A new study uses data from NASA’s PACE satellite to demonstrate a novel method for assessing global plant health. Led by UMBC’s Karl F. Huemmrich, the research leverages PACE’s Ocean Color Instrument to monitor plant responses, as indicated by reflectance from their leaves, to environmental changes like water availability and temperature. Validated against U.S. ground measurements, the technique accurately tracks plant productivity across diverse ecosystems without relying on weather data. The findings will enhance carbon sequestration tracking and early stress detection, offering a cost-effective way to monitor global ecosystems and support conservation and agriculture.

Following deforestation, tropical forests with healthy populations of seed-dispersing animals can absorb up to four times more carbon than similar forests with fewer seed-dispersing animals, according to an MIT study.

DFG to honour Katharina Seeger and Taina Marcos Lima Pinho in Göttingen this September

Researchers have devised a new machine learning method to improve large-scale climate model projections and demonstrated that the new tool makes the models more accurate at both the global and regional level. This advance should provide policymakers with improved climate projections that can be used to inform policy and planning decisions.