Inhibitive Effects of Recent Exceeding Air Temperature Optima of Vegetation Productivity and Increasing Water Limitation on Photosynthesis Reversed Global Greening
Bibliographic record
Abstract
Abstract Global terrestrial vegetation dynamics have been rapidly altered by climate change. A widespread vegetation greenness over a large part of the planet from the 1980s to early this century has been reported, whereas weakening of CO 2 fertilization effects and increasing climate extremes and the adverse impact of increasing rate of warming and severity of drought on vegetation growth were also reported. Earth system models project that the land carbon sink will decrease in size in response to an increase in warming during this century. How global vegetation is changing during this century in response to global warming and water availability across spatial and temporal scales remains uncertain. Our understanding of the widespread vegetation greening or browning processes and identifying the biogeochemical mechanisms remain incomplete. Here we use multiple long‐term satellite leaf area index (LAI) records to investigate vegetation growth trends from 1982 to 2018. We find that the widespread increase of growing‐season integrated LAI (greening) since 1980s was reversed ( p ‐value < 0.05) around the year 2000 over 90% of the global vegetated area, and continued in only 10% of the global vegetated area. The reversal of greening trend was largely explained by the inhibitive effects of excessive optimal temperature on photosynthesis in most of the tropics and low latitudes, and by increasing water limitation (increasing in atmospheric vapor pressure deficit and decreasing in soil water availability) in the northern high latitudes (>45°N). Overall, the reversal of greening trend since 2000 weakened the negative feedback of carbon sequestration on the climatic system and should be considered in the strategies for climate warming mitigation and adaptation. Our findings of the diversity of processes that drive browning across bioclimatic‐zones and ecosystems and of how those driving processes are changing would enhance our ability to project global future vegetation change and its climatic and abiotic consequences.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".