River system classifications and cumulative watershed perspectives to inform sustainable river basin management at global and regional scales
Bibliographic record
Abstract
At present, humans appropriate more than half of the Earth's renewable and accessible water. This high demand for water resources comes at a cost: it puts an estimated 65% of global river discharge under moderate to high threat from anthropogenic drivers of stress. One way to alleviate some of this pressure is to develop and apply sustainable management practices to human activities that affect river systems. To develop best managements practices in this context require methods, data and scientific information that are specific to river systems. Given the interconnectedness of rivers over large spatial extents, sustainable management strategies need to be designed for basin, regional, or even global scales. Sustainable management is multifaceted and often requires drawing information from various disciplines. To advance the sustainable management of large river systems, we need information and data related to different research themes, and we need specific methods that reflect the connected and cumulative nature of river systems. In this thesis, I explore novel data and methods to advance three particular research themes that are closely related to sustainable river management, namely the natural flow regime paradigm, the representation of aquatic biodiversity through proxies, and the concept of hydrologic ecosystem services. I develop one global and three large-scale studies, each representing different contributions, including new data and methods, to the three themes. As an overarching approach to provide and analyze new baseline information, I first develop a multidisciplinary approach to river classification and use it to design a novel river reach typology at the global scale. I then explore this framework for river classifications at two regional scales, where I evaluate river classes (1) as a potential contribution to natural and environmental flow assessments in Canada, and (2) as proxies for fish assemblages in the Greater Mekong Region. Finally, in Canada, I quantify capacity for, demand for, and pressure from freshwater provision and regulation based on hydrological connectivity, and I design a composite indicator of risk to the provision of this hydrologic ecosystem service. The resulting river reach classifications at the global scale, in Canada, and in the Greater Mekong Region provide typologies that can facilitate freshwater conservation efforts and environmental assessments. They also provide a new avenue to support the integration of environmental flow requirements and fish assemblages in large-scale river management. The novel hydrological method to quantify freshwater ecosystem services can be used to design new, large-scale assessments of ecosystem services around the world that account for the connected and cumulative nature of river systems. This quantification also presents a first-time high-resolution mapping of the risk to freshwater provision and regulation in Canada. My conclusions discuss overarching findings from the thesis, including the importance of innovative statistical approaches,…
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.008 | 0.017 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".