Effect of Artificial Nesting Structure Density on Canada Goose Reproductive Success
Bibliographic record
Abstract
We sampled earthworms in Lexington, Kentucky, and compared populations in high-maintenance lawiis (maintained by professional lawn-care companies) to those in low-maintenance lawns (maintained by indi- vidual owners without the use of lawn-care chemicals).We sampled 15 high-maintenance and 15 low- maintenance lawns with similar distributions in terms of geographic location within Lexington, age of house, and length of time the lawn was managed under the current maintenance regimen.Earthworms were col- lected during the period 6 Apr-10 Apr 1998 in each lawn by using formalin as an extractant.Significantly more earthworms per unit area were collected from high-maintenance as from low-maintenance lawns.Conversely, low-maintenance lawns had significantly greater earthworm dn' mass per unit area and dn-mass per individual earthworm.These results suggested that high-maintenance lawn care resulted in stunted growth of earthworms.Since earthworms are one of the most important members of the soil fauna, we suggest that organic methods and alternative plant systems be substituted for chemically maintained lawns.' Corresponding author.biological indicators of soil qualit)-(Blair et al.Journal of the Kfiituck)' Academy of Science 61(1) no significant difference (P = 0.19) between ilirect toxicity, such adverse effects may be the two tvpes of lawns in the proportion of sublethal and chronic, resultinii; in slow growth specimens that were innnature; the median or weight loss (Edwards and Bohlcn 1996).value was 72%.Mitvimum earthworm lengths Since low-miiintenance and high-maintenance were 60 and 65 mm, respectively, in high-lawns were similar in terms of house age and maintenance and low-maintenance lawns; length of time each maintenance regimen had large specimens of L. tcrrcstris were not col-been in use, the direct effect of maintenance lected.Significantlv more earthworms pi-r imit regimen was not confoimded by residues from area v\ere collected from high-inaintenancc i>ast practices or In unecjual representation of versus low-maintenance lawns(Table1). Conold and new houses.some lawn and agricultural chemicals may ad-come more popular with homeowners as in- versely affect non-target organisms including formation on organic practices (e.g., WSHUearthworms and other soil invertebrates (Pot-FM and Duesing 1999) and commercial ser- ter 1994; Potter et al. 1990).In addition to vices (e.g., Bass Custom Landscapes, Inc. Earthworms in Lawns -Jones and Kalisz 1999) becomes available through the internet (e.g., WSHU-FM and Duesing 1999) and as recommendations on specific techniques be- come available through government organiza- tions such as the USDA Cooperative Extension Service (e.g., Bruneau et al. 1997).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".