Center for Tropical Forest Science
CTFS Home |
Asia Program |
SIGEO |
About CTFS |
Research |
Data Sets & Methods |
Publications |
Partners |
Grants & Training |
Staff |
Contact Us |
Asian Plots |
Climate Change |
Global Forest Observatories |
Training Scientists |
A Global Program for Long-Term, Large-Scale Forest Research
The Center for Tropical Forest Science (CTFS) of the Arnold Arboretum and Smithsonian Tropical Research Institute is a global network of forest research plots committed to studying the ecosystem functions and diversity of tropical and temperate forests. The multi-institutional network comprises 28 tropical research plots across Latin America, Africa, Asia, and the US; four temperate plots in North America; and one temperate plot in China. CTFS monitors the growth and survival of some 3 million trees of over 6,500 species.
CTFS conducts long-term, large-scale research on forests around the world to
- Increase scientific understanding of forest ecosystems,
- Inform sustainable forest management and natural-resource policy, and
- Build capacity in forest science.
Ecologists at the Smithsonian Tropical Research Institute established the first plot on Barro Colorado Island (BCI), Panama, in 1980. There, they pioneered long-term tree-census techniques that scientists replicated throughout the tropics, creating a network of forest research plots that would eventually become the Center for Tropical Forest Science. Before 1980, scientists had never attempted to measure tropical forests so intensively and at such a large scale. Today, the scale and intensity of the CTFS research program remain unprecedented in forest science.
A Network Unified by Methodology
Common plot structure and scientific methodology unify the CTFS network. In each plot, typically 25 to 50 hectares, all free-standing trees with a diameter at breast height of at least 1 cm are tagged, measured, identified to species, and recensused approximately every five years. Because each plot follows the same methodology, scientists can directly compare data collected from different forests around the world and detect patterns that would otherwise be impossible to recognize.