Hierarchical regulation of pelagic invertebrates in lakes of the northern Great Plains: a novel model for interdecadal effects of future climate change on lakes
Bibliographic record
Abstract
Endorheic lakes of the northern Great Plains encompass a wide range of environmental parameters (e.g., salinity, pH, DOC, Ca, nutrients, depth) that vary 1000-fold among sites and through the past 2000 years due to variation in basin hydrology and evaporative forcing. However, while many environmental parameters are known to individually influence zooplankton diversity and taxonomic composition, relatively little is known of the hierarchical relationships among potential controls or of how regulatory mechanisms may change in response to climate variation on diverse scales. To address these issues, we surveyed 70 lakes within a 100 000 km2 prairie region to simulate the magnitude of environmental change expected to occur over 100–1000 years and to quantify the unique and interactive effects of diverse environmental parameters in regulating pelagic invertebrate community structure at that scale. Multivariate analyses showed that salinity was the principal correlate of changes in invertebrate composition among lakes, with a sequential loss of taxa between salinities of 4 and 50 g total dissolved solids L−1 until one to two species predominated in highly saline systems. In contrast, changes in the concentrations of Ca2+ and other mineral nutrients exerted secondary controls of invertebrate assemblages independent of salinity, whereas lake depth provided a tertiary regulatory mechanism structuring species composition. In contrast to these large-scale hierarchical patterns, seasonal surveys (May, July, September) of a subset of 21 lakes in each of 2003–2005 revealed that annual meteorological variation had no measurable effect on pelagic invertebrates, despite large differences in temperature, precipitation, and evaporation arising from regional droughts. Together these findings show that pelagic invertebrate communities in saline lakes are resilient to interannual variability in climate, but suggest that lakes of the northern Great Plains may provide a sensitive model to forecast centennial effects of future climate change.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".