Advances in non-invasive tracking of wave-type electric fish in natural and laboratory settings

Recent technological advances greatly improved the possibility to study freely behaving animals in natural conditions. However, many systems still rely on animal-mounted devices, which can already bias behavioral observations. Alternatively, animal behaviors can be detected and tracked in recordings of stationary sensors, e.g., video cameras. While these approaches circumvent the influence of animal-mounted devices, identification of individuals is much more challenging. We take advantage of the individual-specific electric fields electric fish generate by discharging their electric organ (EOD) to record and track their movement and communication behaviors without interfering with the animals themselves. EODs of complete groups of fish can be recorded with electrode arrays submerged in the water and then be tracked for individual fish. Here, we present an improved algorithm for tracking electric signals of wave-type electric fish. Our algorithm benefits from combining and refining previous approaches of tracking individual specific EOD frequencies and spatial electric field properties. In this process, the similarity of signal pairs in extended data windows determines their tracking order, making the algorithm more robust against detection losses and intersections. We quantify the performance of the algorithm and show its application for a data set recorded with an array of 64 electrodes distributed over a 12 m² section of a stream in the Llanos, Colombia, where we managed, for the first time, to track Apteronotus leptorhynchus over many days. These technological advances make electric fish a unique model system for a detailed analysis of social and communication behaviors, with strong implications for our research on sensory coding.

Plastron color patterns allows for individual photo-identification in two different chelonian species

Natural marks have increasingly been used as a tool for individual identification in capture-mark-recapture techniques. Photo-identification is a non-invasive alternative to traditional marking techniques, allowing individual recognition of species through time and space. We tested the APHIS (Automatic Photo Identification) software as a software capable of identifying individuals of Testudo hermanni (Gmelin, 1789) and Emys orbicularis (Linneaus, 1758) in different populations during capture-release sessions in the field based on plastron color patterns, since they can be used as natural marks for identification. For this individual identification, SPM (Spot Pattern Matching) and ITM (Image Template Matching) procedures were tested; achieving 100 % success of individuals recognized in both procedures and visually verified comparing the images. However, ITM procedure was more efficient at recognizing recaptures than SPM because ITM allowed faster recaptures verification, since most of the matches were directly placed on the first position on the candidates list. Previous studies have used photo-identification on freshwater or sea turtles, but never with terrestrial tortoise species. Consequently, it can be corroborated that APHIS is a competent and efficient software considering photo-identification of T. hermanni and E. orbicularis and can be applied with close species with similar and unique individual color patterns in their plastron.

Cross-modal individual recognition in the African penguin and the effect of partnership

An animal's ability to recognize another individual by matching their image to their voice suggests they form internal representations of other individuals. To what extent this ability, termed cross-modal individual recognition, extends to birds other than corvids is unknown. Here, we used an expectancy violation paradigm to determine whether a monogamous territorial seabird (Spheniscus demersus) can cross-modally recognize familiar conspecifics (partners or colony-mates). After pairs of penguins spent time together in an isolated area, one of the penguins was released from the area leaving the focal penguin alone. Subsequently, we played contact calls of the released penguin (congruent condition) or a different penguin (incongruent condition). After being paired with a colony-mate, focal penguins' response latency to the auditory stimulus was faster in the incongruent compared to congruent condition, indicating the mismatch violated their expectations. This behavioural pattern was not observed in focal penguins after being paired with their partner. We discuss these different results in the light of penguins' natural behaviour and the evolution of social communication strategies. Our results suggest that cross-modal individual recognition extends to penguins and reveals, in contrast with previously thought, that social communication between members of this endangered species can also use visual cues.

Evaluation of spot patterns and carapace abnormalities of an Endangered freshwater turtle, Clemmys guttata, as a potential tool for population assignment

Many of the world’s contemporary species of turtle are extinct or threatened with extinction due to habitat loss, increases in anthropogenic sources of mortality, and poaching (illegal collection). The slow life-history strategy of most turtle species magnifies the effects of poaching because the loss of even a few mature individuals can impact population growth. Returning poached turtles to their population of origin, where possible, can mitigate these effects, but identifying the origin of these individuals can be challenging. We hypothesized that spot patterns might allow assignment of Endangered spotted turtles Clemmys guttata to their population of origin. We characterized and compared spot patterns from carapace photographs of 126 individuals from 10 sites. To explore other types of information these photographs might provide, we also documented carapacial scute abnormalities and quantified their association with genetic diversity and latitude. Spot pattern similarity was not higher within populations than among populations and did not accurately differentiate populations. Carapacial scute abnormalities occurred in 82% of turtles and were not correlated with estimates of neutral genetic diversity. Abnormalities were positively correlated with latitude, implicating thermal stress during the early stages of development in the generation of some scute deformities. However, this relationship became non-significant when line (scute seam) abnormalities were excluded from the data, suggesting a different primary cause for the more severe scute deformities. Further research should continue to investigate the drivers of these deformities, as monitoring shifts in the frequency of scute deformities may provide relevant information for conservation and recovery of endangered turtles.

Estimating Population Abundance of Burying Beetles Using Photo-Identification and Mark-Recapture Methods

Successful conservation and management of protected wildlife populations require reliable population abundance data. Traditional capture-mark-recapture methods can be costly, time-consuming, and invasive. Photographic mark-recapture (PMR) is a cost-effective, minimally invasive way to study population dynamics in species with distinct markings or color patterns. We tested the feasibility and the application of PMR using the software Hotspotter to identify Nicrophorus spp. from digital images of naturally occurring spot patterns on their elytra. We conducted a laboratory study evaluating the identification success of Hotspotter on Nicrophorus americanus (Olivier, 1790) and Nicrophorus orbicollis (Say, 1825) before implementation of a mark-recapture study in situ. We compared the performance of Hotspotter using both 'high-quality' and 'low-quality' photographs. For high-quality photographs, Hotspotter had a false rejection rate of 2.7-3.0% for laboratory-reared individuals and 3.9% for wild-caught individuals. For low-quality photographs, the false rejection rate was much higher, 48.8-53.3% for laboratory-reared individuals and 28.3% for wild-caught individuals. We subsequently analyzed encounter histories of wild-caught individuals with closed population models in Program MARK to estimate population abundance. In our study, we demonstrated the utility of using PMR in estimating population abundance for Nicrophorus spp. based on elytral spot patterns.

PhotoId-Whale: Blue whale dorsal fin classification for mobile devices

Photo-identification (photo-id) is a method used in field studies by biologists to monitor animals according to their density, movement patterns and behavior, with the aim of predicting and preventing ecological risks. However, these methods can introduce subjectivity when manually classifying an individual animal, creating uncertainty or inaccuracy in the data as a result of the human criteria involved. One of the main objectives in photo-id is to implement an automated mechanism that is free of biases, portable, and easy to use. The main aim of this work is to develop an autonomous and portable photo-id system through the optimization of image classification algorithms that have high statistical dependence, with the goal of classifying dorsal fin images of the blue whale through offline information processing on a mobile platform. The new proposed methodology is based on the Scale Invariant Feature Transform (SIFT) that, in conjunction with statistical discriminators such as the variance and the standard deviation, fits the extracted data and selects the closest pixels that comprise the edges of the dorsal fin of the blue whale. In this way, we ensure the elimination of the most common external factors that could affect the quality of the image, thus avoiding the elimination of relevant sections of the dorsal fin. The photo-id method presented in this work has been developed using blue whale images collected off the coast of Baja California Sur. The results shown have qualitatively and quantitatively validated the method in terms of its sensitivity, specificity and accuracy on the Jetson Tegra TK1 mobile platform. The solution optimizes classic SIFT, balancing the results obtained with the computational cost, provides a more economical form of processing and obtains a portable system that could be beneficial for field studies through mobile platforms, making it available to scientists, government and the general public.

Parenting in a warming world: thermoregulatory responses to heat stress in an endangered seabird

The frequency of extreme weather events, including heat waves, is increasing with climate change. The thermoregulatory demands resulting from hotter weather can have catastrophic impacts on animals, leading to mass mortalities. Although less dramatic, animals also experience physiological costs below, but approaching, critical temperature thresholds. These costs may be particularly constraining during reproduction, when parents must balance thermoregulation against breeding activities. Such challenges should be acute among seabirds, which often nest in locations exposed to high solar radiation and predation risk. The globally endangered bank cormorant Phalacrocorax neglectus breeds in southern Africa in the winter, giving little scope for poleward or phenological shifts in the face of increasing temperatures. Physiological studies of endangered species sensitive to human disturbance, like the bank cormorant, are challenging, because individuals cannot be captured for experimental research. Using a novel, non-invasive, videographic approach, we investigated the thermoregulatory responses of this seabird across a range of environmental temperatures at three nesting colonies. The time birds spent gular fluttering, a behaviour enhancing evaporative heat loss, increased with temperature. Crouching or standing birds spent considerably less time gular fluttering than birds sitting on nests (ca 30% less at 22°C), showing that postural adjustments mediate exposure to heat stress and enhance water conservation. Crouching or standing, however, increases the vulnerability of eggs and chicks to suboptimal temperatures and/or expose nest contents to predation, suggesting that parents may trade-off thermoregulatory demands against offspring survival. We modelled thermoregulatory responses under future climate scenarios and found that nest-bound bank cormorants will gular flutter almost continuously for several hours a day by 2100. The associated increase in water loss may lead to dehydration, forcing birds to prioritize survival over breeding, a trade-off that would ultimately deteriorate the conservation status of this species.

The challenges of recognising individuals with few distinguishing features: Identifying red foxes Vulpes vulpes from camera-trap photos

Over the last two decades, camera traps have revolutionised the ability of biologists to undertake faunal surveys and estimate population densities, although identifying individuals of species with subtle markings remains challenging. We conducted a two-year camera-trapping study as part of a long-term study of urban foxes: our objectives were to determine whether red foxes could be identified individually from camera-trap photos, and highlight camera-trapping protocols and techniques to facilitate photo identification of species with few or subtle natural markings. We collected circa 800,000 camera-trap photos over 4945 camera days in suburban gardens in the city of Bristol, UK: 152,134 (19%) included foxes, of which 13,888 (9%) contained more than one fox. These provided 174,063 timestamped capture records of individual foxes; 170,923 were of foxes ≥ 3 months old. Younger foxes were excluded because they have few distinguishing features. We identified the individual (192 different foxes: 110 males, 49 females, 33 of unknown sex) in 168,417 (99%) of these capture records; the remainder could not be identified due to poor image quality or because key identifying feature(s) were not visible. We show that carefully designed survey techniques facilitate individual identification of subtly-marked species. Accuracy is enhanced by camera-trapping techniques that yield large numbers of high resolution, colour images from multiple angles taken under varying environmental conditions. While identifying foxes manually was labour-intensive, currently available automated identification systems are unlikely to achieve the same levels of accuracy, especially since different features were used to identify each fox, the features were often inconspicuous, and their appearance varied with environmental conditions. We discuss how studies based on low numbers of photos, or which fail to identify the individual in a significant proportion of photos, risk losing important biological information, and may come to erroneous conclusions.

Seeing spots: quantifying mother-offspring similarity and assessing fitness consequences of coat pattern traits in a wild population of giraffes (Giraffa camelopardalis)

Polymorphic phenotypes of mammalian coat coloration have been important to the study of genetics and evolution, but less is known about the inheritance and fitness consequences of individual variation in complex coat pattern traits such as spots and stripes. Giraffe coat markings are highly complex and variable and it has been hypothesized that variation in coat patterns most likely affects fitness by camouflaging neonates against visually hunting predators. We quantified complex coat pattern traits of wild Masai giraffes using image analysis software, determined the similarity of spot pattern traits between mother and offspring, and assessed whether variation in spot pattern traits was related to fitness as measured by juvenile survival. The methods we described could comprise a framework for objective quantification of complex mammal coat pattern traits based on photographic coat pattern data. We demonstrated that some characteristics of giraffe coat spot shape were likely to be heritable, as measured by mother-offspring regression. We found significant variation in juvenile survival among phenotypic groups of neonates defined by multivariate clustering based on spot trait measurement variables. We also found significant variation in neonatal survival associated with spot size and shape covariates. Larger spots (smaller number of spots) and irregularly shaped or rounder spots (smaller aspect ratio) were correlated with increased survival. These findings will inform investigations into developmental and genetic architecture of complex mammal coat patterns and their adaptive value.

Automated face detection for occurrence and occupancy estimation in chimpanzees

Surveying endangered species is necessary to evaluate conservation effectiveness. Camera trapping and biometric computer vision are recent technological advances. They have impacted on the methods applicable to field surveys and these methods have gained significant momentum over the last decade. Yet, most researchers inspect footage manually and few studies have used automated semantic processing of video trap data from the field. The particular aim of this study is to evaluate methods that incorporate automated face detection technology as an aid to estimate site use of two chimpanzee communities based on camera trapping. As a comparative baseline we employ traditional manual inspection of footage. Our analysis focuses specifically on the basic parameter of occurrence where we assess the performance and practical value of chimpanzee face detection software. We found that the semi-automated data processing required only 2-4% of the time compared to the purely manual analysis. This is a non-negligible increase in efficiency that is critical when assessing the feasibility of camera trap occupancy surveys. Our evaluations suggest that our methodology estimates the proportion of sites used relatively reliably. Chimpanzees are mostly detected when they are present and when videos are filmed in high-resolution: the highest recall rate was 77%, for a false alarm rate of 2.8% for videos containing only chimpanzee frontal face views. Certainly, our study is only a first step for transferring face detection software from the lab into field application. Our results are promising and indicate that the current limitation of detecting chimpanzees in camera trap footage due to lack of suitable face views can be easily overcome on the level of field data collection, that is, by the combined placement of multiple high-resolution cameras facing reverse directions. This will enable to routinely conduct chimpanzee occupancy surveys based on camera trapping and semi-automated processing of footage.

RESEARCH HIGHLIGHTS

Using semi-automated ape face detection technology for processing camera trap footage requires only 2-4% of the time compared to manual analysis and allows to estimate site use by chimpanzees relatively reliably.

Error rates and variation between observers are reduced with the use of photographic matching software for capture-recapture studies

Photographic capture-mark-recapture (CMR) permits individual recognition whilst avoiding many of the concerns involved with marking animals. However, the construction of capture histories from photographs is a time-consuming process. Furthermore, matching accuracy is determined based on subjective judgements of the person carrying out the matching, which can lead to errors in the resulting datasets – particularly in long-term projects where multiple observers match images. We asked 63 volunteers to carry out two photographic-matching exercises using a database of known individuals of the yellow-bellied toad (Bombina variegata). From these exercises, we quantified the matching accuracy of volunteers in terms of false-acceptance and false-rejection rates. Not only were error rates greatly reduced with the use of photographic-matching software, but variation in error rates among volunteers was also lowered. Furthermore, the use of matching software led to substantial increases in matching speeds and an 87% reduction in the false-rejection rate. As even small error rates have the potential to bias CMR analyses, these results suggest that computer software could substantially reduce errors in CMR datasets. The time-savings and reduction in variance among observers suggest that such methods could be particularly beneficial in long-term CMR projects where a large number of images may be matched by multiple observers.

Assessing Rotation-Invariant Feature Classification for Automated Wildebeest Population Counts

Accurate and on-demand animal population counts are the holy grail for wildlife conservation organizations throughout the world because they enable fast and responsive adaptive management policies. While the collection of image data from camera traps, satellites, and manned or unmanned aircraft has advanced significantly, the detection and identification of animals within images remains a major bottleneck since counting is primarily conducted by dedicated enumerators or citizen scientists. Recent developments in the field of computer vision suggest a potential resolution to this issue through the use of rotation-invariant object descriptors combined with machine learning algorithms. Here we implement an algorithm to detect and count wildebeest from aerial images collected in the Serengeti National Park in 2009 as part of the biennial wildebeest count. We find that the per image error rates are greater than, but comparable to, two separate human counts. For the total count, the algorithm is more accurate than both manual counts, suggesting that human counters have a tendency to systematically over or under count images. While the accuracy of the algorithm is not yet at an acceptable level for fully automatic counts, our results show this method is a promising avenue for further research and we highlight specific areas where future research should focus in order to develop fast and accurate enumeration of aerial count data. If combined with a bespoke image collection protocol, this approach may yield a fully automated wildebeest count in the near future.

Effects of Photo and Genotype-Based Misidentification Error on Estimates of Survival, Detection and State Transition using Multistate Survival Models

We simulated multistate capture histories (CHs) by varying state survival (ϕ), detection (p) and transition (ψ), number of total capture occasions and releases per capture occasion and then modified these scenarios to mimic false rejection error (FRE), a common misidentification error, resulting from the failure to match samples of the same individual. We then fit a multistate model and estimated accuracy, bias and precision of state-specific ϕ, p and ψ to better understand the effects of FRE on different simulation scenarios. As expected, ϕ, and p, decreased in accuracy with FRE, with lower accuracy when CHs were simulated under a shorter-term study and a lower number of releases per capture occasion (lower sample size). Accuracy of ψ estimates were robust to FRE except in those CH scenarios simulated using low sample size. The effect of FRE on bias was not consistent among parameters and differed by CH scenario. As expected, ϕ was negatively biased with increased FRE (except for the low ϕ low p CH scenario simulated with a low sample size), but we found that the magnitude of bias differed by scenario (high p CH scenarios were more negatively biased). State transition was relatively unbiased, except for the low p CH scenarios simulated with a low sample size, which were positively biased with FRE, and high p CH scenarios simulated with a low sample size. The effect of FRE on precision was not consistent among parameters and differed by scenario and sample size. Precision of ϕ decreased with FRE and was lowest with the low ϕ low p CH scenarios. Precision of p estimates also decreased with FRE under all scenarios, except the low ϕ high p CH scenarios. However, precision of ψ increased with FRE, except for those CH scenarios simulated with a low sample size. Our results demonstrate how FRE leads to loss of accuracy in parameter estimates in a multistate model with the exception of ψ when estimated using an adequate sample size.

Vocal activity as a low cost and scalable index of seabird colony size

Although wildlife conservation actions have increased globally in number and complexity, the lack of scalable, cost-effective monitoring methods limits adaptive management and the evaluation of conservation efficacy. Automated sensors and computer-aided analyses provide a scalable and increasingly cost-effective tool for conservation monitoring. A key assumption of automated acoustic monitoring of birds is that measures of acoustic activity at colony sites are correlated with the relative abundance of nesting birds. We tested this assumption for nesting Forster's terns (Sterna forsteri) in San Francisco Bay for 2 breeding seasons. Sensors recorded ambient sound at 7 colonies that had 15-111 nests in 2009 and 2010. Colonies were spaced at least 250 m apart and ranged from 36 to 2,571 m(2) . We used spectrogram cross-correlation to automate the detection of tern calls from recordings. We calculated mean seasonal call rate and compared it with mean active nest count at each colony. Acoustic activity explained 71% of the variation in nest abundance between breeding sites and 88% of the change in colony size between years. These results validate a primary assumption of acoustic indices; that is, for terns, acoustic activity is correlated to relative abundance, a fundamental step toward designing rigorous and scalable acoustic monitoring programs to measure the effectiveness of conservation actions for colonial birds and other acoustically active wildlife.

Analyzing visual signals as visual scenes

The study of visual signal design is gaining momentum as techniques for studying signals become more sophisticated and more freely available. In this paper we discuss methods for analyzing the color and form of visual signals, for integrating signal components into visual scenes, and for producing visual signal stimuli for use in psychophysical experiments. Our recommended methods aim to be rigorous, detailed, quantitative, objective, and where possible based on the perceptual representation of the intended signal receiver(s). As methods for analyzing signal color and luminance have been outlined in previous publications we focus on analyzing form information by discussing how statistical shape analysis (SSA) methods can be used to analyze signal shape, and spatial filtering to analyze repetitive patterns. We also suggest the use of vector-based approaches for integrating multiple signal components. In our opinion elliptical Fourier analysis (EFA) is the most promising technique for shape quantification but we await the results of empirical comparison of techniques and the development of new shape analysis methods based on the cognitive and perceptual representations of receivers. Our manuscript should serve as an introductory guide to those interested in measuring visual signals, and while our examples focus on primate signals, the methods are applicable to quantifying visual signals in most taxa.

An ethical issue in biodiversity science: The monitoring of penguins with flipper bands

Individual marking is essential to study the life-history traits of animals and to track them in all kinds of ecological, behavioural or physiological studies. Unlike other birds, penguins cannot be banded on their legs due to their leg joint anatomy and a band is instead fixed around a flipper. However, there is now detailed evidence that flipper-banding has a detrimental impact on individuals. It can severely injure flipper tissues, and the drag effect of their flipper bands results in a higher energy expenditure when birds are moving through the water. It also results in lower efficiency in foraging, since they require longer foraging trips, as well as in lower survival and lower breeding success. Moreover, due to the uncertainty of the rate of band loss, flipper bands induce a scientific bias. These problems, which obviously have serious ethical implications, can be avoided with alternative methods such as radiofrequency identification techniques.