Age-Structured Interactions among Reintroduced Sockeye Salmon, Resident Kokanee, Invasive Mysids, and their Zooplankton Prey in Skaha Lake, British Columbia
Bibliographic record
Abstract
Abstract In 2004, after an 85+ year absence, Sockeye Salmon Oncorhynchus nerka were reintroduced into Skaha Lake, British Columbia. Prior to this, the lake’s planktivore community was dominated by kokanee (lacustrine Sockeye Salmon) and an invasive freshwater shrimp Mysis diluviana, and British Columbia fisheries managers were concerned that reintroduced Sockeye Salmon fry might reduce the abundance of zooplankton prey and negatively affect the abundance and size of kokanee available for the recreational fishery. We looked for possible adverse effects by introducing contrasting densities (0–2,309 fish/ha) of marked, hatchery-origin Sockeye Salmon fry to Skaha Lake over 12 years (2005–2017). During each year, we monitored state change indicators of lake flushing, water temperature, nutrients, phytoplankton, microzooplankton, M. diluviana, kokanee, and Sockeye Salmon. Zooplankton consumption by Sockeye Salmon, kokanee, and M. diluviana was estimated via bioenergetics models. We found that (1) average densities of pelagic fish gradually increased above premanipulation densities and (2) survival (egg to winter) of kokanee fry was variable but positively associated with increased abundances of Sockeye Salmon fry. Average survival of age-0 to age-3+ kokanee in Skaha Lake exhibited no significant trends. We also found that (3) growth rates for age-0 Sockeye Salmon fry and kokanee were stable during 2005–2013, despite moderate increases in fish abundance, but declined in 2017. This decline was associated with record-high biomasses of kokanee and M. diluviana, record rates of zooplankton loss from predation and lake flushing, and reduced zooplankton production. We found that (4) bioenergetics data showed that, on average, 1.8% of annual zooplankton prey consumption was attributable to hatchery-origin Sockeye Salmon fry, 2.8% to Lake Whitefish Coregonus clupeaformis, 13.9% to older kokanee, and 79.6% of the zooplankton was consumed by M. diluviana. We concluded that during 2005–2015 consumption by planktivores never exceeded production by zooplankton, but in 2017, when lake flushing rates were exceptionally high, consumption by planktivores exceeded lake-carrying capacity for pelagic fish. Sockeye Salmon fry played virtually no part in these events.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".