Evaluating theories of drought‐induced vegetation mortality using a multimodel–experiment framework

TLDR: It is suggested 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.

Abstract: 'Summary' 305 I. 'Background' 305 II. 'Model–experiment approach' 306 III. 'Simulations of hydraulic failure and carbon starvation' 310 IV. 'On thresholds vs duration of stress as drivers of mortality' 311 V. 'Interdependence of hydraulic failure and carbon starvation' 314 VI. 'Next-generation, traditional, and empirical models' 316 VII. 'A path forward' 317 VIII. 'Conclusions' 318   'Acknowledgements' 318   References 318 Summary 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 5 yr 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.