A Global Program for Long-Term Large-Scale Forest Research
The Center for Tropical Forest Science (CTFS) is a global network of forest research plots committed to the study of tropical and temperate forest function and diversity. The multi-institutional network comprises more than forty forest research plots across the Americas, Africa, Asia, and Europe, with a strong focus on tropical regions. CTFS monitors the growth and survival of about 4.5 million trees of approximately 8,500 species.
CTFS conducts long-term, large-scale research on forests around the world to:
• Increase scientific understanding of forest ecosystems
• Guide sustainable forest management and natural-resource policy
• Monitor the impacts of climate change
• 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
CTFS plots involve hundreds of scientists from more than 75 institutions worldwide. Individual forest plots are led and managed in each country by one or more partner institutions. CTFS coordinates plots in Asia through partnerships with host-country institutions and the Arnold Arboretum of Harvard University.
Common plot structure and scientific methodology unify the CTFS network. In each plot, which are 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.