Impacts of climate-mediated vegetation shifts and regional climate change on coastal avian community dynamics across the Gulf of Mexico

Climate change is considered to be a major threat to extant biodiversity. In addition to direct impacts of changing climatic conditions, poleward shifts in foundation species associated with warming temperatures may exacerbate impacts on higher trophic level species by altering habitat structure and resource availability. Across the Gulf of Mexico (GoM) reductions in severity and duration of winter freezes have facilitated the expansion of mangroves into previously salt marsh dominated habitat. Using birds as model taxa, I investigated the impacts of climate-mediated shifts in foundational species on multiple facets of avian biodiversity. I paired a long-term, standardized avian monitoring dataset (e.g. U.S. Geological Survey Breeding Bird Count) with environmental variables to investigate drivers of avian biodiversity change along coastal sites throughout the GoM and eastern portion of Florida from 1980-2017. Specifically, I was interested in testing whether expansion of mangrove-dominated wetlands and changes in regional climate change (i.e. temperature and precipitation) drive shifts in bird species richness (α-diversity) or elevated rates of bird community turnover through time (temporal β-diversity). I documented changes in α-diversity and temporal β-diversity in both total and wetland bird communities across the GoM. Increases in mangrove cover at fine-spatial scales predicted changes in α-diversity and temporal β-diversity, whereas, coarse-scale changes in temporal β-diversity were predicted by climate. Increasing prevalence of southerly species were associated with faster rates of warming and increased temporal β-diversity, indicating potential poleward shifts in species ranges may be one factor underlying biodiversity change. Modifications in microclimate, biotic interactions, and resource availability associated with mangrove expansion may underlie observed shifts in bird biodiversity. My findings suggest that climate-mediated shifts in foundation species are likely impacting biodiversity of higher trophic level species and may exacerbate biodiversity change driven by the direct impacts of altered temperature and precipitation regimes. As mangrove habitats are predicted to continue to expand across the GoM, integrating data on in foundation species will be crucial for future assessments and adaptive management of climate-mediated changes in avian biodiversityMarine Scienc

Effects of Knowledge Transfer Practices on Employee’s Performance of Local Government Authorities in Tanzania.

This study examined the effects of knowledge transfer practices on employee performance of Local Government Authorities in Tanzania. Specifically, to determine the effect of mentoring practice, to assess the effect of peer training practices, to investigate the effect of information and communication technology practices and to examine the effect of team work practices on employee performance in LGAs. The study was guided by knowledge-based theory and dynamic theory of organizational knowledge creation, the positivism philosophy with a quantitative approach was adopted. A close-ended questionnaire was used to survey a total of 368 employees drawn from Mbeya City Council, Iringa Municipal Council, Tunduma Town Council and Makete District Council. The multiple linear regression model was used to test the hypotheses. The study findings showed that mentoring practice, information and communication technology practice and team work practice, had statistically positive and significant effect on employee performance in Local Government Authorities. However, peer training practice was statistically insignificant influence on employee’s performance. The study concludes that, team work practice had a strong significant association to affect employee performance. The study therefore, recommends that Local Government Authorities to increase review on training policies in addressing need for knowledge transfer practice on employee performance. Other recommendation of the study was; promotion of the application of information communication technology resources and skills to encourage employee interaction in all levels of local government authorities. Keywords: Knowledge Transfer Practices, Employee Performance, Local Government Authorities, Employees

Inferências e aplicações no modelo de regressão beta com dispersão variável

Regression analysis is one of the statistical techniques widely used to investigate the behavior of a response variable when it is influenced by a set of other variables. Beta regression models are suitable for cases where the response variable is restricted to the interval (0; 1), such as rates and proportions. The beta regression model with varying dispersion, which is the focus of this work, is somewhat general and contains two regression structures, namely: for the mean and dispersion/precision. These regression structures contain covariates, unknown parameters and link functions that allow the modeling of the parameters of interest. In this work we approach both the practical and theoretical application of the beta regression model with varying dispersion. Regarding the practical approach, one of our first objectives was to evaluate and explain the proportion of obese children benefited by the Bolsa Famılia Program in the regions of Brazil through variables related to the social, economic, demographic and nutritional conditions of Bolsa Família recipients in the municipalities of Brazil. The main result was that in two of the five regions of Brazil, the variable per capita spending with Bolsa Família was significant and had a positive influence on obesity, that is, in the municipalities of the two regions that received the most Bolsa Família benefits, there was a tendency to present a higher proportion of obese children, a result that is very worrying and requires attention. Still addressing the obesity topic, a second objective was to evaluate the proportion of obese adults in the United States. For this, we consider some variables related to the social and nutritional conditions of the population of 50 states in that country. The results showed that the states with the highest percentages of physical inactivity tended to present a higher proportion of obese individuals, where as states with higher values of well-being score tended to have a lower proportion. Additionally, we estimated the impact of physical inactivity on the average proportion of obese adults and the results showed that the effect of this impact is positive for all possible values of physical inactivity. Finally, one of our last objectives, now considering the theoretical approach, was to evaluate the effects of specification errors on the inferences of the beta regression model with varying dispersion. For the evaluation of these errors we performed a simulation study considering different scenarios. The results of these simulations showed that the specification errors involving the regression structure of the precision parameter had a considerable influence on the model inferences, indicating a need for more attention in the modeling of this structure.NenhumaA análise de regressão é uma das técnicas estatísticas mais utilizadas para investigar o comportamento de uma variável resposta quando o mesmo é influenciado por um conjunto de outras variáveis. Modelos de regressão beta são adequados para os casos em que a variável resposta está restrita ao intervalo (0; 1), a exemplo de taxas e proporções. O modelo de regressão beta com dispersão variável, que é o foco deste trabalho, é um tanto geral e contêm duas estruturas de regressão, a saber: para a média e dispersão/precisão. Estas estruturas de regressão contêm covariáveis, parâmetros desconhecidos e funções de ligação que permitem a modelagem dos parâmetros de interesse. Neste trabalho abordamos tanto a aplicação prática quanto teórica do modelo de regressão beta com dispersão variável. Em relação a abordagem prática, um dos nossos primeiros objetivos foi de avaliar e explicar a proporção de crianças obesas beneficiadas pelo Programa Bolsa Família nas regiões do Brasil através de variáveis relacionadas as condições sociais, econômicas, demográficas e nutricionais dos beneficiários do Bolsa Família nos municípios brasileiros. O principal resultado encontrado foi que em duas das cinco regiões do Brasil, a variável gasto per capita com o Bolsa Família foi significativa e apresentou influência positiva na obesidade, ou seja, nos municípios destas duas regiões que mais receberam benefícios do Bolsa Família houve uma tendência a apresentar uma maior proporção de crianças obesas, resultado este bastante preocupante e que exige atenção. Ainda abordando o tema obesidade, um segundo objetivo nosso foi de avaliar a proporção de adultos obesos nos Estados Unidos. Para isto, consideramos algumas variáveis relacionadas as condições sociais e nutricionais da população de 50 estados daquele país. Os resultados revelaram que os estados com maiores porcentagens de inatividade física tenderam a apresentar uma maior proporção de indivíduos obesos, enquanto que os estados com maior escore de bem estar tenderam a ter uma menor proporção. Adicionalmente, estimamos o impacto da inatividade física sobre a proporção média de adultos obesos e os resultados revelaram que o efeito deste impacto apresenta forma positiva para todos os possíveis valores de inatividade física. Por fim, um dos nossos últimos objetivos, agora abordando o enfoque teórico, foi de avaliar os efeitos de erros de especifica¸c~ao nas inferências do modelo de regressão beta com dispersão variável. Para a avaliação destes erros realizamos um estudo de simulação considerando diferentes cenários. Os resultados destas simulações revelaram que os erros de especifica¸c~ao envolvendo a estrutura de regressão do parâmetro de precisão apresentaram uma influência considerável nas inferências do modelo, indicando uma necessidade de maior atenção na modelagem desta estrutura

Understanding the relationship between resource consumption and development levels

Developing an empirical understanding of the relationship between built environment material stocks and minimum standards of living is essential to understanding challenges and opportunities for sustainable development. This is particularly important in the Global South given the existing deficits in living standards and the unprecedented rates of urbanization expected in the coming decades. The following body of work seeks to provide an improved understanding of this relationship through an empirical analysis of India which is used as a topical testbed to address this research aim. Multiscale observations reveal widespread challenges to minimum standards of living and resource consumption and thus the achievement of interconnected SDGs. The empirical quantification of the coupling of MS and basic needs outcomes across scales reveals existing national trends, where minimum standards of living have grown with the provision of carbon intensive materials within the built environment. The results also reveal that significant deficits in overall basic needs still exist and that a substantial amount of residential building MS are required to fill deficits for minimal improvements to overall basic needs if current trends are to continue. Through a city- and sub-city scale assessment of built environment MS accumulation within India for the first time, improved insight into the provision of MS in the context of high basic needs outcomes is developed. This is of crucial importance for future policy making given that the observed national trends are likely a result of policy choices in how urban infrastructure and housing are provided within India. The results therefore point to the need to integrate MS thinking and SDG monitoring within future urban planning and to develop empirical understandings of this relationship in other nations of the Global South such that nations identify appropriate strategies to decouple from global trends

Relationship Between Risk Exposure, Volatility Forecasting, and Financial Performance of Hedge Funds

Poor hedge fund performance can impede the financial performance of a business organization. Despite the success of hedge funds, they incurred a loss of 33% during the global economic recession of 2007-2009. Understanding volatility and risk exposures are vital for investors and managers to increase hedge fund returns in various market conditions. Grounded in Markowitz’s modern portfolio theory, the purpose of this quantitative correlational study was to examine the relationship between hedge fund risk exposure, volatility forecasting, and financial performance. Data were collected from archival data from the HedgeNews Africa database and financial databases in South Africa between 2007 and 2020. The results of the multiple linear regression analysis indicated the model was able to predict the financial performance of hedge funds significantly, F(2, 149) = 238, p \u3c 0.001, R2 = .950, with risk exposure (3 month-credit spread), (β = -0.789, t = -9.417, p \u3c 0.001), accounting for the highest contribution to the model. Volatility forecasting did not explain any significant variance in the financial performance of hedge funds. A key recommendation for hedge fund managers is to include risk exposure to maximize financial performance. The implications for positive social change include the potential for maximum profits in turbulent market conditions for institutional and individual investors, which could be applied to provide social amenities for communities and improve the welfare of people