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Soils store large quantities of carbon in the subsoil (below 0.2 m depth) that is generally old and believed to be stabilized over centuries to millennia, which suggests that subsoil carbon sequestration (CS) can be used as a strategy for climate change mitigation. In this article, we review the main biophysical processes that contribute to carbon storage in subsoil and the main mathematical models used to represent these processes. Our guiding objective is to review whether a process understanding of soil carbon movement in the vertical profile can help us to assess carbon storage and persistence at timescales relevant for climate change mitigation. Bioturbation, liquid phase transport, belowground carbon inputs, mineral association, and microbial activity are the main processes contributing to the formation of soil carbon profiles, and these processes are represented in models using the diffusion–advection–reaction paradigm. Based on simulation examples and measurements from carbon and radiocarbon profiles across biomes, we found that advective and diffusive transport may only play a secondary role in the formation of soil carbon profiles. The difference between vertical root inputs and decomposition seems to play a primary role in determining the shape of carbon change with depth. Using the transit time of carbon to assess the timescales of carbon storage of new inputs, we show that only small quantities of new carbon inputs travel through the profile and can be stabilized for time horizons longer than 50 years, implying that activities that promote CS in the subsoil must take into consideration the very small quantities that can be stabilized in the long term.

Procedures for environmental risk assessment for pesticides are under continuous development and subject to debate, especially at higher tier levels. Spatiotemporal dynamics of both pesticide exposure and effects at the landscape scale are largely ignored, which is a major flaw of the current risk assessment system. Furthermore, concrete guidance on risk assessment at landscape scales in the regulatory context is lacking. In this regard, we present an integrated modular simulation model system that includes spatiotemporally explicit simulation of pesticide application, fate, and effects on aquatic organisms. As a case study, the landscape model was applied to the Rummen, a river catchment in Belgium with a high density of pome fruit orchards. The application of a pyrethroid to pome fruit and the corresponding drift deposition on surface water and fate dynamics were simulated. Risk to aquatic organisms was quantified using a toxicokinetic/toxicodynamic model for individual survival at different levels of spatial aggregation, ranging from the catchment scale to individual stream segments. Although the derivation of landscape-scale risk assessment end points from model outputs is straightforward, a dialogue within the community, building on concrete examples as provided by this case study, is urgently needed in order to decide on the appropriate end points and on the definition of representative landscape scenarios for use in risk assessment.

FOCUSPEARL 5.5.5 is a Windows application that allows users to perform simulations to assess pesticide fate in soil for use in regulatory risk assessment in the European Union. It includes the PEARL and SWAP numerical models, agraphical user interface (GUI) and a database storing information defining simulation runs—including all input datafor the nine FOCUS groundwater scenarios. This report provides a technical description of the FOCUSPEARL 5.5.5database and its relationship with the GUI. It is intended for developers and maintainers of the application, to assist further development and quality assurance.---FOCUSPEARL 5.5.5 is een Windows-applicatie waarmee gebruikers simulaties van het gedrag van pesticiden in de bodem kunnen uitvoeren voor risicobeoordeling voor pesticideregistratie. Het omvat de PEARL en SWAP numerieke modellen, een grafische gebruikersinterface, en een database voor het opslaan van de benodigde gegevens voor simulatie-runs, waaronder inputdata voor de negen FOCUS grondwater-scenario’s. Dit rapport geeft een beschrijving van de FOCUSPEARL 5.5.5-database en de relatie met de gebruikersinterface. Het is bedoeld voor ontwikkelaars en beheerders van de applicatie en dient ter ondersteuning van verdere ontwikkeling en kwaliteitsborging.

TOXSWA is a numerical model describing pesticide behavior in an edge-of-field waterbody. It is widely used to predict exposure in regulatory risk assessment for aquatic ecosystems. Exposure concentrations are predicted based upon pesticide process parameters obtained in standardized laboratory experiments. However, few tests of the model performance based on field data have been carried out. We compare simulated concentrations to observations from a field experiment with four shallow stagnant ditches over sprayed with chlorpyrifos, a moderately volatile pesticide with a significant sorption capacity. Input parameters describing the four ditches, such as dimensions, water depth, sediment and macrophyte characteristics were measured in detail. Additionally, laboratory experiments were carried out to determine site-specific values for parameters describing chlorpyrifos degradation in water and sediment, as well as sorption to the two dominant macrophyte species. Based upon these estimated parameters, the correspondence between simulated and measured concentrations in water, sediment and macrophytes is poor. We attribute this discrepancy to a lack of site-specific input for the processes of volatilization and sorption to sediment, which both are important processes for chlorpyrifos. Therefore, we calibrated TOXSWA using the optimization tool PEST. The transfer coefficient for volatilization and the coefficient for sorption to sediment were optimized based on the observed concentrations in water and sediment. This resulted in a substantial improvement of correspondence. Optimized values of the transfer coefficient for volatilization and the coefficient for sorption to sediment are substantially higher than their initial estimates (4–8-fold and 2–4-fold increase, respectively), but can be well explained. The optimized coefficients vary less than a factor 2 between the four ditches. We conclude that TOXSWA can adequately predict chlorpyrifos behavior in the four ditches, p

We present an extension of the dynamic global vegetation model, Lund-Potsdam-Jena Managed Land (LPJmL), to simulate planted forests intended for carbon (C) sequestration. We implemented three functional types to simulate plantation trees in temperate, tropical, and boreal climates. The parameters of these functional types were optimized to fit target growth curves (TGCs). These curves represent the evolution of stemwood C over time in typical productive plantations and were derived by combining field observations and LPJmL estimates for equivalent natural forests. While the calibrated model underestimates stemwood C growth rates compared to the TGCs, it represents substantial improvement over using natural forests to represent afforestation. Based on a simulation experiment in which we compared global natural forest versus global forest plantation, we found that forest plantations allow for much larger C uptake rates on the timescale of 100 years, with a maximum difference of a factor of 1.9, around 54 years. In subsequent simulations for an ambitious but realistic scenario in which 650Mha (14% of global managed land, 4.5% of global land surface) are converted to forest over 85 years, we found that natural forests take up 37PgC versus 48PgC for forest plantations. Comparing these results to estimations of C sequestration required to achieve the 2°C climate target, we conclude that afforestation can offer a substantial contribution to climate mitigation. Full evaluation of afforestation as a climate change mitigation strategy requires an integrated assessment which considers all relevant aspects, including costs, biodiversity, and trade-offs with other land-use types. Our extended version of LPJmL can contribute to such an assessment by providing improved estimates of C uptake rates by forest plantations., Atmospheric Remote Sensing

Understanding climate change effects on forests is important considering the role forests play in mitigating climate change. We studied the effects of changes in temperature, rainfall, atmospheric carbon dioxide (CO2) concentration, solar radiation, and number of wet days (as a measure of rainfall intensity) on net primary productivity (NPP) of the Zambian Zambezi teak forests along a rainfall gradient. Using 1960-1989 as a baseline, we projected changes in NPP for the end of the 21st century (2070-2099). We adapted the parameters of the dynamic vegetation model, LPJ-GUESS, to simulate the growth of Zambian forests at three sites along a moisture gradient receiving annual rainfall of between 700 and more than 1000 mm. The adjusted plant functional type was tested against measured data. We forced the model with contemporary climate data (1960-2005) and with climatic forecasts of an ensemble of five general circulation models (GCMs) following Representative Concentration Pathways (RCPs) RCP4.5 and RCP8.5. We used local soil parameter values to characterize texture and measured local tree parameter values for maximum crown area, wood density, leaf longevity, and allometry. The results simulated with the LPJGUESS model improved when we used these newly generated local parameters, indicating that using local parameter values is essential to obtaining reliable simulations at site level. The adapted model setup provided a baseline for assessing the potential effects of climate change on NPP in the studied Zambezi teak forests. Using this adapted model version, NPP was projected to increase by 1.77% and 0.69% at the wetter Kabompo and by 0.44% and 0.10% at the intermediate Namwala sites under RCP8.5 and RCP4.5 respectively, especially caused by the increased CO2 concentration by the end of the 21st century. However, at the drier Sesheke site, NPP would respectively decrease by 0.01% and 0.04% by the end of the 21st century under RCP8.5 and RCP4.5. The projected decreased NP

We investigated the merits of radiocarbon measurements for estimating soil organic matter (SOM) turnover and vertical transport for a temperate deciduous forest in Germany. Eleven parameters, defining decomposition and transport in the soil carbon model SOMPROF, were estimated using a Bayesian approach based on organic carbon measurements and radiocarbon concentration of SOM and heterotrophic respiration. The addition of radiocarbon data had strong effects on the parameters, most importantly a reduction of the decomposition and production rate of the slowest SOM pool by an order of magnitude, and a similar reduction in advective SOM transport. The modified parameters further led to changes in the partitioning of SOM over the different model pools. The calibration results were subsequently used to perform transient soil carbon projections for the period 1901-2100. These simulations were run with parameter sets from calibrations both with and without radiocarbon. The results show an increase over time of topsoil carbon and a decrease in the subsoil, adding to a net gain overall. Near the end of the 21st century, total carbon stocks stabilize andfor the radiocarbon-constrained modelstart to decrease. However, the changes are small compared to the total stocks. The model results for the calibrations with and without radiocarbon are in general quite similar, but the latter shows notably higher heterotrophic respiration fluxes. Constraining the model with radiocarbon yielded only a small reduction of uncertainty for the total carbon stocks, while for the individual depth compartments, the uncertainty wasincreased. Key Points SOM turnover and transport was estimated using Bayesian calibration Radiocarbon data strongly improved constraint of turnover rate of slow pool Predictive simulation showed small increase of soil C stocks in, AuthorCount:9