Assessing the Legacy of Large Woody Debris as Coastal Protection in BC and Washington
Bibliographic record
Abstract
Large Woody Debris (LWD) accumulates naturally in the coastal environment (Brennan et al., 2009; Sass, 2009) and is thought to be a vital component of a diverse coastal habitat ( Rich et al., 2014). Decreasing natural coverage of LWD (Heathfield & Walker, 2011) and increasing demand for environmentally sensitive coastal protection techniques has led to the promotion of LWD as a viable nature-based method of shoreline protection (e.g. Johannessen et al., 2014; Stewardship Centre for BC, 2016; Washington Department of Fish and Wildlife, 2016). However, there is currently no peer-reviewed literature assessing the efficacy of coastal protection using LWD. This presentation will summarize the results of field investigations focused on assessing the legacy of existing coastal protection or restoration projects using LWD in BC and Washington. Over 30 project sites were identified as having used LWD as a component of the project, generally with the aim of reducing wave induced flooding and/or shoreline erosion. Between June – August 2019, field investigations were conducted at 15 of these existing installations in BC and Washington. The projects ranged in installation date (1999-2018), extent (small private-properties to extensive parks), and design (groynes to large matrix-style installations). Measurements of the LWD placement elevation and beach slope were made using an RTK GPS within BC, and a rotary laser level and rod within Washington where site-access permitted. Surficial sediment sizes were estimated using digital grain size analysis. Additional observations were made on log size, anchoring technique, signs of beach erosion/accretion, and signs of damage to the LWD or anchoring system. This presentation will provide background on the monitoring techniques utilized, summarize key findings of the field investigation, provide preliminary design guidance for the use of LWD as coastal protection, and highlight the value of monitoring and re-evaluating legacy projects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".