Multiscale analysis of the relationship between topography and aboveground biomass in the tropical rainforests of Sulawesi, Indonesia

被引:18
作者
Propastin, Pavel [1 ]
机构
[1] Univ Gottingen, Dept Cartog, GIS & Remote Sensing, Gottingen, Germany
关键词
biomass; altitudinal gradient; topography; GWR; non-stationarity; scale-dependency; GEOGRAPHICALLY-WEIGHTED REGRESSION; SPATIAL NONSTATIONARITY; ALTITUDINAL GRADIENT; MOUNT-NORIKURA; SCALE; UNCERTAINTY; VEGETATION;
D O I
10.1080/13658816.2010.518570
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This article aims to explore spatial and altitudinal non-stationarity in the relationship between aboveground biomass (AGB) of tropical rainforest in Sulawesi (Indonesia) and topography. An autoregressive model through a geographically weighted regression (GWR) framework was used to study the relationship between ground-measured values of AGB and altitude above sea level at 85 sampling plots. The relationships between AGB and altitude were found to be significantly spatially variable and scale-dependent. The results also suggested high altitudinal variability in the examined relationship. Both the strength of the AGB-altitude relationship (rho) and the altitudinal gradient (alpha) showed a high changeability in the horizontal and vertical dimensions. The complex spatio-altitudinal patterns in the GWR-based local estimates of the rho and alpha parameters gave rise to both spatial and altitudinal variations in the scale effects. The approach presented in this study enables finding the most appropriate scale for data analysis within different altitudinal bands. The study found that the changes of the gradient alpha along altitudinal transects relate to prevalent environmental conditions observed at different altitudes, whereas the optimal bandwidth was related to the terrain surface heterogeneity.
引用
收藏
页码:455 / 472
页数:18
相关论文
共 36 条
[1]   Structure, composition and species diversity in an altitude-substrate matrix of rain forest tree communities on Mount Kinabalu, Borneo [J].
Aiba, S ;
Kitayama, K .
PLANT ECOLOGY, 1999, 140 (02) :139-157
[2]  
[Anonymous], ECOLOGY INDONESIA SE
[3]   DETERMINING SPECIES RESPONSE FUNCTIONS TO AN ENVIRONMENTAL GRADIENT BY MEANS OF A BETA-FUNCTION [J].
AUSTIN, MP ;
NICHOLLS, AO ;
DOHERTY, MD ;
MEYERS, JA .
JOURNAL OF VEGETATION SCIENCE, 1994, 5 (02) :215-228
[4]   Some notes on parametric significance tests for geographically weighted regression [J].
Brunsdon, C ;
Fotheringham, AS ;
Charlton, M .
JOURNAL OF REGIONAL SCIENCE, 1999, 39 (03) :497-524
[5]   Geographically weighted regression: A method for exploring spatial nonstationarity [J].
Brunsdon, C ;
Fotheringham, AS ;
Charlton, ME .
GEOGRAPHICAL ANALYSIS, 1996, 28 (04) :281-298
[6]   Spatial variations in the average rainfall-altitude relationship in Great Britain: An approach using geographically weighted regression [J].
Brunsdon, C ;
McClatchey, J ;
Unwin, DJ .
INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2001, 21 (04) :455-466
[7]   Spatial nonstationarity and autoregressive models [J].
Brunsdon, C ;
Fotheringham, AS ;
Charlton, M .
ENVIRONMENT AND PLANNING A-ECONOMY AND SPACE, 1998, 30 (06) :957-973
[8]   Tree allometry and improved estimation of carbon stocks and balance in tropical forests [J].
Chave, J ;
Andalo, C ;
Brown, S ;
Cairns, MA ;
Chambers, JQ ;
Eamus, D ;
Fölster, H ;
Fromard, F ;
Higuchi, N ;
Kira, T ;
Lescure, JP ;
Nelson, BW ;
Ogawa, H ;
Puig, H ;
Riéra, B ;
Yamakura, T .
OECOLOGIA, 2005, 145 (01) :87-99
[9]  
Coops N., 1998, Australian Forestry, V61, P244
[10]   Spatial nonstationarity and scale-dependency in the relationship between species richness and environmental determinants for the sub-Saharan endemic avifauna [J].
Foody, GM .
GLOBAL ECOLOGY AND BIOGEOGRAPHY, 2004, 13 (04) :315-320