Thinking small: Next-generation sensor networks close the size gap in vertebrate biologging

Long-term cooperative relationships among vampire bats are not strongly predicted by their initial interactions

In many group-living animals, survival and reproductive success depend on the formation of long-term social bonds, yet it remains largely unclear why particular pairs of groupmates form social bonds and not others. Can social bond formation be reliably predicted from each individual's immediately observable traits and behaviors at first encounter? Or is social bond formation hard to predict due to the impacts of shifting social preferences on social network dynamics? To begin to address these questions, we asked how well long-term cooperative relationships among vampire bats were predicted by how they interacted during their first encounter as introduced strangers. In Study 1, we found that the first 6 h of observed interactions among unfamiliar bats co-housed in small cages did not clearly predict the formation of allogrooming or food-sharing relationships over the next 10 months. In Study 2, we found that biologger-tracked first contacts during the first 4-24 h together in a flight cage did not strongly predict allogrooming rates over the next 4 months. These results corroborate past evidence that social bonding in vampire bats is not reducible to the individual traits or behaviors observed at first encounter. Put simply, first impressions are overshadowed by future social interactions.

Time synchronisation for millisecond-precision on bio-loggers

Time-synchronised data streams from bio-loggers are becoming increasingly important for analysing and interpreting intricate animal behaviour including split-second decision making, group dynamics, and collective responses to environmental conditions. With the increased use of AI-based approaches for behaviour classification, time synchronisation between recording systems is becoming an essential challenge. Current solutions in bio-logging rely on manually removing time errors during post processing, which is complex and typically does not achieve sub-second timing accuracies.We first introduce an error model to quantify time errors, then optimise three wireless methods for automated onboard time (re)synchronisation on bio-loggers (GPS, WiFi, proximity messages). The methods can be combined as required and, when coupled with a state-of-the-art real time clock, facilitate accurate time annotations for all types of bio-logging data without need for post processing. We analyse time accuracy of our optimised methods in stationary tests and in a case study on 99 Egyptian fruit bats (Rousettus aegyptiacus). Based on the results, we offer recommendations for projects that require high time synchrony.During stationary tests, our low power synchronisation methods achieved median time accuracies of 2.72 / 0.43 ms (GPS / WiFi), compared to UTC time, and relative median time accuracies of 5 ms between tags (wireless proximity messages). In our case study with bats, we achieved a median relative time accuracy of 40 ms between tags throughout the entire 10-day duration of tag deployment. Using only one automated resynchronisation per day, permanent UTC time accuracies of ≤ 185 ms can be guaranteed in 95% of cases over a wide temperature range between 0 and 50 °C. Accurate timekeeping required a minimal battery capacity, operating in the nano- to microwatt range.Time measurements on bio-loggers, similar to other forms of sensor-derived data, are prone to errors and so far received little scientific attention. Our combinable methods offer a means to quantify time errors and autonomously correct them at the source (i.e., on bio-loggers). This approach facilitates sub-second comparisons of simultaneously recorded time series data across multiple individuals and off-animal devices such as cameras or weather stations. Through automated resynchronisations on bio-loggers, long-term sub-second accurate timestamps become feasible, even for life-time studies on animals. We contend that our methods have potential to greatly enhance the quality of ecological data, thereby improving scientific conclusions.

Advances in biologging can identify nuanced energetic costs and gains in predators

Foraging is a key driver of animal movement patterns, with specific challenges for predators which must search for mobile prey. These patterns are increasingly impacted by global changes, principally in land use and climate. Understanding the degree of flexibility in predator foraging and social strategies is pertinent to wildlife conservation under global change, including potential top-down effects on wider ecosystems. Here we propose key future research directions to better understand foraging strategies and social flexibility in predators. In particular, rapid continued advances in biologging technology are helping to record and understand dynamic behavioural and movement responses of animals to environmental changes, and their energetic consequences. Data collection can be optimised by calibrating behavioural interpretation methods in captive settings and strategic tagging decisions within and between social groups. Importantly, many species' social systems are increasingly being found to be more flexible than originally described in the literature, which may be more readily detectable through biologging approaches than behavioural observation. Integrating the effects of the physical landscape and biotic interactions will be key to explaining and predicting animal movements and energetic balance in a changing world.

Feedback loops between 3D vegetation structure and ecological functions of animals

Ecosystems function in a series of feedback loops that can change or maintain vegetation structure. Vegetation structure influences the ecological niche space available to animals, shaping many aspects of behaviour and reproduction. In turn, animals perform ecological functions that shape vegetation structure. However, most studies concerning three-dimensional vegetation structure and animal ecology consider only a single direction of this relationship. Here, we review these separate lines of research and integrate them into a unified concept that describes a feedback mechanism. We also show how remote sensing and animal tracking technologies are now available at the global scale to describe feedback loops and their consequences for ecosystem functioning. An improved understanding of how animals interact with vegetation structure in feedback loops is needed to conserve ecosystems that face major disruptions in response to climate and land-use change.

Bat behavioral immune responses in social contexts: current knowledge and future directions

Animals often mount complex immune responses to infections. Aside from cellular and molecular defense mechanisms, animals can alter their behavior in response to infection by avoiding, resisting, or tolerating negative effects of pathogens. These behaviors are often connected to cellular and molecular immune responses. For instance, sickness behaviors are a set of behavioral changes triggered by the host inflammatory response (e.g., cytokines) and could aid in resisting or tolerating infection, as well as affect transmission dynamics if sick animals socially withdraw or are being avoided by others. To fully understand the group and population level transmission dynamics and consequences of pathogen infections in bats, it is not only important to consider cellular and molecular defense mechanisms, but also behavioral mechanisms, and how both interact. Although there has been increasing interest in bat immune responses due to their ability to successfully cope with viral infections, few studies have explored behavioral anti-pathogen defense mechanisms. My main objective is to explore the interaction of cellular and molecular defense mechanisms, and behavioral alterations that results from infection in bats, and to outline current knowledge and future research avenues in this field.

Methodology for Safe and Effective Subcutaneous Implantation of Wireless Biotelemetry Sensor Devices in Rodents

In this work, a methodology for assessing the impact of implantation surgery on laboratory mice on behavior was created. The study included the design of several implants fabricated on various printed circuit board (PCB) technologies with overall diameters between 26-28mm and weights between 4.5-6.5g. 11 adult CD1 mice were implanted with the devices and their behavior was analyzed using common behavioral benchmark tests. The results show that implants designed to be 10% of the animal's body weight showed no adverse effects on mobility or social behavior. These results illustrate a method to identify and reduce the adverse behavioral changes inherent to device implantation. Additional considerations for implant surgery are provided. These results are validated with the implantation of a Bluetooth Low Energy (BLE) wireless sensor tag. The implanted wireless tag showed an average Received Signal Strength Indicator (RSSI) of 62.96dBm with a standard deviation of 4.95dBm and a variance of 24.5 dBm2. The high RSSI and variance values show that the implant was working well inside of the mouse's body and that the mouse was fully recovered and readily exploring its surroundings.Clinical Relevance-This work 1) studies the behavioral impact of implantable wireless biopotential devices. This will help clinical researchers conducting behavioral studies using sensor implants. 2) demonstrates a working implanted BLE wireless model inside of a mouse. Various wireless connectivity metrics are studied.

Mobile-BAT-A Novel Ultra-Low Power Wildlife Tracking System

We introduce a novel ultra-low power system for tracking animal movements over long periods with an unprecedented high-temporal-resolution. The localization principle is based on the detection of cellular base stations using a miniaturized software-defined radio, weighing 2.0 g, including the battery, and having a size equivalent to two stacked 1-euro cent coins. Therefore, the system is small and lightweight enough to be deployed on small, wide-ranging, or migrating animals, such as European bats, for movement analysis with an unprecedented spatiotemporal resolution. The position estimation relies on a post-processing probabilistic RF pattern-matching method based on the acquired base stations and power levels. In several field tests, the system has been successfully verified, and a run-time of close to one year has been demonstrated.

Experimentally advancing morning emergence time does not increase extra-pair siring success in blue tit males

Extra-pair paternity occurs frequently in socially monogamous birds, but there is substantial variation in extra-pair siring success among males. Several studies have shown that siring success relates to the timing of morning activity, with the earliest active males being more successful, suggesting that early activity is important for acquiring extra-pair copulations. However, these studies are correlational, and it, therefore, remains unclear whether the relationship between timing and extra-pair siring success is causal. An alternative explanation is that successful extra-pair sires tend to be active earlier (e.g., because they are of high quality or in good condition), but that early activity in itself does not increase siring success. We experimentally advanced the emergence time of male blue tits by exposing them to light about half an hour before their natural emergence time. Although males that were exposed to the light treatment emerged from their roost substantially earlier than males that were exposed to a control treatment, light-treated males were not more likely to sire extra-pair offspring. Furthermore, whereas control males showed the expected relation between emergence time and siring success (although not statistically significant), there was no relation between emergence time and extra-pair siring success among light-treated males. Our results suggest that the timing of emergence from the roost is not an important factor underlying extra-pair siring success.

Burmese pythons in Florida: A synthesis of biology, impacts, and management tools

Burmese pythons (Python molurus bivittatus) are native to southeastern Asia, however, there is an established invasive population inhabiting much of southern Florida throughout the Greater Everglades Ecosystem. Pythons have severely impacted native species and ecosystems in Florida and represent one of the most intractable invasive-species management issues across the globe. The difficulty stems from a unique combination of inaccessible habitat and the cryptic and resilient nature of pythons that thrive in the subtropical environment of southern Florida, rendering them extremely challenging to detect. Here we provide a comprehensive review and synthesis of the science relevant to managing invasive Burmese pythons. We describe existing control tools and review challenges to productive research, identifying key knowledge gaps that would improve future research and decision making for python control.

Animal movement ecology in India: insights from 2011-2021 and prospective for the future

The field of animal movement ecology has advanced by leaps and bounds in the past few decades with the advent of sophisticated technology, advanced analytical tools, and multiple frameworks and paradigms to address key ecological problems. Unlike the longer history and faster growth of the field in North America, Europe, and Africa, movement ecology in Asia has only recently been gaining momentum. Here, we provide a review of the field from studies based in India over the last 11 years (2011-2021) curated from the database, Scopus, and search engine, Google Scholar. We identify current directions in the research objectives, taxa studied, tracking technology and the biogeographic regions in which animals were tracked, considering the years since the last systematic review of movement ecology research in the country. As an indication of the growing interest in this field, there has been a rapid increase in the number of publications over the last decade. Class Mammalia continues to dominate the taxa tracked, with tiger and leopard being the most common species studied across publications. Invertebrates and other small and medium-sized animals, as well as aquatic animals, in comparison, are understudied and remain among the important target taxa for tracking in future studies. As in the previous three decades, researchers have focussed on characterising home ranges and habitat use of animals. There is, however, a notable shift to examine the movement decision of animals in human-modified landscapes, although efforts to use movement ecology to understand impacts of climate change remain missing. Given the biogeographic and taxonomic diversity of India, and the fact that the interface between anthropogenic activity and wildlife interactions is increasing, we suggest ways in which the field of movement ecology can be expanded to facilitate ecological insights and conservation efforts. With the advancement of affordable technologies and the availability of analytical tools, the potential to expand the field of movement ecology, shift research foci, and gain new insights is now prime.

Social interactions of juvenile rabbits (Oryctolagus cuniculus) and their potential role in lagovirus transmission

Rabbit Haemorrhagic Disease Virus (RHDV), which is a calicivirus, is used as a biocontrol agent to suppress European wild rabbit populations in Australia. The transmission of RHDV can be influenced by social interactions of rabbits; however, there is a paucity of this knowledge about juvenile rabbits and the roles they may play in the transmission of RHDV. We aimed to quantify the social interactions of juvenile (< 900 g) and adult (> 1200 g) rabbits in a locally abundant population in the Central Tablelands of New South Wales, Australia. Twenty-six juvenile and 16 adult rabbits were fitted with VHF proximity loggers to monitor intra- and inter-group pairings. Use of multiple warrens by these rabbits was investigated using VHF base stations at nine warrens and on foot with a hand-held Yagi antenna. Juvenile rabbits were strongly interconnected with both juveniles and adults within and outside their warren of capture, and almost all juveniles were well-connected to other individuals within their own social group. Inter-group pairings were infrequent and fleeting between adults. Both juvenile and adult rabbits used multiple warrens. However, visits to warrens outside their warren of capture, particularly those within 50 m, were more common and longer in duration in juveniles than in adults. The high connectivity of juveniles within and between warrens in close proximity increases potential pathogen exchange between warrens. Therefore, juvenile rabbits could be of greater importance in lagovirus transmission than adult rabbits. The strength of juvenile rabbit inter- and intra-group pairings, and their tendency to use multiple warrens, highlight their potential to act as ‘superspreaders’ of both infection and immunity for lagoviruses and other pathogens with similar lifecycles. Confirmation of this potential is required through examination of disease progress and rabbit age-related immune responses during outbreaks.

Micro-sized open-source and low-cost GPS loggers below 1 g minimise the impact on animals while collecting thousands of fixes

GPS-enabled loggers have been proven as valuable tools for monitoring and understanding animal movement, behaviour and ecology. While the importance of recording accurate location estimates is well established, deployment on many, especially small species, has been limited by logger mass and cost. We developed an open-source and low-cost 0.65 g GPS logger with a simple smartphone-compatible user interface, that can record more than 10,000 GPS fixes on a single 30 mAh battery charge (resulting mass including battery: 1.3 g). This low-budget ‘TickTag’ (currently 32 USD) allows scientists to scale-up studies while becoming a ‘wearable’ for larger animals and simultaneously enabling high-definition studies on small animals. Tests on two different species (domestic dog, Canis lupus familiaris and greater mouse-eared bats, Myotis myotis) showed that our combination of optimised hardware design and software-based recording strategies increases the number of achievable GPS fixes per g device mass compared to existing micro-sized solutions. We propose that due to the open-source access, as well as low cost and mass, the TickTag fills a technological gap in wildlife ecology and will open up new possibilities for wildlife research and conservation.

Long-term field studies in bat research: importance for basic and applied research questions in animal behavior

Animal species differ considerably in longevity. Among mammals, short-lived species such as shrews have a maximum lifespan of about a year, whereas long-lived species such as whales can live for more than two centuries. Because of their slow pace of life, long-lived species are typically of high conservation concern and of special scientific interest. This applies not only to large mammals such as whales, but also to small-sized bats and mole-rats. To understand the typically complex social behavior of long-lived mammals and protect their threatened populations, field studies that cover substantial parts of a species' maximum lifespan are required. However, long-term field studies on mammals are an exception because the collection of individualized data requires considerable resources over long time periods in species where individuals can live for decades. Field studies that span decades do not fit well in the current career and funding regime in science. This is unfortunate, as the existing long-term studies on mammals yielded exciting insights into animal behavior and contributed data important for protecting their populations. Here, I present results of long-term field studies on the behavior, demography, and life history of bats, with a particular focus on my long-term studies on wild Bechstein's bats. I show that long-term studies on individually marked populations are invaluable to understand the social system of bats, investigate the causes and consequences of their extraordinary longevity, and assess their responses to changing environments with the aim to efficiently protect these unique mammals in the face of anthropogenic global change.

Identifying conservation technology needs, barriers, and opportunities

Amid accelerating threats to species and ecosystems, technology advancements to monitor, protect, and conserve biodiversity have taken on increased importance. While most innovations stem from adaptation of off-the-shelf devices, these tools can fail to meet the specialized needs of conservation and research or lack the support to scale beyond a single site. Despite calls from the conservation community for its importance, a shift to bottom-up innovation driven by conservation professionals remains limited. We surveyed practitioners, academic researchers, and technologists to understand the factors contributing to or inhibiting engagement in the collaborative process of technology development and adoption for field use and identify emerging technology needs. High cost was the main barrier to technology use across occupations, while development of new technologies faced barriers of cost and partner communication. Automated processing of data streams was the largest emerging need, and respondents focused mainly on applications for individual-level monitoring and automated image processing. Cross-discipline collaborations and expanded funding networks that encourage cyclical development and continued technical support are needed to address current limitations and meet the growing need for conservation technologies.

The Philosophy of Outliers: Reintegrating Rare Events Into Biological Science

Individual variation in morphology, physiology, and behavior has been a topic of great interest in the biological sciences. While scientists realize the importance of understanding diversity in individual phenotypes, historically the "minority" results (i.e., outlier observations or rare events) of any given experiment have been dismissed from further analysis. We need to reframe how we view "outliers" to improve our understanding of biology. These rare events are often treated as problematic or spurious, when they can be real rare events or individuals driving evolution in a population. It is our perspective that to understand what outliers can tell us in our data, we need to: (1) Change how we think about our data philosophically, (2) Fund novel collaborations using science "weavers" in our national funding agencies, and (3) Bridge long-term field and lab studies to reveal these outliers in action. By doing so, we will improve our understanding of variation and evolution. We propose that this shift in culture towards more integrative science will incorporate diverse teams, citizen scientists and local naturalists, and change how we teach future students.

Permutation tests for hypothesis testing with animal social network data: Problems and potential solutions

Permutation tests are widely used to test null hypotheses with animal social network data, but suffer from high rates of type I and II error when the permutations do not properly simulate the intended null hypothesis.Two common types of permutations each have limitations. Pre-network (or datastream) permutations can be used to control 'nuisance effects' like spatial, temporal or sampling biases, but only when the null hypothesis assumes random social structure. Node (or node-label) permutation tests can test null hypotheses that include nonrandom social structure, but only when nuisance effects do not shape the observed network.We demonstrate one possible solution addressing these limitations: using pre-network permutations to adjust the values for each node or edge before conducting a node permutation test. We conduct a range of simulations to estimate error rates caused by confounding effects of social or non-social structure in the raw data.Regressions on simulated datasets suggest that this 'double permutation' approach is less likely to produce elevated error rates relative to using only node permutations, pre-network permutations or node permutations with simple covariates, which all exhibit elevated type I errors under at least one set of simulated conditions. For example, in scenarios where type I error rates from pre-network permutation tests exceed 30%, the error rates from double permutation remain at 5%.The double permutation procedure provides one potential solution to issues arising from elevated type I and type II error rates when testing null hypotheses with social network data. We also discuss alternative approaches that can provide robust inference, including fitting mixed effects models, restricted node permutations, testing multiple null hypotheses and splitting large datasets to generate replicated networks. Finally, we highlight ways that uncertainty can be explicitly considered and carried through the analysis.

Habituation of common vampire bats to biologgers

Rapid advancements in biologging technology have led to unprecedented insights into animal behaviour, but testing the effects of biologgers on tagged animals is necessary for both scientific and ethical reasons. Here, we measured how quickly 13 wild-caught and captively isolated common vampire bats (Desmodus rotundus) habituated to mock proximity sensors glued to their dorsal fur. To assess habituation, we scored video-recorded behaviours every minute from 18.00 to 06.00 for 3 days, then compared the rates of grooming directed to the sensor tag versus to their own body. During the first hour, the mean tag-grooming rate declined dramatically from 53% of sampled time (95% CI = 36-65%, n = 6) to 16% (8-24%, n = 9), and down to 4% by hour 5 (1-6%, n = 13), while grooming of the bat's own body did not decline. When tags are firmly attached, isolated individual vampire bats mostly habituate within an hour of tag attachment. In two cases, however, tags became loose before falling off causing the bats to dishabituate. For tags glued to fur, behavioural data are likely to be impacted immediately after the tag is attached and when it is loose before it falls off.

Social foraging in vampire bats is predicted by long-term cooperative relationships

Stable social bonds in group-living animals can provide greater access to food. A striking example is that female vampire bats often regurgitate blood to socially bonded kin and nonkin that failed in their nightly hunt. Food-sharing relationships form via preferred associations and social grooming within roosts. However, it remains unclear whether these cooperative relationships extend beyond the roost. To evaluate if long-term cooperative relationships in vampire bats play a role in foraging, we tested if foraging encounters measured by proximity sensors could be explained by wild roosting proximity, kinship, or rates of co-feeding, social grooming, and food sharing during 21 months in captivity. We assessed evidence for 6 hypothetical scenarios of social foraging, ranging from individual to collective hunting. We found that closely bonded female vampire bats departed their roost separately, but often reunited far outside the roost. Repeating foraging encounters were predicted by within-roost association and histories of cooperation in captivity, even when accounting for kinship. Foraging bats demonstrated both affiliative and competitive interactions with different social calls linked to each interaction type. We suggest that social foraging could have implications for social evolution if "local" within-roost cooperation and "global" outside-roost competition enhances fitness interdependence between frequent roostmates.

Animal tag technology keeps coming of age: an engineering perspective

Animal-borne tags (biologgers) have now become extremely sophisticated, recording data from multiple sensors at high frequencies for long periods and, as such, have become a powerful tool for behavioural ecologists and physiologists studying wild animals. But the design and implementation of these tags is not trivial because engineers have to maximize performance and ability to function under onerous conditions while minimizing tag mass and volume (footprint) to maximize the wellbeing of the animal carriers. We present some of the major issues faced by tag engineers and show how tag designers must accept compromises while maintaining systems that can answer the questions being posed. We also argue that basic understanding of engineering issues in tag design by biologists will help feedback to engineers to better tag construction but also reduce the likelihood that tag-deploying biologists will misunderstand their own results. Finally, we suggest that proper consideration of conventional technology together with new approaches will lead to further step changes in our understanding of wild-animal biology using smart tags. This article is part of the theme issue 'Measuring physiology in free-living animals (Part II)'.

On the move: sloths and their epibionts as model mobile ecosystems

Sloths are unusual mobile ecosystems, containing a high diversity of epibionts living and growing in their fur as they climb slowly through the canopies of tropical forests. These epibionts include poorly studied algae, arthropods, fungi, and bacteria, making sloths likely reservoirs of unexplored biodiversity. This review aims to identify gaps and eliminate misconceptions in our knowledge of sloths and their epibionts, and to identify key questions to stimulate future research into the functions and roles of sloths within a broader ecological and evolutionary context. This review also seeks to position the sloth fur ecosystem as a model for addressing fundamental questions in metacommunity and movement ecology. The conceptual and evidence-based foundation of this review aims to serve as a guide for future hypothesis-driven research into sloths, their microbiota, sloth health and conservation, and the coevolution of symbioses in general.

The Rapid Rise of Next-Generation Natural History

Many ecologists have lamented the demise of natural history and have attributed this decline to a misguided view that natural history is outdated and unscientific. Although there is a perception that the focus in ecology and conservation have shifted away from descriptive natural history research and training toward hypothetico-deductive research, we argue that natural history has entered a new phase that we call “next-generation natural history.” This renaissance of natural history is characterized by technological and statistical advances that aid in collecting detailed observations systematically over broad spatial and temporal extents. The technological advances that have increased exponentially in the last decade include electronic sensors such as camera-traps and acoustic recorders, aircraft- and satellite-based remote sensing, animal-borne biologgers, genetics and genomics methods, and community science programs. Advances in statistics and computation have aided in analyzing a growing quantity of observations to reveal patterns in nature. These robust next-generation natural history datasets have transformed the anecdotal perception of natural history observations into systematically collected observations that collectively constitute the foundation for hypothetico-deductive research and can be leveraged and applied to conservation and management. These advances are encouraging scientists to conduct and embrace detailed descriptions of nature that remain a critically important component of the scientific endeavor. Finally, these next-generation natural history observations are engaging scientists and non-scientists alike with new documentations of the wonders of nature. Thus, we celebrate next-generation natural history for encouraging people to experience nature directly.

Social networks research in ex situ populations: Patterns, trends, and future directions for conservation-focused behavioral research

Social networks research using non-human animals has grown over the past decade, utilizing a wide range of species to answer an array of pure and applied questions. Network approaches have relevance to conservation, evaluating social influences on fecundity, health, fitness and longevity. While the application of network approaches to in situ populations with conservation concern appears in published literature, the degree to which ex situ and zoo-housed populations are the focus of "social networks for conservation research" is limited. Captive environments provide scientists with an ability to understand the social behavior of species that may be hard to observe consistently in the wild. This paper evaluates the scope of network research involving ex situ populations, analyzing output from 2010 to 2019 to determine trends in questions and subjects using ex situ populations. We show that only 8.2% of ex situ social network analysis (SNA) implications are of conservation-focus, apparent in papers relating to birds, carnivores, bats, primates, reptiles, and ungulates. Husbandry and welfare questions predominate in ex situ network research, but over half of these papers have nonpractical application (basic science). The chance of a citation for a basic science paper was 95.4% more than for a conservation-based paper. For taxonomic groups, primate-focused papers had the most citations. The focus of ex situ conservation-based networks research may be driven by the needs of conservation programs (e.g., population recovery outcomes) or by a need to evaluate the efficacy of ex situ conservation goals. We evaluate our findings considering the IUCN's One Plan Approach to conservation to show how in situ and ex situ network research is applicable to global conservation efforts. We have identified that there is a lack of application and evaluation of SNA to wildlife conservation. We highlight future areas of research in zoos and hope to stimulate discussion and collaboration between relevant parties.

An engineering perspective on the development and evolution of implantable cardiac monitors in free-living animals

The latest technologies associated with implantable physiological monitoring devices can record multiple channels of data (including: heart rates and rhythms, activity, temperature, impedance and posture), and coupled with powerful software applications, have provided novel insights into the physiology of animals in the wild. This perspective details past challenges and lessons learned from the uses and developments of implanted biologgers designed for human clinical application in our research on free-ranging American black bears (Ursus americanus). In addition, we reference other research by colleagues and collaborators who have leveraged these devices in their work, including: brown bears (Ursus arctos), grey wolves (Canis lupus), moose (Alces alces), maned wolves (Chrysocyon brachyurus) and southern elephant seals (Mirounga leonina). We also discuss the potentials for applications of such devices across a range of other species. To date, the devices described have been used in fifteen different wild species, with publications pending in many instances. We have focused our physiological research on the analyses of heart rates and rhythms and thus special attention will be paid to this topic. We then discuss some major expected step changes such as improvements in sensing algorithms, data storage, and the incorporation of next-generation short-range wireless telemetry. The latter provides new avenues for data transfer, and when combined with cloud-based computing, it not only provides means for big data storage but also the ability to readily leverage high-performance computing platforms using artificial intelligence and machine learning algorithms. These advances will dramatically increase both data quantity and quality and will facilitate the development of automated recognition of extreme physiological events or key behaviours of interest in a broad array of environments, thus further aiding wildlife monitoring and management.

This article is part of the theme issue ‘Measuring physiology in free-living animals (Part I)’.

Metamorphosis in an Era of Increasing Climate Variability

Most animals have complex life cycles including metamorphosis or other discrete life stage transitions, during which individuals may be particularly vulnerable to environmental stressors. With climate change, individuals will be exposed to increasing thermal and hydrologic variability during metamorphosis, which may affect survival and performance through physiological, behavioral, and ecological mechanisms. Furthermore, because metamorphosis entails changes in traits and vital rates, it is likely to play an important role in how populations respond to increasing climate variability. To identify mechanisms underlying population responses and associated trait and life history evolution, we need new approaches to estimating changes in individual traits and performance throughout metamorphosis, and we need to integrate metamorphosis as an explicit life stage in analytical models.

Temporal dynamics of competitive fertilization in social groups of red junglefowl (Gallus gallus) shed new light on avian sperm competition

Studies of birds have made a fundamental contribution to elucidating sperm competition processes, experimentally demonstrating the role of individual mechanisms in competitive fertilization. However, the relative importance of these mechanisms and the way in which they interact under natural conditions remain largely unexplored. Here, we conduct a detailed behavioural study of freely mating replicate groups of red junglefowl, Gallus gallus, to predict the probability that competing males fertilize individual eggs over the course of 10-day trials. Remating frequently with a female and mating last increased a male's probability of fertilization, but only for eggs ovulated in the last days of a trial. Conversely, older males, and those mating with more polyandrous females, had consistently lower fertilization success. Similarly, resistance to a male's mating attempts, particularly by younger females, reduced fertilization probability. After considering these factors, male social status, partner relatedness and the estimated state of male extragonadal sperm reserves did not predict sperm competition outcomes. These results shed new light on sperm competition dynamics in taxa such as birds, with prolonged female sperm storage and staggered fertilizations. This article is part of the theme issue 'Fifty years of sperm competition'.

Vertical stratification of seed-dispersing vertebrate communities and their interactions with plants in tropical forests

Vertical stratification (VS) is a widespread phenomenon in plant and animal communities in forests and a key factor for structuring their species richness and biodiversity, particularly in tropical forests. The organisms composing forest communities adjust and shape the complex three-dimensional structure of their environment and inhabit a large variety of niches along the vertical gradient of the forest. Even though the degree of VS varies among different vertebrate groups, patterns of compositional stratification can be observed across taxa. Communities of birds, bats, primates, and non-flying small mammals are vertically stratified in terms of abundance, species richness, diversity, and community composition. Frugivorous members of these taxa play important roles as seed dispersers and forage on fruit resources that, in turn, vary in quantity and nutritional value along the vertical gradient. As a consequence, plant-seed disperser interaction networks differ among strata, which is manifested in differences in interaction frequencies and the degree of mutual specialization. In general, the canopy stratum is composed of strong links and generalized associations, while the lower strata comprise weaker links and more specialized interactions. Investigating the VS of communities can provide us with a better understanding of species habitat restrictions, resource use, spatial movement, and species interactions. Especially in the face of global change, this knowledge will be important as these characteristics can imply different responses of species and taxa at a fine spatial scale.

Tracking sickness effects on social encounters via continuous proximity sensing in wild vampire bats

Sickness behaviors can slow the spread of pathogens across a social network. We conducted a field experiment to investigate how sickness behavior affects individual connectedness over time using a dynamic social network created from high-resolution proximity data. After capturing adult female vampire bats (Desmodus rotundus) from a roost, we created “sick” bats by injecting a random half of bats with the immune-challenging substance, lipopolysaccharide, while the control group received saline injections. Over the next 3 days, we used proximity sensors to continuously track dyadic associations between 16 “sick” bats and 15 control bats under natural conditions. Compared to control bats, “sick” bats associated with fewer bats, spent less time near others, and were less socially connected to more well-connected individuals (sick bats had on average a lower degree, strength, and eigenvector centrality). High-resolution proximity data allow researchers to flexibly define network connections (association rates) based on how a particular pathogen is transmitted (e.g., contact duration of &gt;1 vs. &gt;60 min, contact proximity of &lt;1 vs. &lt;10 m). Therefore, we inspected how different ways of measuring association rates changed the observed effect of LPS. How researchers define association rates influences the magnitude and detectability of sickness effects on network centrality. When animals are sick, they often encounter fewer individuals. We tracked this unintentional “social distancing” effect hour-by-hour in a wild colony of vampire bats. Using bat-borne proximity sensors, we compared changes in the social network connectedness of immune-challenged “sick” bats versus “control” bats over time. “Sick” bats had fewer encounters with others and spent less time near others. Associations changed dramatically by time of day, and different measures of association influenced the sickness effect estimates.

Visits at artificial RFID flowers demonstrate that juvenile flower-visiting bats perform foraging flights apart from their mothers

During the transition from parental care to independent life, the development of adequate foraging skills is a major challenge for many juvenile mammals. However, participating in their parents’ knowledge by applying social learning strategies might facilitate this task. For several mammals, communal foraging of adults and offspring is suggested to be an important mechanism in mediating foraging-related information. For the large mammalian taxon of bats, only little is known about foraging-related social learning processes during ontogeny. It is often suggested that following their mothers during foraging flights would represent a valuable option for juveniles to socially learn about foraging, e.g., where to find resource-rich foraging patches, but explicit tests are scarce. In the present study, we investigated the foraging behavior of juvenile flower-visiting bats (Glossophaga soricina) in a dry forest in Costa Rica. We tested whether recently volant, but still nursed pups perform foraging flights alone, or whether pups follow their mothers, which would enable pups to socially learn where to feed. For that, we trained mothers and pups to feed from artificial flowers with a RFID reading system and, subsequently, conducted a field experiment to test whether RFID-tagged mothers and pups visit these flowers communally or independently. Unexpectedly, pups often encountered and visited artificial flowers near the day roost, while mothers rarely did, suggesting that they foraged somewhere further away. Our results demonstrate that still nursed juveniles perform foraging flights apart from their mothers and might learn about the spatial distribution of food without participating in their mother’s knowledge, for instance, by following other conspecifics or applying individual learning strategies. An initial potential lack of foraging success in this period is likely compensated by the ongoing maternal provisioning with breast milk and regurgitated nectar during daytime. Our results contribute to the growing body of research on the ontogeny of mammalian foraging behavior in general.