Yung En Chee

TL;DR: A new statistical explanation of MaxEnt is described, showing that the model minimizes the relative entropy between two probability densities defined in covariate space, which is likely to be a more accessible way to understand the model than previous ones that rely on machine learning concepts.

TL;DR: In this paper, the authors present a critical review on the neoclassical economic framework, tools used for economic valuation of ecosystem services and the economic welfare approach to collective decision-making, from an ecological perspective.

TL;DR: Evidence of common objections to the use of models in environmental decision-making is provided and a set of practical solutions based on theory, empirical evidence and best-practice examples are presented to help modellers substantively address these objections.

TL;DR: There is a movement across empirical disciplines, and now within ecology and evolution, to shape editorial policies to better promote transparency, by either requiring more disclosure by scientists or by developing incentives to encourage disclosure.

TL;DR: In this paper, the authors argue that the tendency to overlook the conservation value of urban environments stems from misconceptions about the ability of native species to persist within cities and towns and that this, in turn, hinders effective conservation action.