The effects of food web structure on ecosystem function exceeds those of precipitation
Bibliographic record
Abstract
Ecosystems are being stressed by climate change, but few studies have tested food web responses to changes in precipitation patterns and the consequences to ecosystem function. Fewer still have considered whether results from one geographic region can be applied to other regions, given the degree of community change over large biogeographic gradients. We assembled, in one field site, three types of macroinvertebrate communities within water-filled bromeliads. Two represented food webs containing both a fast filter feeder-microbial and slow detritivore energy channels found in Costa Rica and Puerto Rico, and one represented the structurally simpler food webs in French Guiana, which only contained the fast filter feeder-microbial channel. We manipulated the amount and distribution of rain entering bromeliads and examined how food web structure mediated ecosystem responses to changes in the quantity and temporal distribution of precipitation. Food web structure affected the survival of functional groups in general and ecosystem functions such as decomposition and the production of fine particulate organic matter. Ecosystem processes were more affected by decreased precipitation than were the abundance of micro-organisms and metazoans. In our experiments, the sensitivity of the ecosystem to precipitation change was primarily revealed in the food web dominated by the single filter feeder-microbial channel because other top-down and bottom-up processes were weak or absent. Our results show stronger effects of food web structure than precipitation change per se on the functioning of bromeliad ecosystems. Consequently, we predict that ecosystem function in bromeliads throughout the Americas will be more sensitive to changes in the distribution of species, rather than to the direct effects caused by changes in precipitation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".