Phylogenetic community patterns suggest Central Indian tropical dry forests are structured by montane climate refuges
Bibliographic record
Abstract
Abstract Aim We used an eco‐phylogenetic approach to investigate the diversity and assembly patterns of tropical dry forests (TDFs) in Central India. We aimed at informing conservation and restoration practices in these anthropogenically disturbed forests by identifying potential habitats of conservation significance and elements of regional biodiversity most vulnerable to human impact and climate change. Location Tropical dry forests of Madhya Pradesh, Central India. Methods We analysed the species richness, stem density, basal area and phylogenetic structure (standardized effect size of MNTD, MPD, PD and community evolutionary distinctiveness cED) of 117 tree species assemblages distributed across a ~230 to ~940 m elevational gradient. We examined how these community measures and taxonomic (Sørensen) and phylogenetic (UniFrac) beta diversity varied with elevation, precipitation, temperature and climatic stress. Results Species richness, phylogenetic diversity, stem density and basal area were positively correlated with elevation, with high‐elevation plots exhibiting cooler temperatures, higher precipitation and lower stress. High‐elevation assemblages also trended towards greater phylogenetic dispersion, which diminished at lower elevations and in drier, more stressful plots. Phylogenetic turnover was observed across the elevation gradient, and species evolutionary distinctiveness increased at lower elevations and under harsher abiotic conditions. Main Conclusions Harsher abiotic conditions at low elevations may act as a selective filter on plant lineages, leading to phylogenetically clustered low‐diversity assemblages. These assemblages contained more evolutionarily distinct species that may contribute disproportionately to biodiversity. Conversely, milder abiotic conditions at high elevations may serve as refuges for drought‐sensitive species, resulting in more diverse assemblages. Conservation practices that prioritize both high‐ and low‐elevation habitats could promote the persistence of evolutionarily distinct species and areas of high biodiversity within the Central Indian landscape. Establishing connectivity between these habitats may provide a range of climatic conditions for species to retreat to or persist within as climates 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 | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".