Effects of vegetation structure and landscape complexity on insect parasitism across an agricultural frontier in Argentina |
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| Institution: | 1. Institute of Regional Ecology, CONICET-National University of Tucumán, CC34, 4107 Yerba Buena, Tucumán, Argentina;2. University of Puerto Rico, Department of Environmental Sciences, College of Natural Sciences, Río Piedras Campus, San Juan, PR 00931, USA;1. Institute of Plant Sciences, Faculty of Biology and Preclinical Medicine, University of Regensburg, D-93040 Regensburg, Germany;2. Institute for Evolution and Biodiversity, Faculty of Biology, University of Münster, D-48149 Münster, Germany;1. Czech University of Life Sciences Prague, Faculty of Forestry and Wood Sciences, Kamýcká 1176, CZ-165 21 Prague, Czech Republic;2. Silva Tarouca Research Institute for Landscape and Ornamental Gardening, Květnové náměstí 391, CZ-252 43 Průhonice, Czech Republic;3. Charles University in Prague, Faculty of Science, Viničná 7, CZ-128 44 Prague, Czech Republic;1. Faculty of Land and Food Systems, University of British Columbia, Vancouver, BC, Canada;2. Department of Natural Resource Sciences, McGill University, Sainte-Anne-de-Bellevue, Quebec, Canada;3. Department of Biology, Quebec Centre for Biodiversity Science, McGill University, Montreal, QC, Canada;4. Department of Natural Resource Sciences and Bieler School of Environment, McGill University, Sainte-Anne-de-Bellevue, QC, Canada;1. GeoZentrum Nordbayern, Department of Geography and Geosciences, Friedrich-Alexander University Erlangen-Nürnberg (FAU), 91054 Erlangen, Germany;2. Department of Biogeography, BayCEER, University of Bayreuth, 95447 Bayreuth, Germany;3. Experimental Plant Ecology, Institute of Botany and Landscape Ecology, Greifswald University, D-17487 Greifswald, Germany;4. Institute of Sport Science, BayCEER, University of Bayreuth, 95447 Bayreuth, Germany;1. College of Horticulture and Plant Protection, Yangzhou University, Yangzhou 225009, China;2. State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, China;3. The Ohio State University-OARDC, Department of Entomology, Wooster, OH 44691, USA |
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| Abstract: | Insect parasitism patterns are influenced by vegetation structure and landscape complexity. Our objective was to examine the effects of vegetation structure and landscape complexity on parasitism based on direct measurements of structure and diversity indices as well as on metrics based on remote sensing using Quickbird images. We collected 2266 lepidopteran larvae and pupae, including different families and habits, to estimate parasitism, and recorded vegetation characteristics in five 100-m2 transects and 18 1 ha-plots in the dry Chaco, Northwest Argentina. We calculated landscape metrics and semivariograms in the plots from the image. The plots represented four “complexity groups”: agricultural, riparian/hedgerow, bare ground, and forest plots. Mean parasitism in the study sites was 10.7% (min: 0%, max: 23%). Parasitism was highest in agricultural plots, lowest in forest plots, and intermediate in riparian/hedgerow and bare ground plots. The landscape model explained parasitism more than the vegetation model. The landscape final model included Normalized Difference Vegetation Index (NDVI) Range, a measure of landscape heterogeneity, and Mean Shape Index, a measure of patch shape irregularity, and their interaction. The vegetation model included basal area and the Coefficient of Variation of tree density among transects, a measure of tree spatial distribution within a plot. Our results agree with previous studies that found higher parasitism in agricultural vs. non-agricultural environments in the subtropics, while riparian/hedgerow plots were important for conserving parasitism, as reported for temperate environments. We showed that under-explored tools such as the semivariogram and satellite band combinations were useful for the assessment of parasitism and that studying vegetation and landscape complexity simultaneously can help us examine mechanisms in detail. The identified variables related to high parasitism should be used for image classifications with a functional approach. |
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| Keywords: | Biocontrol Chaco NDVI Parasitism QuickBird Semivariogram |
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