Handling the phosphorus paradox in agriculture and natural ecosystems: Scarcity,necessity, and burden of P

This special issue of Ambio compiles a series of contributions made at the 8th International Phosphorus Workshop (IPW8), held in September 2016 in Rostock, Germany. The introducing overview article summarizes major published scientific findings in the time period from IPW7 (2015) until recently, including presentations from IPW8. The P issue was subdivided into four themes along the logical sequence of P utilization in production, environmental, and societal systems: (1) Sufficiency and efficiency of P utilization, especially in animal husbandry and crop production; (2) P recycling: technologies and product applications; (3) P fluxes and cycling in the environment; and (4) P governance. The latter two themes had separate sessions for the first time in the International Phosphorus Workshops series; thus, this overview presents a scene-setting rather than an overview of the latest research for these themes. In summary, this paper details new findings in agricultural and environmental P research, which indicate reduced P inputs, improved management options, and provide translations into governance options for a more sustainable P use.     

Achieving forest carbon information with higher certainty: A five-part plan

International negotiations on the inclusion of land use activities into an emissions reduction system for the UN Framework Convention on Climate Change (UNFCCC) have been partially hindered by the technical challenges of measuring, reporting, and verifying greenhouse gas (GHG) emissions and the policy issues of leakage, additionality, and permanence. This paper outlines a five-part plan for estimating forest carbon stocks and emissions with the accuracy and certainty needed to support a policy for Reducing Emissions from Deforestation and forest Degradation, forest conservation, sustainable management of forests, and enhancement of forest carbon stocks (the REDD-plus framework considered at the UNFCCC COP-15) in developing countries. The plan is aimed at UNFCCC non-Annex 1 developing countries, but the principles outlined are also applicable to developed (Annex 1) countries. The parts of the plan are: (1) Expand the number of national forest carbon Measuring, Reporting, and Verification (MRV) systems with a priority on tropical developing countries; (2) Implement continuous global forest carbon assessments through the network of national systems; (3) Achieve commitments from national space agencies for the necessary satellite data; (4) Establish agreed-on standards and independent verification processes to ensure robust reporting; and (5) Enhance coordination among international and multilateral organizations.     

Simulation of NO and N2O emissions from a spruce forest during a freeze/thaw event using an N-flux submodel from the PnET-N-DNDC model integrated to CoupModel

The amount of nitrogen gases (N₂O, NO and N₂) emitted from forest soils depends on interactions between soil properties, climatic factors and soil management. To increase the understanding of nitrogen processes in soil ecosystems, two dynamic models, CoupModel (coupled heat and mass transfer model for soil–plant–atmosphere systems) and the denitrification–decomposition (DNDC) model were selected. Both are dynamic models with different submodels for soil, vegetation, hydrology and climate system. CoupModel has a higher degree of detail on soil physical and abiotic components, whereas the DNDC model contains details of microbiological processes involved in production of nitrogen gases. To improve the previous simple submodel of nitrogen emission in CoupModel, we included a submodel corresponding to the forest version of DNDC containing photosynthesis/evapotranspiration-nitrogen (PnET-N-DNDC model).     

Modeling seasonal course of carbon fluxes and evapotranspiration in response to low temperature and moisture in a boreal Scots pine ecosystem

Environmental conditions act above and below ground, and regulate carbon fluxes and evapotranspiration. The productivity of boreal forest ecosystems is strongly governed by low temperature and moisture conditions, but the understanding of various feedbacks between vegetation and environmental conditions is still unclear. In order to quantify the seasonal responses of vegetation to environmental factors, the seasonality of carbon and heat fluxes and the corresponding responses for temperature and moisture in air and soil were simulated by merging a process-based model (CoupModel) with detailed measurements representing various components of a forest ecosystem in Hyytiälä, southern Finland. The uncertainties in parameters, model assumptions, and measurements were identified by generalized likelihood uncertainty estimation (GLUE). Seasonal and diurnal courses of sensible and latent heat fluxes and net ecosystem exchange (NEE) of CO₂ were successfully simulated for two contrasting years. Moreover, systematic increases in efficiency of photosynthesis, water uptake, and decomposition occurred from spring to summer, demonstrating the strong coupling between processes. Evapotranspiration and NEE flux both showed a strong response to soil temperature conditions via different direct and indirect ecosystem mechanisms. The rate of photosynthesis was strongly correlated with the corresponding water uptake response and the light use efficiency. With the present data and model assumptions, it was not possible to precisely distinguish the various regulating ecosystem mechanisms. Our approach proved robust for modeling the seasonal course of carbon fluxes and evapotranspiration by combining different independent measurements. It will be highly interesting to continue using long-term series data and to make additional tests of optional stomatal conductance models in order to improve our understanding of the boreal forest ecosystem in response to climate variability and environmental conditions.     

Modeling carbon turnover in five terrestrial ecosystems in the boreal zone using multiple criteria of acceptance

Estimates of carbon fluxes and turnover in ecosystems are key elements in the understanding of climate change and in predicting the accumulation of trace elements in the biosphere. In this paper we present estimates of carbon fluxes and turnover times for five terrestrial ecosystems using a modeling approach. Multiple criteria of acceptance were used to parameterize the model, thus incorporating large amounts of multi-faceted empirical data in the simulations in a standardized manner. Mean turnover times of carbon were found to be rather similar between systems with a few exceptions, even though the size of both the pools and the fluxes varied substantially. Depending on the route of the carbon through the ecosystem, turnover times varied from less than one year to more than one hundred, which may be of importance when considering trace element transport and retention. The parameterization method was useful both in the estimation of unknown parameters, and to identify variability in carbon turnover in the selected ecosystems.     

Uncertainty analyses for calibrating a soil carbon balance model to agricultural field trial data in Sweden and Kenya

How do additional data of the same and/or different type contribute to reducing model parameter and predictive uncertainties? Most modeling applications of soil organic carbon (SOC) time series in agricultural field trial datasets have been conducted without accounting for model parameter uncertainty. There have been recent advances with Monte Carlo-based uncertainty analyses in the field of hydrological modeling that are applicable, relevant and potentially valuable in modeling the dynamics of SOC. Here we employed a Monte Carlo method with threshold screening known as Generalized Likelihood Uncertainty Estimation (GLUE) to calibrate the Introductory Carbon Balance Model (ICBM) to long-term field trail data from Ultuna, Sweden and Machang’a, Kenya. Calibration results are presented in terms of parameter distributions and credibility bands on time series simulations for a number of case studies. Using these methods, we demonstrate that widely uncertain model parameters, as well as strong covariance between inert pool size and rate constant parameters, exist when root mean square simulation errors were within uncertainties in input estimations and data observations. We show that even rough estimates of the inert pool (perhaps from chemical analysis) can be quite valuable to reduce uncertainties in model parameters. In fact, such estimates were more effective at reducing parameter and predictive uncertainty than an additional 16 years time series data at Ultuna. We also demonstrate an effective method to jointly, simultaneously and in principle more robustly calibrate model parameters to multiple datasets across different climatic regions within an uncertainty framework. These methods and approaches should have benefits for use with other SOC models and datasets as well.