Upcoming Events

Ecological Niche Modelling using Presence Only (PO) data. An evaluation of methods & applications

Speaker: Angelica Lopez

Location: 11:30 am to 12:30 pm in Building 6, Level C, Room 12

Ecological niche models (ENMs), which are created by linking species’ occurrence data with environmental envelopes, are popular tools to answer fundamental questions in ecology and evolution. However, as a relatively new research line, ENM faces many methodological and practical challenges. Whether it is possible to accurately predict species occurrence probability when working with presence only data, is the main question of the first part of this study. The second part of the thesis moves beyond ENM methodologies, using them to

Linking science with water policy: an assessment of contemporary approaches

Speaker: Michael Peat

Location: 11:30 am to 12:30 pm in Building 6, Level C, Room 12

Governments, researchers and stakeholder groups often call for science to inform water policy on the basis that it will improve the quality of policy decisions, but is the science we produce usable in this policy context? There is a need to improve our understanding of how science can help inform the design and implementation of water policy. Rapid evidence synthesis and adaptive management are two contemporary approaches developed to help integrate science and policy. I will discuss how both approaches

Using genomic, physiological, and landscape data to better inform predictions of biodiversity loss under climate change

Speaker: Dr Renee Catullo

Location: 11:30 am to 12:30 pm in Building 6, Level C, Room 12

Spatial models of biodiversity loss under climate change often assume that species must track their thermal niche across the landscape. However, many species’ ranges are limited by biological, not thermal interactions, and some species have the capacity to evolve in response to the selection pressure of climate change. This means that species have physiological, plastic, and evolutionary capacity to adapt to novel conditions, and these data can increase the accuracy of biodiversity loss prediction. Renee will talk about the information