A new 'view' of ecology and conservation through animal-borne video systems

Foraging dives of southern right whales (Eubalaena australis) in relation to larger zooplankton size prey availability in Golfo Nuevo, Península Valdés, Argentina

Southern right whales (SRWs, Eubalaena australis) have been observed feeding both at and below the surface (< 10 m) in Golfo Nuevo (42°42' S, 64°30' W), Península Valdés, Argentina, an area traditionally recognized as calving ground. In addition, we documented diving feeding behavior in SRWs during their stay in this gulf, which has not been previously described. We assessed this behavior using suction-cup-attached video-imaging tags (CRITTERCAMs) on individual whales. A total of eight CRITTERCAM deployments were successful, and feeding events were documented in all SRWs successfully equipped with CRITTERCAMs. The highest speeds occurred during the ascent phase, and the average diving time was 6 min 45 s ± 3 min 41 s for SRWs. Concurrently, zooplankton samples were collected from the subsurface and bottom of the water in areas where tagged whales dived to assess differences in composition, abundance, and biomass. Copepods dominated the upper layer, while euphausiids were more abundant in the deeper sample. Furthermore, zooplankton total biomass was five times higher at depth (2515.93 mg/m3) compared to the subsurface (500.35 mg/m3). Differences in zooplankton characteristics between depths, combined with CRITTERCAM videos, indicated that SRWs exploit high concentrations of organisms near the seafloor during daytime feeding dives. This study provides baseline insights into how SRWs utilize Península Valdés during their stay in the area.

Machine Learning Methods and Visual Observations to Categorize Behavior of Grazing Cattle Using Accelerometer Signals

Accelerometers worn by animals produce distinct behavioral signatures, which can be classified accurately using machine learning methods such as random forest decision trees. The objective of this study was to identify accelerometer signal separation among parsimonious behaviors. We achieved this objective by (1) describing functional differences in accelerometer signals among discrete behaviors, (2) identifying the optimal window size for signal pre-processing, and (3) demonstrating the number of observations required to achieve the desired level of model accuracy,. Crossbred steers (Bos taurus indicus; n = 10) were fitted with GPS collars containing a video camera and tri-axial accelerometers (read-rate = 40 Hz). Distinct behaviors from accelerometer signals, particularly for grazing, were apparent because of the head-down posture. Increasing the smoothing window size to 10 s improved classification accuracy (p < 0.05), but reducing the number of observations below 50% resulted in a decrease in accuracy for all behaviors (p < 0.05). In-pasture observation increased accuracy and precision (0.05 and 0.08 percent, respectively) compared with animal-borne collar video observations.

The urban lives of green sea turtles: Insights into behavior in an industrialized habitat using an animal-borne camera

The cryptic and aquatic life histories of sea turtles have made them a challenging group to directly observe, leaving significant knowledge gaps regarding social behavior and fine-scale elements of habitat use. Using a custom-designed animal-borne camera, we observed previously undocumented behaviors by green turtles (Chelonia mydas) at a foraging area in San Diego Bay, a highly urbanized ecosystem in California, USA. We deployed a suction-cup-attached pop-off camera (manufactured by Customized Animal Tracking Solutions) on 11 turtles (mean straight carapace length = 84.0 ± 11.2 cm) for between 1 and 30.8 h. Video recordings, limited to sunlit hours, provided 73 h of total observation time between May 2022 and June 2023. We observed 32 conspecific interactions; we classified 18 as active, entailing clear social behaviors, as compared with 14 passive interactions representing brief, chance encounters. There was no evidence for agonistic interactions. The camera additionally revealed that green turtles consistently use metal structures within urban San Diego Bay. In seven instances, turtles exhibited rubbing behavior against metal structures, and we observed two examples of turtles congregating at these structures. High rates of intraspecific interaction exhibited relatively consistently among individuals provide a compelling case for sociality for green turtles in San Diego Bay, adding to a growing research base updating their historical label of "non-social." The frequent use of metal structures by the population, in particular the rubbing of exposed skin, has implications for behavioral adaptations to urban environments. Our study exemplifies the promise of technological advances (e.g., underwater and animal-borne cameras) for updating natural history paradigms, even for well-studied populations.

Automatic recording of rare behaviors of wild animals using video bio-loggers with on-board light-weight outlier detector

Rare behaviors displayed by wild animals can generate new hypotheses; however, observing such behaviors may be challenging. While recent technological advancements, such as bio-loggers, may assist in documenting rare behaviors, the limited running time of battery-powered bio-loggers is insufficient to record rare behaviors when employing high-cost sensors (e.g. video cameras). In this study, we propose an artificial intelligence (AI)-enabled bio-logger that automatically detects outlier readings from always-on low-cost sensors, e.g. accelerometers, indicative of rare behaviors in target animals, without supervision by researchers, subsequently activating high-cost sensors to record only these behaviors. We implemented an on-board outlier detector via knowledge distillation by building a lightweight outlier classifier supervised by a high-cost outlier behavior detector trained in an unsupervised manner. The efficacy of AI bio-loggers has been demonstrated on seabirds, where videos and sensor data captured by the bio-loggers have enabled the identification of some rare behaviors, facilitating analyses of their frequency, and potential factors underlying these behaviors. This approach offers a means of documenting previously overlooked rare behaviors, augmenting our understanding of animal behavior.

Comparing information derived on food habits of a terrestrial carnivore between animal-borne video systems and fecal analyses methods

In recent years, animal-borne video cameras have been used to identify the food habits of many species. However, the usefulness and difficulties of identifying food habits from animal-borne video cameras have not been sufficiently discussed in terrestrial mammals, especially large omnivores. The aim of this study is to compare the video analysis of foraging behavior by Asian black bears (Ursus thibetanus) acquired by camera collars with estimates from fecal analysis. We attached GPS collars equipped with video cameras to four adult Asian black bears in the Okutama mountains in central Japan from May to July 2018 and analyzed video clips for foraging behavior. Simultaneously, we collected bear feces in the same area to determine food habits. We found that using video analyses was advantageous to recognize foods, such as leaves or mammals, that were physically crushed or destroyed while bears chewed and digested foods, which are difficult to identify to species using fecal analyses. On the other hand, we found that camera collars are less likely to record food items that are infrequently or quickly ingested. Additionally, food items with a low frequency of occurrence and short foraging time per feeding were less likely to be detected when we increased the time between recorded clips. As one of the first applications of the video analysis method for bears, our study shows that video analysis can be an important method for revealing individual differences in diet. Although video analysis may have limitations for understanding the general foraging behavior of Asian black bears at the present stage, the accuracy of food habit data from camera collars can be improved by using it in combination with established techniques such as microscale behavior analyses.

Size-Mediated Sea Turtle Behavioral Responses at Artificial Habitats in the Northern Gulf of Mexico

Our understanding of size-specific sea turtle behavior has lagged due to methodological limitations. However, stereo-video cameras (SVC) are an in-water approach that can link body-size and allow for relatively undisturbed behavioral observations. In this study, we conducted SVC dive surveys at local artificial reefs, piers, and jetties in the northern Gulf of Mexico (nGOM) from May 2019 to August 2021. Using SVCs, we measured sea turtle straight carapace length, documented behaviors, and quantified wariness by assessing minimum approach distance (MAD). In green sea turtles (Chelonia mydas), the observed MAD ranged from 0.72 to 5.99 m (mean 2.10 m ± 1.10 standard deviation (SD), n = 73). For loggerhead sea turtles (Caretta caretta), the MAD ranged between 0.93 and 3.80 m (mean 2.12 m ± 0.99 SD, n = 16). Kemp's ridley sea turtles (Lepidochelys kempii) were similar to loggerheads, and MAD ranged from 0.78 to 3.63 m (mean 2.35 m ± 0.99 SD, n = 8). We then evaluated what biological factors could impact the MAD observed by species, but we excluded Kemp's ridleys as the sample size was small. Using a linear mixed model and model selection based on AICc, the top ranked model for both green and loggerhead sea turtles included SCL as the most important factor influencing MAD. MAD did not vary with habitat type for either species. Our results showed that larger individuals, regardless of species, have a greater wariness response, becoming startled at greater distances than smaller individuals. The findings of our study support the use of SVC as an accessible, non-invasive tool to conduct ecologically relevant in-water surveys of sea turtles to link behavioral observations to body size.

Animal tracking moves community ecology: Opportunities and challenges

1. Individual decisions regarding how, why, and when organisms interact with one another and with their environment scale up to shape patterns and processes in communities. Recent evidence has firmly established the prevalence of intraspecific variation in nature and its relevance in community ecology, yet challenges associated with collecting data on large numbers of individual conspecifics and heterospecifics has hampered integration of individual variation into community ecology. 2. Nevertheless, recent technological and statistical advances in GPS-tracking, remote sensing, and behavioral ecology offer a toolbox for integrating intraspecific variation into community processes. More than simply describing where organisms go, movement data provide unique information about interactions and environmental associations from which a true individual-to-community framework can be built. 3. By linking the movement paths of both conspecifics and heterospecifics with environmental data, ecologists can now simultaneously quantify intra- and interspecific variation regarding the Eltonian (biotic interactions) and Grinnellian (environmental conditions) factors underpinning community assemblage and dynamics, yet substantial logistical and analytical challenges must be addressed for these approaches to realize their full potential. 4. Across communities, empirical integration of Eltonian and Grinnellian factors can support conservation applications and reveal metacommunity dynamics via tracking-based dispersal data. As the logistical and analytical challenges associated with multi-species tracking are surmounted, we envision a future where individual movements and their ecological and environmental signatures will bring resolution to many enduring issues in community ecology.

Evaluating Several Vegetation Indices Derived from Sentinel-2 Imagery for Quantifying Localized Overgrazing in a Semi-Arid Region of South Africa

Rangeland monitoring aims to determine whether grazing management strategies meet the goals of sustainable resource utilization. The development of sustainable grazing management strategies requires an understanding of the manner in which grazing animals utilize available vegetation. In this study, we made use of livestock tracking, in situ observations and Sentinel-2 imagery to make rangeland scale observations of vegetation conditions in a semi-arid environment, to better understand the spatial relationships between vegetation conditions and sheep movement patterns. We hypothesized that sheep graze more selectively under low stocking rates—resulting in localized overgrazing. We also assessed the importance of image spatial resolution, as it was assumed localized effects of grazing will be best explained by higher resolution imagery. The results showed that livestock tend to congregate along drainage lines where soils are deeper. The findings demonstrate how the spatial analysis of remotely sensed data can provide a landscape-scale overview of livestock movement patterns. This study illustrates that high-resolution normalized difference vegetation index (NDVI) data can be used as a grazing management tool to determine the spatial variability of productive areas across the semi-arid Upper Karoo rangelands and identify preferred grazing areas.

A Comprehensive Overview of Technologies for Species and Habitat Monitoring and Conservation

The range of technologies currently used in biodiversity conservation is staggering, with innovative uses often adopted from other disciplines and being trialed in the field. We provide the first comprehensive overview of the current (2020) landscape of conservation technology, encompassing technologies for monitoring wildlife and habitats, as well as for on-the-ground conservation management (e.g., fighting illegal activities). We cover both established technologies (routinely deployed in conservation, backed by substantial field experience and scientific literature) and novel technologies or technology applications (typically at trial stage, only recently used in conservation), providing examples of conservation applications for both types. We describe technologies that deploy sensors that are fixed or portable, attached to vehicles (terrestrial, aquatic, or airborne) or to animals (biologging), complemented with a section on wildlife tracking. The last two sections cover actuators and computing (including web platforms, algorithms, and artificial intelligence).

A rare 300 kilometer dispersal by an adult male white-tailed deer

Despite the key roles that dispersal plays in individual animal fitness and meta-population gene flow, it remains one of the least understood behaviors in many species. In large mammalian herbivores, dispersals might span long distances and thereby influence landscape-level ecological processes, such as infectious disease spread. Here, we describe and analyze an exceptional long-distance dispersal by an adult white-tailed deer (Odocoileus virginianus) in the central United States. We also conducted a literature survey to compare the dispersal to previous studies. This dispersal was remarkable for its length, duration, and the life history stage of the dispersing individual. Dispersal is typical of juvenile deer seeking to establish postnatal home ranges, but this dispersal was undertaken by an adult male (age = 3.5). This individual dispersed ~300 km over a 22-day period by moving, on average, 13.6 km/day and achieving a straight-line distance of ~215 km, which was ~174 km longer than any other distance recorded for an adult male deer in our literature survey. During the dispersal, which occurred during the hunting season, the individual crossed a major river seven times, an interstate highway, a railroad, and eight state highways. Movements during the dispersal were faster (mean = 568.1 m/h) and more directional than those during stationary home range periods before and after the dispersal (mean = 56.9 m/h). Likewise, movements during the dispersal were faster (mean = 847.8 m/h) and more directional at night than during the day (mean = 166.4 m/h), when the individual frequently sheltered in forest cover. This natural history event highlights the unpredictable nature of dispersal and has important implications for landscape-level processes such as chronic wasting disease transmission in cervids. More broadly, our study underscores how integrating natural history observations with modern technology holds promise for understanding potentially high impact but rarely recorded ecological events.

Observing the unwatchable: Integrating automated sensing, naturalistic observations and animal social network analysis in the age of big data

In the 4.5 decades since Altmann (1974) published her seminal paper on the methods for the observational study of behaviour, automated detection and analysis of social interaction networks have fundamentally transformed the ways that ecologists study social behaviour. Methodological developments for collecting data remotely on social behaviour involve indirect inference of associations, direct recordings of interactions and machine vision. These recent technological advances are improving the scale and resolution with which we can dissect interactions among animals. They are also revealing new intricacies of animal social interactions at spatial and temporal resolutions as well as in ecological contexts that have been hidden from humans, making the unwatchable seeable. We first outline how these technological applications are permitting researchers to collect exquisitely detailed information with little observer bias. We further recognize new emerging challenges from these new reality-mining approaches. While technological advances in automating data collection and its analysis are moving at an unprecedented rate, we urge ecologists to thoughtfully combine these new tools with classic behavioural and ecological monitoring methods to place our understanding of animal social networks within fundamental biological contexts.

The context dependence of non-consumptive predator effects

Non-consumptive predator effects (NCEs) are now widely recognised for their capacity to shape ecosystem structure and function. Yet, forecasting the propagation of these predator-induced trait changes through particular communities remains a challenge. Accordingly, focusing on plasticity in prey anti-predator behaviours, we conceptualise the multi-stage process by which predators trigger direct and indirect NCEs, review and distil potential drivers of contingencies into three key categories (properties of the prey, predator and setting), and then provide a general framework for predicting both the nature and strength of direct NCEs. Our review underscores the myriad factors that can generate NCE contingencies while guiding how research might better anticipate and account for them. Moreover, our synthesis highlights the value of mapping both habitat domains and prey-specific patterns of evasion success ('evasion landscapes') as the basis for predicting how direct NCEs are likely to manifest in any particular community. Looking ahead, we highlight two key knowledge gaps that continue to impede a comprehensive understanding of non-consumptive predator-prey interactions and their ecosystem consequences; namely, insufficient empirical exploration of (1) context-dependent indirect NCEs and (2) the ways in which direct and indirect NCEs are shaped interactively by multiple drivers of context dependence.

Optimizing the use of biologgers for movement ecology research

The paradigm-changing opportunities of biologging sensors for ecological research, especially movement ecology, are vast, but the crucial questions of how best to match the most appropriate sensors and sensor combinations to specific biological questions and how to analyse complex biologging data, are mostly ignored. Here, we fill this gap by reviewing how to optimize the use of biologging techniques to answer questions in movement ecology and synthesize this into an Integrated Biologging Framework (IBF). We highlight that multisensor approaches are a new frontier in biologging, while identifying current limitations and avenues for future development in sensor technology. We focus on the importance of efficient data exploration, and more advanced multidimensional visualization methods, combined with appropriate archiving and sharing approaches, to tackle the big data issues presented by biologging. We also discuss the challenges and opportunities in matching the peculiarities of specific sensor data to the statistical models used, highlighting at the same time the large advances which will be required in the latter to properly analyse biologging data. Taking advantage of the biologging revolution will require a large improvement in the theoretical and mathematical foundations of movement ecology, to include the rich set of high-frequency multivariate data, which greatly expand the fundamentally limited and coarse data that could be collected using location-only technology such as GPS. Equally important will be the establishment of multidisciplinary collaborations to catalyse the opportunities offered by current and future biologging technology. If this is achieved, clear potential exists for developing a vastly improved mechanistic understanding of animal movements and their roles in ecological processes and for building realistic predictive models.

Through the eye of a Gobi khulan - Application of camera collars for ecological research of far-ranging species in remote and highly variable ecosystems

The Mongolian Gobi-Eastern Steppe Ecosystem is one of the largest remaining natural drylands and home to a unique assemblage of migratory ungulates. Connectivity and integrity of this ecosystem are at risk if increasing human activities are not carefully planned and regulated. The Gobi part supports the largest remaining population of the Asiatic wild ass (Equus hemionus; locally called "khulan"). Individual khulan roam over areas of thousands of square kilometers and the scale of their movements is among the largest described for terrestrial mammals, making them particularly difficult to monitor. Although GPS satellite telemetry makes it possible to track animals in near-real time and remote sensing provides environmental data at the landscape scale, remotely collected data also harbors the risk of missing important abiotic or biotic environmental variables or life history events. We tested the potential of animal born camera systems ("camera collars") to improve our understanding of the drivers and limitations of khulan movements. Deployment of a camera collar on an adult khulan mare resulted in 7,881 images over a one-year period. Over half of the images showed other khulan and 1,630 images showed enough of the collared khulan to classify the behaviour of the animals seen into several main categories. These khulan images provided us with: i) new insights into important life history events and grouping dynamics, ii) allowed us to calculate time budgets for many more animals than the collared khulan alone, and iii) provided us with a training dataset for calibrating data from accelerometer and tilt sensors in the collar. The images also allowed to document khulan behaviour near infrastructure and to obtain a day-time encounter rate between a specific khulan with semi-nomadic herders and their livestock. Lastly, the images allowed us to ground truth the availability of water by: i) confirming waterpoints predicted from other analyses, ii) detecting new waterpoints, and iii) compare precipitation records for rain and snow from landscape scale climate products with those documented by the camera collar. We discuss the added value of deploying camera collars on a subset of animals in remote, highly variable ecosystems for research and conservation.

Advances in population ecology and species interactions in mammals

The study of mammals has promoted the development and testing of many ideas in contemporary ecology. Here we address recent developments in foraging and habitat selection, source–sink dynamics, competition (both within and between species), population cycles, predation (including apparent competition), mutualism, and biological invasions. Because mammals are appealing to the public, ecological insight gleaned from the study of mammals has disproportionate potential in educating the public about ecological principles and their application to wise management. Mammals have been central to many computational and statistical developments in recent years, including refinements to traditional approaches and metrics (e.g., capture-recapture) as well as advancements of novel and developing fields (e.g., spatial capture-recapture, occupancy modeling, integrated population models). The study of mammals also poses challenges in terms of fully characterizing dynamics in natural conditions. Ongoing climate change threatens to affect global ecosystems, and mammals provide visible and charismatic subjects for research on local and regional effects of such change as well as predictive modeling of the long-term effects on ecosystem function and stability. Although much remains to be done, the population ecology of mammals continues to be a vibrant and rapidly developing field. We anticipate that the next quarter century will prove as exciting and productive for the study of mammals as has the recent one.

Cryptic habitat use of white sharks in kelp forest revealed by animal-borne video

Traditional forms of marine wildlife research are often restricted to coarse telemetry or surface-based observations, limiting information on fine-scale behaviours such as predator-prey events and interactions with habitat features. We use contemporary animal-attached cameras with motion sensing dataloggers, to reveal novel behaviours by white sharks, Carcharodon carcharias, within areas of kelp forest in South Africa. All white sharks tagged in this study spent time adjacent to kelp forests, with several moving throughout densely kelp-covered areas, navigating through channels and pushing directly through stipes and fronds. We found that activity and turning rates significantly increased within kelp forest. Over 28 h of video data revealed that white shark encounters with Cape fur seals, Arctocephalus pusillus pusillus, occurred exclusively within kelp forests, with seals displaying predator evasion behaviour during those encounters. Uniquely, we reveal the use of kelp forest habitat by white sharks, previously assumed inaccessible to these large predators.

Using on-board sound recordings to infer behaviour of free-moving wild animals

Technological advances in the last 20 years have enabled researchers to develop increasingly sophisticated miniature devices (tags) that record an animal's behaviour not from an observational, external viewpoint, but directly on the animals themselves. So far, behavioural research with these tags has mostly been conducted using movement or acceleration data. But on-board audio recordings have become more and more common following pioneering work in marine mammal research. The first questions that come to mind when recording sound on-board animals concern their vocal behaviour. When are they calling? How do they adjust their behaviour? What acoustic parameters do they change and how? However, other topics like foraging behaviour, social interactions or environmental acoustics can now be addressed as well and offer detailed insight into the animals' daily life. In this Review, we discuss the possibilities, advantages and limitations of on-board acoustic recordings. We focus primarily on bats as their active-sensing, echolocating lifestyle allows many approaches to a multi-faceted acoustic assessment of their behaviour. The general ideas and concepts, however, are applicable to many animals and hopefully will demonstrate the versatility of on-board acoustic recordings and stimulate new research.

High definition video loggers provide new insights into behaviour, physiology, and the oceanic habitat of a marine predator, the yellow-eyed penguin

Camera loggers are increasingly used to examine behavioural aspects of free-ranging animals. However, often video loggers are deployed with a focus on specific behavioural traits utilizing small cameras with a limited field of view, poor light performance and video quality. Yet rapid developments in consumer electronics provide new devices with much improved visual data allowing a wider scope for studies employing this novel methodology. We developed a camera logger that records full HD video through a wide-angle lens, providing high resolution footage with a greater field of view than other camera loggers. The main goal was to assess the suitability of this type of camera for the analysis of various aspects of the foraging ecology of a marine predator, the yellow-eyed penguin in New Zealand. Frame-by-frame analysis allowed accurate timing of prey pursuits and time spent over certain seafloor types. The recorded video footage showed that prey species were associated with certain seafloor types, revealed different predator evasion strategies by benthic fishes, and highlighted varying energetic consequences for penguins pursuing certain types of prey. Other aspects that could be analysed were the timing of breathing intervals between dives and observe exhalation events during prey pursuits, a previously undescribed behaviour. Screen overlays facilitated analysis of flipper angles and beat frequencies throughout various stages of the dive cycle. Flipper movement analysis confirmed decreasing effort during descent phases as the bird gained depth, and that ascent was principally passive. Breathing episodes between dives were short (<1 s) while the majority of the time was devoted to subsurface scanning with a submerged head. Video data recorded on free-ranging animals not only provide a wealth of information recorded from a single deployment but also necessitate new approaches with regards to analysis of visual data. Here, we demonstrate the diversity of information that can be gleaned from video logger data, if devices with high video resolution and wide field of view are utilized.

High definition video loggers provide new insights into behaviour, physiology, and the oceanic habitat of a marine predator, the yellow-eyed penguin

Camera loggers are increasingly used to examine behavioural aspects of free-ranging animals. However, often video loggers are deployed with a focus on specific behavioural traits utilizing small cameras with a limited field of view, poor light performance and video quality. Yet rapid developments in consumer electronics provide new devices with much improved visual data allowing a wider scope for studies employing this novel methodology. We developed a camera logger that records full HD video through a wide-angle lens, providing high resolution footage with a greater field of view than other camera loggers. The main goal was to assess the suitability of this type of camera for the analysis of various aspects of the foraging ecology of a marine predator, the yellow-eyed penguin in New Zealand. Frame-by-frame analysis allowed accurate timing of prey pursuits and time spent over certain seafloor types. The recorded video footage showed that prey species were associated with certain seafloor types, revealed different predator evasion strategies by benthic fishes, and highlighted varying energetic consequences for penguins pursuing certain types of prey. Other aspects that could be analysed were the timing of breathing intervals between dives and observe exhalation events during prey pursuits, a previously undescribed behaviour. Screen overlays facilitated analysis of flipper angles and beat frequencies throughout various stages of the dive cycle. Flipper movement analysis confirmed decreasing effort during descent phases as the bird gained depth, and that ascent was principally passive. Breathing episodes between dives were short (<1 s) while the majority of the time was devoted to subsurface scanning with a submerged head. Video data recorded on free-ranging animals not only provide a wealth of information recorded from a single deployment but also necessitate new approaches with regards to analysis of visual data. Here, we demonstrate the diversity of information that can be gleaned from video logger data, if devices with high video resolution and wide field of view are utilized.

Search and foraging behaviors from movement data: A comparison of methods

Search behavior is often used as a proxy for foraging effort within studies of animal movement, despite it being only one part of the foraging process, which also includes prey capture. While methods for validating prey capture exist, many studies rely solely on behavioral annotation of animal movement data to identify search and infer prey capture attempts. However, the degree to which search correlates with prey capture is largely untested. This study applied seven behavioral annotation methods to identify search behavior from GPS tracks of northern gannets (Morus bassanus), and compared outputs to the occurrence of dives recorded by simultaneously deployed time-depth recorders. We tested how behavioral annotation methods vary in their ability to identify search behavior leading to dive events. There was considerable variation in the number of dives occurring within search areas across methods. Hidden Markov models proved to be the most successful, with 81% of all dives occurring within areas identified as search. k-Means clustering and first passage time had the highest rates of dives occurring outside identified search behavior. First passage time and hidden Markov models had the lowest rates of false positives, identifying fewer search areas with no dives. All behavioral annotation methods had advantages and drawbacks in terms of the complexity of analysis and ability to reflect prey capture events while minimizing the number of false positives and false negatives. We used these results, with consideration of analytical difficulty, to provide advice on the most appropriate methods for use where prey capture behavior is not available. This study highlights a need to critically assess and carefully choose a behavioral annotation method suitable for the research question being addressed, or resulting species management frameworks established.

Testing the feasibility of wireless sensor networks and the use of radio signal strength indicator to track the movements of wild animals

Context Wireless sensor networks (WSNs) are revolutionising areas of animal behaviour research and are advantageous based on their ability to be deployed remotely and unobtrusively, for long time periods in inaccessible areas. Aims We aimed to determine the feasibility of using a WSN to track detailed movement paths of small animals, e.g. rats (Rattus spp.) 100–400g, too small for current GPS technology, by calibrating active Radio Frequency Identification (RFID) tags and loggers using Radio Frequency Signal Strength Indicator (RSSI) as a proxy for distance. Active RFIDs are also called Wireless Identification (WID) tags. Methods Calibration tests were conducted using a grid of loggers (n=16) spaced at 45-m intervals in clear line-of-sight conditions. WID tags (n=16) were placed between the loggers at 45-m intervals. Eight ‘walks’ were also conducted through the grid using a single WID tag. This involved attaching the tag to a small bottle of water (to simulate the body of an animal), towed around the grid using a 1-m long tow line attached to a volunteer walker. The volunteer also held a GPS device that logged their track. Models were constructed to test the effects of distance, tag movement and individual differences in loggers and tags on the reliability of movement data. Key results Loggers were most successful at detecting tags at distances &lt;50m. However, there was a significant difference in the detection probabilities of individual loggers and also the transmission performance of individual tags. Static tags were less likely to be detected than the mobile tag; and although RSSI was somewhat related to distance, the reliability of this parameter was highly variable. Implications We recommend caution in the future use of current radio frequency ID tags in wireless sensor networks to track the movement of small animals, and in the use of RSSI as an indicator of individual distance values, as extensive in situ calibration is required. ‘Off the shelf’ devices may vary in performance, rendering data unreliable. We emphasise the importance of calibrating all equipment in animal tracking studies to reduce data uncertainty and error.

A preliminary study to estimate contact rates between free-roaming domestic dogs using novel miniature cameras

Information on contacts between individuals within a population is crucial to inform disease control strategies, via parameterisation of disease spread models. In this study we investigated the use of dog-borne video cameras–in conjunction with global positioning systems (GPS) loggers–to both characterise dog-to-dog contacts and to estimate contact rates. We customized miniaturised video cameras, enclosed within 3D-printed plastic cases, and attached these to nylon dog collars. Using two 3400 mAh NCR lithium Li-ion batteries, cameras could record a maximum of 22 hr of continuous video footage. Together with a GPS logger, collars were attached to six free roaming domestic dogs (FRDDs) in two remote Indigenous communities in northern Australia. We recorded a total of 97 hr of video footage, ranging from 4.5 to 22 hr (mean 19.1) per dog, and observed a wide range of social behaviours. The majority (69%) of all observed interactions between community dogs involved direct physical contact. Direct contact behaviours included sniffing, licking, mouthing and play fighting. No contacts appeared to be aggressive, however multiple teeth baring incidents were observed during play fights. We identified a total of 153 contacts–equating to 8 to 147 contacts per dog per 24 hr–from the videos of the five dogs with camera data that could be analysed. These contacts were attributed to 42 unique dogs (range 1 to 19 per video) which could be identified (based on colour patterns and markings). Most dog activity was observed in urban (houses and roads) environments, but contacts were more common in bushland and beach environments. A variety of foraging behaviours were observed, included scavenging through rubbish and rolling on dead animal carcasses. Identified food consumed included chicken, raw bones, animal carcasses, rubbish, grass and cheese. For characterising contacts between FRDD, several benefits of analysing videos compared to GPS fixes alone were identified in this study, including visualisation of the nature of the contact between two dogs; and inclusion of a greater number of dogs in the study (which do not need to be wearing video or GPS collars). Some limitations identified included visualisation of contacts only during daylight hours; the camera lens being obscured on occasion by the dog’s mandible or the dog resting on the camera; an insufficiently wide viewing angle (36°); battery life and robustness of the deployments; high costs of the deployment; and analysis of large volumes of often unsteady video footage. This study demonstrates that dog-borne video cameras, are a feasible technology for estimating and characterising contacts between FRDDs. Modifying camera specifications and developing new analytical methods will improve applicability of this technology for monitoring FRDD populations, providing insights into dog-to-dog contacts and therefore how disease might spread within these populations.

The many faces of fear: a synthesis of the methodological variation in characterizing predation risk

Predators affect prey by killing them directly (lethal effects) and by inducing costly antipredator behaviours in living prey (risk effects). Risk effects can strongly influence prey populations and cascade through trophic systems. A prerequisite for assessing risk effects is characterizing the spatiotemporal variation in predation risk. Risk effects research has experienced rapid growth in the last several decades. However, preliminary assessments of the resultant literature suggest that researchers characterize predation risk using a variety of techniques. The implications of this methodological variation for inference and comparability among studies have not been well recognized or formally synthesized. We couple a literature survey with a hierarchical framework, developed from established theory, to quantify the methodological variation in characterizing risk using carnivore-ungulate systems as a case study. Via this process, we documented 244 metrics of risk from 141 studies falling into at least 13 distinct subcategories within three broader categories. Both empirical and theoretical work suggest risk and its effects on prey constitute a complex, multi-dimensional process with expressions varying by spatiotemporal scale. Our survey suggests this multi-scale complexity is reflected in the literature as a whole but often underappreciated in any given study, which complicates comparability among studies and leads to an overemphasis on documenting the presence of risk effects rather than their mechanisms or scale of influence. We suggest risk metrics be placed in a more concrete conceptual framework to clarify inference surrounding risk effects and their cascading effects throughout ecosystems. We recommend studies (i) take a multi-scale approach to characterizing risk; (ii) explicitly consider 'true' predation risk (probability of predation per unit time); and (iii) use risk metrics that facilitate comparison among studies and the evaluation of multiple competing hypotheses. Addressing the pressing questions in risk effects research, including how, to what extent and on what scale they occur, requires leveraging the advantages of the many methods available to characterize risk while minimizing the confusion caused by variability in their application.

Remote bioenergetics measurements in wild fish: Opportunities and challenges

The generalized energy budget for fish (i.e., Energy Consumed=Metabolism+Waste+Growth) is as relevant today as when it was first proposed decades ago and serves as a foundational concept in fish biology. Yet, generating accurate measurements of components of the bioenergetics equation in wild fish is a major challenge. How often does a fish eat and what does it consume? How much energy is expended on locomotion? How do human-induced stressors influence energy acquisition and expenditure? Generating answers to these questions is important to fisheries management and to our understanding of adaptation and evolutionary processes. The advent of electronic tags (transmitters and data loggers) has provided biologists with improved opportunities to understand bioenergetics in wild fish. Here, we review the growing diversity of electronic tags with a focus on sensor-equipped devices that are commercially available (e.g., heart rate/electrocardiogram, electromyogram, acceleration, image capture). Next, we discuss each component of the bioenergetics model, recognizing that most research to date has focused on quantifying the activity component of metabolism, and identify ways in which the other, less studied components (e.g., consumption, specific dynamic action component of metabolism, somatic growth, reproductive investment, waste) could be estimated remotely. We conclude with a critical but forward-looking appraisal of the opportunities and challenges in using existing and emerging electronic sensor-tags for the study of fish energetics in the wild. Electronic tagging has become a central and widespread tool in fish ecology and fisheries management; the growing and increasingly affordable toolbox of sensor tags will ensure this trend continues, which will lead to major advances in our understanding of fish biology over the coming decades.

Path segmentation for beginners: an overview of current methods for detecting changes in animal movement patterns

Increased availability of high-resolution movement data has led to the development of numerous methods for studying changes in animal movement behavior. Path segmentation methods provide basics for detecting movement changes and the behavioral mechanisms driving them. However, available path segmentation methods differ vastly with respect to underlying statistical assumptions and output produced. Consequently, it is currently difficult for researchers new to path segmentation to gain an overview of the different methods, and choose one that is appropriate for their data and research questions. Here, we provide an overview of different methods for segmenting movement paths according to potential changes in underlying behavior. To structure our overview, we outline three broad types of research questions that are commonly addressed through path segmentation: 1) the quantitative description of movement patterns, 2) the detection of significant change-points, and 3) the identification of underlying processes or 'hidden states'. We discuss advantages and limitations of different approaches for addressing these research questions using path-level movement data, and present general guidelines for choosing methods based on data characteristics and questions. Our overview illustrates the large diversity of available path segmentation approaches, highlights the need for studies that compare the utility of different methods, and identifies opportunities for future developments in path-level data analysis.

Selfies of Imperial Cormorants (Phalacrocorax atriceps): What Is Happening Underwater?

During the last few years, the development of animal-borne still cameras and video recorders has enabled researchers to observe what a wild animal sees in the field. In the present study, we deployed miniaturized video recorders to investigate the underwater foraging behavior of Imperial cormorants (Phalacrocorax atriceps). Video footage was obtained from 12 animals and 49 dives comprising a total of 8.1 h of foraging data. Video information revealed that Imperial cormorants are almost exclusively benthic feeders. While foraging along the seafloor, animals did not necessarily keep their body horizontal but inclined it downwards. The head of the instrumented animal was always visible in the videos and in the majority of the dives it was moved constantly forward and backward by extending and contracting the neck while travelling on the seafloor. Animals detected prey at very short distances, performed quick capture attempts and spent the majority of their time on the seafloor searching for prey. Cormorants foraged at three different sea bottom habitats and the way in which they searched for food differed between habitats. Dives were frequently performed under low luminosity levels suggesting that cormorants would locate prey with other sensory systems in addition to sight. Our video data support the idea that Imperial cormorants’ efficient hunting involves the use of specialized foraging techniques to compensate for their poor underwater vision.

Feral Cats Are Better Killers in Open Habitats, Revealed by Animal-Borne Video

One of the key gaps in understanding the impacts of predation by small mammalian predators on prey is how habitat structure affects the hunting success of small predators, such as feral cats. These effects are poorly understood due to the difficulty of observing actual hunting behaviours. We attached collar-mounted video cameras to feral cats living in a tropical savanna environment in northern Australia, and measured variation in hunting success among different microhabitats (open areas, dense grass and complex rocks). From 89 hours of footage, we recorded 101 hunting events, of which 32 were successful. Of these kills, 28% were not eaten. Hunting success was highly dependent on microhabitat structure surrounding prey, increasing from 17% in habitats with dense grass or complex rocks to 70% in open areas. This research shows that habitat structure has a profound influence on the impacts of small predators on their prey. This has broad implications for management of vegetation and disturbance processes (like fire and grazing) in areas where feral cats threaten native fauna. Maintaining complex vegetation cover can reduce predation rates of small prey species from feral cat predation.

ECOLOGY. Terrestrial animal tracking as an eye on life and planet

Moving animals connect our world, spreading pollen, seeds, nutrients, and parasites as they go about the their daily lives. Recent integration of high-resolution Global Positioning System and other sensors into miniaturized tracking tags has dramatically improved our ability to describe animal movement. This has created opportunities and challenges that parallel big data transformations in other fields and has rapidly advanced animal ecology and physiology. New analytical approaches, combined with remotely sensed or modeled environmental information, have opened up a host of new questions on the causes of movement and its consequences for individuals, populations, and ecosystems. Simultaneous tracking of multiple animals is leading to new insights on species interactions and, scaled up, may enable distributed monitoring of both animals and our changing environment.

Extreme temperatures, foundation species, and abrupt ecosystem change: an example from an iconic seagrass ecosystem

Extreme climatic events can trigger abrupt and often lasting change in ecosystems via the reduction or elimination of foundation (i.e., habitat-forming) species. However, while the frequency/intensity of extreme events is predicted to increase under climate change, the impact of these events on many foundation species and the ecosystems they support remains poorly understood. Here, we use the iconic seagrass meadows of Shark Bay, Western Australia--a relatively pristine subtropical embayment whose dominant, canopy-forming seagrass, Amphibolis antarctica, is a temperate species growing near its low-latitude range limit--as a model system to investigate the impacts of extreme temperatures on ecosystems supported by thermally sensitive foundation species in a changing climate. Following an unprecedented marine heat wave in late summer 2010/11, A. antarctica experienced catastrophic (>90%) dieback in several regions of Shark Bay. Animal-borne video footage taken from the perspective of resident, seagrass-associated megafauna (sea turtles) revealed severe habitat degradation after the event compared with a decade earlier. This reduction in habitat quality corresponded with a decline in the health status of largely herbivorous green turtles (Chelonia mydas) in the 2 years following the heat wave, providing evidence of long-term, community-level impacts of the event. Based on these findings, and similar examples from diverse ecosystems, we argue that a generalized framework for assessing the vulnerability of ecosystems to abrupt change associated with the loss of foundation species is needed to accurately predict ecosystem trajectories in a changing climate. This includes seagrass meadows, which have received relatively little attention in this context. Novel research and monitoring methods, such as the analysis of habitat and environmental data from animal-borne video and data-logging systems, can make an important contribution to this framework.

Falcons pursue prey using visual motion cues: new perspectives from animal-borne cameras

This study reports on experiments on falcons wearing miniature videocameras mounted on their backs or heads while pursuing flying prey. Videos of hunts by a gyrfalcon (Falco rusticolus), gyrfalcon (F. rusticolus)/Saker falcon (F. cherrug) hybrids and peregrine falcons (F. peregrinus) were analyzed to determine apparent prey positions on their visual fields during pursuits. These video data were then interpreted using computer simulations of pursuit steering laws observed in insects and mammals. A comparison of the empirical and modeling data indicates that falcons use cues due to the apparent motion of prey on the falcon's visual field to track and capture flying prey via a form of motion camouflage. The falcons also were found to maintain their prey's image at visual angles consistent with using their shallow fovea. These results should prove relevant for understanding the co-evolution of pursuit and evasion, as well as the development of computer models of predation and the integration of sensory and locomotion systems in biomimetic robots.

Bird-borne video-cameras show that seabird movement patterns relate to previously unrevealed proximate environment, not prey

The study of ecological and behavioral processes has been revolutionized in the last two decades with the rapid development of biologging-science. Recently, using image-capturing devices, some pilot studies demonstrated the potential of understanding marine vertebrate movement patterns in relation to their proximate, as opposed to remote sensed environmental contexts. Here, using miniaturized video cameras and GPS tracking recorders simultaneously, we show for the first time that information on the immediate visual surroundings of a foraging seabird, the Cape gannet, is fundamental in understanding the origins of its movement patterns. We found that movement patterns were related to specific stimuli which were mostly other predators such as gannets, dolphins or fishing boats. Contrary to a widely accepted idea, our data suggest that foraging seabirds are not directly looking for prey. Instead, they search for indicators of the presence of prey, the latter being targeted at the very last moment and at a very small scale. We demonstrate that movement patterns of foraging seabirds can be heavily driven by processes unobservable with conventional methodology. Except perhaps for large scale processes, local-enhancement seems to be the only ruling mechanism; this has profounds implications for ecosystem-based management of marine areas.