Accurate projections of climate change impacts on the vast carbon stores of northern peatlands require detailed knowledge of ecosystem respiration (ER) and its heterotrophic (Rh) and autotrophic (Ra) components. Currently, however, standard flux measurement techniques, i.e. eddy covariance and manual chambers, generate empirical ER data during only night- or daytime, respectively, which are extrapolated to the daily scale based on the paradigm that assumes a uniform diel temperature response. Here, using continuous autochamber measurements, we demonstrate a distinct bimodal pattern in diel peatland ER which contrasts the unimodal pattern inherent to the classical assumption. This feature results from divergent temperature dependencies of day- and nighttime ER due to varying contributions from Rh and Ra. We further find that disregarding these bimodal dynamics causes significant bias in ER estimates across multiple temporal scales. This calls for improved process-based understanding of ER to advance our ability to simulate peatland carbon cycle-climate feedbacks.

The net ecosystem CO2 exchange (NEE) drives the carbon (C) sink-source strength of northern peatlands. Since NEE represents a balance between various production and respiration fluxes, accurate predictions of its response to global changes require an in depth understanding of these underlying processes. Currently, however, detailed information of the temporal dynamics as well as the separate biotic and abiotic controls of the NEE component fluxes is lacking in peatland ecosystems. In this study, we address this knowledge gap by using an automated chamber system established across natural and trenching/vegetation removal plots to partition NEE into its production (i.e., gross and net primary production; GPP and NPP) and respiration (i.e., ecosystem, heterotrophic and autotrophic respiration; ER, Rh and Ra) fluxes in a boreal peatland in northern Sweden. Our results showed that daily NEE patterns were driven by GPP while variations in ER were governed by Ra rather than Rh. Moreover, we observed pronounced seasonal shifts in the Ra/Rh and above/belowground NPP ratios throughout the main phenological phases. Generalized linear model analysis revealed that the greenness index derived from digital images (as a proxy for plant phenology) was the strongest control of NEE, GPP and NPP while explaining considerable fractions also in the variations of ER and Ra. In addition, our data exposed greater temperature sensitivity of NPP compared to Rh resulting in enhanced C sequestration with increasing temperature. Overall, our study suggests that the temporal patterns in NEE and its component fluxes are tightly coupled to vegetation dynamics in boreal peatlands and thus challenges previous studies that commonly identify abiotic factors as key drivers. These findings further emphasize the need for integrating detailed information on plant phenology into process-based models to improve predictions of global change impacts on the peatland C cycle.