The urgent need to identify thresholds to use for decisions about shoreline and riparian development in freshwater systems
Bibliographic record
Abstract
Abstract Freshwater shorelines, including adjacent riparian habitats, are dynamic intersections between land and water that contribute to the maintenance of biodiversity in both realms. These areas are also affected by multiple stressors at local and global scales, from development to climate impacts. Despite increasing alterations to these areas, often to the detriment of connected ecosystems, and despite many regulations for residential and commercial development, there are no established thresholds across countries and governance levels for how much shoreline or riparian development is too much to maintain freshwater ecosystem function. The urgent need to identify thresholds for shoreline and riparian development in freshwater systems is complicated by a number of challenges, yet there is evidence that threshold effects occur after only a small area of a watershed is developed. Here, we summarize current information on development thresholds for shoreline and riparian areas of freshwater systems. We then discuss the inherent challenges in assigning numeric values to such a diverse set of ecosystems (spanning wetlands, lakes, streams, and more), including considerations such as temporal lags, spatial scales, and cumulative effects. We conclude with a call for research needed to overcome knowledge gaps that will enable practitioners to apply scientifically-robust thresholds to decisions regarding shoreline and riparian development. Doing so will benefit all actors by providing evidence to support shoreline policies and development guidelines that are inclusive of the aesthetic, recreational, and functional aspects of freshwater systems.
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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 | 0.003 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".