Article 12 web tool

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Population status and trends at the EU and Member State levels

The Article 12 web tool provides an access to EU assessments and Member States’ data compiled as part of the Habitats Directive - Article 12 reporting process. The EU assessments have been carried out in EU 27 for the period 2008-2012 and in EU28 for the period 2013-2018.

Choose period, species and if relevant sub-specific unit.

Once a selection has been made the breeding distribution of the species can be visualized in a map.

The ‘Data sheet info’ includes notes for each assessment per species.

The ‘Audit trail’ includes the methods used for the EU assessment and justifications for decisions made by the assessors.

Legend
+
Increasing
=
Stable
x
Unknown
-
Decreasing
F
Fluctuating
u
Uncertain

Codes ‘PT’, ‘ES ‘correspond to Portugal mainland (excluding Azores-PTAC and Madeira-PTMA) and Spain mainland (excluding Canary Islands-ESIC) respectively.
Similarly ‘UK’ stands for the United Kingdom of Great Britain and Northern Ireland (excluding Gibraltar-GIB).
The data from delayed delivery by Romania were not used for the EU population status assessment.

Current selection: 2013-2018, Turdus merula. Show all
Data from Member States reports
MS Breeding population Breeding distribution Winter population Breeding area from
gridded maps (km2)
Ssp. / subsp. unit
Population size Population trend Distribution size Distribution trend Population size Population trend
Min
Mouse-over texts for entries below show "Method used" reported for population size as a whole:
estimatePartial - based mainly on extrapolation from limited amount of data
estimateExpert - based mainly on expert opinion, with very limited data
absentData - insufficient or no data available
completeSurvey - complete survey or statistically robust estimate
Country Method used
AT estimatePartial
BE estimateExpert
BG estimatePartial
CY estimateExpert
CZ completeSurvey
DE completeSurvey
DK estimatePartial
EE estimateExpert
ES estimatePartial
ESIC estimateExpert
FI completeSurvey
FR estimatePartial
GIB estimatePartial
GR estimatePartial
HR estimateExpert
HU completeSurvey
IE completeSurvey
IT estimateExpert
LT estimatePartial
LU estimatePartial
LV completeSurvey
MT
NL completeSurvey
PL completeSurvey
PT estimatePartial
PTAC estimatePartial
PTMA estimatePartial
RO completeSurvey
SE estimatePartial
SI completeSurvey
SK estimatePartial
UK estimatePartial
Max
Best value Unit Type est. Change % MS ST period ST direction ST magnitude LT period LT direction LT magnitude
Mouse-over texts for entries below show "Method used" reported for distribution surface area (in km²):
estimatePartial - based mainly on extrapolation from limited amount of data
estimateExpert - based mainly on expert opinion, with very limited data
absentData - insufficient or no data available
completeSurvey - complete survey or statistically robust estimate
Country Method used
AT completeSurvey
BE completeSurvey
BG estimatePartial
CY estimatePartial
CZ completeSurvey
DE estimateExpert
DK completeSurvey
EE estimatePartial
ES completeSurvey
ESIC absentData
FI completeSurvey
FR completeSurvey
GIB estimatePartial
GR estimatePartial
HR estimateExpert
HU completeSurvey
IE completeSurvey
IT estimatePartial
LT estimatePartial
LU estimatePartial
LV completeSurvey
MT
NL completeSurvey
PL absentData
PT estimatePartial
PTAC estimatePartial
PTMA completeSurvey
RO completeSurvey
SE estimatePartial
SI absentData
SK completeSurvey
UK completeSurvey
Area
% MS ST period ST direction ST magnitude LT period LT direction LT magnitude Min
Mouse-over texts below show "Method used" reported for population size value(s):
estimatePartial - based mainly on extrapolation from limited amount of data
estimateExpert - based mainly on expert opinion, with very limited data
absentData - insufficient or no data available
completeSurvey - complete survey or statistically robust estimate
Country Method used
AT
BE
BG
CY
CZ
DE
DK
EE
ES
ESIC
FI
FR
GIB
GR estimatePartial
HR
HU
IE
IT
LT
LU
LV
MT estimateExpert
NL
PL
PT
PTAC
PTMA
RO
SE
SI
SK
UK
Max
Best value Unit Type est. Change % MS ST period ST direction ST magnitude LT period LT direction LT magnitude Status Distrib. % MS
AT
800000
1200000
N/A
p
estimate
genuine
1.7
2007-2018 = N/A | N/A | (9) 1981-2018 x N/A 92700 2.3 2007-2018 = N/A | N/A | (7) 1981-2018 x N/A 84300 2.1
BE
550400
834100
692300
p
estimate
method
#
1.2
2008-2018 - -16 | -8 | (-12) 1973-2018 + 2 | 54 | (28) # 30659 # 0.8 2008-2018 = N/A 1973-2018 = N/A 31800 0.8
BG
800000
1500000
N/A
p
estimate
noChange
2.0
2001-2018 - -30 | 0 | (N/A) 1980-2018 = 0 | 5 | (N/A) 110917 2.8 2001-2018 = 0 | 0 | (N/A) 1980-2018 = 0 | 0 | (N/A) 115700 2.9
CY
200
400
N/A
p
estimate
noChange
2007-2018 = 0 | 0 | (N/A) 1980-2018 + 500 | 1000 | (N/A) 1800 2007-2018 = 0 | 0 | (N/A) 1980-2018 + 30 | 50 | (N/A) 1800
CZ
2100000
4200000
N/A
p
estimate
noChange
#
5.4
2007-2018 + N/A | N/A | (2) 1982-2018 + N/A | N/A | (1) # 85600 2.1 2002-2016 = N/A | N/A | (0.15) 1986-2016 = N/A | N/A | (0) # 80200 2.0
DE
7900000
9550000
N/A
p
estimate
genuine
14.9
2004-2016 + 7 | 14 | (10) 1980-2016 = N/A | N/A | (11) # 356865 8.9 2004-2016 = -10 | 10 | (N/A) 1980-2016 = -30 | 40 | (N/A) 372200 9.3
DK
N/A
N/A
2094328
p
estimate
genuine
#
3.6
2006-2017 = -21 | 6.04000 | (-8.39) 1980-2017 + 7.6 | 34.96 | (20.52) # 59000 1.5 1996-2017 = N/A | N/A | (0.68) 1974-2017 = N/A | N/A | (-0.16) # 58700 1.5
EE
300000
400000
N/A
p
estimate
noChange
0.6
2007-2018 + 30 | 38 | (N/A) 1983-2018 + 37 | 55 | (N/A) 56100 1.4 2007-2018 = 1 | 2 | (N/A) 1980-2018 = 2 | 4 | (N/A) 35900 0.9
ES
8544580
10320358
N/A
p
interval
noChange
#
16.1
2007-2018 + N/A 1980-2018 + N/A 375304 9.3 2007-2018 + 1.1 | N/A | (N/A) 1980-2018 + N/A | 28.4 | (N/A) 389000 9.7
ESIC
20000
100000
N/A
p
minimum
noInfo
#
0.1
2007-2018 x N/A 1980-2018 x N/A # 7000 0.2 2007-2018 x N/A 1980-2018 x N/A # 7900 0.2
FI
550901
787694
659509
p
mean
genuine
1.1
2007-2018 + 19 | 40 | (29) 1980-2018 + 184 | 335 | (252) 227000 5.7 N/A N/A N/A 1980-2010 + 34 | 34 | (N/A) 226900 5.7
FR
5000000
8000000
N/A
p
estimate
knowledge
#
11.1
2007-2018 + N/A | N/A | (10.9) 1996-2017 = -10 | 4.5 | (3.3) # 555200 13.8 2012-2018 = 0 | 0 | (N/A) 1985-2018 = 0 | 0 | (N/A) # 549300 13.7
GIB
101
250
250
p
mean
noChange
2001-2018 = 0 | 0 | (0) 1980-2018 = 0 | 0 | (0) 5 2006-2018 = 0 | 0 | (0) 1980-2018 = 0 | 0 | (0) 200
GR
710000
900000
N/A
p
estimate
knowledge
1.4
2007-2018 = N/A 1980-2018 + N/A | N/A | (21) 193400 4.8 2007-2018 x N/A 1980-2018 x N/A 1760000 3380000 N/A i interval noChange # N/A 2007-2018 = N/A | N/A | (0) 1980-2018 x N/A other 188300 4.7
HR
1000000
3000000
N/A
p
estimate
N/A
3.4
2007-2018 x N/A 1980-2018 x N/A 56561 1.4 2007-2018 = N/A 1980-2018 = N/A 79300 2.0
HU
950000
1070000
N/A
p
interval
genuine
#
1.7
2007-2018 x N/A 1980-2018 x N/A # 93030 # 2.3 2007-2018 = N/A 1980-2018 = N/A # 94800 2.4
IE
3960070
5316172
4613945
i
interval
genuine
#
N/A
2006-2016 + 6.7 | 13 | (9.8) 1980-2016 x N/A # 84300 2.1 2006-2016 = N/A | N/A | (1) 1972-2016 = N/A | N/A | (1) # 83300 2.1
IT
2000000
5000000
N/A
p
estimate
noChange
6.0
2000-2014 + 10 | 20 | (N/A) 1993-2018 = N/A 336000 8.4 2007-2018 = N/A 1993-2018 + 5 | 10 | (N/A) 333300 8.3
LT
270000
370000
N/A
p
estimate
genuine
0.6
2013-2018 + 0 | 5 | (N/A) 1980-2018 + 5 | 10 | (N/A) 73500 1.8 2006-2018 + 0 | 5 | (N/A) 1980-2018 + 0 | 5 | (N/A) 70900 1.8
LU
40000
60000
N/A
p
estimate
noChange
#
2007-2018 = 0 | 0 | (N/A) 1980-2018 + 0 | 10 | (N/A) 1536 # 2007-2018 = 0 | 0 | (N/A) 1980-2018 = 0 | 0 | (N/A) 2400
LV
590899
708788
647165
p
interval
method
1.1
2005-2018 + 2.3 | 36.2 | (18.1) 1991-2016 + 273 | 274 | (N/A) 69900 1.7 2000-2017 = N/A | N/A | (-3) 1980-2017 = N/A | N/A | (13) 67800 1.7
MT
40 200 N/A i estimate noInfo N/A 2008-2018 + N/A | N/A | (20) 1980-2018 + N/A | N/A | (20) other
NL
650000
1100000
N/A
p
estimate
knowledge
1.5
2006-2017 = -1 | 6 | (3) 1984-2017 + 19 | 39 | (29) 45000 1.1 2000-2015 = N/A | N/A | (-0.66) 1977-2015 = N/A | N/A | (-0.88) 40700 1.0
PL
2786000
3865000
N/A
p
interval
genuine
5.7
2007-2018 + 51 | 68 | (59) 1980-2018 x N/A # N/A N/A 2007-2018 x N/A 1980-2018 x N/A N/A N/A
PT
100000
1000000
N/A
p
estimate
noChange
#
0.9
2004-2018 - N/A 1980-2018 x N/A # 89400 # 2.2 2005-2018 = N/A | N/A | (-6) 1980-2018 = N/A # 87000 2.2
PTAC
606445
820827
685599
p
mean
method
#
1.2
2007-2017 + 0.1 | 50 | (N/A) 1980-2018 x N/A # 7400 # 0.2 2008-2018 = N/A 1980-2018 x N/A # 7400 0.2
PTMA
50000
100000
N/A
p
estimate
noChange
#
0.1
2008-2018 + 36 | 54 | (N/A) 1980-2018 = N/A 1800 2001-2018 + N/A | N/A | (1) 1980-2018 + N/A | N/A | (1) # 1900
RO
2623894
3192900
N/A
p
interval
method
5.0
2008-2018 + 1 | 5 | (N/A) 1980-2018 x N/A 216000 5.4 2007-2018 = N/A 1980-2018 = N/A 212100 5.3
SE
1196000
2411000
1815000
p
estimate
noChange
3.1
2007-2018 - -10 | -2 | (-6) 1980-2018 + 21 | 38 | (29) 439800 10.9 2007-2018 = N/A 1980-2018 = N/A 439200 10.9
SI
410000
580000
N/A
p
estimate
noChange
0.8
2008-2018 = N/A | N/A | (0) 1980-2018 x N/A 15000 # 0.4 2007-2018 x N/A 1980-2018 = N/A | N/A | (3) # 13200 0.3
SK
400000
800000
N/A
p
estimate
noChange
1.0
2007-2018 = N/A 1980-2018 = N/A 49020 1.2 2007-2018 = N/A 1980-2018 = N/A 52200 1.3
UK
4807770
5274035
5040902
p
interval
genuine
8.6
2004-2016 = N/A | N/A | (2.45) 1980-2016 = N/A | N/A | (2.06000) # 285200 7.1 1989-2009 = 1.57 | 1.57 | (N/A) 1970-2009 = N/A # 283600 7.1
EU population status assessments
Breeding population Breeding distribution Winter population EU population
status
Contribution
to Target 1
Season Previous status Ssp. / subsp. unit
Population size (min) Population size (max) Unit Short-term trend Long-term trend Area Short-term trend Long-term trend Population size (min) Population size (max) Unit Short-term trend Long-term trend Breeding Wintering
EU28 47800000 71400000 p + + 3790000 NE NE Secure A B Secure Turdus merula