Photosynthesis: from leaves to the biosphere
Above the scale of a few leaves, carbon uptake during photosynthesis cannot be directly measured due to the presence of respiration. Though atmospheric CO2 observations can be used to derive the net carbon balance between photosynthesis and respiration, CO2 observations alone provide insufficient constraints on either component. This is especially true at regional scales where mixing and boundary layer dynamics obscure the CO2 signals of daytime photosynthetic drawdown and nighttime respiratory release. To robustly quantify photosynthesis at regional to global scales requires leveraging novel optical and material constraints specific to photosynthesis, including carbonyl sulfide (COS or OCS), isotope-labeled CO2 and O2 molecules, solar-induced chlorophyll fluorescence (SIF), and near-infrared reflectance of vegetation (NIRv). My research is aimed at integrating COS and SIF observational constraints to improve process-based understanding of photosynthesis across ecosystem, regional, and global scales, thereby delivering more robust predictions of photosynthetic responses to climate variability, stresses, and disturbances.
Relevant work: Sun et al. (2018) Biogeosci., Whelan et al. (2018) Biogeosci., and Kooijmans et al. (2019) PNAS.
Ecosystem respiration
Globally, ecosystem respiration releases a similar amount of CO2 as that assimilated by photosynthesis. The small balance between photosynthesis and ecosystem respiration is the terrestrial carbon sink that offsets a quarter to a third of human-induced CO2 emissions. Warming caused by climate change threatens to amplify ecosystem respiration and reverse the terrestrial carbon sink, creating positive feedback to accelerate climate change. However, the risk posed by such feedback is unclear on centennial time scales due to uncertainty in quantitative, process-based understanding of respiration in plants and soil microbes. Unlike observations of photosynthesis, there are no optical signals or material tracers to uniquely constrain respiratory fluxes. My research seeks to constrain the magnitude, space-time distribution, and climate sensitivities of ecosystem respiration by confronting process-based understanding with a suite of bottom-up and top-down observational constraints, including plot-scale flux observations from towers and soil chambers, remotely sensed drivers of respiration, and atmospheric CO2 observations. The goal is to more robustly quantify the carbon–climate feedback through improved mechanistic understanding and model representations of respiratory processes.
Relevant work: in progress; stay tuned.
Regional carbon balance and its responses to climate
Regional carbon cycle assessments provide the scientific basis underpinning local, national, and international policies to mitigate climate change. However, attribution of the terrestrial carbon budget at regional scales (~103–106 km2) remains highly uncertain because data constraints are usually too sparse to resolve the spatial patterns of carbon fluxes at such scales. Moreover, “bottom-up” terrestrial biosphere models and “top-down” atmospheric inverse models can yield conflicting magnitude, spatial patterns, and temporal dynamics of regional carbon balance. Such divergence reflects fundamental gaps in process-based understanding, which further contribute to the uncertainty in future projections of the carbon balance. My research uses a suite of top-down and bottom-up methods to improve estimates of regional carbon balance and understand key processes that determine its present state and future trajectory, with a focus on regions vulnerable to impacts from rapidly changing climate regimes, including but not limited to temperate, boreal, and Arctic North America. The ultimate goal is to produce robust future projections of regional carbon flux components to aid in making climate change policies.
Relevant work: Sun et al. (2021) AGU Adv.
Terrestrial biosphere model development and evaluation
Terrestrial biosphere models are mathematical embodiments of the understanding of terrestrial ecosystems and their functioning, dynamics, and interactions with components of the earth system. They are essential tools for inferring causal explanations (αἰτίαι) of observed phenomena, generalizing plot-scale findings to regional, continental, and global scales, investigating system behavior of the terrestrial biosphere in a changing climate, and predicting future changes to inform policy decisions. However, there is a wide divergence in the simulated outcome of ecosystem state and functioning across models as well as between models and observations. My research focuses on evaluating model representations of biogeochemical cycling and photosynthesis using top-down atmospheric and satellite observations and bottom-up plot-scale observations, and refining model formulations and parameterization based on the evaluations. The goal is to advance the process-based understanding embodied in models and use improved model simulations to guide natural climate solutions and deliver more robust projections of climate futures.
Relevant work: Sun et al. (2015) Geosci. Model Dev. and Sun et al. (2021) AGU Adv.
