| Summary: | Ecosystems are an integral part of climate, interacting with the atmosphere by modifying fluxes of energy, water, momentum, and carbon---processes whose importance varies spatially. This dissertation focuses on the study of ecoclimate -- unraveling the complex interactions between ecosystems and climate using a variety of tools including simple models, global scale carbon-climate models, and direct analysis of site-level data. Using a global climate model we show that transpired water vapor from expanded vegetation in the Arctic contributes greenhouse warming with a magnitude of forcing larger than that from the associated changes in albedo. This mechanism has not been considered in previous studies and here we suggest that it may negate the negative climate feedbacks expected from the surface latent cooling associated with the expansion of deciduous forest.Additionally we find that large-scale expansion of low albedo mid latitude forests in the model has the ability to increase Northern Hemisphere temperatures, moving the thermal equator northward and thus modifying global circulation patterns. We observe a northward shift of the intertropical convergence zone over Africa suggesting that extratropical vegetation may be partly responsible for the maintenance of precipitation over the Sahara inferred from proxy records of vegetation from ~6000 Years Ago. The ability of vegetation to effect remote circulation has implications for the role that plants may play in the current climate as well as in climates of the past and the future.In an analysis of nighttime respiration across the eddy covariance Ameriflux tower network we find a residual signal in respiration resembing seasonal variations in substrate mass after accounting for the effects of temperature and moisture. The prevalence of a mass signal indicates that allowing temperature sensitivity to change over time unphysically attributes variations in mass and moisture to changes in temperature. Using a simple carbon cycle model we show that ecosystems with long turnover times are most sensitive to long period forcing and therefore it will be harder to detect or attribute changes in these systems. This suggests that it may be easier to detect and attribute changes in the Tropics compared to the Boreal forest.
|
|---|