Resource modification by ecosystem engineers generates hotspots of stream community assembly and ecosystem function
Bibliographic record
Abstract
Ecosystem engineers can generate hotspots of ecological structure and function by facilitating the aggregation of both resources and consumers. However, nearly all examples of such engineered hotspots come from long-lived foundation species, such as marine and freshwater mussels, intertidal cordgrasses, and alpine cushion plants, with less attention given to small-bodied and short-lived animals. Insects often have rapid life cycles and high population densities and are among the most diverse and ubiquitous animals on earth. Although these taxa have the potential to generate hotspots and heterogeneity comparable to that of foundation species, few studies have examined this possibility. We conducted a mesocosm experiment to examine the degree to which a stream insect ecosystem engineer, the net-spinning caddisfly (Tricoptera:Hydropsychidae), creates hotspots by facilitating invertebrate community assembly. Our experiment used two treatments: (1) stream benthic habitat with patches of caddisfly engineers present and (2) a control treatment with no caddisflies present. We show that compared to controls, caddisflies increased local resource availability measured as particulate organic matter (POM) by 43%, ecosystem respiration (ER) by 70%, and invertebrate density, biomass, and richness by 96%, 244%, and 72%, respectively. These changes resulted in increased spatial variation of POM by 25%, invertebrate density by 76%, and ER by 29% compared to controls, indicating a strong effect of caddisflies on ecological heterogeneity. We found a positive relationship between invertebrate density and ammonium concentration in the caddisfly treatment, but no such relationship in the control, indicating that either caddisflies themselves or the invertebrate aggregations they create increased nutrient availability. When accounting for the amount of POM, caddisfly treatments increased invertebrate density by 48% and richness by 40% compared to controls, suggesting that caddisflies may also enhance the nutritional quality of resources for the invertebrate assemblage. The caddisfly treatment also increased the rate of ecosystem respiration as a function of increasing POM compared to the control. Our study demonstrates that insect ecosystem engineers can generate heterogeneity by concentrating local resources and consumers, with consequences for carbon and nutrient cycling.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 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".