THE RELATION BETWEEN PRODUCTIVITY AND SPECIES DIVERSITY IN TEMPERATE–ARCTIC MARINE ECOSYSTEMS
Bibliographic record
Abstract
Energy variables, such as evapotranspiration, temperature, and productivity explain significant variation in the diversity of many groups of terrestrial plants and animals at local to global scales. Although the ocean represents the largest continuous habitat on earth with a vast spectrum of primary productivity and species richness, little is known about how productivity influences species diversity in marine systems. To search for general relationships between productivity and species richness in the ocean, we analyzed data from three different benthic marine ecosystems (epifaunal communities on subtidal rock walls, on navigation buoys in the Gulf of St. Lawrence, and Canadian Arctic macrobenthos) across local to continental spatial scales (<20 to >1000 km) using a standardized proxy for productivity, satellite-derived chlorophyll a. Theoretically, the form of the function between productivity and species richness is either monotonically increasing or decreasing, or curvilinear (hump- or U-shaped). We found three negative linear and three hump-shaped relationships between chlorophyll a and species richness out of 10 independent comparisons. Scale dependence was suggested by more prevalent diversity-productivity relationships at smaller (local, landscape) than larger (regional, continental) spatial scales. Differences in the form of the functions were more closely allied with community type than with scale, as negative linear functions were restricted to sessile epifauna while hump-shaped functions occurred in Arctic macrobenthos (mixed epifauna, infauna). In two of the data sets, (St. Lawrence epifauna and Arctic macrobenthos) significant effects of chlorophyll a co-varied with the effects of salinity, suggesting that environmental stress as well as productivity influences diversity in these marine systems. The co-varying effect of salinity may commonly arise in broad-scale studies of productivity and diversity in marine ecosystems when attempting to sample the largest range of productivity, often encompassing a coastal-oceanic gradient.
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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 | 0.001 | 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) | 0.000 | 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".