Landscape effects of climate, agriculture, and urbanization on benthic invertebrate communities of Canadian prairie lakes
Bibliographic record
Abstract
Paleoecological analyses of fossil chironomid assemblages from eight lakes of the Qu'Appelle Valley, Saskatchewan, Canada, were used to quantify the relative influence of climate, resource use, and urbanization on benthic invertebrate communities 1850–1995. Fossil analyses inferred that Qu'Appelle lakes are naturally productive but that invertebrate communities were altered by agriculture and urbanization. In western lakes, rates of community change (chord distance per 5 yr) were low and nonsignificant (P < 0.05) prior to European settlement, but increased twofold after ~1930–1940. In contrast, uniformly significant rates of community change were recorded in eastern downstream lakes only after the 1960s. In both cases, high rates of change corresponded to alterations in the balance between deep‐water (Chironomus) and littoral species (Cladotanytarsus mancus group, Tanytarsus s.lat. [s.l.]). Comparison of historical and fossil time series (~1920–1993) using variance partitioning analysis (VPA) explained up to 86.6% of past variations in chironomid community composition. Unexpectedly, climate (winter temperature) explained a significant (P , 0.05) and substantial (mean ± SD, n =5 8; 24.8 ± 21.9%) amount of community variance at all sites except Round Lake. In contrast, land‐use practices exhibited significant but less substantial (6.7 ± 6.1%, n = 8) impacts on zoobenthos of five lakes, whereas significant urban impacts (3.6 ± 7.5%, n = 8) were recorded only at two sites. Similarly, redundancy analysis showed that minimum winter or spring temperature significantly influenced the relative abundance of littoral taxa in seven lakes. Such strong effects of climate on benthic invertebrate communities contrast its weak effects on phytoplankton in these lakes and suggest that future environmental change may be expressed differentially among habitats.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".