Decadal‐scale regional changes in <scp>C</scp>anadian freshwater zooplankton: the likely consequence of complex interactions among multiple anthropogenic stressors
Bibliographic record
Abstract
Summary Ecological integrity is increasingly threatened by multiple anthropogenic stressors, but the cumulative impact of stressors is poorly understood because they can interact in unexpected ways. Knowledge of these interactions and their associated impacts is needed to support the conservation of valued ecosystems. We used a large‐scale, replicated field survey and multiple regression analysis to investigate the cumulative impacts of multiple physical, chemical and biological stressors on the crustacean zooplankton assemblages of 34 Canadian Shield lakes between 1980s and 2004–2005. Zooplankton total abundance, species richness, diversity and community structure, as well as the relative abundances of prominent taxonomic orders of zooplankton, changed at a regional scale. These changes occurred in response to changes in water quality and lake thermal regime, and invasion by an exotic predator. Interactions between stressors were common and represented an important determinant of zooplankton assemblage changes over time. We provide the first evidence that the individual and combined impacts of multiple stressors cause regional ecological change over decades. Our results demonstrate the prevalence of stressor interactions in natural environments and highlight the complexity of ecosystem responses to multiple stressors. Zooplankton changes recorded here may be widespread because climate change, acidification, development and the spread of invasive species are globally pervasive. These changes could have cascading impacts because zooplankton is an essential link in aquatic food webs. Our findings highlight the need to consider the interactive effect of stressors when assessing anthropogenic impacts and will inform management and conservation of ecosystems threatened by multiple stressors.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".