NDLI: Predicting the resting sites of Eurygaster integriceps Put. (Hemiptera: Scutelleridae) using a geographic information system

Content Provider	Springer Nature Link
Author	Karimzadeh, R. Hejazi, M. J. Helali, H. Iranipour, S. Mohammadi, S. A.
Copyright Year	2014
Abstract	Sunn pest Eurygaster integriceps Puton is the most destructive insect pest of wheat and barley in Iran. This pest is a univoltine insect that feeds and reproduces in the fields for only 2–3 months of the year and spends the rest of the year in resting sites. In Sunn pest management programs, the pest populations in the fields are estimated by monitoring populations in the resting sites. The objectives of this study were to find variables associated with Sunn pest resting sites, using statistical tools and a geographic information system; and predict resting sites using these variables. This study was conducted in East Azarbaijan province of Iran. Six hundred points were sampled during a three year study. The twelve topographic and environmental variables including elevation, relative elevation, slope, aspect, north–south aspect data, landshape, slope steepness, slope configuration, topographic position, soil moisture potential, sun index and normalized difference vegetation index (NDVI) were examined. The models and variables were evaluated using corrected Akaike’s information criterion (AIC$_{C}$). NDVI, relative elevation, elevation, topographic position, soil moisture potential, north–south aspect and aspect which had high AIC$_{C}$ weight were used in the prediction model. The resting sites of Sunn pest in Marand County of East Azarbaijan province was predicted using the model obtained with the purpose of testing it. Comparing the predicted resting sites with the actual ones revealed that large parts of the predicted areas in south were in accordance with the actual resting sites in Marand. The generated prediction map for E. integriceps can have several applications. Targeted monitoring and management of overwintering populations of Sunn pest using this map will save time and money.
Starting Page	615
Ending Page	626
Page Count	12
File Format	PDF
ISSN	13852256
Journal	Precision Agriculture
Volume Number	15
Issue Number	6
e-ISSN	15731618
Language	English
Publisher	Springer US
Publisher Date	2014-04-04
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Akaike’s information criterion Prediction map Topographic variables Agriculture Soil Science & Conservation Remote Sensing/Photogrammetry Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Atmospheric Sciences
Content Type	Text
Resource Type	Article
Subject	Agricultural and Biological Sciences

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