Spatial Distribution Of Aboveground Biomass Research Articles

Mortality as a key driver of the spatial distribution of aboveground biomass in Amazonian forest: results from a dynamic vegetation model

Abstract. Dynamic Vegetation Models (DVMs) simulate energy, water and carbon fluxes between the ecosystem and the atmosphere, between the vegetation and the soil, and between plant organs. They also estimate the potential biomass of a forest in equilibrium having grown under a given climate and atmospheric CO2 level. In this study, we evaluate the Above Ground Woody Biomass (AGWB) and the above ground woody Net Primary Productivity (NPPAGW) simulated by the DVM ORCHIDEE across Amazonian forests, by comparing the simulation results to a large set of ground measurements (220 sites for biomass, 104 sites for NPPAGW). We found that the NPPAGW is on average overestimated by 63%. We also found that the fraction of biomass that is lost through mortality is 85% too high. These model biases nearly compensate each other to give an average simulated AGWB close to the ground measurement average. Nevertheless, the simulated AGWB spatial distribution differs significantly from the observations. Then, we analyse the discrepancies in biomass with regards to discrepancies in NPPAGW and those in the rate of mortality. When we correct for the error in NPPAGW, the errors on the spatial variations in AGWB are exacerbated, showing clearly that a large part of the misrepresentation of biomass comes from a wrong modelling of mortality processes. Previous studies showed that Amazonian forests with high productivity have a higher mortality rate than forests with lower productivity. We introduce this relationship, which results in strongly improved modelling of biomass and of its spatial variations. We discuss the possibility of modifying the mortality modelling in ORCHIDEE, and the opportunity to improve forest productivity modelling through the integration of biomass measurements, in particular from remote sensing.

A comparison of species composition and stand structure between planted and natural mangrove forests in Shenzhen Bay, South China

Aims For assisting faster restoration of damaged or severely disturbed coastal ecosystems, selected mangrove species have been planted on previously mangrove-inhabited sites of the tropical and subtropical coasts of southern China. The objective of this study was to understand the stand dynamics of the planted mangroves and their functional traits in comparison with natural mangrove forests under similar site conditions. Methods Species composition, stand density, tree size distribution, and aboveground production were investigated along three transects in a 50year-old planted mangrove stand and three transects in an adjacent natural mangrove stand in Shenzhen Bay, South China. Measurements were made on tree distribution by species, stand structure, and aboveground biomass (AGB) distribution. Analyses were performed on the spatial patterns of tree size distribution and species association. Important Findings We found that the planted and natural mangrove stands did not differ in stand density, average diameter at breast height (DBH), species composition, and AGB. Spatial distribution of AGB and frequency at species level were also similar between the planted and natural stands. However, the traits in stand structure were more variable in the planted stand than in the natural stand, indicating higher spatiotemporal heterogeneity in the development and succession of planted mangroves. Geostatistical analyses show that both DBH and AGB were spatially auto-correlated within a specific range in the direction perpendicular to coastline. More than 60% of the variance in these attributes was due to spatial autocorrelation. The Ripley’s K-function analysis shows that the two dominant species, Kandelia obovata and Avicennia marina, clumped in broader scales in the natural stand than in the planted stand and displayed significant interspecific competition across the whole transect. It is suggested that interspecific competition interacts with spatial autocorrelation as the underlying mechanism shaping the mangrove structure. This study demonstrates that at age 50, mangrove plantations can perform similarly in stand structure, spatial arrangement of selected stand characteristics and species associations to the natural mangrove forests.

Modelling the spatial distribution of aboveground biomass based on vegetation index in a tropical forest in Bawangling, Hainan Island, South China.

Aims The biomass of tropical forests plays an important role in the global carbon cycle; however,the distribution of tropical forest biomass based on vegetation index is seldom explored. Our objectives were to evaluate relationships between biomass and vegetation indices and to determine the spatial distribution of the aboveground biomass of tropical forest in Bawangling,Hainan Island,South China. Methods Using measurements of forest biomass from 135 sample plots distributed over the study area,we correlated four vegetation indices (normalized difference vegetation index (NDVI),moisture vegetation index using Landsat's 5 (MVI5),moisture vegetation index using Landsat's band 7 (MVI7) and ratio vegetation index (RVI)) with aboveground biomass (total biomass,climax species biomass and pioneer species biomass) using the Pearson correlation method. We also developed models describing the relationships between forest aboveground biomass and vegetation indices using stepwise linear regression analysis. Three maps of biomass components were produced using the developed models,and residual maps were used to test the validity of the models. Important findings MVI7 and MVI5 are most effective for total biomass and climax species biomass,whereas NDVI and RVI seem to be good indices of pioneer species biomass. The strongly predictive percent areas for total species,climax species and pioneer species biomass models were 69.24,73.98 and 88.08,respectively. Simulated biomasses of total species and climax species were distributed in the center,north and southwest parts of the study area; however,simulated biomass of pioneer species was scattered.