Marine‐derived nutrients shape the functional composition of High Arctic plant communities
Bibliographic record
Abstract
Abstract Low temperatures and nutrient limitation have shaped Arctic plant communities, which are now affected by biome‐wise changes in both climate and nutrient cycling. Rising temperatures are favouring taller plant species with more resource‐acquisitive traits across the Arctic tundra. Simultaneously, declines in seabird populations may reduce subsidies of marine‐derived nutrients to terrestrial ecosystems, potentially favouring more resource‐conservative plant traits. It is crucial to understand the consequences of these concurrent changes in climate and marine‐derived nutrient inputs from seabirds for the functional composition and roles of Arctic plant communities. We use a 'space‐for‐time approach' to compare the functional composition of vascular plant communities across two elevational gradients in High Arctic Svalbard, one where climate is the major environmental driver and one influenced by nutrient input from a seabird colony. We assess changes in 13 traits related to plant size, leaf economics and nutrient cycling along the two gradients, and we also explore the relative contributions of species turnover and intraspecific variation to total trait variation across and between the gradients. Elevation per se had little impact on the plant functional composition. Instead, plants at the top of the seabird nutrient gradient, closest to the nesting sites, were taller and had resource‐acquisitive trait values, such as larger and thicker leaves and higher leaf nutrient contents. Enriched soil δ15N‰ signatures at these sites correlated with resource‐acquisitive values of leaf area, specific leaf area, leaf dry matter content, leaf phosphorous content and with enriched leaf δ15N‰ signatures. This variation in leaf economic traits and isotopes was largely driven by intraspecific variation at the nutrient gradient, whereas species turnover dominated at the reference gradient. Our results are consistent with marine‐derived nutrient subsidies from seabirds being a major driver of functional trait variation in Arctic vegetation. Ongoing declines in seabird populations may therefore affect terrestrial primary producer communities in the Arctic and beyond, with potentially important but unknown implications for biodiversity, consumer and decomposer communities, and ecosystem processes. Read the free Plain Language Summary for this article on the Journal blog.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".