Coupled Biospheric Synchrony of the Coastal Temperate Ecosystem in Northern Patagonia: A Remote Sensing Analysis
Bibliographic record
Abstract
Over the last century, climate change has impacted the physiology, distribution, and phenology of marine and terrestrial primary producers worldwide. The study of these fluctuations has been hindered due to the complex response of plants to environmental forcing over large spatial and temporal scales. To bridge this gap, we investigated the synchrony in seasonal phenological activity between marine and terrestrial primary producers to environmental and climatic variability across northern Patagonia. We disentangled the effects on the biological activity of local processes using advanced time-frequency analysis and partial wavelet coherence on 15 years (2003–2017) of data from MODIS (Moderate Resolution Imaging Spectroradiometer) onboard the Terra and Aqua satellites and global climatic variability using large-scale climate indices. Our results show that periodic variations in both coastal ocean and land productivity are associated with sea surface temperature forcing over seasonal scales and with climatic forcing over multi-annual (2–4 years) modes. These complex relationships indicate that large-scale climatic processes primarily modulate the synchronous phenological seasonal activity across northern Patagonia, which makes these unique ecosystems highly exposed to future climatic change.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".