Environment and predation govern fish community assembly in temperate streams
Bibliographic record
Abstract
Abstract Aim The elucidation of patterns and drivers of community assembly remains a fundamental issue in ecology. Past studies have focused on a limited number of communities at local or regional scales, thus precluding a comprehensive examination of assembly rules. We addressed this challenge by examining stream fish community assembly within numerous independent watersheds spanning a broad environmental gradient. We aimed to answer the following questions: (1) are fish communities structured non‐randomly, and (2) what is the relative importance of environmental filtering, predator–prey interactions and interspecific competition in driving species associations? Location The conterminous USA. Methods We used null models to analyse species associations in streams. Non‐random communities were defined as those where the summed number of segregated and aggregated species pairs exceeded the number expected by chance. We used species traits to characterize species dissimilarity in environmental requirements (ENV), identify potential predator–prey interactions (PRED) and estimate likely degree of competition based on species similarity in body size, feeding strategies and phylogeny (COMP). To evaluate the effect of environmental filtering, predation and competition on species associations, we related ENV, PRED and COMP to the degree of species segregation. Results The majority (75–85%) of watersheds had non‐random fish communities. Species segregation increased with species dissimilarity in environmental requirements (ENV). An increase in competition strength (COMP) did not appear to increase segregation. Species pairs engaging in predator–prey interactions (PRED) were more segregated than non‐predator–prey pairs. ENV was more predictive of the degree of species segregation than PRED. Main conclusions We provide compelling evidence for widespread non‐random structure in US stream fish communities. Community assembly is governed largely by environmental filtering, followed by predator–prey interactions, whereas the influence of interspecific competition appears minimal. Applying a traits‐based approach to continent‐wide datasets provides a powerful approach for examining the existence of assembly rules in nature.
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 | 0.001 |
| 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".