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Abstract Introduction: Plant functional traits are widely used to predict community productivity. However, they are rarely used to predict the performance (in terms of growth diameter, growth height, survival, and integral response index) of woody species planted in degraded soils. Objective: To evaluate the relationship between the functional traits and the performance of 25 woody species planted in disturbed soils affected by oil extraction activities in Ecuadorian Amazon. Methods: Eighteen permanent sampling plots were established and five 6-month-old seedlings of each 25 species were randomly planted in each plot (125 individuals per plot), at a distance of 4×4 m. Eight quantitative functional traits (leaf size, specific leaf area, leaf nitrogen concentration, leaf phosphorus concentration, leaf minimum unit, leaf dry matter content, stem specific density and leaf tensile strength) were determined for each species. Results: The woody species with high performance shows greater leaf size, specific leaf area and Stem Specific Density than those showing low performance. Leaf nitrogen concentration and stem specific density had a direct relationship with the integral response index. The leaf size, leaf phosphorus concentration, leaf dry matter content and leaf tensile strength showed a negative relationship with the integral response index. Conclusions: Our study demonstrated that the performance of woody species o disturbed soils can be predicted satisfyingly by leaf and stem functional traits, presumably because these traits capture most of environmental and neighborhood conditions.
Resumen Introducción: Los rasgos funcionales de las plantas han sido ampliamente utilizados para predecir la productividad (en términos de crecimiento en diámetro, crecimiento en altura, sobrevivencia e índice de respuesta integral) de las comunidades vegetales. Sin embargo, rara vez han sido utilizados para predecir el desempeño de las especies leñosas plantadas en suelos degradados. Objetivo: Evaluar la relación entre el desempeño y los rasgos funcionales de 25 especies leñosas plantadas en suelos afectados por actividades de extracción de petróleo en la Amazonía ecuatoriana. Métodos: Se establecieron 18 parcelas permanentes de muestreo y en cada parcela se sembraron aleatoriamente cinco plántulas de 6 meses de las 25 especies (125 individuos por parcela), a una distancia de 4×4 m. Se determinaron ocho rasgos funcionales (área foliar, área foliar específica, concentración de nitrógeno foliar, concentración de fósforo foliar, unidad mínima foliar, contenido foliar de materia seca, densidad específica del fuste y fuerza tensil foliar) de cada especie. Resultados: Las especies leñosas con alto desempeño presentaron mayor área foliar, área foliar específica y densidad específica del fuste que las especies de bajo desempeño. La concentración de nitrógeno foliar y la densidad específica del fuste mostraron una relación directa. El área foliar, la concentración de fósforo foliar, el contenido de materia seca foliar y la fuerza tensil foliar presentaron una relación inversa con el Índice de Respuesta Integral. Conclusión: Se demostró que el desempeño de las especies leñosas plantadas en suelos alterados puede predecirse satisfactoriamente por rasgos funcionales de hoja y de tallo, debido posiblemente a que los rasgos influyen en el crecimiento y supervivencia de las especies, y reflejan la mayoría de las condiciones ambientales.
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Árvores/crescimento & desenvolvimento , Poluição por Petróleo/análise , Ecossistema Amazônico , EquadorRESUMO
Objective To study the accuracy of Nolla method for age estimation of Northern Chinese Han children aged between 5.00 and 14.99 years based on original transformation tables and multiple regression model. Methods A total of 2 000 orthopantomographs （OPGs） were collected from the Hospital of Stomatology, Xi'an Jiaotong University, including 1 000 males and 1 000 females. Development stage of 7 left mandibular permanent teeth （except third molars） was assessed based on Nolla method, then age estimation was conducted through transformation tables and multiple regression model, respectively. Firstly, the development stage results of 7 permanent teeth were added up and the estimated age was obtained through the original transformation tables. Secondly, 80% of the samples （80 males and 80 females in each age group） were randomly selected from 2 000 OPGs as the train set. The chronological age of the selected patients was taken as the dependent variable, while gender and the development stage results of 7 permanent teeth were taken as the independent variable to establish multiple regression model. The remaining 20% of the samples were substituted into the model as the test set, to verify the accuracy of age estimation by multiple regression model. Results Mean chronological ages of males and females were 10.03±0.09 years and 10.01±0.09 years, respectively. The age estimated by original transformation tables showed an overestimation for males （0.18 years on average） and an underestimation for females （0.02 years on average）, with mean absolute error （MAE） of 0.94 years and 0.97 years, respectively. While the results by multiple regression model showed that males were overestimated by 0.06 years on average and females were underestimated by 0.02 years on average. The MAE was 0.66 years and 0.77 years, respectively. Conclusion The Nolla method is suitable for age estimation of Northern Chinese Han children. Compared with the original transformation tables method, the multiple regression model is more accurate for age estimation.
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Adolescente , Criança , Pré-Escolar , Feminino , Humanos , Masculino , Determinação da Idade pelos Dentes , Povo Asiático , China , Dente Serotino , Radiografia PanorâmicaRESUMO
Objective To analyze the main characteristics of air pollution in Nanchang City, and discuss the correlation between air pollution exposure (especially PM2.5) and the development of pneumonia related intensive care unit (ICU) patients and their lag effect.Methods 2454 patients who lived in Nanchang City admitted to ICU of Jiangxi Provincial People's Hospital from January 1st, 2014 to December 31st, 2016 were enrolled. According to the diagnosis, the patients were divided into pneumonia group (156 cases) and non-pneumonia group (2298 cases). The general clinical characteristics of patients and air pollution concentration in Nanchang in the year between 2014-2016 were collected. Multiple regression model was used to analyze the influence of meteorological factors on the condition of ICU patients associated with pneumonia. Using odds ratio (OR), the correlation intensity of air pollution exposure and pneumonia related ICU patients' development was reflected, and the confidence level of association intensity was reflected by the 95％ confidence interval (95％CI). The distribution lag nonlinear model (DLNM) was established to evaluate the effect of air mass parameters on the time lag effect.Results The results of air pollution analysis in Nanchang City in the year between 2014-2016 showed that the annual average concentration of carbon monoxide (CO), sulfur dioxide (SO2) and nitrogen dioxide (NO2) was low and maintained at the same level in the year between 2014-2016. The annual average concentration of CO and NO2 increased in the year between 2014-2016, but the average annual concentration of SO2 decreased rapidly in the year between 2014-2016, and the average annual concentration of PM2.5 tended to slow down after the year between 2014-2016. The annual average concentration of PM10 decreased in the year between 2014-2016, but continued to rise in the year between 2014-2016. The annual mean concentration of O3 showed a trend of continuous increase from the year between 2014-2016. The age of pneumonia group was generally higher than that of non-pneumonia group, most of them were male, and had higher expected mortality and acute physiology and chronic health evaluation Ⅱ(APACHEⅡ) score. The average air temperature in the pneumonia group was lower than that in the non-pneumonia group on the day of entering the group, and the air pollutants such as PM2.5 and PM10 were significantly higher than those in the non-pneumonia group. The analysis of multiple regression models showed that PM2.5 and air temperature were significantly related to patients with ICU pneumonia on the day of entry (PM2.5:OR = 1.02, 95％CI =1.00-1.03,P < 0.05; air temperature:OR = 0.96, 95％CI = 0.92-0.98,P < 0.05), and the effect of PM2.5 on patients with ICU pneumonia could last for at least 5 days (OR = 1.04, 95％CI = 1.00-1.09,P < 0.05), and the effect disappeared until the 7th day. According to the analysis of the influence of different concentrations of PM2.5 on ICU pneumonia patients, when the PM2.5 concentration reached 200μg/m3, its effect on ICU pneumonia patients would last for 5 days (OR = 1.45, 95％CI = 1.07-1.76,P < 0.01).Conclusion PM2.5 and air temperature are significantly related to the condition of ICU patients with pneumonia, and the influence of high concentration of PM2.5 on ICU patients with pneumonia has a lag effect.