Waterfowl Endozoochory: Traits Drive Plant–Bird Dispersal Interactions in North America
Bibliographic record
Abstract
ABSTRACT Plant biogeography and ongoing changes in plant distributions are influenced by long‐distance dispersal (LDD) of seeds, and migratory waterfowl (Anatidae: Ducks, geese and swans) are particularly important for the dispersal of plants in and around wetlands through gut passage (endozoochory). However, this dispersal is not contemplated by classical dispersal syndromes; hence, currently we have limited understanding of what angiosperm traits predict seed dispersal by waterfowl and any differences due to avian trait variation among waterfowl species. We conducted a literature search for data on the presence of seeds in the alimentary canal or faeces of North American waterfowl as a proxy for dispersal interactions, since an important fraction of these seeds survives gut passage. We present a list of North American flowering plant species ( N = 536) from 95 families potentially dispersed by 38 waterfowl species, together with traits of these plants and their vectors. Owing largely to limited sampling effort, 47% of plant species and 35% of plant genera recorded were only found in a single waterfowl species. A suite of analytical approaches revealed major differences in the traits of plants whose seeds are ingested and likely dispersed between foraging groups (guilds) and in relation to other waterfowl traits. Diving ducks and sea ducks are associated with sublittoral plants that have submerged or floating leaves, and hence with the classical hydrochory syndrome. Dabbling ducks and herbivorous waterfowl (notably geese) are associated with terrestrial herbaceous plants, and also with the unspecialised dispersal syndrome common in terrestrial plants. Plants with larger seeds or of greater height are more likely to be dispersed by dabbling ducks, whereas shorter plants are more likely to be dispersed by geese than by other waterfowl. Network analyses of interactions between waterfowl species and plant traits were generally consistent with these results, but also provided evidence that not all geese, dabbling ducks, or sea duck species are alike in their interactions with plants along the terrestrial–aquatic gradient, but instead occupy distinct dispersal niches. The traditional classification of waterfowl into guilds therefore does not accurately reflect their differing roles in the ingestion and dispersal of plant seeds. Aquatic plant species had more vector species than terrestrial ones. Detailed studies of waterfowl endozoochory and more trait determinations for North American plants are needed to facilitate predictions of LDD as waterfowl population sizes and migration patterns vary in the future with climate change.
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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 | 0.000 | 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) | 0.003 | 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 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".