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1.
Biol Lett ; 16(7): 20200329, 2020 07.
Article in English | MEDLINE | ID: mdl-32673541

ABSTRACT

Foraging by mammalian herbivores has profound impacts on natural and modified landscapes, yet we know little about how they find food, limiting our ability to predict and manage their influence. Mathematical models show that foragers exploiting odour cues outperform a random walk strategy. However, discovering how free-ranging foragers exploit odours in real, complex landscapes has proven elusive because of technological constraints. We took a novel approach, using a sophisticated purpose-built thermal camera system to record fine-scale foraging by a generalist mammalian herbivore, the swamp wallaby (Wallabia bicolor). We tested the hypothesis that odour cues shape forager movement and behaviour in vegetation patches. To do this, we compared wallaby foraging in two odour landscapes: Control (natural vegetation with food and non-food plants interspersed) and +Apple (the same natural vegetation plus a single, highly palatable food source with novel odour (apple)). The +Apple treatment led to strongly directed foraging by wallabies: earlier visits to vegetation patches, straighter movement paths, more hopping and fewer stops than in the Control treatment. Our results provide clear empirical evidence that odour cues are harnessed for efficient, directed search even at this fine scale. We conclude that random walk models miss a key feature shaping foraging within patches.


Subject(s)
Herbivory , Odorants , Animals , Cues , Feeding Behavior , Food , Macropodidae
2.
Trends Biotechnol ; 33(4): 201-7, 2015 Apr.
Article in English | MEDLINE | ID: mdl-25744760

ABSTRACT

The global movement of people and goods has increased the risk of biosecurity threats and their potential to incur large economic, social, and environmental costs. Conventional manual biosecurity surveillance methods are limited by their scalability in space and time. This article focuses on autonomous surveillance systems, comprising sensor networks, robots, and intelligent algorithms, and their applicability to biosecurity threats. We discuss the spatial and temporal attributes of autonomous surveillance technologies and map them to three broad categories of biosecurity threat: (i) vector-borne diseases; (ii) plant pests; and (iii) aquatic pests. Our discussion reveals a broad range of opportunities to serve biosecurity needs through autonomous surveillance.


Subject(s)
Crops, Agricultural , Environmental Monitoring/instrumentation , Robotics/instrumentation , Security Measures
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