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, Scolopax rusticola. 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
CZ completeSurvey
DE estimateExpert
DK completeSurvey
EE estimateExpert
ES completeSurvey
ESIC estimateExpert
FI completeSurvey
FR completeSurvey
GIB
GR estimatePartial
HR estimateExpert
HU estimateExpert
IE absentData
IT estimateExpert
LT estimatePartial
LU estimateExpert
LV completeSurvey
NL completeSurvey
PL estimateExpert
PT
PTAC estimatePartial
PTMA completeSurvey
RO estimateExpert
SE estimatePartial
SI estimateExpert
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
CZ completeSurvey
DE estimateExpert
DK completeSurvey
EE estimatePartial
ES completeSurvey
ESIC absentData
FI completeSurvey
FR completeSurvey
GIB
GR estimatePartial
HR estimateExpert
HU completeSurvey
IE completeSurvey
IT estimatePartial
LT estimatePartial
LU estimateExpert
LV completeSurvey
NL completeSurvey
PL absentData
PT
PTAC estimatePartial
PTMA completeSurvey
RO absentData
SE estimatePartial
SI absentData
SK estimatePartial
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 estimatePartial
CZ
DE
DK
EE
ES estimatePartial
ESIC
FI
FR
GIB estimatePartial
GR estimatePartial
HR
HU
IE
IT
LT
LU
LV
NL
PL
PT estimatePartial
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
4000
10000
N/A
cmales
estimate
noChange
0.7
2007-2018 = N/A 1981-2018 x N/A 28200 2.0 2007-2018 = N/A | N/A | (1) 1981-2018 x N/A 27100 1.9
BE
800
6500
3700
cmales
estimate
method
#
0.3
2008-2018 x N/A 1973-2018 x N/A 26226 # 1.8 2008-2018 x N/A 1973-2018 x N/A 26100 1.9
BG
90
180
N/A
cmales
estimate
noChange
2000-2018 x N/A 1980-2018 x N/A # 5598 0.4 2000-2018 x N/A 1980-2018 x N/A # 5700 0.4
CY
15000 200000 N/A i estimate method N/A 2007-2018 x N/A 1980-2018 x N/A other
CZ
2000
4000
N/A
cmales
estimate
noChange
#
0.3
2007-2018 x N/A 1980-2018 x N/A # 33900 2.4 2002-2016 = N/A | N/A | (-0.94) 1986-2016 + N/A | N/A | (11.7) # 32500 2.3
DE
20000
39000
N/A
cmales
mean
noChange
2.8
2004-2016 = N/A | N/A | (0) 1980-2016 = N/A | N/A | (-8) 255493 17.8 2004-2016 = -10 | 10 | (0) 1980-2016 = -30 | 40 | (N/A) 263900 18.7
DK
N/A
N/A
2000
cmales
estimate
noChange
#
0.2
2006-2017 x N/A 1996-2017 = -9.9 | 72.59 | (25) # 17200 1.2 1996-2017 - N/A | N/A | (-18.09000) 1974-2017 + N/A | N/A | (13.9) # 17200 1.2
EE
20000
40000
N/A
cmales
estimate
genuine
2.9
2006-2017 - -57 | -9 | (N/A) 1980-2017 - -77 | -55 | (N/A) 48100 3.4 2007-2018 = N/A | N/A | (0) 1980-2018 = N/A | N/A | (-5) 24400 1.7
ES
3600
4000
N/A
cmales
estimate
noChange
#
0.4
2007-2018 = N/A 1980-2018 = N/A 4212 0.3 2007-2018 = N/A 1980-2018 x N/A 640000 680000 N/A i interval noChange N/A 2007-2018 = N/A 1980-2018 = N/A other 4600 0.3
ESIC
1000
2500
N/A
cmales
minimum
noInfo
#
0.2
2007-2018 x N/A 1980-2018 x N/A # 2100 # 0.1 2007-2018 x N/A 1980-2018 x 1000 | 2500 | (N/A) # 2800 0.2
FI
138399
260623
177982
cmales
mean
knowledge
17.0
2007-2018 = -37 | 14 | (-15) 1980-2018 + 32 | 231 | (110) 206700 14.4 N/A N/A N/A 1980-2010 + 6 | 6 | (N/A) 206500 14.6
FR
21000
27000
24000
cmales
interval
method
2.3
2007-2018 - -20 | 0 | (-10) 1988-2018 - -40 | -20 | (-30) 79500 5.5 2007-2018 - -20 | 0 | (-10) 1988-2018 - -40 | -20 | (-30) 78400 5.5
GIB
1 5 5 i estimate noChange N/A 2001-2018 = 1 | 5 | (5) 1980-2018 = 1 | 5 | (5) other
GR
N/A
N/A
10
cmales
estimate
noChange
#
2007-2018 = N/A | N/A | (0) 1980-2018 x N/A 200 2007-2018 x N/A 1980-2018 x N/A 2450000 3280000 N/A i interval noChange # N/A 2007-2018 = N/A | N/A | (0) 1980-2018 x N/A other 300
HR
10
50
N/A
cmales
estimate
N/A
2007-2018 x N/A 1980-2018 x N/A 400 2007-2018 x N/A 1980-2018 x N/A 400
HU
50
100
N/A
cmales
estimate
knowledge
#
2007-2018 x N/A 1980-2018 x N/A # 1564 0.1 2007-2018 x N/A 1980-2018 x N/A # 1700 0.1
IE
N/A
N/A
N/A
N/A
N/A
noChange
#
N/A
2000-2011 = N/A 1972-2011 x N/A # 13100 # 0.9 1991-2011 = N/A | N/A | (-4.8) 1972-2011 - N/A | N/A | (-67.5) # 12700 0.9
IT
50
150
N/A
cmales
estimate
noChange
2007-2018 x N/A 1993-2018 + 50 | 70 | (N/A) 22900 1.6 2007-2018 = N/A 1993-2018 + 250 | 255 | (N/A) 22900 1.6
LT
10000
20000
N/A
cmales
estimate
noChange
1.4
2013-2018 = 0 | 0 | (N/A) 1980-2018 = 0 | 0 | (N/A) 24400 1.7 2006-2018 = 0 | 0 | (N/A) 1980-2012 = 0 | 0 | (N/A) 23900 1.7
LU
10
30
N/A
cmales
estimate
noChange
#
2007-2018 x N/A 1980-2018 x N/A # 18 # 2007-2018 x N/A 1980-2018 x N/A 1300
LV
17904
88521
39811
cmales
interval
method
3.8
2006-2018 u -38.7 | 157.3 | (28.3) 1980-2018 x N/A 49400 3.5 2000-2017 + N/A | N/A | (14) 1980-2017 + N/A | N/A | (33) 48900 3.5
NL
2200
3500
N/A
cmales
estimate
knowledge
0.3
2006-2017 = -2 | 39 | (17) 1984-2017 = -31 | 66 | (8) # 20500 1.4 2000-2015 + N/A | N/A | (17.81) 1977-2015 = N/A | N/A | (4.59) 19000 1.4
PL
20000
100000
N/A
cmales
estimate
noChange
5.7
2007-2018 x N/A 1980-2018 x N/A N/A N/A 2007-2018 x N/A 1980-2018 x N/A N/A N/A
PT
N/A N/A 17000 i minimum N/A # N/A 2007-2018 x N/A 1980-2018 x N/A other
PTAC
3247
3704
3461
cmales
mean
noChange
#
0.3
2011-2018 = N/A | N/A | (0.1) 1980-2018 x N/A # 5600 # 0.4 2008-2018 = N/A | N/A | (6.6) 1980-2018 x N/A # 5600 0.4
PTMA
N/A
162
1
cmales
estimate
noChange
2008-2018 - N/A | N/A | (1) 1980-2018 - N/A | N/A | (1) 800 2001-2018 + N/A | 900 | (1) 1980-2018 x N/A | N/A | (1) 800
RO
620
6200
N/A
cmales
estimate
knowledge
0.3
2007-2018 x N/A 1980-2018 x N/A 3900 0.3 2007-2018 x N/A 1980-2018 x N/A 3900 0.3
SE
396000
774000
580000
cmales
estimate
noChange
55.4
2007-2018 = -17 | 29 | (4) 1980-2018 = -49 | 61 | (0) 470900 32.9 2007-2018 = N/A 1980-2018 = N/A 469900 33.3
SI
30
50
N/A
cmales
estimate
knowledge
2007-2018 x N/A 1980-2018 x N/A 1200 # 2007-2018 x N/A 1980-2018 x N/A # 1200
SK
1500
2500
N/A
cmales
estimate
knowledge
0.2
2007-2018 = N/A 1980-2018 = N/A 23375 1.6 2007-2018 = N/A 1980-2018 = N/A 24500 1.7
UK
43079
71105
57108
cmales
estimate
genuine
#
5.5
2004-2016 - N/A | N/A | (-31.26) 1980-2016 - N/A | N/A | (-77.38) # 86600 6.0 1989-2009 - -30.5 | -30.5 | (N/A) 1970-2009 - -51.75 | -51.75 | (N/A) 85800 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 706000 1460000 cmales = = 1420000 NE NE Secure A B Secure Scolopax rusticola