Work

Invasive catfish detection with scent detection dogs

Year: 2025
Type: article
Abstract: Dogs have been demonstrated to be capable detectors of some aquatic species. However, taking dogs into the field for aquatic species detection is not always practical. A recently developed system that involves bringing water samples from the field into a laboratory environment to be evaluated by dogs has shown promise for koi carp ( Cyprinus rubrofuscus ) detection. In the present study, we replicated these methods to evaluate dogs’ ability to detect brown bullhead catfish ( Ameiurus nebulosus ). In Experiment 1, we evaluated the dogs’ detection thresholds for catfish detection and determined that they can detect the presence of catfish at operationally useful biomass concentrations in dechlorinated municipal water. To be operationally feasible, samples taken from field sites would need to be preserved between collection and evaluation. Therefore, in Experiment 2, we examined the influence of two water preservation methods, refrigeration and freezing, and found no evidence of any deleterious effect of either method on dogs’ catfish-detection performance. In Experiment 3, we evaluated the dogs’ performance when working with water from natural water sources and, therefore, containing other volatile organic compounds. Under these conditions, dogs were capable of accurately classifying samples at low biomass concentrations, similar to their performance in Experiment 1. These findings strengthen the evidence for the utility of this system for monitoring waterbodies for incursions of a variety of invasive aquatic species. • Dogs can detect catfish in water samples. • Samples can be collected in the field and analysed by dogs in a laboratory. • Dogs were able to detect catfish at low, operationally useful, concentrations. • Refrigeration and freezing did not impair dogs’ detection performance. • Dogs were also able to perform accurately with natural lake water samples.
Language: English
Open Access status: hybrid
Estimated APC paid: $3,220
OpenAlex ID: W4416732202
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Cites: 25
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