Putting the Lake Back Together: Reintegrating Benthic Pathways into Lake Food Web Models
Bibliographic record
Abstract
Lakes are often used as model ecosystems because they have clearly defined boundaries and identifiable connections with adjacent ecosystems. Furthermore, small lakes are tractable units for construction of ecosystem energy budgets and whole-ecosystem experiments. Thus, limnology has contributed substantially to the understanding of basic ecological principles. However, limnologists themselves are inconsistent in their treatment of the very boundaries that make lakes such valuable conceptual models for ecosystem ecology. The body of limnological research in recent decades has had an overwhelmingly pelagic focus, with the benthic habitat often viewed as merely a source or sink of pelagic nutrients or energy. Two seminal papers in ecology, “The Trophic Dynamic Aspect of Ecology” (Lindeman 1942) and “The Lake as a Microcosm” (Forbes [1887] 1925), fully integrated benthic processes into their description of lake dynamics. Even though these works are still frequently cited, benthic and pelagic habitats have often been treated as discrete food webs with parallel but separate compartments of bacteria, primary producers, and consumers. Thus, most limnologists study either the benthic or, more often, the pelagic habitat, although research on the role of macrophytes in shallow lakes is one important exception (Sand-Jensen and Borum 1991, Scheffer et al. 1993, Jeppesen et al. 1998). We examined the role of benthic primary and secondary production in lake food webs to demonstrate that division of lakes into benthic or pelagic habitats, to be studied in isolation by different researchers, skews the perception of lake food webs. This is particularly true for most of the world's lakes, which are small and have high ratios of littoral surface area to pelagic volume (Wetzel 1990). We chose to use the word reintegrating in our title because we are appealing for a return to the roots of limnological research, in which benthic pathways are viewed as fundamental to a thorough understanding of lake ecosystem function.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".