Functional and phylogenetic structure of island bird communities
Bibliographic record
Abstract
Biodiversity change in anthropogenically transformed habitats is often nonrandom, yet the nature and importance of the different mechanisms shaping community structure are unclear. Here, we extend the classic Theory of Island Biogeography (TIB) to account for nonrandom processes by incorporating species traits and phylogenetic relationships into a study of faunal relaxation following habitat loss and fragmentation. Two possible mechanisms can create nonrandom community patterns on fragment islands. First, small and isolated islands might consist of similar or closely related species because they are environmentally homogeneous or select for certain shared traits, such as dispersal ability. Alternatively, communities on small islands might contain more dissimilar or distantly related species than on large islands because limited space and resource availability result in greater competitive exclusion among species with high niche overlap. Breeding birds were surveyed on 36 islands and two mainland sites annually from 2010 to 2014 in the Thousand Island Lake region, China. We assessed community structure of breeding birds on these subtropical land-bridge islands by integrating species' trait and evolutionary distances. We additionally analysed habitat heterogeneity and variance in size ratios to distinguish biotic and abiotic processes of community assembly. Results showed that functional-phylogenetic diversity increased with island area, and decreased with isolation. Bird communities on the mainland were more diverse and generally less clustered than island bird communities and not different than randomly assembled communities. Bird communities on islands tend to be functionally similar and phylogenetically clustered, especially on small and isolated islands. The nonrandom decline in species diversity and change in bird community structure with island area and isolation, along with the relatively homogeneous habitats on small islands, support the environmental filtering hypothesis. Our study demonstrates the importance of integrating multiple forms of diversity for understanding the effects of habitat loss and fragmentation, and further reveals that TIB could be extended to community measures by moving beyond assumptions of species equivalency in colonisation rates and extinction susceptibilities.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".