State of Salmonid Streams Around the World: A Multi-Scale Investigation of Habitat Quality, Restoration, and Abundance
Bibliographic record
Abstract
Many salmonid species are listed as threatened or endangered, despite over a hundred years of conservation efforts. Additionally, little is known about the spatial extent and abundance of salmonid populations around the world. This research combines ecological and hydrogeomorphological approaches to investigate salmonid abundance in streams. It uses a meta-analysis, field observations and a systematic review to assess restoration options for salmonid populations, determine if a morphological index is aligned with physical habitat and fish-based indices, and explore the range of salmonid abundance in streams around the world. Data from 100 stream restoration projects show that in-stream structures, a common restoration technique for salmonids, increase salmonid abundance. However, most projects are implemented at small spatial scales of a few hundred metres, and monitored for less than 5 years, which may be insufficient time for population changes to be apparent. Hence, it is unclear whether these projects provide a long-term solution. The Morphological Quality Index (MQI) considers fluvial processes at larger scales as well as channel forms, human impacts, and historical changes, but few studies have assessed its relevance for ecosystem health. A significant correlation was found between the MQI and habitat quality (using the Qualitative Habitat Evaluation Index, QHEI), in 26 salmonid streams, but establishing a strong correlation with fish metrics remains challenging. To describe the metrics of salmonid abundance at a broader spatial scale, a database was created using published material of over 1000 rivers with estimated salmonid biomass, covering 27 countries. This allowed detailed analyses of differences in biomass by species, region, period, and sampling techniques. Mean global biomass is 5.2 g/m2, and while most streams are under 10 g/m2, there is a large range (0-70.3 g/m2). Salmonid production recorded for 194 rivers averaged 6.3 g/m2/yr, and biomass and production were highly correlated (R = 0.82) with a mean production to biomass (P/B) ratio of 1.08. Expanding the list of variables in the database can help develop models to predict salmonid biomass, and determine conditions in high biomass streams. This knowledge will be useful for conservation and management authorities to design successful conservation programmes at a watershed scale.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".