In order to enhance in terms of accuracy and predict the modeling of the potential distribution of species, the integration of using principal components of environmental variables as input of maximum entropy (MaxEnt) has been proposed in this study. Principal components selected previously from the principal component analysis results performed in Arc GIS in the environmental variables was used as an input data of MaxEnt instead of raw data to model the potential distribution of red spiny lobster from the year 1997 to 2015 and for three different future scenarios 2020, 2050, and 2070. One set of six original environmental variables pertaining to the years 1997–2015 and one set of four variables for future scenarios were transformed independently into a single multiband raster in Arc GIS in order to select the variables whose eigenvalues explains more than 5% of the total variance with the purpose to use in the modeling prediction in MaxEnt. The years 1997 and 1998 were chosen to compare the accuracy of the model, showing better results using principal components instead of raw data in terms of area under the curve and partial receiver operating characteristic as well as better predictions of suitable areas. Using principal components as input of MaxEnt enhances the prediction of good habitat suitability for red spiny lobster; however, future scenarios suggest an adequate management by researches to elaborate appropriate guidelines for the conservation of the habitat for this valuable specie with face to the climate change.

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In view of the continuous increment of industrial residues, the risk associated with chemical toxicity in the environment has piqued the interest of researchers in pursuit of an alternative methodology for mitigating the apparent toxicity of chemicals. Over the past decade, the applicability of toxicity models and the evaluation of the apparent toxicity of chemicals have been examined for achieving sustainability of the environment and improving water quality. The prediction of toxicant effects with reasonable accuracy in organisms of water bodies and other environmental compartments lies in the application of a chemical toxicity model with further risk assessment analysis. This review summarizes well-known and recent advances of modeling techniques to evaluate and monitor toxicity in the environment. Chemical toxicity models such as the individual-based concentration addition (CA), independent action (IA) and whole-mixture-based concentration addition-independent action (CAIA) are considered, as well as their environmental applications, specific case studies, and further research needs towards sustainability. The gap that needs to be overcome in toxicity studies for the environmental sustainability is noted based on the aspects of environmental chemistry and ecotoxicology, sufficient laboratory equipment, data availability and resources for relevant social parameters needed for investigation.