Missing effects of anthropogenic nutrient deposition on sentinel alpine ecosystems
Bibliographic record
Abstract
Anthropogenic nitrogen (N) deposition affects unproductive remote alpine and circumpolar ecosystems, which are often considered sentinels of global change. Human activities and forest fires can also elevate phosphorus (P) deposition, possibly compounding the ecological effects of increased N deposition given the ubiquity of nutrient co-limitation of primary producers. Low N : P ratios coupled with evidence of NP-limitation from bioassays led us to hypothesize that P indirectly stimulates phytoplankton by amplifying the direct positive effect of N (i.e. serial N-limitation) in alpine ponds. We tested the hypothesis using the first replicated N × P enrichment experiment conducted at the whole-ecosystem level, which involved 12 alpine ponds located in the low N deposition backcountry of the eastern Front Range of the Canadian Rockies. Although applications of N and P elevated ambient N and P concentrations by 2-5×, seston and plankton remained relatively unaffected in the amended ponds. However, additions of ammonium nitrate elevated the δ(15) N signals of both primary producers and herbivores (fairy shrimp; Anostraca), attesting to trophic transfer of N deposition to consumers. Further, in situ bioassays revealed that grazing by high ambient densities of fairy shrimp together with potential competition from algae lining the pond bottoms suppressed the otherwise serially N-limited response by phytoplankton. Our findings highlight how indirect effects of biotic interactions rather the often implicit direct effects of chemical changes can regulate the sensitivities of extreme ecosystems to nutrient deposition.
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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 | 0.002 |
| 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 | 0.001 | 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".