DocumentCode :
1492141
Title :
The toad that ate Australia
Author :
Price, Dick
Volume :
11
Issue :
6
fYear :
1996
fDate :
12/1/1996 12:00:00 AM
Firstpage :
13
Lastpage :
15
Abstract :
In 1935, to combat an infestation of sugar cane beetles, well intentioned growers along Australia´s North Queensland coast introduced a variety of Central American toad (Bufo marinus) to their canefields. The reality, however, has been different. The beetles, unfortunately, live high in the cane stalks, beyond the reach of the ground dwelling toad, which promptly set off on a 60-year march across Australia. Today, both beetle and toad are doing nicely; a one billion strong cane toad army now holds sway over 500,000 square kilometers north, west, and south of the original North Queensland beachhead. To check that advance, Australia´s government is considering releasing a biological agent-a species-specific virus-that will selectively kill the invader. Firstly, however, the possible impacts of these toads must analysed in detail-the method used involves machine learning. By monitoring the population fluctuations of frog species living at the vanguard of the cane toad advance, the speed of the encroachment can be measured, as well as the damage the cane toad causes. The undertaking involves training a computer software program to automatically identify the calls that various species of frog make, monitoring the types and numbers of frogs found at several locations over successive wet seasons when the frogs are active, and marking any population declines as the wave of cane toads passes through
Keywords :
acoustic signal processing; biology computing; ecology; learning (artificial intelligence); pattern recognition; zoology; Australia; Australian government; Bufo marinus; Central American toad; North Queensland coast; biological agent; computer software program; frog species; machine learning; population declines; population fluctuations; species specific virus; sugar cane beetles; wet seasons; Australia; Background noise; Control systems; Education; Humans; Learning systems; Monitoring; Rain; System testing; Vegetation;
fLanguage :
English
Journal_Title :
IEEE Expert
Publisher :
ieee
ISSN :
0885-9000
Type :
jour
DOI :
10.1109/64.546576
Filename :
546576
Link To Document :
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