Modelling of the natural chlorine cycling in a coniferous stand: implications for chlorine-36 behaviour in a contaminated forest environment

Considered as one of the most available radionuclide in soileplant system, 36Cl is of potential concern for long-term management of radioactive wastes, due to its high mobility and its long half-life. To evaluate the risk of dispersion and accumulation of 36Cl in the biosphere as a consequence of a potential contamination, there is a need for an appropriate understanding of the chlorine cycling dynamics in the ecosystems. To date, a small number of studies have investigated the chlorine transfer in the ecosystem including the transformation of chloride to organic chlorine but, to our knowledge, none have modelled this cycle. In this study, a model involving inorganic as well as organic pools in soils has been developed and parameterised to describe the biogeochemical fate of chlorine in a pine forest. The model has been evaluated for stable chlorine by performing a range of sensitivity analyses and by comparing the simulated to the observed values. Finally a range of contamination scenarios, which differ in terms of external supply, exposure time and source, has been simulated to estimate the possible accumulation of 36Cl within the different compartments of the coniferous stand. The sensitivity study supports the relevancy of the model and its compartments, and has highlighted the chlorine transfers affecting the most the residence time of chlorine in the stand. Compared to observations, the model simulates realistic values for the chlorine content within the different forest compartments. For both atmospheric and underground contamination scenarios most of the chlorine can be found in its organic form in the soil. However, in case of an underground source, about two times less chlorine accumulates in the system and proportionally more chlorine leaves the system through drainage than through volatilisation

Improved evaporative flux partitioning and carbon flux in the land surface model JULES: impact on the simulation of land surface processes in temperate Europe

The primary role of land surface models embedded in climate models is to partition surface available energy into upwards, radiative, sensible and latent heat fluxes. Partitioning of evapotranspiration, ET, is of fundamental importance: as a major component of the total surface latent heat flux, ET affects the simulated surface water balance, and related energy balance, and consequently the feedbacks with the atmosphere. In this context it is also crucial to credibly represent the CO2 exchange between ecosystems and their environment. In this study, JULES, the land surface model used in UK weather and climate models, has been evaluated for temperate Europe. Compared to eddy covariance flux measurements, the CO2 uptake by the ecosystem is underestimated and the ET overestimated. In addition, the contribution to ET from soil and intercepted water evaporation far outweighs the contribution of plant transpiration. To alleviate these biases, adaptations have been implemented in JULES, based on key literature references. These adaptations have improved the simulation of the spatio-temporal variability of the fluxes and the accuracy of the simulated GPP and ET, including its partitioning. This resulted in a shift of the seasonal soil moisture cycle. These adaptations are expected to increase the fidelity of climate simulations over Europe. Finally, the extreme summer of 2003 was used as evaluation benchmark for the use of the model in climate change studies. The improved model captures the impact of the 2003 drought on the carbon assimilation and the water use efficiency of the plants. It, however, underestimates the 2003 GPP anomalies. The simulations showed that a reduction of evaporation from the interception and soil reservoirs, albeit not of transpiration, largely explained the good correlation between the carbon and the water fluxes anomalies that was observed during 2003. This demonstrates the importance of being able to discriminate the response of individual component of the ET flux to environmental forcing

Simulating dynamic crop growth with an adapted land surface model – JULES-SUCROS: model development and validation

The increasing demand for ecosystem services, in conjunction with climate change, is expected to signif- icantly alter terrestrial ecosystems. In order to evaluate the sustainability of land and water resources, there is a need for a better understanding of the relationships between crop production, land surface characteristics and the energy and water cycles. These relationships are analysed using the Joint UK Land Environment Simulator (JULES). JULES includes the full hydrological cycle and vegetation effects on the energy, water, and carbon fluxes. However, this model currently only simulates land surface processes in natural ecosystems. An adapted version of JULES for agricultural ecosystems, called JULES-SUCROS has therefore been developed. In addition to overall model improvements, JULES-SUCROS includes a dynamic crop growth structure that fully fits within and builds upon the biogeochemical modelling framework for natural vegetation. Specific agro-ecosystem features such as the development of yield-bearing organs and the phenological cycle from sowing till harvest have been included in the model. This paper describes the structure of JULES-SUCROS and evaluates the fluxes simulated with this model against FLUXNET measurements at 6 European sites. We show that JULES-SUCROS significantly improves the correlation between simulated and observed fluxes over cropland and captures well the spatial and temporal vari- ability of the growth conditions in Europe. Simulations with JULES-SUCROS highlight the importance of vegetation structure and phenology, and the impact they have on land–atmosphere interactions

Differing Responses to Rainfall Suggest More Than One Functional Type of Grassland in South Africa

Grasslands, which represent around 40% of the terrestrial area, are mostly located in arid and semi-arid zones. Semiarid ecosystems in Africa have been identified as being particularly vulnerable to the impacts of increased human pressure on land, as well as enhanced climate variability. Grasslands are indeed very responsive to variations in precipitation. This study evaluates the sensitivity of the grassland ecosystem to precipitation variability in space and time, by identifying the factors controlling this response, based on monthly precipitation data from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) and the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) data from the Multi-angle Imaging SpectroRadiometer-High Resolution (MISR-HR) datasets, used as proxy for productivity, at 60 grassland sites in South Africa. Our results show that MISR-HR products adequately capture the spatial and temporal variability in productivity at scales that are relevant to this study, and they are therefore a good tool to study climate change impacts on ecosystem at small spatial scales over large spatial and temporal domains. We show that combining several determinants and accounting for legacies improves our ability to understand patterns, identify areas of vulnerability, and predict the future of grassland productivity. Mean annual precipitation is a good predictor of mean grassland productivity. The grasslands with a mean annual rainfall above about 530 mm have a different functional response to those receiving less than that amount of rain, on average. On the more arid and less fertile soils, large inter-annual variability reduces productivity. Our study suggests that grasslands on the more marginal soils are the most vulnerable to climate change

L.: Simulating dynamic crop growth with an adapted land surface model – JULESSUCROS: Model development and validation

Abstract The increasing demand for ecosystem services, in conjunction with climate change, is expected to significantly alter terrestrial ecosystems. In order to evaluate the sustainability of land and water resources, there is a need for a better understanding of the relationships between crop production, land surface characteristics and the energy and water cycles. These relationships are analysed by using the Joint UK Land Environment Simulator (JULES). JULES includes the full hydrological cycle and vegetation effects on the energy, water, and carbon fluxes. However, this model currently only simulates land surface processes in natural ecosystems. An adapted version of JULES for agricultural ecosystems, called JULES-SUCROS has therefore been developed. In addition to overall model improvements, JULES-SUCROS includes a dynamic crop growth structure that fully fits within and builds upon the biogeochemical modelling framework for natural vegetation. Specific agro-ecosystem features such as the development of yield-bearing organs and the phenological cycle from sowing till harvest have been included in the model. This paper describes the structure of JULES-SUCROS and evaluates the fluxes simulated with this model against FLUXNET measurements at 6 European sites. We show that JULES-SUCROS significantly improves the correlation between simulated and observed fluxes over cropland and captures well the spatial and temporal variability of the growth conditions in Europe. Simulations with JULES-SUCROS highlight the importance of vegetation structure and phenology, and the impact they have on land-atmosphere interactions

Facilitating the Management of Protected Areas through Multi-Level Ecosystem Accounting on an Example in West Africa

West Africa, already highly influenced by the negative effects of climate change, is additionally characterized by rapid population growth, endemic poverty, and insecurity. This is affecting the natural capital of its ecosystems and the services they provide. Natural capital accounting (NCA) provides the fundamental evidence base required for informing economics and environmental decisions, thus strengthening the conservation and management of natural resources. The objective of this study is to showcase the development and evaluation of a semi-automated NCA platform (Sys4ENCA) designed to support decision making in the context of protected areas management in a multi-level example in western Africa. The accounting results highlight that simulations at the broader scale using national public data show that the natural capital of ecosystems in western Africa depends strongly on the mean climate and its variability. Evaluating regional datasets, the simulation with the platform shows that pressure on land in combination with weak governance reduces the capability of the ecosystem to deliver the required services in a sustainable manner, i.e., in the eastern part of the Bafing-Falémé landscape, where mining and intensive agriculture are fueling loss of natural capital. The results of Tier-3 accounting using local datasets enhanced the spatial variability and highlighted additional hotspots of degradation compared to the regional results, i.e., the prospective construction of a hydro-electricity dam (Koukoutamba) in the southern part of the Moyen-Bafing National Park located in the Bafing-Falémé landscape. The Sys4ENCA platform, combined with a multi-level approach, showed itself to be a valuable tool to facilitate protected area management as it provides not only consolidated information at a local scale but also the broader context and external pressures, i.e., climate change and demand for land. Given its automatized nature, the platform reduces human errors and increases the efficiency, speed, and harmonisation of computation over long timeframes and spatial scales

Linking biochemical and biophysical variables derived from imaging spectrometers to ecological models - The HyEco'04 Group Shoot

We report on the first results of the HyEco'04 campaign carried out in summer 2004 as a joint activity of a bi-national team of Belgian and Dutch researchers. This integrated approach of assessing the complexity of managed natural ecosystems is a demonstrator case for recent focus of airborne imaging spectroscopy activities on ecotones. The floodplain Millingerwaard located east to the city of Nijmegen along the river Rhine has been chosen to demonstrate the potential of imaging spectrometer data to support ecological modelling. Several ground support teams supported the data acquisition of the Hymap sensor during its overflight on two days in July and August 2004. Field measurements concentrated on two approaches: first, radiometric measurements supporting the linking between soil-vegetation-atmosphere transfer modelling (e.g., sunphotometer, leaf optical properties measurements, canopy reflectance, structural parameter measurements (gap fraction, leaf angle distribution, leaf area index) have been performed and secondly supporting additional measurements on vegetation (species mapping, destructive biomass sampling) and soil (moisture, temperature) have been performed. First, we will report on the data quality evaluation of the various data sources and their integration into an integrated system, dealing with various aspects of spatial sampling schemes and potential spatial discontinuities, as well as uncertainty measures. Secondly, we discuss two examples of spatially distributed products derived from either ground based measurements and inventory mapping, extrapolated to the full coverage of the test site or imaging spectrometer derived products. The resulting products are discussed in view of potential incorporation into land-biosphere models, where high or even unknown uncertainty in input data, and limited availability of geographically explicit input data are usually the limiting factors for the application of ecological models on a larger spatial extent (e.g. national).status: publishe