Spectral Indices of Vegetation Condition and Soil Water Content Reflect Controls on CH4 and CO2 Exchange in Sphagnum‐Dominated Northern Peatlands. Issue 7 (30th June 2022) - Tucker, Colin; O'Neill, Ally; Meingast, Karl; Bourgeau‐Chavez, Laura; Lilleskov, Erik; Kane, Evan S.
Abstract: Northern peatlands play an important role in the global C cycle due to their large C stocks and high potential methane (CH4 ) emissions. The CH4 and CO2 cycles of these systems are closely linked to hydrology, with water table level regulating the balance of oxic and anoxic conditions and the water content of Sphagnum mosses that dominate primary production. Previous work has demonstrated that hyperspectral indices well‐suited to the detection of altered hydrology in Sphagnum peatlands are also highly correlated with GPP. However, little work has been done to extend these findings to CH4 effluxes. In this study, we evaluate the utility of four hyperspectral indices, two reflecting vegetation photosynthetic function (chlorophyll index (CI); normalized difference vegetation index) and two reflecting water content (wetness index (WI); floating water band index), for detecting effects of altered water table, precipitation, and vegetation community on CH4 and CO2 exchange in two peatland mesocosm studies. We found that CI is a good predictor of net CO2 exchange, and that it captured both drought and vegetation effects consistently across a broad range of vegetation treatments. Further, we demonstrate for the first time that WI combined with CI explained a significant percentage of CH4 efflux ( R 2  = 0.32–0.57). Our results indicate that CI and WI together may be effective tools for detecting effects of altered hydrology and vegetation on northern Sphagnum ‐peatland CH4 and CO2 emissions, with implications for detecting and modeling changes in emissions of greenhouse gases at scales ranging from the ecosystem to the Earth system. Plain Language Summary: Peatland ecosystems are important contributors to the global cycles of two major greenhouse gases ‐ methane (CH4 ) and carbon dioxide (CO2 ). These ecosystems occur where high water tables inhibit decomposition of plant litter and organic matter. The depth of the non‐saturated layer regulates uptake of CO2 via photosynthesis by Sphagnum mosses which are often abundant to dominant parts of the ecosystem, as well as emission of CH4 by microorganisms living deep in the peat and consumption of CH4 by microorganisms living near the peat surface. Multiple global change factors such as land‐use change, warming, and altered precipitation have the potential to lower water tables in peatlands, thereby affecting greenhouse gas exchange with the atmosphere. Remote sensing methods, such as drones and satellites, can be used to evaluate changes in water tables over large scales, which is useful because northern peatlands are distributed across vast stretches of inaccessible boreal regions. In this study, we evaluated the use of hyperspectral remote sensing techniques to detect changes in water tables in an outdoor experimental facility mimicking natural peatlands, and further detect changes in CH4 and CO2 cycles associated with altered water tables. We find that hyperspectral methods were effective at detecting the effects of altered water tables on greenhouse gas exchange, which supports further work developing these methods for larger scale applications. Key Points: In peatlands altered water tables, precipitation, and vegetation affect CH4 and CO2 exchange of a large terrestrial CO2 sink and CH4 source We show that strong proxies of the processes underlying these effects on CO2 and CH4 exchange can be detected via remote sensing Combining vegetation and peatland mapping with spectral detection of water and photosynthetic capacity will improve our ability to detect greenhouse gas emissions across boreal peatlands