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.

Warning: The map does not show the distribution for sensitive species in LT

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.

Sensitive spatial information for this species is not shown in the map. Current selection: 2013-2018, Lullula arborea. 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 completeSurvey
BE estimatePartial
BG estimatePartial
CY estimateExpert
CZ completeSurvey
DE completeSurvey
DK estimateExpert
EE estimatePartial
ES estimatePartial
FI estimatePartial
FR estimatePartial
GR estimatePartial
HR estimatePartial
HU completeSurvey
IT estimateExpert
LT estimatePartial
LU completeSurvey
LV completeSurvey
NL completeSurvey
PL completeSurvey
PT estimatePartial
RO completeSurvey
SE estimatePartial
SI completeSurvey
SK estimateExpert
UK completeSurvey
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 estimateExpert
CZ completeSurvey
DE estimateExpert
DK completeSurvey
EE estimatePartial
ES completeSurvey
FI completeSurvey
FR completeSurvey
GR estimatePartial
HR completeSurvey
HU completeSurvey
IT estimatePartial
LT estimatePartial
LU completeSurvey
LV completeSurvey
NL completeSurvey
PL absentData
PT estimatePartial
RO completeSurvey
SE estimatePartial
SI estimateExpert
SK estimateExpert
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
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
1100
1800
N/A
p
estimate
method
2007-2018 x N/A 1981-2018 + 20 | 100 | (N/A) 12300 0.7 2007-2018 = N/A | N/A | (10) 1981-2018 = N/A | N/A | (0) 11800 0.7
BE
1200
2000
1600
p
estimate
genuine
2008-2018 + 60 | 167 | (113) 1973-2018 + 471 | 852 | (662) 15280 # 0.9 2008-2018 + N/A | N/A | (90.07000) 1973-2018 + N/A | N/A | (150.78) 20000 1.2
BG
40000
90000
N/A
p
estimate
knowledge
2.6
2001-2018 + 10 | 20 | (N/A) 1980-2018 = 0 | 0 | (N/A) 87747 5.1 2001-2018 = 0 | 0 | (N/A) 1980-2018 = 0 | 0 | (N/A) 92400 5.3
CY
1000
2500
N/A
p
estimate
genuine
2007-2018 + 14 | 25 | (N/A) 1980-2018 x N/A 1800 0.1 2007-2018 = 0 | 0 | (N/A) 1980-2018 = 0 | 0 | (N/A) 1800 0.1
CZ
600
1000
N/A
p
estimate
noChange
2007-2018 x N/A 1980-2018 x N/A # 28500 1.6 2002-2016 + N/A | N/A | (31.79) 1986-2016 + N/A | N/A | (56.7) # 27900 1.6
DE
27000
47000
N/A
p
estimate
genuine
1.5
2004-2016 - -29 | -10 | (-20) 1980-2016 = -30 | 40 | (0) 164254 9.5 2004-2016 + 11 | 40 | (N/A) 1980-2016 = -30 | 40 | (0) 168800 9.8
DK
350
450
N/A
p
estimate
noChange
2004-2017 = N/A 1980-2017 = N/A 19300 1.1 1996-2017 + N/A | N/A | (101) 1974-2017 + N/A | N/A | (84) # 19000 1.1
EE
3000
6000
N/A
p
estimate
method
#
0.2
2007-2018 - -39 | -12 | (N/A) 1983-2018 - -109 | -90 | (N/A) 41100 2.4 2007-2018 = 4 | 6 | (N/A) 1980-2018 = 8 | 9 | (N/A) 19400 1.1
ES
921447
1402781
N/A
p
interval
genuine
#
47.1
2007-2018 + N/A | 1.6 | (0.7) 1980-2018 + N/A | N/A | (10) 183388 10.6 2007-2018 + 5 | N/A | (N/A) 1980-2018 = N/A 192400 11.1
FI
1500
4000
2100
p
estimate
knowledge
2007-2018 = -67 | 17 | (-38) 1988-2018 + N/A | N/A | (313) 36800 2.1 N/A N/A N/A 1980-2010 + 170 | 170 | (N/A) 36800 2.1
FR
110000
170000
N/A
p
estimate
knowledge
5.7
2007-2018 - N/A | N/A | (-23.5) 2001-2018 - N/A | N/A | (-10) 283700 16.4 2009-2017 = N/A 1985-2017 = N/A 282600 16.3
GR
5000
20000
N/A
p
estimate
noChange
0.5
2007-2018 = N/A | N/A | (0) 1980-2018 = N/A | N/A | (0) 102800 5.9 2007-2018 x N/A 1980-2018 x N/A 94900 5.5
HR
10000
30000
N/A
p
estimate
N/A
0.8
2007-2018 x N/A 1980-2018 x N/A 28872 1.7 2007-2018 x N/A 1980-2018 x N/A 38300 2.2
HU
8000
15000
N/A
p
estimate
knowledge
#
0.5
2007-2018 u N/A | N/A | (-81) 1980-2018 - N/A | N/A | (69) # 25547 1.5 2007-2018 = N/A 1980-2018 - -50 | -30 | (N/A) # 26300 1.5
IT
20000
40000
N/A
p
estimate
noChange
1.2
2000-2014 + 5 | 20 | (N/A) 1993-2018 = N/A 174000 10.0 2007-2018 = N/A 1993-2018 + 40 | 45 | (N/A) 173400 10.0
LT
9000
17000
N/A
p
estimate
genuine
0.5
2013-2018 - -10 | -5 | (N/A) 1980-2018 = 0 | 0 | (N/A) 24400 1.4 2006-2018 = 0 | 0 | (N/A) 1980-2012 = 0 | 0 | (N/A) 24000 1.4
LU
20
25
N/A
p
estimate
genuine
#
2007-2018 = -10 | 0 | (N/A) 1980-2018 - -90 | -50 | (N/A) 28 # 2007-2018 = 0 | 0 | (N/A) 1980-2018 - -90 | -80 | (N/A) 1100
LV
6497
30995
14190
p
interval
method
0.6
2005-2018 = -48.4 | 25.8 | (-18.8) 1991-2016 + 469 | 492 | (N/A) 42500 2.5 2000-2017 - N/A | N/A | (-17) 1980-2017 + N/A | N/A | (45) 42200 2.4
NL
4300
5300
N/A
p
estimate
knowledge
0.2
2006-2017 + 31 | 71 | (50) 1984-2017 + 278 | 662 | (438) 18700 1.1 2000-2015 = N/A | N/A | (6.85) 1977-2015 + N/A | N/A | (18.35) 17300 1.0
PL
201000
367000
N/A
p
interval
genuine
11.5
2007-2018 - -38 | -21 | (-30) 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
#
12.2
2004-2018 - N/A 1980-2018 x N/A # 63300 # 3.6 2005-2018 = N/A | N/A | (-25) 1980-2018 = N/A # 62400 3.6
RO
282694
395256
N/A
p
interval
method
13.7
2008-2018 u -4 | 6 | (N/A) 1980-2018 x N/A 160700 9.3 2007-2018 = N/A 1980-2018 x N/A 159800 9.2
SE
9000
20000
15000
p
estimate
noChange
0.6
2007-2018 = -30 | 28 | (-5) 1980-2018 + 100 | 300 | (200) 176500 10.2 2007-2018 = N/A 1980-2018 = N/A 176500 10.2
SI
2800
3800
N/A
p
estimate
genuine
#
0.1
2008-2018 = N/A 1980-2018 x N/A 4500 # 0.3 2007-2018 x N/A 1980-2018 + N/A | N/A | (32) # 3900 0.2
SK
1000
1500
N/A
p
estimate
knowledge
2007-2018 - -30 | -10 | (N/A) 1980-2018 - -50 | -30 | (N/A) 21801 1.3 2007-2018 = N/A 1980-2018 = N/A 22900 1.3
UK
1851
2760
2294
p
interval
genuine
#
2001-2016 + 86 | 178 | (131) 1970-2016 + 470 | 749 | (606) 15500 0.9 1989-2009 + 112.33 | 112.33 | (N/A) 1970-2009 - -20.92 | -20.92 | (N/A) 15300 0.9
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 1580000 3040000 p = = 1760000 NE NE Secure A B Secure Lullula arborea