COS 112-4 - Predicting the upper bounds of aboveground forest biomass across climatic gradients

Wednesday, August 8, 2012: 2:30 PM
E145, Oregon Convention Center
Shengbin Chen, Nanjing Institute of Environmental Sciences, Ministry of Environmental Protection, Nanjing, China and Zhiyun Ouyang, State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China
Background/Question/Methods

Forests are recognized as the most important carbon pool of terrestrial ecosystems. How to estimate the carbon capacity of forests is an important research issue for ecologists. Some authors used old-growth forests with stand age > 300 years to estimate the upper bounds of carbon storage. Unfortunately, few old-growth forests remain; the upper bounds of forest biomass across climatic gradients are not well understood. We assume that aboveground biomass (AGB) of forest is controlled by the combined effect of the amount and ratio of resources (water and energy). Since forests differ in stand age (SA), the amounts of received resources are the products of annual energy and water input and stand age. If we can build a model with water, energy and SA, and set SA to be 300 years, then, we can predict the upper bounds of AGB (UBAGB) across climatic gradient. To this end, we collected 1018 forest plots with the data on coordinates, AGB, and SA in Eastern China. The data of mean annual temperature (TEM, K) and annual precipitation (PRE, mm) were obtained from WorldClim (http://www.worldclim.org/). Multiple regression analyses were performed with ln-transformed data.

Results/Conclusions

PRE was the best single predictor (R2 = 26.4%), followed by SA (R2 = 22.9%), and TEM (R2 = 3.8%). The amount of resource (TEM×PRE×SA) explained more variance in AGB (R2 = 59.3%) than the ratio of resource (TEM/PRE) (R2 = 27.6%), and both of them jointly explained 62.1% of the spatial variance in AGB. UBAGB across a wide climatic gradients were predicted when SA = 300 years. We found that UBAGB were generally higher in tropical and subtropical areas than temperature and cold temperature areas. This model can be easily applied since it needs only three parameters (TEM, PRE, SA), and can predict the impact of changes in climatic conditions and land uses on AGB and UBAGB by just altering TEM, PRE and SA. Our model has important implications for forest restoration and carbon trade.