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

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.

[1]  Andre G. Journel,et al.  Geostatistics for Natural Resources Characterization: Part 1 , 2013 .

[2]  Y. Matsuura,et al.  Carbon stock in litter, deadwood and soil in Japan’s forest sector and its comparison with carbon stock in agricultural soils , 2010 .

[3]  S. Sundarapandian,et al.  Litter production and leaf-litter decomposition of selected tree species in tropical forests at Kodayar in the Western Ghats, India , 1999 .

[4]  R. Geary,et al.  The Contiguity Ratio and Statistical Mapping , 1954 .

[5]  Francisco Cabrera,et al.  Spatial variability of the chemical characteristics of a trace-element-contaminated soil before and after remediation , 2006 .

[6]  Geoffrey M. Jacquez,et al.  Spatial Cluster Analysis , 2008 .

[7]  C. Beijing.  Forest Carbon Storage in China Estimated Using Forestry Inventory Data , 2011 .

[8]  Noel A Cressie,et al.  Statistics for Spatial Data, Revised Edition. , 1994 .

[9]  P. Burrough,et al.  Principles of geographical information systems , 1998 .

[10]  A. Getis.  The Analysis of Spatial Association by Use of Distance Statistics , 2010 .

[11]  Huang Cheng,et al.  The litter of Pinus massoniana ecological public-welfare forest in Zhejiang Province and its relationship with the community characters , 2005 .

[12]  Yunqiang Wang,et al.  Spatial Variability of Soil Organic Carbon in a Watershed on the Loess Plateau , 2009 .

[13]  Ricardo A. Olea,et al.  Geostatistical glossary and multilingual dictionary , 1991 .

[14]  Chaosheng Zhang,et al.  Use of local Moran's I and GIS to identify pollution hotspots of Pb in urban soils of Galway, Ireland. , 2008, The Science of the total environment.

[15]  A. Konopka,et al.  FIELD-SCALE VARIABILITY OF SOIL PROPERTIES IN CENTRAL IOWA SOILS , 1994 .

[16]  L. Anselin.  Local Indicators of Spatial Association—LISA , 2010 .

[17]  K. Harries,et al.  Extreme spatial variations in crime density in Baltimore County, MD , 2006 .

[18]  Yong Li,et al.  Can the spatial prediction of soil organic matter contents at various sampling scales be improved by using regression kriging with auxiliary information , 2010 .

[19]  Fan Jing-yun,et al.  Dynamic forest biomass carbon pools in China and their significance , 2001 .

[20]  J. Tappeiner,et al.  BIOMASS AND NUTRIENT CONTENT OF , 2016 .

[21]  A. Meyer.  Economics Of Climate Change , 1995, Nature.

[22]  P. Moran.  Notes on continuous stochastic phenomena. , 1950, Biometrika.

[23]  R. Kolka,et al.  Long-term management impacts on carbon storage in Lake States forests , 2011 .

[24]  Timothy C. Coburn,et al.  Geostatistics for Natural Resources Evaluation , 2000, Technometrics.

[25]  Chaosheng Zhang,et al.  Spatial variation of soil test phosphorus in a long-term grazed experimental grassland field , 2010 .

[26]  Yun-qiang Wang,et al.  Effect of environmental factors on regional soil organic carbon stocks across the Loess Plateau region, China , 2011 .

[27]  Chaosheng Zhang,et al.  Using Moran's I and geostatistics to identify spatial patterns of soil nutrients in two different long-term phosphorus-application plots , 2011 .

[28]  T Tango,et al.  A class of tests for detecting 'general' and 'focused' clustering of rare diseases. , 1995, Statistics in medicine.

[29]  季碧勇 Ji Biyong,et al.  Spatial distribution of forest carbon in Zhejiang Province with geostatistics based on CFI sample plots , 2012 .

[30]  Björn Berg,et al.  Plant Litter: Decomposition, Humus Formation, Carbon Sequestration , 2003 .

[31]  W. Wiebold,et al.  Different Techniques to Identify Management Zones Impact Nitrogen and Phosphorus Sampling Variability , 2003 .

[32]  H. Du,et al.  The carbon storage in moso bamboo plantation and its spatial variation in Anji County of southeastern China , 2014, Journal of Soils and Sediments.

[33]  D. Cox,et al.  An Analysis of Transformations , 1964 .

[34]  Richard H. Waring,et al.  Forest Ecosystems: Concepts and Management. , 1987 .

[35]  G. McCarty,et al.  SPATIAL VARIABILITY OF SOIL PHOSPHOROUS LEVELS BEFORE AND AFTER POULTRY LITTER APPLICATION , 2006 .

[36]  R. Lark,et al.  Geostatistics for Environmental Scientists , 2001 .

[37]  Noel A. C. Cressie,et al.  Statistics for Spatial Data: Cressie/Statistics , 1993 .

[38]  Xingyi Zhang,et al.  Spatial Variability of Nutrient Properties in Black Soil of Northeast China , 2007 .

[39]  M. Harmon,et al.  Ecology of Coarse Woody Debris in Temperate Ecosystems , 1986 .

[40]  E. Sayer.  Using experimental manipulation to assess the roles of leaf litter in the functioning of forest ecosystems , 2005, Biological reviews of the Cambridge Philosophical Society.

[41]  R. Spiers,et al.  Variability in Contamination by Heavy Metals: Sampling Implications , 2000 .

[42]  J. Tu,et al.  Examining spatially varying relationships between land use and water quality using geographically weighted regression I: model design and evaluation. , 2008, The Science of the total environment.

[43]  Lena Vogler.  The Handbook Of Geographic Information Science , 2016 .

[44]  U. Sainju,et al.  Soil carbon and nitrogen sequestration as affected by long-term tillage, cropping systems, and nitrogen fertilizer sources , 2008 .

[45]  Andrew K. Skidmore,et al.  Environmental Modelling with GIS and Remote Sensing , 2010 .

[46]  Xiaojun Xu,et al.  Implications of ice storm damages on the water and carbon cycle of bamboo forests in southeastern China , 2013 .

[47]  N. Stern.  The Economics of Climate Change: Implications of Climate Change for Development , 2007 .

[48]  Margaret A. Oliver,et al.  Comparing sampling needs for variograms of soil properties computed by the method of moments and residual maximum likelihood , 2007 .

[49]  R. Reese.  Geostatistics for Environmental Scientists , 2001 .