Sea dispersal potential and colonization of the Galápagos littoral flora
Bibliographic record
Abstract
Abstract Aim Seed dispersal by oceanic currents (thalassochory) is considered one of the main long‐distance dispersal (LDD) mechanisms for the colonization of oceanic islands by plants. Diaspores of littoral species are often hypothesized to be physiologically adapted to seawater dispersal, favouring interisland colonization. In this study, we experimentally tested the sea dispersal potential of a large proportion of Galápagos littoral flora and explored its correlation with plant distribution across the archipelago. We propose a simple Sea Dispersal Potential index (SDPi) to quantify the thalassochorous potential of any species. Location Galápagos archipelago. Taxon Littoral angiosperms. Methods We combined information on seed floatability (flotation time) and viability experiments (tetrazolium test) into an SDPi for 19 native littoral plants and tested whether increasing dispersal potential is associated with broader interisland distributions. We then tested if the presence of morphological structures related to thalassochory is associated with the functional SDPi. Results A relatively low, albeit highly variable, SDPi across Galápagos littoral plant species was found. No correlation was found between SDPi and species distributions. Morphological traits hypothesized to favour sea dispersal are not related to thalassorous potentials to reach closest islands, but they are positively associated with SDPi to reach the farthest islands. Main conclusions SDPi is shown to be a useful tool to compare the thalassochorous potentials of entire floras in a given geographical context. The low performance of most of the species questions the general assumption that most littoral plants are highly adapted to long‐distance sea dispersal. Our results support the view that island colonization is a multifactorial process and that the use of dispersal syndromes is insufficient to make biogeographical predictions in macroecology studies. Further research should integrate functional indices (e.g., SDPi) with complementary tools (genetics, remote diaspore tracking) to determine the actual drivers of species dispersal and establishment.
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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) | 0.000 | 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".