Introduction to the theme issue: Measuring physiology in free-living animals

Through the looking glass: attempting to predict future opportunities and challenges in experimental biology

To celebrate its centenary year, Journal of Experimental Biology (JEB) commissioned a collection of articles examining the past, present and future of experimental biology. This Commentary closes the collection by considering the important research opportunities and challenges that await us in the future. We expect that researchers will harness the power of technological advances, such as '-omics' and gene editing, to probe resistance and resilience to environmental change as well as other organismal responses. The capacity to handle large data sets will allow high-resolution data to be collected for individual animals and to understand population, species and community responses. The availability of large data sets will also place greater emphasis on approaches such as modeling and simulations. Finally, the increasing sophistication of biologgers will allow more comprehensive data to be collected for individual animals in the wild. Collectively, these approaches will provide an unprecedented understanding of 'how animals work' as well as keys to safeguarding animals at a time when anthropogenic activities are degrading the natural environment.

Applications of Accelerometers and Other Bio-Logging Devices in Captive and Wild Animals

Bio-logging devices have been widely used in ecology across a range of species to acquire information on the secret lives of animals in the wild, which would otherwise be challenging to obtain via direct observations [...].

Pathogen surveillance and epidemiology in endangered Peninsular bighorn sheep (Ovis canadensis nelsoni)

Peninsular bighorn sheep (Ovis canadensis nelsoni) are found exclusively in Southern California and Baja Mexico. They are federally endangered due to multiple threats, including introduced infectious disease. From 1981 - 2017, we conducted surveillance for 16 pathogens and estimated population sizes, adult survival, and lamb survival. We used mixed effects regression models to assess disease patterns at the individual and population levels. Pathogen infection/exposure prevalence varied both spatially and temporally. Our findings indicate that the primary predictor of individual pathogen infection/exposure was the region in which an animal was captured, implying that transmission is driven by local ecological or behavioral factors. Higher Mycoplasma ovipneumoniae seropositivity was associated with lower lamb survival, consistent with lambs having high rates of pneumonia-associated mortality, which may be slowing population recovery. There was no association between M. ovipneumoniae and adult survival. Adult survival was positively associated with population size and parainfluenza-3 virus seroprevalence in the same year, and orf virus seroprevalence in the previous year. Peninsular bighorn sheep are recovering from small population sizes in a habitat of environmental extremes, compounded by infectious disease. Our research can help inform future pathogen surveillance and population monitoring for the long-term conservation of this population.

How Reproducibility Will Accelerate Discovery Through Collaboration in Physio-Logging

What new questions could ecophysiologists answer if physio-logging research was fully reproducible? We argue that technical debt (computational hurdles resulting from prioritizing short-term goals over long-term sustainability) stemming from insufficient cyberinfrastructure (field-wide tools, standards, and norms for analyzing and sharing data) trapped physio-logging in a scientific silo. This debt stifles comparative biological analyses and impedes interdisciplinary research. Although physio-loggers (e.g., heart rate monitors and accelerometers) opened new avenues of research, the explosion of complex datasets exceeded ecophysiology’s informatics capacity. Like many other scientific fields facing a deluge of complex data, ecophysiologists now struggle to share their data and tools. Adapting to this new era requires a change in mindset, from “data as a noun” (e.g., traits, counts) to “data as a sentence”, where measurements (nouns) are associate with transformations (verbs), parameters (adverbs), and metadata (adjectives). Computational reproducibility provides a framework for capturing the entire sentence. Though usually framed in terms of scientific integrity, reproducibility offers immediate benefits by promoting collaboration between individuals, groups, and entire fields. Rather than a tax on our productivity that benefits some nebulous greater good, reproducibility can accelerate the pace of discovery by removing obstacles and inviting a greater diversity of perspectives to advance science and society. In this article, we 1) describe the computational challenges facing physio-logging scientists and connect them to the concepts of technical debt and cyberinfrastructure, 2) demonstrate how other scientific fields overcame similar challenges by embracing computational reproducibility, and 3) present a framework to promote computational reproducibility in physio-logging, and bio-logging more generally.

An accelerometer-derived ballistocardiogram method for detecting heartrates in free-ranging marine mammals

Physio-logging methods, which use animal-borne devices to record physiological variables, are entering a new era driven by advances in sensor development. However, existing datasets collected with traditional bio-loggers, such as accelerometers, still contain untapped eco-physiological information. Here, we present a computational method for extracting heart rate from high-resolution accelerometer data using a ballistocardiogram. We validated our method with simultaneous accelerometer–electrocardiogram tag deployments in a controlled setting on a killer whale (Orcinus orca) and demonstrate the predictions correspond with previously observed cardiovascular patterns in a blue whale (Balaenoptera musculus), including the magnitude of apneic bradycardia and increase in heart rate prior to and during ascent. Our ballistocardiogram method may be applied to mine heart rates from previously collected accelerometery data and expand our understanding of comparative cardiovascular physiology.

Highlighted Article: Validation of a computational method for extracting heart rate in free-ranging cetaceans from high-resolution accelerometer data using a ballistocardiogram.

Body Temperature Frequency Distributions: A Tool for Assessing Thermal Performance in Endotherms?

There is increasing recognition that rather than being fully homeothermic, most endotherms display some degree of flexibility in body temperature. However, the degree to which this occurs varies widely from the relatively strict homeothermy in species, such as humans to the dramatic seasonal hibernation seen in Holarctic ground squirrels, to many points in between. To date, attempts to analyse this variability within the framework generated by the study of thermal performance curves have been lacking. We tested if frequency distribution histograms of continuous body temperature measurements could provide a useful analogue to a thermal performance curve in endotherms. We provide examples from mammals displaying a range of thermoregulatory phenotypes, break down continuous core body temperature traces into various components (active and rest phase modes, spreads and skew) and compare these components to hypothetical performance curves. We did not find analogous patterns to ectotherm thermal performance curves, in either full datasets or by breaking body temperature values into more biologically relevant components. Most species had either bimodal or right-skewed (or both) distributions for both active and rest phase body temperatures, indicating a greater capacity for mammals to tolerate body temperatures elevated above the optimal temperatures than commonly assumed. We suggest that while core body temperature distributions may prove useful in generating optimal body temperatures for thermal performance studies and in various ecological applications, they may not be a good means of assessing the shape and breath of thermal performance in endotherms. We also urge researchers to move beyond only using mean body temperatures and to embrace the full variability in both active and resting temperatures in endotherms.

Future trends in measuring physiology in free-living animals

Thus far, ecophysiology research has predominantly been conducted within controlled laboratory-based environments, owing to a mismatch between the recording technologies available for physiological monitoring in wild animals and the suite of behaviours and environments they need to withstand, without unduly affecting subjects. While it is possible to record some physiological variables for free-living animals using animal-attached logging devices, including inertial-measurement, heart-rate and temperature loggers, the field is still in its infancy. In this opinion piece, we review the most important future research directions for advancing the field of 'physiologging' in wild animals, including the technological development that we anticipate will be required, and the fiscal and ethical challenges that must be overcome. Non-invasive, multi-sensor miniature devices are ubiquitous in the world of human health and fitness monitoring, creating invaluable opportunities for animal and human physiologging to drive synergistic advances. We argue that by capitalizing on the research efforts and advancements made in the development of human wearables, it will be possible to design the non-invasive loggers needed by ecophysiologists to collect accurate physiological data from free-ranging animals ethically and with an absolute minimum of impact. In turn, findings have the capacity to foster transformative advances in human health monitoring. Thus, we invite biomedical engineers and researchers to collaborate with the animal-tagging community to drive forward the advancements necessary to realize the full potential of both fields. This article is part of the theme issue 'Measuring physiology in free-living animals (Part II)'.