Assessing the effects of pseudo-absences on predictive distribution model performance

Modelling species distributions with presence data from atlases, museum collections and databases is challenging. In this paper, we compare seven procedures to generate pseudoabsence data, which in turn are used to generate GLM-logistic regressed models when reliable absence data are not available. We use pseudo-absences selected randomly or by means of presence-only methods (ENFA and MDE) to model the distribution of a threatened endemic Iberian moth species (Graellsia isabelae). The results show that the pseudo-absence selection method greatly influences the percentage of explained variability, the scores of the accuracy measures and, most importantly, the degree of constraint in the distribution estimated. As we extract pseudo-absences from environmental regions further from the optimum established by presence data, the models generated obtain better accuracy scores, and over-prediction increases. When variables other than environmental ones influence the distribution of the species (i.e., non-equilibrium state) and precise information on absences is non-existent, the random selection of pseudo-absences or their selection from environmental localities similar to those of species presence data generates the most constrained predictive distribution maps, because pseudo-absences can be located within environmentally suitable areas. This study showsthat ifwe do not have reliable absence data, the method of pseudo-absence selection strongly conditions the obtained model, generating different model predictions in the gradient between potential and realized distributions.

Development of chitosan packaging films with carvacrol and grape seed extract as antimicrobial and antioxidant agents

In order to produce packaging films with a broad spectrum of action on microorganisms, the effect of two antimicrobial (AM) to be included in the films, carvacrol and GSE were studied separately on different microorganisms. Carvacrol was more effective against the grampositive bacteria than against the gram-negative bacterium. GSE was not effective against yeast. Subsequently, a search for optimal combinations of carvacrol, GSE and the addition of chitosan (as a third component with film forming properties) was carried out. Response surface analysis showed several synergetic effects and three optimal AM combinations (OAMC) were obtained for each microorganism. The experimental validation confirmed that the optimal solutions found can successfully predict the response for each microorganism. The optimization of mixtures of the three components, but this time, using the same concentration for all microorganisms, was also studied to obtain an OAMC with wide spectrum of activity. The results of the response surface analysis showed several synergistic effects for all microorganisms. Three OAMC, OAMC-1, OAMC-2, OAMC-3, were found to be the optimal mixtures for all microorganisms. The radical scavenging activity (RSA) of the different agents was then compared with a standard antioxidant (AOX) BHT, at different concentrations; as also at the OAMC. The RSA increased in the following order: chitosan