Emerging technologies revolutionise insect ecology and monitoring

Insects are the most diverse group of animals on Earth, but their small size and high diversity have always made them challenging to study. Recent technologi- cal advances have the potential to revolutionise insect ecology and monitoring. We describe the state of the art of four technologies (computer vision, acoustic monitoring, radar, and molecular methods), and assess their advantages, current limitations, and future potential. We discuss how these technologies can adhere to modern standards of data curation and transparency, their implications for citizen science, and their potential for integration among different monitoring programmes and technologies. We argue that they provide unprecedented possibilities for insect ecology and monitoring, but it will be important to foster international standards via collaborationpublishedVersio

Modelling sensory limitation: the role of tree selection, memory and information transfer in bats' roost searching strategies.

Sensory limitation plays an important role in the evolution of animal behaviour. Animals have to find objects of interest (e.g. food, shelters, predators). When sensory abilities are strongly limited, animals adjust their behaviour to maximize chances for success. Bats are nocturnal, live in complex environments, are capable of flight and must confront numerous perceptual challenges (e.g. limited sensory range, interfering clutter echoes). This makes them an excellent model for studying the role of compensating behaviours to decrease costs of finding resources. Cavity roosting bats are especially interesting because the availability of tree cavities is often limited, and their quality is vital for bats during the breeding season. From a bat's sensory point of view, cavities are difficult to detect and finding them requires time and energy. However, tree cavities are also long lasting, allowing information transfer among conspecifics. Here, we use a simple simulation model to explore the benefits of tree selection, memory and eavesdropping (compensation behaviours) to searches for tree cavities by bats with short and long perception range. Our model suggests that memory and correct discrimination of tree suitability are the basic strategies decreasing the cost of roost finding, whereas perceptual range plays a minor role in this process. Additionally, eavesdropping constitutes a buffer that reduces the costs of finding new resources (such as roosts), especially when they occur in low density. We conclude that natural selection may promote different strategies of roost finding in relation to habitat conditions and cognitive skills of animals

Parameters used in the model and their values. See methods section for details (1 second = 1 time step, 1 m = 0.04 spatial units/1 spatial unit = 25 m).

1)<p>Note that since the individual responds only to the nearest recognized tree (of type depending on the discrimination level, see ‘Methods’), the effective ‘infinity’ is achieved by setting a perceptual range larger than the largest nearest neighbour distance between the recognized trees.</p

Number of trees inspected by bats, in relation to perceptual range, group size, tree discrimination skills and forest type.

<p>See caption to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044897#pone-0044897-g003" target="_blank">Figure 3</a> for details.</p

Process of finding new tree cavities by bats and acquisition of information about the presence and distribution of tree cavities in the forest.

<p>Process of finding new tree cavities by bats and acquisition of information about the presence and distribution of tree cavities in the forest.</p

Mean search time (±SD) of tree cavities by bats in relation to forest type, bats’ perceptual range and skills of tree discrimination.

<p>Proportion of trees in forests are coded as A/B/C, A: unsuitable, without cavities, B: confounding, apparently suitable but without cavities, C: suitable, with cavities. For a description of the tree discrimination levels, see Methods section.</p

Proportion of successful bats in search for roosts, in relation to perceptual range, group size, tree discrimination skills and forest type.

<p>See caption to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044897#pone-0044897-g003" target="_blank">Figure 3</a> for details.</p