Forest carbon stocks overestimated for half-century due to flawed formula

Oct. 16 (UPI) -- Climate scientists have been overestimating the amount of carbon stored in Earth's forests for 50 years.

According to a new study published this week in the American Journal of Botany, a flawed tree density formula is to blame for the inaccurate carbon stock estimates. Forest carbon stocks are likely 4 to 5 percent smaller.

Since the 1940s, scientists with the French research organization CIRAD have been cataloguing thousands of tree species. Forest ecologists and climate scientists rely on the database for all kinds of tree- and climate-related modeling efforts.

The CIRAD catalogue includes data on the density of tree specimens and species measured at 12 percent moisture, the average wood moisture content in temperate regions.

But as scientists reported in their new paper on the topic: "It is convenient for ecological purposes to convert this measure to basic wood density."

While studying the formula used to convert densities measure at 12 percent moisture to a measure of basic wood density -- which scientists rely on to estimate tree dry biomass for large-scale modeling efforts -- CIRAD scientists discovered a flaw.

"To start with, I thought we had made a mistake in our calculations or that there was some uncertainty surrounding measurement of the relevant data," Paul Sabatier, researcher at the University of Toulouse, said in a news release. "It was not easy to cast doubt on a formula that had been widely accepted for years and quoted in several scientific articles."

Sabatier and his colleagues at CIRAD developed a new more reliable conversion formula. They used the formula to update the global wood density database. The correction suggests forest carbon stocks have been regularly overestimated by 4 to 5 percent.

"This new conversion factor should be used to derive basic wood densities in global wood density databases," researchers wrote in their paper. "Its use would prevent overestimating global forest carbon stocks and allow predicting better tree species community dynamics from wood density."