Climate extremes hinder early development in young birds
Peer-Reviewed Publication
Updates every hour. Last Updated: 20-May-2026 18:15 ET (20-May-2026 22:15 GMT/UTC)
New research from the University of Oxford published today (11 March) shows that cold snaps and heavy rain can stunt growth and reduce survival prospects in UK great tit nestlings. However, breeding earlier within a season appears to buffer against many of these weather-related effects.
As part of the Horizon Europe project Capable, researchers surveyed around 19’000 people from 13 European countries on 15 specific climate proposals in the summer of 2024. The aim was to determine how much support there is for the individual proposals and which factors influence opinions.
To this end, participants were asked specifically about the reasons behind their decisions. The analysis reveals that costs are the biggest hurdle to the acceptance of climate regulations among the population.
The innovative methodology of the study can be used in future long-term studies to better understand and track the political decisions of the population.
The tidal environment of mangrove forests serves as nurseries for many fish species. Researchers at the University of Gothenburg have measured carbon dioxide and oxygen levels in 23 of world’s mangrove areas. The study sends out a warning that these ecosystems are increasingly threatened as sea temperatures continue to rise.
Climate change since the 1950s has doubled the amount of time per year that millions of people around the world must endure heat so extreme that everyday physical activities cannot be done safely, a new study concludes. Instead of relying on simple measures of heat danger, the researchers used a modeling approach to estimate how much physical activity people of varying ages could perform in different ranges of heat and humidity without their core body temperature rising uncontrollably. Several areas across the South and Southwestern U.S. show hundreds of hours a year of severe limitations.
Computer scientists and weather scientists have taken the first steps toward creating an AI agent capable of analyzing and answering questions in natural language, such as English, about data from AI-driven weather and climate forecasting models. Recently, models driven by AI and deep learning have considerably improved weather forecasting. But analyzing the resulting data remains difficult and time-consuming. A main issue is that these types of AI models are not able to describe their findings in plain language. A secondary issue is that these models are not able to reason about text information, such as meteorology reports and weather bulletins. The UC San Diego research team aims to address both.