Using Moran's I and GIS to study the spatial pattern of forest litter carbon density in a subtropical region of southeastern China

• Main Authors: W. J. Fu, P. K. Jiang, G. M. Zhou, K. L. Zhao
• Format: Article
• Language: English
• Published: Copernicus Publications 2014-04-01
• Series: Biogeosciences
• Online Access: http://www.biogeosciences.net/11/2401/2014/bg-11-2401-2014.pdf
• ISSN: 1726-4170; 1726-4189

Spatial pattern information of carbon density in forest ecosystem including forest litter carbon (FLC) plays an important role in evaluating carbon sequestration potentials. The spatial variation of FLC density in the typical subtropical forests in southeastern China was investigated using Moran's I, geostatistics and a geographical information system (GIS). A total of 839 forest litter samples were collected based on a 12 km (south–north) × 6 km (east–west) grid system in Zhejiang province. Forest litter carbon density values were very variable, ranging from 10.2 kg ha⁻¹ to 8841.3 kg ha⁻¹, with an average of 1786.7 kg ha⁻¹. The aboveground biomass had the strongest positive correlation with FLC density, followed by forest age and elevation. Global Moran's I revealed that FLC density had significant positive spatial autocorrelation. Clear spatial patterns were observed using local Moran's I. A spherical model was chosen to fit the experimental semivariogram. The moderate "nugget-to-sill" (0.536) value revealed that both natural and anthropogenic factors played a key role in spatial heterogeneity of FLC density. High FLC density values were mainly distributed in northwestern and western part of Zhejiang province, which were related to adopting long-term policy of forest conservation in these areas, while Hang-Jia-Hu (HJH) Plain, Jin-Qu (JQ) Basin and coastal areas had low FLC density due to low forest coverage and intensive management of economic forests. These spatial patterns were in line with the spatial-cluster map described by local Moran's I. Therefore, Moran's I, combined with geostatistics and GIS, could be used to study spatial patterns of environmental variables related to forest ecosystem.