Spatial variability of soil phosphorus in relation to the topographic index and critical source areas: sampling for assessing risk to water quality

A measure of soil P status in agricultural soils is generally required for assisting with prediction of potential P loss from agricultural catchments and assessing risk for water quality. The objectives of this paper are twofold: (i) investigating the soil P status, distribution, and variability, both spatially and with soil depth, of two different first-order catchments; and (ii) determining variation in soil P concentration in relation to catchment topography (quantified as the "topographic index") and critical source areas (CSAs). The soil P measurements showed large spatial variability, not only between fields and land uses, but also within individual fields and in part was thought to be strongly influenced by areas where cattle tended to congregate and areas where manure was most commonly spread. Topographic index alone was not related to the distribution of soil P, and does not seem to provide an adequate indicator for CSAs in the study catchments. However, CSAs may be used in conjunction with soil P data for help in determining a more "effective" catchment soil P status. The difficulties in defining CSAs a priori, particularly for modeling and prediction purposes, however, suggest that other more "integrated" measures of catchment soil P status, such as baseflow P concentrations or streambed sediment P concentrations, might be more useful. Since observed soil P distribution is variable and is also difficult to relate to nationally available soil P data, any assessment of soil P status for determining risk of P loss is uncertain and problematic, given other catchment physicochemical characteristics and the sampling strategy employed.     

Multiple sources of predictive uncertainty in modeled estimates of net ecosystem CO2 exchange

Net ecosystem CO₂ exchange (NEE) is typically measured directly by eddy covariance towers or is estimated by ecosystem process models, yet comparisons between the data obtained by these two methods can show poor correspondence. There are three potential explanations for this discrepancy. First, estimates of NEE as measured by the eddy-covariance technique are laden with uncertainty and can potentially provide a poor baseline for models to be tested against. Second, there could be fundamental problems in model structure that prevent an accurate simulation of NEE. Third, ecosystem process models are dependent on ecophysiological parameter sets derived from field measurements in which a single parameter for a given species can vary considerably. The latter problem suggests that with such broad variation among multiple inputs, any ecosystem modeling scheme must account for the possibility that many combinations of apparently feasible parameter values might not allow the model to emulate the observed NEE dynamics of a terrestrial ecosystem, as well as the possibility that there may be many parameter sets within a particular model structure that can successfully reproduce the observed data. We examined the extent to which these three issues influence estimates of NEE in a widely used ecosystem process model, Biome-BGC, by adapting the generalized likelihood uncertainty estimation (GLUE) methodology. This procedure involved 400,000 model runs, each with randomly generated parameter values from a uniform distribution based on published parameter ranges, resulting in estimates of NEE that were compared to daily NEE data from young and mature Ponderosa pine stands at Metolius, Oregon. Of the 400,000 simulations run with different parameter sets for each age class (800,000 total), over 99% of the simulations underestimated the magnitude of net ecosystem CO₂ exchange, with only 4.07% and 0.045% of all simulations providing satisfactory simulations of the field data for the young and mature stands, even when uncertainties in eddy-covariance measurements are accounted for. Results indicate fundamental shortcomings in the ability of this model to produce realistic carbon flux data over the course of forest development, and we suspect that much of the mismatch derives from an inability to realistically model ecosystem respiration. However, difficulties in estimating historic climate data are also a cause for model-data mismatch, particularly in a highly ecotonal region such as central Oregon. This latter difficulty may be less prevalent in other ecosystems, but it nonetheless highlights a challenge in trying to develop a dynamic representation of the terrestrial biosphere.     

Testing a new model of aphid abundance with sedentary and non-sedentary predators

Aphid population dynamics has been thoroughly investigated, especially in tree-dwelling aphids. Among the controls of the aphid rate of increase are the negative effects of antagonists, the positive effects of mutualists, the density-dependence of the aphid dynamics, and the non-stationary quality of plant tissues. Here we present a mechanistic model of aphid growth that considers most of these governing factors using a simple formulation. What is new in this model is that it considers two kinds of antagonists. The first kind is a guild of aphid predator specialists that includes ladybirds (Coleoptera: Coccinellidae), but also species of some families of Hemiptera, Diptera, and Neuroptera. The second kind of antagonists consists of omnivores or generalist predators and in this particular setting is exemplified by the European earwig Forficula auricularia (Dermaptera: Forficulidae). The model developed here compared the effects of these two different kinds of aphid predators, the second one always at the site (sedentary predators) and the first one that arrives in important numbers only once the aphid population has already developed to some degree (non-sedentary predators). Multiple model parameter sets, representing different hypotheses about controls on aphid populations, were evaluated within the Generalised Likelihood Uncertainty Estimation (GLUE) methodology. The model correctly reproduced the experimental data obtained in an organic citrus grove showing the important effect that sedentary predators as earwigs can have on the aphid populations. Low densities of sedentary predators or even low predation rates can have a disproportionate effect on the final aphid density, as they prey on small populations, when the per capita effect on the aphid population is higher. During the main spring peak of aphids the role of non-sedentary predators is secondary, as they track the aphid density rather than control it. However, these non-sedentary predators are important within the proposed model to keep the second autumn peak of aphids at low values.     

Controls on catchment-scale patterns of phosphorus in soil, streambed sediment, and stream water

Many models of phosphorus (P) transfer at the catchment scale rely on input from generic databases including, amongst others, soil and land use maps. Spatially detailed geochemical data sets have the potential to improve the accuracy of the input parameters of catchment-scale nutrient transfer models. Furthermore, they enable the assessment of the utility of available, generic spatial data sets for the modeling and prediction of soil nutrient status and nutrient transfer at the catchment scale. This study aims to quantify the unique and joint contribution of soil and sediment properties, land cover, and point-source emissions to the spatial variation of P concentrations in soil, streambed sediments, and stream water at the scale of a medium-sized catchment. Soil parent material and soil chemical properties were identified as major factors controlling the catchment-scale spatial variation in soil total P and Olsen P concentrations. Soil type and land cover as derived from the generic spatial database explain 33.7% of the variation in soil total P concentrations and 17.4% of the variation in Olsen P concentrations. Streambed P concentrations are principally related to the major element concentrations in streambed sediment and P delivery from the hillslopes due to sediment erosion. During base flow conditions, the total phosphorus (<0.45 microm) concentrations in stream water are mainly controlled by the concentrations of P and the major elements in the streambed sediment.     

Developing a translational discourse to communicate uncertainty in flood risk between science and the practitioner

The language and tools of risk and uncertainty estimation in flood risk management (FRM) are rarely optimized for the extant communication challenge. This paper develops the rationale for a pragmatic semiotics of risk communication between scientists developing flood models and forecasts and those professional groups who are the receptors for flood risk estimates and warnings in the UK. The current barriers to effective communication and the constraints involved in the formation of a communication language are explored, focusing on the role of the professional's agenda or "mission" in creating or reducing those constraints. The tools available for the development of this discourse, for both flood warnings in real time and generalized FRM communications, are outlined. It is argued that the contested ownership of the articulation of uncertainties embedded in flood risk communications could be reduced by the development of a formally structured translational discourse between science and professionals in FRM, through which process "codes of practice" for uncertainty estimation in different application areas can be developed. Ways in which this might take place in an institutional context are considered.