Detecting the Invisible: Interspecies Communication as Signal Architecture: Evaluating Electrical Ecology and the Possibility of Artificially Embedded Detection Systems

Interspecies Communication as Signal Architecture: Evaluating Electrical Ecology and the Possibility of Artificially Embedded Detection Systems

Low Rents, April 2026

Abstract

Interspecies communication encompasses a wide range of signaling modalities, including acoustic, chemical, tactile, vibrational, visual, and electrical channels. While traditionally studied within ecological and evolutionary frameworks, emerging research in electrical ecology, particularly involving pollinators such as bees, demonstrates that organisms can detect and respond to weak environmental electromagnetic fields.

This paper synthesizes empirical evidence across interspecies communication systems and introduces a novel interpretive framework: that biological signaling modalities may serve as analogues for engineered detection systems. Specifically, we investigate whether references to bees and electrical interactions in Justin Posey’s Beyond the Map’s Edge chapter "The Snout Scout" can be interpreted as a metaphor, or operational clue, indicating the presence of a hidden signal-emitting device.

Through comparative analysis of biological systems and technological signal architectures (e.g., Bluetooth Low Energy beacons, RF transmitters, and passive electromagnetic anomalies), we argue that several properties of interspecies signaling, detectability thresholds, modality layering, environmental attenuation, and receiver specialization, map directly onto modern sensing technologies.

We propose that Posey’s framing of “invisible signals” may intentionally mirror biological systems in which only the appropriately tuned receiver can detect the signal, suggesting a hybrid ecological–technological puzzle design.

Introduction

Communication is traditionally defined as the transfer of information between a sender and a receiver, resulting in a measurable change in the receiver’s behavior or physiological state. Within evolutionary biology, this process has been extensively studied in conspecific contexts, where signaling systems are shaped by natural selection to optimize reproductive success, survival, and social coordination. However, communication across species boundaries, interspecies communication, introduces a more complex landscape in which information exchange may be cooperative, exploitative, incidental, or even deceptive.

A central challenge in this domain lies in distinguishing between signals, which are traits selected specifically because they influence receivers, and cues, which are incidental by-products that nevertheless convey usable information. This distinction becomes particularly blurred in interspecific interactions, where many receivers evolve to exploit information that the sender did not evolve to provide. Classic examples include predator kairomones, heterospecific alarm-call networks, and plant volatile emissions that attract parasitoids.

Despite this ambiguity, a growing body of empirical research demonstrates that interspecies information transfer is both widespread and mechanistically sophisticated. Across ecological systems, ranging from terrestrial plant–insect interactions to marine symbioses and aerial predator–prey dynamics, organisms utilize diverse modalities to encode and decode information. These modalities include acoustic signals (e.g., alarm calls and mimicry), chemical gradients (e.g., volatile organic compounds and quorum sensing), tactile interactions (e.g., cooperative grooming and contact signaling), vibrational cues (e.g., substrate-borne alarms), visual displays (e.g., bioluminescent mimicry), and, more recently, electrical fields.

Among these, electrical signaling has emerged as a particularly compelling and underexplored modality. Research in electrical ecology has demonstrated that certain organisms, most notably pollinators such as bumblebees, are capable of detecting weak electric fields generated by environmental interactions. Flowers, for example, maintain electric potentials relative to the atmosphere and surrounding ground, and these fields are dynamically altered by the presence and activity of pollinators. Bees are able to detect these variations through mechanosensory structures, allowing them to discriminate between recently visited and unvisited flowers and thereby optimize foraging efficiency.

The implications of this capability extend beyond pollination biology. Electrical fields are inherently invisible, spatially distributed, and continuously present, forming a layer of environmental information that is inaccessible without specialized detection mechanisms. Unlike visual or acoustic signals, which are often salient and directly perceptible, electrical signals operate at the threshold of detection, requiring both sensitivity and appropriate interpretive frameworks. This raises a broader conceptual question:

To what extent are ecological systems structured not only by visible and audible signals, but by hidden layers of information that are only available to organisms, or instruments, capable of detecting them?

This question becomes particularly relevant when considering the convergence between biological signaling systems and modern sensing technologies. Advances in engineering have produced a wide range of devices capable of detecting weak signals across multiple modalities, including radio frequency (RF) transmissions, electromagnetic field (EMF) variations, and low-energy acoustic or vibrational emissions. Many of these systems operate on principles analogous to biological detection: sensitivity to gradients, noise filtering, and modality-specific tuning.

Within this interdisciplinary context, it becomes possible to reinterpret certain narrative or descriptive elements, particularly those invoking biological phenomena, as potential analogues or metaphors for engineered systems. One such case arises in Justin Posey’s Beyond the Map’s Edge, in which references are made to bees interacting with electrical outputs in natural environments. While such references may be read as observational or poetic, they also align closely with established principles of electrical ecology and, by extension, with the functional characteristics of modern signal detection systems.

This paper explores the possibility that such references may serve a dual purpose:

As accurate descriptions of biological phenomena, and
As conceptual cues pointing toward a signal-based detection framework rather than a purely spatial or visual search paradigm

Accordingly, the central research question guiding this study is:

That references to bees and electrical signaling in Beyond the Map’s Edge may function as a metaphor, or instruction, for detecting an artificially embedded signal associated with a hidden object.

To address this question, the paper proceeds in three stages. First, it establishes a conceptual and evidentiary framework for evaluating interspecies communication across modalities. Second, it synthesizes a series of well-documented case studies, analyzing their mechanisms, functions, and evolutionary plausibility. Third, it maps these biological systems onto technological analogues, evaluating whether the structural similarities are sufficient to support the proposed hypothesis.

By situating biological communication within a broader framework of information detection and interpretation, this study aims to bridge the gap between ecology and engineering, and to explore the possibility that the principles governing natural systems may be deliberately mirrored in human-designed contexts.

Conceptual Framework: Biological Signals as Engineering Analogues

Signals, Cues, and Detectability

Biological systems distinguish between signals (selected for communication) and cues (incidentally informative).

In engineering terms, this distinction maps closely to:

Intentional broadcasts (signals)
Environmental emissions or leakage (cues)

Both can be detected - but only by receivers with the appropriate sensitivity and decoding mechanisms.

Electrical Ecology and Sensory Thresholds

Bees detect electric fields via mechanosensory hairs that respond to electrostatic forces. These fields are extremely weak, often on the order of tens to hundreds of volts per meter, but still reliably detectable.

This establishes three critical principles:

Signals need not be strong to be functional
Detection depends on receiver tuning, not signal magnitude alone
Environmental embedding can obscure signals from general perception

These principles are directly transferable to engineered systems.

Biological Case Studies as Signal Design Templates

Electrical Detection: Bees and Floral Fields

Bumblebees use electric field gradients to identify recently visited flowers. The field changes dynamically as bees interact with flowers, creating a temporal signal layer.

Engineering parallel:

Passive EM emitters or charged surfaces
Detectable via specialized sensors (EMF meters, antenna arrays)
Signal varies based on interaction or proximity

Chemical Signaling: Kairomones and Constraints

Fish release bile salts that Daphnia detect to avoid predation. These signals persist because they are tied to essential biological processes.

Engineering parallel:

Unavoidable emissions (heat, RF leakage)
Detectable even if not intentionally broadcast
Useful for indirect localization

Acoustic Deception: Drongos

Drongos exploit alarm-call systems to manipulate other species.

Engineering parallel:

Signal spoofing
False positives in detection systems
Requirement for validation mechanisms

Vibrational Signaling: Treehopper–Ant Systems

Treehoppers recruit ants using substrate vibrations.

Engineering parallel:

Ground-based signal propagation
Detectable via contact sensors
Limited range but high specificity

Mapping Biological Modalities to Detection Technologies

Biological Modality	Mechanism	Technological Analog	Detection Method
Electrical	Field gradients	BLE beacon / EM emitter	RF scanner / EMF meter
Chemical	Diffusing compounds	Gas emission / thermal plume	Sensor arrays
Acoustic	Alarm calls	Audio beacon	Microphone array
Vibrational	Substrate signals	Ground vibration device	Geophone
Visual	Bioluminescence	LED/optical marker	Optical detection

This mapping demonstrates that each major biological signaling modality discussed has a technological analogue.

Central Hypothesis: Posey’s Signal as Hidden Infrastructure

Interspecies Signaling as a Model for Embedded Detection Systems

Formal Statement of the Hypothesis

The central hypothesis of this study is that:

References to bees and electrical interactions in Beyond the Map’s Edge function as an intentional metaphor, or operational abstraction, indicating the presence of a hidden, artificially embedded signal that is detectable only through modality-specific sensing analogous to biological systems.

This hypothesis rests on the convergence of three independently validated domains:

Biological systems demonstrate reliable detection of weak, non-visible signals (e.g., electric fields, chemical gradients)

Physical systems allow for low-power, localized signal emission across multiple modalities (e.g., RF, EM, acoustic, vibrational)

Narrative encoding strategies can embed technical instruction within metaphorical or ecological descriptions

The intersection of these domains creates a plausible framework in which biological phenomena are used as instructional analogues for engineered detection tasks.

Decomposition of the Hypothesis

To move from conceptual plausibility to analytical rigor, the hypothesis can be decomposed into four interdependent components:

Signal Existence

There exists a localized, physically measurable signal embedded within the environment.

This signal may take one or more of the following forms:

Electromagnetic field variation

Radio frequency emission (continuous or intermittent)

Acoustic or ultrasonic output

Vibrational transmission through substrate

Critically, the signal is assumed to be:

Low power (to avoid broad detectability)

Spatially constrained (detectable only within proximity)

Environmentally integrated (masked by background conditions)

Modality-Specific Detectability

The signal is not readily detectable through unaided human perception, but requires instrumentation or specialized techniques.

This aligns directly with biological precedents:

Bees detect electric fields via mechanosensory hairs

Daphnia detect dissolved chemical cues at extremely low concentrations

Birds interpret acoustic patterns imperceptible to human discrimination

Thus, detectability is not a function of signal absence, but of receiver capability.

Instructional Encoding via Biological Analogy

The reference to bees and electrical interactions functions as a conceptual mapping, not merely a descriptive passage.

Specifically, it encodes three operational ideas:

Invisible signal presence → electrical field analogy

Receiver specialization → bees as tuned detectors

Gradient-based discovery → movement toward signal source

This form of encoding is consistent with:

Puzzle design strategies

Indirect instructional frameworks

Cognitive anchoring through natural systems

Required Search Paradigm Shift

If the above components hold, then the correct search strategy is not purely spatial but instrumental and signal-driven.

This requires transitioning from:

Static interpretation → Dynamic measurement

Visual inspection → Multi-modal sensing

Location-based reasoning → Signal-gradient tracking

Mechanistic Pathways for Signal Implementation

For the hypothesis to be physically viable, the signal must be realizable within known technological constraints. Several candidate mechanisms satisfy these criteria:

Low-Power RF Emitters

Devices such as Bluetooth Low Energy (BLE) beacons or LoRa transmitters can emit identifiable signals with minimal power consumption and limited range.

Detectable via handheld scanners

Signal strength decays predictably with distance

Can be intermittent or encoded

Passive Electromagnetic Anomalies

Metallic objects, wiring, or charged surfaces can create localized electromagnetic disturbances.

Detectable via EMF meters

Do not require active power in all cases

May blend into environmental noise

Acoustic or Ultrasonic Emitters

Low-frequency or ultrasonic devices can produce signals outside normal human hearing.

Detectable with specialized microphones

Subject to terrain and atmospheric attenuation

Can create directional gradients

Vibrational Transmission

Devices embedded in or coupled to substrate (rock, soil, wood) can produce detectable vibrations.

Detectable via contact sensors or geophones

Highly localized

Resistant to long-range detection

Signal Properties and Environmental Constraints

For the system to remain undiscovered under conventional search conditions, it must satisfy several constraints:

Signal Attenuation

All candidate modalities exhibit distance-dependent decay, typically following inverse-square or exponential attenuation patterns.

This creates:

A detection radius

A gradient usable for directional searching

Noise Masking

Environmental conditions (wind, thermal variation, RF noise) create background interference.

Effective signal design must:

Operate within or near noise thresholds

Require filtering or comparative measurement

Temporal Variability

Signals may be:

Continuous

Intermittent

Condition-dependent (e.g., temperature, movement)

This introduces an additional layer of complexity consistent with biological signaling systems.

Predictions Derived from the Hypothesis

A robust hypothesis must generate testable predictions. If correct, the following should be observable:

Anomalous signal detection

Measurable deviation from baseline in one or more modalities

Spatial gradient behavior

Signal strength increases as distance to source decreases

Modality specificity

Signal detectable only within a particular sensing domain

Localized detection zone

Signal disappears beyond a defined radius

Repeatability

Detection is consistent under similar environmental conditions

Falsifiability Criteria

The hypothesis can be rejected if:

No measurable signal is detected across relevant modalities

Observed signals do not exhibit spatial gradient behavior

Detected anomalies are fully explained by known environmental sources

No correlation exists between signal presence and hypothesized location

This ensures that the framework remains empirically grounded rather than purely interpretive.

Integration with Biological Models

The strength of this hypothesis lies in its grounding within biological precedent.

In natural systems:

Signals are often weak, localized, and context-dependent

Detection depends on specialized receivers

Information is embedded in environmental gradients

The proposed system mirrors these characteristics, suggesting that biological communication may serve as a functional blueprint for engineered detection challenges.

Synthesis

Taken together, the hypothesis reframes the problem space from one of hidden objects to one of hidden information.

Rather than assuming that the target is concealed solely through physical means, it posits that concealment may instead be achieved through modal invisibility - the use of signals that exist but are not perceivable without the correct tools or interpretive framework.

This leads to a final, unifying proposition:

The critical variable is not the presence of the object, but the alignment between the signal it emits and the receiver used to detect it.

Discussion

The synthesis presented in this study reveals that interspecies communication is not a marginal or anomalous phenomenon, but rather a fundamental organizing principle of ecological systems. Across taxa and environments, organisms continuously generate, modify, and exploit information embedded in physical media - air, water, substrate, and electromagnetic fields. These interactions span a continuum from tightly coevolved signaling systems to opportunistic cue exploitation and sensory interference, suggesting that the distinction between “communication” and “environmental information use” is often one of interpretation rather than mechanism.

Communication as Environmental Information Processing

One of the most consistent insights across the examined case studies is that communication does not require discrete, intentional “messages” in the human sense. Instead, many systems operate through gradients, modulations, and probabilistic associations, where receivers interpret changes in environmental states rather than explicit symbolic signals.

For example, herbivore-induced plant volatiles form complex, diffuse chemical plumes shaped by atmospheric conditions, while electric fields surrounding flowers fluctuate dynamically with pollinator activity. Similarly, substrate-borne vibrational signals and acoustic alarm calls propagate through noisy environments, requiring receivers to extract relevant information from variable and often degraded inputs.

From a systems perspective, these processes can be understood as forms of distributed sensing, in which information is not localized but embedded within the structure of the environment itself. Organisms function as both transmitters and receivers within these networks, contributing to and interpreting shared informational landscapes.

This reframing has important implications. It suggests that the key variable in communication is not merely signal production, but receiver capability - that is, the ability to detect, filter, and interpret relevant features of the environment. In this sense, communication systems are defined as much by the evolution of receivers as by the evolution of signals.

The Signal–Cue Continuum Revisited

The classical distinction between signals and cues becomes increasingly difficult to maintain under this framework. While theoretically useful, the dichotomy assumes a level of intentionality and evolutionary specificity that is often not empirically demonstrable.

Many of the strongest examples reviewed here occupy ambiguous positions along this continuum. Floral electric fields, for instance, are clearly detected and used by bees, yet it remains uncertain whether these fields evolved specifically to influence pollinator behavior or whether they arise as unavoidable physical consequences of plant–environment interactions. Similarly, plant volatiles can function as indirect defense mechanisms, but they are also exploited by herbivores and other unintended receivers.

Rather than treating signals and cues as discrete categories, it may be more productive to conceptualize interspecies communication as a spectrum of informational interactions, characterized by varying degrees of evolutionary coupling between sender and receiver. At one end are tightly coevolved mutualistic systems with clear bidirectional benefits; at the other are purely incidental emissions that are opportunistically exploited.

This perspective aligns with emerging views of ecological systems as information networks, where multiple species participate in overlapping channels of information exchange, each with different levels of specificity and reliability.

Electrical Ecology and the Problem of Invisibility

Among the modalities examined, electrical signaling is uniquely positioned to challenge conventional assumptions about communication. Unlike acoustic or visual signals, which are typically salient and easily observable, electrical fields are inherently invisible, continuous, and spatially diffuse. Their detection requires specialized sensory structures or instruments capable of resolving weak field gradients against background noise.

The ability of bees to detect floral electric fields demonstrates that such signals can be both biologically meaningful and behaviorally actionable, despite their low amplitude and lack of direct perceptibility.

This introduces a critical conceptual shift:

Communication can occur through channels that are entirely inaccessible without the appropriate detection mechanism.

In other words, the absence of observable evidence does not imply the absence of information. Instead, it may reflect a limitation in the observer’s sensory or technological capabilities.

This principle is well established in physics and engineering, where phenomena such as electromagnetic radiation, radio frequency transmission, and acoustic vibrations often operate outside the range of human perception. The convergence between these domains and biological systems suggests that electrical ecology may represent a bridge between natural and engineered information systems.

Biological Systems as Templates for Engineered Detection

The structural similarities between biological signaling modalities and technological detection systems are not merely superficial. In both cases, effective information transfer depends on a shared set of constraints and design principles, including:

Signal attenuation and range limitations
Environmental noise and interference
Receiver sensitivity and tuning
Spatial and temporal variability

For instance, low-power radio frequency devices such as Bluetooth Low Energy (BLE) beacons operate using weak signals that attenuate rapidly with distance and are influenced by environmental factors such as terrain, vegetation, and atmospheric conditions. Detection relies on measuring signal strength gradients and filtering noise - processes that closely parallel how organisms track chemical plumes or electric fields.

Similarly, passive electromagnetic emissions and unintended signal leakage, analogous to biological cues, can be detected and exploited by receivers without any intentional signaling by the source.

These parallels suggest that biological systems may serve as functional analogues or design templates for engineered detection systems, particularly in contexts where signals must remain unobtrusive or difficult to detect without specialized tools.

Implications for Signal-Based Search Paradigms

When viewed through this integrated framework, the hypothesis explored in this paper gains conceptual coherence. References to bees interacting with electrical outputs can be interpreted not only as descriptions of ecological phenomena, but as metaphorical representations of signal detection processes.

In this interpretation, the key insight is not the specific biological interaction, but the underlying principle:

That meaningful information may be present in the environment but remains inaccessible without the correct detection modality.

Applied to a search context, this suggests a fundamental shift in strategy. Rather than relying exclusively on visual inspection or geographic reasoning, a searcher would need to adopt a multi-modal detection approach, incorporating tools capable of identifying weak or embedded signals.

Such an approach would prioritize:

Detection of signal gradients rather than fixed points
Identification of anomalies relative to background conditions
Iterative refinement of receiver sensitivity and filtering parameters

Importantly, this framework does not require the presence of a high-power or easily detectable signal. On the contrary, the most biologically analogous systems involve low-energy, short-range signals that are only detectable within specific spatial and environmental contexts.

Limitations and Alternative Interpretations

Despite the conceptual alignment between biological and technological systems, several limitations must be acknowledged.

First, the proposed hypothesis remains indirect and inferential. While the biological analogues are well supported, there is no direct empirical evidence demonstrating the existence of an engineered signal in the specific context under consideration.

Second, biological systems often exhibit redundancy and multimodality, with multiple overlapping channels of information. It is therefore possible that references to electrical interactions serve as one of many potential interpretive pathways rather than a definitive instruction.

Third, the risk of overfitting interpretation must be considered. The mapping between biological and technological systems, while structurally compelling, may reflect general principles of information transfer rather than intentional design in any particular instance.

Future research should therefore focus on empirical validation through field-based experimentation, including systematic scanning across multiple modalities, controlled testing of detection equipment, and quantitative analysis of environmental signal variation.

Toward an Integrated Theory of Hidden Signals

The broader implication of this work is that communication, whether biological or engineered, can be understood as a process of encoding, embedding, and detecting information within physical systems.

Biological organisms have evolved to exploit these processes with remarkable efficiency, often operating at the limits of physical detectability. Technological systems, in turn, replicate these principles through instrumentation and signal processing.

By integrating these perspectives, it becomes possible to conceptualize a unified framework in which:

Signals may be intentionally or unintentionally produced
Information may be visible or hidden
Detection depends on the alignment between signal properties and receiver capabilities

Within such a framework, the distinction between natural and artificial systems becomes less significant than the shared constraints governing information transfer.

Synthesis

Taken together, the evidence suggests that interspecies communication is best understood not as a discrete category of biological interaction, but as part of a broader continuum of information dynamics in complex systems.

Electrical ecology, in particular, highlights the existence of hidden layers of environmental information that are both real and actionable, yet inaccessible without appropriate detection mechanisms.

When these principles are applied to interpretive or exploratory contexts, they imply that the challenge is not solely one of location, but of perception and methodology.

The critical question, therefore, is not simply whether a signal exists, but whether the observer is equipped, conceptually and technologically, to detect it.

Conclusion

This study set out to examine interspecies communication not only as a biological phenomenon, but as a broader architecture of information transfer across systems. Through synthesis of acoustic, chemical, tactile, vibrational, visual, and electrical modalities, a consistent pattern emerges: organisms routinely detect, interpret, and act upon signals that are imperceptible without specialized receivers.

Across the strongest cases, legume–rhizobium signaling, honeyguide–human cooperation, and cleaner wrasse–client interactions, communication systems demonstrate clear evolutionary shaping, bidirectional influence, and measurable functional outcomes. In contrast, many widely cited examples, including kairomone-mediated predator avoidance and heterospecific alarm-call interpretation, are more accurately understood as cue exploitation, where receivers extract information from signals not evolved for them. This distinction is not trivial; it defines the boundary between intentional communication and opportunistic detection.

Within this framework, electrical ecology occupies a particularly important position. Unlike chemical or acoustic signals, which are often more intuitively understood, electrical fields represent a subtle, spatially embedded modality that operates continuously in the background of ecological systems. The demonstrated ability of pollinators such as bees to detect weak electric fields—mediated through mechanosensory structures and influenced by environmental conditions—establishes that biologically meaningful information can exist in forms that are effectively invisible to unaided perception.

This realization provides the conceptual bridge to the central hypothesis explored in this paper. If biological systems routinely exploit weak, embedded signals through specialized detection mechanisms, then it is both theoretically and practically plausible that similar principles could be intentionally replicated in engineered contexts. The mapping between biological signaling modalities and technological analogues, particularly in the domains of low-power radio frequency transmission, electromagnetic field detection, and sensor-based localization, reveals a strong structural correspondence. In both cases, successful detection depends less on signal strength than on receiver tuning, environmental context, and search strategy.

Interpreted through this lens, references to bees and electrical interactions in Beyond the Map’s Edge can be understood not merely as descriptive natural observations, but as a potential instructional metaphor. The emphasis on organisms perceiving what is otherwise undetectable suggests a shift in problem framing; from locating a static object through visual or geographic reasoning to identifying a target through signal-based detection. In such a framework, the “hidden” nature of the object is not solely a function of physical concealment, but of modal invisibility, accessible only through the correct interpretive or technological approach.

Importantly, this hypothesis does not require the existence of a high-power or easily detectable transmission system. On the contrary, the most consistent parallels with biological systems suggest that an effective design would favor low-energy, short-range, and environmentally masked signals, analogous to floral electric fields or substrate-borne vibrations. Such signals would be inherently resistant to casual discovery while remaining detectable to individuals employing the correct tools and methodologies.

This reframing has significant implications for both the interpretation of interspecies communication and the design of human-mediated search problems. It suggests that biological systems can serve not only as subjects of study, but as design templates for engineered information systems - particularly those intended to operate below the threshold of general perception. At the same time, it highlights the importance of interdisciplinary approaches that integrate behavioral ecology, physics, and engineering in order to fully understand how information is transmitted and detected in complex environments.

Several limitations must be acknowledged. The proposed hypothesis remains speculative in the absence of direct empirical validation of an engineered signal. Furthermore, biological analogues, while structurally informative, do not guarantee intentional design in any specific case. Future work should therefore prioritize field-based detection experiments, systematic scanning across multiple modalities (e.g., RF, EM, acoustic, and vibrational), and controlled evaluation of environmental signal gradients. Such efforts would allow the hypothesis to transition from conceptual plausibility to empirical testability.

In conclusion, interspecies communication reveals that the natural world is saturated with information channels that are invisible, context-dependent, and receiver-specific. By extending this principle into the realm of engineered systems, this paper proposes that the boundary between biological signaling and technological detection may be more permeable than traditionally assumed. Whether interpreted as metaphor, misdirection, or deliberate instruction, the integration of electrical ecology into the analytical framework fundamentally alters the search paradigm:

The problem is no longer simply where to look, but how to detect.

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