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Species 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 species belonging to that group.
Optionally, further refine your query by selecting one of the available biogeographical regions for that species.
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 species.

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

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

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

Sensitive spatial information for this species is not shown in the map.

Current selection: 2013-2018, Vascular plants, Liparis loeselii, All bioregions. Annexes Y, Y, N. Show all Vascular plants
Member States reports
MS Region Range (km2) Population Habitat for the species Future prospects Overall assessment Distribution
area (km2)
Surface Status
(% MS)
Trend FRR
Min
Member State
code
Reporting units Alternative units
Min Max Best value Unit Type of estimate Min Max Best value Unit Type of estimate
AT 3000 6000 N/A i minimum 113 N/A N/A grids1x1 minimum
DE 600 1500 N/A i estimate 8 11 9.50 localities estimate
FR 10000 20000 N/A i estimate N/A N/A N/A estimate
IT 8 400 N/A i estimate N/A N/A N/A N/A
RO 80 1000 N/A i estimate N/A N/A N/A estimate
SI N/A N/A 13 i minimum 13 19 N/A grids1x1 N/A
SK 34 1223 N/A i estimate N/A N/A N/A N/A
BE 261 3312 N/A i estimate N/A N/A N/A N/A
DE 773 773 773 i mean 773 773 5002.40 localities mean
FR 10000 22000 N/A i mean 74 74 N/A localities mean
NL 20000 40000 N/A i estimate N/A N/A N/A N/A
UK N/A N/A 13349 i estimate N/A N/A N/A N/A
EE 12000 18000 N/A i estimate N/A N/A N/A N/A
FI 5 10 N/A i estimate N/A N/A N/A N/A
LT 16000 20000 N/A i minimum N/A N/A N/A N/A
LV 1200 9000 N/A i estimate 58 65 N/A grids10x10 estimate
SE N/A N/A 100000 i estimate N/A N/A N/A N/A
AT 82 N/A N/A i minimum 15 N/A N/A grids1x1 minimum
CZ 5400 7500 N/A i interval N/A N/A N/A interval
DE 50000 100000 64898 i estimate 217 239 228 localities estimate
DK N/A 6496 N/A i estimate N/A N/A N/A N/A
FR 26539 49309 N/A i mean 32 32 32 colonies mean
IT 4 200 N/A i estimate N/A N/A N/A N/A
PL 8000 10000 N/A i mean N/A N/A N/A N/A
RO 200 800 N/A i estimate N/A N/A N/A estimate
SE N/A N/A 1000 i mean N/A N/A N/A N/A
SI N/A N/A 6 i minimum 6 12 N/A grids1x1 minimum
FR 80 100 N/A i mean N/A N/A N/A mean
HU 2400 2700 N/A i estimate N/A N/A N/A N/A
SK N/A N/A N/A i estimate N/A N/A N/A N/A
Max
Best value Unit Type est. Method Status
(% MS)
Trend FRP Unit Occupied
suff.
Unoccupied
suff.
Status Trend Range
prosp.
Population
prosp.
Hab. for sp.
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 5000 28.87 = > 3000 6000 N/A i minimum c 20.51 + > Y U1 + poor poor poor U1 U1 + U1 + noChange noChange 3900 a 39.80
DE ALP 1769 10.22 = 1769 600 1500 N/A i estimate b 4.79 = > localities Unk XX = good poor unk U1 U1 = U1 - noChange method 1400 b 14.29
FR ALP 5300 30.61 - 10000 20000 N/A i estimate a 68.38 - Y Unk U1 - unk poor good U1 U1 - U1 = genuine noChange 2300 a 23.47
IT ALP 2400 13.86 - > 8 400 N/A i estimate b 0.93 = >> N Y U2 = bad bad poor U2 U2 - U1 - knowledge noChange 900 a 9.18
RO ALP 1100 6.35 = > 80 1000 N/A i estimate b 2.46 = 1250 i Y U1 = good poor poor U1 U1 = U1 N/A noChange noChange 300 a 3.06
SI ALP 1666 9.62 = N/A N/A 13 i minimum b 0.06 - > N Unk U1 - good poor poor U1 U1 - U1 - noChange noChange 900 b 9.18
SK ALP 82.20 0.47 = 34 1223 N/A i estimate a 2.87 = > Y FV = good poor poor U1 U1 = U1 = N/A N/A 100 b 1.02
BE ATL 200 2.78 = >> 261 3312 N/A i estimate a 2.89 u >> N Unk U2 + bad poor bad U2 U2 = U2 + noChange genuine 200 a 2.27
DE ATL 318 4.42 - 696 773 773 773 i mean b 1.25 x >> localities N N U2 = bad bad bad U2 U2 x U2 - noChange method 400 b 4.55
FR ATL 2400 33.34 = > 10000 22000 N/A i mean a 25.84 + Unk Unk XX = poor poor poor U1 U1 + U2 = genuine genuine 4200 a 47.73
NL ATL 3900 54.17 = 20000 40000 N/A i estimate b 48.46 = Y FV = good good good FV FV = U1 - genuine genuine 3600 a 40.91
UK ATL 381.63 5.30 + 790 N/A N/A 13349 i estimate a 21.56 + >> N N U1 + poor good poor U1 U2 + U2 - noChange genuine 400 a 4.55
EE BOR 20500 32.58 = 12000 18000 N/A i estimate b 10.86 = Y U1 = good good poor U1 U1 = U1 = noChange noChange 10700 b 33.33
FI BOR 200 0.32 = >> 5 10 N/A i estimate a 0.01 - >> N N U2 - poor bad poor U2 U2 - U2 - noChange noChange 200 a 0.62
LT BOR 22200 35.28 = > 16000 20000 N/A i minimum c 13.03 - > N Y U1 - poor poor poor U1 U1 - U1 x N/A N/A 8300 b 25.86
LV BOR 9721 15.45 = x 1200 9000 N/A i estimate b 3.69 - 9000 i Y U1 = good poor poor U1 U1 - U1 = knowledge knowledge 8200 a 25.55
SE BOR 10300 16.37 = 10300 N/A N/A 100000 i estimate b 72.41 = 110000 i N Y U1 - good good poor U1 U1 - U1 - noChange noChange 4700 a 14.64
AT CON 400 0.39 = >> 82 N/A N/A i minimum a 0.07 = >> Y U1 + bad bad poor U2 U2 + U2 - noChange knowledge 500 a 0.66
CZ CON 800 0.77 = 5400 7500 N/A i interval a 5.23 = > N Y U1 - good poor poor U1 U1 - U1 - noChange noChange 700 a 0.92
DE CON 18469 17.89 = > 50000 100000 64898 i estimate b 52.67 - > localities N Unk U1 - poor poor poor U1 U1 - U1 = noChange method 12300 b 16.25
DK CON 3834 3.71 = > N/A 6496 N/A i estimate b 2.64 = > N Y U1 = poor poor poor U1 U1 = U1 + N/A N/A 1300 b 1.72
FR CON 9100 8.81 = 26539 49309 N/A i mean a 30.78 = > N N U2 - poor poor poor U1 U2 - U2 = N/A genuine 5900 a 7.79
IT CON 1200 1.16 - > 4 200 N/A i estimate a 0.08 - >> N Y U2 - bad bad bad U2 U2 - U2 - noChange noChange 500 a 0.66
PL CON 66600 64.50 = 8000 10000 N/A i mean a 7.30 - 40000 i Y U1 - good poor poor U1 U2 - U1 - genuine noChange 53400 a 70.54
RO CON 800 0.77 = > 200 800 N/A i estimate b 0.41 = 1000 i Y U1 = good poor poor U1 U1 = U1 N/A noChange noChange 100 a 0.13
SE CON 1200 1.16 = 2700 N/A N/A 1000 i mean a 0.81 = 2000 i N N U2 - bad bad bad U2 U2 - U2 = noChange noChange 600 a 0.79
SI CON 845 0.82 = N/A N/A 6 i minimum b 0 - > N Unk U1 - good poor poor U1 U1 - U1 - noChange noChange 400 b 0.53
FR MED 200 100 - x 80 100 N/A i mean a 100 - x Unk Unk XX = unk unk unk XX U2 - U1 = genuine noChange 200 a 100
HU PAN 489 72.15 = 2400 2700 N/A i estimate a 100 - > Unk U1 - poor poor poor U1 U1 - U1 = noChange genuine 500 a 71.43
SK PAN 188.71 27.85 = N/A N/A N/A i estimate a 0 - > N N U2 - bad bad bad U2 U2 = U2 = N/A N/A 200 b 28.57
Automatic Assessments Show,Hide
EU biogeographical assessments
MS/EU28 Region Surface Status
Range
Trend FRR Min Max Best value Unit Status
Population
Trend FRP Unit Status
Hab. for
species
Trend Range
prosp.
Population
prosp.
Hab. for sp.
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 ALP 17317.2 1 - < 18057.2 13735 30136 21935 i 1 - > 21935 i 2XP - 2XP MTX - U1 = nc gen U1 C

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 ATL 9100 2XP = >> 9100 44383 79434 61908 i 2XP + >> 61908 i 2XP + 2XP MTX + U2 - nc gen U2 B1

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 BOR 62921 1 = > 62921 129205 147010 138107 i 1 = > 138107 i 2XP = 2XP MTX - U1 - nc nc U1 C

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 CON 103248 2XP = > 103248 94479 175393 123210 i 2XP - > 123210 i 2XP - 2XP MTX - U1 - gen nc U1 C

12/19

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 MED 200 0MS - x 80 100 90 i 0MS - x 0MS = unk unk unk 0MS MTX - U1 = gen gen U1 C

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 PAN 677.71 2GD = x 2GD - > i 2GD 2GD MTX - U1 = gen gen U1 C

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
The current dataset is readonly, so you cannot add a conclusion.

Legal notice: A minimum amount of personal data (including cases of submitted comments during the public consultation) is stored in the web tool. These data are necessary for the functioning of the tool and are only accessible to tool administrators.

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.