Using a Forest Stand Simulation Model to Examine the Ecological and Climatic Significance of the Late-Quaternary Pine-Spruce Pollen Zone in Eastern Virginia, U.S.A.

Author:

Bonan Gordon B.,Hayden Bruce P.

Abstract

AbstractFull-glacial pollen records from southeastern United States are composed primarily of pine and spruce, with lesser amounts of fir, birch, and oak. A simulation model of forest dynamics was used to reconstruct the composition and structure of these forests on the Delmarva Peninsula of Virginia, where pollen data were available to test the model, and climate and soils data were available to drive the model. Reconstructed annual precipitation and summer air temperature were consistent with modern analog estimates from the pollen record. Annual precipitation was also consistent with climates simulated by atmospheric general circulation models, but summers were colder. Correcting these simulated climates for possible errors resulted in summer air temperature consistent with our estimate. However, two alternative parameter sets relating simulated tree growth to air temperature sums precluded robust forest reconstructions. With one parameter set, the species dominating the simulated forests were not consistent with the pollen record. The other parameter set produced forests more consistent with paleoecological data, indicating that the climate was correct. These differences in simulated forest composition reflected inadequacies in the parameterization of air temperature effects in forest models.

Publisher

Cambridge University Press (CUP)

Subject

General Earth and Planetary Sciences,Earth-Surface Processes,Arts and Humanities (miscellaneous)

Cited by 45 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Index;Climate Change and Terrestrial Ecosystem Modeling;2019-02-28

2. References;Climate Change and Terrestrial Ecosystem Modeling;2019-02-28

3. Appendices;Climate Change and Terrestrial Ecosystem Modeling;2019-02-28

4. Canopy Chemistry;Climate Change and Terrestrial Ecosystem Modeling;2019-02-28

5. Vegetation Demography;Climate Change and Terrestrial Ecosystem Modeling;2019-02-28

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