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*** 1. Movement ecology of small wild animals is often reliant on radio‐tracking methods due to the size and weight restrictions of available transmitters. In manual radio telemetry, large errors in spatial position and infrequent relocations prevent the effective analysis of small‐scale movement patterns and dynamic aspects of habitat selection. Automatic radio‐tracking systems present a potential solution for overcoming these drawbacks. However, existing systems use customized electronics and commercial software or exclusively record presence/absence data instead of triangulating the position of tagged individuals. *** 2. We present a low‐cost automatic radio‐tracking system built from consumer electronic devices that can locate the position of radio transmitters under field conditions. We provide information on the hardware components, describe mobile and stationary set‐up options, and offer open‐source software solutions. *** 3. We describe the workflow from hardware setup and antenna calibration, to recording and processing the data and present a proof of concept for forest‐dwelling bats using a mixed forest as study area. With an average bearing error of 6.8° and a linear error of 21 m within a distance ranging from 65 m to 190 m, the accuracy of our system exceeds that of both traditional methods as well as manual telemetry. *** 4. This affordable and easy‐to‐use automatic radio‐tracking system complements existing tools in movement ecology research by combining the advantages of lightweight and cost‐efficient radio telemetry with an automatic tracking set‐up. This article is protected by copyright. All rights reserved.
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Methods Ecol Evol. 2019;00:1–10.  
The analysis of animal movements based on tracking data enables
ecologists to investigate questions related to habitat and resource
utilization (Wyckof f, Sawyer, Albeke, Garman, & Kauffman, 2018),
migration and dispersal (Cagnacci, Boitani, Powell, & Boyce, 2010;
Walton, Samelius, Odden, & Willebrand, 2018) or to build predic-
tive models of animal behaviour (Browning et al., 2018). Recent im-
provement s in tracking technology have increased the number of
locations recorded per animal from a few dozen by manual radio te-
lemetr y to millions of movement steps from GPS tags and satellite
telemetry, leading Kays , Crofoot, Jetz, & Wikelski (2015) to proclaim
  Accepted:28August2 019
DOI : 10.1111 /20 41-210X.13294
Introduction of an automatic and open‐source radio‐tracking
system for small animals
Jannis Gottwald1| Ralf Zeidler2| Nicolas Friess1| Marvin Ludwig1|
Christoph Reudenbach1| Thomas Nauss1
1Faculty of Geography, Philipps-University
Marburg, Marburg, Germany
2Freies Ins titut für Datenanalyse – Di pl.-
Phys. Ralf Zeidler, Freiburg, Germany
Ralf Zeidler
Funding information
Ministry of the Environment, Climate
Protection and the Energ y Sector Baden-
Württemberg, Germany; Hessen State
Ministry for Higher Educ ation, Researc h and
the Ar ts, Germany
Handling Editor: Chris Sutherland
1. Movement ecology of small wild animals is often reliant on radio-tracking methods
due to the size and weight restrictions of available transmitters. In manual radio
telemetry, large errors in spatial position and infrequent relocations prevent the ef-
fective analysis of small-scale movement patterns and dynamic aspects of habitat
selection. Automatic radio-tracking systems present a potential solution for over-
coming these drawbacks. However, existing systems use customized electronics and
commercial software or exclusively record presence/absence data instead of trian-
gulating the position of tagged individuals.
2. We present a low-cost automatic radio-tracking system built from consumer elec-
tronic devices that can locate the position of radio transmitters under field condi-
tions. We provide information on the hardware components, describe mobile and
stationary set-up options, and offer open-source software solutions.
3. We describe the workflow from hardware setup and antenna calibration, to record-
ing and processing the data and present a proof of concept for forest-dwelling bats
using a mixed forest as study area. With an average bearing error of 6.8° and a
linear error of 21 m within a distance ranging from 65 m to 190 m, the accuracy of
our system exceeds that of both traditional methods as well as manual telemetry.
4. This affordable and easy-to-use automatic radio-tracking system complements
existing tools in movement ecology research by combining the advantages of
lightweight and cost-efficient radio telemetry with an automatic tracking set-up.
automatic radio-tracking, Marburg Open Forest, movement ecology, open-source, radio-
tracking, telemetry, triangulation
This is an op en access article under t he terms of the Creat ive Commons Attributio n License, which permits use, dist ribution and reproduc tion in any medium,
provide d the orig inal work is proper ly cited .
© 2019 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society
Methods in Ecology and Evoluon
a new golden age of animal tracking. To complement this more finely
resolved movement data, researchers have also developed a variety
of sophisticated analytical techniques such as path segmentation
analysis, step-selection functions and autocorrelated kernel meth-
ods (Fleming et al., 2015; Seidel, Dougherty, Carlson, & Getz, 2018).
Despite numerous advantages, both GPS tracking and satellite te-
lemetr y are still limited in their application to practical conservation
and ecological research. The cost of tags notwithstanding, size and
weight have limited their deployment in the past. New developments
have success fully reduced t he weight of such tag s to ~1 g (e.g. PinPoint
GPS tags, Lotek Wireless, Newmarket, CA). Nevertheless, bat tery
lifetime and recording frequency are inversely related to weight, so
the tags either record with low frequency or have short battery life-
times (e.g. 5 nights for a 4.2 g GPS tag with a 30 -s GPS-fixed sched-
ule; Roeleke, Teige, Hoffmeister, Klingler, & Voigt, 2016). Lightweight
GPS tags also need to be retrieved to access the data (Hallworth &
Marra, 2015), which either directly or indirectly increases most stud-
ies' expenditures in the form of lost material or data (Smith, Har t,
Mazzotti, Basille, & Romagosa, 2018; Tomkiewicz, Fuller, Kie, & Bates,
2010). These limitations aside, such tags are also too heav y for spe-
cies weighing less than 20 g, as their weight should not exceed 5% of
the individual's body mass to which it is attached (Brooks, Bonyongo,
& Harris, 2008). This leaves radio tags, with weights as low as 0.2 g,
as the single option for 5 0% of European passerines (Bau er, 2012) and
80% of European bats (Dietz, Nill, & Helversen, 2016).
Manual radio telemetry has disadvantages including labour in-
tensity, low temporal and spatial resolution (Montgomery, Roloff,
Ver Hoef, & Millspaugh, 2010; Thomas, Holland, & Minot, 2011),
infrequent and irregularly timed locations (Alexander & Maritz,
2015), small sample sizes (usually one frequency at a time; (Kays
et al., 2011)) and areal restrictions due to safet y concerns for field
workers (Smith et al., 2018). The qualit y of the resulting data also
precludes any advanced analytical techniques created for fine-scale
tracking data. Several working groups have designed automatic te-
lemetr y systems to overcome these drawbacks (Kays et al., 2011;
the key feature of modern automatic telemetr y systems is a contin-
uous signal record sent by radio tags using a st ationary automatic
receiver and a combination of either omnidirectional or directional
Yagi-Uda antennae. The former can detect presence and absence,
while the latter can detect the timing and direction of movement
(Crysler, Ronconi, & Taylor, 2016; Falconer, Mitchell, Taylor, &
Tozer, 2016). Existing systems use customized electronic devices
with proprietar y soft ware (Kays et al., 2011; Weiser et al., 2016)
BOX 1 Hardware overview
A Station with four antennae positioned in the cardinal directions and tuned to the regional frequency for wildlife telemetry (around
150.100 MHz in Germany)
B One RTL-SDR dongle per antenna (e.g. Nooelec NESDR SMart SDR, Nooelec, NY, USA) with a frequency range of 25–1,700 MHz and
a maximal sample rate of 2 MHz (quadrature sampling)
C Raspberry Pi 3B single-board computer (Farnell elements14, Leeds, UK) with the Raspbian operating system with a Docker-based
D High-capacity power supply with voltage regulation to work with the single-board computer, recommended for longer deployment
times. Battery time can be further increased through solar panels and a solar charge regulator.
E Power bank (20 Ah at 3.6 V ), able to supply a station for ~8 hr, recommended for mobile setups
F Mobile WiFi hot spot (Huawei E5330, Shenzhen, China), enables remote access within reach of the station's Raspberry Pi
Methods in Ecology and Evoluon
or monitor presence and absence in large-scale movement studies,
but cannot triangulate the position of a tagged individual (Taylor et
al., 2017). Here, we describe an automatic radio-tracking system
for locating individuals Zeidler, R. (2017) that has a high temporal
and spatial resolution and works with inexpensive consumer elec-
tronics, flexible antenna designs and user-friendly, open-source
software. In addition to a field test of system accuracy, we present
a proof of concept based on forest-dwelling bats that illustrates the
general use of the system under field conditions.
2.1 | Core system
The low-cost, automatic radio-tracking system (Box 1, A, B, C) con-
sists of three basic elements: (a) a receiver chip, (b) antennae and
(c) a single-board computer (e.g. Raspberry Pi). Common DVB-T tel-
evision receivers with RTL2832U chips process the radio signal (e.g.
Nooelec NESDR SMArt SDR, NooElec, NY USA). Inexpensive soft-
ware-defined radios (RTL-SDRs, Laufer, 2015) allow multiple radio
signals to be simultaneously recorded. The RTL-SDRs connect the
single-board computer with the Yagi-Uda antennae.
To calculate the source direction of incoming signals, the antenna
pole at a given station requires an array of at least three directional
antennae (and an equal number of receivers) together with informa-
tion about their orientation. The number of receivers that one com-
puter can monitor depends on the number of available USB ports.
At least two antenna setups with known coordinates must be
available and within the range of the radio source to triangulate the
tag's position. Each station should be connected to the Internet
to guarantee synchronized system times with e.g. a mobile Wi-Fi
hotspot carrying a SIM card (Box 1, F). The Network Time Protocol
synchronizes the station times when they are first operational and
approximately every 5 min thereafter.
The stations are operated using custom software. Operational
hardware settings on the receiving units can be done by remote
access in a user-friendly web-interface. This includes the setting of the
monitored frequency band, activation of receivers as well as settings
to reduce the recording of interference. Once the receivers are acti-
vated, they digitize incoming signals. An algorithm based on liquidSDR
(Gaeddert, 2016) automatically detects peaks in the radio signals along
with timestamps, the frequency relative to a user-defined mid-fre-
quency (Hz), signal bandwidth (Hz), duration of the signal (s) and signal
streng th (dB; For additional information see
2.2 | Transmitter specifications
The system suppor ts any type of radio tag common in wildlife radio te-
lemetr y. Individual tags are identified by their specific frequency. The
number of tags that can be simultaneously monitored depends on the
tag feat ures and the possi ble width of the fre quency band, a s constrained
by the CPU per formance (e.g. 250 kHz for the Raspberry Pi 3 Model B,
1 MHz for the Model A+). With highly stable tag frequencies, tags can
have frequencies as small as 1 kHz apar t. Pulse timing is irrelevant for
signal detection, which enables tags that transfer additional information
(e.g. body temperature by varying time intervals between pulses) to be
deployed. Tags are attached to the animal's skin, fur or feathers using
skin glue that dissolves after a certain time. Alternatively, tags can be
attached by e.g. harnesses and collars. Depending on the size of the tag,
they can be operational between a few days and several months.
2.3 | Principle of bearing calculation and
Signal amplification of a direc tional antenna depends on the angle
of the incoming electromagnetic wave. The relation between the
gain of a directional antenna and the angle of arrival can be approxi-
mated using a cosine func tion (Figure 1, Equation 1, Rabinovich &
Alexandrov, 2013), where g(ω) describes the gain or loss relative to
the angle ω in degrees compared to the gain of ω = 0°.
90 ×𝜔
FIGURE 1 Radiation pattern of
directional antennae
Methods in Ecology and Evoluon
In comparing two antennae of the same design, the absolute
gain in dB can be ignored because the values will be subtracted.
Assuming that the propagation path of the incoming electromag-
netic wave to the antenna is the same for both antennae (see also
calibration), the direction of arrival (ω) of the transmitter signal
is calculated by comparing the relative gains of two neighboring
antennae (Equations 2, 3, 4) with α describing the angle between
the antennae (Figure 2).
To calculate Δg in Equation 4, the dif ference in signal strength
between the two antennae (sl and sr) is normalized with the maxi-
mum signal strength difference Δm (Equation 5).
This can be derived by either simulating the gain pattern of the
antennae or a simple field experiment, in which the signal loss of the
antenna pointing directly at the tag (0°) is compared to the signal loss
of an antenna angled 90° relative to the tag.
Therefore, the direction of arrival is a function of the normal-
ized signal loss between the antennae and the angle bet ween those
The tag's position is approximated by finding the point of inter-
section of two lines produced by bearing calculations at two sepa-
rate stations. If more than two stations simultaneously receive the
signal, the centroid of the resulting polygon is calculated.
2.4 | Calibration
Recorded signals may dif fer in strength due to varying sensitivities
of the components (e.g. antennae, cables, plugs, receivers). Since the
90 ×𝜔
90 ×(𝜔𝛼)
with 𝛼=90
×arcos (Δg)with 𝛼=90
90 ))
FIGURE 2 Incoming signal (wavy line), angle ω in degrees
compared to ω = 0°, angle between antennae α
FIGURE 3 Calibration curves of
four HB9CV antennae arranged in an
array with 90° difference between
neighbouring antennae (Station 3–S3). A
radio tag was placed c. 115 m away and
the array was slowly turned on its vertical
Methods in Ecology and Evoluon
bearing calculation relies on an equal net gain at each receiving arm,
each arm must be calibrated. Calibration cur ves can be produced by
mounting a transmitter at a fixed distance to the station and rotating
the station around its vertical axis (Figure 3). Calculating the differ-
ence between each antenna's local maximum and the strongest local
maximum signal returns a correction value for each receiving arm.
Adding the correction value to the recorded signal strength adjusts
every antenna to the same maximum signal strength.
2.5 | Data processing
Different processing workflows were tested to identify relevant set-
tings and boundary conditions for obtaining optimal tracking results.
The bearing calculation requires that each receiving arm reliably
record the signal. An individual antenna may drop a signal when the
angle of the incoming electromagnetic wave strongly deviates from
the angle of possible maximum gain (ω = 0°). Furthermore, very small
or large intersection angles between bearings from two stations may
produce erroneous or no triangulations, if bearings run parallel.
We tested the effect of available antennae on the accuracy of
bearing calculations. The error of each bearing based on two, three
or four receiving antennae was assessed by the difference in the cal-
culated bearing and the angle between a station and the respective
test position.
To assess the influence of intersection angles between bear-
ings, we triangulated points and iteratively increased and decreased
the allowed minimum and maximum intersec tion angle by 10°,
respectively. For each set of triangulation points, we calculated the
position error, which is the mean dist ance bet ween the expected
and measured positions.
Data were processed using r version 3.6.0 (R Core Team, 2019).
The functions are publicly available as an r Shiny analysis tool (https
:// track ingeu/ logger_app) or an r package (https :// track ingeu/ radio track ingeu ).
2.6 | Accuracy study on an empty field
In Januar y 2019, we installed and tested this system on a bare field
free of vegetation to assess the its potential accuracy and evalu-
ate the data processing algorithm. The test setup comprised three
stations, each equipped with four directional antennae (HB9CV,
Telemetrie-Service Dessau) connected to RTL-SDR receivers
(Nooelec NESDR SMArt SDR, NooElec). The system was mounted
on 2.5 m tripods that were installed in an isosceles triangle forma-
tion with 200 m side length. The stations were calibrated against a
transmitter at a fixed distance of 115 m. After calibration, a sight-
ing compassed was used to position each station's antennae in the
cardinal directions. A regular, 50 m-wide test grid was constructed
between the stations and a 400 µW VHF radio-tag with a frequency
of 150.203 kHz and a pulse interval of 0.7 s mounted on a 2 m pole
was placed at each intersection of the test grid (Figure 4). The inter-
sections and the stations were localized with a dif ferential GPS. The
distance of the radio-tracking stations to the test positions ranged
from 65 m to 190 m.
FIGURE 4 Testing scheme. Radio-
tracking stations (S1–S3) were placed in
an isosceles triangle and a radio tag was
placed on each reference position for
2 min (M1–M6)
Methods in Ecology and Evoluon
2.7 | Usability study of forest‐dwelling bats in a
mixed forest area
Results from an ongoing study that is part of the LOEWE priority pro-
gram Nature 4.0 – Sensing Biodiversity are briefly presented and dis-
cussed to demonstrate the system's capability under field conditions.
In 2019, 15 tracking stations were installed in the Marburg Open
Forest, the open research and education forest of the University of
Marburg, to track bats and songbirds over each breeding season until
2022. Each station is equipp ed with an array of four HB9CV antennae
mounted on 9 m aluminium poles. The stations record movement and
body temperature data of tagged bats, which belong to one of four
forest-dwelling species (Nyctalus leisleri, Myotis daubentonii, Myotis be
chsteinii, Barbastella barbastellus). The temperature sensitive tags (V3,
Telemetrie-Service Dessau, 0.35 g) vary the time interval between
consecutive signals based on the individual's skin temperature.
Exemplary results of bat ac tivit y are shown for 26 June 2019.
The optimal settings as identified in the accuracy test study were
used to triangulate individuals' positions. In order to handle and tag
the bats, a special license was granted by the Nature Conservancy
Department of Central Hessen (‘Obere Naturschutzbehörde
Mittelhessen, Regierungspräsidium Gießen’, v54-19c 2015 h01).
Tags were attached to the skin between the scapula with skin adhe-
sive (Manfred Sauer GmbH, Lobbach Germany) and the weight of the
attached tags was always <5% of the tagged individual's body mass.
3.1 | Results of the accuracy study
Correction values obtained from local maxima in the calibration curves
ranged between 0.07 dB and 2.9 dB with the lowest and highest devia-
tions in maximum received signal s trength for st ations S3 and S2, resp ec-
tively ( Table 1). Thu s, calibrat ion had the stro ngest effec t on S2, improvin g
the bearing error from a median of 11.6° to 5.4° (Figure 5). Calibration
improved the median bearing accuracy by 2° across all stations.
Bearings calculated based on signals recorded by two antennae de-
viated from the real angle by 14.9° (median). Bearing error was reduced
to 6.8° when more than two antennae received a signal (Figure 6).
The position error decreased as the minimum and maximum
permissible intersection angles converged towards 90° (Figure 7).
Minimum and maximum angles of 40° and 140°, respectively, sub-
stantially improved results as well as sharply reducing the number
of triangulated point s. Placing additional limits on the intersection
angle steadily reduced the available data.
Positions were triangulated with calibrated signal strengths and a
minimum of three available antennae. Since a substantial number of
locations were lost due to restrictions to the intersection angle, we tri-
angulated positions with all intersection angles and with intersection
angles re stricted to 40 –140 °. Including a ll possible inters ection angles in
the tria ngulation process r esults in 673 locatio ns and a mean positio ning
error of 25 m. The triangulated points scatter in string-shaped patterns
TABLE 1 Correction values in dB based on calibration curves
obtained in the field
[dB] 0°
[dB] 90°
[dB] 180°
[dB] 270°
S1 2.2 1.7 00.07
S2 0.26 1.7 02 .9
S3 0.8 00.9 0.98
FIGURE 5 Difference in angle error
before and after calibration. Calibration
substantially reduces the number of
points with a high bearing error (outliers in
the boxplot)
Methods in Ecology and Evoluon
around the reference positions (Figure 8). Restricting the intersection
angles to a minimum of 40 ° and a maximum of 140° reduces this error
to 21 m. However, this results in a substantial loss of triangulated points
(292; Figure 8) with no points for position M5 (Figure 8).
3.2 | Results of the forest usability study
Tracking the movement of M. bechsteinii reveals different areas of
activity throughout the night (Figure 9, left). During 5-min intervals
that night (Figure 9, right), 301 positions were recorded within an
activity area of approximately 50 m2.
Body temperature patterns of four different bat species are
shown for nocturnal activity and resting in the day roost (Figure 10).
For the B. barbastellus as well as for the M. daubentonii, a clear drop
of the body temperature of approximately 7°C was recorded shor tly
before and after sunrise, respectively.
The automatic radio-tracking system presented in this paper incorpo-
rates the advantages of lightweight and cost-efficient radio telemetry
into a continuous tracking setup. This enhances the number of tri-
angulated positions without manual telemetry and allows analytical
techniques previously reserved for fine-scale GPS tracks to be used.
These techniques enable researchers to glean important information
about dif ferent behaviour al states of an individual over lar ge trajecto-
ries. The exemplar y 5-min tracking interval, for example, shows a low
displacement in spatial units in relation to the time spent within the
area in question, which may be interpreted as an intensive area-re-
stricted search and, thus, foraging behaviour (Knell & Codling, 2012).
Overall, the accuracy of the radio-tracking system from the
field test compares well to reported manual bearing errors of ex-
perienced field workers (Bartolommei, Francucci, & Pezzo, 2013).
However, this strongly depends on the data processing techniques
used. Antenna calibration reduces the bearing error, confirming both
the underlying theoretic al assumption and the need for calibration
to obtain reasonable results. For more precise results, all bearings
calculated based on fewer than three available antennae should be
excluded from triangulated results. Reducing the intersection angle
improves results, yet also reduces the size of the dataset .
Since incorrect positioning in our field test appears systematic,
errors can be more accurately considered than in manual telemetry
and may be further reduced by, for example, field experiments that
are able to capture this regularity.
FIGURE 6 Absolute deviation of the bearings from the real
angle depending on the number of antennae available. The mean
absolute error is 7° with a standard deviation of 6.
FIGURE 7 Distance error and available
locations depending on the allowed
cutting angle
Methods in Ecology and Evoluon
The low-cost solution for automatic radio-tracking presented
in this study enables researchers to apply automatic radio-track-
ing techniques in the field while the open-source hardware and
software components allows for active participation in future
development. As the principle of calculating bearing is based on
physical properties shared by most directional antennae, these
algorithms are suitable for triangulating positions with data
gathered by other systems such as SensorGnome (https ://senso Further relevant features, such as recording tagged
individuals' body temperature have also been implemented and
Continuously measuring animal positions and movement with a
long-term antenna setup can greatly contribute to research into animal
behaviour. The movement tracks it generates are comparable to those
generated by satellite and GPS tracking techniques, even below the
canopy in forested areas. This allows researchers to investigate ques-
tions related to small-scale habitat and resource utilization, choice of
breeding sites or migration and dispersal events in organism groups
FIGURE 8 Localization point s with all cutting angles bet ween two antennae allowed (lef t) and with cutting angles restricted to 40–140°
(right). Isolines represent point density increasing from the outside to the inside
FIGURE 9 Tracking data of a Bechstein's bat recorded on the night of 26 June 2019 (left). Yellow crosses indicate permanent radio-
tracking stations. The bounding box (black box) highlights the area of 5 min of relocations shown in detail in the right part of the figure
Methods in Ecology and Evoluon
that movement ecologists cannot yet adequately study due to size re-
strictions. In this vein, this affordable and easy-to-use automatic radio-
tracking system adds a power ful tool to movement ecology research.
The first permanent setup of the system was implemented at
Marburg Open Forest – the open research and education forest
of Marburg University. The research is funded by the Hessen State
Ministr y for Higher Education, Research and the Arts, Germany,
as part of the LOEWE priority project Nature 4.0 – Sensing
Biodiversity. is the outcome of a feasibility study
financially supported by the Ministry of the Environment, Climate
Protection and the Energy Sector Baden-Württemberg, Germany.
R.Z. invented the system and developed the algorithms for bearing
calculation. J.G., C.R., M.L., N.F. and T.N. provided development sup-
port, especially in the development regarding dislocation corrections
and monitoring of body temperature. J.G. and M.L. collected the test
data; bat foraging data were collected by J.G. J.G., M.L . and N.F. led
the writing of the manuscript. All authors interpreted the data and
contributed to the manuscript.
Example data is provided online on Zenodo (Zenodo https ://doi.
org/10.5281/zenodo.3381909 (Gottwald, 2019)) and can be pro-
cessed using the r package “rad iotracki ngeu (https ://
radio track ingeu/ radio track ingeu , Zenodo https ://
zenodo.3381316 (Zeidler, 2019)).
Jannis Gottwald
Ralf Zeidler
Nicolas Friess
Marvin Ludwig
FIGURE 10 24-hr temperature curves of four dif ferent bat species
Methods in Ecology and Evoluon
Christoph Reudenbach
Thomas Nauss
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... A second limitation was the labor-intensive task of tracking finches with portable antennas in variable, but generally harsh, climatic conditions. A potential solution could be the implementation of automated radio tracking, consisting of a system of antennas distributed across the landscape, thus scanning a broader area with less effort (e.g., Cellular Tracking Technologies (CTT), Bridge et al., 2011;Motus et al., 2017); or with an open source telemetry system (Gottwald et al., 2019). Such a network of antennas scattered in the landscape would be particularly useful for determining the movement patterns of nonbreeding finches flocking and moving long distances. ...
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Movement patterns and habitat selection of animals have important implications for ecology and evolution. Darwin's finches are a classic model system for ecological and evolutionary studies, yet their spatial ecology remains poorly studied. We tagged and radio-tracked five (three females, two males) medium ground finches (Geospiza fortis) to examine the feasibility of telemetry for understanding their movement and habitat use. Based on 143 locations collected during a 3-week period, we analyzed for the first time home-range size and habitat selection patterns of finches at El Garrapatero, an arid coastal ecosystem on Santa Cruz Island (Galápagos). The average 95% home range and 50% core area for G. fortis in the breeding season was 20.54 ha ± 4.04 ha SE and 4.03 ha ± 1.11 ha SE, respectively. For most of the finches, their home range covered a diverse set of habitats. Three finches positively selected the dry-forest habitat, while the other habitats seemed to be either negatively selected or simply neglected by the finches. In addition, we noted a communal roosting behavior in an area close to the ocean, where the vegetation is greener and denser than the more inland dry-forest vegetation. We show that telemetry on Darwin's finches provides valuable data to understand the movement ecology of the species. Based on our results, we propose a series of questions about the ecology and evolution of Darwin's finches that can be addressed using telemetry.
... An alternative method of increasing readings throughout the day is by setting up an ad-hoc wireless telemetry system at a particular habitat which can automatically triangulate the location of tagged individuals. Such a system is suggested by Gottwald et al. (2019) who proposes it as budget friendly option especially when number of personnel is limited. Other future studies should also look at comparing species movement across different habitats or over longer periods of time, in order to increase the scalability of the study. ...
Ecological corridors are crucial for the survival of species; they facilitate movement between different areas within a species' home range, whilst aiding genetic exchange across the metapopulation, thus maintaining viable their populations. Despite their importance, maintaining corridors for conservation purposes is no easy task, largely because of conflicts-of-use and related impacts, mostly resulting in habitat loss and fragmentation. This study takes a species-approach towards understanding ecological corridors across specific areas in the Maltese islands. The species selected for this study are the blue rock thrush, Monticola solitarius (Linnaeus 1758), the Old-World swallowtail butterfly, Papilio machaon melitensis (Eller, 1936) and the Mediterranean chameleon, Chamaeleo chamaeleon (Linnaeus 1758). These three faunal species are noteworthy, being of ecological significance, charismatic, and protected under different legal instruments. This study focuses on telemetry, wherein radio tags are affixed to a voucher specimen from each of the aforementioned species to follow their respective movements over an approximate period of two weeks of field monitoring. Appropriate permits were acquired from respective official agencies. The sites of release include Mdina, Comino and Buskett respectively. P. m. melitensis tagged individuals were recorded to undertake a short sea crossing between the islands of Comino and Gozo, subsequently, each making their way to the northern side of Gozo. Each butterfly is estimated to have covered a minimum distance of approximately 16.6 km in 17 days. C. chamaeleon was noted to remain within a woodland habitat without crossing into adjacent garrigue-dominated karst, with the tagged male demonstrating the most vagility from the monitored sample. Not enough data was collected for M. Solitarius to establish movement patterns due to complications which arose during field sessions. Based on present findings, the study proposes a number of recommended measures for ecological connectivity within the local context for the different target species researched.
... Radio telemetry is useful for tracking individuals (e.g. Gottwald et al., 2019), but not for diversity monitoring. Lidar has been used to detect the backscattering of a laser beam from flying insects at distances between 100 and 300 m and of laser-induced fluorescence (Guan et al., 2010). ...
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Rapid changes of the biosphere observed in recent years are caused by both small and large scale drivers, like shifts in temperature, transformations in land-use, or changes in the energy budget of systems. While the latter processes are easily quantifiable, documentation of the loss of biodiversity and community structure is more difficult. Changes in organismal abundance and diversity are barely documented. Censuses of species are usually fragmentary and inferred by often spatially, temporally and ecologically unsatisfactory simple species lists for individual study sites. Thus, detrimental global processes and their drivers often remain unrevealed. A major impediment to monitoring species diversity is the lack of human taxonomic expertise that is implicitly required for large-scale and fine-grained assessments. Another is the large amount of personnel and associated costs needed to cover large scales, or the inaccessibility of remote but nonetheless affected areas. To overcome these limitations we propose a network of Automated Multisensor stations for Monitoring of species Diversity (AMMODs) to pave the way for a new generation of biodiversity assessment centers. This network combines cutting-edge technologies with biodiversity informatics and expert systems that conserve expert knowledge. Each AMMOD station combines autonomous samplers for insects, pollen and spores, audio recorders for vocalizing animals, sensors for volatile organic compounds emitted by plants (pVOCs) and camera traps for mammals and small invertebrates. AMMODs are largely self-containing and have the ability to pre-process data (e.g. for noise filtering) prior to transmission to receiver stations for storage, integration and analyses. Installation on sites that are difficult to access require a sophisticated and challenging system design with optimum balance between power requirements, bandwidth for data transmission, required service, and operation under all environmental conditions for years. An important prerequisite for automated species identification are databases of DNA barcodes, animal sounds, for pVOCs, and images used as training data for automated species identification. AMMOD stations thus become a key component to advance the field of biodiversity monitoring for research and policy by delivering biodiversity data at an unprecedented spatial and temporal resolution.
... Tracking data, however, are often limited to a small number of individuals (< 30) over short time periods (days to months), restricting the ability of researchers to generate broad-scale inferences [15][16][17]. In addition, individual-level tracking data are often constrained due to organisms or species having small body size [18,19], budgetary limitations [20], or high tag loss (anatomical, behavioral, animal safety [21][22][23]). It can also be challenging to mark and track a sample of individuals that adequately represent broadly distributed species or species with large populations (e.g., [24,25]). ...
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As human and automated sensor networks collect increasingly massive volumes of animal observations, new opportunities have arisen to use these data to infer or track species movements. Sources of broad scale occurrence datasets include crowdsourced databases, such as eBird and iNaturalist, weather surveillance radars, and passive automated sensors including acoustic monitoring units and camera trap networks. Such data resources represent static observations, typically at the species level, at a given location. Nonetheless, by combining multiple observations across many locations and times it is possible to infer spatially continuous population-level movements. Population-level movement characterizes the aggregated movement of individuals comprising a population, such as range contractions, expansions, climate tracking, or migration, that can result from physical, behavioral, or demographic processes. A desire to model population movements from such forms of occurrence data has led to an evolving field that has created new analytical and statistical approaches that can account for spatial and temporal sampling bias in the observations. The insights generated from the growth of population-level movement research can complement the insights from focal tracking studies, and elucidate mechanisms driving changes in population distributions at potentially larger spatial and temporal scales. This review will summarize current broad-scale occurrence datasets, discuss the latest approaches for utilizing them in population-level movement analyses, and highlight studies where such analyses have provided ecological insights. We outline the conceptual approaches and common methodological steps to infer movements from spatially distributed occurrence data that currently exist for terrestrial animals, though similar approaches may be applicable to plants, freshwater, or marine organisms.
... The use of UAVs and other ongoing technological advances are creating further possibilities for tracking the movement of insects and will likely increase the use of tracking tags in insect ecology [11,20,[71][72][73]. Furthermore, there are non-tracking cases in which insects are used to carry devices [20,21]. ...
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In this study, we describe an inexpensive and rapid method of using video analysis and identity tracking to measure the effects of tag weight on insect movement. In a laboratory experiment, we assessed the tag weight and associated context-dependent effects on movement, choosing temperature as a factor known to affect insect movement and behavior. We recorded the movements of groups of flightless adult crickets Gryllus locorojo (Orthoptera:Gryllidae) as affected by no tag (control); by light, medium, or heavy tags (198.7, 549.2, and 758.6 mg, respectively); and by low, intermediate, or high temperatures (19.5, 24.0, and 28.3°C, respectively). Each individual in each group was weighed before recording and was recorded for 3 consecutive days. The mean (± SD) tag mass expressed as a percentage of body mass before the first recording was 26.8 ± 3.7% with light tags, 72 ± 11.2% with medium tags, and 101.9 ± 13.5% with heavy tags. We found that the influence of tag weight strongly depended on temperature, and that the negative effects on movement generally increased with tag weight. At the low temperature, nearly all movement properties were negatively influenced. At the intermediate and high temperatures, the light and medium tags did not affect any of the movement properties. The continuous 3-day tag load reduced the average movement speed only for crickets with heavy tags. Based on our results, we recommend that researchers consider or investigate the possible effects of tags before conducting any experiment with tags in order to avoid obtaining biased results.
... However, recognizing individuals on images, particularly small and nocturnal species or species that lack unique visually detectable features, is challenging (Rowcliffe et al., 2008), as is the recognition of individuals based on acoustic recordings (Stowell et al., 2019). By contrast, the automatic tracking of bats using lightweight VHF radio transmitters offers several advantages (Gottwald et al., 2019;Kays et al., 2011;Taylor et al., 2017): (a) VHF signals can be used as triggers for other sensors and (b) they may support the recognition of individuals in video sequences based on comparisons of the VHF signal patterns with the movements observed in the video. ...
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Bats represent a highly diverse group of mammals and are essential for ecosystem functioning. However, knowledge about their behavior, ecology, and conservation status is limited. Direct observation of marked individuals (commonly applied to birds) is not possible for bats due to their small size, rapid movement, and nocturnal lifestyle, while neither popular observation methods such as camera traps nor conventional tracking technologies sufficiently capture the behavior of individuals. The combination and networking of different sensors in a single system can overcome these limitations, but this potential has been explored only to a limited extent. We present BatRack, a multi‐sensor device that combines ultrasonic audio recordings, automatic radio telemetry, and video camera recordings in a single modular unit. BatRack facilitates the individual or combined scheduling of sensors and includes a mutual triggering mode. It consists of off‐the‐shelf hardware and both its hardware blueprints and the required software have been published under an open license to allow scientists and practitioners to replicate the system. We tested the suitability of radio telemetry and audio sensors as camera triggers and evaluated the detection of individuals in video recordings compared to radio telemetry signals. Specifically, BatRack was used to monitor the individual swarming behavior of six members of a maternity colony of Bechstein’s bat. Preliminary anecdotal results indicate that swarming intensity is related to reproductive state and roost switching.. BatRack allows researchers to recognize individual bats and monitor their behavioral patterns using an easily deployed and scalable system. BatRack is thus a promising approach to obtaining detailed insights into the behavioral ecology of bats.
... Drones have been applied to a variety of ecological survey applications, including aerial mapping and wildlife tracking. In addition, software-defined radios (SDRs), which allow us to rapidly reconfigure a radio and receive a large swath of the radio spectrum simultaneously, have matured to the point that there are sufficiently low cost, robust, and lightweight radios commercially available that can be used as part of a UAV sensor payload that can track multiple animals simultaneously (Gottwald et al., 2019;Nabeel & Bloessl, 2016;Nguyen et al., 2019;Santos et al., 2014;Vonehr et al., 2016;Webber et al., 2017). ...
Radio telemetry is a commonly used technique in conservation biology and ecology, particularly for studying the movement and range of individuals and populations. Traditionally, most radio telemetry work is done using handheld directional antennae and either direction‐finding and homing techniques or radio‐triangulation techniques. Over the past couple of decades, efforts have been made to utilize unmanned aerial vehicles to make radio‐telemetry tracking more efficient, or cover more area. However, many of these approaches are complex and have not been rigorously field‐tested. To provide scientists with reliable quality tracking data, tracking systems need to be rigorously tested and characterized. In this paper, we present a novel, drone‐based, radio‐telemetry tracking method for tracking the broad‐scale movement paths of animals over multiple days and its implementation and deployment under field conditions. During a 2‐week field period in the Cayman Islands, we demonstrated this system's ability to localize multiple targets simultaneously, in daily 10 min tracking sessions over a period of 2 weeks, generating more precise estimates than comparable efforts using manual triangulation techniques.
Conference Paper
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Long-term animal monitoring in natural habitats provides significant insights into the animals’ behavior, interactions, health, or external influences. However, the sizes of monitoring devices attachable to animals strongly depends on the animals’ sizes, and thus the range of possible sensors including batteries is severely limited. Gathered data can be offloaded from monitoring devices to data sinks in a wireless sensor network using available radio access technologies, but this process also needs to be as energy-efficient as possible. This paper presents an approach to combine the benefits of high-throughput WiFi and robust low-power LoRa communication for energy-efficient data offloading. WiFi is only used when connectivity between mobile devices and data sinks is available, which is determined by LoRa-based distance estimations without the need for additional GPS sensors. A prototypical implementation on low-end commodity-off-the-shelf hardware is used to evaluate the proposed approach in a German mixed forest using a simple path loss model for distance estimation. The system provides an offloading success rate of 87%, which is similar to that of a GPS-based approach, but with around 37% less power consumption.
Conference Paper
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We present tRackIT OS, open-source software for reliable VHF radio tracking of (small) animals in their wildlife habitat. tRackIT OS is an operating system distribution for tRackIT stations that receive signals emitted by VHF tags mounted on animals and are built from low-cost commodity-off-the-shelf hardware. tRackIT OS provides software components for VHF signal processing, system monitoring, configuration management, and user access. In particular, it records, stores, analyzes, and transmits detected VHF signals and their descriptive features, e.g., to calculate bearings of signals emitted by VHF radio tags mounted on animals or to perform animal activity classification. Furthermore, we provide results of an experimental evaluation carried out in the Marburg Open Forest, the research and teaching forest of the University of Marburg, Germany. All components of tRackIT OS are available under a GNU GPL 3.0 open source license at
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Dispersal is a fundamental process that facilitates population and range expansion by providing a mechanism for colonization and metapopulation linkages. Yet quantifying the dispersal process, particularly long-distance dispersal events, has been inherently difficult due to technological and observational limitations. Additionally, dispersal distance calculated as the straight-line distance between initiation and settlement fails to account for the actual movement path of the animal during dispersal. Here, we highlight six long-distance dispersal events, representing some of the longest dispersal distances recorded for red foxes. Cumulative dispersal movements ranged from 132 to 1036 km and occurred within both sexes (1 female, 5 males). With one exception, dispersal events ranged from 7 to 22 days and tended to be directed north-northwest. Importantly, cumulative movements were up to five times longer than straight-line distances, with two foxes traveling an additional 114 and 256 km before returning to, and settling in, areas previously encountered during dispersal. This suggests a role of habitat assessment and homing behavior during dispersal and indicates that the capacity and potential for dispersal are not limiting factors to either sex in a red fox population. Dispersal capacity should thus be considered regarding transboundary management and disease control of red fox populations.
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The growing field of movement ecology uses high resolution movement data to analyze animal behavior across multiple scales: from individual foraging decisions to population-level space-use patterns. These analyses contribute to various subfields of ecology – inter alia behavioral, disease, landscape, resource, and wildlife – and facilitate novel exploration in fields ranging from conservation planning to public health. Despite the growing availability and general accessibility of animal movement data, much potential remains for the analytical methods of movement ecology to be incorporated in all types of geographic analyses. This review provides for the Geographical Information Sciences (GIS) community an overview of the most common movement metrics and methods of analysis employed by animal ecologists. Through illustrative applications, we emphasize the potential for movement analyses to promote transdisciplinary GIS/wildlife-ecology research.
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Migratory ungulates are often exposed to anthropogenic infrastructure along their migration routes. Understanding the influence of such development on migratory behavior is critical to successful planning and conservation. Impermeable barriers have obvious and detrimental effects to migratory ungulate populations, but the influence of semi-permeable barriers, where the connectivity of migration habitat is maintained but the migration routes are compromised by anthropogenic development, remains unclear. We evaluated the influence of development on the migratory behavior of individual mule deer (Odocoileus hemionus) in western Wyoming, USA. We used fine-scale movement data to evaluate the influence of anthropogenic infrastructure on deer movement rates, stopover use, and fidelity to migration routes for individual animals across multiple seasons and years. Deer avoided human infrastructure when selecting stopover sites. Fidelity to migration routes and stopover areas, as measured by the degree of spatial overlap between years, was not influenced by development, except in one heavily developed area. Our results suggested that deer increased rate of movement, reduced time in stopovers, and shifted stopovers in areas of intense development. In most cases, deer maintained fidelity to migration routes, regardless of development, suggesting that deer mediated exposure to development by altering movement—rates and timing—rather than the routes they traversed. This work adds to a growing number of studies indicating that development can disrupt migratory behavior. Understanding how different types and intensities of development influence migration can help inform land-use planning and conservation of migratory ungulates.
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Background: GPS telemetry has revolutionized the study of animal spatial ecology in the last two decades. Until recently, it has mainly been deployed on large mammals and birds, but the technology is rapidly becoming miniaturized, and applications in diverse taxa are becoming possible. Large constricting snakes are top predators in their ecosystems, and accordingly they are often a management priority, whether their populations are threatened or invasive. Fine-scale GPS tracking datasets could greatly improve our ability to understand and manage these snakes, but the ability of this new technology to deliver high-quality data in this system is unproven. In order to evaluate GPS technology in large constrictors, we GPS-tagged 13 Burmese pythons (Python bivittatus) in Everglades National Park and deployed an additional 7 GPS tags on stationary platforms to evaluate habitat-driven biases in GPS locations. Both python and test platform GPS tags were programmed to attempt a GPS fix every 90 min. Results: While overall fix rates for the tagged pythons were low (18.1%), we were still able to obtain an average of 14.5 locations/animal/week, a large improvement over once-weekly VHF tracking. We found overall accuracy and precision to be very good (mean accuracy = 7.3 m, mean precision = 12.9 m), but a very few imprecise locations were still recorded (0.2% of locations with precision > 1.0 km). We found that dense vegetation did decrease fix rate, but we concluded that the low observed fix rate was also due to python microhabitat selection underground or underwater. Half of our recovered pythons were either missing their tag or the tag had malfunctioned, resulting in no data being recovered. Conclusions: GPS biologging technology is a promising tool for obtaining frequent, accurate, and precise locations of large constricting snakes. We recommend future studies couple GPS telemetry with frequent VHF locations in order to reduce bias and limit the impact of catastrophic failures on data collection, and we recommend improvements to GPS tag design to lessen the frequency of these failures.
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To prevent further global declines in biodiversity, identifying and understanding key habitats is crucial for successful conservation strategies. For example, globally, seabird populations are under threat and animal movement data can identify key at-sea areas and provide valuable information on the state of marine ecosystems. To date, in order to locate these areas, studies have used global positioning system (GPS) to record position and are sometimes combined with time-depth recorder (TDR) devices to identify diving activity associated with foraging, a crucial aspect of at-sea behaviour. However, the use of additional devices such as TDRs can be expensive, logistically difficult and may adversely affect the animal. Alternatively, behaviours may be resolved from measurements derived from the movement data alone. However, this behavioural analysis frequently lacks validation data for locations predicted as foraging (or other behaviours). Here, we address these issues using a combined GPS and TDR dataset from 108 individuals by training deep learning models to predict diving in European shags, common guillemots and razorbills. We validate our predictions using withheld data, producing quantitative assessment of predictive accuracy. The variables used to train these models are those recorded solely by the GPS device: variation in longitude and latitude, altitude and coverage ratio (proportion of possible fixes acquired within a set window of time). Different combinations of these variables were used to explore the qualities of different models, with the optimum models for all species predicting non-diving and diving behaviour correctly over 94% and 80% of the time, respectively. We also demonstrate the superior predictive ability of these supervised deep learning models over other commonly used behavioural prediction methods such as hidden Markov models. Mapping these predictions provides useful insights into the foraging activity of a range of seabird species, highlighting important at sea locations. These models have the potential to be used to analyse historic GPS datasets and further our understanding of how environmental changes have affected these seabirds over time.
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We describe a new collaborative network, the Motus Wildlife Tracking System (Motus;, 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.
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Worldwide, many countries aim at countering global climate change by promoting renewable energy. Yet, recent studies highlight that so-called green energy, such as wind energy, may come at environmental costs, for example when wind turbines kill birds and bats. Using miniaturized GPS loggers, we studied how an open-space foraging bat with high collision risk with wind turbines, the common noctule Nyctalus noctula (Schreber, 1774), interacts with wind turbines. We compared actual flight trajectories to correlated random walks to identify habitat variables explaining the movements of bats. Both sexes preferred wetlands but used conventionally managed cropland less than expected based on availability. During midsummer, females traversed the land on relatively long flight paths and repeatedly came close to wind turbines. Their flight heights above ground suggested a high risk of colliding with wind turbines. In contrast, males recorded in early summer commuted straight between roosts and foraging areas and overall flew lower than the operating range of most turbine blades, suggesting a lower collision risk. Flight heights of bats suggest that during summer the risk of collision with wind turbines was high for most studied bats at the majority of currently installed wind turbines. For siting of wind parks, preferred bat habitats and commuting routes should be identified and avoided.
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Bank Swallows (Riparia riparia) congregate in large nocturnal roosts during the non-breeding season. Scant evidence suggests that Bank Swallows may also congregate regularly in nocturnal roosts during the breeding period. To help clarify the issue, we used automated radio-telemetry to document the roosting behavior of 11 males and 11 females that were tending nests with young at two nesting colonies. Nineteen of the 22 birds (86%) spent at least one night roosting away from the colony, and 13 of the 22 birds (59%) spent at least one night roosting likely within a large marsh located ∼30 km away from the colonies. Females tended to roost overnight at the colony more than males. The proportion of nights birds spent roosting away from the colony was highly variable between individuals. Minimum flight speeds to an evening roost site (∼30 km distant) were significantly greater than return flights back to the colony in the morning. Our study confirms that breeding Bank Swallows do in fact regularly roost away from the colony during the nestling period. Our study also highlights some new and intriguing questions regarding how Bank Swallows use the landscape during the breeding season, and the potential importance of wetland roost sites in the proximity of breeding colonies.
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Background: Island breeding birds present an ideal system for studying migratory movements in passerines because their populations are clearly demarcated, and individuals must depart on migration from a single location. The Ipswich Sparrow (Paserculus sandwichensis princeps) is a subspecies of the Savannah Sparrow that breeds exclusively on Sable Island, Nova Scotia, Canada and winters along the Atlantic coast of North America. We used a network of 34 automated VHF telemetry receivers to track radio-tagged adult and juvenile Ipswich Sparrows from their breeding island southward through the first half of their fall migratory journey. Results: We compared adult to juvenile timing and routes. We show that juveniles leave the island approximately 24 days prior to adults and remain temporally separated from them during migration through Nova Scotia. Juveniles have different overwater orientations that result in migratory routes with shorter ocean crossings and a longer overall distance travelled compared to adults. Juveniles also have more frequent and longer stopovers, and displayed some reverse migration. Conclusion: We demonstrate that migratory routes differ between adults and juveniles, suggesting that routes change as individuals age, possibly through learning or social interactions. These differential routes also suggest that sparrows experience risk in different ways with juveniles selecting shorter overwater flights with less navigational risk at the cost of increased time spent in migration.