Wading bird functional diversity in a floodplain: Influence of habitat type and hydrological cycle
Bibliographic record
Abstract
Abstract Waterbirds play important roles in maintaining ecosystem functioning in wetlands. However, the lack of essential information about the levels of interaction between waterbirds and wetland characteristics is a major impediment for service valuation. In this study, we examined the influence of the flood pulse across different freshwater habitats on the functional diversity and possible assembly structuring mechanisms of herons and storks in a neotropical floodplain. We investigated functional richness, evenness and divergence as descriptors of the functional diversity in rivers, channels and both connected and isolated lagoons across different phases of the hydrological cycle. We also compared observed values of functional diversity with expected null models to untangle the main mechanisms driving assemblages. We found spatiotemporal variation in functional diversity in wader assemblages of the high Paraná River floodplain. The functional diversity of Pelecaniformes and Ciconiiformes varied mainly in rivers, channels and connected lagoons opposed to isolated lagoons in a floodplain, and mostly during flood events, right after floods or after a long period of drought. This suggests that the variation in the water level plays different roles in maintaining wading birds' functional diversity in connected and isolated habitats. Also, wading bird assemblages in this floodplain may be structured by neutral mechanisms, independent of habitat type or hydrological period, which may support the idea that species traits are not important in explaining their coexistence patterns. Our study contributes to the understanding of how environmental variations may affect functional diversity, a first step towards understanding how changes in waterbird communities affect the magnitude and stability of services provided by them.
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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 | 0.001 |
| 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".