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, Garrulus glandarius. 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 estimatePartial
CZ completeSurvey
DE completeSurvey
DK estimatePartial
EE estimateExpert
ES estimatePartial
FI completeSurvey
FR estimatePartial
GR estimatePartial
HR estimateExpert
HU completeSurvey
IE estimateExpert
IT estimateExpert
LT estimatePartial
LU estimatePartial
LV completeSurvey
NL completeSurvey
PL completeSurvey
PT 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
FI completeSurvey
FR completeSurvey
GR estimatePartial
HR estimateExpert
HU completeSurvey
IE completeSurvey
IT estimatePartial
LT estimatePartial
LU estimatePartial
LV completeSurvey
NL completeSurvey
PL absentData
PT estimatePartial
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
FI
FR
GR
HR
HU
IE
IT
LT
LU
LV
NL
PL
PT
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
20000
35000
N/A
p
estimate
method
0.5
2007-2018 = N/A | N/A | (9) 1981-2018 x N/A 89800 2.6 2007-2018 + N/A | N/A | (14) 1981-2018 x N/A 83300 2.4
BE
39900
77300
58600
p
estimate
genuine
1.0
2008-2018 - -28 | -3 | (-17) 1973-2018 + 81 | 251 | (166) # 30659 # 0.9 2008-2018 = N/A 1973-2018 = N/A 31600 0.9
BG
100000
200000
N/A
p
estimate
noChange
2.5
2000-2018 = 0 | 0 | (N/A) 1980-2018 = 0 | 0 | (N/A) 104993 3.1 2000-2018 = 0 | 0 | (N/A) 1980-2018 = 0 | 0 | (N/A) 109200 3.2
CY
4700
8200
N/A
p
estimate
genuine
0.1
2007-2018 + 2 | 56 | (N/A) 1980-2018 x N/A 2300 2007-2018 = 0 | 0 | (N/A) 1980-2018 = 0 | 0 | (N/A) 2300
CZ
180000
360000
N/A
p
estimate
noChange
#
4.5
2007-2018 = N/A | N/A | (-1) 1982-2018 + N/A | N/A | (2) # 83700 2.4 2002-2016 = N/A | N/A | (0.48) 1986-2016 = N/A | N/A | (2.11) # 79100 2.3
DE
510000
690000
N/A
p
estimate
genuine
10.0
2004-2016 = -7 | 16 | (4) 1980-2016 = N/A | N/A | (11) 355370 10.4 2004-2016 = -10 | 10 | (0) 1980-2016 = -30 | 40 | (N/A) 367500 10.8
DK
N/A
N/A
35274
p
estimate
genuine
#
0.6
2006-2017 - -47.91 | -21.59 | (-35.98) 1980-2017 - -28.7 | -2.49 | (-16.59) # 47900 1.4 1996-2017 = N/A | N/A | (-5.33) 1974-2017 = N/A | N/A | (-7.64) # 47800 1.4
EE
30000
50000
N/A
p
estimate
noChange
0.7
2007-2018 = -14 | 41 | (N/A) 1983-2018 + 208 | 291 | (N/A) 49300 1.4 2007-2018 = N/A | N/A | (-2) 1980-2018 = N/A | N/A | (-3) 17300 0.5
ES
1032159
1522538
N/A
p
interval
knowledge
#
21.3
2007-2018 = N/A 1980-2018 + N/A 212147 6.2 2007-2018 + N/A | N/A | (55.54) 1980-2018 + 26 | N/A | (N/A) 221800 6.5
FI
91105
141447
112165
p
mean
genuine
1.9
2007-2018 = -27 | 6 | (-11) 1980-2018 - 11 | 52 | (35) 192400 5.6 N/A N/A N/A 1980-2010 + 8 | 8 | (N/A) 192200 5.6
FR
400000
1000000
N/A
p
estimate
noChange
11.7
2007-2018 = N/A | N/A | (-1.1) 2001-2018 + N/A | N/A | (11) 507000 14.8 2009-2017 = N/A 1985-2017 = N/A 502400 14.7
GR
40000
70000
N/A
p
estimate
knowledge
0.9
2007-2018 + N/A | N/A | (57) 1980-2018 = N/A 142600 4.2 2007-2018 x N/A 1980-2018 x N/A 133700 3.9
HR
N/A
N/A
26800
i
mean
N/A
#
N/A
2007-2018 x N/A 1980-2018 x N/A 47213 # 1.4 2007-2018 x N/A 1980-2018 x N/A 71300 2.1
HU
66000
80000
N/A
p
interval
genuine
#
1.2
2007-2018 = N/A 1980-2018 + 45 | 125 | (N/A) 93011 2.7 2007-2018 = N/A 1980-2018 = N/A # 95800 2.8
IE
5000
14999
N/A
p
estimate
noChange
#
0.2
2000-2011 x N/A 1980-2011 x N/A # 42400 # 1.2 1991-2011 + N/A | N/A | (96) 1972-2011 + N/A | N/A | (19) # 41800 1.2
IT
300000
600000
N/A
p
estimate
noChange
7.5
2000-2014 + 5 | 15 | (N/A) 1993-2018 + 200 | 500 | (N/A) 267900 7.8 2007-2018 - -10 | -5 | (N/A) 1993-2018 + 25 | 30 | (N/A) 267000 7.8
LT
50000
80000
N/A
p
estimate
noChange
1.1
2013-2018 = N/A 1980-2018 + 5 | 10 | (N/A) 73500 2.1 2006-2018 = 0 | 0 | (N/A) 1980-2012 = 0 | 0 | (N/A) 71400 2.1
LU
3000
4000
N/A
p
estimate
noChange
#
2009-2018 u -40 | 40 | (N/A) 1980-2018 x N/A 1352 # 2007-2018 = 0 | 0 | (N/A) 1980-2018 = 0 | 0 | (N/A) 2400
LV
138149
232089
179061
p
interval
method
3.0
2005-2018 = -9.9 | 52.1 | (17.4) 1991-2016 + 531 | 536 | (N/A) 64700 1.9 2000-2017 = N/A | N/A | (-2) 1980-2017 = N/A | N/A | (18) 63200 1.9
NL
45000
65000
N/A
p
estimate
knowledge
0.9
2006-2017 = -8 | 8 | (-1) 1984-2017 = -6 | 31 | (11) 43400 1.3 2000-2015 = N/A | N/A | (-0.22) 1977-2015 + N/A | N/A | (14.21) 39500 1.2
PL
546000
664000
N/A
p
interval
genuine
10.1
2007-2018 + 6 | 30 | (17) 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
500000
N/A
p
estimate
noChange
#
5.0
2004-2018 = N/A 1980-2018 x N/A 72600 # 2.1 2005-2018 = N/A | N/A | (-21) 1980-2018 = N/A # 70800 2.1
RO
338014
490700
N/A
p
interval
method
6.9
2008-2018 = -4 | 3 | (N/A) 1980-2018 x N/A 202000 5.9 2007-2018 = N/A 1980-2018 x N/A 199100 5.8
SE
178000
407000
294000
p
estimate
noChange
4.9
2007-2018 = -16 | 1 | (-8) 1980-2018 - -44 | -26 | (-36) 437300 12.7 2007-2018 = N/A 1980-2018 = N/A 436700 12.8
SI
20000
30000
N/A
p
estimate
noChange
0.4
2008-2018 = N/A | N/A | (0) 1980-2018 x N/A 10700 # 0.3 2007-2018 x N/A 1980-2018 = N/A | N/A | (18) # 9100 0.3
SK
12500
25000
N/A
p
estimate
genuine
0.3
2007-2018 - -40 | -20 | (N/A) 1980-2018 - -40 | -20 | (N/A) 47610 1.4 2007-2018 = N/A 1980-2018 = N/A 50700 1.5
UK
N/A
N/A
170727
p
estimate
genuine
#
2.9
2004-2016 = N/A | N/A | (4.93) 1980-2016 = N/A | N/A | (5.93) # 209800 6.1 1989-2009 + 18.2 | 18.2 | (N/A) 1970-2009 + 17.4 | 17.4 | (N/A) 208400 6.1
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 4130000 7080000 p = + 3220000 NE NE Secure A B Secure Garrulus glandarius