Dynamic treeline and cryosphere response to pronounced mid-Holocene climatic variability in the US Rocky Mountains.

Climate-driven changes in high-elevation forest distribution and reductions in snow and ice cover have major implications for ecosystems and global water security. In the Greater Yellowstone Ecosystem of the Rocky Mountains (United States), recent melting of a high-elevation (3,091 m asl) ice patch exposed a mature stand of whitebark pine () trees, located ~180 m in elevation above modern treeline, that date to the mid-Holocene (c. 5,950 to 5,440 cal y BP).

The 1831 CE mystery eruption identified as Zavaritskii caldera, Simushir Island (Kurils).

Polar ice cores and historical records evidence a large-magnitude volcanic eruption in 1831 CE. This event was estimated to have injected ~13 Tg of sulfur (S) into the stratosphere which produced various atmospheric optical phenomena and led to Northern Hemisphere climate cooling of ~1 °C. The source of this volcanic event remains enigmatic, though one hypothesis has linked it to a modest phreatomagmatic eruption of Ferdinandea in the Strait of Sicily, which may have emitted additional S through magma-crust interactions with evaporite rocks.

Pan-European atmospheric lead pollution, enhanced blood lead levels, and cognitive decline from Roman-era mining and smelting.

Ancient texts and archaeological evidence indicate substantial lead exposure during antiquity that potentially impacted human health. Although lead exposure routes were many and included the use of glazed tablewares, paints, cosmetics, and even intentional ingestion, the most significant for the nonelite, rural majority of the population may have been through background air pollution from mining and smelting of silver and lead ores that underpinned the Roman economy. Here, we determined potential health effects of this air pollution using Arctic ice core measurements of Roman-era lead pollution, atmospheric modeling, and modern epidemiology-based relationships between air concentrations, blood lead levels (BLLs), and cognitive decline.

An evaluation of a checklist in musculoskeletal radiographic image interpretation when using artificial intelligence.

Introduction: Artificial intelligence (AI) is being used increasingly in image interpretation tasks. Human reliance on technology and bias can cause decision errors. A checklist, used with the AI to mitigate against such biases, may optimise the use of AI technologies and promote good decision hygiene.