Visual acuity trade-offs and microhabitat driven adaptation of searching behaviour in psyllids (Hemiptera: Psylloidea: Aphalaridae)

Abstract

There was an error published in J. Exp. Biol. 218, 1564-1571.The images in Fig. 5 were mislabelled. The correct version is given below.The authors apologise for any inconvenience this may have caused. ABSTRACTInsects have evolved morphological and physiological adaptations in response to selection pressures inherent to their ecology. Consequently, visual performance and acuity often significantly vary between different insect species. Whilst psychophysics has allowed for the accurate determination of visual acuity for some Lepidoptera and Hymenoptera, very little is known about other insect taxa that cannot be trained to positively respond to a given stimulus. In this study, we demonstrate that prior knowledge of insect colour preferences can be used to facilitate acuity testing. We focused on four psyllid species (Hemiptera: Psylloidea: Aphalaridae), namely Ctenarytaina eucalypti, Ctenarytaina bipartita, Anoeconeossa bundoorensis and Glycaspis brimblecombei, that differ in their colour preferences and utilization of different host-plant modules (e.g. apical buds, stems, leaf lamellae) and tested their visual acuity in a modified Y-maze adapted to suit psyllid searching behaviour. Our study revealed that psyllids have visual acuity ranging from 6.3 to 8.7 deg. Morphological measurements for different species showed a close match between inter-ommatidial angles and behaviourally determined visual angles (between 5.5 and 6.6 deg) suggesting detection of colour stimuli at the single ommatidium level. Whilst our data support isometric scaling of psyllids' eyes for C. eucalypti, C. bipartita and G. brimblecombei, a morphological trade-off between light sensitivity and spatial resolution was found in A. bundoorensis. Overall, species whose microhabitat preferences require more movement between modules appear to possess superior visual acuity. The psyllid searching behaviours that we describe with the help of tracking software depict species-specific strategies that presumably evolved to optimize searching for food and oviposition sites.

Innate colour preferences of the Australian native stingless bee Tetragonula carbonaria Sm.

“…For this purpose, a multiple regression analysis was performed to understand the potential effect of four previously identified spectral characteristics of the stimuli: (1) brightness, (2) green contrast, (3) chromatic contrast and (4) spectral purity on the number of landings observed for each colour (Wyszecki and Stiles 1982;Giurfa et al 1996Giurfa et al , 1997Spaethe et al 2001;Kemp et al 2015). The different properties were calculated from reflectance spectra data following methods by (Chittka 1992;Chittka et al 1994;Spaethe et al 2001), and assuming a green background for chromatic adaptation (refer to "Materials and methods" for details) a Colour categories follow those by Chittka et al (1994) b Sensu ) The regression analysis was done using a count regression model (a case of the generalised linear model) assuming a Poisson distribution and a logit link to account for the discrete nature of the response variable (Faraway 2006). Analyses were done using the glm routine available for the R statistical programming language 3.2.3 (R Core Team 2015).…”

“…The arena lid was constructed of UV transparent Plexiglas as per Norgate et al (2010). Illumination (10/14 h day/ night) was provided by four Philips Master TLS HE slimline 28 W/865 UV + daylight fluorescent tubes (Philips, Holland) with specially fitted high frequency (1200 Hz) ATEC Jupiter EGF PMD2614-35 electronic dimmable ballasts and diffused by Rosco 216 (Germany) UV transmitting screen (spectra shown in Farnier et al 2015). This illumination approximately matches daylight illumination conditions for bees including the Australian context (Dyer 1998;Dyer and Chittka 2004).…”

“…In model species like the honeybee, the analyses of colour choices modelled in either the Hexagon colour space or an independent receptor noise space (Kemp et al 2015) are significantly correlated [Kendall's tau (τ) = 0.993, P < 0.0001] suggesting that colour choices are independent of specific model assumptions (Dyer and Neumeyer 2005;van der Kooi et al 2016). We used spectral properties for the lab lighting (Farnier et al 2015) and assumed that the colour visual system was adapted to the green background (Fig. 1).…”

Apple Proliferation Phytoplasma Influences the Pattern of Plant Volatiles Emitted Depending on Pathogen Virulence

“…Psyllid behaviors related to aggregation will be important to elucidate to better understand the epidemiology of phytoplasmas. Nevertheless, olfactory, gustatory and visual plant cues affecting psyllid behavior also need to be documented to understand the movement of psyllids between hosts and among modules within hosts (Farnier et al, 2014(Farnier et al, , 2015Orlovskis et al, 2015).…”

Chemical Communication between Phytopathogens, Their Host Plants and Vector Insects and Eavesdropping by Natural Enemies

“…Liberibacter) (Weintraub and Beanland, 2006;Hogenhout et al, 2008). Besides visual (Farnier et al, 2014(Farnier et al, , 2015 and tactile signals, these vector insects use information provided by plant odors (kairomones) for the identification of appropriate hosts for feeding and oviposition (Orlovskis et al, 2015). These volatile organic compounds (VOCs) may be produced constitutively (Soroker et al, 2004) or can be induced by plant pathogens (Mayer et al, 2008a,b;Rid et al, 2016).…”