Holocene Land Cover Change in North America:  Trends, Drivers, and Feedbacks
Bibliographic record
Abstract
Land cover governs biogeophysical and biogeochemical feedbacks between the land surface and atmosphere. Holocene vegetation-atmosphere interactions are of particular interest, both to understand the climate effects of intensifying human land use and as a possible explanation for the Holocene Conundrum, a widely studied mismatch between simulated and reconstructed temperatures. Progress addressing the Conundrum has been limited by a lack of data-constrained, quantified, and consistent reconstructions of Holocene land cover change. Following protocols from PAGES LandCover6k, a network of 1445 sedimentary pollen records from the Neotoma Paleoecology Database, and the REVEALS pollen-vegetation model coupled with a Bayesian spatial model, we developed land cover reconstructions with uncertainty for North America for 25 time intervals spanning the Holocene. We use these spatially comprehensive land cover maps to determine the pattern and magnitude of land cover changes at continental to regional scales and discuss underlying ecological, climatic, and anthropogenic drivers. Finally, we infer Holocene radiative forcing from these land cover shifts.Major land cover changes in North America include: 1) Early Holocene afforestation is attributed to rising temperatures and deglaciation, which likely amplified early Holocene warming via the albedo effect; 2) A continental-scale mid-Holocene peak in summergreen trees and shrubs (8.5 to 4 ka) may have been caused by a positive and understudied feedback loop among insolation, temperature, and phenological seasonality. 3) A last-millennium decrease in summergreen trees and shrubs with corresponding increases in open land, likely driven by intensifying land use and neoglacial cooling. Land cover trends vary within and across regions due to individualistic taxon-level responses to environmental change. Major species-level events, such as the mid-Holocene decline of eastern hemlock, may have altered regional climates. The substantial land-cover changes reconstructed here underscore the importance of biogeophysical vegetation feedbacks to Holocene climate dynamics. Continental-scale radiative forcing inferred from land cover change indicates early and late pre-industrial Holocene warming interrupted by a mid-Holocene period of cooling and followed by cooling in the recent millenia. These forcings from natural vegetation change are of the same order of magnitude as global forcings resulting from changes in atmospheric greenhouse gas concentrations from 1750 to 2019.These Holocene reconstructions for North America serve the Earth system modeling community by providing better-constrained land cover scenarios and benchmarks for model evaluation, that improve the understanding of regional- to global-scale processes driving Holocene land cover dynamics.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".