The uncertain climate footprint of wetlands under human pressure.

Significant climate risks are associated with a positive carbon-temperature feedback in northern latitude carbon-rich ecosystems, making an accurate analysis of human impacts on the net greenhouse gas balance of wetlands a priority. Here, we provide a coherent assessment of the climate footprint of a network of wetland sites based on simultaneous and quasi-continuous ecosystem observations of CO2 and CH4 fluxes. Experimental areas are located both in natural and in managed wetlands and cover a wide range of climatic regions, ecosystem types, and management practices. Based on direct observations we predict that sustained CH4 emissions in natural ecosystems are in the long term (i.e., several centuries) typically offset by CO2 uptake, although with large spatiotemporal variability. Using a space-for-time analogy across ecological and climatic gradients, we represent the chronosequence from natural to managed conditions to quantify the "cost" of CH4 emissions for the benefit of net carbon sequestration. With a sustained pulse-response radiative forcing model, we found a significant increase in atmospheric forcing due to land management, in particular for wetland converted to cropland. Our results quantify the role of human activities on the climate footprint of northern wetlands and call for development of active mitigation strategies for managed wetlands and new guidelines of the Intergovernmental Panel on Climate Change (IPCC) accounting for both sustained CH4 emissions and cumulative CO2 exchange.

Evaluating the use of an Unmanned Aerial Vehicle (UAV)-based active AirCore system to quantify methane emissions from dairy cows.

Enteric fermentation and manure methane emissions from livestock are major anthropogenic greenhouse gas emissions. In general, direct measurements of farm-scale methane emissions are scarce due to the source complexity and the limitations of existing atmospheric sampling methods. Using an innovative UAV-based active AirCore system, we have performed accurate atmospheric measurements of CH4 mole fractions downwind of a dairy cow farm in the Netherlands on four individual days during the period from March 2017 to March 2019. The total CH4 emission rates from the farm were determined using the UAV-based mass balance approach to be 1.1-2.4 g/s. After subtracting estimated emission factors of manure onsite, we derived the enteric emission factors to be 0.20-0.51 kgCH4/AU/d (1 AU = 500 kg animal weight) of dairy cows. We show that the uncertainties of the estimates were dominated by the variabilities in the wind speed and the angle between the wind and the flight transect. Furthermore, nonsimultaneous sampling in the vertical direction of the plume is one of the main limiting factors to achieving accurate estimate of the CH4 emissions from the farm. In addition, a N2O tracer release experiment at the farm was performed when both a UAV and a mobile van were present to simultaneously sample the N2O tracer and the CH4 plumes from the farm, improving the source quantification with a correction factor of 1.04 and 1.22 for the inverse Gaussian approach and for the mass balance approach, respectively. The UAV-based active AirCore system is capable of providing useful estimates of CH4 emissions from dairy cow farms. The uncertainties of the estimates can be improved when combined with accurate measurements of local wind speed and direction or when combined with a tracer approach.

Forest tree growth is linked to mycorrhizal fungal composition and function across Europe.

Most trees form symbioses with ectomycorrhizal fungi (EMF) which influence access to growth-limiting soil resources. Mesocosm experiments repeatedly show that EMF species differentially affect plant development, yet whether these effects ripple up to influence the growth of entire forests remains unknown. Here we tested the effects of EMF composition and functional genes relative to variation in well-known drivers of tree growth by combining paired molecular EMF surveys with high-resolution forest inventory data across 15 European countries. We show that EMF composition was linked to a three-fold difference in tree growth rate even when controlling for the primary abiotic drivers of tree growth. Fast tree growth was associated with EMF communities harboring high inorganic but low organic nitrogen acquisition gene proportions and EMF which form contact versus medium-distance fringe exploration types. These findings suggest that EMF composition is a strong bio-indicator of underlying drivers of tree growth and/or that variation of forest EMF communities causes differences in tree growth. While it may be too early to assign causality or directionality, our study is one of the first to link fine-scale variation within a key component of the forest microbiome to ecosystem functioning at a continental scale.

Deposition monitoring networks: what monitoring is required to give reasonable estimates of ammonia/ammonium?

Deposition is one of the main loss terms for ammonia and ammonium from the atmosphere. It is also the input for ecosystems that can lead to drastic changes and effects. Deposition networks are needed to evaluate the need and the effect of policies to reduce nitrogen emissions, but also for studying deposition parameters and for developing deposition models. As with ambient concentrations of ammonia, deposition, especially dry deposition, varies strongly in space and in time. Furthermore, the bi-directional surface-atmosphere exchange of ammonia makes the combination of ambient concentration measurements with inferential models inadequate. Developing deposition monitoring networks with reasonable accuracy and representativeness is therefore not straightforward. In Europe several projects have addressed deposition monitoring. From these results it is concluded that a monitoring strategy should consist of a network with a limited amount of super sites combined with a larger number of sites where low cost methods are applied, together with models for generalisation.

Monitoring and modelling of biosphere/atmosphere exchange of gases and aerosols in Europe.

Monitoring and modelling of deposition of air pollutants is essential to develop and evaluate policies to abate the effects related to air pollution and to determine the losses of pollutants from the atmosphere. Techniques for monitoring wet deposition fluxes are widely applied. A recent intercomparison experiment, however, showed that the uncertainty in wet deposition is relatively high, up to 40%, apart from the fact that most samplers are biased because of a dry deposition contribution. Wet deposition amounts to about 80% of the total deposition in Europe with a range of 10-90% and uncertainty should therefore be decreased. During recent years the monitoring of dry deposition has become possible. Three sites have been operational for 5 years. The data are useful for model development, but also for model evaluation and monitoring of progress in policy. Data show a decline in SO(2) dry deposition, whereas nitrogen deposition remained constant. Furthermore, surface affinities for pollutants changed leading to changes in deposition. Deposition models have been further developed and tested with dry deposition measurements and total deposition measurements on forests as derived from throughfall data. The comparison is reasonable given the measurement uncertainties. Progress in ozone surface exchange modelling and monitoring shows that stomatal uptake can be quantified with reasonable accuracy, but external surface uptake yields highest uncertainty.

NitroGenius: a nitrogen decision support system. A game to develop the optimal policy to solve the Dutch nitrogen pollution problem.

A nitrogen decision support system in the form of a game (NitroGenius) was developed for the Second International Nitrogen Conference. The aims were to: i) improve understanding among scientists and policy makers about the complexity of nitrogen pollution problems in an area of intensive agricultural, industrial, and transportation activity (The Netherlands); and ii) search for optimal policy solutions to prevent pollution effects at lowest economic and social costs. NitroGenius includes a model of nitrogen flows at relevant spatial and temporal scales including emissions of ammonia and nitrogen oxides and contamination of surface- and groundwaters. NitroGenius also includes an economic model describing relationships for important sectors and impacts of different nitrogen control measures on Gross Domestic Product (GDP), unemployment, energy use, and environmental costs. About 50 teams played NitroGenius during the Second International Nitrogen Conference. The results show that careful planning and selection of abatement options can solve Dutch nitrogen problems at reasonable cost.