caa a22 4500 475750950 CHVBK 20180406123523.0 cr unu---uuuuu 170329e20000701xx s 000 0 eng 10.1023/A:1009802819390 doi (NATIONALLICENCE)springer-10.1023/A:1009802819390 Fairbanks Dean CSIR Division of Water, Environment and Forestry, 0001, Pretoria, South Africa aut Physio-climatic classification of South Africa's woodland biome [Elektronische Daten] [Dean Fairbanks] In an effort to develop more holistic ecosystem approaches to resource assessment and management, landscapes need to be stratified into homogeneous geographic regions. These regions can then be used in a monitoring framework to develop reliable estimates of ecosystem productivity. A regional characterization of the woodland biome has been developed for South Africa, delineated by satellite imagery and using environmental data and a rigorous statistical methodology. Distribution maps of key environmental variables are analyzed by factor analysis, an iterative clustering technique and maximum likelihood classification to quantify and identify homogeneous physio-climatic units. A spatial clustering technique was used to identify regions, which are statistically different with regard to five physiographic, climatic and edaphic variables deemed important within southern African savanna woodlands. The woodland biome of South Africa at 1km resolution was successively divided. Thirty year mean monthly temperature, total plant-available water balance of soil, elevation, landscape topographic position, and landscape soil fertility were used as input classification variables. The map data were submitted to a factor analysis and varimax axis rotation. The factor analysis removes correlations from the input variables, reduces the dimensionality, and normalizes the axis measurements. A cluster analysis was performed on the three principal factor scores using a modified iterative optimization clustering procedure to determine the finest level of classes statistically permitable. Twenty-seven identified unimodal cluster signatures were then submitted to a maximum likelihood classification where the statistical probability of the GIS cell assignment is carried out to determine class membership. The final map of custom physio-climatic regions is described, and these custom regions are compared with a vegetation potential map of the woodland types identified in the South African summer rainfall zone. Kluwer Academic Publishers, 2000 Abiotic variables nationallicence Clustering nationallicence Ecoregions nationallicence GIS nationallicence Principal Component Analysis nationallicence Savannas nationallicence South Africa nationallicence Plant Ecology Kluwer Academic Publishers 149/1(2000-07-01), 71-89 1385-0237 149:1<71 2000 149 11258 https://doi.org/10.1023/A:1009802819390 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1023/A:1009802819390 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Fairbanks Dean CSIR Division of Water, Environment and Forestry, 0001, Pretoria, South Africa aut NATIONALLICENCE 773 0- Plant Ecology Kluwer Academic Publishers 149/1(2000-07-01), 71-89 1385-0237 149:1<71 2000 149 11258 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer