Study Of Animal Behaviour Research Articles

Incorporating vertical dimensionality improves biological interpretation of hidden Markov model outputs

Quantifying animal movement is a central component of ecological inquiry. Movement patterns provide insights into how animals make habitat decisions in pursuit of their life‐history requirements. Within this context, animals are expected to modulate their movement when navigating landscape complexities like steep or uneven slopes. However, the analytical tendency to predict animal movement as a function of bivariate (x, y) telemetry data (i.e. 2D methods) excludes such complexities and presumes that the landscapes over which this movement occurs are completely flat. Failure to consider vertical dimensionality may inhibit quantification and interpretation of animal behaviors, such as outputs of hidden Markov models (HMMs) built upon geometric measurements of animal movement like step length and turning angle. To explore the analytical consequences of this assumption, we utilized a dataset of GPS collared pumas Puma concolor in the Santa Cruz mountains of central California. We fit HMMs using traditional 2D step lengths and turning angles and compared them to HMMs built upon movement geometries in which we incorporated vertical dimensionality (i.e. 2D+). We then used a combination of quantitative inspection of model outputs and visual evaluation in 3D rendering software to understand what new states and biological interpretations can be facilitated by using 2D+ data. We found that 2D+ HMMs outperformed 2D HMMs in their ability to explain variation in vertical dimensionality. Furthermore, 2D+ models were able to isolate distinctive behavioral states associated with vertical dimensionality, such as movements on and off ridgelines. Our results show that 2D+ techniques enable researchers to directly investigate variation in animal movement and behavioral states across complex landscapes. We discuss the implications of our results for future study of animal behavior and energetics as well as illustrate how our methods can be tractably incorporated into HMMs to enable researchers to gain greater insights into animal movement ecology.

Automated monitoring of honey bees with barcodes and artificial intelligence reveals two distinct social networks from a single affiliative behavior

Barcode-based tracking of individuals is revolutionizing animal behavior studies, but further progress hinges on whether in addition to determining an individual’s location, specific behaviors can be identified and monitored. We achieve this goal using information from the barcodes to identify tightly bounded image regions that potentially show the behavior of interest. These image regions are then analyzed with convolutional neural networks to verify that the behavior occurred. When applied to a challenging test case, detecting social liquid transfer (trophallaxis) in the honey bee hive, this approach yielded a 67% higher sensitivity and an 11% lower error rate than the best detector for honey bee trophallaxis so far. We were furthermore able to automatically detect whether a bee donates or receives liquid, which previously required manual observations. By applying our trophallaxis detector to recordings from three honey bee colonies and performing simulations, we discovered that liquid exchanges among bees generate two distinct social networks with different transmission capabilities. Finally, we demonstrate that our approach generalizes to detecting other specific behaviors. We envision that its broad application will enable automatic, high-resolution behavioral studies that address a broad range of previously intractable questions in evolutionary biology, ethology, neuroscience, and molecular biology.

Approximations of algorithmic and structural complexity validate cognitive-behavioral experimental results.

Being able to objectively characterize the intrinsic complexity of behavioral patterns resulting from human or animal decisions is fundamental for deconvolving cognition and designing autonomous artificial intelligence systems. Yet complexity is difficult in practice, particularly when strings are short. By numerically approximating algorithmic (Kolmogorov) complexity (K), we establish an objective tool to characterize behavioral complexity. Next, we approximate structural (Bennett's Logical Depth) complexity (LD) to assess the amount of computation required for generating a behavioral string. We apply our toolbox to three landmark studies of animal behavior of increasing sophistication and degree of environmental influence, including studies of foraging communication by ants, flight patterns of fruit flies, and tactical deception and competition (e.g., predator-prey) strategies. We find that ants harness the environmental condition in their internal decision process, modulating their behavioral complexity accordingly. Our analysis of flight (fruit flies) invalidated the common hypothesis that animals navigating in an environment devoid of stimuli adopt a random strategy. Fruit flies exposed to a featureless environment deviated the most from Levy flight, suggesting an algorithmic bias in their attempt to devise a useful (navigation) strategy. Similarly, a logical depth analysis of rats revealed that the structural complexity of the rat always ends up matching the structural complexity of the competitor, with the rats' behavior simulating algorithmic randomness. Finally, we discuss how experiments on how humans perceive randomness suggest the existence of an algorithmic bias in our reasoning and decision processes, in line with our analysis of the animal experiments. This contrasts with the view of the mind as performing faulty computations when presented with randomized items. In summary, our formal toolbox objectively characterizes external constraints on putative models of the "internal" decision process in humans and animals.

Body condition metrics explain fish movement in experimental streams

AbstractBody condition refers to an array of physiological or nutritious states in animals, but body condition is typically measured using a single metric in animal behavior studies. In this paper, we conducted a three‐day laboratory study to evaluate whether metrics of body condition affected movement of wild‐caught creek chub (Semotilus atromaculatus) at 16 and 22°C. Movement was counted between two circular tanks connected by a straight corridor, which was equipped with a pair of passive integrated transponder antennas. Fish movement was most frequent during periods of darkness in a simulated photoperiod, and more mobile individuals consistently moved more frequently across the 3 days. In general, individuals in better body condition were more mobile than those in poorer condition, and different metrics of body condition affected movement to different degrees. Specifically, per cent weight loss and dry matter content (ratio of wet versus dehydrated weight) were better predictors of movement than weight‐at‐length, which is most typically used as a surrogate of body condition in animals. In addition, body condition and length interacted to affect fish movement, where body condition affected movement of smaller individuals more significantly than that of larger individuals. Body condition effects on activity were similar at 16 and 22°C. This study demonstrates that body condition metrics may not always affect certain behavior in a similar way. Body condition metrics need to be carefully selected when used in the context of animal behavior, and more than a single metric should be tested when feasible.

The Societal Value of the Modern Zoo: A Commentary on How Zoos Can Positively Impact on Human Populations Locally and Globally

Modern zoos and aquariums have evolved greatly since the end of the Second World War, to become centres of conservation excellence and scientific institutions for the study of animal behaviour, ecology, husbandry management. Whilst the impact of zoos and aquariums to biodiversity conservation, population management and advancement of species care is well documented, their positive impacts on society (including the communities that they are located within) is less well known. The four established aims of the modern zoo—Conservation, Education, Recreation (Engagement) and Research—provide a strong foundation for wider review and critique of the societal value of zoos and aquariums. This article synthesises what such value may be, and how it could be measured, from a systematic review of the literature pertaining to each of these four established aims. It also recommends areas of future scientific inquiry to further study the wider impact of zoos on their local communities and on human populations and behaviour more generally. Including Wellbeing as a fifth aim of the modern zoo would also cement their wider societal value. Further scrutiny of the societal value of the modern zoo enhances the value of the zoo’s living collection and the green spaces that it manages to provide accessibility to biodiversity and nature-centric education essential to long-term, planetary friendly human behaviour change.

Drones and machine-learning for monitoring dugong feeding grounds and gillnet fishing

Fishing provides an important food source for humans, but it also poses a threat to many marine ecosystems and species. Declines in wildlife populations due to fishing activities can remain undetected without effective monitoring methods that guide appropriate management actions. In this study, we combined the use of unmanned aerial vehicle-based imaging (drones) with machine-learning to develop a monitoring method for identifying hotspots of dugong foraging based on their feeding trails and associated seagrass beds. We surveyed dugong hotspots to evaluate the influence of gillnet fishing activities on dugong feeding grounds (Saco East and Saco West) at Inhaca Island, southern Mozambique. The results showed that drones and machine-learning can accurately identify and monitor dugong feeding trails and seagrass beds, with an F1 accuracy of 80 and 93.3%, respectively. Feeding trails were observed in all surveyed months, with the highest density occurring in August (6040 ± 4678 trails km-2). There was a clear overlap of dugong foraging areas and gillnet fishing grounds, with a statistically significant positive correlation between fishing areas and the frequency of dugong feeding trails. Dugongs were found to feed mostly in Saco East, where the number of gillnet stakes was 3.7 times lower and the area covered by gillnets was 2.6 times lower than in Saco West. This study highlights the clear potential of drones and machine-learning to study and monitor animal behaviour in the wild, particularly in hotspots and remote areas. We encourage the establishment of effective management strategies to monitor and control the use of gillnets, thereby avoiding the accidental bycatch of dugongs.

ХЕДЖИНГ КАК ОБЩЕСЕМИОТИЧЕСКОЕ ЯВЛЕНИЕ

Alexander Barulin’s most notable results have to do with the communicative aspects of the human protolanguage. This kind of research differs from the conventional reconstructions of proto-languages because it cannot rely on material traces left by ancient humans, and the linguistic structures properly speaking are hardly available. Thus, linguists cannot put forward a description of phonetic and grammatical systems of the languages of the first humans. Instead, conjectures are usually made based on the etological-communicative studies of animal behaviour. Following Alexander Barulin, animal communication displays certain signs analogous to ‘hedges’, whose main function consists in accommodating information conveyed as a sort of ‘goods’ in communicative ‘exchange’. Hedges of “possibly” vs. “probably” types belong to linguistic techniques extensively used both in West-European and in Russian discourses. Lexical properties of such hedges interact with grammatical and pragmatical categories of tense, mood, and negation.

Metabolic and behavioural effects of hermit crab shell removal techniques: Is heating less invasive than cracking?

Hermit crabs (Paguroidea; Latreille 1802) offer great opportunities to study animal behaviour and physiology. However, the animals' size and sex cannot be determined when they are inside their shell; information crucial to many experimental designs. Here, we tested the effects of the two most common procedures used to make crabs leave their shells: heating the shell apex and cracking the shell with a bench press. We compared the effects of each of the two procedures on the metabolic rate, hiding time, and duration of the recovery time relative to unmanipulated hermit crabs. The hermit crabs forced to abandon their shell through heating increased their respiratory rate shortly after the manipulation (1 h) and recovered their metabolic rate in less than 24 h, as occurs in individuals suddenly exposed to high temperatures in the upper-intertidal zone. Hermit crabs removed from their shells via cracking spent more time hiding in their new shells; this effect was evident immediately after the manipulation and lasted more than 24 h, similar to responses exhibited after a life-threatening predator attack. Both methods are expected to be stressful, harmful, or fear-inducing; however, the temperature required to force the crabs to abandon the shell is below the critical thermal maxima of most inhabitants of tropical tide pools. The wide thermal windows of intertidal crustaceans and the shorter duration of consequences of shell heating compared to cracking suggest heating to be a less harmful procedure for removing tropical hermit crabs from their shells.

Characterizing Three Azides for Their Potential Use as C. elegans Anesthetics.

Sodium azide (NaN 3 ) is widely used as an anesthetic in the C. elegans community for studying animal behavior. It is not known whether other azides can function as anesthetics. This is quite important for the C. elegans labs in which NaN 3 is not a convenient choice, such as all the labs located in China, where NaN 3 is under tight regulation, and alternative anesthetics need to be characterized. In the present study, we focused on another three azides, potassium azide (KN 3 ), trimethylsilyl azide (TMSA), and diphenyl phosphoryl azide (DPPA), which are not regulated in China. We characterized their performance in chemotactic behavioral assays and buffer-based assays. Our results suggest that KN 3 can immobilize worms as effectively as NaN 3 in the above-mentioned assays. Therefore, we recommend KN 3 as a routine anesthetic for C. elegans labs.

Commercial television and primate ethology: facial expressions between Granada and London Zoo.

This article examines the significant relationship that existed between commercial British television and the study of animal behaviour. Ethological research provided important content for the new television channel, at the same time as that coverage played a substantial role in creating a new research specialism, the study of primate facial expressions, for this emergent scientific discipline. The key site in this was a television and film unit at London Zoo administered by the Zoological Society and Granada TV. The Granada unit produced 'Animal expressions', a twenty-five-minute television film based on research on monkeys and apes by the Dutch postgraduate student and soon-to-be-leading-authority Jan van Hooff. Recovering the production and multiple uses of 'Animal expressions', this paper offers the first sustained historical analysis of science on commercial television. I show how Granada patronage helped Van Hooff to support his argument that human expressions such as smiling and laughter shared common evolutionary origins with similar facial movements in nonhuman primates. Emphasizing the mutual shaping of science and ITV, I argue that 'Animal expressions' repurposed televisual conventions of framing talking heads, and blended serious science with the comedy of 'funny faces', thereby epitomizing Granada's public-service strategy at a time when commercial television was defending itself from criticism in the Pilkington report.

Going Deeper than Tracking: A Survey of Computer-Vision Based Recognition of Animal Pain and Emotions

Advances in animal motion tracking and pose recognition have been a game changer in the study of animal behavior. Recently, an increasing number of works go ‘deeper’ than tracking, and address automated recognition of animals’ internal states such as emotions and pain with the aim of improving animal welfare, making this a timely moment for a systematization of the field. This paper provides a comprehensive survey of computer vision-based research on recognition of pain and emotional states in animals, addressing both facial and bodily behavior analysis. We summarize the efforts that have been presented so far within this topic—classifying them across different dimensions, highlight challenges and research gaps, and provide best practice recommendations for advancing the field, and some future directions for research.

What’s Black and White and Pink All Over? Lesser Flamingo Nocturnal Behaviour Captured by Remote Cameras

The study of animal behaviour is important for the development of husbandry and management practices for zoo-housed species. Yet, data are typically only collected during daylight hours, aligning with human work schedules rather than animal activity patterns. To remedy this, 24 h data collection is needed. This study investigated the behaviour of a captive flock of lesser flamingos to understand temporal changes in their time-activity patterns. Two remote camera traps were placed around the birds’ outdoor enclosure and one within the indoor house. Counts of birds visible within specific enclosure zones were recorded from photographic data. Behaviour was defined as active or inactive, and modified Spread of Participation Index (SPI) was used to calculate enclosure zone occupancy. Results indicated that lesser flamingos are active overnight, and to a similar amount as in the daytime. Proportions of birds observed as active were significantly higher at later times of the day (i.e., dusk) when compared to the number of active birds in the morning. Enclosure usage was diverse and indoor and outdoor zones could be used by different numbers of birds at different times of the day. Variation in enclosure usage may indicate the changing needs of the flamingos when housed indoors overnight and when they have night-time access to an outdoor enclosure. This research has identified the need for further research into the nocturnal behaviour and space use of lesser flamingos and suggests the need for 24 h research in captive birds, and other zoo-held species, especially when species are locked indoors or face behavioural restriction overnight due to biosecurity measures surrounding zoonoses outbreaks, e.g., Avian Influenza.

Structural analyses in the study of behavior: From rodents to non-human primates.

The term "structure" indicates a set of components that, in relation to each other, shape an organic complex. Such a complex takes on essential connotations of functionally unitary entity resulting from the mutual relationships of its constituent elements. In a broader sense, we can use the word "structure" to define the set of relationships among the elements of an emergent system that is not determined by the mere algebraic sum of these elements, but by the interdependence relationships of these components from which the function of the entire structure itself derives. The behavior of an integrated living being can be described in structural terms via an ethogram, defined as an itemized list of behavioral units. Akin to an architectural structure, a behavioral structure arises from the reciprocal relationships that the individual units of behavior establish. Like an architectural structure, the function of the resulting behaving complex emerges from the relationships of the parts. Hence, studying behavior in its wholeness necessitates not only the identification of its constitutive units in their autarchic individuality, but also, and importantly, some understanding of their relationships. This paper aimed to critically review different methods to study behavior in structural terms. First, we emphasized the utilization of T-pattern analysis, i.e., one of the most effective and reliable tools to provide structural information on behavior. Second, we discussed the application of other methodological approaches that are based on the analysis of transition matrices, such as hierarchical clustering, stochastic analyses, and adjusted residuals. Unlike T-pattern analysis, these methods allow researchers to explore behavioral structure beyond its temporal characteristics and through other relational constraints. After an overview of how these methods are used in the study of animal behavior, from rodents to non-human primates, we discussed the specificities, advantages and challenges of each approach. This paper could represent a useful background for all scientists who intend to study behavior both quantitatively and structurally, that is in terms of the reciprocal relationships that the various units of a given behavioral repertoire normally weave together.

The importance of animal behavior for ecosystem services

Animal behavior plays a critical role in the delivery of ecosystem services, yet the study of animal behavior and ecosystem services rarely intersect. The study of behavior-mediated ecosystem services should be prioritized, focusing on the conditions that allow these critical behaviors to persist and adapt to global change.

Vision-Based Quadruped Pose Estimation and Gait Parameter Extraction Method

In the study of animal behavior, the prevention of sickness, and the gait planning of legged robots, pose estimation, and gait parameter extraction of quadrupeds are of tremendous importance. However, there are several varieties of quadrupeds, and distinct species frequently have radically diverse body types, limb configurations, and gaits. Currently, it is challenging to forecast animal pose estimation with any degree of accuracy. This research developed a quadruped animal pose estimation and gait parameter extraction method to address this problem. A computational framework including three components of target screening, animal pose estimation model, and animal gaits parameter extraction, which can totally and efficiently solve the problem of quadruped animal pose estimation and gait parameter extraction, makes up its core. On the basis of the HRNet network, an improved quadruped animal keypoint extraction network, RFB-HRNet, was proposed to enhance the extraction effect of quadruped pose estimation. The basic concept was to use a DyConv (dynamic convolution) module and an RFB (receptive field block) module to propose a special receptive field module DyC-RFB to optimize the feature extraction capability of the HRNet network at stage 1 and to enhance the feature extraction capability of the entire network model. The public dataset AP10K was then used to validate the model’s performance, and it was discovered that the proposed method was superior to alternative methods. Second, a two-stage cascade network was created by adding an object detection network to the front end of the pose estimation network to filter the animal object in input images, which enhanced the pose estimation effect of small targets and multitargets. The acquired keypoints data of animals were then utilized to extract the gait parameters of the experimental objects. Experiment findings showed that the gait parameter extraction model proposed in this research could effectively extract the gait frequency, gait sequence, gait duty cycle, and gait trajectory parameters of quadruped animals, and obtain real-time and accurate gait trajectory.

Increasingly detailed insights in animal behaviours using continuous on-board processing of accelerometer data

Background:Studies of animal behaviour, ecology and physiology are continuously benefitting from progressing biologging techniques, including the collection of accelerometer data to infer animal behaviours and energy expenditure. In one of the most recent technological advances in this space, on-board processing of raw accelerometer data into animal behaviours proves highly energy-, weight- and cost-efficient allowing for continuous behavioural data collection in addition to regular positional data in a wide range of animal tracking studies.Methods:We implemented this latest development in collecting continuous behaviour records from 6 Pacific Black Ducks Anas superciliosa to evaluate some of this novel technique’s potential advantages over tracking studies lacking behavioural data or recording accelerometer data intermittently only. We (i) compared the discrepancy of time-activity budgets between continuous records and behaviours sampled with different intervals, (ii) compared total daily distance flown using hourly GPS fixes with and without additional behavioural data and (iii) explored how behaviour records can provide additional insights for animal home range studies.Results:Using a total of 690 days of behaviour records across six individual ducks distinguishing eight different behaviours, we illustrated the improvement that is obtained in time-activity budget accuracy if continuous rather than interval-sampled accelerometer data is used. Notably, for rare behaviours such as flying and running, error ratios > 1 were common when sampling intervals exceeded 10 min. Using 72 days of hourly GPS fixes in combination with continuous behaviour records over the same period in one individual duck, we showed behaviour-based daily distance estimation is significantly higher (up to 540%) than the distance calculated from hourly sampled GPS fixes. Also, with the same 72 days of data for one individual duck, we showed how this individual used specific sites within its entire home range to satisfy specific needs (e.g. roosting and foraging).Conclusion:We showed that by using trackers allowing for continuous recording of animal behaviour, substantial improvements in the estimation of time-activity budgets and daily traveling distances can be made. With integrating behaviour into home-range estimation we also highlight that this novel tracking technique may not only improve estimations but also open new avenues in animal behaviour research, importantly improving our knowledge of an animal’s state while it is roaming the landscape.

A skew in poo: Biases in primate fecal isotope analysis and recommendations for standardized sample preparation.

Feces are a treasure trove in the study of animal behavior and ecology. Stable carbon and nitrogen isotope analysis allows to assessthe dietary niches of elusive primate species and primate breastfeeding behavior. However, some fecal isotope data may unwillingly be biased towardthe isotope ratios of undigested plant matter, requiring more consistent sample preparation protocols. We assess the impact of this potential data skew in 114 fecal samples of wild bonobos (Pan paniscus) by measuring the isotope differences (Δ13 C, Δ15 N) between bulk fecal samples containing larger particles (>1 mm) and filtered samples containing only small particles (<1 mm). We assess the influence of fecal carbon and nitrogen content (ΔC:N) and sample donor age (subadult, adult) on the resulting Δ13 C, Δ15 N values (n = 228). Additionally, we measure the isotope ratios in three systematically sieved fecal samples of chimpanzees (Pan troglodytes verus), with particle sizes ranging from 20 μm to 8 mm (n = 30). We found differences in fecal carbon and nitrogen content, with the smaller fecal fraction containing more nitrogen on average. While the Δ13 C values were small and not affected by age or ΔC:N, the Δ15 N values were significantly influenced by fecal ΔC:N, possibly resulting from the differing proportions of undigested plant macroparticles. Significant relationships between carbon stable isotope ratios (δ13 C) values and %C in large fecal fractions of both age groups corroborated this assessment. Δ15 N values were significantly larger in adults than subadults, which should be of concern in isotope studies comparing adult females with infants to assess breastfeeding. We found a random variation of up to 3.0‰ in δ13 C and 2.0‰ in nitrogen stable isotope ratios within the chimpanzee fecal samples separated by particle sizes. We show that particle size influences isotope ratios and propose a simple, cost-effective filtration method for primate feces to exclude larger undigested food particles from the analysis, which can easily be adopted by labs worldwide.

Open-source intelligence for conservation biology.

Open-source intelligence (OSINT) evolved in spy agencies but now is rapidly changing many fields of study, from anthropology to zoology. Despite the fact that OSINT occasionally is used in conservation biology, there is little recognition that some tools and frameworks used by conservation professionals are drawn from this well-established field. In conservation biology, OSINT is sometimes used to evaluate wildlife crime, human-wildlife and human-environment interactions, animal behavior, and questions of distribution and abundance. Recognizing the conceptual foundations of the field would allow expansion of conservation biology, not only in the areas noted above, but also, for example, in study of habitat use, habitat change, and animal behavior. This recognition would also provide frameworks for conceptual advancement, especially in terms of data and privacy management. Failure to recognize the underpinnings of OSINT tools in conservation biology harms the field because it limits how research is framed, thought about, and implemented. Likewise, taking an OSINT perspective to conservation problems, rather than simply thinking in terms of big data, can enrich the field, expand science, and increase knowledge and understanding of biology and biodiversity.

Behavioral and endocrine responses to noninteractive live and video conspecifics in males of the Siamese fighting fish.

The physiological mechanisms underlying variation in aggression in fish remain poorly understood. One possibly confounding variable is the lack of standardization in the type of stimuli used to elicit aggression. The presentation of controlled stimuli in videos, a.k.a. video playback, can provide better control of the fight components. However, this technique has produced conflicting results in animal behavior studies and needs to be carefully validated. For this, a similar response to the video and an equivalent live stimulus needs to be demonstrated. Further, different physiological responses may be triggered by live and video stimuli, and it is important to demonstrate that video images elicit appropriate physiological reactions. Here, the behavioral and endocrine responses of male Siamese fighting fish Betta splendens to a matched-for-size conspecific fighting behind a one-way mirror, presented live or through video playback, were compared. The video playback and live stimulus elicited a strong and similar aggressive response by the focal fish, with a fight structure that started with stereotypical threat displays and progressed to overt attacks. Postfight plasma levels of the androgen 11-ketotestosterone were elevated as compared to controls, regardless of the type of stimuli. Cortisol also increased in response to the video images, as previously described for live fights in this species. These results show that the interactive component of a fight and its resolution are not needed to trigger an endocrine response to aggression in this species. The study also demonstrates for the first time in a fish a robust endocrine response to video stimuli and supports the use of this technique for researching aggressive behavior in B. splendens.

A simple methodology for creating and applying replicable, photograph‐accurate coloration to 3D‐printed models for animal behavior studies

AbstractResearchers often use artificial models of animals to elicit and study behavior. Until recently, these models were typically handcrafted; however, 3D‐printing technology has been adopted by researchers looking to create accurate and consistent animal models from scans of living animals, taxidermies, or existing models. While 3D‐printing techniques create models with accurate and repeatable shape and size, applying coloration to these models is still typically achieved with traditional methods, such as painting by hand. These approaches can be time‐consuming and require high levels of artistic skill, creating a barrier to producing realistic models, especially when more than one model or standardized coloration is required. Here, we present a simple workflow to avoid these issues by creating a photograph‐accurate paper “skin” that can be glued onto 3D‐printed animal models to provide surface coloration. We have used this methodology to create avian models for several experiments, and found that it can create highly detailed and standardized models with minimal training and is independent of artistic skill. Additionally, this method allows the files needed to accurately recreate models to be shared digitally with other researchers, further enhancing repeatability in the field.