The flooded habitat adaptation, niche differentiation, and evolution of Myristicaceae trees in the Western Ghats biodiversity hotspot in India
Bibliographic record
Abstract
Abstract Environmental heterogeneity is considered as one of the main drivers of habitat specialization and niche evolution among tropical plant lineages, and local‐scale habitat specialization promotes niche differentiation among sister taxa. In this study, we examined the degree to which habitat specialization leads to niche differentiation across the distribution range of a given species using five species of the family Myristicaceae native to Western Ghats, India, as an example. In the Western Ghats, Myristicaceae species occur in two main habitat types, namely, freshwater swamps (flooded habitat) and terra firme forest (non‐flooded habitat), distributed across a seasonal flooding gradient. First, we reconstructed the evolutionary history of flooded habitat specialization among global and Western Ghats Myristicaceae by mapping flooded habitat association and traits conferring flood tolerance (e.g., aerial roots) on a dated phylogeny. Then, we investigated climatic niche differences among lineages occupying flooded and terra firme habitats using occurrence data and environmental variables. Our analysis revealed swampy habitat occurrence as the probable ancestral state with subsequent speciation events leading to adaptation to non‐swampy habitats. We also show that traits conferring flood tolerance have evolved independently several times during the evolution of Myristicaceae. Furthermore, phylogenetically distantly related Myristicaceae taxa occupying different habitats (flooded and terra firme habitat) in Western Ghats show significant niche divergence. Overall, the repeated gain of swampy habitat specialization and associated morphological traits and evidence for habitat‐associated climatic niche divergence among Myristicaceae taxa suggest that seasonal flooding may have been an important driver of ecological diversification in this primitive plant family.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".