Soil-nutrient availability modifies the response of young pioneer and late successional trees to elevated carbon dioxide in a Brazilian tropical environment

The aim of this work was to determine the impact of three levels of [CO2] and two levels of soil-nutrient availability on the growth and physiological responses of two tropical tree species differing in their ecological group: Croton urucurana Baillon, a pioneer (P), and also Cariniana legalis (Martius) Kuntze, a late succession (LS). We aimed to test the hypothesis that P species have stronger response to elevated [CO2] than LS species as a result of differences in photosynthetic capacity and growth kinetics between both functional groups. Seedlings of both species were grown in open-top-chambers under high (HN) or low (LN) soil-nutrient supply and exposed to ambient (380 mu mol mol(-1)) or elevated (570 and 760 mu mol mol(-1)) [CO2]. Measurements of gas exchange, chlorophyll a fluorescence, seedling biomass and allocation were made after 70 days of treatment. Results suggest that elevated [CO2] significantly enhances the photosynthetic rates (A) and biomass production in the seedlings of both species, but that soil-nutrient supply has the potential to modify the response of young tropical trees to elevated [CO2]. In relation to plants grown in ambient [CO2], the P species grown under 760 mu mol mol(-1) [CO2] showed increases of 28% and 91% in A when grown in LN and HN, respectively. In P species grown under 570 mu mol mol(-1) [CO2], A increased by 16% under HN, but there was no effect in LN. In LS species, the enhancement of A by effect of 760 mu mol mol(-1) [CO2] was 30% and 70% in LN and HN, respectively. The exposure to 570 mu mol mol(-1) [CO2] stimulated A by 31% in HN, but was no effect in LN. Reductions in stomatal conductance (g(s)) and transpiration (E), as a result of elevated [CO2] were observed. Increasing the nutrient supply from low to high increased both the maximum rate of carboxylation (V-cmax) and maximum potential rate of electron transport (J(max)). As the level of [CO2] increased, both the V-cmax and the J(max) were found to decrease, whereas the J(max)/V-cmax ratio increased. In the LS species, the maximum efficiency of PSII (F-v/F-m) was higher in the 760 mu mol mol(-1) [CO2] treatment relative to other [CO2] treatments. The results suggest that when grown under HN and the highest [CO2], the performance of the P species C. urucurana, in terms of photosynthesis and biomass enhancement, is better than the LS species C. legalis. However, a larger biomass is allocated to roots when C. legalis seedlings were exposed to elevated [CO2]. This response would be an important strategy for plant survival and productivity of the LS species under drought stresses conditions on tropical environments in a global-change scenario. (C) 2011 Elsevier B.V. All rights reserved.

The Tripartite Ramsey Number for Trees

We prove that for all epsilon>0 there are alpha>0 and n(0)is an element of N such that for all n >= n(0) the following holds. For any two-coloring of the edges of Kn, n, n one color contains copies of all trees T of order t <=(3 - epsilon)n/2 and with maximum degree Delta(T)<= n(alpha). This confirms a conjecture of Schelp. (c) 2011 Wiley Periodicals, Inc. J Graph Theory 69: 264300, 2012

Predicting smear negative pulmonary tuberculosis with classification trees and logistic regression: a cross-sectional study

Abstract Background Smear negative pulmonary tuberculosis (SNPT) accounts for 30% of pulmonary tuberculosis cases reported yearly in Brazil. This study aimed to develop a prediction model for SNPT for outpatients in areas with scarce resources. Methods The study enrolled 551 patients with clinical-radiological suspicion of SNPT, in Rio de Janeiro, Brazil. The original data was divided into two equivalent samples for generation and validation of the prediction models. Symptoms, physical signs and chest X-rays were used for constructing logistic regression and classification and regression tree models. From the logistic regression, we generated a clinical and radiological prediction score. The area under the receiver operator characteristic curve, sensitivity, and specificity were used to evaluate the model's performance in both generation and validation samples. Results It was possible to generate predictive models for SNPT with sensitivity ranging from 64% to 71% and specificity ranging from 58% to 76%. Conclusion The results suggest that those models might be useful as screening tools for estimating the risk of SNPT, optimizing the utilization of more expensive tests, and avoiding costs of unnecessary anti-tuberculosis treatment. Those models might be cost-effective tools in a health care network with hierarchical distribution of scarce resources.

Evolving decision trees with beam search-based initialization and lexicographic multi-objective evaluation

Decision tree induction algorithms represent one of the most popular techniques for dealing with classification problems. However, traditional decision-tree induction algorithms implement a greedy approach for node splitting that is inherently susceptible to local optima convergence. Evolutionary algorithms can avoid the problems associated with a greedy search and have been successfully employed to the induction of decision trees. Previously, we proposed a lexicographic multi-objective genetic algorithm for decision-tree induction, named LEGAL-Tree. In this work, we propose extending this approach substantially, particularly w.r.t. two important evolutionary aspects: the initialization of the population and the fitness function. We carry out a comprehensive set of experiments to validate our extended algorithm. The experimental results suggest that it is able to outperform both traditional algorithms for decision-tree induction and another evolutionary algorithm in a variety of application domains.