Impacts of vegetation on climate and the global water and carbon cycles

Abstract

It is widely recognized that climate influences the terrestrial water and carbon cycles, but land processes also exert a strong control on climate by modifying land-to-atmosphere fluxes of water, energy, and momentum. This dissertation focuses on feedbacks between vegetation, climate, and the global water and carbon cycles through a series of modeling studies that address how climate impacts vegetation (Chapter 2), how land parameter uncertainty impacts climate (Chapter 3), and how atmospheric feedbacks modulate changes in land processes (Chapter 4). Chapter 1 introduces previous work in biosphere-atmosphere interactions, and outlines key outstanding questions in this area of research. Chapter 2 focuses on how climate influences vegetation, disentangling how different atmospheric drivers contribute to observed declines in tropical forest photosynthesis under high temperatures. It is challenging to disentangle the impact of direct temperature effects vs. vapor pressure deficit (VPD) effects on vegetation because these quantities are tightly correlated. I use two terrestrial biosphere models and observational data to show that plant hydraulics and photosynthetic temperature acclimation govern the strength of temperature and VPD effects. This work identifies a novel source of compensating errors in models – models can match the observed apparent ecosystem-level photosynthesis response to temperature by excluding plant hydraulics and photosynthetic temperature acclimation (which yields stronger direct temperature effects) or by including both processes (which yields stronger VPD effects). However, these two sets of assumptions yield divergent predictions of ecosystem resilience to warming, underscoring the importance of accurately representing these processes in models. Chapter 3 focuses on the impact of land processes on climate, by evaluating the impact of land parameter uncertainty in a coupled Earth system model. Prior research has demonstrated that uncertainty in the representation of land processes drives uncertainty in land surface water, energy, and carbon fluxes. However, the influence of land process uncertainty on the climate system remains underexplored. I run an ensemble of simulations where I perturb 18 parameters governing land processes in a coupled Earth system model. Using this perturbed parameter ensemble (PPE), I demonstrate that land parameters generate biogeophysical feedbacks that substantially impact mean temperature and precipitation, primarily through parameters’ influence on evapotranspiration. Notably, the spatial patterns of parameter-driven changes in precipitation and temperature differ from those due to radiatively-driven warming. My analysis demonstrates that land parameter uncertainty propagates to the entire Earth system, highlighting an underappreciated impact of land processes in determining the mean climate state and providing insights into where and how land process uncertainty influences climate. Chapter 4 analyzes land-atmosphere interactions, quantifying how land-driven climate changes feed back on the global water and carbon cycles. I isolate the impact of atmospheric feedbacks by comparing the coupled PPE with a paired land-only PPE in which the atmosphere does not respond to changes in land surface properties. I find that atmospheric feedbacks dampen land-driven hydrologic changes in climatologically wet regions, but amplify hydrologic changes in some climatologically dry regions. I also identify several hot spots where atmospheric feedbacks have a regionally significant impact on photosynthesis. This analysis provides insights into where and how atmospheric feedbacks modulate terrestrial processes, posing a challenge to the widespread practice of developing and evaluating land models in an uncoupled configuration and then deploying them to understand and predict terrestrial processes in a coupled context. Chapter 5 presents a discussion of the implications of the results in Chapters 2-4 as well as plans for future research.