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Data Modelling (data + modelling)

Distribution by Scientific Domains

Earth and Environmental Science	60%

Selected Abstracts

Resolving the biodiversity paradox

ECOLOGY LETTERS, Issue 8 2007
James S. Clark
Abstract The paradox of biodiversity involves three elements, (i) mathematical models predict that species must differ in specific ways in order to coexist as stable ecological communities, (ii) such differences are difficult to identify, yet (iii) there is widespread evidence of stability in natural communities. Debate has centred on two views. The first explanation involves tradeoffs along a small number of axes, including ,colonization-competition', resource competition (light, water, nitrogen for plants, including the ,successional niche'), and life history (e.g. high-light growth vs. low-light survival and few large vs. many small seeds). The second view is neutrality, which assumes that species differences do not contribute to dynamics. Clark et al. (2004) presented a third explanation, that coexistence is inherently high dimensional, but still depends on species differences. We demonstrate that neither traditional low-dimensional tradeoffs nor neutrality can resolve the biodiversity paradox, in part by showing that they do not properly interpret stochasticity in statistical and in theoretical models. Unless sample sizes are small, traditional data modelling assures that species will appear different in a few dimensions, but those differences will rarely predict coexistence when parameter estimates are plugged into theoretical models. Contrary to standard interpretations, neutral models do not imply functional equivalence, but rather subsume species differences in stochastic terms. New hierarchical modelling techniques for inference reveal high-dimensional differences among species that can be quantified with random individual and temporal effects (RITES), i.e. process-level variation that results from many causes. We show that this variation is large, and that it stands in for species differences along unobserved dimensions that do contribute to diversity. High dimensional coexistence contrasts with the classical notions of tradeoffs along a few axes, which are often not found in data, and with ,neutral models', which mask, rather than eliminate, tradeoffs in stochastic terms. This mechanism can explain coexistence of species that would not occur with simple, low-dimensional tradeoff scenarios. [source]

2D data modelling by electrical resistivity tomography for complex subsurface geology

GEOPHYSICAL PROSPECTING, Issue 2 2006
E. Cardarelli
ABSTRACT A new tool for two-dimensional apparent-resistivity data modelling and inversion is presented. The study is developed according to the idea that the best way to deal with ill-posedness of geoelectrical inverse problems lies in constructing algorithms which allow a flexible control of the physical and mathematical elements involved in the resolution. The forward problem is solved through a finite-difference algorithm, whose main features are a versatile user-defined discretization of the domain and a new approach to the solution of the inverse Fourier transform. The inversion procedure is based on an iterative smoothness-constrained least-squares algorithm. As mentioned, the code is constructed to ensure flexibility in resolution. This is first achieved by starting the inversion from an arbitrarily defined model. In our approach, a Jacobian matrix is calculated at each iteration, using a generalization of Cohn's network sensitivity theorem. Another versatile feature is the issue of introducing a priori information about the solution. Regions of the domain can be constrained to vary between two limits (the lower and upper bounds) by using inequality constraints. A second possibility is to include the starting model in the objective function used to determine an improved estimate of the unknown parameters and to constrain the solution to the above model. Furthermore, the possibility either of defining a discretization of the domain that exactly fits the underground structures or of refining the mesh of the grid certainly leads to more accurate solutions. Control on the mathematical elements in the inversion algorithm is also allowed. The smoothness matrix can be modified in order to penalize roughness in any one direction. An empirical way of assigning the regularization parameter (damping) is defined, but the user can also decide to assign it manually at each iteration. An appropriate tool was constructed with the purpose of handling the inversion results, for example to correct reconstructed models and to check the effects of such changes on the calculated apparent resistivity. Tests on synthetic and real data, in particular in handling indeterminate cases, show that the flexible approach is a good way to build a detailed picture of the prospected area. [source]

GPR microwave tomography for diagnostic analysis of archaeological sites: the case of a highway construction in Pontecagnano (Southern Italy)

ARCHAEOLOGICAL PROSPECTION, Issue 3 2009
R. Castaldo
Abstract Interpretation of ground-penetrating radar (GPR) data usually involves data processing similar to that used for seismic data analysis, including also migration techniques. Alternatively, in the past few years, microwave tomographic approaches exploiting more accurate models of the electromagnetic scattering have gained interest, owing to their capability of providing accurate results and stable images. Within this framework, this paper deals with the application of a microwave tomography approach, based on the Born Approximation and working in the frequency domain. The case study is a survey performed during the realization of the third lane of the most important highway in southern Italy (the Salerno-Reggio Calabria, near Pontecagnano, Italy). It is shown that such an inversion approach produces well-focused images, from which buried structures can be more easily identified by comparison to traditional radar images. Moreover, the visualization of the reconstruction results is further enhanced through a three-dimensional volumetric rendering of the surveyed region, simply achieved by staggering the reconstructed GPR two-dimensional profiles. By means of this rendering it is possible to follow the spatial continuity of the buried structures in the subsurface thus obtaining a very effective geometrical characterization. The results are very useful in our case where, due to important civil engineering works, a fast diagnosis of the archaeological situation was needed. The quality of our GPR data modelling was confirmed by a test excavation, where a corner of a building and the eastern part of another house, with its courtyard, were found at the depth and horizontal position suggested by our interpretation. Copyright © 2009 John Wiley & Sons, Ltd. [source]

Modelling Tree Roots in Mixed Forest Stands by Inhomogeneous Marked Gibbs Point Processes

BIOMETRICAL JOURNAL, Issue 3 2009
Stefanie Eckel
Abstract The aim of the paper is to apply point processes to root data modelling. We propose a new approach to parametric inference when the data are inhomogeneous replicated marked point patterns. We generalize Geyer's saturation point process to a model, which combines inhomogeneity, marks and interaction between the marked points. Furthermore, the inhomogeneity influences the definition of the neighbourhood of points. Using the maximum pseudolikelihood method, this model is then fitted to root data from mixed stands of Norway spruce (Picea abies (L.) Karst.) and European beech (Fagus sylvatica L.) to quantify the degree of root aggregation in such mixed stands. According to the analysis there is no evidence that the two root systems are not independent. [source]