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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, 91F0 Riparian mixed forests of Quercus robur, Ulmus laevis and Ulmus minor, Fraxinus excelsior or Fraxinus angustifolia, along the great rivers (Ulmenion minori, 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)
0.58 0.02 1499.40
N/A N/A N/A
0.78 N/A N/A
0.25 4.72 0.36
1.24 0.41 N/A
N/A 0.01 N/A
3.80 4.63 N/A
323.50 275.50 225.50
0.45 0.45 N/A
23.90 N/A N/A
6 1 N/A
N/A N/A 2.91
4.19 1.04 N/A
0.20 0.80 7
6.70 1.70 91.60
N/A N/A 0.53
39.59 N/A N/A
85.17 17.19 8.46
110.69 56.56 10.81
218.50 306.50 306.50
1082.63 200 N/A
55.95 6.84 0.16
63.60 236.40 N/A
452 61 N/A
0.10 0.20 0.03
53 44 N/A
5 5 5
N/A 28.92 67.48
N/A N/A 4.89
29.69 1.19 0.19
N/A N/A N/A
61.83 13.06 2.38
84 104.50 26.50
146 41 N/A
1.57 5.03 60.39
82 N/A 46
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 2400 30.33 x x 10 20 N/A estimate b 42.52 - >> 0.58 - 0.58 0.02 - 0.02 999.40 - 1999.40 U2 x bad bad bad U2 U2 x U2 = noChange noInfo 2600 b 44.83
FR ALP N/A 0 N/A N/ N/A N/A N/A N/A 0 N N/ N/A - N/A N/A - N/A N/A - N/A N/A N/A N/A N/A N/A N/A N/A N N/A N/A noChange noChange N/A a 0
HR ALP 200 2.53 = N/A N/A 0.78 estimate a 2.21 = 0.78 - 0.78 N/A - N/A N/A - N/A FV = good good good FV FV = N/A N/A noChange noChange 200 a 3.45
IT ALP 3200 40.44 - >> 4.36 31.33 N/A estimate b 50.58 - >> 0.25 - 0.25 4.72 - 4.72 0.36 - 0.36 U2 - bad bad bad U2 U2 - U2 - noChange noChange 1100 b 18.97
SK ALP 2112.03 26.69 = N/A N/A 1.66 estimate b 4.69 = 1.24 - 1.24 0.41 - 0.41 N/A - N/A U1 u good poor poor U1 U1 = FV N/A knowledge N/A 1900 b 32.76
BE ATL 300 0.30 = >> 0.01 0.01 0.01 estimate a 0 = >> N/A - N/A 0.01 - 0.01 N/A - N/A U2 = poor poor good U1 U2 = U2 = method noChange 100 a 0.26
DE ATL 13272 13.30 = > 8.33 8.53 8.43 estimate b 1.66 = >> 2.66 - 4.94 3.49 - 5.77 N/A - N/A U2 x poor bad unk U2 U2 = U2 = noChange noChange 9300 a 23.97
FR ATL 84500 84.69 = 28938 400 600 500 interval b 98.17 = x 99 - 548 51 - 500 1 - 450 U2 x good unk bad U2 U2 = U1 = noChange noChange 27800 a 71.65
NL ATL 1700 1.70 = > N/A N/A 0.90 estimate a 0.18 = >> 0.20 - 0.70 0.20 - 0.70 N/A - N/A U2 - poor bad bad U2 U2 - U2 = noChange method 1600 a 4.12
BG BLS 5200 100 = 5200 N/A N/A 23.90 estimate a 100 = 23.90 23.90 - 23.90 N/A - N/A N/A - N/A FV = poor poor poor U1 U1 + U1 = noChange method 1800 a 100
EE BOR 3900 4.01 = N/A N/A 7 estimate a 30.24 - 6 - 6 1 - 1 N/A - N/A U1 + good good good FV U1 x U1 + noChange noChange 2100 a 12.65
LT BOR 64787 66.67 = 64787 N/A N/A 2.91 estimate a 12.57 u > N/A - N/A N/A - N/A 2.91 - 2.91 U2 - good poor poor U2 U2 x U2 - knowledge knowledge 4700 a 28.31
LV BOR 8493 8.74 x x 4.47 6 N/A estimate b 22.62 x x 3.58 - 4.80 0.89 - 1.20 N/A - N/A U1 = good poor poor U1 U1 x U2 - knowledge knowledge 4500 b 27.11
SE BOR 20000 20.58 = 20000 8 8 8 estimate b 34.56 x 5 0.20 - 0.20 0.80 - 0.80 7 - 7 U1 x good unk poor U1 U1 x U2 x knowledge noChange 5300 b 31.93
AT CON 8900 1.96 x > 70 130 100 estimate b 3.26 - >> 6.70 - 6.70 1.70 - 1.70 61.60 - 121.60 U2 x bad bad bad U2 U2 x U2 = noChange noInfo 6300 b 2.34
BE CON 1000 0.22 = 0.50 0.56 0.53 estimate a 0.02 - >> N/A - N/A N/A - N/A 0.50 - 0.56 U2 x good bad bad U2 U2 - U2 x noChange genuine 700 a 0.26
BG CON 38400 8.47 = 38400 N/A N/A 39.59 estimate a 1.29 = 39.59 39.59 - 39.59 N/A - N/A N/A - N/A FV = poor poor poor U1 U1 + U1 = noChange method 14800 a 5.50
CZ CON 25500 5.62 = N/A N/A 110.82 estimate a 3.61 = 85.17 - 85.17 17.19 - 17.19 8.46 - 8.46 U1 - good poor poor U1 U1 - U1 - noChange noChange 14500 a 5.39
DE CON 35586 7.85 = > 147.98 179.72 163.85 estimate b 5.34 = > 102.63 - 118.75 45.82 - 67.30 10.76 - 10.87 U2 - poor poor bad U2 U2 - U2 = noChange genuine 26600 a 9.89
FR CON 20352 4.49 x >> 137 476 372 interval c 12.13 - >> 137 - 300 137 - 476 137 - 476 U2 - poor bad bad U2 U2 - U2 - noChange noChange 21400 a 7.96
HR CON 19000 4.19 = N/A N/A 1282.63 estimate a 41.83 = 982.63 - 1182.63 100 - 300 N/A - N/A U1 - good poor bad U2 U2 - N/A N/A N/A 18500 a 6.88
IT CON 29900 6.60 - >> 71.57 101.18 N/A estimate b 2.82 - >> 55.95 - 55.95 6.84 - 6.84 0.16 - 0.16 U2 - bad bad bad U2 U2 - U2 - noChange noChange 17800 b 6.62
PL CON 220500 48.64 = N/A N/A 300 estimate b 9.78 = 16.30 - 110.90 189.10 - 283.70 N/A - N/A U2 - good good poor U1 U2 - U2 - noChange noChange 117700 b 43.77
RO CON 41800 9.22 = > N/A N/A 513 estimate b 16.73 = > 452 - 452 61 - 61 N/A - N/A U1 = poor poor poor U1 U1 = U1 = N/A N/A 25900 a 9.63
SE CON 10000 2.21 = 10000 0.40 0.40 0.40 estimate b 0.01 x 1 0.10 - 0.10 0.20 - 0.20 0.03 - 0.03 U2 x good bad bad U2 U2 x U2 x noChange noChange 1800 b 0.67
SI CON 2400 0.53 = > N/A N/A 97 estimate b 3.16 = > 48 - 58 39 - 49 N/A - N/A U2 - poor bad bad U2 U2 - U2 - noChange noChange 2900 b 1.08
FR MED 1570 6.22 = x N/A 10 N/A estimate c 3.52 = x N/A - 10 N/A - 10 N/A - 10 U2 u poor poor poor U2 U2 = U2 = noChange noInfo 1500 a 5.91
GR MED 567 2.25 = N/A N/A 96.40 estimate b 67.90 - N/A - N/A 28.92 - 28.92 67.48 - 67.48 U2 + good poor bad U2 U2 = U1 = knowledge noChange 8600 b 33.86
HR MED 800 3.17 = N/A N/A 4.89 estimate a 3.45 = N/A - N/A N/A - N/A 4.89 - 4.89 FV x good good good FV FV = N/A N/A N/A 800 a 3.15
IT MED 20000 79.25 + > 30.02 41.34 N/A estimate b 25.13 u >> 29.69 - 29.69 1.19 - 1.19 0.19 - 0.19 U2 x poor bad bad U2 U2 = U2 - noChange noChange 13600 b 53.54
PT MED 2300 9.11 - N/A N/A N/A d 0 = N/A - N/A N/A - N/A N/A - N/A U1 - good good poor U1 U1 - U1 = knowledge knowledge 900 c 3.54
CZ PAN 5000 8 = N/A N/A 77.27 estimate a 14.14 - 61.83 - 61.83 13.06 - 13.06 2.38 - 2.38 U1 - good poor poor U1 U1 - U1 - noChange noChange 2500 a 4.30
HU PAN 38013 60.84 = > 180 250 N/A estimate b 39.36 - >> 65 - 103 92 - 117 23 - 30 U2 - good bad bad U2 U2 - U1 - knowledge noChange 39700 b 68.33
RO PAN 10700 17.13 = > N/A N/A 187 estimate b 34.23 = > 146 - 146 41 - 41 N/A - N/A U1 = poor poor poor U1 U1 = U1 = N/A N/A 6300 a 10.84
SK PAN 8767.71 14.03 = N/A N/A 67 estimate b 12.27 - > 1.57 - 1.57 5.03 - 5.03 60.39 - 60.39 U1 u good poor poor U1 U2 x U2 = N/A N/A 9600 b 16.52
RO STE 8000 100 = N/A N/A 128 estimate a 100 = > 82 - 82 N/A - N/A 46 - 46 U1 = good good poor U1 U1 = U1 = N/A N/A 5200 a 100
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 62480.71 1 = > 62480.71 511.27 581.27 546.27 1 - >> 546.2 - | - | - - | - | - - | - | - 2XA - poor bad bad 2XA MTX - U1 - nong nc U1 C

04/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 STE 8000 0MS = 8000 128 0MS = > 82 | 82 | - - | - | - 46 | 46 | - 0MS = 0MS MTX = U1 = nc nc U1 D

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 ALP 7912.03 1 - >> 7912.03 16.79 53.76 35.28 1 - >> 35.28 - | - | - - | - | - - | - | - 2XA - bad bad bad 2XA MTX - U2 - nc nc U2 C

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 ATL 99772 1 = ≈ 99772 409.25 609.45 509.35 1 = > 509.35 101.86 | 553.640 | 327.75 54.7 | 506.48 | 280.59 1.0 | 450.0 | 225.5 0EQ x good poor bad 2XA MTX = U1 = nong nc U2 D

03/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 BLS 5200 0MS = 5200 23.90 0MS = 23.90 23.9 | 23.9 | - - | - | - - | - | - 0MS = 0MS MTX + U1 = nc nong U1 B1

04/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 BOR 97180 0EQ = ≈ 97180 2XA x - | - | - - | - | - - | - | - 2XA + good unk poor 2XA MTX x U2 = nong nong U2 D

04/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 CON 453338 2XA = > 453338 2XA = - | - | - - | - | - - | - | - 2XA - poor poor bad 2XA MTX - U2 - nc nc U2 C

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 MED 25237 1 + > 25237 2GD x - | - | - - | - | - - | - | - 2GD x poor bad bad 2GD MTX = U2 - nc nong U2 D

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
BG CON - | - | - - | - | - - | - | - 2GD poor 2GD MTX N/A U1 N/A U2 0/2

03/20

WWF Bulgaria

Institution: WWF Bulgaria

Member State: BG

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

04/20

WWF Bulgaria

Institution: WWF Bulgaria

Member State: BG

WWF Bulgaria
The current dataset is readonly, so you cannot add a conclusion.

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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.