Topic: climate change

The Science Show examines mineral nodules formed around fossil shark teeth on the deep-sea floor and the ecological risks of exploiting them. The programme also considers plant responses to climate change, debates over introduced species, and the contributions and limitations of three influential scientists.

Toni Lyn Morelli and Alexej Sirén discuss how climate change alters the geographical distribution of species. As habitats change, movement can offer plants and animals a route to persistence, but it also reshapes ecological relationships. The episode examines these shifts and their implications for conservation and the communities that share affected environments.

2024 BACN Early-Career Prize Lecture Many of our decisions affect other people. Our choices can decelerate climate change, stop the spread of infectious diseases, and directly help or harm others. Prosocial behaviours – decisions that help others – could contribute to reducing the impact of these challenges, yet their computational and neural mechanisms remain poorly understood. I will present recent work that examines prosocial motivation, how willing we are to incur costs to help others, prosocial learning, how we learn from the outcomes of our choices when they affect other people, and pro

Bjørn Samset discusses the consequences of greenhouse-gas emissions and pathways for addressing climate change. Conversation in Norwegian.

Dag Hessen discusses environmental tipping points and the connections between climate change and biodiversity loss. Conversation in Norwegian.

Climate change is one of our generation's greatest challenges, with increasingly severe consequences on global ecosystems and populations. Machine Learning has the potential to address many important challenges in climate change, from both mitigation (reducing its extent) and adaptation (preparing for unavoidable consequences) aspects. To present the extent of these opportunities, I will describe some of the projects that I am involved in, spanning from generative model to computer vision and natural language processing. There are many opportunities for fundamental innovation in this field, ad

Multi-agent reinforcement learning (MARL) has recently shown great promise as an approach to networked system control. Arguably, one of the most difficult and important tasks for which large scale networked system control is applicable is common-pool resource (CPR) management. Crucial CPRs include arable land, fresh water, wetlands, wildlife, fish stock, forests and the atmosphere, of which proper management is related to some of society’s greatest challenges such as food security, inequality and climate change. This talk will consist of three parts. In the first, we will briefly look at clima