Local and latitudinal variation in abundance: the mechanisms shaping the distribution of an ecosystem engineer
Bibliographic record
Abstract
Ecological processes that determine the abundance of species within ecological communities vary across space and time. These scale-dependent processes are especially important when they affect key members of a community, such as ecosystem engineers that create shelter and food resources for other species. Yet, few studies have examined the suite of processes that shape the abundance of ecosystem engineers. Here, we evaluated the relative influence of temporal variation, local processes, and latitude on the abundance of an engineering insect-a rosette-galling midge, Rhopalomyia solidaginis (Diptera: Cecidomyiidae). Over a period of 3-5 years, we studied the density and size of galls across a suite of local experiments that manipulated genetic variation, soil nutrient availability, and the removal of other insects from the host plant, Solidago altissima (tall goldenrod). We also surveyed gall density within a single growing season across a 2,300 km latitudinal transect of goldenrod populations in the eastern United States. At the local scale, we found that host-plant genotypic variation was the best predictor of rosette gall density and size within a single year. We found that the removal of other insect herbivores resulted in an increase in gall density and size. The amendment of soil nutrients for four years had no effect on gall density, but galls were smaller in carbon-added plots compared to control and nitrogen additions. Finally, we observed that gall density varied several fold across years. At the biogeographic scale, we observed that the density of rosette gallers peaked at mid-latitudes. Using meta-analytic approaches, we found that the effect size of time, followed by host-plant genetic variation and latitude were the best predictors of gall density. Taken together, our study provides a unique comparison of multiple factors across different spatial and temporal scales that govern engineering insect herbivore density.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".