Genomic and niche divergence in an Amazonian palm species complex
Bibliographic record
Abstract
Abstract Environmental heterogeneity across the landscape can cause lineage divergence and speciation. The Geonoma macrostachys (Arecaceae) species complex has been proposed as a candidate case of ecological speciation in Amazonia due to evidence of habitat partitioning and pre-zygotic reproductive barriers between co-occurring morphotypes at a local scale. In this study, we provide a continent-wide perspective of the divergence patterns in G. macrostachys by integrating data from morphological traits, target sequence capture, climate, soil and reproductive biology. A morphometric analysis revealed four morphogroups, defined by traits related to leaf shape. A coalescence-based phylogenetic analysis did not recover the morphogroups as monophyletic, indicating independent evolution of leaf shape across geographical space. We demonstrate scale-dependent habitat differentiation for two of the morphogroups, in which segregation driven mostly by climate was complete at the regional scale but incomplete at the continental scale. Contrary to previous evidence of reproductive isolation in the form of different pollinators and flowering times between sympatric G. macrostachys forms in Peru and Ecuador, these were not found in Colombia, suggesting reproductive barriers have evolved multiple times across its geographical range. Taken together, our findings suggest that ecological divergence and local adaptation is driving diversification in G. macrostachys, and that hyperdiverse regions such as Amazonia are probable arenas for ecological divergence in sympatry.
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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".