Temporal Variability of MODIS Phenological Indices in the Temperate Rainforest of Northern Patagonia
Bibliographic record
Abstract
Western Patagonia harbors unique and sparsely studied terrestrial ecosystems that are threatened by land use changes and exposure to basin-scale climatic variability. We assessed the performance of two satellite vegetation indices derived from MODIS–Terra, EVI (Enhanced Vegetation Index) and NDVI (Normalized Difference Vegetation Index), over the northern and southern sectors of the Chiloé Island System (CIS) to advance our understanding of vegetation dynamics in the region. Then we examined their time-varying relationships with two climatic indices indicative of tropical and extratropical influence, the ENSO (El Niño–Southern Oscillation) and the Antarctic Oscillation (AAO) index, respectively. The 17-year time series showed that only EVI captured the seasonal pattern characteristic of temperate regions, with low (high) phenological activity during Autumn-Winter (Spring–Summer). NDVI saturated during the season of high productivity and failed to capture the seasonal cycle. Temporal patterns in productivity showed a weakened seasonal cycle during the past decade, particularly over the northern sector. We observed a non-stationary association between EVI and both climatic indices. Significant co-variation between EVI and the Niño–Southern Oscillation index in the annual band persisted from 2001 until 2008–2009; annual coherence with AAO prevailed from 2013 onwards and the 2009–2012 period was characterized by coherence between EVI and both climate indices over longer temporal scales. Our results suggest that the influence of large-scale climatic variability on local weather patterns drives phenological responses in the northern and southern regions of the CIS. The imprint of climatic variability on patterns of primary production across the CIS may be underpinned by spatial differences in the anthropogenic modification of this ecosystem, as the northern sector is strongly modified by forestry and agriculture. We highlight the need for field validation of satellite indices around areas of high biomass and high endemism, located in the southern sector of the island, in order to enhance the utility of satellite vegetation indices in the conservation and management of austral ecosystems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 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 teacher head, 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".