Between 2000 and 2020, 42% of tree lines around the world crept upward, largely because of climate change. But 25% moved downhill, seemingly because of factors such as land use changes and wildfires.
mapping
Posted inNews
This Arctic Atlas Shows Where Oil and Gas Activities Overlap with Wildlife and Indigenous Communities
To slow climate change, the world must keep its fossil fuels in the ground. New maps of Arctic activities show where resources should stay put.
Posted inResearch & Developments
New USGS Tool Fills in the Gaps on U.S. Water Supply
The National Water Availability Assessment Data Companion is the first tool that integrates information about water availability in individual watersheds at a national scale.
Posted inNews
Scientists Remap Earth’s Gravity
An uncommon way of looking at the world reveals the evolution of a deep gravity hole beneath Antarctica.
Posted inNews
These Underprotected Brazilian Wetlands Store Carbon with Staggering Density
The Cerrado, largely overlooked in climate science and policy, is a critical carbon sink, according to new research.
Posted inNews
Scientists Create the First Map of Deep Earthquakes Beneath Continents
Scientists once thought Earth’s continental mantle was too weak for earthquakes. A new global map of 459 deep tremors suggests otherwise.
Posted inNews
Oozing Gas Could Be Making Stripes in Mercury’s Craters
Scientists are using new computational tools to analyze troves of old spacecraft data to better understand one of Mercury’s unsolved mysteries.
Posted inResearch Spotlights
Making a Map to Make a Difference
A new study highlights the partnership between scientists and nonscientist community members in building an interactive GIS map to show flooding risk in a Superfund site.
Posted inNews
Nationwide Soil Microbiome Mapping Project Connects Students and Scientists
Researchers and students are building a comprehensive picture of the microbial life beneath our feet.
Posted inNews
Report: 13 Great Lakes’ Worth of Water Underlies the Contiguous United States
Researchers used 1 million data points and a machine learning algorithm to estimate groundwater stores with higher resolution than ever before.