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Return of the bats? A prototype indicator of trends in European bat populations in underground hibernacula

Authors:
  • Amphibian and Reptile Conservation Trust, United Kingdom
  • Jasja Dekker Dierecologie

Abstract and Figures

Monitoring data on hibernating bats were aggregated for the first time across a number of European countries. These supranational trends revealed that nine out of sixteen bat species examined increased at their hibernation sites in Europe between 1993-2011, while only one is decreasing. This is reflected in the positive trend shown by a prototype multispecies bat indicator which combined the individual species trends. Our findings suggest that after a period of strong decline in the 20th century, populations of most of the investigated bat species are stabilizing or recovering, although with profound differences between European bio-geographical regions and countries. Bat populations in the Continental region have a less positive tendency, compared to those in the Atlantic region. More data from more countries may reveal whether these differences are systematical. So far, the prototype indicator covers nine countries and 16 of the 45 bat species found in Europe. The next steps will be to refine the methodology behind the indicator and to improve the indicator's representation of European bat populations and its capacity to compare trends among biogeographic regions. This should be achieved by participation of more countries and incorporating data from additional bat species, including data collected by other surveillance methods, such as summer roost counts. Robust information on trends in bat populations at a range of geographic scales is essential to the long-term conservation of bats. Further development of this indicator will make an important contribution to conservation of bats because it will stimulate international cooperation and capacity building for monitoring and research, thus exchanging and broadening knowledge of the status of bats and improving the identification of threats.
Content may be subject to copyright.
Please
cite
this
article
in
press
as:
Van
der
Meij,
T.,
et
al.,
Return
of
the
bats?
A
prototype
indicator
of
trends
in
European
bat
populations
in
underground
hibernacula.
Mammal.
Biol.
(2014),
http://dx.doi.org/10.1016/j.mambio.2014.09.004
ARTICLE IN PRESS
G Model
MAMBIO-40699;
No.
of
Pages
8
Mammalian
Biology
xxx
(2014)
xxx–xxx
Contents
lists
available
at
ScienceDirect
Mammalian
Biology
jou
rn
al
hom
epage:
www.elsevier.com/locate/mambio
Original
Investigation
Return
of
the
bats?
A
prototype
indicator
of
trends
in
European
bat
populations
in
underground
hibernacula
Thomas
Van
der
Meija,,
A.J.
Van
Striena,
K.A.
Haysomb,
J.
Dekkerc,d,
J.
Russb,
K.
Bialae,
Z.
Biharif,
E.
Jansenc,
S.
Langtonb,
A.
Kuralig,
H.
Limpensc,
A.
Meschedeh,
G.
Petersonsi,
P.
Presetnikj,
J.
Prügerk,
G.
Reiterl,
L.
Rodriguesm,
W.
Schorchtn,
M.
Uhrino,
V.
Vintulisi
aStatistics
Netherlands
(CBS),
The
Hague,
The
Netherlands
bBat
Conservation
Trust,
London,
United
Kingdom
cDutch
Mammal
Society,
Nijmegen,
The
Netherlands
dJasja
Dekker
Dierecologie,
Arnhem,
The
Netherlands
eEuropean
Environment
Agency,
Copenhagen,
Denmark
fNature
Foundation,
Tokaj,
Hungary
gNatura
Alapítvány
University
of
Debrecen,
Debrecen,
Hungary
hBavarian
Environment
Agency,
Augsburg,
Germany
iLatvian
University
of
Agriculture,
Faculty
of
Veterinary
Medicine,
Jelgava,
Latvia
jCentre
for
Cartography
of
Fauna
and
Flora,
Ljubljana,
Slovenia
kCoordination
Centre
Bat
Conservation
Thuringia
Stiftung
Fledermaus,
Erfurt,
Germany
lAustrian
Coordination
Centre
for
Bat
Conservation
and
Research
(KFFÖ),
Leonding,
Austria
mInstituto
da
Conservac¸
ão
da
Natureza
e
das
Florestas
(ICNF),
Lisboa,
Portugal
nInteressengemeinschaft
Fledermausschutz
und
-forschung
in
Thüringen
e.V.
(IFT
e.V.),
Schweina,
Germany
oInstitute
of
Biology
and
Ecology,
Faculty
of
Science,
P.
J. ˇ
Safárik
University,
Koˇ
sice,
Slovakia
a
r
t
i
c
l
e
i
n
f
o
Article
history:
Received
2
June
2014
Accepted
12
September
2014
Handled
by
Danilo
Russo
Available
online
xxx
Keywords:
Bioindicator
Chiroptera
Monitoring
Methodology
TRIM
a
b
s
t
r
a
c
t
Monitoring
data
on
hibernating
bats
were
aggregated
for
the
first
time
across
a
number
of
European
countries.
These
supranational
trends
revealed
that
nine
out
of
16
bat
species
examined
increased
at
their
hibernation
sites
in
Europe
between
1993
and
2011,
while
only
one
is
decreasing.
This
is
reflected
in
the
positive
trend
shown
by
a
prototype
multispecies
bat
indicator
which
combined
the
individual
species
trends.
Our
findings
suggest
that
after
a
period
of
strong
decline
in
the
20th
century,
populations
of
most
of
the
investigated
bat
species
are
stabilising
or
recovering,
although
with
profound
differences
between
European
bio-geographical
regions
and
countries.
Bat
populations
in
the
Continental
region
have
a
less
positive
tendency,
compared
to
those
in
the
Atlantic
region.
More
data
from
more
countries
may
reveal
whether
these
differences
are
systematical.
So
far,
the
prototype
indicator
covers
9
countries
and
16
of
the
45
bat
species
found
in
Europe.
The
next
steps
will
be
to
refine
the
methodology
behind
the
indicator
and
to
improve
the
indicator’s
representation
of
European
bat
populations
and
its
capacity
to
compare
trends
among
biogeographic
regions.
This
should
be
achieved
by
participation
of
more
countries
and
incorporating
data
from
additional
bat
species,
including
data
collected
by
other
surveillance
methods,
such
as
summer
roost
counts.
Robust
information
on
trends
in
bat
populations
at
a
range
of
geographic
scales
is
essential
to
the
long-term
conservation
of
bats.
Further
development
of
this
indicator
will
make
an
important
contribution
to
conservation
of
bats
because
it
will
stimulate
international
cooperation
and
capacity
building
for
monitoring
and
research,
thus
exchanging
and
broadening
knowledge
of
the
status
of
bats
and
improving
the
identification
of
threats.
©
2014
Deutsche
Gesellschaft
für
Säugetierkunde.
Published
by
Elsevier
GmbH.
All
rights
reserved.
Corresponding
author
at:
Postbus
24500,
2490HA
The
Hague,
The
Netherlands.
Tel.:
+31
703374212.
E-mail
address:
t.vandermeij@cbs.nl
(T.
Van
der
Meij).
Introduction
In
the
latter
half
of
the
twentieth
century
dramatic
declines
of
bat
populations
were
reported
throughout
western
Europe
(Hutson
et
al.,
2001;
Racey
and
Stebbings
1972;
Ransome,
1989;
Stebbings
1988;
Temple
and
Terry,
2007).
Some
species
even
became
locally
http://dx.doi.org/10.1016/j.mambio.2014.09.004
1616-5047/©
2014
Deutsche
Gesellschaft
für
Säugetierkunde.
Published
by
Elsevier
GmbH.
All
rights
reserved.
Please
cite
this
article
in
press
as:
Van
der
Meij,
T.,
et
al.,
Return
of
the
bats?
A
prototype
indicator
of
trends
in
European
bat
populations
in
underground
hibernacula.
Mammal.
Biol.
(2014),
http://dx.doi.org/10.1016/j.mambio.2014.09.004
ARTICLE IN PRESS
G Model
MAMBIO-40699;
No.
of
Pages
8
2
T.
Van
der
Meij
et
al.
/
Mammalian
Biology
xxx
(2014)
xxx–xxx
extinct
(Bontadina
et
al.
2000;
Haysom
et
al.
2010;
Stebbings
1988).
Declines
were
attributed
to
various
causes,
including
widespread
agricultural
intensification
and
changes
in
landscape
structure,
dis-
turbance
and
destruction
of
hibernacula
and
summer
roost
sites,
degradation
and
fragmentation
of
feeding
sites,
pesticides
used
for
remedial
timber
treatment
and
in
agriculture,
declines
of
insect
prey,
deliberate
killing
and
water
pollution
(e.g.,
Bontadina
et
al.
2000;
Brosset
et
al.,
1985;
Hutson
et
al.,
2001;
Jefferies,
1972;
Leeuwangh
and
Voûte,
1985;
Mitchell-Jones
et
al.,
1989;
Shore
et
al.,
1990;
Stebbings
and
Griffith,
1986;
Wickramasinghe
et
al.,
2003).
Concern
about
the
state
of
bat
populations
stimulated
research,
species
monitoring
and
conservation
measures
and
eventually
led
to
international
agreements,
in
particular
the
Agreement
on
the
Conservation
of
Populations
of
European
Bats
(EUROBATS,
see
Hutson,
2006)
and
the
inclusion
of
bats
in
other
protective
conser-
vation
legislation,
most
notably
their
listing
under
Annexes
II
and
IV
of
the
EU
Habitats
Directive
92/43/CEE.
The
Habitats
Directive
is
now
one
of
the
most
powerful
legal
instruments
for
biodiversity
conservation
and
an
effective
driving
force
for
nature
protection
in
the
European
Union.
Member
states
are
obliged
to
report
regularly
about
the
conservation
status
of
those
species
listed
on
its
Annexes,
including
all
European
bat
species.
Worldwide
concern
about
the
rate
and
scale
of
loss
of
habi-
tats
and
species
also
led
to
the
Convention
on
Biodiversity
(CBD)
in
1992.
Despite
setting
targets
to
reduce
the
rate
of
biodiversity
loss
significantly
at
the
global,
regional
and
national
levels
by
2010,
biodiversity
decline
has
continued.
In
2010,
the
10th
Conference
of
Parties
to
the
CBD
adopted
a
new
global
Strategic
Plan
for
Biodiver-
sity
2011–2020.
In
response,
the
EU
launched
a
new
Biodiversity
Strategy
(2011/2307).
This
strategy
aims
to
halt
biodiversity
loss
and
the
degradation
of
ecosystem
services
by
2020,
restore
ecosys-
tems,
and
make
a
contribution
to
addressing
global
biodiversity
loss.
To
monitor
progress
in
biodiversity
conservation
at
the
Pan-
European
level,
a
European
Environment
Agency
(EEA)
initiative
called
Streamlining
European
Biodiversity
Indicators
(SEBI)
estab-
lished
a
suite
of
indicators
to
provide
summary
information
on
environmental
change
for
decision
makers
and
the
public.
For
SEBI
indicator
01,
“Trends
in
abundance
and
distribution
of
selected
species”,
indicators
for
birds
and
butterflies
were
developed
since
2007
(Gregory
et
al.,
2005,
2008;
Van
Strien
et
al.,
2001;
Van
Swaay
et
al.,
2010);
however
it
was
recognised
that,
where
suitable
data
were
available,
the
indicator
set
should
be
expanded
to
incorpo-
rate
information
on
other
taxa.
Bats
had
been
proposed
previously
as
biodiversity
indicators
and
in
the
UK,
the
official
government
biodiversity
indicator
statistics
have
included
a
measure
of
the
UK
bat
population
trends
since
2008
(JNCC,
2008;
Jones
et
al.,
2009).
In
2011,
following
an
assessment
of
the
rationale
for
developing
a
bat
indicator
and
the
availability
of
bat
monitoring
data
through-
out
European
countries
(Haysom,
2008),
the
EEA
funded
a
project
to
develop
a
prototype
pan-European
bat
indicator
(Haysom
et
al.,
2014).
The
project
was
executed
by
the
Bat
Conservation
Trust,
the
Dutch
Mammal
Society
and
Statistics
Netherlands
in
cooper-
ation
with
the
coordinators
of
national
or
regional
bat
monitoring
schemes
in
9
countries.
This
paper
describes
the
methodology
used
for
constructing
the
indicator,
provides
the
results
of
a
prototype
indicator
based
on
bat
trend
data
from
9
countries,
examines
the
constituent
national
and
regional
trends
and
outlines
suggestions
for
improvements
and
further
development.
Material
and
methods
Monitoring
data
Bat
occurrence
or
abundance
data
are
available
in
many
Euro-
pean
countries
and
from
different
types
of
monitoring
programmes
Fig.
1.
Bio-geographical
grouping
of
countries
contributing
to
the
prototype
Euro-
pean
hibernating
bat
indicator.
For
this
project
the
Alpine
and
Pannonian
regions
were
merged
with
the
Continental
region.
(Battersby,
2010;
Haysom,
2008).
Large-scale
surveillance
capable
of
delivering
regional
or
national
data
usually
relies
on
a
large
net-
work
of
volunteer
surveyors,
who
are
organised
by
a
body
such
as
a
Non-Governmental
Organisation
(NGO),
often
financially
sup-
ported
by
local
or
national
governments.
Of
these
programmes,
counts
of
overwintering
bats
in
accessible
hibernacula
such
as
caves,
mines
or
cellars,
have
the
longest
history
and
are
the
most
common
and
widespread
source
of
bat
population
data
in
Europe
(Haysom,
2008).
Many
bat
species
are
faithful
to
traditional
hiber-
nation
sites
in
which
they
can
be
found
as
single
animals
or
in
small
to
very
large
cluster
sizes.
Although
usually
only
part
of
all
bats
in
a
site
can
be
counted,
the
proportion
of
counted
bats
is
assumed
to
be
stable
over
the
years.
Therefore
hibernacula
counts
are
considered
a
suitable
method
for
determining
relative
population
changes
for
22
of
the
45
European
bat
species
(Battersby,
2010).
Hibernacula
counts
were
the
most
extensive
and
readily
avail-
able
source
of
data
from
existing
surveillance
schemes.
Therefore
we
decided
to
use
these
for
the
development
of
the
prototype
pan-
European
bat
indicator.
For
species
that
overwinter
in
tree
holes
or
wall
cavities
count
data
are
scarce
and
data
from
other
surveillance
schemes
are
also
limited.
Hibernation
count
data
for
this
study
came
from
underground
sites,
mines,
cellars
and
other
man-made
structures
such
as
ice-
houses
in
9
countries:
Austria,
Germany
(Federal
States
Bavaria
and
Thuringia),
Hungary,
Latvia,
the
Netherlands,
Portugal,
Slo-
vakia,
Slovenia
and
the
United
Kingdom
(Fig.
1).
Between
them
the
10
monitoring
schemes
covered
27
species
and
represent
a
total
of
around
6000
sites,
approximately
2300
of
which
are
monitored
annually
through
a
network
of
more
than
760
surveyors
(Table
1).
Full
details
of
the
protocols
and
results
for
some
of
these
individual
monitoring
schemes
are
published
elsewhere
(e.g.,
Barlow
et
al.,
in
press;
Dijkstra
and
Korsten,
2005;
Meschede
and
Rudolph,
2010;
Presetnik
et
al.,
2011;
Tress
et
al.,
2012;
Uhrin
et
al.
2010).
From
these
countries
data
were
extracted
for
16
species
and
two
cryptic
species
groups
(see
Table
2),
covering
a
period
of
19
years
(Haysom
et
al.,
2014),
although
the
length
of
time
series
available
for
indi-
vidual
species
varied
among
countries,
ranging
between
six
and
26
years
(Table
1,
2).
The
data
were
gathered,
entered
into
databases
and
validated
and
error-checked
by
each
partner.
During
counts
at
hibernation
sites,
surveyors
identify
bats
at
the
species
level.
Some
bat
sibling
species
cannot
be
separated
reliably
Please
cite
this
article
in
press
as:
Van
der
Meij,
T.,
et
al.,
Return
of
the
bats?
A
prototype
indicator
of
trends
in
European
bat
populations
in
underground
hibernacula.
Mammal.
Biol.
(2014),
http://dx.doi.org/10.1016/j.mambio.2014.09.004
ARTICLE IN PRESS
G Model
MAMBIO-40699;
No.
of
Pages
8
T.
Van
der
Meij
et
al.
/
Mammalian
Biology
xxx
(2014)
xxx–xxx
3
Table
1
Summary
of
data
made
available
by
participating
countries
(1993
=
winter
1993/1994).
Country
Approximate
no.
of
sites
Approximate
no.
of
sites
counted
each
year
Time
series
Austria
(AT)
200
100
1993–2011
Germany
Bavaria
(DE-B)
2300
350
1993–2010
Germany
Thüringia
(DE-T)
1500
177
1993–2011
Hungary
(HU) 850
49
2005–2009
Latvia
(LV)
120
120
1993–2011
Netherlands
(NL)
1100
600
1986–2011
Portugal
(PT)
38
21
1988–2011
Slovakia
(SK)
50
50
1998–2007
Slovenia
(SI)
65
20–50
2003–2011
United
Kingdom
(UK)
617
361
1997–2011
where
they
occur
together
in
hibernacula,
because
their
identifi-
cation
by
morphological
characteristics
is
difficult
without
close
examination,
a
practice
that
is
avoided
to
minimise
disturbance
during
hibernation.
This
is
true
for
Myotis
mystacinus
and
Myotis
brandtii
and
for
Myotis
myotis
and
Myotis
blythii.
For
these
species
trends
were
produced
for
the
combined
species,
e.g.
M.
mystaci-
nus/M.
brandtii.
Furthermore,
in
some
countries,
Plecotus
austriacus
was
not
distinguished
from
Plecotus
auritus
when
there
were
only
a
few
P.
austriacus
relative
to
the
number
of
P.
auritus.
In
these
cases,
we
treated
these
records
as
representing
the
brown
long-eared
bat
alone.
Statistical
analysis
The
procedure
to
calculate
the
pan-European
bat
indicator
was
similar
to
the
methods
applied
to
the
pan-European
indicators
developed
previously
for
birds
and
butterflies
(Gregory
et
al.,
2005,
2008;
Van
Strien
et
al.,
2001;
Van
Swaay
et
al.,
2010).
The
procedure
consist
of
a
hierarchical
schedule
of
combining
analysis
results
of
the
computer
programme
TRIM
(i.e.,
time
totals,
covariants
and
standard
errors)
on
a
lower
level
to
produce
yearly
indices
and
average
yearly
change
per
species
on
a
higher
level
and
finally
com-
bining
the
results
per
species
into
a
single
multi-species
indicator.
The
successive
steps
in
this
procedure
were:
1.
Calculating
national
trends.
National
trends,
expressed
as
aver-
age
yearly
increase
or
decrease
and
annual
indices
of
species,
expressed
as
percentage
of
count
numbers
in
the
first
year,
were
computed
using
the
computer
programme
TRIM,
which
is
an
efficient
implementation
of
log-linear
regression
devel-
oped
by
Statistics
Netherlands
(Pannekoek
and
Van
Strien,
2001).
This
programme
was
developed
specifically
for
the
analysis
of
wildlife
count
data
and
offers
solutions
for
several
statistical
problems
encountered
in
animal
monitoring
by
volunteer
field
workers:
missing
data
and
under-
or
oversampling
of
certain
habitats
or
regions.
Missing
values
occur
when
sites
are
not
counted
each
year,
e.g.
because
no
volunteers
could
be
recruited
to
count
particular
sites.
Under-
or
oversampling
leads
to
poor
representativeness
and
occurs,
e.g.
because
volunteers
are
more
easily
recruited
in
some
regions
then
in
others.
If
not
taken
into
account
properly,
both
phenomena
may
lead
to
biased
trend
estimates.
TRIM
estimates
missing
values,
based
on
the
changes
in
other
sites
(Braak
et
al.,
1994).
TRIM
also
allows
the
use
of
weighting
factors
to
give
certain
sets
of
sites
higher
or
lower
weight
in
order
to
dampen
the
effects
of
oversampling
and
undersampling.
National
data
and
results
were
assumed
to
be
representative
for
the
involved
species
and
countries.
2.
Calculating
regional
trends.
The
national
data
were
then
com-
bined
into
trends
for
bio-geographical
regions
(Fig.
1).
We
did
not
combine
the
raw
data,
but
we
instead
aggregated
the
estimated
total
numbers
per
year
as
produced
in
the
first
step.
Combining
total
numbers
across
countries
is
straightforward
in
cases
where
we
restricted
the
analysis
to
a
time
period
for
which
data
were
available
for
all
countries.
The
obvious
method
is
to
add
the
esti-
mated
totals
for
each
country.
Since
the
estimates
of
the
year
totals
are
independent
between
countries,
the
variance
of
each
combined
total
is
the
sum
of
the
variances
of
the
corresponding
country
totals.
This
procedure
is
equivalent
to
applying
TRIM
to
the
raw
data
for
all
sites
from
all
countries
with
an
interac-
tion
term
country
×
year,
i.e.,
allowing
annual
indices
to
differ
Table
2
Slopes
of
individual
species
trends
calculated
for
each
country
and
for
two
bio-geographical
regions.
Trends
are
characterised
by
slope
and
standard
error
as
significant
decrease
(slope
±1.96
*
SE
<1),
significant
increase
(slope
±1.96
*
SE
>1),
stable
(slope
1.96
*
SE
>0.95
and
slope
+1.96
*
SE
<1.05)
or
uncertain
(all
others).
Significant
decrease
and
increase
are
underlined,
stable
trends
are
in
normal
font
and
uncertain
trends
are
in
italics.
Hibern.:
+hibernating
predominantly
in
underground
sites,
o
also
in
other
structures,
e.g.
trees,
wall-cavities.
Region:
A
Atlantic,
B
Boreal,
C
Continental,
M
Mediterranean;
Country
for
abbreviations
see
Table
1).
Biogeographical
region
A
M
C
B
Country
UK
NL
Combined
PT
DE
-B
DE
-T
AT
HU
SK
SI
Combined
LV
Period
Hibern.
’97–’11
’86–’11
’93–’11
’88–’11
’93–’10
’93–’11
’93–’11
’05–’09
’98–’07
’03–’11
’93–’11
’93–’11
Rhinolophus
euryale
+
1.06
1.31
0.98
0.94a
Rhinolophus
ferrumequinum
+
1.04
1.04a0.98
1.08
1.02
1.03
1.03
0.98
1.05
Rhinolophus
hipposideros +
1.05
1.05a1.04
1.04
1.16
1.07
1.10
1.07
1.05
1.07
Myotis
myotis/blythii
+
1.05
1.07
1.07
1.03
1.06
0.99
5.61
0.99
1.01
1.01
Myotis
bechsteinii
o
0.99
1.00
0.81
1.02
0.97
0.96
Myotis
nattereri
+
1.06
1.12
1.10
1.03
1.01
1.00
1.11
0.99
1.02
1.02
Myotis
mystacinus/brandtii
+
1.03
1.06
1.05
1.05
1.08
1.30
0.99
1.00
1.06
1.08
Myotis
emarginatus
+
1.13
1.13
0.92
1.99
1.08
1.00a
Myotis
dasycneme
+
1.05
1.04
0.91
1.11
0.99a0.98
Myotis
daubentonii
o
1.01
1.03
1.02
1.04
1.00
0.97
1.12
0.98
1.02
1.05
Eptesicus
nilssonii
o
0.99
1.03
1.11
1.12
1.04
1.00
Eptesicus
serotinus
o
1.01
1.03
1.04
0.91
1.0
Plecotus
auritus
o
1.00
1.03
1.00
0.99
0.98
0.97
1.21
0.95
0.98
0.97
Plecotus
austriacus
o
0.96
0.88
1.32
0.83
0.92
Barbastella
barbastellus
o
1.04
1.03
1.05
1.09
0.95
0.94
1.04
Miniopterus
schreibersii
+
0.99
0.95
1.54
0.97
aBased
on
a
shorter
period
because
of
data
availability:
Continental
M.
dasycneme
and
R.
euryale
1998–2009;
Continental
M.
emarginatus
1998–2011;
Atlantic
R.
ferrume-
quinum
and
R.
hipposideros
1997–2011
Please
cite
this
article
in
press
as:
Van
der
Meij,
T.,
et
al.,
Return
of
the
bats?
A
prototype
indicator
of
trends
in
European
bat
populations
in
underground
hibernacula.
Mammal.
Biol.
(2014),
http://dx.doi.org/10.1016/j.mambio.2014.09.004
ARTICLE IN PRESS
G Model
MAMBIO-40699;
No.
of
Pages
8
4
T.
Van
der
Meij
et
al.
/
Mammalian
Biology
xxx
(2014)
xxx–xxx
between
countries.
Combing
the
estimated
total
numbers
per
country
therefore
produces
exactly
the
same
estimates
of
com-
bined
year
totals
as
analysing
the
raw
data
and
their
standard
errors
are
also
equal.
Unfortunately,
the
monitoring
schemes
differ
in
years
covered
and
the
missing
year
totals
for
certain
countries
make
combi-
nation
of
year
totals
more
complicated.
The
missing
year
totals
were
estimated
by
TRIM
in
a
way
equivalent
to
imputing
miss-
ing
counts
for
particular
sites,
but
the
estimation
procedure
was
slightly
different
and
incorporated
the
standard
errors
and
covariances
of
the
year
totals
per
country
(Van
Strien
et
al.,
2001).
This
procedure
has
the
advantage
that
national
coordinators
do
not
need
to
share
their
raw
data
but
only
the
results
of
apply-
ing
TRIM.
In
addition
to
the
benefit
of
generating
national
results
in
the
first
step,
this
circumvents
any
concerns
about
the
use
of
raw
data
by
anyone
other
than
the
owners
in
the
country
of
ori-
gin.
Hibernacula
sites
are
sensitive
and
so
sometimes
locations
and
number
of
species
are
kept
secret.
Due
to
natural
variation
in
species
distribution
and
surveil-
lance
history,
not
all
nations
have
data
for
each
species
for
the
same
time
period.
So
estimation
of
missing
data
is
also
needed
to
generate
complete
time
totals
for
each
country,
species
and
year
within
the
bio-geographic
regions.
These
missing
values
were
again
imputed
by
TRIM,
but
to
avoid
imputing
values
based
on
data
from
too
few
countries,
the
time
period
for
calculation
of
supranational
trends
was
shortened
to
1993–2011.
For
every
year
in
this
period
data
from
at
least
5
countries
and
14
species
were
available
(Fig.
2).
3.
Calculating
European
species
trends.
The
output
of
those
regions
was
used
as
input
for
equivalent
calculations
at
a
pan-
European
level.
Again
estimation
is
needed
to
generate
complete
time
totals.
In
this
case
for
every
bio-geographic
region,
species
and
year
at
a
European
scale.
4.
Constructing
the
indicator.
Finally
a
single
pan-European
indicator
for
bats
was
calculated
by
taking
the
geometric
means
of
the
European
indices
of
individual
species
as
described
by
Gregory
et
al.
(2005)
and
Van
Strien
et
al.
(2011).
We
also
calculated
combined
species
indicators
for
the
Atlantic
and
Continental
region
in
the
same
way
(Fig.
1).
Combined
indicators
for
the
Boreal
and
Mediterranean
region
were
not
calculated
because
both
regions
are
represented
by
one
country
only.
Biogeographic
regions
were
taken
according
to
Euro-
pean
Environment
Agency
(http://www.eea.europa.eu/data-
and-maps/figures/biogeographical-regions-in-europe-1),
and
each
country
was
assigned
only
to
one
region,
even
though
some
actually
lie
in
more
than
one
(e.g.,
Slovenia,
Austria).
This
was
done
because
we
started
with
national
trends
and
could
not
split
these
in
trends
for
regions
within
countries.
Weighting
factors
Differences
in
methodology
and/or
sampling
strategy
per
coun-
try
ensure
that
in
every
country
a
different
proportion
of
the
total
population
is
counted.
An
intensive
monitoring
scheme
may
result
in
relatively
high
count
numbers
in
countries
with
a
small
popu-
lation.
The
contribution
to
the
pan-European
trend
of
a
species
of
a
country
with
a
large
population
of
this
species
should
be
bigger
than
the
contribution
of
countries
with
a
small
population.
Rather
than
giving
each
country
an
equal
influence
on
the
overall
trend
we
wanted
to
correct
count
results
per
country
by
weighting
factors
in
such
a
way
that
they
reflected
differences
in
the
population
sizes
of
each
country.
Weighting
factors
are
needed
both
for
combining
national
trends
to
generate
bio-geographical
region
trends
and
for
combining
regional
trends
to
pan-European
trends.
Weighting
fac-
tors
to
correct
for
over-
or
under-sampling
within
a
country
may
also
be
needed,
but
fall
beyond
the
scope
of
our
study.
Using
weighting
factors
based
on
exact
or
relative
population
sizes
would
be
ideal,
but
unfortunately
reliable
estimates
of
popu-
lation
sizes
of
bat
species
in
each
country
are
rarely
available.
As
a
suitable
alternative
for
calculating
the
weighting
factors
based
on
population
sizes
we
used
the
range
of
each
bat
species
as
com-
piled
in
the
IUCN
Red
List
of
Threatened
Species
(IUCN,
2010).
These
ranges
are
drawn
from
various
sources
and
reviewed
by
bat
experts,
and
these
data
are
in
the
public
domain.
Further
infor-
mation
on
the
methodology
for
compiling
these
data
is
available
at
http://www.iucnredlist.org
online.
For
political
boundaries,
we
used
Vector
Map
VMAP0
(NIMA,
2010).
This
is
a
vector-based
col-
lection
of
geographic
data
developed
by
the
National
Imagery
and
Mapping
Agency
from
the
United
States,
which
is
also
available
in
the
public
domain.
The
weighting
factor
for
each
species–country
combination
was
defined
as
the
proportion
of
the
range
of
that
species
in
that
country.
In
combining
the
pan-European
trends
of
each
species
into
a
single
indicator
no
weighting
was
applied;
each
species
counted
equally.
Selecting
a
group
of
species
or
giving
more
weight
to
certain
species
may
be
considered
if
for
instance
special
attention
is
needed
for
red
list
species
or
typical
forest
dwelling
species.
Fig.
2.
Schematic
representation
of
European
indicator
construction.
Please
cite
this
article
in
press
as:
Van
der
Meij,
T.,
et
al.,
Return
of
the
bats?
A
prototype
indicator
of
trends
in
European
bat
populations
in
underground
hibernacula.
Mammal.
Biol.
(2014),
http://dx.doi.org/10.1016/j.mambio.2014.09.004
ARTICLE IN PRESS
G Model
MAMBIO-40699;
No.
of
Pages
8
T.
Van
der
Meij
et
al.
/
Mammalian
Biology
xxx
(2014)
xxx–xxx
5
Table
3
Slope,
number
of
hibernation
sites
in
which
the
species
was
observed,
and
trend
of
species
for
the
combined
countries
(see
Table
2
for
definition
of
trends).
Species
Slope
Trend
Error
of
slope
Number
of
sites
Rhinolophus
euryale
1.08
Increase
0.03
37
Rhinolophus
ferrumequinum 1.04 Increase
0.01
272
Rhinolophus
hipposideros
1.06
Increase
0.01
619
Myotis
myotis/blythii
(oxygnathus)
1.02
Increase
0.00
1748
Myotis
bechsteinii
0.96
Uncertain
0.04
500
Myotis
nattereri
1.05
Increase
0.01
2066
Myotis
mystacinus/brandtii
1.06
Increase
0.00
1506
Myotis
emarginatus
1.08
Increase
0.02
111
Myotis
dasycneme 1.00 Stable
0.01 230
Myotis
daubentonii
1.02
Increase
0.00
2125
Eptesicus
nilssonii
1.03
Uncertain
0.02
309
Eptesicus
serotinus
1.02
Stable
0.01
201
Plecotus
auritus
0.99
Stable
0.01
3655
Plecotus
austriacus
0.91
Decline
0.03
399
Barbastella
barbastellus
1.04
Increase
0.01
973
Miniopterus
schreibersi
1.00
Stable
0.01
44
Results
National
trends
Results
of
trends
for
individual
species
do
not
show
striking
differences
between
countries
(see
Table
2).
Most
species
show
an
increasing
population
trend
in
more
than
one
country
and
do
not
show
the
opposite
trend
in
other
countries.
For
one
species,
P.
austriacus,
significant
trends
are
only
declining.
Only
three
species
have
opposing
trends:
Barbastella
barbastellus,
P.
auritus
and
Rhi-
nolophus
ferrumequinum.
Remarkably
all
but
one
declining
trends
of
species
are
found
in
continental
countries.
The
number
of
species
with
uncertain
trends
showed
much
variation
between
countries.
Whereas
the
United
Kingdom,
the
Netherlands,
Thuringia
and
Latvia
had
no
uncertain
trends
at
all,
Austria,
Hungary
and
Slovakia
had
uncertain
trends
for
at
least
seven
species.
Differences
between
trends
of
individual
species
are
large
in
the
countries
in
the
Continental
region.
While
Hungary
has
the
highest
but
uncertain
average
trend
of
all
countries,
its
neighbours
Slovenia
and
Austria
have
the
low-
est.
Biogeographic
trends
In
the
Atlantic
region
eight
out
of
nine
species
had
increas-
ing
population
trends
at
their
hibernation
sites
while
none
were
observed
to
decline.
In
contrast,
only
six
of
16
species
in
the
Con-
tinental
region
increased
while
one
species,
P.
austriacus,
declined.
Tests
for
differences
in
slope
for
the
nine
species
for
which
both
Continental
and
Atlantic
region
trends
were
produced
sug-
gested
smaller
increases
in
the
Continental
region
(n
=
9;
paired
t-test;
p
=
0.09).
The
difference
was
greatest
for
Myotis
and
Plecotus
species
(n
=
7;
paired
t-test;
p
=
0.04)
but
there
was
no
signif-
icant
difference
between
the
regions
for
the
two
Rhinolophus
species.
Yearly
combined
species
indicators
for
these
regions,
calculated
as
geometric
averages
of
the
indices
for
each
species
in
each
year,
show
the
differences
between
the
Atlantic
and
Continental
region
(Fig.
3).
The
most
remarkable
difference
is
the
opposite
trends
in
2003–2011,
where
the
Atlantic
region
has
an
ongoing
increase
while
in
the
Continental
region
the
increase
of
the
first
ten
years
is
entirely
offset
by
a
decrease
after
2003.
European
trends
and
indicator
The
final
combination
of
trends
at
the
European
level
resulted
in
nine
species
with
a
significant
positive
trend.
Only
P.
aus-
triacus
showed
a
moderate
decline
(Table
3).
For
two
species,
Myotis
bechsteinii
and
Eptesicus
nilssonii,
no
European
trend
could
be
determined,
probably
due
to
high
between-year
vari-
ation.
Four
species
appeared
to
be
stable
(Haysom
et
al.,
2013).
The
prototype
of
the
European
bat
indicator,
calculated
by
taking
the
geometric
means
of
the
indices
for
all
16
species,
showed
a
positive
trend
for
bats
as
a
group
in
the
time
period
1993–2011
(Fig.
3).
Since
2000
the
trend
seems
rather
stable,
but
has
a
marked
dip
in
2007
(Fig.
4).
Fig.
3.
Combined
species
population
trends
for
two
bio-geographic
regions.
Con-
tinental
(9
species)
is
based
on
a
subset
of
9
Continental
species,
matching
the
9
species
in
the
Atlantic
region
(slopes:
Atlantic:
1.05;
Continental:
1.00;
Continental,
9
species:
1.02).
Fig.
4.
The
prototype
of
the
European
indicator
of
trends
in
bat
populations,
based
on
hibernacula
counts
in
9
countries
(slope:
1.02).
Please
cite
this
article
in
press
as:
Van
der
Meij,
T.,
et
al.,
Return
of
the
bats?
A
prototype
indicator
of
trends
in
European
bat
populations
in
underground
hibernacula.
Mammal.
Biol.
(2014),
http://dx.doi.org/10.1016/j.mambio.2014.09.004
ARTICLE IN PRESS
G Model
MAMBIO-40699;
No.
of
Pages
8
6
T.
Van
der
Meij
et
al.
/
Mammalian
Biology
xxx
(2014)
xxx–xxx
Conclusions
and
discussion
The
pan-European
indicator
shows
that
bat
populations
on
aver-
age
have
increased
at
hibernation
sites
between
1993
and
2011.
Although
not
all
species
and
regions
show
an
equally
positive
trend,
and
more
recently
the
trend
is
flattening,
this
result
sug-
gests
that
bats
may
have
recovered
partly
from
the
massive
decline
reported
during
the
latter
half
of
the
twentieth
century.
This
there-
fore
also
suggests
that
targeted
conservation
policies
may
have
been
successful.
There
are
some
caveats
in
our
study
however,
so
the
conclusion
that
bat
populations
are
increasing
should
be
treated
with
some
caution.
In
the
first
place,
we
should
note
that
the
indicator
does
not
include
data
from
all
European
countries
and
bio-geographic
regions,
nor
does
it
represent
the
majority
of
European
bat
species.
The
robustness
of
the
indicator
would
be
much
improved
by
expanding
it
to
cover
a
greater
proportion
of
Europe,
so
that
it
can
become
more
representative
of
both
Europe
and
its
component
regions.
Although
we
know
of
up
to
20
countries
with
poten-
tially
suitable
survey
data,
time
and
budget
restrictions
during
the
project
limited
the
number
of
participation
countries
to
9.
The
pro-
cess
of
grouping
countries
into
bio-geographic
ranges
was
rather
constrained,
with
Portugal
being
the
only
Mediterranean
country,
Latvia
the
only
Boreal
country
and
countries
with
parts
in
Con-
tinental,
Alpine
and
Pannonian
regions
classified
together
as
one
Continental
region.
But
the
differences
in
the
trends
between
only
two
bio-geographic
regions
Atlantic
and
Continental
which
are
not
yet
understood
indicate
the
potential
of
our
data
to
detect
conservation
issues
at
the
regional
scale.
Although
incorporating
data
from
more
countries
is
definitely
required,
the
impact
on
the
combined
European
trends
of
each
species
and
the
combined
indicator
may
not
be
substantial.
If
the
trends
in
newly
added
countries
were
found
to
diverge
as
little
as
those
that
have
already
been
incorporated,
we
would
expect
the
expanded
overall
indicator
to
remain
positive.
Since
it
is
unsatisfactory
to
speculate,
recruiting
additional
countries
would
contribute
to
the
robustness
of
the
indicator
and
is
therefore
a
major
goal
for
the
next
update.
Although
trends
and
indices
for
species
generally
indicate
that
bat
populations
have
increased
and
national
species
population
trends
generally
point
in
the
same
direction,
species
trends
in
the
Continental
region
show
more
variability
and
are
often
uncertain.
The
uncertainty
is
probably
caused
when
national
species
trends
are
calculated
from
relatively
few
data,
from
a
limited
number
of
sites
and
a
limited
number
of
years
(e.g.,
Hungary,
Slovenia),
in
combination
with
a
high
variance
in
counts
and
site
characteristics.
This
may
lead
to
outliers
such
as
the
slope
value
of
5.61
(Table
2)
for
M.
myotis/blythii
in
Hungary.
Such
outliers
may
potentially
have
a
large
influence
on
overall
trends,
but
the
fact
that
this
is
based
on
a
small
sample
of
European
bat
populations
data
largely
prevents
this.
The
Continental
trend
for
M.
myotis/blythii
(slope
value
1.01,
Table
2)
would
only
have
been
0.0045
lower
without
the
input
of
Hungary,
changing
it
from
a
mild
increase
to
a
stable
trend.
A
response
to
the
uncertainty
of
some
national
species
trends
could
be
to
exclude
these
from
the
overall
European
Indicator.
However,
on
the
European
level
the
inclusion
of
more
data
leads
to
smaller
standard
errors
and
a
more
reliable
outcome,
hence
the
decision
to
include
data
of
species
with
uncertain
trends
on
a
national
level.
High
standard
errors
and
uncertain
trends
on
a
national
level
are
of
course
undesirable
for
the
countries
concerned
and
should
be
a
stimulus
to
improve
monitoring
schemes
and/or
gaining
more
data.
The
reasons
behind
the
larger
differences
between
national
trends
(e.g.,
B.
barbastellus,
Table
2)
in
the
Continental
region
are
unknown.
Due
to
the
inclusion
of
Alpine
and
Pannonian
regions,
the
Continental
region
is
likely
to
be
more
heterogeneous
than
the
other
regions
while
especially
Alpine
hibernacula
are
difficult
to
monitor
because
of
the
inaccessibility
of
many
sites.
Differences
in
habitat
management,
landscape,
agricultural
practices
or
other
potential
drivers
may
also
be
important,
but
more
investigation
is
required
to
understand
the
mechanisms
behind
these
differences.
One
of
the
weaknesses
of
this
study
is
the
rather
crude
weighting
procedure,
based
on
distribution
area
alone.
Hibernacula
are
often
located
at
different
and
sometimes
distant
locations
from
summer
colonies
so
migration
and
seasonal
differences
in
distribution
and
density
are
common
phenomena
among
bats.
The
methodology
does
not
take
these
differences
into
account
and
could
certainly
be
improved
with
a
weighting
procedure
that
is
better
equipped
to
take
these
differences
into
account.
Despite
that,
we
would
not
expect
a
refinement
of
the
weighting
procedure
to
affect
the
overall
conclusion
that
populations
of
some
species
studied
within
this
area
have
increased,
because
trends
in
different
countries
generally
point
in
the
same
direction.
Different
weighting
factors
can
change
the
relative
influence
of
trends
from
a
country,
but
they
do
not
change
the
direction
of
trends.
The
prototype
indicator
only
uses
data
from
counts
in
hibernac-
ula
that
are
accessible
to
people.
The
species
observed
represent
approximately
40%
of
the
European
bat
fauna
and
64%
of
the
species
that
Battersby
(2010)
considered
generally
suited
to
surveillance
in
this
kind
of
hibernacula.
Nine
of
the
16
species
used
in
the
indicator
hibernate
predominantly
in
underground
sites.
The
other
seven
species
also
hibernate
in
other
much
less
accessible
struc-
tures
such
as
trees
and
wall
cavities
that
cannot
generally
be
surveyed
(Dietz
et
al.,
2009).
However,
only
anecdotal
evidence
is
available
as
regards
the
proportions
of
animals
hibernating
in
over-
ground
(hard
to
count)
sites
and
in
underground
(easier
to
survey)
sites,
let
alone
how
stable
these
proportions
are.
On
top
of
that,
hibernation
behaviour
is
also
influenced
by
climate
and
weather
conditions.
The
resulting
indicator
is
therefore
biased
towards
trends
for
species
that
predominantly
hibernate
in
man-accessible
hibernacula.
Species
that
use
other
types
of
hibernacula,
have
dif-
ferent
ecology
or
behaviour
and
may
be
subject
to
other
influences.
As
a
consequence,
they
may
show
different
population
trends.
The
best
way
of
addressing
this
potential
bias
would
be
to
incorpo-
rate
data
from
other
monitoring
approaches
such
as
summer
roosts
counts
or
bat
detector
surveys.
Since
methods
of
surveillance
vary
in
their
suitability
for
each
species
and
since
all
methods
bring
potential
biases
(Battersby,
2010),
integrating
different
types
of
data
may
increase
certainty
in
the
European
species
trends
and
the
overall
indicator.
Incorporation
of
data
from
different
methods
within
the
framework
of
the
indicator
is
not
a
technical
problem
and
data
from
such
surveys
are
already
available
(Battersby,
2010;
Haysom,
2008).
But
including
these
data
requires
careful
selection
of
suitable
monitoring
methods
for
each
species
and
country
and
may
require
different
weight
factors
for
each
method.
For
instance
one
of
the
challenging
aspects
of
combining
summer
and
winter
counts
is
whether
and
how
to
combine
those
for
migrating
bats.
Can
summer
counts
of
a
species
be
combined
with
winter
counts
of
the
same
species
if
we
only
have
summer
counts
in
one
country
and
winter
counts
in
another?
Incorporating
data
for
more
species
and
from
other
methods
is
another
major
goal
for
the
next
version
of
the
indicator.
In
the
next
update
of
the
indicator
special
attention
is
needed
regarding
the
treatment
of
data
on
rare
species
or
species
recorded
at
small
numbers
of
sites
with
a
high
variability
in
number
of
bats
counted
(e.g.,
Rhinolophus
euryale,
Miniopterus
schreibersi).
For
such
species,
the
indices
may
be
heavily
affected
by
artefacts
in
survey
methodology
or
occasional
outliers.
For
example,
some
peaks
in
the
trend
of
R.
euryale
may
be
due
to
recent
discoveries
of
new
chambers
in
a
large
hibernaculum.
Such
species-specific
peaks
in
the
data
do
not
have
a
great
impact
on
the
indicator
trend,
unless
this
occurs
for
a
species
that
has
a
limited
range
or
when
very
few