The underestimated dynamics and impacts of water-based recreational activities on freshwater ecosystems
Bibliographic record
Abstract
Recreational activities on, in, and along freshwaters (e.g., boating, bathing, angling) positively contribute to human well-being but can also concurrently stress aquatic ecosystems. While outdoor recreation, aquatic ecosystems, and human well-being form coupled social-ecological systems, inherent fluxes and interactions between these have rarely been properly quantified. This paper synthesizes information on links between water-based recreational activities, effects on freshwater ecosystems integrity and recreational quality, and proposes a novel framework for assessment and integrated management. This framework is based on understanding relationships between recreational quality, demand and use, and recreational use-induced impacts on ecosystem state and function, as well as ecological and social carrying capacities. Current management approaches of freshwater ecosystems addressing economic, environmental, or recreational aspects are poorly linked and harmonized, and are further constrained by inadequate information on the dynamics and densities of recreational uses. Novel assessment and monitoring methods are needed to capture the short-term peak dynamics of water-based recreational uses, and we argue social media could play an increasingly important role here. An integrative recreation ecology management concept combined with peak usage information has great potential to form the basis for next-generation management approaches of freshwater and other ecosystems.
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 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 | 0.001 |
| 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 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".