Accurate spatio-temporal predictions of land-cover are fundamentally important for assessing geomorphological and ecological patterns and processes. This study quantifies the epistemic uncertainty in the species distribution modeling, which is generated by spatio-temporal gaps between the biogeographical data, model selection and model complexity. Epistemic uncertainty is generally given by the sum of subjective and objective uncertainty. The subjective uncertainty generated by the modeler-choice in the manipulation of the environmental variables was analyzed.

This paper presents a spatial framework which can be used to perform multi-criteria assessments for different purposes. We tested the framework on a case study of evaluating potential expansion for irrigated pasture in the Limestone Coast of South Australia. The core of the framework is the fuzzy linguistic ordered weighted averaging (FLOWA) model which integrates and implements fuzzy quantifiers, Ordered Weighted Averaging (OWA) and Analytical Hierarchy Process (AHP) in the ArcGIS environment.

This article explores evidence of deforestation and forest management practices in the Maya lowlands during the pre-Columbian period. In the early twentieth century, scholars first began to examine the role of the environment in the rise and collapse of the great southern Maya polities of the Classic period, proposing that deforestation was an important factor in their political fragmentation and depopulation between the eighth and tenth centuries. In the last twenty-five years, this hypothesis has gained broad acceptance largely due to research at the ancient city of Copan, Honduras.