Local Seafood Availability in San Diego, California Seafood Markets

Like many developed coastal cities, San Diego, California has strong geographic and recreational ties to the adjacent ocean, but weak culinary ones. Less than 10% of the seafood consumed in the U.S., and San Diego in particular, is domestic. The popularity and abundance of farmers’ markets and other local markets in San Diego indicates an interest among producers and the public alike in cultivating local, diverse food systems, but this trend has been slower to catch on for seafood. The goal of this project was, therefore, to define and begin to understand the influences on the patterns of locally sourced, domestic seafood availability in San Diego. This study focused on seafood availability in seafood markets including researching market websites and contacting seafood counter managers to determine the general frequency (consistent, occasional, none) at which the markets sold seafood produced by San Diego fishermen or aquafarmers. Seafood market locations were mapped, and demographic and spatial information was gathered for each market’s zip code. The results of the study revealed that only 8% of San Diego’s 86 seafood markets consistently carried San Diego-sourced seafood, and 14% of markets carried it on occasion. Increased density of these local seafood markets was correlated with proximity to the coast, with almost 80% of the markets located within 2 km of the coast. Neither per capita income nor racial diversity was correlated with local seafood market density, indicating that factors contributing to coastal isolation matter more than wealth or diversity in determining where local seafood is sold. The geographic disparity in local seafood availability may be due to a variety of factors, including a small fishing fleet, prevalence of imported seafood, limited waterfront and urban infrastructure needed to support a local seafood system, and a lack of public awareness about local fisheries. Information gleaned from this study can inform further investigation into the influences on local, equitable seafood systems, as well as help consumers, producers and marketers to make informed decisions about seafood purchases and marketing efforts.

Bayes quadratic unbiased estimator of spatial covariance parameters

This work presents Bayes invariant quadratic unbiased estimator, for short BAIQUE. Bayesian approach is used here to estimate the covariance functions of the regionalized variables which appear in the spatial covariance structure in mixed linear model. Firstly a brief review of spatial process, variance covariance components structure and Bayesian inference is given, since this project deals with these concepts. Then the linear equations model corresponding to BAIQUE in the general case is formulated. That Bayes estimator of variance components with too many unknown parameters is complicated to be solved analytically. Hence, in order to facilitate the handling with this system, BAIQUE of spatial covariance model with two parameters is considered. Bayesian estimation arises as a solution of a linear equations system which requires the linearity of the covariance functions in the parameters. Here the availability of prior information on the parameters is assumed. This information includes apriori distribution functions which enable to find the first and the second moments matrix. The Bayesian estimation suggested here depends only on the second moment of the prior distribution. The estimation appears as a quadratic form y'Ay , where y is the vector of filtered data observations. This quadratic estimator is used to estimate the linear function of unknown variance components. The matrix A of BAIQUE plays an important role. If such a symmetrical matrix exists, then Bayes risk becomes minimal and the unbiasedness conditions are fulfilled. Therefore, the symmetry of this matrix is elaborated in this work. Through dealing with the infinite series of matrices, a representation of the matrix A is obtained which shows the symmetry of A. In this context, the largest singular value of the decomposed matrix of the infinite series is considered to deal with the convergence condition and also it is connected with Gerschgorin Discs and Poincare theorem. Then the BAIQUE model for some experimental designs is computed and compared. The comparison deals with different aspects, such as the influence of the position of the design points in a fixed interval. The designs that are considered are those with their points distributed in the interval [0, 1]. These experimental structures are compared with respect to the Bayes risk and norms of the matrices corresponding to distances, covariance structures and matrices which have to satisfy the convergence condition. Also different types of the regression functions and distance measurements are handled. The influence of scaling on the design points is studied, moreover, the influence of the covariance structure on the best design is investigated and different covariance structures are considered. Finally, BAIQUE is applied for real data. The corresponding outcomes are compared with the results of other methods for the same data. Thereby, the special BAIQUE, which estimates the general variance of the data, achieves a very close result to the classical empirical variance.

Assessing the users’ need for a spatial decision support system of smallholder farming in Kenya

Accurate data of the natural conditions and agricultural systems with a good spatial resolution are a key factor to tackle food insecurity in developing countries. A broad variety of approaches exists to achieve precise data and information about agriculture. One system, especially developed for smallholder agriculture in East Africa, is the Farm Management Handbook of Kenya. It was first published in 1982/83 and fully revised in 2012, now containing 7 volumes. The handbooks contain detailed information on climate, soils, suitable crops and soil care based on scientific research results of the last 30 years. The density of facts leads to time consuming extraction of all necessary information. In this study we analyse the user needs and necessary components of a system for decision support for smallholder farming in Kenya based on a geographical information system (GIS). Required data sources were identified, as well as essential functions of the system. We analysed the results of our survey conducted in 2012 and early 2013 among agricultural officers. The monitoring of user needs and the problem of non-adaptability of an agricultural information system on the level of extension officers in Kenya are the central objectives. The outcomes of the survey suggest the establishment of a decision support tool based on already available open source GIS components. The system should include functionalities to show general information for a specific location and should provide precise recommendations about suitable crops and management options to support agricultural guidance on farm level.