期刊
NEW PHYTOLOGIST
卷 200, 期 2, 页码 304-321出版社
WILEY
DOI: 10.1111/nph.12465
关键词
carbon starvation; cavitation; die-off; dynamic global vegetation models (DGVMs); hydraulic failure; photosynthesis; process-based models
资金
- New Phytologist Trust and Trustees
- Department of Energy-Office of Science
- LANL-LDRD
- ICREA Funding Source: Custom
- NERC [NE/I011749/1] Funding Source: UKRI
- Natural Environment Research Council [NE/I011749/1] Funding Source: researchfish
- Direct For Biological Sciences
- Division Of Environmental Biology [1232294] Funding Source: National Science Foundation
- Division Of Integrative Organismal Systems
- Direct For Biological Sciences [743148] Funding Source: National Science Foundation
Model-data comparisons of plant physiological processes provide an understanding of mechanisms underlying vegetation responses to climate. We simulated the physiology of a pinon pine-juniper woodland (Pinus edulis-Juniperus monosperma) that experienced mortality during a 5yr precipitation-reduction experiment, allowing a framework with which to examine our knowledge of drought-induced tree mortality. We used six models designed for scales ranging from individual plants to a global level, all containing state-of-the-art representations of the internal hydraulic and carbohydrate dynamics of woody plants. Despite the large range of model structures, tuning, and parameterization employed, all simulations predicted hydraulic failure and carbon starvation processes co-occurring in dying trees of both species, with the time spent with severe hydraulic failure and carbon starvation, rather than absolute thresholds per se, being a better predictor of impending mortality. Model and empirical data suggest that limited carbon and water exchanges at stomatal, phloem, and below-ground interfaces were associated with mortality of both species. The model-data comparison suggests that the introduction of a mechanistic process into physiology-based models provides equal or improved predictive power over traditional process-model or empirical thresholds. Both biophysical and empirical modeling approaches are useful in understanding processes, particularly when the models fail, because they reveal mechanisms that are likely to underlie mortality. We suggest that for some ecosystems, integration of mechanistic pathogen models into current vegetation models, and evaluation against observations, could result in a breakthrough capability to simulate vegetation dynamics.
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