Integrative and Comparative Biology

Robotic herding offers a promising off-animal approach to controlling the spatial distribution of grazing livestock. Nevertheless, the habituation of cattle to herding stimuli remains a critical obstacle to its practical use. This study presents the first field investigation of behavioral responses of grazing cattle to herding by a quadruped robot. We compared the herding efficacy of a drone and a quadruped robot, and tracked daily changes in responsiveness during continuous herding. Trials were conducted in a 1.1-ha pasture with Japanese Black breeding cows from June to October 2023. The quadruped robot elicited stronger avoidance responses with shorter latencies than the drone, and herding was more successful with the robot. During consecutive daily herding with the robot, behavioral responsiveness declined progressively over the initial 5 days, at a markedly slower rate than previously reported for drone herding. Following a 24-day interruption, responsiveness partially increased, but declined rapidly again over the subsequent two days. These results indicate that the quadruped robot constitutes a more persistent aversive stimulus than a drone for grazing cattle, although habituation management strategies (such as diversifying stimuli or combining sensory modalities) will be necessary for sustained control of grazing distribution.

Developing robust methods to quantify how animals allocate time across behaviours is essential for understanding energy use, habitat requirements, and responses to environmental change. For cryptic, semi-aquatic mammals such as the platypus, direct observation is difficult, creating a reliance on remote biologging approaches that can reliably infer behaviour in the wild. However, aquatic environments can both smooth acceleration signals through hydrodynamic damping and introduce noise from water movement, turbulence, and drag, potentially obscuring behavioural differences of similar magnitudes. We tested whether progressively incorporating biomechanical and frequency-domain (FFT-derived) predictors improved behavioural classification in hydrodynamically challenging aquatic environments. Tri-axial accelerometers were deployed on four ex situ platypuses, with synchronised video observations used to validate behaviour. From the acceleration data, we derived three predictor classes of increasing complexity: summary statistics describing activity level, engineered biomechanical variables capturing posture and body orientation, and FFT-derived features describing movement rhythm. These predictors were progressively incorporated into Random Forest models to classify five behaviours: burrow resting, surface resting, grooming, travelling/foraging, and diving. Model performance improved with increasing predictor complexity, although gains were behaviour specific. FFT-derived features substantially improved classification of rhythmic behaviours such as diving and foraging, while engineered biomechanical predictors improved grooming detection. In contrast, resting behaviours, particularly surface resting, showed little improvement. Overall accuracy increased from [~]75% to [~]88% when frequency-domain features were included. Misclassification was greatest among behaviours with overlapping or low-amplitude signals, and cross-individual validation revealed reduced model generalisability, indicating that individual variation in movement patterns constrained transferability. Incorporating frequency-domain features substantially improved behavioural classification in platypuses, particularly for rhythmic behaviours such as diving and foraging. This study provides the first validated accelerometry-based behavioural classification framework for the species and highlights the importance of matching predictor selection to behavioural mechanics. More broadly, the approach offers a transferable framework for aquatic and semi-aquatic taxa.

Object detection models based on deep learning are increasingly used to reduce the manual workload associated with the processing of video recordings in behavioural research, but reproducible workflows describing how ecologists can build such models themselves remain scarce. Here, we present a step-by-step workflow for constructing a species-specific detection model and apply it as a case study to the red-legged seriema (Cariama cristata), a widely distributed but poorly studied Neotropical bird. Using 60 videos recorded with camera traps as well as non-stop recording cameras at the campus of the Universidade Federal de Vicosa (Florestal, Minas Gerais, Brazil) between 2023 and 2026, we extracted and annotated 480 images to train a YOLO26-nano detection model. On the validation set, the model achieved a precision of 0.934 and a recall of 0.786 (mAP@50 = 0.870), while performance on the independent test set was slightly lower, with a precision of 0.865 and a recall of 0.740 (mAP@50 = 0.740). When applied to unseen footage, the model processed video at roughly 4.6 times real-time speed on a standard CPU and correctly classified all four test videos for the presence or absence of seriemas. Most missed detections involved seriemas that were distant, partially out of frame, or recorded with the lower-quality non-stop cameras. These results showed that a usable detection model can be built from a comparatively small curated dataset, and the accompanying workflow and code are intended to lower the barrier for ecologists seeking to apply object detection to their own study species.

When sensory modalities yield conflicting information, animals must rapidly reassess stimuli to select their actions. We induced auditory-visual conflict in free-flying echolocating Egyptian fruit bats, by fitting animals with prisms that shifted the perceived visual location of a landing perch while echoes returned from its veridical location. Bats that course-corrected within a single goal-directed flight did so by decoupling sonar gaze from steering, to enable rapid reweighting of visual and auditory cues. We designed artificial agents that used Bayesian inference to construct estimates of goal locations in their environment. When competing estimates directed active-sensing behaviors distinctly from steering, agents course-corrected more rapidly. Consistent with this idea, when bats were fit with prisms and earplugs that attenuated auditory localization cues, they were unable to course-correct. Removing prisms produced no systematic after-effects. Our framework suggests that instead of correcting their behavior after failure, animals could efficiently employ active sensing to resolve sensory conflict before failure occurs. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=178 SRC="FIGDIR/small/743555v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@16262edorg.highwire.dtl.DTLVardef@4cd82aorg.highwire.dtl.DTLVardef@103e6fforg.highwire.dtl.DTLVardef@13292bf_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOCover figure.C_FLOATNO Bat wearing helmet with clear-glasses and tracking markers. Photograph (C) 2026 Nikita M. Finger / Moss Laboratory. C_FIG

Cruising speed is a key factor affecting prey-search efficiency and migration range in continuously swimming animals. Tunas and lamnid sharks (e.g., white sharks) have convergently evolved traits for high-speed cruising, including the ability to maintain slow-twitch, aerobic red muscle (RM) warmer than ambient water, known as RM endothermy. Despite their well-known high cruising speeds, kinematic features underlying their elevated speeds remain unclear. Swim speed is the product of tailbeat frequency (TBF; Hz) and stride length (SL, the absolute distance traveled per tailbeat; m). RM endothermy is expected to elevate TBF by enhancing muscle contraction performance. Furthermore, within RM-endothermic fishes, tunas and lamnid sharks may exhibit distinct kinematic features because of differences in caudal fin morphology and tailbeat amplitude. Here, we compiled kinematic parameters from 20 fish species, including five RM-endothermic species, measured in the wild using animal-borne sensors. Comparative analyses showed that, for a given body mass and water temperature, RM-endothermic fishes exhibited 1.9 times higher cruising speed and TBF than ectothermic fishes, while SL remained similar. Within RM-endothermic fishes, tunas exhibited 2.3 times higher TBF than similar-sized lamnid sharks, whereas lamnid sharks showed 1.7 times longer SL than similar-sized tunas. These results indicate that RM endothermy is generally associated with higher TBF, while significant kinematic differences remain between tunas and lamnid sharks. This divergence may be partly explained by the greater caudal fin area and tailbeat amplitude in lamnid sharks. It may also reflect contrasting skeletal types of teleosts and elasmobranchs, which potentially influence body stiffness and swimming kinematics.

Honey bees can swim on the water surface toward dark regions, a behavior known as scototaxis that may facilitate escape from water. Although this behavior has been reported in both honey bees and solitary bees, variation among honey bee species remains poorly understood. We compared scototaxis during swimming in four honey bee species representing two nesting types: open-nesting (Apis florea and A. dorsata) and cavity-nesting (A. cerana and A. mellifera). Individual bees were released into a water-filled arena containing a dark sector, and their landing angles were recorded. All species exhibited significant orientation toward the dark sector. However, open-nesting species showed significantly stronger orientation than cavity-nesting species. No significant differences were detected between replicate colonies within species or between species within the same nesting type, whereas differences between nesting types were highly significant. Hierarchical clustering based on orientation strength placed Osmia, a solitary cavity-nesting bee from our previous study, in the same behavioral cluster as the two open-nesting Apis species rather than the cavity-nesting honey bees. We also measured swimming duration, distance, and velocity, but found no consistent differences between nesting types. These results demonstrate substantial interspecific variation in swimming scototaxis. The behavioral clustering is consistent with the hypothesis that strong scototaxis represents an ancestral trait that has been reduced in the derived A. cerana/A. mellifera lineage.

The sea star Patiria miniata is a widely used and powerful model organism for cell, developmental, and reproductive biology, but it has lacked genetic tools for expressing transgenes or endogenously tagging proteins. We developed a protocol to endogenously tag a broadly expressed actin gene and to express additional fluorescent markers from the same locus, using CRISPR/Cas9 genome editing. We also identified and isolated a promoter sequence of this actin gene which drives expression of transgenes. This promoter and transgene cassette can be introduced via a plasmid into the genome and persist through metamorphosis into the juvenile stage. Robust methods to induce metamorphosis that result in healthy juveniles are essential for developing stable transgenic lines and have been lacking in the field. Here we report a fast and efficient approach to induce the metamorphosis of larvae into healthy juveniles by introducing surf clam shells. Thus, we present a reliable method to generate both CRISPR/Cas9 knock-in and plasmid-integrated transgenic juvenile P. miniata, enabling future research on their fascinating biology, including regeneration, oogonial stem cells, metamorphosis, and more.

Riparian environments are characterised by a high diversity of arthropod species, linking the aquatic with the terrestrial ecosystem. One of the dominant arthropod predators in this ecotone, carabid beetles are of particular interest as they may also act as facultative scavengers, feeding on carrion deposited along the shoreline. To test whether carabids feed on carrion, we examined the feeding preferences of the abundant riparian carabid Bembidion elongatum in a laboratory feeding trial, offering freshly killed and 24 hours post mortem Drosophila melanogaster. We subsequently assessed the detection probability of ribosomal prey RNA and DNA in predator gut contents using Drosophila-specific RT-PCR and PCR assays, and quantified nucleotide abundance by quantitative real-time PCR at 0, 3, 6, and 12 hours post-feeding. In the feeding experiment, B. elongatum showed a significant preference for fresh over carrion prey. Following consumption, the quantities of prey DNA and RNA in the predators gut declined over a 12-hour post-feeding period. However, no differences were detected in prey DNA or RNA quantities between individuals fed fresh prey and those fed carrion. Only immediately after consumption was the DNA:RNA ratio significantly lower in individuals fed fresh prey compared to those fed carrion while this difference was not observed at later time points. Overall, our results indicate that ingested ribosomal prey RNA in predators is present in high quantities, and that the DNA:RNA ratio is not a suitable indicator for distinguishing between consumption of carrion and fresh prey.

Advances in camera technology and computer vision techniques have allowed researchers to track animals in 3D in ways which previously were difficult or impossible. Many such 3D tracking tools make use of multiple cameras, but unfamiliarity with the principles and technology involved can make it difficult to employ such techniques. In this protocol, we describe Braid, open-source software for live, multi-camera 3D tracking of insects. Using background-subtraction, Braid performs detection of objects without requiring the use of physical markers affixed to the insect. Braid constructs low-latency 3D position estimates using Kalman filtering and nearest neighbor data association. We document in detail the process of tracking freely flying bees within a flight arena using Braid. This protocol includes instructions on installation, configuration of cameras, setup, calibration, and operation. Within the system described here, we demonstrate that Braid can achieve position estimates accurate to <1 millimeter (within a 0.3 cubic meter volume). These factors make Braid suitable for tracking small, fast-flying animals like insects. Braid's low latency allows live tracking, removing the necessity to collect large video files and making it suitable for integration in closed loop systems such as virtual reality. Code is available at https://github.com/strawlab/strand-braid

Winter poses harsh physiological challenges for insects living in temperate ponds due to the combination of low temperatures and reduced oxygen levels (hypoxia). Despite these stressors, water boatmen (Hesperocorixa sp.), backswimmers (Notonecta sp.) and diving beetles (Laccophilus maculosus) remain active year-round in eastern Nova Scotia, including in ice- covered ponds. However, the underlying mechanisms that allow pond insects to survive overwintering have not been widely studied. We hypothesized that cold and hypoxia tolerance would improve from September to March in these insects, with changes in whole-animal and biochemical correlates of tolerance to both stressors. We collected insects from the field and stocked them in outdoor freshwater mesocosms. Every two months, between September 2023 and April 2024, we characterized whole animal responses and biochemical changes. Whole insect cold tolerance assays indicated a trend of improved ability to sustain voluntary muscle control (CTmin) at lower temperatures in winter-collected insects and higher internal fluid freezing temperatures (SCP). There were no changes in whole animal correlates of hypoxia tolerance over time (surface respiration frequency, submersion and surface time). Potential cryoprotectants like proline, myo-inositol and trehalose increased in concentration in multiple insect taxa during winter but were relatively low compared to terrestrial insect studies. As lactate dehydrogenase activity did not change, there is little evidence that the insects experienced functional hypoxia sufficient to induce anaerobic metabolism. Overall, this research has established a baseline cold and hypoxia tolerance dataset in understudied pond insects. Summary StatementPond insects remain active during low temperature and low oxygen conditions associated with ice cover in winter, supported by physiological and biochemical changes.

Many insect populations are experiencing thermal stress as a result of global change, making it imperative to investigate how their relationship with other organisms will be impacted by heat disturbances. Microbial symbionts, such as bacteria, have the potential to enhance or inhibit an insect's thermal tolerance. Solitary bee larvae host bacteria within their food stores ("pollen provisions"), which have been shown to benefit survival and development; however, it is unclear how heatwaves brought about by climate change will impact their relationships with these bacterial partners. In this study, we subjected blue orchard bee (Osmia lignaria) eggs and larvae to a 4-day heatwave (35 {degrees}C daytime:22 {degrees}C nighttime) or kept them at control temperatures (25 {degrees}C daytime:15 {degrees}C nighttime), then returned all bees to control temperatures for a 5-day recovery period. We assessed bacterial communities within pollen provisions and larval development stage pre-heatwave (Day 0), immediately post-heatwave (Day 4), and following the recovery period (Day 9). Bacterial community composition, diversity, and abundance were resilient to heat stress, but larval bees developed faster when subjected to a heatwave. This finding refutes the hypothesis that bacteria within pollen provisions modulate blue orchard bee responses to heat, suggesting instead that developmental effects could be more largely shaped by bee physiology or interactions with microorganisms other than bacteria.

The sea anemone Aiptasia is a model system for understanding cnidarian loss of symbiotic algae under heat stress (bleaching). While Aiptasia polyps have been widely used to study this process, accurate symbiosis phenotyping grapples with discordant length scales: fine spatial resolution (~100 um) is needed across a whole organism (~5 mm). To address this, we consider small (~100 um), optically transparent Aiptasia larvae as a bleaching model suitable for whole-organism phenotyping by fluorescence microscopy with larvae classified as symbiotic when algae are localized within gastrodermal cells. To expedite phenotyping, we introduce a machine-learning (ML) image-analysis pipeline (SYMPHONY) designed for single-larva resolution analysis of intact larvae. SYMPHONY efficiently identifies the cellular location of internalized algae (accuracy: 79%, precision: 82%, recall: 79%, F1 score: 79%; training dataset composed of 1611 total objects). Additionally, SYMPHONY reports statistically significant larval bleaching under heat stress and corroborates manual phenotyping results, while significantly reducing operator labor from hours to minutes. The combination of the Aiptasia larvae model and the SYMPHONY pipeline aims to accelerate our understanding of symbiosis breakdown.

Many social insects, such as ants, change their behavior stereotypically from nursing to foraging as they age, a concept known as temporal polyethism. Biogenic amines are associated with these specific behaviors, but much about them remains poorly understood in these animals. Many aminergic systems lack anatomical characterization, and little is known about the expression of genes required for the aforementioned behavioral phenotypes. Here, we studied Pogonomyrmex barbatus brains and identified the neurons that produce two relevant amines, dopamine and octopamine, by detecting their synthesis enzymes, tyrosine hydroxylase and tyramine beta-hydroxylase, and their transcripts. We also compared the expression of both genes in young nurses and mature foragers by measuring the fluorescence intensity. Dopaminergic and octopaminergic neurons are predominantly located in the protocerebrum and in the subesophageal zone. Neurons that produce dopamine are also present in the optic lobes, whereas octopamine-producing ones show clusters in the antennal lobes. Both genes are downregulated as the organism ages. A reduction in the expression of these genes might be correlated with the mature workers increased propensity to perform extranidal tasks, such as foraging.

The ability of prey to eavesdrop on predator vocalizations is expected to increase survival by reducing detection and capture. Unfortunately, most research has been conducted in vertebrates, and little is known about this ability in invertebrates. We measured latency to emerge, overall activity, and shelter visits in wild-caught fall field crickets (Gryllus pennsylvanicus) in response to acoustic playback. Stimuli included multiple predator vocalizations, non-predator vocalizations, white noise, and a control. We predicted that crickets would reduce activity, spend more time in shelter, and freeze in response to stimuli representing greater risk. Contrary to our predictions, crickets traveled greater distances, spent more time moving, and spent less time in shelter in response to predator vocalizations versus controls. We did not, however, find clear differences in responses between predator vocalizations and other treatments. Our results suggest that crickets may not differentiate between the vocalizations of predators, non-predators, and other abrupt sounds. Consequently, eavesdropping may not be a viable method of assessing predation risk for this species and its general use remains unclear.

Human-influenced environments pose challenges but also provide wildlife with anthropogenic resources. Individuals vary widely in their ability to exploit such resources, often as a function of behavioural type. However, we lack a clear understanding of how variation in behavioural traits influences stages of resource exploitation required to use anthropogenic resources. Using fully automated foraging puzzles, we examined how boldness and sociability influenced three aspects of resource exploitation - discovery, problem-solving, and overall performance - in two wild populations of California ground squirrels (Otospermophilus beecheyi). Bolder individuals discovered the resource earlier, solved the task faster and achieved higher performance, indicating that boldness promotes efficient exploitation of anthropogenic resources across multiple stages in the process. Greater sociability and more opportunities to observe conspecifics solving the task led to faster problem-solving, consistent with evidence for observational learning. Squirrels in the recreational-use population - with regular exposure to humans and anthropogenic food - were faster to discover the resource than those in a trail-use population - where human exposure was transient and no anthropogenic food available. Problem-solving latency and performance were consistent between populations. Our findings highlight how individual variation in behavioural traits drives performance in novel ecological contexts, providing a mechanistic understanding of behavioural plasticity in human-influenced environments.

Animals face a fundamental trade-off between food-related competition and predation risk in how they allocate time and behavior. Nocturnal mammals offer a particularly tractable system for testing this trade-off because moonlight creates a natural, quantifiable gradient in both predation risk and the visibility needed for safe movement. We used minute-by-minute focal observations of nine kinkajous (Potos flavus; 4 female, 5 male) in Panama to test how fruit abundance and moonlight predicted nocturnal activity budgets (percent time traveling, feeding, resting) and nightly travel distance. Beta-family generalized linear mixed models and a linear mixed model of log travel distance showed that fruit abundance was positively associated with percent time traveling and with nightly travel distance, and negatively associated with percent time feeding: kinkajous traveled more and fed less per hour when fruit was abundant, consistent with movement between many nearby productive trees rather than prolonged feeding at a few. Males traveled less as moonlight increased, while females traveled more. Rainfall had no independent effect. We interpret the sex-reversed moonlight response as evidence that moonlight elevates predation risk for males while facilitating movement for the more food-limited females of this frugivorous carnivore.

Animals reproduce across a spectrum from oviparity to viviparity. Internal gestation and live birth have inherent advantages despite their costs. However, comparative analyses of key drivers, such as resilience to dehydration, lack taxonomic breadth. In this study, we assessed whether live birth improves the ability to proliferate in environments with limited access to water. To do so, we used the viviparous cockroach, Diploptera punctata, as a model of viviparity to assess dehydration-induced damage during extended periods of water deprivation. During pregnancy, maternal survival did not decline during dry periods compared with non-pregnant individuals, suggesting that pregnancy has minimal impact on resistance to dehydration stress. When mothers are deprived of water for 2 weeks, they show an increase in osmolality after one week, while their embryos show no change in osmolality until after two weeks, at which point abortions occur. Periods of dehydration increased the duration of pregnancy, likely due to a slower production of in utero milk, but there was no change in the size of progeny. After birth, viviparous D. punctata newborns showed increased survival under dry conditions compared to two other ovoviviparous species, which are much smaller and dehydrate more quickly. The combined impact of increased dehydration resistance during pregnancy and during the first independent phase indicates a benefit of prolonged viviparity in Diploptera punctata. This study provides evidence that viviparity in animal systems could enable progeny survival during drought.

Environmental predictability influences the value of information acquired through experience, yet relatively little is known about how instability in resource characteristics influences behavioural organisation during foraging. We tested whether repeated changes in floral orientation, a manipulation of environmental predictability, affect pollen foraging in bumblebees (Bombus terrestris) by exposing naive workers to either stable floral conditions (single flower orientation) or repeated inter-trial changes in flower orientation (three alternating flower orientations), under constant resource availability. We quantified pollen collection, foraging efficiency, revisitation behaviour, floral coverage and sonication behaviour across three successive foraging trials of either constant or variable flower orientation, before assessing performance in a common post-treatment preference test in which bees were offered all three flower orientations and higher pollen rewards. Environmental instability altered the organisation of foraging behaviour. Bees exposed to unstable floral conditions progressively reduced flower revisitation behaviour and were less likely to perform sonication, although floral coverage, defined as the number of unique flowers visited, remained unchanged. Contrary to our predictions, instability had only weak immediate effects on pollen acquisition and foraging efficiency compared to bees tested under stable conditions. However, previous exposure to instability generated carry-over effects in the common post-treatment preference test. Bees previously exposed to unstable conditions were significantly less likely to return with pollen and consequently collected less pollen overall than bees previously exposed to stable conditions. Our results demonstrate that environmental instability can influence pollen foraging in ways that are not captured by immediate measures of performance. Although behavioural adjustments appeared to buffer short-term consequences during repeated foraging trials, carry-over effects were evident when bees were later tested in a common high-reward, multi-orientation floral array. These findings highlight the importance of considering both behavioural flexibility and carry-over effects when evaluating how organisms respond to changing environments.

Populations are exposed to multiple anthropogenic stressors simultaneously; however, the combined effects are poorly understood. Climate change is starkly impacting marine ecosystems and consequently fishes, with warming temperatures and increases in frequencies and durations of extreme climate events. Concurrently, plastics, such as nylon used in fishing industries, are contaminating marine waters at unprecedented levels, with detrimental effects on fishes. Here we studied the cumulative effects of warming and nylon microplastic fibres on the behavior and physiology of threespine stickleback (Gasterosteus aculeatus) by exposing fish to conditions of 15{degrees}C and 20{degrees}C and nylon concentrations of 0, 1, 10, and 100 mg/g (mg nylon/g food) for 4 weeks. Feeding rates responded complexly to multiple stressors, as increasing concentrations of plastic reduced feeding rates, with warming having an antagonistic effect. Furthermore, we observed "coughing" behaviors in response to ingestion of microfibres and a unique reselection tendency of food items previously selected by conspecifics. Under warming conditions, critical thermal maximum (CTmax) increased; however, exposure to plastics led to reductions in CTmax and thermal safety margins. Given these results, we anticipate reduced acclimation capacities, greater anxiety, and reductions in foraging efficiencies with increasing concentrations of plastic. Cumulatively, these stressors will yield greater energetic trade-offs and decreased accuracy in food selection with stark implications for marine ecosystem dynamics.

Insects solve complex behavioural tasks with remarkable efficiency, using minimal neural hardware tuned to the specific requirements of their ecological niches. To truly understand or replicate these behaviours, it is insufficient to model the brain in isolation: one must account for the dynamic, closed-loop interactions between the environment, the physical organisation of the sensory periphery, and internal biophysical dynamics. To address these issues for visually controlled behaviours, we present RhabdoForge, a modular, hardware-agnostic and high-performance rendering framework specifically designed for insect neuroethology and neuromorphic research. Designed for seamless integration into Python-based workflows, RhabdoForge implements both real-time ray-tracing and stochastic path-tracing using hardware-agnostic GPU pipelines. Crucially, the engine moves beyond the static "ommatidium-as-a-pixel" paradigm by introducing a fully parametrisable model where every layer of the compound eye (from the geometric shape and the topological lattice to the internal rhabdomere blueprint) is a discrete, swappable component. The engine is capable of simulating the high-frequency, sub-ommatidial rhabdomere photomechanical actuation, allowing for the investigation of a variety of active sensing phenomena within a real-time closed-loop environment. The framework also includes an automated morphological pipeline that allows transforming 2D anatomical data into faithful 3D sensory models. We validate the engine through two case studies: a closed-loop optic-flow centring response in a virtual tunnel, and the recovery of spatial hyperacuity via rhabdomere microsaccades. By providing a bridge between high-fidelity visual ecology and neuromorphic modelling, RhabdoForge enables researchers to explore how the interplay of sensory optics and neural processing can generate complex behaviour in both biological and artificial agents.