Niall P. McNamara

Despite their importance for global CH ₄ biogeochemistry, there is limited evidence on seasonal patterns in CH ₄ stable isotope composition from peatlands. We conducted a 2.5‐year study investigating seasonal changes in CH ₄ fluxes and dual‐stable isotopes (δ ¹³ C, δ ² H) in an ombrotrophic peat bog in Northern England. We performed chamber flux measurements and incubation experiments to quantify CH ₄ and CO ₂ fluxes, CH ₄ isotopes, and CH ₄ production and oxidation potential. CH ₄ fluxes varied significantly across seasons and years, with exceptionally high emissions (>45,000 μmol m ⁻² h ⁻¹ ) recorded in summer 2016, contrasting with median fluxes of 10.6–91.8 μmol m ⁻² h ⁻¹ . Fluxes correlated with soil temperature and soil solution DOC and color, but not with water table depth, which had limited variability. Laboratory CH ₄ production potentials peaked below the water table at 30–40 cm depths, while oxidation potential decreased with depth. Carbon and hydrogen isotope δ‐values ranged from −88.4‰ to −73.2‰ and −345.3‰ to −275.6‰, respectively and showed opposing trends as ẟ ¹³ C increased with CH ₄ flux while ẟ ² H decreased. This is consistent with increasing fluxes being driven by acetoclastic methanogenesis. Our results highlight that seasonal shifts in CH ₄ emissions are accompanied by changes in isotopic signatures, even without major changes in water table or CH ₄ oxidation. Incorporating temporal variability into isotope‐based CH ₄ source attribution may therefore improve constraints on peatland emissions in global CH ₄ budgets.

Summary: Tree stems in Amazonian floodplains emit substantial methane (CH ₄ ), yet controls on emission variability remain unclear. Emissions span orders of magnitude between várzea (nutrient‐rich) and igapó (nutrient‐poor) forests and among trees, suggesting controls beyond flooding. We tested whether site‐level biogeochemistry better explains stem CH ₄ variability than species identity by measuring emissions from two co‐occurring species with contrasting wood densities – Eschweilera coriacea and Hevea spruceana – across várzea and igapó forests. Emissions were paired with porewater chemistry (electrical conductivity, dissolved oxygen, dissolved CH ₄ , and dissolved organic carbon), methane production potential (MPP), and root biomass. Stem CH ₄ emissions were significantly higher in várzea than in igapó, independent of species or stem height. Várzea porewaters displayed higher conductivity, dissolved CH ₄ and MPP, near‐neutral pH, and lower oxygen, with fine roots concentrated in the 0‐ to 50‐cm soil layer, indicating a shallow CH ₄ supply zone. Basal stem emissions in várzea correlated with shallow porewater chemistry and fine‐root biomass, whereas relationships in igapó were weak. These findings show that Amazonian floodplain stem CH ₄ emissions are governed by shallow site‐level biogeochemistry, rather than species identity alone and should be incorporated into basin‐scale CH ₄ budgets and process models to capture spatial variability.

Floodplains are integral parts of river systems, often characterised by periodic flooding. Increased river flooding caused by climate change potentially has significant impacts on oxidation-reduction processes in floodplain soils, altering soil oxygen availability, microbial populations, carbon and nitrogen cycling, and greenhouse gas (GHG) emissions. Flooding can also cause the deposition of metal-contaminated sediments on floodplain soils. During flooding, redox-driven changes in metal speciation can alter metal solubility and bioavailability, thereby affecting soil microbial composition and GHG emissions. Although the effects of flooding on redox-sensitive soil processes are well documented, few studies have examined the combined effects of flooding and metal contamination on soil GHG emissions.To address this gap, we conducted an outdoor mesocosm experiment using intact floodplain soil cores collected from sites with contrasting flood histories (frequently vs rarely flooded), with varying levels of background metal concentrations. Soil cores were inundated for seven weeks to simulate a flood event. GHG fluxes were measured twice weekly before, during, and after the flood event. Two closed-chamber approaches were employed: CO₂ and CH₄ concentrations were measured in real-time for three minutes per chamber using an ultraportable greenhouse gas analyser, while discrete chamber gas samples were collected at four time points over a one-hour enclosure period for N₂O analysis by gas chromatography. A wide range of redox-sensitive soil parameters (oxygen concentration, pH, dissolved organic carbon, metals, and anions) were measured in soil pore water weekly. Soil subsamples collected before and after flooding will be used for metagenomic analysis to assess changes in microbial community composition and the abundance of functional genes associated with key redox processes, including GHG emissions. By integrating redox geochemistry and metagenomic analyses, this study aims to provide mechanistic insight into how flooding and metal mobility regulate microbial functions and soil GHG emissions.

Rationale: The analysis of natural abundance isotopes in biogenic N ₂ O molecules provides valuable insights into the nature of their precursors and their role in biogeochemical cycles. However, current methodologies (for example, the isotopocule map approach) face limitations, as they only enable the estimation of combined contributions from multiple processes at once rather than discriminating individual sources. This study aimed to overcome this challenge by developing a novel methodology for the partitioning of N ₂ O sources in soil, combining natural abundance isotopes and the use of a ¹⁵ N tracer ( ¹⁵ N Gas Flux method) in parallel incubations. Methods: Laboratory incubations of an agricultural soil were conducted to optimize denitrification conditions through increased moisture and nitrate amendments, using nitrate that was either ¹⁵ N‐labeled or unlabeled. A new linear system combined with Monte Carlo simulation was developed to determine N ₂ O source contributions, and the subsequent results were compared with FRAME, a Bayesian statistical model for stable isotope analysis. Results: Our new methodology identified bacterial denitrification as the dominant process (87.6%), followed by fungal denitrification (9.4%), nitrification (1.5%), and nitrifier denitrification (1.6%). Comparisons with FRAME showed good agreement, although FRAME estimated slightly lower bacterial denitrification (80%) and higher nitrifier‐denitrification (9%) contributions. Conclusions: This approach provides an improved framework for accurately partitioning N ₂ O sources, enhancing understanding of nitrogen cycling in agroecosystems, and supporting broader environmental applications.

Grassland management practices and their interactions with climatic variables have significant impacts on soil greenhouse gas (GHG) emissions. Mathematical models can be used to simulate the impacts of management and potential changes in climate beyond the temporal extent of short-term field experiments. In this study, field measurements of nitrous oxide (N₂O), carbon dioxide (CO₂), and methane (CH₄) emissions from grassland soils were used to test and validate the DNDC (DeNitrification-DeComposition) model. The model was then applied to predict changes in GHG emissions due to interactions between climate warming and grassland management in a 30-year simulation. Sensitivity analysis showed that the DNDC model was susceptible to changes in temperature, rainfall, soil carbon and N-fertiliser rate for predicting N₂O and CO₂ emissions, but not for net CH₄ emissions. Validation of the model suggests that N₂O emissions were well described by N-fertilised treatments (relative variation of 2%), while non-fertilised treatments showed higher variations between measured and simulated values (relative variation of 26%). CO₂ emissions (plant and soil respiration) were well described by the model prior to hay meadow cutting but afterwards measured emissions were higher than those simulated. Emissions of CH₄ were on average negative and largely negligible for both simulated and measured values. Long-term scenario projections suggest that net GHG emissions would increase over time under all treatments and interactions. Overall, this study confirms that GHG emissions from intensively managed, fertilised grasslands are at greater risk of being amplified through climate warming, and represent a greater risk of climate feedbacks.

The Indonesian state forest managers have accepted farmer-managed coffee agroforestry in their estates as part of their social forestry program. Access by local farming communities to state-owned plantation forestry supports public motivation to maintain forest cover. However, balancing the expectations and needs of forest managers with those of the local farming communities is not easy. Coffee yields in Indonesia are lower than those of neighboring countries, suggesting that there is scope for improvement. Here we describe an experimental research platform developed through an international collaboration between the Universitas Brawijaya (UB), the UK Centre for Ecology and Hydrology (UKCEH), and smallholder coffee farmers to explore options for improving pine-coffee agroforestry systems within existing regulations. Located in a former state-owned pine production forest on the slopes of the stratovolcano, Mount Arjuna, in the Malang Regency of East Java, the research platform has seven instrumented research plots (40 × 60 m²), where agronomic practices can be trialed. The aim of the platform is to support the development of sustainable agronomic practices to improve the profitability of coffee agroforestry and thus the livelihood of low-income rural communities. Current trials are focused on improving coffee yields and include pine canopy trimming, fertilizers, and coffee pruning trials, with links to the development of socio-economic and environmental models. Whilst it is too early to assess the full impacts on yields, a survey of farmers demonstrated a positive attitude to canopy pruning, although with some concern over labor cost. The initial ecosystem modelling has highlighted the benefits of coffee agroforestry in balancing environmental and economic benefits. Here we provide a detailed description of the site, the current trials, and the modelling work, with the hope of highlighting opportunities for future collaboration and innovation.

Forests are often considered to be able to play a significant role in tackling global warming. To fully understand their potential in mitigating climate change and to develop more accurate ecosystem GHG flux budgets and process-based models of forests, we require more knowledge of methane (CH4) and nitrous oxide (N2O) exchange in forests, their underlying processes, environmental controls and responses to forest management. In recent years, it is becoming evident that not only soils but also the trees themselves may significantly contribute to CH4 and N2O fluxes in forest ecosystems.Our research mainly focussed on greenhouse gas (GHG) exchange in temperate UK forests on both mineral and organic soils. We will primarily concentrate on CH4 fluxes as N2O fluxes were often relatively low in these forests and, by including CO2 fluxes, we will put them into the context of the overall ecosystem GHG exchange. A range of flux methods at different scales were used in our field studies to be able to capture the often high temporal and spatial variability of the GHG exchange between the atmosphere and either soils, tree stems or entire trees aboveground, and to identify potential drivers of the fluxes. The impact of management practices including clear fell, drainage and the resulting micro-topography, and forest-to-bog restoration on CH4 fluxes from organic soils following the first forest rotation will also be described. We regularly used novel automated and chamber approaches and technologies, and the advantages and limitations of the different flux approaches and their use to upscale fluxes to the landscape scale will be evaluated.

In tropical regions, land-use pressures between natural forest, commercial tree plantations, and agricultural land for rural communities are widespread. One option is to increase the functionality of commercial plantations by allowing agroforestry within them by rural communities. Such land-sharing options could address wider societal and environmental issues and reduce pressure on natural forest. To investigate the trade-offs involved, we used InVEST to model the ecosystem services provided by growing coffee under commercial pine plantations in Indonesia against other land-use options. Pine–coffee agroforestry provided worse supporting and regulating services (carbon, sediment and nitrogen retention, catchment runoff) than natural forest; however, it provided greater provisioning services (product yield) directly to smallholders. Converting pine monoculture into pine-coffee agroforestry led to increases in all ecosystem services, although there was an increased risk to water quality. Compared with coffee and root crop monocultures, pine–coffee agroforestry provided higher levels of supporting and regulating services; however, product yields were lower. Thus, opening up pine plantations for agroforestry realises additional income-generating opportunities for rural communities, provides wider ecosystem service benefits, and reduces pressure for land-use change. Lower smallholder yields could be addressed through the management of shade levels or through Payments for Ecosystem Services schemes.