Predicted soil organic carbon stocks and changes in the Brazilian Amazon between 2000 and 2030

Currently we have little understanding of the impacts of land use change on soil C stocks in the Brazilian Amazon. Such information is needed to determine impacts'6n the global C cycle and the sustainability of agricultural systems that are replacing native forest. The aim of this study was to predict soil carbon stocks and changes in the Brazilian Amazon during the period between 2000 and 2030, using the GEFSOC soil carbon (C) modelling system. In order to do so, we devised current and future land use scenarios for the Brazilian Amazon, taking into account: (i) deforestation, rates from the past three decades, (ii) census data on land use from 1940 to 2000, including the expansion and intensification of agriculture in the region, (iii) available information on management practices, primarily related to well managed pasture versus degraded pasture and conventional systems versus no-tillage systems for soybean (Glycine max) and (iv) FAO predictions on agricultural land use and land use changes for the years 2015 and 2030. The land use scenarios were integrated with spatially explicit soils data (SOTER database), climate, potential natural vegetation and land management units using the recently developed GEFSOC soil C modelling system. Results are presented in map, table and graph form for the entire Brazilian Amazon for the current situation (1990 and 2000) and the future (2015 and 2030). Results include soil organic C (SOC) stocks and SOC stock change rates estimated by three methods: (i) the Century ecosystem model, (ii) the Rothamsted C model and (iii) the intergovernmental panel on climate change (IPCC) method for assessing soil C at regional scale. In addition, we show estimated values of above and belowground biomass for native vegetation, pasture and soybean. The results on regional SOC stocks compare reasonably well with those based on mapping approaches. The GEFSOC system provided a means of efficiently handling complex interactions among biotic-edapho-climatic conditions (> 363,000 combinations) in a very large area (similar to 500 Mha) such as the Brazilian Amazon. All of the methods used showed a decline in SOC stock for the period studied; Century and RothC simulated values for 2030 being about 7% lower than those in 1990. Values from Century and RothC (30,430 and 25,000 Tg for the 0-20 cm layer for the Brazilian Amazon region were higher than those obtained from the IPCC system (23,400 Tg in the 0-30 cm layer). Finally; our results can help understand the major biogeochemical cycles that influence soil fertility and help devise management strategies that enhance the sustainability of these areas and thus slow further deforestation. (C) 2007 Elsevier B.V. All rights reserved.

A semi-quantitative approach to deriving a model structure for the uptake of organic chemicals by vegetation

An expert elicitation exercise was undertaken to determine those components and processes that are most important for modeling plant uptake of organic chemicals. The state of our knowledge of these processes was also assessed. This semi-quantitative analysis allowed the construction of an idealized model with seven compartments; soil bulk, soil water, roots, stem, leaves, fruit, and air. Three main areas were identified further research: 1) the uptake of organic chemicals by fruit; 2) the internal transfer of organic chemicals between plant structures (e.g., stem and leaves); and 3) the transfer via the soil-air-plant pathway. Until new data becomes available to quantify these processes, it is proposed that an equilibrium partitioning approach is used between plant components other than fruit or that models consist of both an edible and inedible compartment.

Plant uptake of non-ionic organic chemicals

Plant uptake of organic chemicals is an important process when considering the risks associated with land contamination, the role of vegetation in the global cycling of persistent organic pollutants, and the potential for industrial discharges to contaminate the food chain. There have been some significant advances in our understanding of the processes of plant uptake of organic chemicals in recent years; most notably there is now a better understanding of the air to plant transfer pathway, which may be significant for a number of industrial chemicals. This review identifies the key processes involved in the plant uptake of organic chemicals including those for which there is currently little information, e.g., plant lipid content and plant metabolism. One of the principal findings is that although a number of predictive models exist using established relationships, these require further validation if they are to be considered sufficiently robust for the purposes of contaminated land risk assessment or for prediction of the global cycling of persistent organic pollutants. Finally, a number of processes are identified which should be the focus of future research

Phylogenetic variation in the tolerance and uptake of organic contaminants

An investigation into the phylogenetic variation of plant tolerance and the root and shoot uptake of organic contaminants was undertaken. The aim was to determine if particular families or genera were tolerant of, or accumulated organic pollutants. Data were collected from sixty-nine studies. The variation between experiments was accounted for using a residual maximum likelihood analysis to approximate means for individual taxa. A nested ANOVA was subsequently used to determine differences at a number of differing phylogenetic levels. Significant differences were observed at a number of phylogenetic levels for the tolerance to TPH, the root concentration factor and the shoot concentration factor. There was no correlation between the uptake of organic pollutants and that of heavy metals. The data indicate that plant phylogeny is an important influence on both the plant tolerance and uptake of organic pollutants. If this study can be expanded, such information can be used when designing plantings for phytoremediation or risk reduction during the restoration of contaminated sites.

The use of earth observation techniques to improve catchment-scale pollution predictions

Remote sensing can potentially provide information useful in improving pollution transport modelling in agricultural catchments. Realisation of this potential will depend on the availability of the raw data, development of information extraction techniques, and the impact of the assimilation of the derived information into models. High spatial resolution hyperspectral imagery of a farm near Hereford, UK is analysed. A technique is described to automatically identify the soil and vegetation endmembers within a field, enabling vegetation fractional cover estimation. The aerially-acquired laser altimetry is used to produce digital elevation models of the site. At the subfield scale the hypothesis that higher resolution topography will make a substantial difference to contaminant transport is tested using the AGricultural Non-Point Source (AGNPS) model. Slope aspect and direction information are extracted from the topography at different resolutions to study the effects on soil erosion, deposition, runoff and nutrient losses. Field-scale models are often used to model drainage water, nitrate and runoff/sediment loss, but the demanding input data requirements make scaling up to catchment level difficult. By determining the input range of spatial variables gathered from EO data, and comparing the response of models to the range of variation measured, the critical model inputs can be identified. Response surfaces to variation in these inputs constrain uncertainty in model predictions and are presented. Although optical earth observation analysis can provide fractional vegetation cover, cloud cover and semi-random weather patterns can hinder data acquisition in Northern Europe. A Spring and Autumn cloud cover analysis is carried out over seven UK sites close to agricultural districts, using historic satellite image metadata, climate modelling and historic ground weather observations. Results are assessed in terms of probability of acquisition probability and implications for future earth observation missions. (C) 2003 Elsevier Ltd. All rights reserved.

Distribution of selected heavy metals in sediments of the Agueda river (Central Portugal)

The state of river water deterioration in the Agueda hydrographic basin, mostly in the western part, partly reflects the high rate of housing and industrial development in this area in recent years. The streams have acted as a sink for organic and inorganic loads from several origins: domestic and industrial sewage and agricultural waste. The contents of the heavy metals Cr, Cd, Ni, Cu, Pb, and Zn were studied by sequential chemical extraction of the principal geochemical phases of streambed sediments, in the <63 mum fraction, in order to assess their potential availability to the environment, investigating, the metal concentrations, assemblages, and trends. The granulometric and mineralogical characteristics of this sediment fraction were also studied. This study revealed clear pollution by Cr, Cd, Ni, Cu, Zn, and Pb, as a result from both natural and anthropogenic origins. The chemical transport of metals appears to be essentially by the following geochemical phases, in decreasing order of significance: (exchangeable + carbonates) much greater than (organics) much greater than (Mn and Fe oxides and hydroxides). The (exchangeable + carbonate) phase plays an important part in the fixation of Cu, Ni, Zn, and Cd. The organic phase is important in the fixation of Cr, Pb, and also Cu and Ni. Analyzing the metal contents in the residual fraction, we conclude that Zn and Cd are the most mobile, and Cr and Pb are less mobile than Cu and Ni. The proximity of the pollutant sources and the timing of the influx of contaminated material control the distribution of the contaminant-related sediments locally and on the network scale.

Modeling the mechanisms that control in-stream dissolved organic carbon dynamics in upland and forested catchments

[1] We present a new, process-based model of soil and stream water dissolved organic carbon (DOC): the Integrated Catchments Model for Carbon (INCA-C). INCA-C is the first model of DOC cycling to explicitly include effects of different land cover types, hydrological flow paths, in-soil carbon biogeochemistry, and surface water processes on in-stream DOC concentrations. It can be calibrated using only routinely available monitoring data. INCA-C simulates daily DOC concentrations over a period of years to decades. Sources, sinks, and transformation of solid and dissolved organic carbon in peat and forest soils, wetlands, and streams as well as organic carbon mineralization in stream waters are modeled. INCA-C is designed to be applied to natural and seminatural forested and peat-dominated catchments in boreal and temperate regions. Simulations at two forested catchments showed that seasonal and interannual patterns of DOC concentration could be modeled using climate-related parameters alone. A sensitivity analysis showed that model predictions were dependent on the mass of organic carbon in the soil and that in-soil process rates were dependent on soil moisture status. Sensitive rate coefficients in the model included those for organic carbon sorption and desorption and DOC mineralization in the soil. The model was also sensitive to the amount of litter fall. Our results show the importance of climate variability in controlling surface water DOC concentrations and suggest the need for further research on the mechanisms controlling production and consumption of DOC in soils.

Health Benefits of Organic Food: effects of the environment

Public concern over impacts of chemicals in plant and animal production on health and the environment has led to increased demand for organic produce, which is usually promoted and often perceived as containing fewer contaminants, more nutrients, and being positive for the environment. These benefits are difficult to quantify, and potential environmental impacts on such benefits have not been widely studied. This book addresses these key points, examining factors such as the role of certain nutrients in prevention and promotion of chronic disease, potential health benefits of bioactive compounds in plants, the prevalence of food-borne pesticides and pathogens and how both local and global environmental factors may affect any differences between organic and conventionally produced food. This book is an essential resource for researchers and students in human health and nutrition, environmental science, agriculture and organic farming. Main Contents 1. Organic farming and food systems: definitions and key characteristics. 2. The health benefits of n-3 fatty acids and their concentrations in organic and conventional animal-derived foods. 3. Environmental impacts on n-3 content of foods from ruminant animals. 4. Health benefits and selenium content of organic vs conventional foods. 5. Environmental impacts concerning the selenium content of foods. 6. Contaminants in organic and conventional food: the missing link between contaminant levels and health effects. 7. Mycotoxins in organic and conventional foods and effects of the environment. 8. Human pathogens in organic and conventional foods and effects of the environment. 9. What does consumer science tell us about organic foods? 10. The beneficial effects of dietary flavonoids: sources, bioavailability and biological functions. 11. Environmental regulation of flavonoid biosynthesis. 12. Nitrates in the human diet. 13. Impacts of environment and management on nitrate in vegetables and water. 14. Effects of the environment on the nutritional quality and safety of organically produced foods: Round-up and summary.

A multi-scale framework for strategic management of diffuse pollution

A multi-scale framework for decision support is presented that uses a combination of experiments, models, communication, education and decision support tools to arrive at a realistic strategy to minimise diffuse pollution. Effective partnerships between researchers and stakeholders play a key part in successful implementation of this strategy. The Decision Support Matrix (DSM) is introduced as a set of visualisations that can be used at all scales, both to inform decision making and as a communication tool in stakeholder workshops. A demonstration farm is presented and one of its fields is taken as a case study. Hydrological and nutrient flow path models are used for event based simulation (TOPCAT), catchment scale modelling (INCA) and field scale flow visualisation (TopManage). One of the DSMs; The Phosphorus Export Risk Matrix (PERM) is discussed in detail. The PERM was developed iteratively as a point of discussion in stakeholder workshops, as a decision support and education tool. The resulting interactive PERM contains a set of questions and proposed remediation measures that reflect both expert and local knowledge. Education and visualisation tools such as GIS, risk indicators, TopManage and the PERM are found to be invaluable in communicating improved farming practice to stakeholders. (C) 2008 Elsevier Ltd. All rights reserved.

Towards a nutrient export risk matrix approach to managing agricultural pollution at source

A generic Nutrient Export Risk Matrix (NERM) approach is presented. This provides advice to farmers and policy makers on good practice for reducing nutrient loss and is intended to persuade them to implement such measures. Combined with a range of nutrient transport modelling tools and field experiments, NERMs can play an important role in reducing nutrient export from agricultural land. The Phosphorus Export Risk Matrix (PERM) is presented as an example NERM. The PERM integrates hydrological understanding of runoff with a number of agronomic and policy factors into a clear problem-solving framework. This allows farmers and policy makers to visualise strategies for reducing phosphorus loss through proactive land management. The risk Of Pollution is assessed by a series of informed questions relating to farming intensity and practice. This information is combined with the concept of runoff management to point towards simple, practical remedial strategies which do not compromise farmers' ability to obtain sound economic returns from their crop and livestock.

The turnover of organic carbon in subsoils. Part 2. Modelling carbon turnover

A new model, RothPC-1, is described for the turnover of organic C in the top metre of soil. RothPC-1 is a version of RothC-26.3, an earlier model for the turnover of C in topsoils. In RothPC-1 two extra parameters are used to model turnover in the top metre of soil: one, p, which moves organic C down the profile by an advective process, and the other, s, which slows decomposition with depth. RothPC-1 is parameterized and tested using measurements (described in Part 1, this issue) of total organic C and radiocarbon on soil profiles from the Rothamsted long-term field experiments, collected over a period of more than 100 years. RothPC-1 gives fits to measurements of organic C and radiocarbon in the 0-23, 23-46, 46-69 and 69-92 cm layers of soil that are almost all within (or close to) measurement error in two areas of regenerating woodland (Geescroft and Broadbalk Wildernesses) and an area of cultivated land from the Broadbalk Continuous Wheat Experiment. The fits to old grassland (the Park Grass Experiment) are less close. Two other sites that provide the requisite pre- and post-bomb data are also fitted; a prairie Chernozem from Russia and an annual grassland from California. Roth-PC-1 gives a close fit to measurements of organic C and radiocarbon down the Chernozem profile, provided that allowance is made for soil age; with the annual grassland the fit is acceptable in the upper part of the profile, but not in the clay-rich Bt horizon below. Calculations suggest that treating the top metre of soil as a homogeneous unit will greatly overestimate the effects of global warming in accelerating the decomposition of soil C and hence on the enhanced release of CO2 from soil organic matter; more realistic estimates will be obtained from multi-layer models such as RothPC-1.

Predicted soil organic carbon stocks and changes in Kenya between 1990 and 2030

Under the United Nations Framework Convention on Climate Change (UNFCCC), Non-Annex 1 countries such as Kenya are obliged to report green house gas (GHG) emissions from all sources where possible, including those from soils as a result of changes in land use or land management. At present, the convention encourages countries to estimate emissions using the most advanced methods possible, given the country circumstances and resources. Estimates of soil organic carbon (SOC) stocks and changes were made for Kenya using the Global Environment Facility Soil Organic Carbon (GEFSOC) Modelling System. The tool conducts analysis using three methods: (1) the Century general ecosystem model; (2) the RothC soil C decomposition model; and (3) the Intergovernmental Panel on Climate Change (IPCC) method for assessing soil C at regional scales. The required datasets included: land use history, monthly mean precipitation, monthly mean minimum and maximum temperatures for all the agro-climatic zones of Kenya and historical vegetation cover. Soil C stocks of 1.4-2.0 Pg (0-20 cm), compared well with a Soil and Terrain (SOTER) based approach that estimated similar to .8-2.0 Pg (0-30 cm). In 1990 48% of the country had SOC stocks of < 18 t C ha(-1) and 20% of the country had SOC stocks of 18-30 t C ha(-1), whereas in 2000 56% of the country had SOC stocks of < 18 t C ha(-1) and 31% of the country had SOC stocks of 18-30 t C ha(-1). Conversion of natural vegetation to annual crops led to the greatest soil C losses. Simulations suggest that soil C losses remain substantial throughout the modelling period of 1990-2030. All three methods involved in the GEFSOC System estimated that there would be a net loss of soil C between 2000 and 2030 in Kenya. The decline was more marked with RothC than with Century or the IPCC method. In non-hydric soils the SOC change rates were more pronounced in high sandy soils compared to high clay soils in most land use systems. (C) 2007 Elsevier B.V. All rights reserved.

Mineralised organic remains from cesspits at the Roman town of Silchester: Processes and preservation

Mineralised organic remains (including apple pips and cereal grains) collected during the ongoing excavations of Insula IX at the Roman town of Silchester, Hampshire have been analysed by a combination of SEM-EDX, powder XRD and IR spectroscopy. The experiments included mapping experiments using spatially resolved versions of each technique. IR and powder XRD mapping have been carried out utilising the synchrotron source at The Daresbury Laboratory oil stations 11.1 and 9.6. It is concluded that these samples are preserved by rapid mineralisation in the carbonate-substituted calcium phosphate mineral, dahllite. The rapid mineralisation leads to excellent preservation of the samples and a small crystal size. The value of IR spectroscopy in studying materials like this where the crystal size is small is demonstrated. A comparison is made between the excellent preservation seen in this context and the much poorer preservation of mineralised remains seen in Context 5276 or Cesspit 5251. Comments on the possible mechanism of mineralisation of these samples are made. (C) 2008 Elsevier B.V.. All rights reserved.