• Energy Research

Evidence of plant root biomass and production in peatlands at the level of species or plant functional type (PFT) is needed for defining ecosystem functioning and predicting its future development. However, such data are limited due to methodological difficulties and the toilsomeness of separating roots from peat. We developed Fourier transform infrared (FTIR) spectroscopy based calibration models for quantifying the mass proportions of several common peatland species, and alternatively, the PFTs that these species represented, in composite root samples. We further tested whether woody roots could be classified into diameter classes, and whether dead and living roots could be separated. We aimed to solve whether general models applicable in different studies can be developed, and what would be the best way to build such models. FTIR spectra were measured from dried and powdered roots: both "pure roots", original samples of 25 species collected in the field, and "root mixtures", artificial composite samples prepared by mixing known amounts of pure roots of different species. Partial least squares regression was used to build the calibration models. The general applicability of the models was tested using roots collected in different sites or times. Our main finding is that pure roots can replace complex mixtures as calibration data. Using pure roots, we constructed generally applicable models for quantification of roots of the main PFTs of northern peatlands. The models provided accurate estimates even for far distant sites, with root mean square error (RMSE) 1.4-6.6% for graminoids, forbs and ferns. For shrubs and trees the estimates were less accurate due to higher within-species heterogeneity, partly related to variation in root diameter. Still, we obtained RMSE 3.9-10.8% for total woody roots, but up to 20.1% for different woody-root types. Species-level and dead-root models performed well within the calibration dataset but provided unacceptable estimates for independent samples, limiting their routine application in field conditions. Our PFT-level models can be applied on roots separated from soil for biomass determination or from ingrowth cores for estimating root production. We present possibilities for further development of species-level or dead-root models using the pure-root approach.

The global goal to mitigate climate change (CC) is to achieve net zero greenhouse gas emissions (GHGE) by 2050; the European Union (EU) aim is to cut GHGE at least by 55% already by 2030. These ambition targets require new GHGE mitigation measures across all land use sectors (LULUCF), where wetlands, as carbon (C) rich ecosystem, can effectively contribute to climate targets, biodiversity, and water-related ecosystem services. Natural peatlands accumulate C effectively due to water-logged conditions. However, they can turn into high GHG sources if they are drained, therefore there is still need to enhance knowledge regarding how and/or how much C is sequestered or released by peatlands after their restoration, as well as the socioeconomic effects.“ALFAwetlands - Restoration for the future” (www.alfawetlands.eu) is a Horizon Europe funded project (2022-2026), which is coordinated by Luke and carried out at local to EU levels with 15 partners across Europe. It’s main goal, in short, is to mitigate CC while supporting biodiversity and ecosystem services (BES) and being socially just and rewarding. This includes, e.g., increasing the knowledge about C storage and release in peatlands, specifically after restoration. While, in terms of C fluxes, focussing on peatlands, the project scope is larger and includes additionally floodplains, coastal wetlands and few artificial wetlands. ALFAwetlands will develop and indicate management alternatives for wetlands including such that have been or will be restored during this project. Measures under this project are not restricted to ecological restoration but include rehabilitation and re-vegetation action to improve ecosystem conditions (e.g., peatland forest: continuous-cover-forestry, cultivated peatlands: paludiculture). Studies are conducted in 9 Living Labs (LL’s) including 30 sites, which are located in wetlands in different parts of Europe (north-south gradient). At the local level, LL’s support and integrate interdisciplinary and multi-actor research on ecological, environmental, economic, and social issues. Experimental data from local sites are scaled-up and will be utilized e.g., by models to gain and understanding the potential impacts of upscaled wetland restoration measures. To achieve ALFAwetlands goals, 5 research workpackages are being implemented, namely: 1)improve geospatial knowledge base of wetlands, 2)co-create socially fair and rewarding pathways for wetland restoration, 3)estimate effects of restoration on GHGE and BES, with the data achieved from field experiments, 4)develop policy relevant scenarios for CC and BES, and 5)study societal impacts of wetland restoration. The project will also encourage stakeholders to utilise outputs and support their active participation in wetland management.

Summary Ericaceous shrubs adapt to the nutrient‐poor conditions in ombrotrophic peatlands by forming symbiotic associations with ericoid mycorrhizal (ERM) fungi. Increased nutrient availability may diminish the role of ERM pathways in shrub nutrient uptake, consequently altering the biogeochemical cycling within bogs. To explore the significance of ERM fungi in ombrotrophic peatlands, we developed the model MWMmic (a peat cohort‐based biogeochemical model) into MWMmic‐NP by explicitly incorporating plant‐soil nitrogen (N) and phosphorus (P) cycling and ERM fungi processes. The new model was applied to simulate the biogeochemical cycles in the Mer Bleue (MB) bog in Ontario, Canada, and their responses to fertilization. MWMmic_NP reproduced the carbon(C)–N–P cycles and vegetation dynamics observed in the MB bog, and their responses to fertilization. Our simulations showed that fertilization increased shrub biomass by reducing the C allocation to ERM fungi, subsequently suppressing the growth of underlying Sphagnum mosses, and decreasing the peatland C sequestration. Our species removal simulation further demonstrated that ERM fungi were key to maintaining the shrub–moss coexistence and C sink function of bogs. Our results suggest that ERM fungi play a significant role in the biogeochemical cycles in ombrotrophic peatlands and should be considered in future modeling efforts.

AbstractPeatlands cover only 3–4% of the Earth’s surface, but they store nearly 30% of global soil carbon stock. This significant carbon store is under threat as peatlands continue to be degraded at alarming rates around the world. It has prompted countries worldwide to establish regulations to conserve and reduce emissions from this carbon rich ecosystem. For example, the EU has implemented new rules that mandate sustainable management of peatlands, critical to reaching the goal of carbon neutrality by 2050. However, a lack of information on the extent and condition of peatlands has hindered the development of national policies and restoration efforts. This paper reviews the current state of knowledge on mapping and monitoring peatlands from field sites to the globe and identifies areas where further research is needed. It presents an overview of the different methodologies used to map peatlands in nine countries, which vary in definition of peat soil and peatland, mapping coverage, and mapping detail. Whereas mapping peatlands across the world with only one approach is hardly possible, the paper highlights the need for more consistent approaches within regions having comparable peatland types and climates to inform their protection and urgent restoration. The review further summarises various approaches used for monitoring peatland conditions and functions. These include monitoring at the plot scale for degree of humification and stoichiometric ratio, and proximal sensing such as gamma radiometrics and electromagnetic induction at the field to landscape scale for mapping peat thickness and identifying hotspots for greenhouse gas (GHG) emissions. Remote sensing techniques with passive and active sensors at regional to national scale can help in monitoring subsidence rate, water table, peat moisture, landslides, and GHG emissions. Although the use of water table depth as a proxy for interannual GHG emissions from peatlands has been well established, there is no single remote sensing method or data product yet that has been verified beyond local or regional scales. Broader land-use change and fire monitoring at a global scale may further assist national GHG inventory reporting. Monitoring of peatland conditions to evaluate the success of individual restoration schemes still requires field work to assess local proxies combined with remote sensing and modeling. Long-term monitoring is necessary to draw valid conclusions on revegetation outcomes and associated GHG emissions in rewetted peatlands, as their dynamics are not fully understood at the site level. Monitoring vegetation development and hydrology of restored peatlands is needed as a proxy to assess the return of water and changes in nutrient cycling and biodiversity.

AbstractNorthern peatlands are a globally significant source of methane (CH4), and emissions are projected to increase due to warming and permafrost loss. Understanding the microbial mechanisms behind patterns in CH4 production in peatlands will be key to predicting annual emissions changes, with stable carbon isotopes (δ13C‐CH4) being a powerful tool for characterizing these drivers. Given that δ13C‐CH4 is used in top‐down atmospheric inversion models to partition sources, our ability to model CH4 production pathways and associated δ13C‐CH4 values is critical. We sought to characterize the role of environmental conditions, including hydrologic and vegetation patterns associated with permafrost thaw, on δ13C‐CH4 values from high‐latitude peatlands. We measured porewater and emitted CH4 stable isotopes, pH, and vegetation composition from five boreal‐Arctic peatlands. Porewater δ13C‐CH4 was strongly associated with peatland type, with δ13C enriched values obtained from more minerotrophic fens (−61.2 ± 9.1‰) compared to permafrost‐free bogs (−74.1 ± 9.4‰) and raised permafrost bogs (−81.6 ± 11.5‰). Variation in porewater δ13C‐CH4 was best explained by sedge cover, CH4 concentration, and the interactive effect of peatland type and pH (r2 = 0.50, p < 0.001). Emitted δ13C‐CH4 varied greatly but was positively correlated with porewater δ13C‐CH4. We calculated a mixed atmospheric δ13C‐CH4 value for northern peatlands of −65.3 ± 7‰ and show that this value is more sensitive to landscape drying than wetting under permafrost thaw scenarios. Our results suggest northern peatland δ13C‐CH4 values are likely to shift in the future which has important implications for source partitioning in atmospheric inversion models.

AbstractEstimates of regional and global freshwater N2O emissions have remained inaccurate due to scarce data and complexity of the multiple processes driving N2O fluxes the focus predominantly being on summer time measurements from emission hot spots, agricultural streams. Here, we present four‐season data of N2O concentrations in the water columns of randomly selected boreal lakes covering a large variation in latitude, lake type, area, depth, water chemistry, and land use cover. Nitrate was the key driver for N2O dynamics, explaining as much as 78% of the variation of the seasonal mean N2O concentrations across all lakes. Nitrate concentrations varied among seasons being highest in winter and lowest in summer. Of the surface water samples, 71% were oversaturated with N2O relative to the atmosphere. Largest oversaturation was measured in winter and lowest in summer stressing the importance to include full year N2O measurements in annual emission estimates. Including winter data resulted in fourfold annual N2O emission estimates compared to summer only measurements. Nutrient‐rich calcareous and large humic lakes had the highest annual N2O emissions. Our emission estimates for Finnish and boreal lakes are 0.6 and 29 Gg N2O‐N/year, respectively. The global warming potential of N2O from lakes cannot be neglected in the boreal landscape, being 35% of that of diffusive CH4 emission in Finnish lakes.