Recovery based on plot experiments is a poor predictor of landscape-level population impacts of agricultural pesticides

Current European Union regulatory risk assessment allows application of pesticides provided that recovery of nontarget arthropods in-crop occurs within a year. Despite the long-established theory of source-sink dynamics, risk assessment ignores depletion of surrounding populations and typical field trials are restricted to plot-scale experiments. In the present study, the authors used agent-based modeling of 2 contrasting invertebrates, a spider and a beetle, to assess how the area of pesticide application and environmental half-life affect the assessment of recovery at the plot scale and impact the population at the landscape scale. Small-scale plot experiments were simulated for pesticides with different application rates and environmental half-lives. The same pesticides were then evaluated at the landscape scale (10 km × 10 km) assuming continuous year-on-year usage. The authors' results show that recovery time estimated from plot experiments is a poor indicator of long-term population impact at the landscape level and that the spatial scale of pesticide application strongly determines population-level impact. This raises serious doubts as to the utility of plot-recovery experiments in pesticide regulatory risk assessment for population-level protection. Predictions from the model are supported by empirical evidence from a series of studies carried out in the decade starting in 1988. The issues raised then can now be addressed using simulation. Prediction of impacts at landscape scales should be more widely used in assessing the risks posed by environmental stressors.

Landscape gene flow, coexistence and threshold effect: The case of genetically modified herbicide tolerant oilseed rape (Brassica napus)

Globally there have been a number of concerns about the development of genetically modified crops many of which relate to the implications of gene flow at various levels. In Europe these concerns have led the European Union (EU) to promote the concept of 'coexistence' to allow the freedom to plant conventional and genetically modified (GM) varieties but to minimise the presence of transgenic material within conventional crops. Should a premium for non-GM varieties emerge on the market, the presence of transgenes would generate a 'negative externality' to conventional growers. The establishment of maximum tolerance level for the adventitious presence of GM material in conventional crops produces a threshold effect in the external costs. The existing literature suggests that apart from the biological characteristics of the plant under consideration (e.g. self-pollination rates, entomophilous species, anemophilous species, etc.), gene flow at the landscape level is affected by the relative size of the source and sink populations and the spatial arrangement of the fields in the landscape. In this paper, we take genetically modified herbicide tolerant oilseed rape (GM HT OSR) as a model crop. Starting from an individual pollen dispersal function, we develop a spatially explicit numerical model in order to assess the effect of the size of the source/sink populations and the degree of spatial aggregation on the extent of gene flow into conventional OSR varieties under two alternative settings. We find that when the transgene presence in conventional produce is detected at the field level, the external cost will increase with the size of the source area and with the level of spatial disaggregation. on the other hand when the transgene presence is averaged among all conventional fields in the landscape (e.g. because of grain mixing before detection), the external cost will only depend on the relative size of the source area. The model could readily be incorporated into an economic evaluation of policies to regulate adoption of GM HT OSR. (c) 2007 Elsevier B.V. All rights reserved.

Export of dissolved organic carbon from an upland peatland during storm events: implications for flux estimates

Most of the dissolved organic carbon (DOC) exported from catchments is transported during storm events. Accurate assessments of DOC fluxes are essential to understand long-term trends in the transport of DOC from terrestrial to aquatic systems, and also the loss of carbon from peatlands to determine changes in the source/sink status of peatland carbon stores. However, many long-term monitoring programmes collect water samples at a frequency (e.g. weekly/monthly) less than the time period of a typical storm event (typically <1–2 days). As widespread observations in catchments dominated by organo-mineral soils have shown that both concentration and flux of DOC increases during storm events, lower frequency monitoring could result in substantial underestimation of DOC flux as the most dynamic periods of transport are missed. However, our intensive monitoring study in a UK upland peatland catchment showed a contrasting response to these previous studies. Our results showed that (i) DOC concentrations decreased during autumn storm events and showed a poor relationship with flow during other seasons; and that (ii) this decrease in concentrations during autumn storms caused DOC flux estimates based on weekly monitoring data to be over-estimated, rather than under-estimated, because of over rather than under estimation of the flow-weighted mean concentration used in flux calculations. However, as DOC flux is ultimately controlled by discharge volume, and therefore rainfall, and the magnitude of change in discharge was greater than the magnitude of decline in concentrations, DOC flux increased during individual storm events. The implications for long-term DOC trends are therefore contradictory, as increased rainfall could increase flux but cause an overall decrease in DOC concentrations from peatland streams. Care needs to be taken when interpreting long-term trends in DOC flux rather than concentration; as flux is calculated from discharge estimates, and discharge is controlled by rainfall, DOC flux and rainfall/discharge will always be well correlated.

Issues in the assimilation of the sources of a trace gas by inverse modelling

The problem of reconstructing the (otherwise unknown) source and sink field of a tracer in a fluid is studied by developing and testing a simple tracer transport model of a single-level global atmosphere and a dynamic data assimilation system. The source/sink field (taken to be constant over a 10-day assimilation window) and initial tracer field are analysed together by assimilating imperfect tracer observations over the window. Experiments show that useful information about the source/sink field may be determined from relatively few observations when the initial tracer field is known very accurately a-priori, even when a-priori source/sink information is biased (the source/sink a-priori is set to zero). In this case each observation provides information about the source/sink field at positions upstream and the assimilation of many observations together can reasonably determine the location and strength of a test source.

Characterising phosphorus and nitrate inputs to a rural river using high-frequency concentration-flow relationships

The total reactive phosphorus (TRP) and nitrate concentrations of the River Enborne, southern England, were monitored at hourly interval between January 2010 and December 2011. The relationships between these high-frequency nutrient concentration signals and flow were used to infer changes in nutrient source and dynamics through the annual cycle and each individual storm event, by studying hysteresis patterns. TRP concentrations exhibited strong dilution patterns with increasing flow, and predominantly clockwise hysteresis through storm events. Despite the Enborne catchment being relatively rural for southern England, TRP inputs were dominated by constant, non-rain-related inputs from sewage treatment works (STW) for the majority of the year, producing the highest phosphorus concentrations through the spring–summer growing season. At higher river flows, the majority of the TRP load was derived from within-channel remobilisation of phosphorus from the bed sediment, much of which was also derived from STW inputs. Therefore, future phosphorus mitigation measures should focus on STW improvements. Agricultural diffuse TRP inputs were only evident during storms in the May of each year, probably relating to manure application to land. The nitrate concentration–flow relationship produced a series of dilution curves, indicating major inputs from groundwater and to a lesser extent STW. Significant diffuse agricultural inputs with anticlockwise hysteresis trajectories were observed during the first major storms of the winter period. The simultaneous investigation of high-frequency time series data, concentration–flow relationships and hysteresis behaviour through multiple storms for both phosphorus and nitrate offers a simple and innovative approach for providing new insights into nutrient sources and dynamics.

Living to die and dying to live: the survival strategy behind leaf senescence

Senescence represents the final developmental act of the leaf, during which the leaf cell is dismantled in a coordinated manner to remobilize nutrients and to secure reproductive success. The process of senescence provides the plant with phenotypic plasticity to help it adapt to adverse environmental conditions. Here, we provide a comprehensive overview of the factors and mechanisms that control the onset of senescence. We explain how the competence to senesce is established during leaf development, as depicted by the senescence window model. We also discuss the mechanisms by which phytohormones and environmental stresses control senescence, as well as the impact of source-sink relationships on plant yield and stress tolerance. In addition, we discuss the role of senescence as a strategy for stress adaptation and how crop production and food quality could benefit from engineering or breeding crops with altered onset of senescence.

Linking pesticide exposure and spatial dynamics: An individual-based model of wood mouse (Apodemus sylvaticus) populations in agricultural landscapes

The wood mouse is a common and abundant species in agricultural landscape and is a focal species in pesticide risk assessment. Empirical studies on the ecology of the wood mouse have provided sufficient information for the species to be modelled mechanistically. An individual-based model was constructed to explicitly represent the locations and movement patterns of individual mice. This together with the schedule of pesticide application allows prediction of the risk to the population from pesticide exposure. The model included life-history traits of wood mice as well as typical landscape dynamics in agricultural farmland in the UK. The model obtains a good fit to the available population data and is fit for risk assessment purposes. It can help identify spatio-temporal situations with the largest potential risk of exposure and enables extrapolation from individual-level endpoints to population-level effects. Largest risk of exposure to pesticides was found when good crop growth in the “sink” fields coincided with high “source” population densities in the hedgerows. Keywords: Population dynamics, Pesticides, Ecological risk assessment, Habitat choice, Agent-based model, NetLogo

The role of soil microbes in the global carbon cycle: tracking the below-ground microbial processing of plant-derived carbon for manipulating carbon dynamics in agricultural systems.

It is well known that atmospheric concentrations of carbon dioxide (CO2) (and other greenhouse gases) have increased markedly as a result of human activity since the industrial revolution. It is perhaps less appreciated that natural and managed soils are an important source and sink for atmospheric CO2 and that, primarily as a result of the activities of soil microorganisms, there is a soil-derived respiratory flux of CO2 to the atmosphere that overshadows by tenfold the annual CO2 flux from fossil fuel emissions. Therefore small changes in the soil carbon cycle could have large impacts on atmospheric CO2 concentrations. Here we discuss the role of soil microbes in the global carbon cycle and review the main methods that have been used to identify the microorganisms responsible for the processing of plant photosynthetic carbon inputs to soil. We discuss whether application of these techniques can provide the information required to underpin the management of agro-ecosystems for carbon sequestration and increased agricultural sustainability. We conclude that, although crucial in enabling the identification of plant-derived carbon-utilising microbes, current technologies lack the high-throughput ability to quantitatively apportion carbon use by phylogentic groups and its use efficiency and destination within the microbial metabolome. It is this information that is required to inform rational manipulation of the plant–soil system to favour organisms or physiologies most important for promoting soil carbon storage in agricultural soil.

Assessing nitrogen dynamics in European ecosystems, integrating measurement and modelling: conclusions

This contribution closes this special issue of Hydrology and Earth System Sciences concerning the assessment of nitrogen dynamics in catchments across Europe within a semi-distributed Integrated Nitrogen model for multiple source assessment in Catchments (INCA). New developments in the understanding of the factors and processes determining the concentrations and loads of nitrogen are outlined. The ability of the INCA model to simulate the hydrological and nitrogen dynamics of different European ecosystems is assessed and the results of the first scenario analyses investigating the impacts of deposition, climatic and land-use change on the nitrogen dynamics are summarised. Consideration is given as to how well the model has performed as a generic too] for describing the nitrogen dynamics of European ecosystems across Arctic, Maritime. Continental and Mediterranean climates, its role in new research initiatives and future research requirements.

Towards an improved understanding of the nitrate dynamics in lowland, permeable river-systems: Applications of INCA-N

The Integrated Catchment Model of Nitrogen (INCA-N) was applied to the Lambourn and Pang river-systems to integrate current process-knowledge and available-data to test two hypotheses and thereby determine the key factors and processes controlling the movement of nitrate at the catchment-scale in lowland, permeable river-systems: (i) that the in-stream nitrate concentrations were controlled by two end-members only: groundwater and soil-water, and (ii) that the groundwater was the key store of nitrate in these river-systems. Neither hypothesis was proved true or false. Due to equifinality in the model structure and parameters at least two alternative models provided viable explanations for the observed in-stream nitrate concentrations. One model demonstrated that the seasonal-pattern in the stream-water nitrate concentrations was controlled mainly by the mixing of ground- and soil-water inputs. An alternative model demonstrated that in-stream processes were important. It is hoped further measurements of nitrate concentrations made in the catchment soil- and ground-water and in-stream may constrain the model and help determine the correct structure, though other recent studies suggest that these data may serve only to highlight the heterogeneity of the system. Thus when making model-based assessments and forecasts it is recommend that all possible models are used, and the range of forecasts compared. In this study both models suggest that cereal production contributed approximately 50% the simulated in-stream nitrate toad in the two catchments, and the point-source contribution to the in-stream load was minimal. (c) 2006 Elsevier B.V. All rights reserved.

Assessing nitrogen dynamics in European ecosystems, integrating measurement and modelling: conclusions

This contribution closes this special issue of Hydrology and Earth System Sciences concerning the assessment of nitrogen dynamics in catchments across Europe within a semi-distributed Integrated Nitrogen model for multiple source assessment in Catchments (INCA). New developments in the understanding of the factors and processes determining the concentrations and loads of nitrogen are outlined. The ability of the INCA model to simulate the hydrological and nitrogen dynamics of different European ecosystems is assessed and the results of the first scenario analyses investigating the impacts of deposition, climatic and land-use change on the nitrogen dynamics are summarised. Consideration is given as to how well the model has performed as a generic too] for describing the nitrogen dynamics of European ecosystems across Arctic, Maritime. Continental and Mediterranean climates, its role in new research initiatives and future research requirements.

Robust dynamics of Amazon dieback to climate change with perturbed ecosystem model parameters

Climate change science is increasingly concerned with methods for managing and integrating sources of uncertainty from emission storylines, climate model projections, and ecosystem model parameterizations. In tropical ecosystems, regional climate projections and modeled ecosystem responses vary greatly, leading to a significant source of uncertainty in global biogeochemical accounting and possible future climate feedbacks. Here, we combine an ensemble of IPCC-AR4 climate change projections for the Amazon Basin (eight general circulation models) with alternative ecosystem parameter sets for the dynamic global vegetation model, LPJmL. We evaluate LPJmL simulations of carbon stocks and fluxes against flux tower and aboveground biomass datasets for individual sites and the entire basin. Variability in LPJmL model sensitivity to future climate change is primarily related to light and water limitations through biochemical and water-balance-related parameters. Temperature-dependent parameters related to plant respiration and photosynthesis appear to be less important than vegetation dynamics (and their parameters) for determining the magnitude of ecosystem response to climate change. Variance partitioning approaches reveal that relationships between uncertainty from ecosystem dynamics and climate projections are dependent on geographic location and the targeted ecosystem process. Parameter uncertainty from the LPJmL model does not affect the trajectory of ecosystem response for a given climate change scenario and the primary source of uncertainty for Amazon 'dieback' results from the uncertainty among climate projections. Our approach for describing uncertainty is applicable for informing and prioritizing policy options related to mitigation and adaptation where long-term investments are required.

Free atmospheric CO2 enrichment increased above ground biomass but did not affect symbiotic N2-fixation and soil carbon dynamics in a mixed deciduous stand in Wales

Through increases in net primary production (NPP), elevated CO2 is hypothesizes to increase the amount of plant litter entering the soil. The fate of this extra carbon on the forest floor or in mineral soil is currently not clear. Moreover, increased rates of NPP can be maintained only if forests can escape nitrogen limitation. In a Free atmospheric CO2 Enrichment (FACE) experiment near Bangor, Wales, 4 ambient CO2 and 4 FACE plots were planted with patches of Betula pendula, Alnus glutinosa and Fagus sylvatica on a former arable field. Four years after establishment, only a shallow L forest floor litter layer had formed due to intensive bioturbation. Total soil C and N contents increased irrespective of treatment and species as a result of afforestation. We could not detect an additional C sink in the soil, nor were soil C stabilization processes affected by FACE. We observed a decrease of leaf N content in Betula and Alnus under FACE, while the soil C/N ratio decreased regardless of CO2 treatment. The ratio of N taken up from the soil and by N2-fixation in Alnus was not affected by FACE. We infer that increased nitrogen use efficiency is the mechanism by which increased NPP is sustained under elevated CO2 at this site.