Tracking striking algal changes over the last ~400 years using subfossil pigments in a high mountain lake (Sierra Nevada, Spain): Have we entered an unprecedented era?
Bibliographic record
Abstract
Abstract. Remote aquatic ecosystems have been shown to be affected by the rapid intensification of human-driven climate change, along with increasing atmospheric nutrient deposition. There is an increasing body of evidence from paleolimnology that indicates changes in the composition of diatoms due to both factors. However, there is a paucity of studies that examine changes in the composition of the overall algal community over extended periods of time. This study investigates shifts in pigment assemblage composition and algal biomass over approximately the past 430 years, using high-resolution, well-dated sediment cores from Borreguil Lake, a high-altitude lake in the Sierra Nevada Mountains (Southern Spain). Significant changes in both algal biomass and community composition were observed throughout the core, with notable intensification since the ca. 1970s. These changes appear to be a regional response primarily driven by climate and atmospheric aerosols. Algal biomass exhibited two significant peaks approximately between 1740–1840 and from 1970 to the present, with the latter period reaching unprecedented concentrations. Algal composition exhibited two major shifts: one around 1840 and another in the 1970s. From the bottom to the top, these shifts were characterized by an increase in cyanobacteria (indicated by aphanizophyll and scytonemin), cryptophytes (indicated by alloxanthin), and green algae (indicated by lutein and zeaxanthin), at the expense of diatoms (indicated by diatoxanthin). Statistical analyses revealed that both algal biomass and composition were strongly influenced by warming temperatures, reduced precipitation, and enhanced Saharan dust deposition. In particular, the increase in nitrogen-fixing cyanobacteria (indicated by aphanizophyll) since the 1970s has led to previously unrecorded nitrogen fixation in the lake. This is probably due to reduced nitrogen availability linked to enhanced Saharan phosphorus inputs. The observed changes in the algal community, including the significant increase of cyanobacteria biomass, are unprecedented in the last ~400 years in the Sierra Nevada lakes and are likely occurring in other Mediterranean lake regions, particularly in oligotrophic lakes. Projected increases in global temperatures and Saharan dust deposition will likely continue to affect the ecological condition of these ecosystems.
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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 | 0.001 | 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) | 0.000 | 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 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".