Acoustic Estimation of Infestations and Population Densities of White Grubs (Coleoptera: Scarabaeidae) in Turfgrass

Abstract

Incidental sounds produced by Phyllophaga crinita (Burmeister) and Cyclocephala lurida (Bland) (Coleoptera: Scarabaeidae) white grubs were monitored with single- and multiple-sensor acoustic detection systems in turf fields and golf course fairways in Texas. The maximum detection range of an individual acoustic sensor was measured in a greenhouse as approximately the area enclosed in a 26.5-cm-diameter perimeter (552 cm2). A single-sensor acoustic system was used to rate the likelihood of white grub infestation at monitored sites, and a four-sensor array was used to count the numbers of white grubs at sites where infestations were identified. White grub population densities were acoustically estimated by dividing the estimated numbers of white grubs by the area of the detection range. For comparisons with acoustic monitoring methods, infestations were assessed also by examining 10-cm-diameter soil cores collected with a standard golf cup-cutter. Both acoustic and cup-cutter assessments of infestation and estimates of white grub population densities were verified by excavation and sifting of the soil around the sensors after each site was monitored. The single-sensor acoustic method was more successful in assessing infestations at a recording site than was the cup-cutter method, possibly because the detection range was larger than the area of the soil core. White grubs were recovered from >90% of monitored sites rated at medium or high likelihood of infestation. Infestations were successfully identified at 23 of the 24 sites where white grubs were recovered at densities >50/m2, the threshold for economic damage. The four-sensor array yielded the most accurate estimates of the numbers of white grubs in the detection range, enabling reliable, nondestructive estimation of white grub population densities. However, tests with the array took longer and were more difficult to perform than tests with the single sensor.

Temporal and spatial dynamics in soil acoustics and their relation to soil animal diversity

“…Only a few studies have addressed ecoacoustics in soils, and these mainly focused on physical phenomena such as the movement of water fronts through the pore system [ 18 ] or changes in the structure of the soil matrix [ 19 ]. Other initial studies have focused on soil biophonies and attempted to detect soil pests acoustically [ 20 ], have investigated acoustic emissions of insects that use the substrate (plant surfaces and soils) for vibratory communication [ 21 ] or addressed the biological activity related to earthworms [ 22 ]. By contrast, audio recordings belowground with a restricted analyzable spectrum and focusing on a broad spectrum of soil animals have never been analyzed before.…”

New experimental techniques for studying root herbivores.

“…Acoustic technology, with a long history of use for the detection of hidden insect infestations in food and wood, has considerable potential for addressing important questions involving the physiology, behaviour, and ecology of root feeding insects (see review by Johnson et al, 2007). In the last few years, several different types of sensors, including microphones (Mankin et al, 2000;Zhang et al, 2003a), accelerometers (Mankin et al, 2001), piezoelectric probes (Mankin and Lapointe, 2003;Mankin and Fisher, 2007), and geophones (Mankin and Benshemesh, 2006) have been tested successfully in detection and monitoring applications. Microphones and accelerometers provide the most easily interpretable signals in low background noise, but the signals from piezoelectric sensors are inexpensive to amplify and easily filtered to reduce background noise.…”

Non‐invasive techniques for investigating and modelling root‐feeding insects in managed and natural systems

“…Although X‐ray microtomography offers a novel laboratory based approach, advances have also been made in development of field techniques based on acoustic detection. Acoustic technology has been considered in multiple applications for its potential to detect hidden infestations of insects in food (Brain, 1924; Adams et al , 1953; Vick et al , 1988), wood (Fujii et al , 1990; Scheffrahn et al , 1993; Lemaster et al , 1997) and, more recently, in the soil (Mankin et al , 2000, 2001; Zhang et al , 2003a). Several different microphone and accelerometer systems have been used successfully to detect sounds generated by subterranean larvae in citrus groves (Mankin et al , 2001), forage fields (Brandhorst‐Hubbard et al , 2001) and nursery containers (Mankin & Fisher, 2002a, 2002b).…”

“…The most recent refinements in acoustic techniques have primarily been in reductions of cost and in development of signal processing techniques to distinguish insect signals from noise (Mankin et al , 2000) and identify temporal patterns (Zhang et al , 2003b) and spatial distributions (Mankin et al , 2002; Zhang et al , 2003a) of insect activity. Originally, most of the software implementing the new techniques was written in efficient, but technically difficult C or C++ code, but higher‐level, user friendly tools such as Matlab (MathWorks, Inc., Natick, Massachusetts) have become available that enable more rapid progress in development of soil insect detection and monitoring applications.…”