Aggregating taxa and the influence of scale: Potential concerns for analysis of stability using functional measures
Bibliographic record
Abstract
Abstract A functional group approach to analyzing ecological processes calls for aggregating species populations' data (e.g., biomass, abundance) into larger functional units. This method offers a more direct insight into the coarse community and ecosystem dynamics than a species level. Since aggregation changes the scale of analysis, it is reasonable to expect that the results and inferences will also change. To gauge the nature and size of this effect, we examined two sets of communities using the same methodology at taxonomic and functional levels. We asked how asynchrony among constituent populations stabilizes the regional biomass or abundance in two systems: zooplankton in North American temperate lakes and rock pool invertebrates in Jamaica. We aggregated species into pairs by organism size for the functional level analysis because it correlates well with life history traits. We hypothesized that taxonomical and functional level analyses would yield different pictures and inferences. We analyzed asynchrony among local populations, metapopulations, and populations of different species at different locations. We found that in lakes, different asynchrony classes contributed to the stabilization of the regional metric than in the rock pools. We further found that aggregation of taxa into functional units changed the pattern of differences between lakes and rock pools revealed by taxonomical analysis and that each set of communities responded differently to species lumping. While aggregating taxa leads to different results, the taxonomic and functional lenses add new insights to the biological interpretation of mechanisms stabilizing communities when interpreted jointly. Specifically, population asynchrony—a known stabilizing factor—can provide complementary stabilizing mechanisms when seen through taxonomic and functional lenses. Without exposing these modes, inferences about abundance/biomass/richness stabilizing contributions arising from asynchrony will remain tenuous. Exposing these modes offers a path for significant breakthroughs in linking local, spatial, and functional structures to multispecies system dynamics.
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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".