The “Blue” Habitat of Urban & Suburban Areas and approaches for its biodiversity research: A scoping review
Bibliographic record
Abstract
This article explores recent research initially driven by interest in studying the “Blue” Habitat of Urban and Suburban Areas (BHUS), focusing on water-related ecosystems. BHUS, encompassing a wide range of aquatic habitats, is crucial to ecosystem health but is increasingly threatened by biodiversity loss resulting from climate change, land-use expansion, and unsustainable practices. Through a scoping review of 93 peer-reviewed studies, this article establishes a framework to classify BHUS types, identify target species, and analyze diverse and latest techniques in water system research. The main themes for studying biodiversity and environmental aspects of these blue habitats are highlighted, along with the urgent need to address BHUS in urban biodiversity conservation. Findings reveal that water systems are biologically rich but present unique research challenges due to their variability and dynamic, interconnected nature. While there is growing recognition of the need to consider human influence, many studies overlook the complex, adaptive nature of BHUS as an integrated system. The article gives insight into establishing a comprehensive framework and integrating diverse methodologies and technologies for specialized research of the BHUS biodiversity, emphasizing the role of advancing technologies and interdisciplinary collaboration between urbanism and ecology. These approaches are essential to support sustainable development that addresses conservation needs and mitigates urbanization's impacts on BHUS. Further research should explore how spatial planning and strategies can more effectively integrate blue habitats to strengthen biodiversity conservation within the global urbanization context. • The “Blue” Habitat of Urban and Sub-urban Areas (BHUS), focusing on water ecosystems within the global urbanization context. • Urban growth led to blue habitat loss and biodiversity decline, while remaining underexplored in spatial planning. • Classify BHUS types, identify species, outline main themes for studying the BHUS. • Advanced techniques offer significant opportunities to enhance BHUS conservation efforts.
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.014 | 0.016 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".