macroinvertebrate traits influences ecosystem functioning in a large river floodplain
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The biodiversity–ecosystem function hypothesis postulates that higher biodiversity is correlated with faster ecosystem process rates and increased ecosystem stability in fluctuating environments. Exhibiting high spatiotemporal habitat diversity, floodplains are highly productive ecosystems, supporting communities that are naturally resilient and highly diverse. We examined linkages among floodplain wetland habitats, invertebrate communities and their associated traits, and ecosystem function across 60 sites within the floodplain wetlands of the lower Wolastoq | Saint John River, New Brunswick, using structural equation modelling and Threshold Indicator Taxa ANalysis. We identified key environmental filters structuring invertebrate communities, by linking increased niche differentiation through shoreline change, flood pulse dynamics, and macrophyte bed complexity with increased taxa and functional diversity. Examination of traits linked to ecosystem functions revealed that more resilient wetlands with balance between primary productivity and decomposition as carbon sources were associated with greater functional evenness and richness, while habitat patches with elevated decomposition rates had lower functional richness, reflecting a simplified, more disturbed habitat. While our more complex overarching SEM model was ultimately compromised by an overspecified number of pathways, our results nevertheless are indicative of a divergence between wetland and riverine ecosystems in their relationships linking biodiversity and ecosystem function, illustrating how to define ecosystem health in wetland habitats, and demonstrating how critical functions support healthy wetland habitats by providing increased resilience to disturbance. Read the free Plain Language Summary for this article on the Journal blog.
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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 | 0.000 | 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) | 0.073 | 0.001 |
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 it