Lower Trophic Relations within the Lake Ontario Invertebrate Community as Assessed by Chemical Tracers
Bibliographic record
Abstract
The lower trophic food web of Lake Ontario plays an important role in the lake’s ecosystem, yet the trophic relationships of these taxa are not well understood. Utilizing carbon (δ13C) and nitrogen (δ15N) stable isotopes as a tool to trace the flow of energy through the system, the main objective of this thesis was to understand the isotopic variability and trophic relationships of invertebrate taxa through space and season in Lake Ontario. Using an extensive dataset collected in 2012 and 2013, this study was conducted in two research chapters. The first chapter assessed variation in the isotopic signature of three important groups, two invertebrate species and particulate organic matter (POM). To account for lipid biases on δ13C, two lipid normalization models were developed for Mysis and Dressiends and were found to be more efficient for freshwater invertebrates than existing models for marine invertebrates and fish. Variation in the isotopic signature of POM was related to the variation in the amount of carbon and nitrogen in the water column as it changes throughout the year. Both δ13C and δ15N in Mysis showed similar seasonal trends to POM, a common baseline in freshwater systems, which demonstrates the pelagic diet of Mysis and the effectiveness of POM as a baseline for pelagic taxa. Dreissenid isotopes also followed POM, but had strong relationships with depth, suggesting that POM is less relevant of a baseline for this filter feeding species in the offshore. An increase in observed dreissenid δ15N with depth was attributed to a greater dependence on microbes in their diet. Chapter three focused on the resource partitioning of the lower trophic invertebrate functional feeding groups of Lake Ontario, including benthic invertebrates, sessile filter feeders, pelagic herbivores, and pelagic predators. Utilizing 13 taxa and quantifying isotopic niche for each taxon to compare across several seasonal and spatial variables, this study found a high degree of overlap in resource use among Lake Ontario functional invertebrate groups. Additionally, pelagic herbivores and sessile filter feeders were utilizing similar resources in the nearshore but utilized different resources in the offshore. Pelagic taxa in Lake Ontario were less sensitive to site depth than benthic taxa as productivity declines with depth from the surface. This study demonstrates that to accurately quantify energy pathways in Lake Ontario, and likely all large lakes, baselines should be sampled from both the nearshore and offshore. Further, stable isotope baselines are essential to understanding the isotopic variation of a system that is unrelated to diet, but they must be sampled thoroughly and well understood before conclusions about food web structure and function can be fully understood.
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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 | 0.002 | 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".