Kulahci, I. G., Dornhaus, A. & Papaj, D. R. Multimodal signals enhance decision making in foraging bumble-bees. Proc. Biol. Sci. 275, 797–802 (2008).
Goldshtein, A. et al. Reinforcement learning enables resource partitioning in foraging bats. Curr. Biol. 30, 4096–4102.e4096 (2020).
Google Scholar
Skogen, K. A., Overson, R. P., Hilpman, E. T. & Fant, J. B. Hawkmoth pollination facilitates long-distance pollen dispersal and reduces isolation across a gradient of land-use change. Ann. Mo. Bot. Gard. 104, 495–511 (2019). 417.
Deng, J.-Y., van Noort, S., Compton, S. G., Chen, Y. & Greeff, J. M. Conservation implications of fine scale population genetic structure of Ficus species in South African forests. Ecol. Manag. 474, 118387 (2020).
Galizia, C. G. et al. Relationship of visual and olfactory signal parameters in a food-deceptive flower mimicry system. Behav. Ecol. 16, 159–168 (2004).
Gibernau, M., HossaertMcKey, M., Frey, J. & Kjellberg, F. Are olfactory signals sufficient to attract fig pollinators. Ecoscience 5, 306–311 (1998).
Kapustjansky, A., Chittka, L. & Spaethe, J. Bees use three-dimensional information to improve target detection. Naturwissenschaften 97, 229–233 (2010).
Google Scholar
Hempel de Ibarra, N., Langridge, K. V. & Vorobyev, M. More than colour attraction: behavioural functions of flower patterns. Curr. Opin. Insect Sci. 12, 64–70 (2015).
Boff, S., Henrique, J. A., Friedel, A. & Raizer, J. Disentangling the path of pollinator attraction in temporarily colored flowers. Int. J. Trop. Insect Sci. 41, 1305–1311 (2021).
Leonard, A. S. & Papaj, D. R. ‘X’ marks the spot: the possible benefits of nectar guides to bees and plants. Funct. Ecol. 25, 1293–1301 (2011).
Dobson, H. E. M. & Bergström, G. The ecology and evolution of pollen odors. Plant Syst. Evol. 222, 63–87 (2000).
Google Scholar
Raguso, R. A. Why are some floral nectars scented? Ecology 85, 1486–1494 (2004).
Corbet, S. A., Kerslake, C. J. C., Brown, D. & Morland, N. E. Can bees select nectar-rich flowers in a patch. J. Apic. Res. 23, 234–242 (1984).
Policha, T. et al. Disentangling visual and olfactory signals in mushroom-mimicking Dracula orchids using realistic three-dimensional printed flowers. N. Phytol. 210, 1058–1071 (2016).
Google Scholar
Stout, J. C., Goulson, D. & Allen, J. A. Repellent scent-marking of flowers by a guild of foraging bumblebees (Bombus spp.). Behav. Ecol. Sociobiol. 43, 317–326 (1998).
Howell, A. D. & Alarcón, R. Osmia bees (Hymenoptera: Megachilidae) can detect nectar-rewarding flowers using olfactory cues. Anim. Behav. 74, 199–205 (2007).
von Arx, M. Floral humidity and other indicators of energy rewards in pollination biology. Commun. Integr. Biol. 6, e22750–e22750 (2013).
Goyret, J. The breath of a flower: CO2 adds another channel-and then some-to plant-pollinator interactions. Commun. Integr. Biol. 1, 66–68 (2008).
Google Scholar
Bradbury, J. W. & Vehrencamp, S. L. Principles of Animal Communication 2nd edn (Sinauer Associates, 2011).
McMeniman, C. J., Corfas, R. A., Matthews, B. J., Ritchie, S. A. & Vosshall, L. B. Multimodal integration of carbon dioxide and other sensory cues drives mosquito attraction to humans. Cell 156, 1060–1071 (2014).
Google Scholar
Smith, J. M. & Harper, D. Animal Signals (Oxford Univ. Press, 2003).
Smith, M. J. & Harper, D. G. C. Animal signals: models and terminology. J. Theor. Biol. 177, 305–311 (1995).
Google Scholar
Laidre, M. E. & Johnstone, R. A. Animal signals. Curr. Biol. 23, R829–R833 (2013).
Google Scholar
Smith, J. M. Must reliable signals always be costly? Anim. Behav. 47, 1115–1120 (1994).
Guerenstein, P. G., A.Yepez, E., van Haren, J., Williams, D. G. & Hildebrand, J. G. Floral CO2 emission may indicate food abundance to nectar-feeding moths. Naturwissenschaften 91, 329–333 (2004).
Google Scholar
Goyret, J., Markwell, P. M. & Raguso, R. A. Context- and scale-dependent effects of floral CO2 on nectar foraging by Manduca sexta. Proc. Natl Acad. Sci. USA 105, 4565–4570 (2008).
Google Scholar
Thom, C., Guerenstein, P. G., Mechaber, W. L. & Hildebrand, J. G. Floral CO2 reveals flower profitability to moths. J. Chem. Ecol. 30, 1285–1288 (2004).
Google Scholar
Gilbert, F. S., Haines, N. & Dickson, K. Empty flowers. Funct. Ecol. 5, 29–39 (1991).
von Arx, M., Goyret, J., Davidowitz, G. & Raguso, R. A. Floral humidity as a reliable sensory cue for profitability assessment by nectar-foraging hawkmoths. Proc. Natl Acad. Sci. USA 109, 9471–9476 (2012).
Google Scholar
Harrap, M. J. M., Hempel de Ibarra, N., Knowles, H. D., Whitney, H. M. & Rands, S. A. Floral humidity in flowering plants: A preliminary survey. Front. Plant Sci. https://doi.org/10.3389/fpls.2020.00249 (2020).
Harrap, M. J. M. & Rands, S. A. The role of petal transpiration in floral humidity generation. Planta 255, 78 (2022).
Google Scholar
Harrap, M. J. M., Hempel de Ibarra, N., Knowles, H. D., Whitney, H. M. & Rands, S. A. Bumblebees can detect floral humidity. J. Exp. Biol. https://doi.org/10.1242/jeb.240861 (2021).
Hebets, E. A. & Papaj, D. R. Complex signal function: developing a framework of testable hypotheses. Behav. Ecol. Sociobiol. 57, 197–214 (2005).
Bronstein, J. L., Huxman, T., Horvath, B., Farabee, M. & Davidowitz, G. Reproductive biology of Datura wrightii: the benefits of a herbivorous pollinator. Ann. Bot. 103, 1435–1443 (2009).
Johnson, C. A. et al. Coevolutionary transitions from antagonism to mutualism explained by the co-opted antagonist hypothesis. Nat. Commun. https://doi.org/10.1038/s41467-021-23177-x (2021).
Clark, C. J. The role of power versus energy in courtship: what is the ‘energetic cost’ of a courtship display? Anim. Behav. 84, 269–277 (2012).
Willmott, A. P. & Ellington, C. P. The mechanics of flight in the hawkmoth Manduca sexta. I. Kinematics of hovering and forward flight. J. Exp. Biol. 200, 2705–2722 (1997).
Google Scholar
Shields, V. D. C. & Hildebrand, J. G. Fine structure of antennal sensilla of the female sphinx moth, Manduca sexta (Lepidoptera: Sphingidae). II. Auriculate, coeloconic, and styliform complex sensilla. Can. J. Zool. 77, 302–313 (1999).
Lee, J. K. & Strausfeld, N. J. Structure, distribution and number of surface sensilla and their receptor cells on the olfactory appendage of the male moth Manduca sexta. J. Neurocytol. 19, 519–538 (1990).
Google Scholar
Shields, V. D. & Hildebrand, J. G. Recent advances in insect olfaction, specifically regarding the morphology and sensory physiology of antennal sensilla of the female sphinx moth Manduca sexta. Microsc. Res. Tech. 55, 307–329 (2001).
Google Scholar
Tichy, H. & Loftus, R. Hygroreceptors in insects and a spider: Humidity transduction models. Naturwissenschaften 83, 255–263 (1996).
Google Scholar
Ahrens, M., Huang, K.-H., Narayan, S., Mensh, B. & Engert, F. Two-photon calcium imaging during fictive navigation in virtual environments. Front. Neural Circuits https://doi.org/10.3389/fncir.2013.00104 (2013).
Lacher, V. Elektrophysiologische untersuchungen an einzelnen rezeptoren für geruch, kohlendioxyd, luftfeuchtigkeit und tempratur auf den antennen der arbeitsbiene und der drohne (Apis mellifica L.). Z. f.ür. Vgl. Physiologie 48, 587–623 (1964).
Waldow, U. Elektrophysiologische untersuchungen an feuchte-, trocken- und kälterezeptoren auf der antenne der wanderheuschrecke Locusta. Z. f.ür. Vgl. Physiologie 69, 249–283 (1970).
Yokohari, F. & Tateda, H. Moist and dry hygroreceptors for relative humidity of the cockroach, Periplaneta americana L. J. Comp. Physiol. 106, 137–152 (1976).
Tichy, H. Low rates of change enhance effect of humidity on the activity of insect hygroreceptors. J. Comp. Physiol. A Neuroethol. Sens Neural Behav. Physiol. 189, 175–179 (2003).
Google Scholar
Tichy, H., Hellwig, M. & Kallina, W. Revisiting theories of humidity transduction: a focus on electrophysiological data. Front. Physiol. 8, 650 (2017).
Tichy, H. & Kallina, W. Insect hygroreceptor responses to continuous changes in humidity and air pressure. J. Neurophysiol. 103, 3274–3286 (2010).
Google Scholar
Wolfin, M. S., Raguso, R. A., Davidowitz, G. & Goyret, J. Context dependency of in-flight responses by Manduca sexta moths to ambient differences in relative humidity. J. Exp. Biol. https://doi.org/10.1242/jeb.177774 (2018).
Smith, G., Kim, C. & Raguso, R. A. Pollen accumulation on hawkmoths varies substantially among moth-pollinated flowers. Preprint at bioRxiv https://doi.org/10.1101/2022.07.15.500245 (2022).
Haverkamp, A., Bing, J., Badeke, E., Hansson, B. S. & Knaden, M. Innate olfactory preferences for flowers matching proboscis length ensure optimal energy gain in a hawkmoth. Nat. Commun. 7, 11644 (2016).
Google Scholar
Harrison, A. S. & Rands, S. A. The ability of bumblebees Bombus terrestris (hymenoptera: Apidae) to detect floral humidity is dependent upon environmental humidity. Environ. Entomol. 51, 1010–1019 (2022).
Kelber, A. What a hawkmoth remembers after hibernation depends on innate preferences and conditioning situation. Behav. Ecol. 21, 1093–1097 (2010).
Riffell, J. A. et al. Flower discrimination by pollinators in a dynamic chemical environment. Science 344, 1515–1518 (2014).
Google Scholar
Schellenberg, R. The trouble with humidity: the hidden challenge of RH calibration. Cal. Lab. 9, 40–42 (2002).
Roddy, A. B., Brodersen, C. R. & Dawson, T. E. Hydraulic conductance and the maintenance of water balance in flowers. Plant Cell Environ. 39, 2123–2132 (2016).
Google Scholar
Sane, S. P. & Jacobson, N. P. Induced airflow in flying insects. II. Measurement of induced flow. J. Exp. Biol. 209, 43–56 (2006).
Daly, K. C., Kalwar, F., Hatfield, M., Staudacher, E. & Bradley, S. P. Odor detection in Manduca sexta is optimized when odor stimuli are pulsed at a frequency matching the wing beat during flight. PLoS ONE 8, e81863 (2013).
Google Scholar
Yokohari, F. Hygroreceptor mechanism in the antenna of the cockroach. Periplaneta. J. Comp. Physiol. 124, 153 (1978).
Loftus, R. Temperature-dependent dry receptor on antenna of Periplaneta. Tonic response. J. Comp. Physiol. 111, 153–170 (1976).
Tichy, H. & Kallina, W. Sensitivity of honeybee hygroreceptors to slow humidity changes and temporal humidity variation detected in high resolution by mobile measurements. PLoS ONE 9, e99032 (2014).
Google Scholar
Galen, C., Sherry, R. A. & Carroll, A. B. Are flowers physiological sinks or faucets? Costs and correlates of water use by flowers of Polemonium viscosum. Oecologia 118, 461–470 (1999).
Google Scholar
Elle, E., van Dam, N. M. & Hare, J. D. Cost of glandular trichomes, a “resistance” character in Datura wrightii regel (solanaceae). Evolution 53, 22–35 (1999).
Elle, E. & Hare, J. D. Environmentally induced variation in floral traits affects the mating system in Datura wrightii. Funct. Ecol. 16, 79–88 (2002).
Marler, C. A. & Ryan, M. J. Energetic constraints and steroid hormone correlates of male calling behaviour in the túngara frog. J. Zool. 240, 397–409 (1996).
Bernal, X. E., Rand, A. S. & Ryan, M. J. Acoustic preferences and localization performance of blood-sucking flies (Corethrella Coquillett) to túngara frog calls. Behav. Ecol. 17, 709–715 (2006).
Raguso, R. A. Flowers as sensory billboards: progress towards an integrated understanding of floral advertisement. Curr. Opin. Plant Biol. 7, 434–440 (2004).
Peach, D. A. H., Gries, R., Zhai, H., Young, N. & Gries, G. Multimodal floral cues guide mosquitoes to tansy inflorescences. Sci. Rep. 9, 3908 (2019).
Google Scholar
Riffell, J. A. & Alarcón, R. Multimodal floral signals and moth foraging decisions. PLoS ONE 8, e72809 (2013).
Google Scholar
van der Kooi, C. J., Kevan, P. G. & Koski, M. H. The thermal ecology of flowers. Ann. Bot. 124, 343–353 (2019).
Terry, L. I., Roemer, R. B., Walter, G. H., Booth, D. & Lee, K. P. Thrips’ responses to thermogenic associated signals in a cycad pollination system: the interplay of temperature, light, humidity and cone volatiles. Funct. Ecol. 28, 857–867 (2014).
Bronstein, J. L., Alarcón, R. & Geber, M. The evolution of plant–insect mutualisms. N. Phytol. 172, 412–428 (2006).
Schaefer, H. M. & Ruxton, G. D. Deception in plants: mimicry or perceptual exploitation. Trends Ecol. Evol. 24, 676–685 (2009).
Franchi, G. G., Nepi, M. & Pacini, E. Is flower/corolla closure linked to decrease in viability of desiccation-sensitive pollen? Facts and hypotheses: a review of current literature with the support of some new experimental data. Plant Syst. Evol. 300, 577–584 (2014).
Safavian, D. et al. High humidity partially rescues the Arabidopsis thaliana exo70A1 stigmatic defect for accepting compatible pollen. Plant Reprod. 27, 121–127 (2014).
Google Scholar
Shivanna, K. R. & Cresti, M. Effects of high humidity and temperature stress on pollen membrane integrity and pollen vigour in Nicotiana tabacum. Sex. Plant Reprod. 2, 137–141 (1989).
Richman, S. K. et al. The sensory and cognitive ecology of nectar robbing. Front. Ecol. Evol. https://doi.org/10.3389/fevo.2021.698137 (2021).
Raguso, R. A. et al. Trumpet flowers of the Sonoran Desert: floral biology of Peniocereus Cacti and Sacred Datura. Int. J. Plant Sci. 164, 877–892 (2003).
Google Scholar
Carazo, P. & Font, E. ‘Communication breakdown’: the evolution of signal unreliability and deception. Anim. Behav. 87, 17–22 (2014).
Schemske, D. W. Evolution of floral display in the orchid Brassavola nodosa. Evolution 34, 489–493 (1980).
Haber, W. A. Pollination by deceit in a mass-flowering tropical tree Plumeria rubra L. (apocynaceae). Biotropica 16, 269–275 (1984).
Brandenburg, A., Kuhlemeier, C. & Bshary, R. Hawkmoth pollinators decrease seed set of a low-nectar Petunia axillaris line through reduced probing time. Curr. Biol. 22, 1635–1639 (2012).
Google Scholar
Bye, R. & Sosa, V. Molecular phylogeny of the jimsonweed genus Datura (solanaceae). Syst. Bot. 38, 818–829 (2013).
Kariñho-Betancourt, E., Agrawal, A. A., Halitschke, R. & Núñez-Farfán, J. Phylogenetic correlations among chemical and physical plant defenses change with ontogeny. N. Phytol. 206, 796–806 (2015).
Kawahara, A. Y. et al. Evolution of Manduca sexta hornworms and relatives: biogeographical analysis reveals an ancestral diversification in Central America. Mol. Phylogenet. Evol. 68, 381–386 (2013).
Contreras, H. L. et al. The effect of ambient humidity on the foraging behavior of the hawkmoth Manduca sexta. J. Comp. Physiol. A Neuroethol. Sens. Neural Behav. Physiol. 199, 1053–1063 (2013).
Cardoso, J. C. F., Gonzaga, M. O., Cavalleri, A., Maruyama, P. K. & Alves-Silva, E. The role of floral structure and biotic factors in determining the occurrence of florivorous thrips in a dystilous shrub. Arthropod-Plant Interact. 10, 477–484 (2016).
Nicolson, S. W. Sweet solutions: nectar chemistry and quality. Philos. Trans. R. Soc. Lond. B Biol. Sci. 377, 20210163 (2022).
Google Scholar
Pellmyr, O. & Thien, L. B. Insect reproduction and floral fragrances: keys to the evolution of the Angiosperms. Taxon 35, 76–85 (1986).
Enjin, A. et al. Humidity sensing in Drosophila. Curr. Biol. 26, 1352–1358 (2016).
Google Scholar
Knecht, Z. A. et al. Distinct combinations of variant ionotropic glutamate receptors mediate thermosensation and hygrosensation in Drosophila. eLife 5, e17879 (2016).
Knecht, Z. A. et al. Ionotropic receptor-dependent moist and dry cells control hygrosensation in Drosophila. eLife 6, e26654 (2017).
Croset, V. et al. Ancient protostome origin of chemosensory ionotropic glutamate receptors and the evolution of insect taste and olfaction. PLoS Genet. 6, e1001064–e1001064 (2010).
Dahake, A. et al. MATLAB codes: a signal-like role for floral humidity in a nocturnal pollination system. Zenodo https://doi.org/10.5281/zenodo.7320037 (2022).
Pereira, T. D. et al. Fast animal pose estimation using deep neural networks. Nat. Methods 16, 117–125 (2019).
Google Scholar
Nilsson, S. R. et al. Simple behavioral analysis (SimBA) – an open source toolkit for computer classification of complex social behaviors in experimental animals. Preprint at bioRxiv https://doi.org/10.1101/2020.04.19.049452 (2020).
Casey, T. M. Flight energetics of sphinx moths: power input during hovering flight. J. Exp. Biol. 64, 529–543 (1976).
Google Scholar
Riffell, J. A. et al. Behavioral consequences of innate preferences and olfactory learning in hawkmoth-flower interactions. Proc. Natl Acad. Sci. USA 105, 3404–3409 (2008).
Google Scholar
Lott, G. K., Johnson, B. R., Bonow, R. H., Land, B. R. & Hoy, R. R. g-PRIME: a free, windows based data acquisition and event analysis software package for physiology in classrooms and research labs. J. Undergrad. Neurosci. Educ. 8, A50–A54 (2009).
Chaure, F. J., Rey, H. G. & Quiroga, R. Q. A novel and fully automatic spike-sorting implementation with variable number of features. J. Neurophysiol. 120, 1859–1871 (2018).
Google Scholar
Tichy, H. Humidity-dependent cold cells on the antenna of the stick insect. J. Neurophysiol. 97, 3851–3858 (2007).
Campbell, R. raacampbell/shadedErrorBar. https://github.com/raacampbell/shadedErrorBar (2022).
Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. https://doi.org/10.18637/jss.v067.i01 (2015).
Broadhead, G. T. & Raguso, R. A. Associative learning of non-sugar nectar components: amino acids modify nectar preference in a hawkmoth. J. Exp. Biol. https://doi.org/10.1242/jeb.234633 (2021).
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