Risk Factors Associated With the Prevalence of Tuberculosis-Like Lesions in Fenced Wild Boar and Red Deer in South Central Spain

In recent decades the management of large game mammals has become increasingly intensive in south central Spain (SCS), resulting in complex epidemiological scenarios for disease maintenance, and has probably impeded schemes to eradicate tuberculosis (TB) in domestic livestock. We conducted an analysis of risk factors which investigated associations between the pattern of tuberculosis-like lesions (TBL) in wild boar (Sus scrofa) and red deer (Cervus elaphus) across 19 hunting estates from SCS and an extensive set of variables related to game management, land use and habitat structure. The aggregation of wild boar at artificial watering sites was significantly associated with an increasing risk of detecting TBL in both species, which probably relates to enhanced opportunities for transmission. Aggregation of wild boar at feeding sites was also associated with increased risks of TBL in red deer. Hardwood Quercus spp. forest availability was marginally associated with an increased risk of TB in both species, whereas scrubland cover was associated with a reduced individual risk of TBL in the wild boar. It is concluded that management practices that encourage the aggregation of hosts, and some characteristics of Mediterranean habitats could increase the frequency and probability of both direct and indirect transmission of TB. These findings are of concern for both veterinary and public health authorities, and reveal tuberculosis itself as a potential limiting factor for the development and sustainability of such intensive game management systems in Spanish Mediterranean habitats.

Taking account of dependent species in management of the Southern Ocean krill fishery: estimating crabeater seal abundance off east Antarctica

1. The crabeater seal Lobodon carcinophaga is considered to be a key species in the krill-based food web of the Southern Ocean. Reliable estimates of the abundance of this species are necessary to allow the development of multispecies, predator–prey models as a basis for management of the krill fishery in the Southern Ocean. 2. A survey of crabeater seal abundance was undertaken in 1500 000 km2 of pack-ice off east Antarctica between longitudes 64–150° E during the austral summer of 1999/2000. Sighting surveys, using double observer line transect methods, were conducted from an icebreaker and two helicopters to estimate the density of seals hauled out on the ice in survey strips. Satellite-linked dive recorders were deployed on a sample of seals to estimate the probability of seals being hauled out on the ice at the times of day when sighting surveys were conducted. Model-based inference, involving fitting a density surface, was used to infer densities in the entire survey region from estimates in the surveyed areas. 3. Crabeater seal abundance was estimated to be between 0.7 and 1.4 million animals (with 95% confidence), with the most likely estimate slightly less than 1 million. 4. Synthesis and applications. The estimation of crabeater seal abundance in Convention for the Conservation of Antarctic Marine Living Resources (CCAMLR) management areas off east Antarctic where krill biomass has also been estimated recently provides the data necessary to begin extending from single-species to multispecies management of the krill fishery. Incorporation of all major sources of uncertainty allows a precautionary interpretation of crabeater abundance and demand for krill in keeping with CCAMLR’s precautionary approach to management. While this study focuses on the crabeater seal and management of living resources in the Southern Ocean, it has also led to technical and theoretical developments in survey methodology that have widespread potential application in ecological and resource management studies, and will contribute to a more fundamental understanding of the structure and function of the Southern Ocean ecosystem.

Distance software: design and analysis of distance sampling surveys for estimating population size

1. Distance sampling is a widely used technique for estimating the size or density of biological populations. Many distance sampling designs and most analyses use the software Distance. 2. We briefly review distance sampling and its assumptions, outline the history, structure and capabilities of Distance, and provide hints on its use. 3. Good survey design is a crucial prerequisite for obtaining reliable results. Distance has a survey design engine, with a built-in geographic information system, that allows properties of different proposed designs to be examined via simulation, and survey plans to be generated. 4. A first step in analysis of distance sampling data is modeling the probability of detection. Distance contains three increasingly sophisticated analysis engines for this: conventional distance sampling, which models detection probability as a function of distance from the transect and assumes all objects at zero distance are detected; multiple-covariate distance sampling, which allows covariates in addition to distance; and mark–recapture distance sampling, which relaxes the assumption of certain detection at zero distance. 5. All three engines allow estimation of density or abundance, stratified if required, with associated measures of precision calculated either analytically or via the bootstrap. 6. Advanced analysis topics covered include the use of multipliers to allow analysis of indirect surveys (such as dung or nest surveys), the density surface modeling analysis engine for spatial and habitat-modeling, and information about accessing the analysis engines directly from other software. 7. Synthesis and applications. Distance sampling is a key method for producing abundance and density estimates in challenging field conditions. The theory underlying the methods continues to expand to cope with realistic estimation situations. In step with theoretical developments, state-of- the-art software that implements these methods is described that makes the methods accessible to practicing ecologists.

Studies on the Helminth Fauna of Alaska. XLI. Observations on Cestodes of the Genus Diplogonoporus Lönnberg, 1892 (Diphyllobothriidae)

The study of a collection of cestodes assigned to the genus Diplogonoporus Lönnberg, 1892 disclosed but two species, D. balaenopterae Lönnberg, 1892, and D. tetrapterus (von Siebold, 1848) (provis.). These cestodes occur characteristically in marine mammals but occasionally are found in terrestrial hosts; D. balaenopterae is recorded for the first time from the domestic dog, and it is concluded that D. grandis (Blanchard, 1894), from man, is conspecific with D. balaenopterae. The latter species is recorded for the first time from the humpback whale, Megaptera novaeangliae (Borowski). The relatively small D. tetrapterus, a common parasite of the Steller sea lion, Eumetopias jubata (Schreber), is reported for the first time from the sea otter, Enhydra lutris Linnaeus, and from the domestic mink, Mustela vison Schreber. Descriptions of representative specimens are presented, and the taxonomic status of other species assigned to Diplogonoporus is discussed. Although the diplogonadic organization of these cestodes is somewhat variable, it is nevertheless constant and serves to characterize the genus Diplogonoporus. The process of asexual reproduction by means of transverse subdivision of primary segments is described. This ability and the diplogonadic structure of these cestodes are considered to be adaptations that increase the production of eggs and thereby the probability of reproductive success in the marine habitat.

Applications of Linear Programming to Coding Theory

Maximum-likelihood decoding is often the optimal decoding rule one can use, but it is very costly to implement in a general setting. Much effort has therefore been dedicated to find efficient decoding algorithms that either achieve or approximate the error-correcting performance of the maximum-likelihood decoder. This dissertation examines two approaches to this problem. In 2003 Feldman and his collaborators defined the linear programming decoder, which operates by solving a linear programming relaxation of the maximum-likelihood decoding problem. As with many modern decoding algorithms, is possible for the linear programming decoder to output vectors that do not correspond to codewords; such vectors are known as pseudocodewords. In this work, we completely classify the set of linear programming pseudocodewords for the family of cycle codes. For the case of the binary symmetric channel, another approximation of maximum-likelihood decoding was introduced by Omura in 1972. This decoder employs an iterative algorithm whose behavior closely mimics that of the simplex algorithm. We generalize Omura's decoder to operate on any binary-input memoryless channel, thus obtaining a soft-decision decoding algorithm. Further, we prove that the probability of the generalized algorithm returning the maximum-likelihood codeword approaches 1 as the number of iterations goes to infinity.