Edited by: Deseada Parejo, University of Extremadura, Spain
Reviewed by: Andrew Mark Allen, Radboud University Nijmegen, Netherlands; Vicente Urios, University of Alicante, Spain
This article was submitted to Behavioral and Evolutionary Ecology, a section of the journal Frontiers in Ecology and Evolution
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The use of animal-born sensors for location-based tracking and bio-logging in terrestrial systems has expanded dramatically in the past 10 years. This rapid expansion has generated new data on how animals interact with and respond to variation in their environment, resulting in important ecological, physiological, and evolutionary insights. Although understanding the finer details of animal locations has important management relevance, applied studies are not prominent in the movement ecology literature. This is despite the long history of applied studies of animal movement and the urgent and growing need for evidence-based conservation guidance, especially in the challenging field of human-wildlife interactions. The goal of this review is to evaluate the realized contribution of tracking-based animal movement ecology to solving specific conservation problems, and to identify barriers that may hinder expansion of that contribution. To do this, we (a) briefly review the history and technologies used in animal tracking and bio-logging, (b) use a series of literature searches to evaluate the frequency with which movement ecology studies are designed to solve specific conservation problems, and (c) use this information to identify challenges that may limit the applied relevance of the field of movement ecology, and to propose pathways to expand that applied relevance. Our literature review quantifies the limited extent to which research in the field of movement ecology is designed to solve specific conservation problems, but also the fact that such studies are slowly becoming more prevalent. We discuss how barriers that limit application of these principles are likely due to constraints imposed by the types of data used commonly in the field. Problems of scale mismatch, error compounding, and data paucity all create challenges that are relevant to the field of movement ecology but may be especially pertinent in applied situations. Finding solutions to these problems will create new opportunity for movement ecologists to contribute to conservation science.
The use of animal-born sensors for location-based tracking and bio-logging in terrestrial systems has expanded dramatically in the recent past (Kays et al.,
Although this work has led to basic scientific advances, understanding the finer details of animal locations and state also has important applied or management relevance (Wilson et al.,
In spite of the applied relevance of understanding animal movement and the long history of animal tracking for applied purposes, applied studies are not prominent in the movement ecology literature. This may be because of ethical concerns associated with tracking rare species (Cooke et al.,
Our review begins by briefly covering the history of applied terrestrial animal tracking and bio-logging, and the current sensor technologies and environmental databases used in the field. This history is important because it is highly applied, in contrast to the modern basic emphasis of movement ecology. Likewise, describing sensor technology is important because doing so highlights constraints that may influence the applied potential of work done using these tools. Some of these issues are covered in greater detail in other reviews (Robinson et al.,
There is a long history of humans tracking animal movement for specific game management goals. Prehistoric communities of hunters-gatherers tracked and anticipated animal movements (Epp,
Development of newer communication protocols has accelerated access to a suite of remotely collected sensor data, supplied in large volumes, that has moved animal tracking away from its applied roots. For example, mobile telephony [Global System for Mobile communication (GSM) or Code Division Multiple Access (CDMA)] has been used to transmit high precision Global Positioning Satellite (GPS) locations and other data collected on mammals (Bunnefeld et al.,
There is a rapidly growing suite of miniaturized digital sensors available as off-the-shelf hardware components that can provide detailed information on animals. Although the newest of these sensors have been used primarily to advance basic ecological understanding, they have the potential for extensive use in applied ecology. Likewise, understanding these sensors and their details provides some potential insight into reasons for the limited conservation application of movement ecology principles.
More than 30 types of sensors are commercially available to technology developers and manufacturers (
Types of sensors available from commercial manufacturers that have been or that could be integrated into on-board animal bio-logging devices in terrestrial systems.
Accelerometer−1-axis and 3-axis | Movement, behavior | Mosser et al., |
GPS | Location, speed, direction, geofencing | – |
Light sensors—IR, visible and UV | Geolocation, context for behavior | Bridge et al., |
Temperature |
Context for behavior, ecol. interactions and physiology | Mandel et al., |
Camera (photo or video) | Behavior, ecological interactions | Moll et al., |
Identification sensors |
Behavior | Bonter and Bridge, |
Inertial measurement unit sensors |
Movement, behavior | Reynolds et al., |
Magnetometers | Movement, behavior | Guo et al., |
Microphones (sound) | Behavior, ecol. interactions | Cvikel et al., |
Physiological |
Physiology, behavior | Arlettaz et al., |
Air speed (Pitot tubes) | Air speed measurement | Reynolds et al., |
Biometric (fingerprint, retinal) | – | N/A |
Current and capacitive | – | N/A |
Dead reckoning | Animal movement | Wilson et al., |
Flex and force | Movement, behavior | N/A |
Gyroscopes−2-axis and 3-axis | Movement, behavior | N/A |
Gas/pollution sensors |
Respiration, toxicology | N/A |
Humidity | Context for behavior | N/A |
Proximity (radio and acoustic) | Social behavior, ecol. interactions | Prange et al., |
Solar and nuclear radiation | Context for behavior, toxicology | N/A |
A common step in processing sensor data gathered via animal tracking or bio-logging data is to associate them with external data describing the environment animals occupy. GIS and web-based tools have been developed to make these associations (Kemp et al.,
External data sets regularly associated with animal tracking or bio-logging data, some of the typical parameters in those datasets that are associated with terrestrial animal movement data, and the typical spatial and temporal scales at which the data are collected.
Digital Elevation Models (DEM) | Ground elevation, topography, roughness, etc. | 1 m−1 km | Static |
Geological data | Soil or substrate type | 10 m—regional | Static |
Land use and land cover maps | Vegetative cover, land use, imagery, features | 30 m−1 km | Annual/seasonal |
Political data | Administrative boundaries | Variable | Variable |
Population density | Human population density (continuous/categorical) | Variable | Annual |
Primary productivity data | NDVI, NPP, and their oceanic equivalents | ≥250 m | Seasonal/weekly |
Socio-economic data | GDP, etc. | Country or regional | Annual |
Air quality | Particulates, toxins, | Regional | Variable |
Astronomical data | Sunrise, sunset, solar activity, moon phase, magnetic | Location-specific | – |
Global climate indices | ENSO, NAO, SOI, drought | Continental-scale | Annual/seasonal |
Hydrology and water data | Interpolated or derived data of many types | Large-scale | – |
Modeled weather data | Interpolated or derived data of many types | 30+ km | 3–24 h |
Measured weather data | Location-specific data of many types | Location-specific | Variable |
Within the field of terrestrial wildlife management, there has been no shortage of studies of animal home range and habitat associations, movements, connectivity, and biogeography (Kie et al.,
To assess this observation, we conducted a series of literature searches to evaluate the realized prevalence of research that applies movement ecology principles to solve specific terrestrial conservation problems. Because different academic search engines may generate different types of results, we conducted 5 different searches using two search engines [GoogleScholar (GS) and Web of Science (WS)]. In our searches, we used four different dyads of search terms, pairing the term “movement ecology” with the terms “wildlife management” (GS + WS), “conservation biology” (WS), “species conservation” (WS), and “conservation” (WS). In our search engine surveys, we limited time frames to the period starting in 2008, when the field of movement ecology was defined (Nathan et al.,
In our interpretation of search results, we differentiated between research with ecological goals that has the potential to provide information for use in management, and research whose goals was to address specific conservation problems. Our approach builds on recent keyword-based searches that consider larger numbers of papers in less detail (Fraser et al.,
It should be noted that although we were stringent in considering which papers fit into the “Relevant” category, many papers fit into more than one of the other categories. For instance, some manuscripts reviewed background and proposed, and sometimes even used, new or modified tools. As such, these manuscripts reasonably could have been categorized as “Review,” “Descriptive,” or “Tools.” We were less stringent in assigning papers to these non-relevant categories and, thus, it may not be appropriate to use our summaries of categorization of papers for goals other than those we present here.
Searching GoogleScholar for the words “movement ecology” yielded about 10,300 results; searching for the words “wildlife management” yielded about 781,000 results. However, searching for the two together, and limiting our search period to the period starting in 2008 yielded about 1,900 results. We reviewed the first 200 of these (when sorted by Google's “relevance”;
Results from six literature searches to assess the degree to which modern movement ecology principles are integrated into conservation biology.
Movement ecology & wildlife management | GS | 200 | 28 | 70 | 54 | 14 | 25 | 9 |
14% | 35% | 27% | 7% | 13% | 5% | |||
Movement ecology & wildlife management | WoS | 8 | 1 | 1 | 2 | 2 | 2 | |
13% | 13% | 25% | 25% | 25% | 0% | |||
Movement ecology & conservation biology | WoS | 9 | 1 | 2 | 1 | 5 | 0 | 0 |
11% | 22% | 11% | 56% | 0% | 0% | |||
Movement ecology & species conservation | WoS | 8 | 2 | 5 | 0 | 1 | 0 | 0 |
25% | 63% | 0% | 13% | 0% | 0% | |||
Movement ecology & conservation | WoS | 202 | 29 | 107 | 23 | 13 | 22 | 8 |
14% | 53% | 11% | 6% | 11% | 4% | |||
Movement ecology journal | All | 184 | 7 | 111 | 43 | 4 | 12 | 7 |
4% | 60% | 23% | 2% | 7% | 4% | |||
We performed four other searches using Web of Science. Searching for the terms “movement ecology” and “wildlife management” returned eight papers, of which one was relevant (
Number of papers published in which movement ecology principles were used to solve specific conservation problems. These data are based on returns from a search of Web of Science for the terms “movement ecology” and “conservation.” The search returned 202 papers, of which 16 were categorized as those in which movement ecology principles were used to solve specific conservation problems.
Finally, we reviewed all 184 articles published in the journal “Movement Ecology” since its creation (
Although our literature search illustrated the paucity with which modern movement ecology approaches are used to generate solutions to specific conservation problems, it also highlighted several examples of this being done. Here, to illustrate those examples, we summarize the major themes in these and related publications.
Wildlife management problems have been addressed in a movement ecology framework by overlaying tracking data on data layers describing anthropogenic activity. For example, one paper noted in our literature search maps animal movement in the context of proposed oil and gas development (Sawyer et al.,
Human-wildlife conflict issues also have been addressed with real-time alerts generated by tracking technologies commonly used in movement ecology. For example, alerts were created when California condors (Sheppard et al.,
Movement ecology approaches have been used in a few other applied settings. For example, statistical modeling of remotely gathered bio-logging data can provide new insight about the environment an animal experiences. In this vein, analysis of data from soaring birds has been used as a tool to infer information about wind velocity and scale that may contribute to high-resolution weather observations (Treep et al.,
Finally, a recurring theme in our review was the presence of a fairly large number of papers pointing out the relevance to conservation biology of principles developed via movement ecology (i.e., “call to arms”). These pieces illustrate a broader recognition that there is value to using principles of movement ecology for conservation purposes. That said, the fact that such papers still are being published suggests that there is room for improvement in this regard.
Movement ecology aims to triangulate among the organism's internal state, its capacity to move, and the external factors it experiences (Nathan et al.,
Literature review suggests that making linkages between animal movement and the environment is prone to bias imposed by variation in the scale, accuracy, and precision of environmental data types. These biases manifest themselves in at least three different and highly relevant ways. The first of these is the problem of mismatches in scale between different sources of data used in movement research (i.e., a “scale mismatch problem”; see
A second bias can be imposed by compounding of measurement errors in data sets commonly used in movement ecology (i.e., an “error compounding problem”). For example, when estimating an animal's location in 3D, GPS measurement error combines with error and averaging within an elevation model (Péron et al.,
A third bias may be imposed by the paucity of data describing ecologically relevant resources (e.g., distribution of food, nests, or den sites; a “data paucity problem”). This is akin to the knowledge gap problem identified in previous reviews (Fraser et al.,
Addressing all three of these problems would have relevance to both fundamental and applied ecology. However, because so many management problems are scale- and measurement-specific, solving these issues may be especially relevant to applied ecology. With this in mind, one way to give the field of movement ecology more applied relevance may be through integration of data from less frequently used on-board or intrinsic sensors that can describe and map the environment the animal experiences (e.g., Treep et al.,
All of these solutions though share a common theme. In each case, they illustrate the value of onboard sensors to measure the actual environment the animal experiences, contributing to potential resolution of the data mismatch, error compounding, and data paucity problems. Such an approach would reduce reliance on coarse-scale environmental data layers that may limit application of movement ecology principles to conservation settings.
It was evident in our review that miniaturization of new generations of sensors has created reams of data that yield both opportunity and overload. The first ARGOS telemetry systems used a single sensor to measure location. Modern devices use a suite of sensors to measure repeatedly the location, the environment, and the animal's condition, actions, and physiology. Integration of these data from multiple sensors, although rarely achieved, allows users to refine understanding not only of animal movement but also of error in any one sensor. These refinements make data more accurate and precise and, thus, more relevant to both fundamental and applied ecology.
Developing the conceptual and quantitative tools to integrate, validate, analyze, and interpret these data is non-trivial. As a consequence, it is not unusual for users of sensor data in basic ecological studies to classify behaviors without externally validating their classification algorithms (e.g., Bishop et al.,
Perhaps the greatest technological limitation to data collection via remotely-sensed animal bio-logging is the narrow bandwidth pipe connecting the animal in the field to the computing servers that host the data. Such constraints are especially relevant to applied ecology because conservation-dependent terrestrial species are only sometimes well-suited to intensive study. Thus, massive amounts of accelerometry data from griffon vultures in Europe and the Middle East can be sent over VHF systems, in part because these birds are colonial and regularly return to a set of nest cliffs (Nathan et al.,
In certain areas the use of mobile phone telemetry can greatly expand the volume and speed of data transfer from bio-logging devices to scientists. That said, even 4G and LTE systems often are insufficient to transfer the large quantities of data collected at many measurements per second. This is likely why wildlife accelerometry that uses GSM systems is, to date, largely experimental (Yuan et al.,
The constraints we highlight here are all influential for movement ecology in general, and not exclusively for solving conservation problems. In fact, the early research into animal movement was more strongly influenced by these constraints than is modern movement ecology, yet it was still highly applied. Similarly, rapid advances have been made linking movement ecology and conservation management in the marine environment, despite greater data constraints than in terrestrial settings.
Since these constraints didn't influence historical or marine studies, it is therefore not easy to understand why the constraints we identify in literature may limit applied relevance of movement ecology to terrestrial conservation management. One possible explanation is that, in the subset of marine ecological and early animal movement studies that are relevant to conservation, measurements are collected and models built at relatively large spatial and temporal scales (e.g., hours and kilometers, see
Our review highlights the fact that principles of movement ecology are sometimes used to solve specific conservation problems. However, there is immense potential for expansion in this regard and that potential is starting to be realized, as illustrated by the increase in papers in this area in the past 2 years. There are constraints that may limit the continued expansion in this area. Some of these constraints include those highlighted by others, such as the availability of data or results, improved dialogue between scientists and practitioners, and development of frameworks for incorporating movement ecology into conservation (Fraser et al.,
The concept for this manuscript was developed as a result of discussions between the two authors. TK led writing. Both authors participated in revising and editing the document.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The authors thank V. Braunisch, A. Duerr, T. Miller, and S. Poessel for insightful comments on drafts of the manuscript. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
The Supplementary Material for this article can be found online at: