Modeling Productivity in Mangrove Forests as Impacted by Effective Soil Water Availability and Its Sensitivity to Climate Change Using Biome-BGC

Abstract

Ecosystem dynamics and the responses to climate change in mangrove forests are poorly understood. We applied the biogeochemical process model Biome-BGC to simulate the dynamics of net primary productivity (NPP) and leaf area index (LAI) under the present and future climate conditions in mangrove forests in Shenzhen, Zhanjiang, and Qiongshan across the southern coast of China, and in three monocultural mangrove stands of two native species, Avicennia marina and Kandelia obovata, and one exotic species, Sonneratia apetala, in Shenzhen. The soil hydrological process of the model was modified by incorporating a soil water (SW) stress index to account for the impact of the effective SW availability in the coastal wetland. Our modified Biome-BGC well predicted the dynamics of NPP and LAI in the mangrove forests at the study sites. We found that the six mangrove systems differed in sensitivity to variations in the effective SW availability. At the ecosystem level, however, soil salinity alone could not entirely explain the limitation of the effective SW availability on the productivity of mangrove forests. Increasing atmospheric CO2 concentration differentially affected growth of different mangrove species but only had a small impact on NPP (<7%); whereas a doubling of atmospheric CO2 concentration associated with a 2°C temperature rise would increase NPP by 14–19% across the three geographically separate mangrove forests and by 12% to as much as 68% across the three monocultural mangrove stands. Our simulation analysis indicates that temperature change is more important than increasing CO2 concentration in affecting productivity of mangroves at the ecosystem level, and that different mangrove species differ in sensitivity to increases in temperature and CO2 concentration.