Abstract
The use of detection dogs in conservation studies has expanded across species, conditions and habitats. However, it is incorrect to assume the potential associated with these surveys is automatically linked to the dog's sense of smell. Instead, an accurate detection dog rate is directly linked to many caveats in dog–handler training. Selecting a detection dog is directly linked to a clearly defined study design and must balance various factors, including: olfactory ability, physical structure, energy level, personality and social traits. Selection of training samples should ensure sufficient variation in target and nontarget species, independent of whether the goal is to locate evidence of the animal (e.g. scat, feather) or the physical animal. Just as not all dogs are appropriate, not all persons are suitable for this type of work, as the handler must be consistent and attentive to details with an incredible physical and mental endurance to sustain the time in the field. Testing in controlled and field situations can determine if the personalities of the dog and handler balance, with time needed for each to gain the ability to ‘read’ the other. Proper training for the dog and handler is essential, with special attention paid to the innate reactions of the latter. After training of the team is complete, testing trials should mimic field conditions. While there is no single model to becoming a handler in wildlife detection dog studies, incorporating these fundamental concepts with professional training can help optimize sample detection rate, minimize handler and dog frustration, and maximize overall success with this technique.
Highlights
The dog is given to someone to take home. If it is the handler, are they a year-round or seasonal employee? How will the dog be housed during the off-season? How will the dog be maintained for future deployment? Is it possible to continue training and testing trials during the off-season or is the target species seasonally limited? Is the dog’s temperament/drive such that it will maintain its work ethic during the off-season? While there are always exceptions, one must prepare for the possibility that a highly driven dog who will work long hours and cover the shear miles a project may need, may not want to turn back into a normal pet dog left at home for long hours while the people go off to work
The use of detection dogs provides an approach to gather data on one or more species independent of many factors, including species behavior, its rarity, physical habitat and environmental conditions. The expansion of this noninvasive technique worldwide reinforces the need for all involved to remember that an accurate detection rate is directly linked to a strong dog–handler foundation
A study should not be designed to fit a particular detection dog nor should one select a dog based on its tight bond with the handler
Summary
Prior to any dog–handler selection or training, it is essential that the goals and objectives of the study be clearly defined, including: defining target species, habitat conditions, potential seasonality, type and number of samples needed and study duration. Transects are by nature a systematic approach to data collection Applying these strict standards to detection dogs can result in problems, as they may fail to account for changes that affect the dog’s olfactory search, including: terrain, wind direction, ambient temperatures and relative humidity. While there are always exceptions, one must prepare for the possibility that a highly driven dog who will work long hours and cover the shear miles a project may need, may not want to turn back into a normal pet dog left at home for long hours while the people go off to work This is especially true of younger/newer dogs, this issue can improve with age depending on the dog’s base temperament and work ethic. The time required for these refresher trials will be independent of the number of odors the dog is trained to locate (Williams and Johnston 2002) and instead depend on the individual dynamics of the dog–handler team
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