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JOURNAL OF DESERT RESEARCH  2013, Vol. 33 Issue (4): 1071-1077    DOI: 10.7522/j.issn.1000-694X.2013.00151
Biology and Soil     
Application of GAM Approach on Pattern of Grasshoppers’ Geographical Distribution: A case study in the upper reaches of Heihe River
LI Li-li, ZHAO Cheng-zhang, YIN Cui-qin, WANG Da-wei, ZHANG Jun-xia
College of Geography and Environment Science/Research Center of Wetland Resources Protection and Industrial Development Engineering of Gansu Provicnce, Northwest Normal University, Lanzhou 730070, China
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Abstract  

Combining the field sampling-based regression analysis of community versus habitat attributes and GIS supported spatial prediction of topography factors is a new approach for the quantitative study of insect-environment relationship. As one of the non-parameter model types, Generalized Additive Models (GAM) is an efficient tool in regression analysis-spatial prediction, partly for its flexibility to a wide variety of data types. A spatially explicit database for environment factors that frequently rely on digitalized elevation model is the requisite background for spatial prediction. In this study, we employed the non-parametric GAM model to explore the potential distribution of the grasshopper richness in the upper reaches of Heihe River, western China. For each data requirement of GAM, 6 topographic indices were extracted and analyzed. The results showed that: (1) The structure and deviation square values of the models were different for different ecospecies indices, so were the model stability, indicating their differences in response to the gradients of topographic indices. (2) The relationship between habitat cosmopolitan species and topographic indices was not significant, and only local topography affected the density; The relationship between habitat common living and topographic indices was closer than between habitat cosmopolitan species and topographic indices, the most prominent effects came from profile of the micro-topography and the elevation in large scale; habitat rare species distribution pattern relied on topographic indices most closely, and the most prominent effects came from elevation, plan and aspect. (3) The predictions of the density patterns of rare species passed the validation with an independent sampling data, that of common living succeeded partially, but the prediction for the density of cosmopolitan species failed. (4) Efficient and adequate predictive variables were crucial for the interpretative capability of the models. The environmental factors and random factor were significantly correlated with those of accuracy and maneuverability of valuation for model and algorithm of the tree-based method. So the GAM model function for the probability species richness made sufficiently use of topographic index information, and realized multiple factors.

Key words:  grassland      grasshoppers      upper reaches of Heihe River      generalized additive model (GAM)      spatial pattern      prediction     
Received:  02 March 2012      Published:  28 April 2012
ZTFLH:  Q968.1  

Cite this article: 

LI Li-li, ZHAO Cheng-zhang, YIN Cui-qin, WANG Da-wei, ZHANG Jun-xia. Application of GAM Approach on Pattern of Grasshoppers’ Geographical Distribution: A case study in the upper reaches of Heihe River. JOURNAL OF DESERT RESEARCH, 2013, 33(4): 1071-1077.

URL: 

http://www.desert.ac.cn/EN/10.7522/j.issn.1000-694X.2013.00151     OR     http://www.desert.ac.cn/EN/Y2013/V33/I4/1071

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