An urban wildlife habitat experiment: conservation implications of altering management regimes on animals and plants along urban and rural rights-of-way
Bibliographic record
Abstract
Abstract Biodiversity along rights-of-way (ROWs) can decline due to local-scale management, including frequent urban mowing and spraying, or with increasing amount of urban infrastructure surrounding those grassy spaces. Distinguishing effects of mowing regime from effects of surrounding urban land are necessary to determine what management strategies effectively conserve wildlife in different landscapes, and to justify changes in management that could increase populations of weeds. We used a manipulative Before/After-Control/Impact (BACI) experiment in 17 transmission line ROWs during 2007–2009, along an urbanization gradient, to disentangle effects of mowing frequency and the amount of urban land (buildings, hard surfaces like concrete, asphalt) surrounding ROWs. In the BACI study, we halted mowing and spraying for 1 year in five urban ROWs, introduced two rounds of mowing per year in three rural ROWs, and compared vegetation and arthropods found within these manipulated ROWs and within three urban and six rural control ROWs. European skipper butterflies Thymelicus lineola, lepidopteran biomass in herbaceous vegetation, milkweeds (Asclepias spp.) and Canada thistle Cirsium arvense increased when mowing and spraying were halted for one year. Conversely, monarch butterflies Danaus plexippus, legume cover and dandelion Taraxacum officinale increased when mowing was introduced to rural ROWs. To increase taller butterfly resource plants while still controlling weeds within urban ROWs, we recommend reducing management frequency within the interior of ROWs while maintaining frequent management along ROW borders that are adjacent to infrastructure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".