Neotropical Rivers as Potential Interaction Corridors: An Evaluation of Frugivory Metanetworks Across Two Biogeographic Domains in South America
Bibliographic record
Abstract
ABSTRACT Aim Frugivory interactions vary widely, yet their connectivity and spatial structuring at regional scales remain poorly understood. Using a metanetwork approach, we aim to test whether large rivers and their associated riparian habitats function as “interaction corridors” by linking otherwise segregated local networks. We studied avian frugivory in two contiguous Neotropical domains: the xerophytic Chaco and the humid Paraná, the latter embedded within a riverine corridor shaped by South America's second largest lowland river system. Location Santa Fe Province, Argentina. Taxon Avian frugivores and fleshy fruiting plants. Methods We recorded avian frugivory interactions across six forest sites spanning two neotropical Biogeographic domains. Then, we constructed aggregated and domain‐specific metanetworks to test whether sites are functionally connected through ecological interactions facilitated by riverine connectivity. We quantified (i) measures of connectance, nestedness, and modularity, (ii) interactions centrality and their correlated functional traits, and (iii) assessed beta diversity of species and interactions, which allowed us to evaluate patterns of turnover and nestedness across spatial and biogeographic gradients. Results The aggregated metanetwork revealed a connected core (Paraná) and a peripheral region (Chaco), characterised by high turnover of plants and interactions, moderate bird turnover and high plant nestedness. The chaco network exhibited higher modularity, lower connectance and nestedness, and greater beta diversity. In contrast, the Paraná network showed higher connectance and lower beta diversity, nestedness and modularity. Consistently, most interactions were peripheral and site‐specific, with only a small subset of interactions connecting sites. Trait analyses revealed differences in Interaction roles in Paraná but not in Chaco. Main Conclusions Our findings highlight the potential role of large rivers, and their associated riparian habitats, as functional corridors of species dispersal and interaction flows, influencing the spatial structuring of frugivory metacommunities at large scales. This has important implications for biodiversity conservation and the maintenance of ecosystem processes in Neotropical land and riverscapes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".