Importance of the study context in community assembly processes: a quantitative synthesis of forest bird communities
Bibliographic record
Abstract
Abstract Species composition is constrained by two upper‐level processes in ecological contexts where the dispersion of organisms is not severely limited, namely selection and ecological drift. This intuitive framework has motivated a constant flow of empirical models for linking the species matrix to the local environmental descriptors, in which the environment rarely explains more than 30–40% of the variation in species composition. In most cases, researchers only approximate the environmental axes that drive fitness differences between species, as the list of measured descriptors reflect both logistical constraints and hypothesis‐driven questions. Moreover, contextual factors, such as the species pool size (SPS) and the spatial extent of the sampled area, could moderate species–environment associations through sampling effects and dispersal limitations. This study's objective was to quantify the influence of contextual factors (i.e., related to the circumstances in which the study was conducted) on the species–environment association strength on the basis of a synthesis of 156 models of forest bird communities. Our results reveal that factors related to the SPS and the number of independent environmental axes studied affect our capacity to detect selection, whereas spatial factors such as the study's spatial extent and latitude are less important determinants. The study context explains almost a third of the observed variation in the strength of the species–environment association. We conclude that strong species–environment associations can be found for properly designed studies of forest bird communities, which raises the question of whether ecologists have underestimated the importance of selection in community assembly processes.
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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) | 0.000 | 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".