Temperature field forecast in concrete dam with the use of ARIMA models and the finite element method

This article describes a forecasting method, with the application of statistical models Auto-Regressive Integrated Moving Average (ARIMA) and a heat conduction model to forecast the temperature field in a buttress block of Itaipu dam. Monthly temperature series in 2010-2014 of surface thermometers to block were fitted with cubic splines and the series, now daily, were used as inputs for specific ARIMA models to produce forecasts as outputs. These outputs were used as boundary conditions to the thermal model of the block and this solved by the Finite Element Method (FEM). Obtained thus predicted temperature fields of block. The error MAPE between the values obtained by MEF and the real, in a test point, (where is an internal thermometer) measured the performance of the forecast of ARIMA models, and this was satisfactory, achieving near 15%. The proposed method has an innovative character for thermal analysis structures, in particular in concrete dams

Detection of anti-Toxoplasma gondii antibodies in beef cattle slaughtered on Guarapuava city, Paraná State, Brazil.

Com os objetivos de determinar a ocorrência de anticorpos contra Toxoplasma gondii em gado de corte da região de Guarapuava, Paraná e de correlacionar esta com a idade, o sexo e a raça dos animais, amostras de sangue de 250 bovinos foram obtidas e enviadas ao laboratório de Zoonoses e Saúde Pública do Departamento de Medicina Veterinária Preventiva da Universidade Estadual de Londrina. Após obtenção dos soros, estes foram armazenados a -20ºC, até a realização dos exames. A detecção de anticorpos anti-T. gondii foi realizada utilizando-se a Reação de Imunofluorescência Indireta (cut off ≥1:64). Os dados foram tabulados e analisados por meio dos testes exato de Fisher e de qui-quadrado (p≤0,05) para correlacionar os resultados da sorologia com as variáveis analisadas. Das 250 amostras de soro avaliadas, 77 (30,8%) foram positivas para T. gondii. Os títulos obtidos foram 1:64 (70) e 1:256 (sete). Os resultados demonstram ampla distribuição do protozoário entre os rebanhos bovinos de corte na região de Guarapuava, PR. Animais soropositivos estavam presentes em 56% (14/25) das propriedades avaliadas. Animais sem raça definida apresentaram maiores índices de soropositivos para T. gondii (P=0,001). A idade apresentou correlação positiva com a ocorrência de anticorpos contra T. gondii (P=0,01), indicando transmissão horizontal do agente. A alta incidência de bovinos de corte sororreagentes ao T. gondii observada neste trabalho indica o risco potencial do consumo de carne bovina para a infecção toxoplásmica humana.With the aim to determine the occurrence of antibodies against Toxoplasma gondii in beef cattle of the region of Guarapuava, Paraná State, Brazil and to correlate this with the age, the sex and the breed of the animals, samples of blood of 250 bovine were obtained and sent to the Zoonoses and Public Health Laboratory of the Preventive Veterinary Medicine Department of the State University of Londrina. After getting the serums, these were stored to -20ºC, up to the realization of the examinations. The detection of antibodies anti-T. gondii was carried out by IFAT (cut off ≥1:64). The statistical analysis was carried out through Fisher's exact and of qui-square tests (p≤0,05) to correlate the results of the serology with the analyzed variables. Of 250 evaluated samples of serum, 77 (30.8 %) were positive for T. gondii. The titles obtained were 1:64 (70) and 1:256 (seven). The results demonstrate large distribution of the protozoa among beef cattle in the region of Guarapuava, PR. Animals seropositives were present in 56% (14/25) evaluated properties. Animals mix breed presented higher rates of seropositives for T. gondii (P=0.001). The age presented positive correlation with the occurrence of antibodies against T. gondii (P=0.01), indicating horizontal transmission of the agent. The high incidence of beef cattle positives to T. gondii observed in this work indicates the potential risk of the consumption of meat cattle for the human toxoplasmic infection

Mapping density, diversity and species-richness of the Amazon tree flora

Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution

Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology

In a time of rapid global change, the question of what determines patterns in species abundance distribution remains a priority for understanding the complex dynamics of ecosystems. The constrained maximization of information entropy provides a framework for the understanding of such complex systems dynamics by a quantitative analysis of important constraints via predictions using least biased probability distributions. We apply it to over two thousand hectares of Amazonian tree inventories across seven forest types and thirteen functional traits, representing major global axes of plant strategies. Results show that constraints formed by regional relative abundances of genera explain eight times more of local relative abundances than constraints based on directional selection for specific functional traits, although the latter does show clear signals of environmental dependency. These results provide a quantitative insight by inference from large-scale data using cross-disciplinary methods, furthering our understanding of ecological dynamics

Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology

In a time of rapid global change, the question of what determines patterns in species abundance distribution remains a priority for understanding the complex dynamics of ecosystems. The constrained maximization of information entropy provides a framework for the understanding of such complex systems dynamics by a quantitative analysis of important constraints via predictions using least biased probability distributions. We apply it to over two thousand hectares of Amazonian tree inventories across seven forest types and thirteen functional traits, representing major global axes of plant strategies. Results show that constraints formed by regional relative abundances of genera explain eight times more of local relative abundances than constraints based on directional selection for specific functional traits, although the latter does show clear signals of environmental dependency. These results provide a quantitative insight by inference from large-scale data using cross-disciplinary methods, furthering our understanding of ecological dynamics

Author correction: One sixth of Amazonian tree diversity is dependent on river floodplains

In the version of the article initially published, the affiliation of Edgardo Manuel Latrubesse was incorrect and has now been amended to Environmental Sciences Graduate Program-CIAMB, Federal University of Goiás, Goiânia, Brazil in the HTML and PDF versions of the article

Mapping density, diversity and species-richness of the Amazon tree flora

Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution

One sixth of Amazonian tree diversity is dependent on river floodplains

Amazonia’s floodplain system is the largest and most biodiverse on Earth. Although forests are crucial to the ecological integrity of floodplains, our understanding of their species composition and how this may differ from surrounding forest types is still far too limited, particularly as changing inundation regimes begin to reshape floodplain tree communities and the critical ecosystem functions they underpin. Here we address this gap by taking a spatially explicit look at Amazonia-wide patterns of tree-species turnover and ecological specialization of the region’s floodplain forests. We show that the majority of Amazonian tree species can inhabit floodplains, and about a sixth of Amazonian tree diversity is ecologically specialized on floodplains. The degree of specialization in floodplain communities is driven by regional flood patterns, with the most compositionally differentiated floodplain forests located centrally within the fluvial network and contingent on the most extraordinary flood magnitudes regionally. Our results provide a spatially explicit view of ecological specialization of floodplain forest communities and expose the need for whole-basin hydrological integrity to protect the Amazon’s tree diversity and its function

Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology

In a time of rapid global change, the question of what determines patterns in species abundance distribution remains a priority for understanding the complex dynamics of ecosystems. The constrained maximization of information entropy provides a framework for the understanding of such complex systems dynamics by a quantitative analysis of important constraints via predictions using least biased probability distributions. We apply it to over two thousand hectares of Amazonian tree inventories across seven forest types and thirteen functional traits, representing major global axes of plant strategies. Results show that constraints formed by regional relative abundances of genera explain eight times more of local relative abundances than constraints based on directional selection for specific functional traits, although the latter does show clear signals of environmental dependency. These results provide a quantitative insight by inference from large-scale data using cross-disciplinary methods, furthering our understanding of ecological dynamics.</p

The Maximum Entropy Formalism of statistical mechanics in a biological application: a quantitative analysis of tropical forest ecology

In a time of rapid global change, the question of what determines patterns in species abundance distribution remains a priority for understanding the complex dynamics of ecosystems. The constrained maximization of information entropy provides a framework for the understanding of such complex systems dynamics by a quantitative analysis of important constraints via predictions using least biased probability distributions. We apply it to over two thousand hectares of Amazonian tree inventories across seven forest types and thirteen functional traits, representing major global axes of plant strategies. Results show that constraints formed by regional relative abundances of genera explain almost ten times more of local relative abundances then constraints based on either directional or stabilizing selection for specific functional traits, although the latter does show clear signals of environmental dependency. These results provide a quantitative insight by inference from large-scale data using cross-disciplinary methods, furthering our understanding of ecological dynamics