Editorial: What sensory ecology might learn from landscape ecology?

Editorial on the Research Topic
What sensory ecology might learn from landscape ecology?

Increasing awareness by the mid-20th century that the spatio-temporal heterogeneity of the environment has a crucial impact on the flow of both matter and energy at various scales (population, community, and ecosystem level) gave rise to Landscape Ecology as ecological discipline (Naveh and Lieberman, 1984; Forman and Godron, 1986). Almost contemporarily, science witnessed the dawn of Sensory Ecology (Ali, 1978; Lythgoe, 1979; Huber and Markl, 1983; Barth, 1986; Dusenbery, 1992; recent review in Willemart, 2023), which focuses on understanding information flow in the environment (signal generation, propagation, perception, and interpretation). Just like the flow of matter and energy, information flow is far from constant owing to spatio-temporal variations of the biotic and abiotic environment (Endler, 1993; Pijanowski et al., 2011). These natural fluctuations have driven the evolution of plastic sensory systems in animals (Pyza, 2013; Maruska and Butler, 2021). However, the efficiency of information flow is threatened by rapid human modifications of the environment by increasing the acoustic, chemical, and visual noise, thereby interfering with the information necessary for communication and orientation (Pijanowski et al., 2011; Riffell et al., 2014; Duarte et al., 2021).

The present Research Topic is an effort to integrate Sensory Ecology and Landscape Ecology, calling attention to the importance of considering environmental heterogeneity in investigations of sensory adaptations of animals. A crucial first step is to measure the variation in a particular sensory landscape. In their contribution, Nilsson et al. highlight the importance of quantifying the distribution of light reaching animals' eyes in different environments. The authors demonstrate the association of vertical light gradients with weather conditions, time of day, and season. This information is vital for species that primarily use vision for finding suitable habitats, foraging, and for social interactions. Many animals, however, rely on chemical information in the environment, which is strongly influenced by the variability of air speed and direction. Analyzing air movement dynamics in a tropical dry forest in Costa Rica, DePasquale et al. found that air speed and turbulence increased with height above ground, peaked at midday, and may be lower in late than early successional parts of the forest. Species that use olfaction as primary source of information may have adapted to and even exploit this predictability of air movement patterns.

Spatio-temporal variations in the sensory environment are certainly the dominant driver of the evolution of sensory systems. Using statistical methods to control for effects of phylogenetic proximity and repeated measurements in their data sets, Huang et al. found strong evidence that relative eye size across six snake families from Taiwan changes with habitat type (bigger in terrestrial than aquatic snakes) and activity pattern (bigger in diurnal than nocturnal snakes). Thus, low light conditions associated with both aquatic and nocturnal lifestyles may have facilitated the evolution and/or improvement of sensory modalities alternative to vision, as is well-known in fish. Weakly electric fish, for instance, generate discharges of their electric organs to sense their environment and to communicate. In addition to an increased electrical activity during night time, Mucha et al. observed elevated electric organ discharges in visually complex habitats (floating vegetation in dense swamps) during the day in two species from Uganda. These findings emphasize the importance of spatio-temporal heterogeneity in light intensity concerning the use of different sensory modalities in these animals.

The evolution of signals goes hand in hand with the evolution of the sensory systems of receivers. The main drivers are sexual selection, competition, and predation. Despite their species specificity, signals may vary between and even within populations, as is the case with floral colors of a plant population in the Atacama Desert. Martínez-Harms et al. suggest that different color phenotypes, associated with different pigment compositions, are perceived differently by pollinators. This, eventually, enhances cross-pollination among individuals of the same phenotype and drives diversifying (positive) selection. By contrast, Yeager and Barnett found no evidence for positive selection in aposematic signal variation in a poison frog population from Ecuador. The authors argue that phenotype variation has not been reduced due to a weak purifying (negative) selection on a signal that is highly conspicuous to mates, rivals, and predators. In addition to sexual selection, competition, and predation, signal divergence between environments may be due to spatio-temporal variations in biotic and abiotic variables. In their contribution, Schirmer et al. show divergent color patterns in butterfly assemblages from two neighboring biomes in northeastern Brazil. The authors argue that darker wings in species from the rainforest are, presumably, associated with increased parasite-pressure, whereas lighter wing colors in the tropical dry forest may be an adaptive response to an elevated need for thermoregulation in this biome.

Although crucial for our understanding of the evolution of sensory systems and signals, information on spatio-temporal variations of the environment is frequently challenging to obtain. In their review, Chhaya et al. advocate the use of long-term acoustic monitoring to assess both the structure and the dynamics of acoustic communities (ensemble of vocalizing species in the environment), thereby providing real-time information on species distributions and movements. Similarly, Gonzales et al. propose long-term visual monitoring through remote sensing tools to map floral resource isolation and to investigate changes of resource patches over time. Such long-term monitoring techniques are key to identify anthropogenic changes in the sensory landscape that cause disturbances of information flow in the environment.

Human actions interfere with the environment at multiple levels. Anthropogenic climate change, for instance, increases the frequency of prolonged periods of excessive heat. Perl et al. investigated the impact of such heat waves during the final stage of pupal development on the behavior of a bumble bee species. The observed negative effects on vision, mechanoreception, olfaction, and taste show how human disturbances may alter the sensory systems of bumble bees and, thus, the way they perceive the environment. Yet, anthropogenic interference is not restricted to alterations of sensory systems. Signaling, as well, may be compromised in human-changed landscapes. Koneru and Caro demonstrate multiple ways of how visual signaling in animals is influenced by anthropogenic environmental changes. Human impacts range from alterations in pigment production through dietary changes to increasing colouration-background mismatches through changes in climate and landscape. Nair and Balakrishnan discuss how changes in the sensory environment interfere with the transmission and reception of acoustic sexual signals in katydids. In their study, the reduction of available signaling sites, owing to anthropogenic habitat modifications, provoked sub-optimal clustering of the males, thereby increasing competition over females.

Over the past decades, the impact of anthropogenic disturbances on ecosystem functioning has become a hot topic in Ecology. This Research Topic highlights the importance of integrative approaches, uniting Landscape Ecology and Sensory Ecology, to comprehend how natural and anthropogenically-driven environmental variations shape information flow and, eventually, natural selection in animals. Key questions for future research to answer in this context are: (1) To what extent do spatio-temporal variations in the abiotic environment at different geographic scales affect signal propagation? (2) To what extent do spatio-temporal variations in the biotic and abiotic environment drive the differentiation of sensory niches among animals? (3) Which environmental cues do animals use for decision-making, such as microhabitat choice? (4) How does anthropogenic interference influence the generation, propagation, reception, and discrimination of sensory information? We hope that this compilation of manuscripts stimulates new research in this direction, studying the sensory challenges for animals in a rapidly changing word.

Author contributions

MH, FG, PM, and DP drafted the manuscript. All authors contributed to the article and approved the submitted version.

Funding

MH was funded by a grant of the National Council for Scientific and Technological Development (CNPq, Grant: 311590/2019-5). DP was financially supported by a grant of the CAPES Foundation of the Brazilian Ministry of Education (Finance Code 001) and a CNPq Researcher Scholarship.

Acknowledgments

We thank all the authors and reviewers who have participated in this Research Topic. Thanks also to John Endler for fruitful discussions and feedback on articles published in this special topic.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

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References

Ali, M. A. (1978). Sensory Ecology: Review and Perspectives. New York, NY: Plenum Press.

Google Scholar

Barth, F. G. (1986). Vibrationssinn und vibratorische Umwelt der Spinnen. Naturwissenschaften 73, 519–530. doi: 10.1007/BF00368159

CrossRef Full Text | Google Scholar

Duarte, C. M., Chapuis, L., Collin, S. P., Costa, D. P., Devassy, R. P., Eguiluz, V. M., et al. (2021). The soundscape of the Anthropocene ocean. Science 371, 583. doi: 10.1126/science.aba4658

PubMed Abstract | CrossRef Full Text

Dusenbery, D. B. (1992). Sensory Ecology: How Organisms Acquire and Respond to Information. New York, NY: W.H. Freeman.

Google Scholar

Endler, J. (1993). The Color of light in forests and its implications. Ecol. Monogr. 63, 1–27. doi: 10.2307/2937121

CrossRef Full Text | Google Scholar

Forman, R. T. T., and Godron, M. (1986). Landscape Ecology. New York, NY: Wiley & Sons.

Google Scholar

Huber, F., and Markl, H., (eds.). (1983) Neuroethology and Behavioral Physiology: Roots And Growing Points. Berlin, Heidelberg: Spinger-Verlag.

Google Scholar

Lythgoe, J. N. (1979). The Ecology of Vision. New York, NY: Oxford University Press.

Google Scholar

Maruska, K. P., and Butler, J. M. (2021). Reproductive- and social-state plasticity of multiple sensory systems in a cichlid fish. Integr. Comp. Biol. 61, 249–268. doi: 10.1093/icb/icab062

PubMed Abstract | CrossRef Full Text | Google Scholar

Naveh, Z., and Lieberman, A. S. (1984). Landscape Ecology: Theory and Application. New York, NY: Springer-Verlag.

Google Scholar

Pijanowski, B. C., Villanueva-Rivera, L. J., Dumyahn, S. L., Farina, A., Krause, B. L., Napoletano, B. M., et al. (2011). Soundscape ecology: the science of sound in the landscape. BioScience 61, 203–216. doi: 10.1525/bio.2011.61.3.6

CrossRef Full Text | Google Scholar

Pyza, E. M. (2013). Plasticity in invertebrate sensory systems. Front. Physiol. 4, 226. doi: 10.3389/fphys.2013.00226

PubMed Abstract | CrossRef Full Text | Google Scholar

Riffell, J. A., Shlizerman, E., Sanders, E., Abrell, L., Medina, B., Hinterwirth, A. J., et al. (2014). Flower discrimination by pollinators in a dynamic chemical environment. Science 344, 1515–1518. doi: 10.1126/science.1251041

PubMed Abstract | CrossRef Full Text | Google Scholar

Willemart, R. (2023). The evolution of the concept of sensory ecology and the influence of behavioral ecology. An. Acad. Bras. Cienc. [In Press].