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Updated: Mar 26, 2026

Modification and Application of a Leaf Blower-vac for Field Sampling of Arthropods
Published on: August 10, 2016
Designing Standardized and Optimized Surveys to Assess Invertebrate Biodiversity in Tropical Irrigated Rice Using
Kenneth G Schoenly1, Alberto T Barrion2
1Department of Biological Sciences, California State University, Stanislaus, 1 University Circle, Turlock, CA 95382 (kschoenly@csustan.edu), kschoenly@csustan.edu.
Abstract:
Insect pest management depends on simple, rapid, and reliable sampling methods that should also be standardized and optimized. We tested structured inventory, community characterization, and sampling optimization approaches on the invertebrate fauna of Philippine irrigated rice, undisrupted by pesticides, using seven field methods and species richness models. Canopy and floodwater invertebrates were intensively and repetitively sampled from 600 quadrats (∼0.1-m(2) planar area) over dry and wet cropping seasons in one field at the International Rice Research Institute in the Philippines. In the canopy, pooled counts from D-Vac and plant dissections (PD) on the same rice hills ("absolute methodology") were compared with three other methods (i.e., FARMCOP, Blower-Vac, sweep-net), while, in the floodwater, the area collector ("absolute methodology") was compared with three other methods (i.e., FARMCOP, Blower-Vac, strainer-net). Overall, 25 and 50% of the observed richness of canopy and floodwater taxa, respectively, were caught by all four methods. Estimated inventory completeness for the canopy and floodwater averaged 82 and 98%, respectively, after all methods were pooled. To maximize observed richness, optimization results for the canopy recommended allocating the highest sampling effort to D-Vac and PD, followed by the Blower-Vac, whereas the area collector should be assigned the highest sampling effort in the floodwater, followed by the strainer-net or Blower-Vac. Our results suggest that structured inventory and species richness models are useful tools for setting optimization criteria and stopping rules for sampling crop-invertebrate assemblages based on inventory completeness and for enabling more informative biodiversity comparisons.
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