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Habitat assessments at EU biogeographical level

The Article 17 web tool provides an access to EU biogeographical and Member States’ assessments of conservation status of the habitat types and species of Community interest compiled as part of the Habitats Directive - Article 17 reporting process. These assessments have been carried out in EU25 for the period 2001-2006, in EU 27 for the period 2007-2012 and in EU28 for the period 2013-2018.

Choose a period, a group, then a habitat type belonging to that group.
Optionally, further refine your query by selecting one of the available biogeographical regions for that habitat type.
Once a selection has been made the conservation status can be visualised in a map view.

The ‘Data sheet info’ includes notes for each regional and overall assessment per habitat.

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

Note: Rows in italic shows data not taken into account when performing the assessments (marginal presence, occasional, extinct prior HD, information, etc)

Legend
FV
Favourable
XX
Unknown
U1
Unfavourable-Inadequate
U2
Unfavourable-Bad
Current selection: 2013-2018, Forests, 91E0 Alluvial forests with Alnus glutinosa and Fraxinus excelsior (Alno-Padion, Alnion incanae, Salicion albae), All bioregions. Show all Forests
Member States reports
MS Region Range (km2) Area (km2) Structure and functions (km2) Future prospects Overall assessment Distribution area(km2)
Surface Status
(% MS)
Trend FRR Min Max Best value Type est. Method Status
(% MS)
Trend FRA
Area in good condition (km2)
Good
(adjusted mean value)
Not good
(adjusted mean value)
Not Known
(adjusted mean value)
3.30 1.80 114.90
0.10 N/A N/A
14 1.50 2.50
1.39 0.37 13.30
0.35 N/A 1.15
200 200 200
2.57 N/A N/A
16.89 14.57 0.67
20.05 23 N/A
N/A N/A 3
N/A N/A 10
15.50 10.50 N/A
3.23 2.34 36.43
3.20 109.05 19.15
64.86 31.68 N/A
N/A 7.81 N/A
41.26 27.39 332.16
637.50 468 610
16.66 2.98 N/A
29 39 N/A
N/A N/A N/A
3.44 11.01 94.64
0.36 N/A N/A
37 1 N/A
N/A N/A N/A
N/A N/A 287.10
80.55 24.05 N/A
7 7 26
37.50 70 N/A
N/A N/A 48.50
44.21 N/A N/A
457.92 103.54 52.32
572.13 193.98 N/A
1.18 184.10 N/A
849 1040 1040
234.32 N/A N/A
116.27 11.54 0.28
3.15 0.20 0.94
422.05 602.95 N/A
N/A N/A 64.70
3 5 2
55 50 N/A
27.99 92.88 125.40
N/A N/A 40
76.41 N/A 8.49
40.34 4.94 9.06
N/A N/A N/A
7.10 2.20 1.29
144 282.50 73.50
1.58 1.03 5.39
Good
Not good Not known Status Trend Range
prosp.
Area
prosp.
S & f
prosp.
Status Curr. CS Curr. CS
trend
Prev. CS Prev. CS
trend
Status
Nat.
of ch.
CS trend
Nat. of ch.
Distrib. Method % MS
AT ALP 43000 14.81 x > 80 160 N/A minimum b 19.02 x >> 3.30 - 3.30 1.80 - 1.80 74.90 - 154.90 U2 x poor bad bad U2 U2 x U1 - genuine noInfo 33500 a 19.34
BG ALP 15500 5.34 = 15500 N/A N/A 0.10 estimate a 0.02 u 0.10 0.10 - 0.10 N/A - N/A N/A - N/A FV = poor poor poor U1 U1 = U1 = noChange noChange 6800 a 3.93
DE ALP 3977 1.37 = 3977 13 21 17 estimate c 2.69 = 13 - 15 1 - 2 2 - 3 FV = good good good FV FV = FV N/A noChange noChange 4700 b 2.71
ES ALP 9800 3.37 = N/A N/A 15.07 estimate b 2.39 u > 1.39 - 1.39 0.37 - 0.37 13.30 - 13.30 XX x good good good FV U1 x U1 x noChange noChange 4000 b 2.31
FI ALP 7200 2.48 = N/A N/A 1.50 estimate b 0.24 = 0.35 - 0.35 N/A - N/A 1.15 - 1.15 XX = good good poor U1 U1 = FV N/A genuine noChange 2200 b 1.27
FR ALP 34600 11.91 - > N/A 400 N/A estimate c 31.69 - > N/A - 400 N/A - 400 N/A - 400 XX x bad bad bad U2 U2 - U2 = noChange noChange 19500 b 11.26
HR ALP 900 0.31 = N/A N/A 2.57 estimate a 0.41 = 2.57 - 2.57 N/A - N/A N/A - N/A FV = good good good FV FV = N/A N/A noChange noChange 800 a 0.46
IT ALP 57500 19.80 + > 97 198.62 N/A estimate b 23.42 - >> 16.89 - 16.89 14.57 - 14.57 0.67 - 0.67 U2 - poor bad bad U2 U2 - U2 - noChange noChange 35700 b 20.61
PL ALP 15200 5.23 = 30 56 43 estimate b 6.81 = 7.80 - 32.30 10.80 - 35.20 N/A - N/A U1 = good good poor U1 U1 = U2 = knowledge noChange 10500 b 6.06
RO ALP 46300 15.94 = N/A N/A 6 estimate a 0.95 = > N/A - N/A N/A - N/A N/A - 6 XX x good good unk FV U1 = U1 = N/A method 16900 a 9.76
SE ALP 26000 8.95 = 26000 10 10 10 estimate b 1.58 = 10 N/A - N/A N/A - N/A 10 - 10 U1 x good good poor U1 U1 = FV N/A knowledge noChange 7900 b 4.56
SI ALP 1722 0.59 - > N/A N/A 26 estimate b 4.12 - > 10 - 21 5 - 16 N/A - N/A U1 - poor poor poor U1 U1 - U1 - noChange noChange 1700 b 0.98
SK ALP 28720.70 9.89 = > N/A N/A 42 estimate b 6.66 + > 3.23 - 3.23 2.34 - 2.34 36.43 - 36.43 U1 u poor poor poor U1 U1 = U1 = N/A N/A 29000 b 16.74
BE ATL 22000 3.30 = 119 146 131 estimate b 6.78 - >> 1.50 - 4.90 107.40 - 110.70 16.70 - 21.60 U2 - good poor poor U1 U2 - U2 + noChange genuine 18600 a 4.99
DE ATL 62095 9.31 = 93.70 99.37 96.54 estimate b 4.99 = > 55.36 - 74.37 22.17 - 41.18 N/A - N/A U2 x good poor bad U2 U2 = U2 = noChange noChange 50600 b 13.57
DK ATL 13473 2.02 = N/A N/A 7.81 estimate b 0.40 x N/A - N/A 7.81 - 7.81 N/A - N/A U2 u good good bad U2 U2 x U2 = N/A N/A 3100 b 0.83
ES ATL 70000 10.50 = N/A N/A 400.82 estimate b 20.74 = x 41.14 - 41.38 26.55 - 28.22 331.21 - 333.11 U1 x good poor unk U1 U1 = U1 x noChange knowledge 57900 b 15.53
FR ATL 221000 33.15 = 97004 700 1500 N/A minimum c 56.91 - > 215 - 1060 86 - 850 30 - 1190 U2 - good poor bad U2 U2 - U2 - noChange noChange 91800 b 24.62
IE ATL 61000 9.15 = N/A N/A 19.64 minimum a 1.02 - 151.25 16.66 - 16.66 2.98 - 2.98 N/A - N/A U1 - good bad bad U2 U2 - U2 + noChange knowledge 19800 a 5.31
NL ATL 16100 2.41 = N/A N/A 68 estimate b 3.52 - > 12 - 46 22 - 56 N/A - N/A U1 x good poor poor U1 U1 x U1 - noChange method 12200 a 3.27
PT ATL 6400 0.96 = N/A N/A N/A d 0 = N/A - N/A N/A - N/A N/A - N/A U1 - good poor poor U1 U1 - FV N/A knowledge knowledge 4800 c 1.29
UK ATL 194652.73 29.20 = 194652.73 N/A N/A 109.08 estimate b 5.64 = 119.99 3.44 - 3.44 11.01 - 11.01 94.64 - 94.64 U2 x good poor bad U2 U2 = U2 = noChange noChange 114000 b 30.58
BG BLS 3600 100 = 3600 N/A N/A 0.36 estimate a 100 = 0.36 0.36 - 0.36 N/A - N/A N/A - N/A FV = poor poor poor U1 U1 + U1 = noChange method 2900 a 100
EE BOR 11000 2.45 = N/A N/A 38 estimate a 7.92 = 37 - 37 1 - 1 N/A - N/A FV + good good good FV FV + U1 + knowledge knowledge 4400 a 2.19
FI BOR 91600 20.36 = > N/A N/A 10 minimum c 2.08 - >> N/A - N/A N/A - N/A N/A - N/A XX - bad bad bad U2 U2 - U2 - noChange noChange 24100 b 12.01
LT BOR 64787 14.40 = 64787 N/A N/A 287.10 estimate a 59.85 u N/A - N/A N/A - N/A 287.10 - 287.10 U1 u good good poor U1 U1 x U1 = knowledge knowledge 56200 a 28
LV BOR 64482 14.33 = x 87.31 121.89 N/A estimate b 21.81 x x 67.23 - 93.86 20.08 - 28.03 N/A - N/A U1 x good poor poor U1 U1 x U2 - knowledge knowledge 63800 b 31.79
SE BOR 218000 48.46 = 218000 40 40 40 estimate b 8.34 - 150 7 - 7 7 - 7 26 - 26 U1 x good bad bad U2 U2 x U1 x knowledge noChange 52200 b 26.01
AT CON 28800 2.54 = > 100 115 110 estimate a 2.38 x >> 35 - 40 65 - 75 N/A - N/A U2 x poor bad bad U2 U2 x U1 = genuine noInfo 20500 a 2.24
BE CON 15400 1.36 = 44 53 48.70 interval a 1.05 + >> N/A - N/A N/A - N/A 44 - 53 U1 = good poor bad U2 U2 + U2 x noChange genuine 12500 a 1.37
BG CON 61100 5.40 = 61100 N/A N/A 44.21 estimate a 0.96 = 44.21 44.21 - 44.21 N/A - N/A N/A - N/A FV = poor poor poor U1 U1 + U1 = noChange method 33900 a 3.71
CZ CON 85900 7.59 = N/A N/A 613.77 estimate a 13.29 = 457.92 - 457.92 103.54 - 103.54 52.32 - 52.32 U2 - good good poor U1 U2 - U2 - noChange noChange 76900 a 8.42
DE CON 279902 24.73 = 762.28 769.94 766.11 estimate b 16.59 = > 400.49 - 743.77 135.79 - 252.17 N/A - N/A U2 + good poor bad U2 U2 + U2 = noChange genuine 269600 b 29.52
DK CON 29544 2.61 = N/A N/A 185.28 estimate b 4.01 x N/A - 2.35 182.93 - 185.28 N/A - N/A U2 u good good bad U2 U2 x U2 = N/A N/A 19900 b 2.18
FR CON 106700 9.43 = 864 1216 1040 estimate c 22.53 - > 673 - 1025 864 - 1216 864 - 1216 U2 - poor bad bad U2 U2 - U2 = noChange noChange 100100 b 10.96
HR CON 21100 1.86 = N/A N/A 234.32 estimate a 5.08 = 234.32 - 234.32 N/A - N/A N/A - N/A FV = good good good FV FV = N/A N/A noChange noChange 19800 a 2.17
IT CON 84900 7.50 + 271.33 330.97 N/A estimate b 6.52 - >> 116.27 - 116.27 11.54 - 11.54 0.28 - 0.28 U1 - good bad bad U2 U2 - U2 - noChange noChange 49300 b 5.40
LU CON 3800 0.34 + 3.36 4.30 N/A estimate b 0.08 + 6.10 3.15 - 3.15 0.20 - 0.20 0.94 - 0.94 FV + good poor good U1 U2 + U2 + noChange genuine 2600 a 0.28
PL CON 316600 27.98 = N/A N/A 1025 estimate b 22.20 = 167.50 - 676.60 348.40 - 857.50 N/A - N/A U2 - good good poor U1 U2 - U2 = noChange knowledge 267000 b 29.23
RO CON 75900 6.71 = > N/A N/A 129.40 estimate a 2.80 = > N/A - N/A N/A - N/A N/A - 129.40 U1 x poor poor poor U1 U1 = U1 = N/A N/A 27500 a 3.01
SE CON 17000 1.50 = 17000 10 10 10 estimate b 0.22 - 10 3 - 3 5 - 5 2 - 2 U2 x good poor bad U2 U2 x U2 x noChange noChange 8200 b 0.90
SI CON 5072 0.45 = > N/A N/A 105 estimate b 2.27 - > 45 - 65 40 - 60 N/A - N/A U2 - good bad bad U2 U2 - U2 - noChange noChange 5500 b 0.60
ES MED 126500 44.15 = x N/A N/A 246.28 estimate b 58.14 = > 27.99 - 27.99 92.05 - 93.72 124.57 - 126.24 U2 - unk poor unk XX U2 - U1 x knowledge knowledge 65500 b 41.09
FR MED 45700 15.95 = x 34 46 N/A estimate c 9.44 - x N/A - N/A N/A - N/A 34 - 46 U1 u good poor poor U2 U2 - U2 = noChange noInfo 21400 b 13.43
GR MED 694 0.24 = N/A N/A 84.90 estimate b 20.04 = 76.41 - 76.41 N/A - N/A 8.49 - 8.49 FV = good good poor U1 U1 = FV N/A knowledge method 11500 b 7.21
IT MED 50900 17.77 + 49.84 54.96 N/A estimate b 12.37 = 40.34 - 40.34 4.94 - 4.94 9.06 - 9.06 U1 u poor poor poor U1 U1 = U1 = noChange noChange 23600 b 14.81
PT MED 62700 21.89 = N/A N/A N/A d 0 = N/A - N/A N/A - N/A N/A - N/A U1 - good poor poor U1 U1 - FV N/A knowledge knowledge 37400 c 23.46
CZ PAN 5800 7.04 = N/A N/A 10.60 estimate a 2.04 = 7.10 - 7.10 2.20 - 2.20 1.29 - 1.29 U1 = good good poor U1 U1 = U1 - noChange noChange 3100 a 3.75
HU PAN 68709 83.36 = 450 550 N/A estimate b 96.41 = > 115 - 173 273 - 292 62 - 85 U2 - good poor bad U2 U2 - U1 - method noChange 71100 b 86.08
SK PAN 7917.05 9.61 - > N/A N/A 8 estimate b 1.54 - > 1.58 - 1.58 1.03 - 1.03 5.39 - 5.39 FV u poor poor poor U1 U2 - U2 - N/A N/A 8400 b 10.17
Automatic Assessments Show,Hide
EU biogeographical assessments
MS/EU28 Region Surface Status
Range
Trend FRR Min Max Best value Status
Area
Trend FRA Good Not good Not known Status Str.
& funct.
Trend Range
prosp.
Area
prosp.
S & f
prosp.
Status
Future
prosp.
Curr. CS Curr. CS
trend
2012 CS 2012 CS
trend
Status
Nat.
of ch.
CS trend
Nat. of ch.
2001-06 status
with
backcasting
Target 1
EU28 PAN 82426.05 2GD 2GD - | - | - - | - | - - | - | - 2GD 2GD MTX - U1 - nong nc U1 C

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 BOR 449869 1 = > 449869 2GD - | - | - - | - | - - | - | - 2GD 2GD MTX x U2 - nc nong U2 D

03/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 CON 1131718 1 = > 1131718 2GD - | - | - - | - | - - | - | - 2GD 2GD MTX - U2 = nc nong U2 C

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 MED 286494 2GD = 2GD - | - | - - | - | - - | - | - 2GD 2GD MTX - U1 = nong nong U1 C

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 ALP 2GD = 2GD - | - | - - | - | - - | - | - 2GD 2GD MTX - U2 - nc nc U2 C

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 ATL 666720.73 0EQ = ≈ 666720.73 2XR - | - | - - | - | - - | - | - 2XR 2XR MTX - U2 - nc nc U2 C

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 BLS 3600 0MS = 3600 0.36 0MS = 0.36 0.36 | 0.36 | - - | - | - - | - | - 0MS = 0MS MTX + U1 = nc nong U1 B1

04/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
BG BLS - | - | - - | - | - - | - | - 2GD 2GD MTX N/A U1 N/A U1 0/2

04/20

WWF Bulgaria

Institution: WWF Bulgaria

Member State: BG

WWF Bulgaria
BG CON - | - | - - | - | - - | - | - 2GD 2GD MTX N/A U1 N/A U2 0/2

03/20

WWF Bulgaria

Institution: WWF Bulgaria

Member State: BG

WWF Bulgaria
BG ALP - | - | - - | - | - - | - | - 2GD poor 2GD MTX N/A U1 - U2 0/2

03/20

WWF Bulgaria

Institution: WWF Bulgaria

Member State: BG

WWF Bulgaria
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The distribution data for France (2013 – 2018 reporting) were corrected after the official submission of the Article 17 reports by France. The maps displayed via this web tool take into account these corrections, while the values under Distribution area (km2) used for the EU biogeographical assessment are based on the original Article 17 report submitted by France. More details are provided in the feedback part of the reporting envelope on CDR.