Credit: Pixabay/CC0 Public Domain To effectively protect biodiversity in an era of climate change, ecologists first have to know where animal and plant species are located and then be able to predict what habitats will be available to them in the future. To help them in these tasks, the scientists use species distribution models that identify species' habitats from observational data and climate scenarios. Trouble is, these models are often severely limited. They often aren't good at accounting for uncertainty: if the species is not sufficiently well-described, if the relevant climatic conditions are poorly understood, or if the model is simply not very accurate, the models tend to be inaccurate. So when they're used to guide public policy or assess the effectiveness of decision-making, it becomes crucial to say when their predictions might be flawed. This is the methodological problem addressed by Timothée Poisot, a professor in Université de Montréal Department of Biological Sciences.…