Balanço e análise da sustentabilidade energética na produção orgânica de hortaliças.

Os insumos e serviços utilizados na produção vegetal representam custo energético. Dependendo desses fatores e das produtividades obtidas, a conversão da produção em energia determinará a eficiência energética do sistema. A agricultura orgânica somente atingirá a missão de preservação ambiental se tiver comprovada sustentabilidade energética. Neste trabalho, objetivou-se caracterizar os balanços energéticos dos cultivos orgânicos e analisar sua sustentabilidade, em comparação aos sistemas convencionais. Monitoraram-se campos de produção de dez culturas, de 1991 a 2000 em Domingos Martins-ES. Os dados do sistema convencional foram obtidos pelas médias dos coeficientes técnicos da região. Quantificaram-se os coeficientes técnicos, convertendo suas grandezas físicas em equivalentes energéticos, expressos em kcal. O sistema orgânico gastou 4.571.159 kcal ha-1 e apresentou 12.696.712 kcal ha-1 de energia inserida na colheita, mostrando balanço médio de 2,78. Esse valor foi similar ao obtido no sistema convencional (1,93). As participações dos componentes nos gastos do sistema orgânico foram embalagem (35,8%), composto orgânico (17,2%), irrigação (12,6%), sementes/mudas (12,4%) e mão-de-obra (11,0%), serviços mecânicos (5,0%) e frete (4,5%). Se os custos com embalagens fossem eliminados, os gastos do sistema orgânico seriam reduzidos para 2.930.113 kcal ha-1, aumentando sua eficiência. A maioria dos cultivos orgânicos pode ser considerada sustentável em transformação de energia, com balanços superiores a 1,00 e produção média diária de 80.421 kcal ha-1 por dia, superior à necessidade mínima de 58.064 kcal ha-1

Performance measures for upper gastrointestinal endoscopy:A European Society of Gastrointestinal Endoscopy (ESGE) Quality Improvement Initiative

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A New (Old), Invasive Ant in the Hardwood Forests of Eastern North America and Its Potentially Widespread Impacts

Biological invasions represent a serious threat for the conservation of biodiversity in many ecosystems. While many social insect species and in particular ant species have been introduced outside their native ranges, few species have been successful at invading temperate forests. In this study, we document for the first time the relationship between the abundance of the introduced ant, Pachycondyla chinensis, in mature forests of North Carolina and the composition, abundance and diversity of native ant species using both a matched pair approach and generalized linear models. Where present, P. chinensis was more abundant than all native species combined. The diversity and abundance of native ants in general and many individual species were negatively associated with the presence and abundance of P. chinensis. These patterns held regardless of our statistical approach and across spatial scales. Interestingly, while the majority of ant species was strongly and negatively correlated with the abundance and presence of P. chinensis, a small subset of ant species larger than P. chinensis was either as abundant or even more abundant in invaded than in uninvaded sites. The large geographic range of this ant species combined with its apparent impact on native species make it likely to have cascading consequences on eastern forests in years to come, effects mediated by the specifics of its life history which is very different from those of other invasive ants. The apparent ecological impacts of P. chinensis are in addition to public health concerns associated with this species due to its sometimes, deadly sting

Effects of the Training Dataset Characteristics on the Performance of Nine Species Distribution Models: Application to Diabrotica virgifera virgifera

Many distribution models developed to predict the presence/absence of invasive alien species need to be fitted to a training dataset before practical use. The training dataset is characterized by the number of recorded presences/absences and by their geographical locations. The aim of this paper is to study the effect of the training dataset characteristics on model performance and to compare the relative importance of three factors influencing model predictive capability; size of training dataset, stage of the biological invasion, and choice of input variables. Nine models were assessed for their ability to predict the distribution of the western corn rootworm, Diabrotica virgifera virgifera, a major pest of corn in North America that has recently invaded Europe. Twenty-six training datasets of various sizes (from 10 to 428 presence records) corresponding to two different stages of invasion (1955 and 1980) and three sets of input bioclimatic variables (19 variables, six variables selected using information on insect biology, and three linear combinations of 19 variables derived from Principal Component Analysis) were considered. The models were fitted to each training dataset in turn and their performance was assessed using independent data from North America and Europe. The models were ranked according to the area under the Receiver Operating Characteristic curve and the likelihood ratio. Model performance was highly sensitive to the geographical area used for calibration; most of the models performed poorly when fitted to a restricted area corresponding to an early stage of the invasion. Our results also showed that Principal Component Analysis was useful in reducing the number of model input variables for the models that performed poorly with 19 input variables. DOMAIN, Environmental Distance, MAXENT, and Envelope Score were the most accurate models but all the models tested in this study led to a substantial rate of mis-classification