Northern hemisphere photosynthetic trends 1982–99
Bibliographic record
Abstract
Abstract We examined trends in the averaged May–September AVHRR normalized difference vegetation index (NDVI) from 1982 to 1999 for the northern hemisphere. NDVI is closely related to the amount of absorbed photosynthetically active radiation; hence, trends in NDVI reflect trends in photosynthetic activity of land‐surface vegetation. Linear and nonlinear trend analysis techniques were applied to four differently processed and corrected Advanced Very High Resolution Radiometer (AVHRR) NDVI data sets. The results were compared in order to evaluate the effects of trends in NDVI unrelated to vegetation activity. We consistently found significant positive trends in averaged NDVI for latitude bands above 35°N in all but one data set; this one data set lacked corrections for sensor drift and instrument calibration. An impressive improvement in data quality was achieved by applying calibration and corrections for atmospheric effects. Conservative estimates of the trends over the 1982–99 period range from 0.0015 to 0.0045 NDVI units year −1 for global latitude bands from 35 to 75°N, with trends generally higher in the 1990s than in the 1980s; trends in NDVI were larger than trends explained by artefacts. In the 1980s, North American and Eurasian trends were roughly comparable, whereas in the 1990s the North American trends were generally higher. A pixel‐level analysis shows the trends to be widespread, with large areas of Canada, Europe and northern Asia experiencing significant positive increases across all vegetated landcovers.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.002 | 0.001 |
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".