Variation in carbon and nitrogen concentrations among peatland categories at the global scale

Publisher Copyright: © 2022 This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.Peatlands account for 15 to 30% of the world's soil carbon (C) stock and are important controls over global nitrogen (N) cycles. However, C and N concentrations are known to vary among peatlands contributing to the uncertainty of global C inventories, but there are few global studies that relate peatland classification to peat chemistry. We analyzed 436 peat cores sampled in 24 countries across six continents and measured C, N, and organic matter (OM) content at three depths down to 70 cm. Sites were distinguished between northern (387) and tropical (49) peatlands and assigned to one of six distinct broadly recognized peatland categories that vary primarily along a pH gradient. Peat C and N concentrations, OM content, and C:N ratios differed significantly among peatland categories, but few differences in chemistry with depth were found within each category. Across all peatlands C and N concentrations in the 10-20 cm layer, were 440 ± 85.1 g kg-1 and 13.9 ± 7.4 g kg-1, with an average C:N ratio of 30.1 ± 20.8. Among peatland categories, median C concentrations were highest in bogs, poor fens and tropical swamps (446-532 g kg-1) and lowest in intermediate and extremely rich fens (375-414 g kg-1). The C:OM ratio in peat was similar across most peatland categories, except in deeper samples from ombrotrophic tropical peat swamps that were higher than other peatlands categories. Peat N concentrations and C:N ratios varied approximately two-fold among peatland categories and N concentrations tended to be higher (and C:N lower) in intermediate fens compared with other peatland types. This study reports on a unique data set and demonstrates that differences in peat C and OM concentrations among broadly classified peatland categories are predictable, which can aid future studies that use land cover assessments to refine global peatland C and N stocks.Peer reviewe

The ABCflux database : Arctic-boreal CO2 flux observations and ancillary information aggregated to monthly time steps across terrestrial ecosystems

Past efforts to synthesize and quantify the magnitude and change in carbon dioxide (CO2) fluxes in terrestrial ecosystems across the rapidly warming Arctic-boreal zone (ABZ) have provided valuable information but were limited in their geographical and temporal coverage. Furthermore, these efforts have been based on data aggregated over varying time periods, often with only minimal site ancillary data, thus limiting their potential to be used in large-scale carbon budget assessments. To bridge these gaps, we developed a standardized monthly database of Arctic-boreal CO2 fluxes (ABCflux) that aggregates in situ measurements of terrestrial net ecosystem CO2 exchange and its derived partitioned component fluxes: gross primary productivity and ecosystem respiration. The data span from 1989 to 2020 with over 70 supporting variables that describe key site conditions (e.g., vegetation and disturbance type), micrometeorological and environmental measurements (e.g., air and soil temperatures), and flux measurement techniques. Here, we describe these variables, the spatial and temporal distribution of observations, the main strengths and limitations of the database, and the potential research opportunities it enables. In total, ABCflux includes 244 sites and 6309 monthly observations; 136 sites and 2217 monthly observations represent tundra, and 108 sites and 4092 observations represent the boreal biome. The database includes fluxes estimated with chamber (19 % of the monthly observations), snow diffusion (3 %) and eddy covariance (78 %) techniques. The largest number of observations were collected during the climatological summer (June-August; 32 %), and fewer observations were available for autumn (September-October; 25 %), winter (December-February; 18 %), and spring (March-May; 25 %). ABCflux can be used in a wide array of empirical, remote sensing and modeling studies to improve understanding of the regional and temporal variability in CO2 fluxes and to better estimate the terrestrial ABZ CO2 budget. ABCflux is openly and freely available online (Virkkala et al., 2021b, https://doi.org/10.3334/ORNLDAAC/1934).Peer reviewe

Plant functional traits play the second fiddle to plant functional types in explaining peatland CO2 and CH4 gas exchange

Abstract Peatlands constitute a significant soil carbon (C) store, yet the C gas flux components show distinct spatial variation both between and within peatlands. Determining the controls on this variability could aid in our understanding of the response of peatlands to global changes. In this study, we assess the usefulness of different vegetation related parameters to explain spatial variation in peatland C gas flux components. We hypothesise that spatial variation is best explained by trait-based indices (similarly to other terrestrial ecosystems), and that the impact of soil physicochemical properties, such as nitrogen (N) content or water level, can be manifested through the traits. Furthermore, we expect that the spatial variability associated with each of the C gas flux components can be explained by a distinct set of traits. To address our aim, we used a successional peatland chronosequence from wet meadows to a bog, along which all variables were recorded with similar methods and under similar climatic conditions. We observed spatial variability with all measured gas fluxes, with carbon dioxide (CO2) fluxes showing significant variability between sites, while within site variability was more important for methane (CH4) fluxes. As expected, our results show that the impacts of physicochemical conditions were directed via vegetation. However, the cover of functional plant types that capture multiple traits proved to be more powerful in explaining gas flux variability compared to functional trait-based indices. Our findings imply that for future gas flux modelling purposes, rather than attempting to use individual traits — as is the ongoing trend in ecology — it might be more useful to refine plant functional groupings and ensure they are based on a set of plant traits relevant for the studied ecosystem process. This could be facilitated by the collation of a large data set of traits measured from peatlands

Modelling the habitat preference of two key Sphagnum species in a poor fen as controlled by capitulum water content

Abstract Current peatland models generally treat vegetation as static, although plant community structure is known to alter as a response to environmental change. Because the vegetation structure and ecosystem functioning are tightly linked, realistic projections of peatland response to climate change require the inclusion of vegetation dynamics in ecosystem models. In peatlands, Sphagnum mosses are key engineers. Moss community composition primarily follows habitat moisture conditions. The known species habitat preference along the prevailing moisture gradient might not directly serve as a reliable predictor for future species compositions, as water table fluctuation is likely to increase. Hence, modelling the mechanisms that control the habitat preference of Sphagna is a good first step for modelling community dynamics in peatlands. In this study, we developed the Peatland Moss Simulator (PMS), which simulates the community dynamics of the peatland moss layer. PMS is a process-based model that employs a stochastic, individual-based approach for simulating competition within the peatland moss layer based on species differences in functional traits. At the shoot-level, growth and competition were driven by net photosynthesis, which was regulated by hydrological processes via the capitulum water content. The model was tested by predicting the habitat preferences of Sphagnum magellanicum and Sphagnum fallax – two key species representing dry (hummock) and wet (lawn) habitats in a poor fen peatland (Lakkasuo, Finland). PMS successfully captured the habitat preferences of the two Sphagnum species based on observed variations in trait properties. Our model simulation further showed that the validity of PMS depended on the interspecific differences in the capitulum water content being correctly specified. Neglecting the water content differences led to the failure of PMS to predict the habitat preferences of the species in stochastic simulations. Our work highlights the importance of the capitulum water content with respect to the dynamics and carbon functioning of Sphagnum communities in peatland ecosystems. Thus, studies of peatland responses to changing environmental conditions need to include capitulum water processes as a control on moss community dynamics. Our PMS model could be used as an elemental design for the future development of dynamic vegetation models for peatland ecosystems

Spatially varying peatland initiation, Holocene development, carbon accumulation patterns and radiative forcing within a subarctic fen

Abstract High latitude peatlands act as globally important carbon (C) sinks and are in constant interaction with the atmosphere. Their C storage formed during the Holocene. In the course of time, the aggregate effect of the C fluxes on radiative forcing (RF) typically changes from warming to cooling, but the timing of this shift varies among different peatlands. Here we investigated Holocene peatland development, including vegetation history, vertical peat growth and the lateral expansion of a patterned subarctic fen in northern Finland by means of multiple sampling points. We modelled the Holocene RF by combining knowledge on past vegetation communities based on plant macrofossil stratigraphies and present in situ C flux measurements. The peatland initiated at ca. 9500 calibrated years Before Present (cal yr BP), and its lateral expansion was greatest between ca. 9000 and 7000 cal yr BP. After the early expansion, vertical peat growth proceeded very differently in different parts of the peatland, regulated by internal and external factors. The pronounced surface microtopography, with high strings and wet flarks, started to form only after ca. 1000 cal yr BP. C accumulation within the peatland recorded a high degree of spatial variability throughout its history, including the recent past. We applied two flux scenarios with different interpretation of the initial peatland development phases to estimate the RF induced by C fluxes of the fen. After ca. 4000 cal yr BP, at the latest, the peatland RF has been negative (cooling), mainly driven by C uptake and biomass production, while methane emissions had a lesser role in the total RF. Interestingly, these scenarios suggest that the greatest cooling effect took place around ca. 1000 cal yr BP, after which the surface microtopography established. The study demonstrated that despite the high spatial heterogeneity and idiosyncratic behaviour of the peatland, the RF of the studied fen followed the general development pattern of more southern peatlands. Holocene climate variations and warm phases did not seem to induce any distinctive and consistent peatland-scale patterns in C accumulation, whereas our data suggests that the changes in vegetation related to autogenic succession were reflected in the C accumulation patterns and RF more clearly

Hidden becomes clear:optical remote sensing of vegetation reveals water table dynamics in northern peatlands

Abstract The water table and its dynamics are one of the key variables that control peatland greenhouse gas exchange. Here, we tested the applicability of the Optical TRApezoid Model (OPTRAM) to monitor the temporal fluctuations in water table over intact, restored (previously forestry-drained), and drained (under agriculture) northern peatlands in Finland, Estonia, Sweden, Canada, and the USA. More specifically, we studied the potential and limitations of OPTRAM using water table data from 2018 through 2021, across 53 northern peatland sites, i.e., covering the largest geographical extent used in OPTRAM studies so far. For this, we calculated OPTRAM based on Sentinel-2 data with the Google Earth Engine cloud platform. First, we found that the choice of vegetation index utilised in OPTRAM does not significantly affect OPTRAM performance in peatlands. Second, we revealed that the tree cover density is a major factor controlling the sensitivity of OPTRAM to water table dynamics in peatlands. Tree cover density greater than 50% led to a clear decrease in OPTRAM performance. Finally, we demonstrated that the relationship between water table and OPTRAM often disappears when WT deepens (ranging between 0 to −100 cm, depending on the site location). We identified that the water table where OPTRAM ceases to be sensitive to variations is highly site-specific. Overall, our results support the application of OPTRAM to monitor water table dynamics in intact and restored northern peatlands with low tree cover density (below 50%) when the water table varies from shallow to moderately deep. Our study makes significant steps towards the broader implementation of optical remote sensing data for monitoring peatlands subsurface moisture conditions over the northern region