4 resultados para Infinite-Population Social

em DigitalCommons@University of Nebraska - Lincoln


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Classical sampling methods can be used to estimate the mean of a finite or infinite population. Block kriging also estimates the mean, but of an infinite population in a continuous spatial domain. In this paper, I consider a finite population version of block kriging (FPBK) for plot-based sampling. The data are assumed to come from a spatial stochastic process. Minimizing mean-squared-prediction errors yields best linear unbiased predictions that are a finite population version of block kriging. FPBK has versions comparable to simple random sampling and stratified sampling, and includes the general linear model. This method has been tested for several years for moose surveys in Alaska, and an example is given where results are compared to stratified random sampling. In general, assuming a spatial model gives three main advantages over classical sampling: (1) FPBK is usually more precise than simple or stratified random sampling, (2) FPBK allows small area estimation, and (3) FPBK allows nonrandom sampling designs.

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In social species, breeding system and gregarious behavior are key factors influencing the evolution of large-scale population genetic structure. The killer whale is a highly social apex predator showing genetic differentiation in sympatry between populations of foraging specialists (ecotypes), and low levels of genetic diversity overall. Our comparative assessments of kinship, parentage and dispersal reveal high levels of kinship within local populations and ongoing male-mediated gene flow among them, including among ecotypes that are maximally divergent within the mtDNA phylogeny. Dispersal from natal populations was rare, implying that gene flow occurs without dispersal, as a result of reproduction during temporary interactions. Discordance between nuclear and mitochondrial phylogenies was consistent with earlier studies suggesting a stochastic basis for the magnitude of mtDNA differentiation between matrilines. Taken together our results show how the killer whale breeding system, coupled with social, dispersal and foraging behaviour, contributes to the evolution of population genetic structure.

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Moose Alces alces gigas in Alaska, USA, exhibit extreme sexual dimorphism, with adult males possessing large, elaborate antlers. Antler size and conformation are influenced by age, nutrition and genetics, and these bony structures serve to establish social rank and affect mating success. Population density, combined with anthropogenic effects such as harvest, is thought to influence antler size. Antler size increased as densities of moose decreased, ostensibly a density-dependent response related to enhanced nutrition at low densities. The vegetation type where moose were harvested also affected antler size, with the largest-antlered males occupying more open habitats. Hunts with guides occurred in areas with low moose density, minimized hunter interference and increased rates of success. Such hunts harvested moose with larger antler spreads than did non-guided hunts. Knowledge and abilities allowed guides to satisfy demands of trophy hunters, who are an integral part of the Alaskan economy. Heavy harvest by humans was also associated with decreased antler size of moose, probably via a downward shift in the age structure of the population resulting in younger males with smaller antlers. Nevertheless, density-dependence was more influential than effects of harvest on age structure in determining antler size of male moose. Indeed, antlers are likely under strong sexual selection, but we demonstrate that resource availability influenced the distribution of these sexually selected characters across the landscape. We argue that understanding population density in relation to carrying capacity (K) and the age structure of males is necessary to interpret potential consequences of harvest on the genetics of moose and other large herbivores. Our results provide researchers and managers with a better understanding of variables that affect the physical condition, antler size, and perhaps the genetic composition of populations, which may be useful in managing and modeling moose populations.

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The role of social cognition in severe mental illness (SMI) has gained much attention, especially over the last decade. The impact of deficits in socio-cognitive functioning has been found to have detrimental effects on key areas of day-to-day functioning in individuals with SMI, such as gaining and maintaining employment and overall experienced quality of life. Treatment of individuals with SMI is challenging, as the presentation of individual signs and symptoms is rather heterogeneous. There are several treatment approaches addressing deficits ranging from broader social and interpersonal functioning to neurocognitive and more intrapersonal functioning. As research in the domain of social cognition continues to identify specific deficits and its functional detriments, treatment options need to evolve to better target identified functional deficits. Social Cognition and Interaction Training (SCIT) was recently developed to address specific socio-cognitive deficits in an inpatient population of individuals with schizophrenia-spectrum disorders. This study applied SCIT in an outpatient SMI population as many deficits remain after individuals’ symptoms are less severe and overall functioning is more stable than during the acute inpatient phase of their rehabilitation. Specifically, this study has two objectives. First, to demonstrate that deficits in social cognition persist after the acute phase of illness has abated. Second, to demonstrate that these deficits can be ameliorated via targeted treatment such as SCIT. Data was gathered in local outpatient treatment settings serving a heterogeneous SMI population. Adviser: William D. Spaulding