Riverine connectivity modulates elemental fluxes through a 200- year period of intensive anthropic change in the Magdalena River floodplains, Colombia
Bibliographic record
Abstract
• Multiple human pressures have changed the sources and concentrations of sediment biogeochemistry in Magdalena River floodplain lakes. • River-lake connectivity modulates human-drivers and sediment biogeochemistry. • Connected lakes receive higher fluxes of heavy metals while isolated lakes accumulate more nutrients and OM. • Land-cover change is more important than climate in shaping the composition of lake sediment biogeochemistry. Tropical floodplain lakes are increasingly impacted by human activities, yet their pathways of spatial and temporal degradation, particularly under varying hydrological connectivity regimes and climate change, remain poorly understood. This study examines surface-sediment samples and 210 Pb-dated sediment cores from six floodplain lakes, representing a gradient in hydrological connectivity in the lower Magdalena River Basin, Colombia. We analysed temporal and spatial variations in several sediment biogeochemical indicators: the concentration and flux of nutrients, heavy metals, and organic matter (OM), and redox conditions, flooding and erosion. Multiple factor analysis (MFA) of surface-sediments identified redox conditions, OM, flooding, heavy metals and lake connectivity as the main contributors to spatial variability within- and between-lakes sediments, accounting for 48 % of the total variation. Additionally, no clear distinction was found between littoral and open-water sediment characteristics. Isolated lakes sediments exhibited reductive conditions rich in OM and nutrients, whereas connected lakes sediments showed greater heavy metal enrichment and higher concentrations of coarse river-fed material. Generalised additive models identified significant changes in the biogeochemical indicators since the late 1800s, that accelerated post-1980s. Shifts in OM, erosion, flooding, redox conditions, land-cover change, heavy metals and climate were identified by MFA as the main drivers of change, explaining 60 %-71 % of the variation in the connected lakes and 53 %-72 % in the isolated lakes. Post-1980s, connected lakes transitioned from conditions of higher accumulation of OM and little erosion to higher accumulation of heavy metals and river-fed material. Conversely, isolated lakes, shifted from detrital-heavy metal-rich sediments to OM-, and nutrient-rich, reductive sediments. Sedimentation rates also surged post-1980s, particularly in highly connected lakes, from 0.14 ± 0.07 g cm² yr⁻¹ to 0.5 ± 0.5 g cm² yr⁻¹, with elevated fluxes of metals, OM and nutrients. These changes in sediment biogeochemistry align with deforestation, river regulation and prolonged dry periods, highlighting the complexities behind establishing reliable reference conditions for pollution assessments in large, human-impacted tropical river systems.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".