Root system traits are important in view of current challenges such as sustainable crop production with reduced fertilizer input or in resource-limited environments. We present a novel approach for recovering root architectural parameters based on imageanalysis techniques. It is based on a graph representation of the segmented and skeletonized image of the root system, where individual roots are tracked in a fully automated way. Using a dynamic root architecture model for deciding whether a specific path in the graph is likely to represent a root helps to distinguish root overlaps from branches and favors the analysis of root development over a sequence of images. After the root tracking step, global traits such as topological characteristics as well as root architectural parameters are computed. Analysis of neutron radiographic root system images of lupine (Lupinus albus) grown in mesocosms filled with sandy soil results in a set of root architectural parameters. They are used to simulate the dynamic development of the root system and to compute the corresponding root length densities in the mesocosm. The graph representation of the root system provides global information about connectivity inside the graph. The underlying root growth model helps to determine which path inside the graph is most likely for a given root. This facilitates the systematic investigation of root architectural traits, in particular with respect to the parameterization of dynamic root architecture models.

Soils and sediments polluted with crude oil are of major environmental concern on various contaminated sites. Outdoors pot experiments were conducted to test the phytodegradation potential of common reed (Phragmites australis) and poplar (Populus nigra × maximowiczii) in fertilised and non-fertilised control treatments. Two topsoils (E, G) of different texture were mixed with crude oil. Soil analysis included hydrocarbon (HC) measurements, detection of labile phosphorus and mineralised nitrogen as well as dehydrogenase activity. Increased HC degradation by native soil biota was clearly related to higher P availability in soil G and to fertilisation in soil E. Except of the non-fertilised common reed treatment, plants did not enhance crude oil degradation. We found even inhibited degradation of high molecular weight HC in the presence of plants together with declining labile phosphorous concentrations due to planting on soil E. Native soil biota were able to use the whole range of crude oil compounds (C 10 to C 60 ) as a carbon source in the presence of sufficient nutrient concentrations in soil. This study is the first to show that reduced HC degradation in the higher molecular weight crude oil fraction (C 20 to C 40 ) is likely to be a consequence of decreased phosphorus availability for microorganisms in the plant rhizosphere.

SummaryWe studied the variation of soil properties on a six-ha artificial catchment constructed near Cottbus, Germany, to investigate processes of initial ecosystem genesis. We wanted to see whether spatial auto-correlation patterns could be identified three years after site construction. Topsoil was sampled at 192 locations using a balanced nested design involving six spatial scales (0.2 m to >60 m) and analysed for particle size, organic matter content, pH, soluble P, and various fractions of selected metals. Variance components were estimated by residual maximum likelihood. The uncertainty of variance estimates was characterized by the Fisher Information matrix and likelihood joint confidence regions. The latter approach was used for the first time to characterize uncertainties of variance estimates in spatial nested sampling. Likelihood ratio tests showed that all variables were spatially auto-correlated, but the allocation of the variance to specific spatial scales was highly uncertain. For most variables, at least one variance component could not be estimated precisely because the profile likelihood was either flat or the maximum lay on the boundary of the parameter space. Uncertainty estimates derived from the Fisher Information either could not be computed or were unrealistic in these cases. Likelihood joint confidence regions gave more realistic uncertainty estimates. Joint confidence regions for accumulated variance components showed that the shape of the estimated variograms was poorly defined for most variables. Simulations indicated that poor identification of variance components might be a general problem of nested sampling surveys, which has been under-estimated in the past. Hence, our work provides some incentive for re-examining the statistical properties of the methodology.

Aims and Background Many plants preferentially grow roots into P-enriched soil patches, but little is known about how the presence of arbuscular mycorrhizal fungi (AMF) affects this response. Methods Lotus japonicus (L.) was grown in a low-P soil with (a) no additional P, (b) homogeneous P (28 mg pot −1), (c) low heterogeneous P (9.3 mg pot −1), and (d) high heterogeneous P (28 mg pot −1). Each P treatment was combined with one of three mycorrhiza treatments: no mycorrhizae, Glomus intraradices, indigenous AMF. Real-time PCR was used to assess the abundance of G. intraradices and the indigeneous AMF G. mosseae and G. claroideum. Results Mycorrhization and P fertilization strongly increased plant growth. Homogeneous P supply enhanced growth in both mycorrhizal treatments, while heterogeneous P fertilization increased biomass production only in treatments with indigenous AMF inoculation. Preferential root allocation into P-enriched soil was significant only in absence of AMF. The abundance of AMF species was similar in P-enriched and unfertilized soil patches. Conclusion Mycorrhization may completely override preferential root growth responses of plants to Ppatchiness in soil. The advantage of this effect for the plants is to give roots more freedom to forage for other resources in demand for growth and to adapt to variable soil conditions.