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Chemical communication plays an important role in mammalian life history decisions. Animals send and receive information based on body odour secretions. Odour cues provide important social information on identity, kinship, sex, group membership or genetic quality. Recent findings show, that rodents alarm their conspecifics with danger-dependent body odours after encountering a predator. In this study, we aim to identify the chemistry of alarm pheromones (AP) in the bank vole, a common boreal rodent. Furthermore, the vole foraging efficiency under perceived fear was measured in a set of field experiments in large outdoor enclosures. During the analysis of bank vole odour by gas chromatography–mass spectrometry, we identified that 1-octanol, 2-octanone, and one unknown compound as the most likely candidates to function as alarm signals. These compounds were independent of the vole’s sex. In a field experiment, voles were foraging less, i.e. they were more afraid in the AP odour foraging trays during the first day, as the odour was fresh, than in the second day. This verified the short lasting effect of volatile APs. Our results clarified the chemistry of alarming body odour compounds in mammals, and enhanced our understanding of the ecological role of AP and chemical communication in mammals.
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Oecologia (2021) 196:667–677
https://doi.org/10.1007/s00442-021-04977-w
BEHAVIORAL ECOLOGY –ORIGINAL RESEARCH
Bank vole alarm pheromone chemistry andeffects inthefield
ThorbjörnSievert1 · HannuYlönen1 · JamesD.Blande2 · AmélieSaunier2 · DavevanderHulst3·
OlgaYlönen1· MarkoHaapakoski1
Received: 26 May 2021 / Accepted: 19 June 2021 / Published online: 25 June 2021
© The Author(s) 2021
Abstract
Chemical communication plays an important role in mammalian life history decisions. Animals send and receive information
based on body odour secretions. Odour cues provide important social information on identity, kinship, sex, group member-
ship or genetic quality. Recent findings show, that rodents alarm their conspecifics with danger-dependent body odours after
encountering a predator. In this study, we aim to identify the chemistry of alarm pheromones (AP) in the bank vole, a common
boreal rodent. Furthermore, the vole foraging efficiency under perceived fear was measured in a set of field experiments in
large outdoor enclosures. During the analysis of bank vole odour by gas chromatography–mass spectrometry, we identified
that 1-octanol, 2-octanone, and one unknown compound as the most likely candidates to function as alarm signals. These
compounds were independent of the vole’s sex. In a field experiment, voles were foraging less, i.e. they were more afraid in
the AP odour foraging trays during the first day, as the odour was fresh, than in the second day. This verified the short lasting
effect of volatile APs. Our results clarified the chemistry of alarming body odour compounds in mammals, and enhanced
our understanding of the ecological role of AP and chemical communication in mammals.
Keywords Bank vole· Alarm pheromone· Mammalian body odour· Predator–prey interactions
Introduction
Predator–prey interactions are among the strongest drivers
of evolution (Abrams 1986, 2000; Yoshida etal. 2003). In
the context of an evolutionary arms race, early recognition
of predation risk by prey is essential for prey survival and
fitness. Cues of increased predation risk range from very
reliable cues like sighting of a predator or its direct attack
(Blumstein etal. 2000; Van der Veen 2002), to more general
and less accurate ones like signs or markings of predator
revealing its presence or visit in vicinity. These signs include
odorous faeces or other scent cues (Kats and Dill 1998).
However, these cues do not necessarily have to originate
from the predator, as the other option for information on
predator are cues carried by conspecific prey, which often
can even be more reliable than a mere predator odour (Blum-
stein etal. 2000; Randler 2006; MacLean and Bonter 2013).
After perceiving increased predation risk, multiple
mechanisms and adaptations by prey animals are possible,
from simple immediate behavioural responses to long-term
physiological or even intergenerational adaptations (Abrams
2000). Anti-predatory behaviours employed in prey range
from simple avoidance of high-risk areas (Ferrero etal.
2011; Clinchy etal. 2013; Pérez-Gómez etal. 2015) and
freezing to decrease detectability (Wallace and Rosen 2000;
Sundell and Ylönen 2004), over changes in vigilance and
foraging (Brown 1999; Ylönen and Brown 2007; Embar
etal. 2011), to drastic changes in the reproductive behav-
iours (Ylönen and Ronkainen 1994; Sih 1994; Mappes and
Ylönen 1997; Mönkkönen etal. 2009; Haapakoski etal.
2012, 2018; Sievert etal. 2019).
If a prey individual survives a direct encounter with
a predator, it may increase its own and its conspecifics’
Communicated by Janne Sundell.
* Thorbjörn Sievert
thorbjoern.sievert@gmx.net
1 Department ofBiological andEnvironmental Science,
Konnevesi Research Station, University ofJyväskylä, P.O.
Box35, 40014Jyväskylä, Finland
2 Department ofEnvironmental andBiological Sciences,
University ofEastern Finland, P.O. Box1627, 70211Kuopio,
Finland
3 Environmental Sciences Department, Resource Ecology
Group, Wageningen University, 6700AAWageningen,
Netherlands
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668 Oecologia (2021) 196:667–677
1 3
survival and later fitness by signalling predator presence
intraspecifically. Several means of intra-species predator
communication have been studied in animals, from sim-
ple group flight behaviours in birds (Adamo and McKee
2017) to elaborate vocal signalling in primates (Ouattara
etal. 2009) and Mungotinae (Townsend etal. 2012; Col-
lier etal. 2017). Another pathway of communication is
fear or risk signalling body secretions or alarm phero-
mones (AP). These are widespread in invertebrates, such
as sea anemones (Howe and Sheikh 1975), ants (Crewe
and Blum 1970b), aphids (Bowers etal. 1972; Beale etal.
2006) or mites (Kuwahara etal. 1989), but also occur in
vertebrates such as fish (von Frisch 1938; Wisenden etal.
2004; Mathis and Smith 2008). In the last two decades, a
growing number of studies were able to show the presence
of AP also in mammals, such as Wistar rats (Kiyokawa
etal. 2004; Gutiérrez-García etal. 2007; Inagaki etal.
2009, 2014), C57BL/6J and OMP-GFP mice (Brechbühl
etal. 2013), Cabrera voles (Microtus cabrerae) (Gomes
etal. 2013), and even in domestic cattle (Aubrac breed)
(Boissy etal. 1998) and pigs (Vieuille-Thomas and Signo-
ret 1992). Several of the aforementioned species live in
social groups, so the secretion of AP serves to warn the
group, family or colony.
While the structure of AP remains unresolved for most
mammalian species, it has been identified in, for exam-
ple, aphids (Bowers etal. 1972), sea anemones (Howe and
Sheikh 1975), and several insects (Heath and Landolt 1988;
Kuwahara etal. 1989). Work on lab rodents has allowed for
the analyses of alarm pheromones in Wistar rats (Inagaki
etal. 2014), and C57BL/6J and OMP-GFP mice (Brechbühl
etal. 2013).
In this study, we use the term “pheromone” to indicate
semiochemical communication between individuals of the
same species, as opposed to allelochemicals which facilitate
communication between two different species (Dicke and
Sabelis 1988; Sbarbati and Osculati 2006). We acknowl-
edge that the secretion discussed in this study may have
allelochemical properties, but there is no evidence of this
in mammals yet.
Semiochemical communication is of great importance in
mammals (Müller-Schwarze 1983; Dehnhard 2011; Apps
2013). It is used to convey a wide array of information,
among others reproductive status (Pankevich etal. 2004),
immunocompetence (Spehr etal. 2006), stress (Gomes
etal. 2013) and effects in the mate choice (Roberts etal.
2010). This does not only occur in small mammalian spe-
cies (Gomes etal. 2013; Inagaki etal. 2014), but also in
large ones, e.g. muskox (Ovibos moschatus) and giant pan-
das (Ailuropoda melanoleuca) (Flood 1992; Wilson etal.
2018), as well as in primates (Evans 2006; Setchell etal.
2011) and humans (Stern and McClintock 1998; Thornhill
and Gangestad 1999).
Previous behavioural studies have already shown alarm
pheromone effects on reproductive behaviour in bank voles,
specifically differences in the number of offspring (Haapa-
koski etal. 2018), the amount of parturitions (Sievert etal.
2019), and several transgenerational effects (Sievert etal.
2020). While the effects of an alarm pheromone exposure
have been studied, the actual nature remains unclear. This
study combines two goals with two different experimental
designs: first to identify the chemicals involved in semio-
chemically signalling alarm in bank voles and second, to
verify the effects of these alarm compounds on behavioural
decisions of bank voles in the field compared to direct preda-
tor presence cue in form of predator odour. In the labora-
tory study, we sampled vole-derived volatile organic com-
pounds (VOC) after exposing our experimental bank voles
to three different stimuli: a live predator (P), handling by a
researcher (H), and no stimulus (C). The VOCs were col-
lected by dynamic headspace sampling and analysed by gas
chromatography-mass spectrometry (GC–MS). In the field
study, we investigated how the presence of alarm phero-
mone, compared to predator odour and a control, shapes
the foraging effort of voles over time. For the field part of
the experiment, we predicted alarm pheromones to carry
important but sensitive information, and expected to see only
short-time effect of volatile APs compared to more long-
lasting risk cue of predator odours.
Materials andmethods
Study animals andsite
The bank vole (Myodes glareolus) is one of the most com-
mon small rodents living in a variety of northern temperate
and boreal European forest habitats west of the Urals (Sten-
seth 1985). The species is granivorous-omnivorous, with
their diet consisting mainly of seeds and buds, but also of
other plant materials or invertebrates (Hansson 1979; Eccard
and Ylönen 2006). In Central Finland, where this work was
conducted, bank voles breed three to five times per season,
which lasts from May until September (Mappes etal. 1995;
Koivula etal. 2003).
Bank voles are preyed upon by a diverse predator assem-
blage, including least weasels (Mustela nivalis) and stoats
(Mustela erminea) (Ylönen 1989; Meri etal. 2008). The
least weasel is an especially effective hunter of voles due to
their size and excellent hunting skills, least weasels are likely
able to kill bank voles whenever the two species come into
direct contact (Tidhar etal. 2007; Haapakoski etal. 2012).
We conducted our study at Konnevesi Research Station in
Central Finland (62°37N, 26°20E). In the laboratory, males
and females were maintained in the same room. The adult
voles used in the study were wild-caught individuals that
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669Oecologia (2021) 196:667–677
1 3
were housed in the lab during the winter months preceding
the study period. Winter colonies are formed from the last
cohort of voles of the previous summer. Thus, their age at
the time of the experiment is about 7months. The winter
population is housed on a short photoperiod (8L:16D) at
around 17°C throughout the winter and male voles’ testes
are abdominal and female vaginas are closed. Samples were
taken from non-reproductive animals, to minimize contami-
nation related to oestrus cycles or sexual maturity. All ani-
mals were individually marked with ear tags (#1005-1L1,
National Band & Tag Company, Newport, KY, USA). Voles
were kept individually in 42cm × 26cm × 15cm transpar-
ent cages with wire mesh lids and supplied with adlibitum
water and food. 7days prior to sampling voles were placed
into smaller 24 × 18 × 14cm cages, equipped with the glass
sampling container. The bedding materials in each cage con-
sisted of wood shavings and hay.
Weasels were housed individually in
60cm × 160cm × 60cm cages in an outdoor shelter. Each
cage had a nest box and wood shavings and hay as bedding.
Throughout the experiment (and during the two-week period
before its initiation), weasels were exclusively fed dead bank
voles.
Treatments andVOC sampling
One week before sampling, voles were changed to the small
sampling cages containing their usual bedding, including a
glass sampling container with a volume of 250ml covered
with a dark cardboard sleeve to simulate a safe refuge. This
served to minimize the stress to the vole as much as possible.
The control (C) treatment was achieved by switching the
glass container for a clean one. The lid to the glass container
was closed as soon as the vole entered it voluntarily. Every
lid was fashioned with an inlet and outlet and the inside of
each lid was covered with a sheet of polytetrafluoroethylene
to prevent reactions of the VOC with the lid. Once the lid
was attached, the sampling of the air from the chamber to get
the control sample was started. The handling (H) treatment
consisted of 3min of simulated standard handling proce-
dures by the same researcher for every sampling (sexing,
checking ear tag, checking PIT tag etc.) after which the ani-
mals were immediately transferred to a sampling container.
For the predator (P) treatment, a vole in a live trap (Ugglan
Special, Grahnab AB, Gnosjö, Sweden), was introduced into
a weasel cage for 3min. Afterwards, the vole was directly
transferred into the sampling container. Each vole was sam-
pled for VOCs individually.
Containers were cleaned at 75°C for 20min with water
before and between sampling bouts. Pressurized (Gardner
Denver Thomas GmbH, Puchheim, Germany) and filtered,
both through an air filter (Wilkerson model M03C2X00;
Wilkerson Corp., Richland, MI, USA) and through active
charcoal, inlet air was introduced into glass containers at
a flow rate of 255–260ml min−1. After 20min of flushing
air through the tubes and filters, but not the sampling con-
tainers, VOC emissions were collected for 20min (length
determined with pilot samples) into pre-conditioned car-
tridges filled with 200mg Tenax TA (60/80 mesh, Markes
International, UK) positioned at the outlet of the glass con-
tainer. Cartridges were connected via clean silicone tubes
to a vacuum pump (Bühler Technologies GmbH, Ratingen,
Germany), which pulled air through the cartridges with a
flow rate of 240ml min−1. Inlet and outlet airflows were
calibrated with a gas flow calibrator (mini Buck calibrator,
Buck, USA).
After collection, cartridges were stored at 4°C for a
maximum of 3weeks before analysis. Blanks (collected
from empty glass containers) were also sampled with
the same method to identify potential contaminants. The
blanks were collected daily from the room where the VOC
collection took place and from inside the weasel cages to
exclude a potential contamination of weasel odour in our
samples. Analysis of VOCs collected into the cartridges was
performed by GC–MS (7890A GC and 5975C VL MSD;
Agilent Technologies, USA) with samples thermally des-
orbed with an automated thermal desorption unit (TD-100;
Markes International Ltd, UK). Samples were desorbed at
250°C for 10min, and cryofocused at −30°C in split-
less mode. The column used to separate molecules was an
HP5-MS (60 m × 0.25mm × 0.5µm, Agilent, USA). The
chromatographic program was set up as follows: 40°C at the
start with a hold of 2min, a 3°C min−1 temperature ramp
until 210°C, and then a 10°C min−1 temperature ramp to
300°C. This last temperature was held for 5min to clean
the column. The carrier gas was helium. VOC identification
was conducted via comparison with a series of analytical
standards [see Saunier and Blande (2019)], comparison of
mass spectra to the NIST and Wiley libraries and the cal-
culation of Kovats indices (through the injection of alkanes
C8–C20) with comparison to available literature (Adams
2007) (https:// webbo ok. nist. gov/). The following analytical
standards were used: 2-hexenal, 3-hexen-1-ol, benzaldehyde,
3-hexen-1-ol acetate, nonanal, benzyl nitrile, methyl salicy-
late, alpha-pinene, beta-pinene, beta-myrcene, alpha-phel-
landrene, 3-carene, limonene, eucalyptol, ocimene, linalyl
acetate, caryophyllene, bisabolol. Once the identification
was done, the quantification for each compound was real-
ized based on calibration curves obtained with the injec-
tion of analytical standards used for identification. Then,
we normalized the quantity obtained according to the inlet
and outlet flows as well as the time of collection (see below).
We provide the experimental m/z spectra of 2-ocatanone,
1-octanol, and unknown compound 7 (Appendix1), along
with the theoretical NIST spectra for 2-ocatanone and
1-octanol (Appendix2) in the Supplemental Material.
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670 Oecologia (2021) 196:667–677
1 3
A total of 23 voles was used in this experiment, 13 for
the C treatment and the same ten animals for both H and P.
Field experiment
Field study was conducted using five 0.25-ha outdoor enclo-
sures close to the Konnevesi Research Station in Central
Finland (Ylönen and Eccard 2004) during July and August.
Eight voles (four of each sex) were released in five enclo-
sures each. With two repetitions, this resulted in 80 voles
total. The enclosures were emptied of other rodents by live
trapping before each replication. One week after releasing
the voles, three wooden boxes (60 × 40 × 30cm), with lids,
about 10m apart from each other, were arranged in a tri-
angle at the centre of each enclosure. Each box contained
one odour cue, control (C), predator odour (PO) or alarm
pheromone (AP). The 1dl odour cues were obtained as
described in Sievert etal. (2020), i.e. clean wood shaving,
soiled bedding from weasel cages, and bedding from weasel
exposed voles, respectively. Each box contained further a
seed tray for determining foraging efficiency of voles under
each treatment using the giving-up-density (GUD) method
(Brown 1988) (explained in the next paragraph). The trays
were lidless boxes (19 × 19 × 6cm) containing 8dl of sand
into which 20 unhusked sunflower seeds were mixed. The
foraging patch was renewed each day, the sand was sieved
and the remaining untouched seeds were counted to obtain
the GUD.
Brown (1988, 1999) framed the harvest rate an animal
makes at a given patch as a balance of the energetic gains
and costs attributed to foraging effort, predation, and missed
opportunity costs. The density of food remaining in a patch
after the forager stops foraging is called a givingup density
(GUD) (Brown 1999) and reflects the point where the energy
remaining in the patch is equal to or outweighed by the
combined costs to the forager. The GUD, as a method, has
been adapted to test a large variety of elements affecting the
strategic decisions animals take (Bedoya-Perez etal. 2013)
and has been widely applied as a measure for habitat use
(Ylönen etal. 2002; Orrock etal. 2004; Bleicher etal. 2018).
In predator–prey studies, a low GUD (more consumed) is
interpreted as an indicator of low perceived predation risk,
while a high GUD (less consumed) is an indicator of a high
perceived predation pressure(Brown 1999; Bedoya-Perez
etal. 2013; Bleicher 2017).
Data analysis
The Emission Rates of VOCs collected by dynamic head-
space sampling (ER) were calculated with the following
formula:
with ER expressed in ng * h−1 * vole−1. X is the compound
quantity (ng), Ai and Ao are the inlet and outlet air flows (ml
* min−1), respectively, and t is the sampling time in h.
Statistical analyses were performed with the R software
(R Core Team 2021). Partial Least Squares Discriminant
Analysis (PLS-DA) was performed on ER for all treat-
ments using the package ‘vegan’ (Oksanen etal. 2020) and
‘RVAideMemoire’ (Hervé 2021) with a cross-validation
based on 50 submodels (fivefold outer loop and fourfold
inner loop). Pairwise tests were performed based on PLS-
DA with 999 permutations to highlight the differences
between treatments. The PLS-DA graphics were drawn
with ‘MetaboAnalystR’ (Chong and Xia 2018; Chong
etal. 2019). The Variables Importance for Projection (VIP)
scores, obtained through PLS-DA, were used to select the
compounds of interest (the ten compounds with the highest
scores). Kruskal–Wallis tests followed by Nemenyi post hoc
tests were done for these components of interest to compare
the ER.
For the GUD measurements, generalized linear mixed
models (GLMM) with a Poisson distribution were calcu-
lated, ‘lme4’ (Bates etal. 2015). To achieve the best model
fit, first the interaction was removed, then other factors, only
leaving Treatment for the simplest model. Each treatment
was compared to the C (control) treatment. The most fitting
model was chosen based on AICc, package ‘MuMIn’ (Bar-
ton 2020). A model was considered the best if the difference
in AICc from the next model was greater than 2.5. Appropri-
ate random effects were chosen by AICc.
All plots were generated with ‘ggplot2’ (Wickham 2016)
and ‘MetaboAnalystR’ (Chong and Xia 2018; Chong etal.
2019).
Results
Emission rates
To investigate differences at the compound level, PLS-DA
was performed for the emission rates of the individual com-
pounds emitted for each treatment (Fig.1). A global per-
mutation test of the PLS-DA showed significant differences
(PLS-DA, 999 permutations, P = 0.001), while a pairwise
permutation test confirmed these (PLS-DA, 999 permuta-
tions, P = 0.001) for all three pairwise comparisons. An
analysis of the ten compounds of interest revealed signifi-
cantly higher ER in the P treatment compared to both H and
C, analysed by a Kruskal–Wallis test (Table1). None of the
ten compounds was detected in the C samples, and five were
detected in the H samples at a low rate (Fig.2). An analysis
ER
=
X
Ai
tAo
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671Oecologia (2021) 196:667–677
1 3
focusing on sex differences for the ten compounds found no
significant differences.
Giving‑up‑densities
The effects of predation risk cue and AP on the GUDs were
similar during the first day of the experiment. Voles foraged
on average 1.25 seeds less in the PO patch (GLMM, df = 6,
P = 0.0403) compared to the C patch during the first day
(Fig.3). On the second day (Fig.3), the voles foraged overall
about 30.2% more (GLMM, df = 6, P = 0.004) but signifi-
cantly more, about 74.3% more in the AP patch (GLMM,
df = 6, P < 0.001).
Discussion
The first result in the volatile compound (VOC) analyses
shows clearly that a disturbed or scared individual smells
differently than an undisturbed control vole (Fig.1). The
grouping of the different treatments clearly shows no
overlap of the VOCs of animals from the control group
and animals from either the handling or weasel exposure
group. This simple result verifies the idea that animals can
use body odours for signalling and information exchange
between conspecifics (Flood 1992; Inagaki etal. 2009;
Wilson etal. 2018). The handling and predator-scared
groups overlap. However, the range of handling com-
pounds seems to be very narrow compared to the wider
range of possible fear compounds.
Further, our study could identify and narrow down the
list of possible VOCs, which could act as alarm phero-
mones in bank voles. We were able to identify ten com-
pounds of interest, which all appear with higher emission
rates in animals who previously encountered a weasel (P
treatment). We also were able to show that in our field
experiment, AP secretion lost their alarming function
and efficiency after just one day in the field. It seems that
after the volatile alarming compounds vanish, longer last-
ing social odours are left and, as shown in many studies
before, social odours may signal safety (Kiyokawa 2015;
Al Aïn etal. 2017) and they could attract voles for non-
risky foraging.
From our list of ten compounds of interest, most have
been previously found in animals (see Appendix3. for a
list of references) with the exception of Car-3-en-2-one,
which to our knowledge has not been found in other ani-
mals. Two of them have previously been associated with
alarm pheromones or other alarm secretions. 2-Octanone
Fig. 1 Partial Least Squares—Discriminant Analysis (PLS-DA)
based on emission rates according to treatment. Treatments: control
(C), Handling (H), and Predator (P)
Table 1 Top 10 alarm pheromone components, sorted by VIP score
The CAS identifier together with the retention time is reported for each component. P values for the Nemenyi post hoc test for each comparision
are shown
Component CAS Retention time
(minutes)
VIP score Difference C–H
(P value)
Difference C–P
(P value)
Difference
H–P (P
value)
3-octen-2-one 1669-44-9 23.433 1.897 1 0.005 < 0.001
3-methylbutanal 590-86-3 6.986 1.896 1 0.005 < 0.001
2-amylfuran 3777-69-3 21.031 1.755 1 0.01 0.002
2-octanone 111-13-7 20.957 1.755 1 0.01 0.002
camphene 79-92-5 18.898 1.753 1 0.01 0.002
3-3-5-trimethylcyclohexanol 116-02-9 24.150 1.683 0.95 0.007 0.004
Unknown compound 7 NA 31.087 1.676 0.955 0.006 0.003
1-octanol 111-87-5 25.016 1.674 0.95 0.007 0.004
Car-3-en-2-one 107493-44-7 32.243 1.649 0.861 0.003 0.004
Butyrolactone 96-48-0 16.972 1.624 0.924 0.009 0.007
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672 Oecologia (2021) 196:667–677
1 3
has been found in the alarm secretions of several ant spe-
cies (Crewe and Blum 1970a; Dumpert 1972; Brand etal.
1989) and lorises (Hagey etal. 2007). 1-Octanol has been
found in the alarm secretions of several bee species (John-
son etal. 1985; Collins etal. 1989; Hunt etal. 2003) and
stink bugs (Yamashita etal. 2016). 1-Octanol also showed
the highest emission rate of all compounds of interest in
our experiment (Fig.2), followed by unknown compound
7. We provide the experimental m/z spectra of 2-ocat-
anone, 1-octanol, and unknown compound 7, along with
the theoretical NIST spectra for 2-ocatanone and 1-octanol
in the Supplemental Material.
Evidence of interpreting heterospecific alarm cues is
well established, however only in the aquatic environment
Fig. 2 Total emission rates (ng * h−1 * vole−1) for the compounds
of interest, grouped by treatment. Treatments: control (C), Handling
(H), and Predator (P). Components in panel a, b and c are grouped by
maximum emission rates during the experiment for an easier visual
comparison. All components show significant differences between P
vs C and P vs H, see Table1 for details
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673Oecologia (2021) 196:667–677
1 3
(Briones-Fourzán etal. 2008; Vogel etal. 2017; Magellan
etal. 2019), with the exception of one termite species (Cris-
taldo etal. 2016). While there is strong evidence that phy-
logenetic closeness is a major factor (Hazlett and McLay
2005), there is evidence of cross-phyla communication
(Kaliszewicz and Uchmański 2009). In terrestrial species,
interspecies communication of alarm signals appears most
commonly with alarm calls (Templeton and Greene 2007;
Vitousek etal. 2007; Lea etal. 2008; Magrath etal. 2009).
Within vertebrates, there are examples of the ability to inter-
pret alarm calls correctly across taxonomic classes (Vitousek
etal. 2007; Lea etal. 2008).
While our experiment does not provide the data to con-
clude whether there is a common structure in alarm chemi-
cals, there is evidence from previous work permitting us to
entertain the possibility. This would be a potential expla-
nation for the occurrence of our identified compounds in,
mostly, insects. In our study, we took only into account the
major compounds to highlight potential alarm pheromone.
However, we could have missed important signals by choos-
ing this method. Indeed, it has been shown in plant–insect
interactions, that minor compounds could have an important
effect as chemical cues just like major compounds (Clavijo
Mccormick etal. 2014). To go further, a similar experiment
should be done focused on minor compounds.
A previous attempt to find a common features of olfactory
communication (in terrestrial vertebrates) concluded that the
range of compounds is widespread and bigger range of spe-
cies is needed for proper conclusions (Apps etal. 2015). We
share the assessment, as the studies on mammalian alarm
pheromones are scarce. Unlike the work by Brechbühl etal.
(2013), which found sulphur-containing compounds, our
compounds of interest did not include any nitrogen- or sul-
phur-containing chemicals. This might be partially due to a
completely different sampling method. While our method is
non-invasive, the work by Brechbühl etal. (2013) included
CO2 euthanasia to induce stress. Their results have been
challenged by (Kiyokawa etal. 2013), pointing out that
sampling from sacrificed animals results in collecting early
decay volatiles. However, work on rats identified sulphur- or
nitrogen-free chemicals as AP (Inagaki etal. 2014). Their
work, with methods comparable to ours, identified 4-meth-
ylpentanal and hexanal as potential APs, which were not part
of our compounds of interest.
While sampling from live animals allows for a greater
risk of contaminations, it also allows for more ecologically
relevant information. In our experiment, the animals were
contained, but similar methods showed the possibility to
sample from freely roaming individuals (Weiß etal. 2018).
Our methods aimed for a non- or minimal-invasive approach,
but also to apply a stimulus, i.e. predator exposure, that is
similar to a stimulus in the wild. We believe that the meth-
ods in this experiment represent a good balance between a
controlled and natural environment.
In our field experiment, no clear difference in foraging
effort was observed in the AP GUD was observed on the
first day, which is in line with our previous results (Sievert
etal. 2019). However, a clear increase in foraging effort
in AP patches after just one day, we suggest two factor for
explaining this result. First, the AP is very short-lived and
the remaining odour just signals the presence of conspecif-
ics, or, secondly, the AP becomes rapidly so diluted that it
requires a greater investigation effort (Parsons etal. 2018),
which in turn leads to the discovery of food resources in
the GUD patches and increased foraging. Either way, the
information content concerning a predator presence or risk
appears to be minimal at this point. Previous studies on bank
vole AP argued that it is secreted in cases of immediate and
acute risk (Sievert etal. 2019) and should it have an effective
alarming function, it needs a rapid transfer to other conspe-
cifics, group members or even kin. The short-lived character
of AP in the field experiment supports this idea.
While weasels are the main factor of vole mortality
(Norrdahl and Korpimäki 1995), previous work on vole-
weasel interactions has shown that, if presented with the
opportunity, bank voles prefer to take arboreal escape routes
while chased and weasels are unlikely to follow (Mäkeläinen
etal. 2014). This, or other immediate survival enhancing
responses, increase the chance for a successful escape and
lays the fundament for evolution of adaptive signalling of
conspecifics via AP.
To summarize, in this study, we adapted a new method
to identify a group of chemicals likely to serve as alarm
pheromone compounds in a common mammal species, the
bank vole. Three of those, namely 1-octanol, 2-octanone,
and unknown compound 7, are likely to be the main actors.
In the field experiment, we confirmed that the information
Fig. 3 Giving-up density by treatment. Treatments: control (C), pred-
ator odour (PO), and alarm pheromone (AP). Asterisk (*) indicates a
significant difference from control at P < 0.05. Three asterisks (***)
in this figure indicate a significant difference from the same treatment
on the previous day at P < 0.001
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
674 Oecologia (2021) 196:667–677
1 3
carried in AP is short-lived, as we were expecting if AP
functions to signal an acute and rapid event of very high
risk. Our result expands the knowledge on predator–prey
interactions and how predation risk can be communicated
to unaware conspecifics.
Supplementary Information The online version contains supplemen-
tary material available at https:// doi. org/ 10. 1007/ s00442- 021- 04977-w .
Acknowledgements We would like to thank Brigitte Weiß and Anja
Widding for discussion and advice at an early planning stage. We
would also like to thank the technical staff at the Konnevesi Research
Station for building the necessary equipment.
Author contribution statement TS, MH, JDB, AS, and HY designed
the study. TS, AS, OY and DH collected data. TS and AS performed
the analysis. TS, MH, HY, AS and JDB were involved in writing the
manuscript.
Funding Open access funding provided by University of Jyväskylä
(JYU). The study was funded by an Academy of Finland grant awarded
to HY (Project No. 288990).
Availability of data and material The R code is available from the fig-
share repository at https:// doi. org/ 10. 6084/ m9. figsh are. 13148 465 and
the raw data is available from the figshare repository at https:// doi. org/
10. 6084/ m9. figsh are. 13148 351.
Code availability The R code is available from the figshare repository
at https:// doi. org/ 10. 6084/ m9. figsh are. 13148 465.
Declarations
Conflict of interest The authors have no conflict of interest or compet-
ing interests.
Ethics approval All experiments were conducted in accordance
with institutional, European, and national guidelines. Experiments
were conducted under permission for animal experimentation from
the University of Jyväskylä No.ESAVI/6370/04.10.07/2014 granted
by the Regional State Administrative Agency for Southern Finland
(Etelä-Suomen aluehallintovirasto). Keeping weasels in captivity for
experimental use was done under the permission KESELY/2022/2015
granted by the Centre for Economic Development, Transport and the
Environment for Central Finland (Keski-Suomen ELY-keskus).
Consent to participate Not applicable.
Consent for publication Not applicable.
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long
as you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are
included in the article’s Creative Commons licence, unless indicated
otherwise in a credit line to the material. If material is not included in
the article’s Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will
need to obtain permission directly from the copyright holder. To view a
copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.
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