Nesting ecology of a population of red-necked grebes in Northwestern Ontario
Bibliographic record
Abstract
One of the largest, documented breeding populations of Red-necked Grebes \n(Podiceps grisegena holboelli) in the world was studied at Whitefish Lake, Ontario in \n1993 and 1994. Whitefish Lake (WFL) represents a unique area compared to other \nstudy sites that show mostly solitary nesting Red-necked Grebes or a few pairs/lake. \nThe population of nesting Red-necked Grebes at WFL is large for this species. It is also \nexceptionally dense (mean 1.01 pair per hectare) for this territorial species and could be \nconsidered a semi-colonial situation. The mean number of pairs nesting on the lake for \n1993 and 1994 was 49 (range 59-39). \nThe objective of the study was to expand on the limited information available on \nthe Red-necked Grebe and to acquire data on nest and nest-site characteristics, egg \nmeasurements, clutch size, egg laying period, incubation period, hatching success, and \nyoung produced. Census results for 1993 show that peak nesting occurred on 21 June \nwith 59 nests with eggs. Total number of eggs reached a maximum for 1993 at n = 202 \nfor 21 June. Total nests with eggs peaked n = 39 on 22 June, 1994 while total eggs (n \n= 135) peaked on 30 June, 1994. \nThe population is strongly associated with uncultivated wild rice (Zizania \npalustris) stands in shallow bays of the lake. Shallow, uniform water depth, and the \nhigh productivity of Whitefish Lake provide abundant food and vegetation for grebe \nbreeding activities. Eighty-five percent of 121 nests in 1994 were constructed primarily \nof wild rice, the most abundant emergent species in the study area. One hundred and six of the 121 (88%) of the nests at Whitefish Lake were floating nests attached to the \nlake substrate by a column of sub-surface vegetation and detritus. \nNest-site selection in Red-necked Grebes is influenced by underwater \ncharacteristics such as water depth, availability of nest material and anchors for the \nnest. Early evidence of future plant emergence, (future) shelter from wind and waves \nand protection/concealment from predators and some form of anchorage (debris, sticks \nor logs) evident only from underwater searches. \nA factorial ANOVA revealed significant differences between nest and non-nest \nsites for depth and vegetation density. Water depth at nests (57.4 ? 35.3 cm, n = 180) \nwas significantly shallower than non-nest sites (86.9 ? 27.9 cm, n = 120). Overall \nvegetation density was higher for nest sites than non-nest sites. \nMean distance for nearest neighbour for 148 nests at Whitefish Lake was 27.2 ? \n30.0 m (range 1.5-185). Aggregation indices calculated from study area indicated that \nclumping occurred and a simple test of significance for deviation from randomness \nrevealed significant differences for all of eleven sections sampled. \nWater depth and vegetation density must be considered when evaluating the \nquality of territory selected by grebes. A study investigating all variables potentially \nassociated with breeding success is recommended. Since aggregations of this size and \ndensity are so rare for this grebe species. Whitefish Lake represents a suitable site for \nfuture research. \nThere are over 50,000 lakes in Ontario (OMNR) in which only a handful of have \nbeen identified to have nesting Red-necked Grebes. Regional and provincial surveys \ncould provide additional data for comparison with Whitefish and other lakes. It is important to establish more specific hypotheses on the habitat and nest site selection of \nthis Grebe and perhaps determine the variables that can be attributed to their breeding \nsuccess in Ontario.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 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".