Short-term effects of anthropogenic sediment additions on biogeochemical properties of the Fraser River Estuary
Bibliographic record
Abstract
Intertidal mudflats are globally important ecosystems in estuaries. In the Fraser River Estuary in British Columbia, Canada, these habitats host diverse surficial biofilms (microphytobenthos and other microorganisms) that underpin several important functions, including supporting estuarine food webs, biogeochemical cycling, the latter including nutrient provisioning that sustains benthic productivity. However, these habitats are suffering from elevation loss and habitat degradation due to sediment deficit, elevated salinity, relative sea-level rise, and herbivory of migratory birds. Recently, mudflats at Sturgeon Bank, Fraser River Estuary, British Columbia, Canada, have received managed sediment additions as part of the broader Sturgeon Bank Sediment Enhancement Pilot Project at the estuary. The short-term biogeochemical responses of intertidal biofilms can be used as an early signal to assess restoration effectiveness and to predict potential ecological outcomes of restoration interventions. This study compared sediment attributes (organic matter, photosynthetic pigments, and fatty acid composition) at Sturgeon Bank at treatment and control sites under a modified Before-After-Control-Impact (BACI) design, spanning four sampling years in the springs from 2022 to 2024 and from winter to summer in 2025. Linear-mixed effects modelling and analysis of variance revealed that the studied parameters varied annually from 2022 to 2025, with few differences between treatment and control sites, and only a significant treatment-by-year interaction for organic matter in 2025. However, fatty acid analyses indicated potential shifts in the community composition of intertidal biofilm towards greater contributions of dinoflagellates and bacteria at treatment sites. These findings demonstrate that estuarine mudflat ecosystems are highly dynamic and can be resilient to anthropogenic sediment additions. Interannual variability in hydrodynamics and climate were important factors in changes to biofilm biomass, nutritional quality, and phytoplankton taxonomic composition, with mud surface temperature, solar radiation, and freshet-induced salinity fluctuations exerting stronger impacts than the sediment treatment itself. These results highlight the significance of integrating biogeochemical monitoring with traditional physical and meteorological metrics to accurately assess restoration outcomes in dynamic estuaries. This study provides a foundation for adaptive management strategies and informs blue carbon accounting efforts in sediment-deficient coastal ecosystems globally.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.001 | 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 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".