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VOLUME 12, ISSUE 1, ARTICLE 8
Taylor, P. D., T. L. Crewe, S. A. Mackenzie, D. Lepage, Y. Aubry, Z. Crysler, G. Finney, C. M. Francis, C. G. Guglielmo, D. J. Hamilton, R. L.
Holberton, P. H. Loring, G. W. Mitchell, D. Norris, J. Paquet, R. A. Ronconi, J. Smetzer, P. A. Smith, L. J. Welch, and B. K. Woodworth. 2017. The
Motus Wildlife Tracking System: a collaborative research network to enhance the understanding of wildlife movement. Avian Conservation and
Ecology 12(1):8. https://doi.org/10.5751/ACE-00953-120108
Copyright © 2017 by the author(s). Published here under license by the Resilience Alliance.
Methodology
The Motus Wildlife Tracking System: a collaborative research network
to enhance the understanding of wildlife movement
Philip D. Taylor 1,2, Tara L. Crewe 2,3, Stuart A. Mackenzie 2, Denis Lepage 2, Yves Aubry 4, Zoe Crysler 1,2, George Finney 2, Charles M.
Francis 5, Christopher G. Guglielmo 6, Diana J. Hamilton 7, Rebecca L. Holberton 8, Pamela H. Loring 9,10, Greg W. Mitchell 11, D. Ryan
Norris 12, Julie Paquet 13, Robert A. Ronconi 1,14, Jennifer R. Smetzer 9, Paul A. Smith 11, Linda J. Welch 15 and Bradley K. Woodworth
1,12
1Biology Department, Acadia University, Wolfville, Nova Scotia, Canada, 2Bird Studies Canada, Port Rowan, Ontario, Canada,
3Department of Biology, University of Western Ontario, London, Ontario, Canada, 4Canadian Wildlife Service, Environment and
Climate Change Canada, Quebec, Quebec, Canada, 5Canadian Wildlife Service, Environment and Climate Change Canada, Ottawa,
Ontario, Canada, 6Department of Biology, Advanced Facility for Avian Research, University of Western Ontario, London, Ontario,
Canada, 7Department of Biology, Mount Allison University, Sackville, New Brunswick, Canada, 8Lab of Avian Biology, University
of Maine, Orono, Maine, USA, 9Department of Environmental Conservation, University of Massachusetts Amherst,
Massachusetts, USA, 10United States Fish and Wildlife Service, Division of Migratory Birds, Northeast Region, Hadley,
Massachusetts, USA, 11Wildlife Research Division, Environment and Climate Change Canada, Ottawa, Ontario, Canada,
12Department of Integrative Biology, University of Guelph, Guelph, Ontario, Canada, 13Canadian Wildlife Service, Environment
and Climate Change Canada, Sackville, New Brunswick, Canada, 14Canadian Wildlife Service, Environment and Climate Change
Canada, Dartmouth, Nova Scotia, Canada, 15United States Fish and Wildlife Service, Maine Coastal Islands NWR, Milbridge,
Maine
ABSTRACT. We describe a new collaborative network, the Motus Wildlife Tracking System (Motus; https://motus.org), which is an
international network of researchers using coordinated automated radio-telemetry arrays to study movements of small flying organisms
including birds, bats, and insects, at local, regional, and hemispheric scales. Radio-telemetry has been a cornerstone of tracking studies
for over 50 years, and because of current limitations of geographic positioning systems (GPS) and satellite transmitters, has remained
the primary means to track movements of small animals with high temporal and spatial precision. Automated receivers, along with
recent miniaturization and digital coding of tags, have further improved the utility of radio-telemetry by allowing many individuals to
be tracked continuously and simultaneously across broad landscapes. Motus is novel among automated arrays in that collaborators
employ a single radio frequency across receiving stations over a broad geographic scale, allowing individuals to be detected at sites
maintained by others. Motus also coordinates, disseminates, and archives detections and associated metadata in a central repository.
Combined with the ability to track many individuals simultaneously, Motus has expanded the scope and spatial scale of research
questions that can be addressed using radio-telemetry from local to regional and even hemispheric scales. Since its inception in 2012,
more than 9000 individuals of over 87 species of birds, bats, and insects have been tracked, resulting in more than 250 million detections.
This rich and comprehensive dataset includes detections of individuals during all phases of the annual cycle (breeding, migration, and
nonbreeding), and at a variety of spatial scales, resulting in novel insights into the movement behavior of small flying animals. The
value of the Motus network will grow as spatial coverage of stations and number of partners and collaborators increases. With continued
expansion and support, Motus can provide a framework for global collaboration, and a coordinated approach to solving some of the
most complex problems in movement biology and ecology.
Le Système de suivi de la faune Motus : un réseau de recherche collaboratif visant à mieux comprendre
le déplacement des animaux
RÉSUMÉ. Le Système de suivi de la faune Motus (Motus; https://motus.org), un nouveau réseau collaboratif de chercheurs
internationaux, repose sur un ensemble coordonné de stations automatisées de radiotélémétrie pour étudier le déplacement de petits
organismes volant, comme les oiseaux, les chauves-souris et les insectes, aux échelles locales et régionales, et à celle de l'hémisphère.
Pierre angulaire pour les études de suivi depuis plus de 50 ans, la radiotélémétrie est encore le principal moyen de suivre le déplacement
de petits animaux avec une grande précision temporelle et spatiale, en raison des limites que présentent les émetteurs basés sur le système
de positionnement géographique (GPS) ou satellite. Des stations réceptrices automatisées, de pair avec la récente miniaturisation et le
codage digital des émetteurs, sont derrière l'utilité accrue de la radiotélémétrie, qui permet désormais de suivre constamment et
simultanément de nombreux individus sur de vastes territoires. Parmi les dispositifs automatisés, Motus est novateur car il permet aux
collaborateurs l'emploi d'une fréquence radio unique pour toutes les stations réceptrices installées sur le vaste territoire, chacun des
Address of Correspondent: Tara L. Crewe, 115 Front Road, Po Box 160, Port Rowan, ON , Canada, N0E 1M0, tcrewe@birdscanada.org
Avian Conservation and Ecology 12(1): 8
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individus suivis pouvant être détectés à des sites entretenus par d'autres collaborateurs. Motus coordonnent, disséminent et archivent
aussi les détections et les métadonnées associées dans un site central de stockage. Grâce à sa capacité de suivre un grand nombre
d'individus simultanément, Motus a permis d'étendre la portée et l'échelle spatiale des questions scientifiques pouvant être résolues au
moyen de la radiotélémétrie, de l'échelle locale à régionale, et même à celle de l'hémisphère. Depuis sa création en 2012, plus de 9000
individus appartenant à de plus de 87 espèces d'oiseaux, de chauves-souris et d'insectes ont été suivis, fournissant plus de 250 millions
de détections. Ce jeu de données, riche et détaillé, comprend des détections d'individus à toutes les étapes du cycle annuel (nidification,
migration et hors nidification) et à une variété d'échelles spatiales, menant à des découvertes sur le comportement de déplacement de
petits animaux volant. Le réseau Motus prendra encore plus de valeur au fur et à mesure que la couverture spatiale des stations et le
nombre de partenaires et de collaborateurs augmenteront. En raison de l'expansion et de l'appui continu reçu, Motus peut fournir un
cadre de travail pour la collaboration globale et une approche coordonnée dans la résolution de quelques-uns des problèmes les plus
complexes en biologie et écologie du déplacement.
Key Words: automated radio-telemetry; behavior; full life-cycle biology; migration; migratory connectivity; movement biology; movement
ecology; stopover
TRACKING WILDLIFE MOVEMENT
Declines in populations of many species of birds, bats, and insects
have emphasized the need for an improved understanding of the
factors that limit and regulate populations, particularly in the face
of a rapidly changing landscape and climate. For migratory
species, a key element to identifying limiting factors and planning
conservation is understanding their movement patterns, including
migratory connectivity—the links between habitat used at
different times of year, including breeding territories, migratory
stopover sites, and wintering areas (Marra et al. 2011). Advances
in tracking technologies continue to allow researchers to track
smaller animals with greater temporal and geographic precision
than ever before, which is revolutionizing our understanding of
the movements of organisms and the factors that influence
movement and survival during all phases of their life cycle (Fraser
et al. 2012, Kays et al. 2015).
Many limitations and trade-offs still exist in the use of current
tracking technologies, particularly for small animals (< 50 g),
which comprise the vast majority of biodiversity (Bridge et al.
2011, Kays et al. 2015). Long-distance movements have generally
been tracked with either satellite tags or with various types of
data loggers. The smallest tags currently available that can be
detected by satellite, using Geographic Positioning System (GPS)
to determine locations, still weigh 3.5 g, which is too heavy for
most animals < 100 g. Data loggers including GPS provide
accurate position estimates (± 30 m or better) and have been used
to track individuals throughout their entire annual cycle, delineate
migratory connectivity, and estimate home range centers on
breeding and wintering grounds (Hallworth and Marra 2015).
However, because of power needs, temporal resolution must be
compromised to extend battery life, and the mass of the smallest
units is near 1 g, too large to place on most small animals. Data
loggers using light-level geolocators (GLS) can weigh as little as
0.3 g and have provided much novel information on migratory
connectivity for small songbirds and shorebirds, but such devices
have relatively low location accuracy (at best ± 50–100 km)
particularly near the equinox when many temperate species
migrate (Fudickar et al. 2012, McKinnon et al. 2013,
Rakhimberdiev et al. 2016), or in polar environments where there
is continuous light or darkness. Individuals carrying either of
these types of tags also need to be recaptured to retrieve location
data, which limits their use to species with high breeding or
wintering site fidelity. Importantly, only surviving and returning
individuals can be recaptured for data retrieval and this is a
problematic bias for studies of movement ecology.
Radio-telemetry has been used to track wildlife movements for
over 50 years (Adams 1965, Cochran et al. 1965). For many small
organisms, e.g., small reptiles, amphibians, insects, bats and birds,
radio-telemetry remains a viable method to track local and
regional movements with a high degree of temporal and spatial
precision, without the need to recapture individuals or remotely
download data from tags (Cagnacci et al. 2010, Bridge et al. 2011,
Kays et al. 2015). Tags can be very small and light (< 0.21 g), and
pulse frequency (typically 2–10 times per minute) provides high
temporal accuracy, which is useful for categorizing behavioral
states (movement, resting, flights). However, in traditional radio-
telemetry, the need to manually detect tagged animals, either by
foot, car, or plane, requires a large amount of effort by field
personnel, placing limits on the number of individuals that can
be tracked, the number and time span of detections that can be
collected (field staff cannot monitor continuously, 24 hours a
day), and on the spatial scale that can be sampled. Human
presence while tracking can also alter the natural behavior of the
tracked animal. This results in limited and potentially biased
information on the activity and movement patterns of individuals
and populations.
Recent advances in miniaturization of electronics and computers
have led to broader use of automated radio-telemetry systems
(Cochran et al. 1965), which enable the continuous recording of
tag signals from fixed position or mobile receivers and at times of
the day or in weather conditions that otherwise limit traditional
radio telemetry projects. Automated radio-telemetry systems such
as the Automated Radio Telemetry System (ARTS; Kays et al.
2011), the Biological AutomAted RAdiotelemetry System
(BAARA; Řeřucha et al. 2015), the Advanced Tracking and
Localization of Animals in real-life Systems (http://move-ecol-
minerva.huji.ac.il), and the Quail Ridge Automated Animal
Tracking System (http://qraat.ucdavis.edu) are typically
employed at local (Goymann et al. 2010, Ward et al. 2014, Louder
et al. 2015) or regional spatial scales (Mills et al. 2011, Taylor et
al. 2011, Deppe et al. 2015). These can provide moderately
accurate positional data (± ~1–15 km), limited primarily by the
situation of receiving stations and the strength of the signal
emitted by the tag. In cases where tagged animals are easily
approached, supplementary hand-held radio tracking can allow
for position accuracy of < 5 m.
Avian Conservation and Ecology 12(1): 8
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Fig. 1. Locations of Motus receiving stations in the Western Hemisphere between 2014 and 2016.
Stations deployed in Europe are not shown. Permanent (active through most of the year) stations
are shown by open circles, while stations that were set up temporarily for research-specific needs
are shown by ×. Insets show the location of towers in the grid array in Ontario (A), and the
turnstile or "fence" style of array along the coast of northeastern North America (B), which has
been used to detect tagged migrants as they depart over the ocean during migration, coming onto
land after a flight, or flying down the coast.
We introduce the Motus Wildlife Tracking System (hereafter
“Motus”; https://motus.org), a continental scale tracking
network. Initially inspired by the Ocean Tracking Network (http://
oceantrackingnetwork.org), Motus is unique among the
automated radio telemetry systems described above in that it
functions as a network of collaborating researchers and
organizations managing independent arrays of receiving towers
over a relatively large spatial extent. All data is processed through
a centralized database, and digitally coded tags allow many
thousands of individuals to be tracked simultaneously on a single
frequency, which allows detection of tags by any receiver in the
network. Because receivers are listening continuously on a single
frequency (as opposed to cycling through many possible
frequencies), the probability of detecting any given tag in the
vicinity of a receiver is vastly improved over traditional,
nonautomated methods.
The conceptual framework behind Motus expands the scope and
spatial scale of research and conservation questions that can be
addressed compared to traditional radio-telemetry and other
tracking technologies, particularly for small animals that cannot
currently be tracked using GPS loggers, or for studies that require
high temporal resolution. In this paper, we describe the physical
and database infrastructure behind Motus, summarize novel
advancements that have been made in movement ecology as a
result of this effort, and discuss potential future applications in
light of the expected continued growth of the network and rapid
advances in technology.
THE MOTUS NETWORK
Motus has its roots in an automated radio-telemetry network
developed at Acadia University and implemented at a regional
scale with numerous partners in northeastern North America in
2012–2013. This network was inspired by development of the
relatively low-cost Sensorgnome receiver (https://sensorgnome.
org), described below. In 2014, with funding and support from a
Canadian Foundation for Innovation grant, Motus was
Avian Conservation and Ecology 12(1): 8
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developed as a program of Bird Studies Canada, in partnership
with Acadia University, Western University, the University of
Guelph, and other collaborating researchers and organizations.
By the end of 2016, Motus had expanded to include more than
120 independent research projects, and comprised over 325 active
receiver stations across 11 countries and 3 continents (Fig. 1). We
anticipate it will continue to expand.
Tags (transmitting device)
To date, most tags used in the Motus system have been coded
“nanotags” manufactured by Lotek Wireless (Newmarket,
Ontario: http://lotek.com). These tags range in mass from ~0.2 to
2.6 g and have an estimated lifespan of between 10 days and 3
years, depending on battery size (smaller batteries have shorter
lifespans) and how often the radio transmission is emitted. When
activated, each tag emits a very rapid series of radio transmissions
(pulses) with a coded sequence, repeated at fixed intervals (burst
rate). The combination of sequence code and burst rate is used
to uniquely identify individual tags. More rapid burst rates result
in higher power consumption and shorter lifespans, but also
increase detection and recognition probabilities. This means that
researchers must choose burst rates and tag sizes, trading off the
length of time an animal is tracked with temporal resolution, and
therefore detectability.
Motus can also accommodate other types of tags, provided they
operate on the same frequency. This can be useful for projects in
which the primary goal is not necessarily spatial tracking, for
example measuring temperature variation in sedentary animals
(McGuire et al. 2012, 2014). The use of noncoded tags in the
broader Motus network is somewhat limited because only a small
number of such tags can be uniquely defined for any given
frequency (by changing the timing between or length of pulses).
In principle, any tag that uses some form of “on-off” radio pattern
can be employed within Motus. However, where signal
characteristics overlap across individuals, they cannot be uniquely
identified and this can complicate tracking of movements over
large spatial scales.
Prior to tag deployment, researchers “register” tags with Motus
by submitting a recording of the tag signal, obtained using a
compatible receiver. Recordings allow for a measure of the pattern
of the coded signal (to 1 ms), the exact burst rate, and other signal
characteristics from which a unique ID is derived. This ensures
that a record of specific tag characteristics is stored in the
database, and that no conflicts exist with other tags in the system.
Current compatible tags use pulse-width modulated codes that
accommodate over 500 unique coded IDs. Linking codes with
unique burst rates (prime numbers at 0.1 s) allows for tens of
thousands of uniquely coded tags within the array at any one
time, all transmitting on the same frequency. Having all tags
transmitting on a single frequency eliminates the need for receivers
to “listen” sequentially on multiple frequencies, which decreases
the probability of detecting tags on any given frequency.
Once registered, tags are activated by the user and affixed to
animals using glue, sutures, or a variety of harness designs (e.g.,
Rappole and Tipton 1991, Warnock and Warnock 1993, Hill et
al. 1999, Naef-Daenzer 2007, Streby et al. 2015). Prior to
deployment, additional information is collected about the animal
(e.g., species, weight and other morphometric measurements, age,
sex, presence of other identifying tags such as numbered bands)
and submitted to the Motus database. Once activated, tags can
be detected by any station throughout the network that is
monitoring the appropriate frequency.
Receiver stations
A receiver station comprises a power source, a receiver, and one
or more antennas tuned to a specific frequency (currently 166.380
MHz in the Western Hemisphere, and 150.100 MHz in Europe).
Compatible receivers currently include Sensorgnome receivers, a
relatively low cost receiver that can be built using open-source
software and off-the-shelf hardware, or Lotek SRX/DX series
receivers. Most receivers are equipped with a high-accuracy GPS
sensor that allows for precise time synchronization and
geolocation of the receiver. The total costs for a receiver station
varies depending on the number and type of antennas, whether
existing infrastructure can be used to mount antennas, and the
power source. Information about receiver deployments, including
geographic coordinates, start and anticipated end date and time,
and antenna configuration and orientation, is registered in the
Motus database, and made available to all users.
Receivers can accommodate multiple antennas, which are
mounted on nearby structures or self-standing towers. Anywhere
from one to six antennas are typically mounted at a single station.
Sensorgnome receivers monitor each antenna continuously using
software-defined antenna-specific radio receivers, whereas Lotek
receivers use an antenna switchbox to cycle sequentially among
antennas based on user-defined criteria, which will decrease the
probability of detecting a tag on a given antenna. For close-range
tracking of individuals, short- to medium-range antennas with a
broad beam, such as small omni-directional antennas (360°
detection radius with a range of up to ~500 m) or 3–5 element
Yagi antennas (detection range 2–3 km) tend to be more
appropriate. For longer-range detection (> 3 km), directional 9-
element Yagi antennas are more useful. Tagged individuals are
regularly detected simultaneously by sensorgnome receivers
greater than 20 km apart using 9-element Yagi antennas, which
gives some indication of the normal range of the antenna (~15
km). Long-distance detections are most likely when birds are in
flight, well above the ground, and in line of sight of the antenna,
although many factors influence detection distance, including
height and orientation of transmitting and receiving antennas,
and landscape features including topography, habitat structure,
and human-made structures. Interference created by
electromagnetic disturbance such as transmitting cellular or other
antenna (common in urban areas), or at times of the day when
people (and electronic devices) are more active, may also decrease
the effective detection distance of a station. Stations are placed
to minimize this interference.
Stations can be connected directly to a main power source (which
reduces cost and maintenance), or run from solar-powered deep
cycle batteries. Sensorgnome receivers allow for a direct
connection to the internet via Ethernet or cellular phone network,
which can provide real-time data transfer to the Motus database.
Data from unconnected stations need to be downloaded manually
from the receiver. In both cases, data are stored locally until
deleted by a user, for security. Motus encourages station managers
to maintain active receivers year-round, although some project-
specific stations are activated over shorter time periods (see
https://motus.org for additional information on station setup).
Avian Conservation and Ecology 12(1): 8
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Network configuration
Because of the collaborative nature of Motus, the placement and
maintenance of receivers throughout the network is driven
primarily by the independent goals of collaborators. A map of
receiver stations active at any point in time is available at https://
motus.org. Although some of the expansion to date has been ad-
hoc, Bird Studies Canada and other organizations are leading a
coordinated effort to guide the placement of new stations and fill
spatial gaps to maximize Motus users’ ability to address broad-
scale research and conservation goals.
The configuration of project-specific arrays will depend on
research goals. A single strategically placed station at a breeding
or stopover site might be sufficient on its own to gather
information on activity level, including diel activity, stopover
duration, and arrival or departure timing of individuals within
detection range. Strategic grids of stations are the most commonly
used configuration by Motus collaborators. Grids with closely
spaced stations are useful to detect local movements and activity
levels, and grids with more distant stations are useful to detect
movements across broader landscapes (Fig. 1, inset A). Turnstile
or fence arrays consist of stations deployed in a line to detect
migrants as they move past in latitude or longitude. These have
proven effective for detecting migrants as they move past
geographic funnels or bottlenecks, including the Gulf of Mexico
coast, Gulf of Maine coast, the lower Great Lakes, and the
Panama Canal (Fig. 1, inset B). Point-to-point arrays, with
receivers or groups of receivers at well-known breeding,
wintering, and stopover areas, are also useful for detecting
migratory movements between specific geographic locations.
These have proven very effective for shorebirds that stage over a
discrete series of known geographic locations. For any species,
the use of closely-spaced grids allows activity levels (e.g., stopover
duration, departure timing, diel activity) and local- and broad-
scale movement parameters (e.g., migratory speed, timing,
orientation) to be estimated. Transient receivers on moving/
floating platforms can capture movements of birds at sea (Crysler
2015, Loring 2016; Ronconi, Taylor, Crysler, et al., unpublished
manuscript).
Data flow
Motus relies on a centralized database housed at Bird Studies
Canada’s national data center. All tag, station, project, and user
metadata are submitted by users, archived in the database, and
linked and managed through the Motus research platform (Fig.
2). All tag detection data collected at receiving stations are joined
with the master tag and station metadata to produce a complete
database of unique detections from each station. Station
performance such as on/off cycles of receivers, GPS, or antenna
are also compiled and summarized.
To detect tags, radio signals captured by the receivers are
compared against the tag recordings submitted to Motus during
tag registration. Minimal processing of raw detection data occurs
prior to making data accessible to researchers (primarily
removing detections that are outside of the deployment period
for a specific tag). Once processed, the principal investigator(s)
of each project can access a master project file that contains raw
detection data including signal strength values, standard
deviation in signal strength, and run length (number of
continuous detections of a unique code by a receiver). Users are
provided with all data necessary to run additional data filters, for
example to look for false-positive detections, and to assess activity
levels of birds based on variability in signal strength values over
time. Metadata, e.g., geographic location and antenna
orientation, are provided for all stations where a given tag was
detected. The archiving of all movement data in this way facilitates
retrospective, cross-project analyses. Motus encourages such data
sharing to support broad research and conservation objectives,
but principal investigators maintain control over detections of
their tags, and can establish a data sharing level that controls the
availability of detailed detection and associated metadata to third
parties.
Fig. 2. Conceptual diagram of the flow of information and data
through the Motus network. Researchers tag animals, which
then have the potential to generate detection data throughout
the array. Data are fed into the Motus database, and the web
interface provides users with tools to access, summarize, and
visualize their data, or the potential to access additional tools
through alternative data portals such as Movebank and the
Avian Knowledge Network. The interpretation of detection
data can contribute to conservation science, policy, and
management, and to public engagement and education.
CURRENT USES
Since its inception in 2012, Motus collaborators have undertaken
over 120 research projects, and tracked over 9000 individuals of
87 species across 9 avian orders (Procellariiformes, Falconiformes,
Gruiformes, Charadriiformes, Cuculiformes, Strigiformes,
Caprimulgiformes, Piciformes, and Passeriformes) comprising 25
avian families. Motus users have also tracked 9 species of
insectivorous bats (family Vespertilionidae), and two families of
large insects (Aeshnidae and Nymphalidae). Many of these
projects would not have been possible with existing alternative
tracking technologies, either because they did not offer sufficient
temporal or spatial precision, the animals could not be
recaptured, or the animals were too small to support larger tags.
Projects to date have logged over 250 million detections at over
560 receiving stations (Fig. 1) and, for many projects, a large
Avian Conservation and Ecology 12(1): 8
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portion of tagged animals (sometimes exceeding 80%) are
detected at stations beyond the original tagging site. This wealth
of data has led to comprehensive and diverse applications in the
study of breeding and postbreeding dispersal, stopover and
migration behavior, and overwintering ecology. For example,
detection data from Motus collaborators have been used to
estimate stopover duration (Dossman et al. 2016, Mann et al.
2017, Neima 2017), activity level, e.g., onset of diel activity,
stopover versus active migration (Crysler et al. 2016; Morbey et
al., unpublished data), regional and site fidelity during migratory
stopover (Mann et al. 2017, Neima 2017), precise departure and
arrival times (Mitchell et al. 2015, Dossman et al. 2016, Müller
et al. 2016), departure and flight orientation (Mitchell et al. 2015,
Crysler et al. 2016, Kishkinev et al. 2016, Neima 2017), flight
distance, time, and therefore flight speed (Woodworth et al. 2014,
2015, Brown and Taylor 2015, Mitchell et al. 2015, Crysler et al.
2016, Falconer et al. 2016), colony attendance patterns (Loring
2016), and types of movements, e.g., migratory, relocation
(Woodworth et al. 2014, 2015, Crysler et al. 2016).
The ability to estimate these parameters has led to advancements
in our understanding of the movement behavior of small animals,
including the spatial and temporal scale of migratory stopover
(Woodworth et al. 2015, Mann et al. 2017, Neima 2017), the
influence of ecological barriers on movement behaviour
(Woodworth et al. 2015, Crysler 2016, Dossman et al. 2016),
postfledging dispersal movements (Brown and Taylor 2015,
Crysler 2015), migratory connectivity (McKellar et al. 2015), the
proximate mechanisms of orientation and navigation (Kishkinev
et al. 2016), and effects of availability of roosting habitat on
duration of stay (Mann et al. 2017). We have also gained
understanding of how movements are influenced by intrinsic and
extrinsic factors, including age (Brown and Taylor 2015, Mitchell
et al. 2015, Crysler et al. 2016, Dossman et al. 2016, Kennedy et
al. 2016), sex (Falconer et al. 2016), physiological condition
(Dossman et al. 2016, Eikenaar et al. 2017), habitat (Woodworth
et al. 2014), and weather (Mitchell et al. 2015, Dossman et al.
2016, Loring 2016, Neima 2017).
Motus is also providing collaborators with an opportunity to
combine detection data from stations deployed internationally
across a vast geographic area. Although many gaps in station
coverage still exist, tagged individuals nevertheless have the
potential to be detected over local, regional, and hemispheric
spatial scales, and during all parts of their life cycle. One example
is from a project tagging Swainson’s Thrushes (Catharus ustulatus)
and Gray-cheeked Thrushes (Catharus minimus) in the Andes and
Sierra Nevada Mountains of Colombia in 2015 and 2016.
Collaborative projects of Selva-Research for Conservation in the
Neotropics, Environment and Climate Change Canada,
Universidad de los Andes, University of Saskatchewan, Western
University, University of Guelph, and Bird Studies Canada, have
been examining local overwintering ecology (Andes), stopover
behavior, and departure decisions (Sierra Nevada) of these species
(Fig. 3; Gonzalez and Hobson, unpublished data). Battery life of
the tags was between 180 to 320 days, which, in addition to
providing local information on daily activity levels, stopover
duration, and departure timing, also resulted in the opportunistic
detection of many tagged individuals at northern stations while
en-route to their breeding grounds, including by the turnstile
“fences” in Indiana and along the Gulf of Mexico coast (Fig. 4).
These additional detections provided novel information on the
exact time of passage past precise locations along their (previously
unknown) migratory route (Fig. 5), and the first measurements
of migratory speeds for these species over a broad spatial scale.
This example demonstrates the potential of the Motus
collaborative network to monitor local, regional, continental, and
hemispheric scale movements, and argues strongly for its
continued and strategic expansion to fill spatial gaps in coverage,
particularly at key natural barriers that can funnel migrant
passage.
Fig. 3. Raw signal strength (dB) data for a radio-tagged
Swainson’s Thrush (Catharus ustulatus) detected on three
antennas (A.1, oriented 270°; A.2, oriented 150°; and A.3,
oriented 0°) on a Motus station deployed in the Andes,
Colombia in 2016 (Figure 4, site A; Gonzalez and Hobson,
unpublished data). After it was tagged on 16 March, this
individual remained at the overwintering site until its departure
on 29 April 2016. Patterns in signal strength variation during
overwintering suggest greater activity levels during the day
(higher variation), and reduced activity at night (lower
variation; left panels). The right panels show signal strength
data immediately before and during departure on 29 April,
which shows a period of inactivity followed by departure from
the site at approximately 23:40 (GMT).
CHALLENGES, OPPORTUNITIES AND FUTURE
DIRECTIONS
Data collected by Motus are filling important knowledge gaps
about the movement, biology, and ecology of small migrants at
a variety of spatial and temporal scales, while promoting
international collaborative research. In particular, Motus excels
in applications where continuous detections with high temporal
resolution is important, e.g., estimation of flight speeds, fine-scale
behavior, or timing of movements, and where an archival tag like
a GPS or GLS introduces problematic biases, e.g., one cannot
study survival during migration by recapturing only living birds.
Complementary to other technologies including stable isotope
analyses, archival GPS/GLS, satellite tags, and data loggers,
Motus has the potential to play an important role in
understanding migratory connectivity and the factors influencing
movement and survival throughout the annual life cycle for a wide
variety of species.
Since its inception, the spatial expansion of Motus has been
fuelled by the dedication, resources, and interest of collaborating
Avian Conservation and Ecology 12(1): 8
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Fig. 4. Twelve (A-L) Motus stations on which a Swainson’s
Thrush (Catharus ustulatus), tagged on 16 March 2016 as part
of an overwintering study in Colombia, was detected during
spring migration (closed red circles; Gonzalez and Hobson,
unpublished data). Black circles show the location of Motus
stations that were active between 29 April and 31 May 2016, i.
e., between the time this individual left its overwintering site
(Fig. 3) and passed by the most northern site (L). Red broken
lines depict the great circle path between sites, and may not
accurately represent the migratory path of this individual. In
addition to giving some indication of migratory connectivity,
detections collected at sites A-L can provide information on
stopover duration, time of departure, time of passage past each
site (Figs. 3, 5), and thus derived metrics including ground
speed.
individuals and organizations, interest that has grown largely out
of the ability to garner novel movement data for small animals at
a spatial and temporal scale that was previously only possible for
larger animals. Given the current state of communications and
agreements with collaborators, we expect the number of
permanent stations to continue to increase, and cover a broader
geographic scale. Although this ground-up approach to spatial
expansion is expected to remain a key organizing feature of
Motus, there is also a need to develop a
Fig. 5. Raw signal strength data for a radio-tagged Swainson’s
Thrush (Catharus ustulatus) detected at Motus stations C-H, I,
K, and L (Fig. 4) after departing on migration from its
overwintering site in Colombia on 29 April 2016 (Gonzalez and
Hobson, unpublished data). Clear parabolas in signal strength
values suggest the individual passed directly through
(perpendicular to) the antenna beam, whereas a more
consistent signal strength suggests the individual is flying in the
same direction as the antenna beam. Signal strength values are
not directly comparable between plots on the left and right
because data were collected using Lotek receivers on the left,
and using Sensorgnome receivers on the right.
top-down approach to the positioning of stations that will address
priority-based research and conservation objectives and fill
spatial gaps. Of note are plans to place towers at key migratory
bottlenecks, including the Gulf of Mexico coast, throughout the
Caribbean and Central America, and at strategic places in South
America and Europe. Investments from Motus partners and
funders will be required to deploy and maintain permanent
stations in priority locations that may not otherwise be covered.
Alternative approaches to expansion are also being explored,
including the development of home receiver kits that can be
purchased and installed by citizen scientists or local naturalist
groups at a low cost.
Inconsistent spatial coverage is currently one of the primary
factors limiting broad-scale animal movement questions that can
be addressed using Motus. Knowledge of migratory behavior
obtained from alternative technologies, including GPS, GLS,
isotope signatures, and band recoveries can, and is, being used to
inform priority areas for targeted Motus projects and subsequent
expansion. Likewise, Motus can also complement knowledge
obtained from lower resolution position data obtained from GLS,
stable isotopes, and band recoveries. For individuals large enough
to carry GPS tags, using both GPS and Motus technology
together can provide accurate position data with low temporal
resolution (GPS) throughout the annual life cycle, and less
accurate location data with higher temporal resolution (Motus)
in regions with receiving stations, e.g., in the Atlantic arrays (Fig.
1). Combined, these two technologies could provide a
comprehensive understanding of postbreeding dispersal and
Avian Conservation and Ecology 12(1): 8
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migratory routes (GPS and Motus), stopover durations and their
approximate locations (Motus), daily activity levels, timing of
departure from breeding locations, stopovers, and overwintering
locations (GPS and Motus), and for larger species, some data on
home-range size during breeding and overwintering periods
(GPS). At a smaller spatial scale, manual radio-telemetry can be
used in combination with Motus to determine precise locations
and to collect observations of animal behavior that could not be
derived from Motus data alone, e.g., habitat patch use, foraging
habitat and behavior, or prey preference.
Despite the benefits and broad utility of the Motus system, it is
important to recognize the limitations of this technology. First,
tag life is limiting for some sizes/species; for the smallest organisms
capable of carrying a tag (< 10 g), studies are currently limited to
a range of 10–90 days depending on the chosen burst rate. Also,
only signals that are transmitted within range of a station are
recorded, and that range can vary considerably because of
environmental and technical factors, some of which are not yet
clearly understood. For example, the nature of VHF signals is
such that animals in flight are more readily detected (and at much
greater ranges) than animals near ground or under the cover of
vegetation. More study is needed on the effect of these factors on
detectability, and how to incorporate this information into data
modeling. Plans are currently underway to double-tag homing
pigeons with GPS and coded tags, to estimate detection
parameters, including station range and probability of detection
when in range, and to assess how our inference of movement
parameters (migratory path, speed, and orientation of flight)
from Motus compares to reality.
When received, detection data have relatively low geographic
resolution compared to GPS technology, although still much
higher than GLS. Geographic resolution can be as low as the
theoretical range of an antenna, although simultaneous
detections on multiple antenna and stations, together with
information on signal strength, can allow for more precise
estimates of position. Nevertheless, imprecise position data are
sufficient to estimate relevant parameters, including diel activity
levels, departure timing, orientation, and flight speed.
Supplemental manual tracking can be used to produce much more
accurate position information for animals on the ground. Further
work is needed to determine the configuration and spacing of
towers and antennas that optimizes the accuracy and precision
of position estimates, and also to develop algorithms to estimate
position as accurately as possible through triangulation or other
modeling techniques.
There are also challenges associated with maintenance of the
receiver network. Automated stations can suffer from unplanned
outages due to insufficient power, electronic problems, or weather
and other unforeseen circumstances. Therefore, all stations
require some level of consistent oversight. Annual maintenance
costs need to be taken into consideration when establishing new
stations because stations need to be visited regularly to download
data and inspect the equipment; costs vary with frequency of visits
and remoteness of the station. It is important to emphasize,
though, that costs of maintaining the network are considered
minimal when compared with the costs of traditional radio-
telemetry, which include the cost of staffing field personnel and
the inability to collect continuous, high temporal resolution
detection data at large spatial scales. Current development of
cellular monitoring systems for Sensorgnomes will allow for
remote monitoring and control of stations, and our ultimate aim
is to fully automate as much of the system as possible.
The Motus database also relies heavily on the accuracy and
timeliness of user-provided tag and station metadata, and in turn
detection data. These are manageable issues, but do require
dedication and discipline from the user community to populate
the database with accurate and timely information. To facilitate
data providing and access, Motus’ central data repository is being
designed to alleviate many logistical challenges that researchers
may encounter when working with large datasets, including the
input, storage, management, and analysis of data (Urbano et al.
2010). In addition to basic visualizations that are publicly
available on the web, a user-friendly web-based interface and R
(http://r-project.org) package is being developed that will help
Motus users more efficiently manage, summarize and visualize
their data. We also anticipate that Motus users will be able to
connect their data to Movebank (http://movebank.org) to benefit
from their visualization and analysis tools. Combined, these
features will allow researchers to more efficiently publish their
research and maintain archival copies of their data for future use.
An added-value of the entire system is the collaborative research
network itself. With a growing network of collaborating
researchers and organizations, there is potential to use the Motus
network as ground-based receiving stations to collect data from
a variety of tracking technologies outside the current Motus
framework. Alternative receivers, or modifications to current
receivers, could theoretically be employed by Motus to collect
data from any remote-sensing device such as satellite, including
the International Cooperation for Animal Research Using Space
Initiative (ICARUS) (http://icarusinitiative.org), GPS, and data
logging tags with VHF or other means of transmitting data to
ground-based stations. Although GPS and satellite technologies
are advancing rapidly, there are financial and technical limitations
to decreasing the size of tags and to the amount of data that can
be stored and transmitted via satellite.
By utilizing a coordinated, collaborative, and international
approach to automated radio-telemetry, Motus has broadened
the spatial and temporal scale over which small animals can be
tracked. To use the Motus network effectively, study objectives
need to be clearly defined, and projects planned based on the
limitations and reasonable expectations of the technology,
including the current spatial configuration of receiving stations.
Given that we anticipate continued expansion of the receiver
network, the number and breadth of questions that can be
addressed using Motus should also expand. For example, with
more complete geographic coverage, including strategically
placed fences to capture latitudinal movement past migratory
bottlenecks, Motus could be used to track longer distance
migrations, and complete migrations between overwintering and
breeding grounds. Particularly for shorebirds with distinct
breeding, stopover, and overwintering sites, migration could
conceivably be monitored by receiver stations at each site. Such
data could eventually be used to estimate survival and transition
parameters during different periods of the life cycle, using
traditional mark-recapture methods. Greater spatial coverage will
also improve our ability to track short- and long-distance
Avian Conservation and Ecology 12(1): 8
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dispersal, providing information on survival, breeding success,
and, when combined with other demographic or abundance data
during stationary periods of the year, factors limiting populations
throughout the annual cycle. Given the rapid progress to date and
the flexibility of the system for both expansion and linkages with
other automated or airborne tracking technologies, we believe
that Motus is well positioned to play an important role in solving
some of the world’s most complex problems in movement ecology
well into the future.
Responses to this article can be read online at:
http://www.ace-eco.org/issues/responses.php/953
Acknowledgments:
Motus began as Sensorgnome.org through Acadia University and
is now a program of Bird Studies Canada (BSC) in partnership
with Acadia University and collaborating researchers and
organizations (see https://motus.org/data/partners.jsp). Motus is
indebted to the pioneering work and dedication of J. Brzustowski,
lead developer of the SensorGnome (https://sensorgnome.org/,
Acadia University). Motus is supported by BSC and collaborating
researchers and organizations, CANARIE, Inc., the Government of
Canada through Environment and Climate Change Canada and
Natural Resources Canada, the Crabtree Foundation, the W.
Garfield Weston Foundation, the Ontario Research Fund, the Nova
Scotia Research and Innovation Trust, and through the Canada
Foundation for Innovation in partnership with Western University,
Acadia University, and the University of Guelph. Substantial
financial and intellectual contributions to the development of Motus
have also been made by the United States Fish and Wildlife Service,
Bureau of Ocean Energy Management, Encana Corporation's Deep
Panuke Education & Training and Research & Development Fund,
Natural Sciences and Engineering Research Council of Canada
(NSERC) Collaborative Research and Development Grant to PDT,
Lotek Wireless, Mitacs, and TD Friends of the Environment
Foundation. Many additional individual research partners have
made significant contributions to Motus through their own research
programs and institutions. Motus would not be possible without the
participation of hundreds of landowners and volunteers who host
and maintain Motus stations. The writing of this manuscript was
supported by a Mitacs Accelerate grant to TLC, in partnership with
BSC, the University of Western Ontario, and Lotek Wireless, and
a NSERC Discovery Grant to PDT. Special thanks to the Colombia
thrush research group for use of their data, in particular A. M.
Gonzalez, K. Hobson, C. Gomez, and N. Bayly. We also thank the
collaborators operating stations used in the thrush example:
Mississippi State University (S. Rush, J. Fuera, and M. Woodrey),
Louisiana Department of Wildlife and Fisheries (M. Seymour),
and Université du Québec à Rimouski (M.P. Laplante). The
findings and conclusions in this article are those of the author(s)
and do not necessarily represent the views of the U.S. Fish and
Wildlife Service.
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Editor-in-Chief: Keith A.Hobson
Subject Editor: Scott Wilson