Predicting spatio-temporal Culicoides imicola distributions in Spain based on environmental habitat characteristics and species dispersal

被引:10
作者
Peters, J. [1 ]
Waegeman, W. [1 ]
Van Doninck, J. [2 ]
Ducheyne, E. [3 ]
Calvete, C. [4 ]
Lucientes, J. [5 ]
Verhoest, N. E. C. [2 ]
De Baets, B. [1 ]
机构
[1] Univ Ghent, Dept Math Modelling Stat & Bioinformat, KERMIT, B-9000 Ghent, Belgium
[2] Univ Ghent, Dept Forest & Water Management, Lab Hydrol & Water Management, B-9000 Ghent, Belgium
[3] Avia GIS, B-2980 Zoersel, Belgium
[4] Gobierno Aragon, Unidad Sanidad & Prod Anim, CITA, Zaragoza 50059, Spain
[5] Univ Zaragoza, Dept Patol Anim, Zaragoza 50071, Spain
关键词
Species dispersal; Species distribution model (SDM); Random Forests; Model testing; Variable importance; MODIS; Bluetongue; Veterinary epidemiology; BLUETONGUE VIRUS VECTORS; SPATIAL AUTOCORRELATION; CLIMATE-CHANGE; SEASONAL DISTRIBUTION; OBSOLETUS COMPLEX; RANDOM FORESTS; BITING MIDGES; SOIL-MOISTURE; MODELS; ABUNDANCE;
D O I
10.1016/j.ecoinf.2014.05.006
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
The use of distance variables expressing the likelihood of species occurrence at a given site in relation to the distance to observed species presence is demonstrated to improve species distribution models, especially when combined with environmental variables which relate species occurrence to the environmental habitat characteristics. In this study we developed models to predict the spatio-temporal distribution of Culicoides imicola, which is the main transmission vector for the bluetongue virus in the Mediterranean region. We investigated (i) the importance of the environmental habitat characterization by means of bioclimatic variables, (ii) the effect of different distance variables to model the dispersal process, and (iii) the suitability of two different parameter identification procedures to determine the distance variables for species distribution modeling. Results showed that niche-based species distribution models, which only use environmental data, could estimate the occurrence of Culicoides imicola accurately, given that environmental data of the period of high species abundance (April until October) was included. The use of these models may therefore be hampered for predictive risk assessment aiming to estimate the probabilities and magnitude of undesired effects caused by the occurrence of C. imicola. Species distribution models accounting for species dispersal in addition to the environmental habitat characteristics, i.e. hybrid models, did provide accurate predictions of C. imicola distributions well before the onset of the season of high species abundance. A Gaussian or negative exponential function of the distance to presence locations was most suitable to model insect dispersal. The enhanced predictive capacity of these models potentially leads towards an increased model applicability in risk assessment and disease control. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:69 / 80
页数:12
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