Spatial scales of interactions among bacteria and between bacteria and the leaf surface.

Microbial life on plant leaves is characterized by a multitude of interactions between leaf colonizers and their environment. While the existence of many of these interactions has been confirmed, their spatial scale or reach often remained unknown. In this study, we applied spatial point pattern analysis to 244 distribution patterns of Pantoea agglomerans and Pseudomonas syringae on bean leaves. The results showed that bacterial colonizers of leaves interact with their environment at different spatial scales. Interactions among bacteria were often confined to small spatial scales up to 5-20 μm, compared to interactions between bacteria and leaf surface structures such as trichomes which could be observed in excess of 100 μm. Spatial point-pattern analyses prove a comprehensive tool to determine the different spatial scales of bacterial interactions on plant leaves and will help microbiologists to better understand the interplay between these interactions

Dundee Discussion Papers in Economics 253:Spatial Interactions in Hedonic Pricing Models: The Urban Housing Market of Aveiro, Portugal

Spatial heterogeneity, spatial dependence and spatial scale constitute key features of spatial analysis of housing markets. However, the common practice of modelling spatial dependence as being generated by spatial interactions through a known spatial weights matrix is often not satisfactory. While existing estimators of spatial weights matrices are based on repeat sales or panel data, this paper takes this approach to a cross-section setting. Specifically, based on an a priori definition of housing submarkets and the assumption of a multifactor model, we develop maximum likelihood methodology to estimate hedonic models that facilitate understanding of both spatial heterogeneity and spatial interactions. The methodology, based on statistical orthogonal factor analysis, is applied to the urban housing market of Aveiro, Portugal at two different spatial scales

Structural Interactions in Spatial Panels

Until recently, much effort has been devoted to the estimation of panel data regression models without adequate attention being paid to the drivers of diffusion and interaction across cross section and spatial units. We discuss some new methodologies in this emerging area and demonstrate their use in measurement and inferences on cross section and spatial interactions. Specifically, we highlight the important dis?tinction between spatial dependence driven by unobserved common factors and those based on a spatial weights matrix. We argue that, purely factor driven models of spatial dependence may be somewhat inadequate because of their connection with the exchangeability as?sumption. Limitations and potential enhancements of the existing methods are discussed, and several directions for new research are highlighted.Cross Sectional and Spatial Dependence, Spatial Weights Matrix, Interactions and Diffusion, Monetary Policy Committee, Generalised Method of Moments.

Can Ecological Interactions be Inferred from Spatial Data?

The characterisation and quantication of ecological interactions, and the construction of species distributions and their associated ecological niches, is of fundamental theoretical and practical importance. In this paper we give an overview of a Bayesian inference framework, developed over the last 10 years, which, using spatial data, offers a general formalism within which ecological interactions may be characterised and quantied. Interactions are identied through deviations of the spatial distribution of co-occurrences of spatial variables relative to a benchmark for the non-interacting system, and based on a statistical ensemble of spatial cells. The formalism allows for the integration of both biotic and abiotic factors of arbitrary resolution. We concentrate on the conceptual and mathematical underpinnings of the formalism, showing how, using the Naive Bayes approximation, it can be used to not only compare and contrast the relative contribution from each variable, but also to construct species distributions and niches based on arbitrary variable type. We show how the formalism can be used to quantify confounding and therefore help disentangle the complex causal chains that are present in ecosystems. We also show species distributions and their associated niches can be used to infer standard "micro" ecological interactions, such as predation and parasitism. We present several representative use cases that validate our framework, both in terms of being consistent with present knowledge of a set of known interactions, as well as making and validating predictions about new, previously unknown interactions in the case of zoonoses

Multipolar Interactions in the Anderson Lattice with Orbital Degeneracy

Microscopic investigation is performed for intersite multipolar interactions in the orbitally degenerate Anderson lattice, with CeB$_6$ taken as an exemplary target. In addition to the $f^0$ intermediate state, $f^2$ Hund's-rule ground states are included as intermediate states for the interactions. The conduction-band states are taken as plane waves and the hybridization as spherically symmetric. The spatial dependences of multipolar interactions are given by the relative weight of partial wave components along the pair of sites. It is clarified how the the anisotropy arises in the interactions depending on the orbital degeneracy and the spatial configuration. The stability of the $\Gamma_5$ antiferro-quadrupole order in the phase II of CeB$_6$ is consistent with our model. Moreover, the pseudo-dipole interactions follow a tendency required by the phenomenological model for the phase III.Comment: 30 pages, 4 figure

Segregation and Strategic Neighborhood Interaction

We introduce social interactions into the Schelling model of residential choice. These social interactions take the form of a Prisoner's Dilemma game played with neighbors. First, we study the Schelling model over a wide range of utility functions and then proceed to study a spatial Prisoner's Dilemma model. These models provide a benchmark for studying a combined model with preferences over like-typed neighbors and payoffs in the spatial Prisoner's Dilemma game. We study this combined model both analytically and using agent-based simulations. We find that the presence of these additional social interactions may increase or decrease segregation compared to the standard Schelling model. If the social interactions result in cooperation then segregation is reduced, otherwise it is increased.Schelling Tipping Model, Spatial Prisoner's Dilemma, Cooperation, Segregation