Multispecies sensory networks, where different species prioritize different sensory modalities and then use heterospecific information in a likely noncooperative fashion, may allow animals to improve foraging over large areas for cryptic prey. We test this hypothesis in procellariiform seabirds that forage in mixed flocks, where both prey odors and visual cues provided by other foraging hetero-and conspecifics might improve success rates. Using agent-based models, we explored the impact of social strategies on olfactory foraging for Antarctic krill (Euphausia superba). Our results suggest that social foraging enables species with different sensory adaptations to achieve similar success rates. Additionally, our results indicate that foraging is more successful in mixed-species rather than single-species flocks, where individuals can monitor the activity of other birds that are using different sensory foraging strategies than themselves to find prey. These results suggest that sensory-based foraging networks may be more critical to their survival than previously assumed. Finally, we show that success rates decrease at low population densities. As seabird populations continue to decline, understanding and preserving these social foraging networks may be essential for their conservation and ecological success. Overall, our study provides insights into the critical role of multispecies sensory networks to foraging success, wherein different species have different sensory adaptations for locating prey. While we used empirical anatomical and behavioral data specific to procellariiforms to inform our models, our approach and results may have broader implications for other species as well.

Many animals use the geomagnetic field to migrate long distances with high accuracy; however, research has shown that individual responses to magnetic cues can be highly variable. Thus, it has been hypothesized that magnetoreception alone is insufficient for accurate migrations and animals must either switch to a more accurate sensory cue or integrate their magnetic sense over time. Here we suggest that magnetoreceptive migrators could also use collective navigation strategies. Using agent-based models, we compare agents utilizing collective navigation to both the use of a secondary sensory system and time-integration. Our models demonstrate that collective navigation allows for 70% success rates for noisy navigators. To reach the same success rates, a secondary sensory system must provide perfect navigation for over 73% of the migratory route, and time integration must integrate over 50 time-steps, indicating that magnetoreceptive animals could benefit from using collective navigation. Finally, we explore the impact of population loss on animals relying on collective navigation. We show that as population density decreases, a greater proportion of individuals fail to reach their destination and that a 50% population reduction can result in up to a 37% decrease in the proportion of individuals completing their migration.

To investigate the active sensing strategies used by echolocating bats of the genera Rhinolophus and Hipposideros, we have constructed a 9-meter long flight tunnel, which incorporates an array of 32 ultrasonic microphones distributed throughout the tunnel. Rhinolophus and Hipposideros are of special interest because of their highly flexible biosonar system; these bats emit pulses from their nasal cavities, using complex noseleaf structures to quickly and precisely alter the beam-form and direction of emissions. Additionally, each species utilizes a unique combination of constant-frequency (CF) and frequency-modulated (FM) ultrasonic signals with varying durations, repetition rates, and frequencies. We plan to trap several species of wild Bornean bats of these genera and fly individual bats through the tunnel; a time-of-arrival algorithm will be used to localize the position of each bat at the time of each biosonar pulse emission, and an amplitude-comparison method to measure the horizontal and vertical direction of each emission from the bat’s noseleaf. We will also incorporate relatively simple foliage obstacles into the tunnel; this will create complex acoustic clutter and allow us to determine how bats of different species adjust their biosonar sampling strategies in order to navigate around novel obstacles in a cluttered environment.

Radio frequency electromagnetic noise (RF) of anthropogenic origin has been shown to disrupt magnetic orientation behavior in some animals. Two sources of natural RF might also have the potential to disturb magnetic orientation behavior under some conditions: solar RF and atmospheric RF. In this review, we outline the frequency ranges and electric/magnetic field magnitudes of RF that have been shown to disturb magnetoreceptive behavior in laboratory studies and compare these to the ranges of solar and atmospheric RF. Frequencies shown to be disruptive in laboratory studies range from 0.1 to 10 MHz, with magnetic magnitudes as low as 1 nT reported to have effects. Based on these values, it appears unlikely that solar RF alone routinely disrupts magnetic orientation. In contrast, atmospheric RF does sometimes exceed the levels known to disrupt magnetic orientation in laboratory studies. We provide a reference for when and where atmospheric RF can be expected to reach these levels, as well as a guide for quantifying RF measurements.

Studying model organisms in their natural environments is essential for advancing bioinspired science and technology. Echolocating bats can be models to inspire new technology for sonar sensing, mobility with flapping flight as well as the integration of these two capabilities. Bat species belonging to genera such as Rhinolophus and Hipposideros stand out for their ability to navigate and hunt prey in dense vegetation. To further the study of echolocation and flight strategies in these genera, field-based research methods have been used to observe, record, and capture bats in Brunei Darussalam. This work was conducted at Andulau Forest Reserve on the border of Belait and Tutong Districts, various other field sites in Tutong District, as well as at Mata Mata in Brunei-Muara District from June 2022 through August 2022. Harp traps were primarily used to capture bats, a less invasive capture technique compared to other types of netting and thought to be more effective against the sophisticated echolocation capabilities of these bats. Acoustic recordings were collected at trap sites and upon processing. These recordings can be utilized to advance passive acoustic monitoring and to improve software that can distinguish species based on sonar characteristics which can also support general biodiversity monitoring.

Many bat species rely on biosonar as their primary source of sensory information about their environments. Species that are able to navigate amid dense vegetation use this biosonar information to guide highly dexterous flight maneuvers. Understanding the connection between biosonar inputs and flight outputs poses a challenge, because the flight apparatus of bats has the most degrees of freedom of any flight system—whether natural or man-made. At the same time, the biosonar inputs consist of just two one-dimensional acoustic time signals (i.e., echoes received at the two ears). Due to the complexity and large variability in the echoes and the flight maneuvers of bats, understanding the input-output relationships requires the ability to collect large amounts of quantitative data on the acoustics and the flight kinematics. In addition, comparing different bat species could offer a window into the principles behind the evolutionary co-adaptation of biosonar and flight. To accomplish this, a cylindrical flight tunnel that integrates synchronized arrays of 50 high-speed video cameras and 32 ultrasonic microphones has been set up on the island of Borneo. This instrument is complemented by a set of custom deep-learning techniques that can handle the large amounts of data that are being produced.

Diverse taxa use Earth’s magnetic field in combination with other sensory modalities to accomplish navigation tasks ranging from local homing to long-distance migration across continents and ocean basins. Several animals have the ability to use the inclination or tilt of magnetic field lines as a component of a magnetic compass sense that can be used to maintain migratory headings. In addition, a few animals are able to distinguish among different inclination angles and, in effect, exploit inclination as a surrogate for latitude. Little is known, however, about the role that magnetic inclination plays in guiding long-distance migrations. In this paper, we use an agent-based modelling approach to investigate whether an artificial agent can successfully execute a series of transequatorial migrations by using sequential measurements of magnetic inclination. The agent was tested with multiple navigation strategies in both present-day and reversed magnetic fields. The findings (i) demonstrate that sequential inclination measurements can enable migrations between the northern and southern hemispheres, and (ii) demonstrate that an inclination-based strategy can tolerate a reversed magnetic field, which could be useful in the development of autonomous engineered systems that must be robust to magnetic field changes. The findings also appear to be consistent with the results of some animal navigation experiments, although whether any animal exploits a strategy of using sequential measurements of inclination remains unknown.

Evidence from live gray whale strandings suggests that their navigation may be disrupted by increased radio frequency noise generated by solar storms, suggesting the potential for magnetoreception in this species.

........................................................................................................................................................ 6 Chapter 1: Introduction ................................................................................................................................. 7 1.1 The Goal of the Experiment ................................................................................................................ 7 Chapter 2: Theory ......................................................................................................................................... 9 2.1 Solar Cells ........................................................................................................................................... 9 2.2 3 Generation Solar Cells—DSSCs .................................................................................................... 9 Chapter 3: Deposition of TiO2 onto the Diatom Frustule ............................................................................ 13 3.1 Isolation and Purification .................................................................................................................. 13 3.2 Peptide Mediated Deposition ............................................................................................................ 14 3.3 Confirming Deposition ..................................................................................................................... 16 3.4 Results on the TiO2 deposition .......................................................................................................... 17 Chapter 4: Assembling and Testing the Solar Cells ................................................................................... 22 4.1 Assembling the Solar Cells ............................................................................................................... 22 4.2 Testing............................................................................................................................................... 25 4.3 Results From testing the Solar Cells ................................................................................................. 27 4.3.a Saturation Current ...................................................................................................................... 27 4.3.b Incorporating Frustules into DSSCs .......................................................................................... 33 4.3.c Final Solar Cells ......................................................................................................................... 34 Conclusion .................................................................................................................................................. 37 Citations ...................................................................................................................................................... 38 Acknowledgements ..................................................................................................................................... 42 Appendix ..................................................................................................................................................... 43 Theory ..................................................................................................................................................... 43 Experimental Technique ......................................................................................................................... 44