Welcome to the Department of Biology. Exciting research in the Woolley Lab. Moreover, unlike auditory regions, activity in the NCC parallels behavioral preferences and thus appears to be a novel node in the avian circuitry for evaluating acoustic information for mate choice. And Van der Linden A.

Our research is focused on the causes and consequences of biodiversity change. Important human causes include habitat loss and fragmentation from land cover change, climate change, and pollution. We also study how biodiversity change impacts ecosystems and the costs and benefits that arise. We translate our research into knowledge for conservation and policy. We are particularly focused on the restoration of ecological connectivity in human-dominated landscapes.

Causes and consequences of ant diversity. Determinants of geographic distribution in odonates. Biotic drivers of biological invasions. Climate change, biodiversity and northern ecosystems. Community Ecology and Biogeography Lab. Causes and consequences of ant diversity. Causes and consequences of ant diversity.

This year, the QCBS will hold its fifth annual symposium from December 10th to December 12th 2014 at the New Residence Hall. Of McGill University which was recently renovated. The first day will be dedicated to the workshop Biodiversity in the global sustainability agenda. On December 10, 2014. Of the 2014 QCBS symposium, on December 11th and 12th. QCBS WORKSHOP AND SYMPOSIUM 2014.

Cartographie des articles scientifiques sur la biodiversité. Les arbres de la ville de Montréal. Les arbres de la Ville de Montréal. Inventaire des données de terrain en biodiversité. Programmes de suivi de la biodiversité au Québec. Cartographie des articles scientifiques sur la biodiversité.

Our objective is to apply network science to design an ecological network for the lowlands of Saint-Laurence around greater Montreal. This network is designed to maintain biodiversity and ecosystem services and be resilient to expected regional climate change and land use change over the coming century.

I focus on a problem called transfer learning. It comes naturally to us, e. we use what we learned for walking when learning to run, but almost all machine learning algorithms build models from nothing.