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Article 17 > Species summary

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 UK, HR, FI, LV

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, Cypripedium calceolus, 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 20000 50000 25000 i minimum 638 638 638 grids1x1 minimum
BG 15 35 N/A i minimum N/A N/A N/A N/A
DE N/A N/A N/A i estimate 94 94 94 grids5x5 estimate
ES 3487 8033 N/A i estimate N/A N/A N/A N/A
FR 10000 50000 N/A i minimum N/A N/A N/A minimum
HR N/A N/A 200 i minimum N/A N/A N/A N/A
IT 136 61200 N/A i estimate N/A N/A N/A N/A
PL 800 850 N/A i estimate N/A N/A N/A N/A
RO 200 4000 N/A i estimate 1 77 N/A localities estimate
SE N/A N/A 20000 i estimate N/A N/A N/A N/A
SI N/A N/A 32 i minimum 28 32 N/A grids1x1 minimum
SK 13949 20090 N/A i estimate N/A N/A N/A N/A
DE 100 500 150 i estimate 3 3 3 grids5x5 estimate
UK N/A N/A 2 i minimum N/A N/A N/A N/A
EE 30800 80000 N/A i estimate N/A N/A N/A N/A
FI 270000 350000 N/A i estimate N/A N/A N/A N/A
LT 8000 10000 N/A i minimum N/A N/A N/A N/A
LV 4500 5000 N/A i estimate N/A N/A 71 grids1x1 estimate
SE N/A N/A 1000000 i estimate N/A N/A N/A N/A
AT 1000 2000 1500 i minimum 78 78 78 grids1x1 minimum
CZ 2918 3615 N/A i interval 149 149 N/A localities interval
DE 10000 50000 20000 i estimate 398 400 399 grids5x5 estimate
DK N/A 2255 N/A i estimate N/A N/A N/A N/A
FR 1000 10000 N/A i mean N/A N/A N/A mean
PL 28000 32000 N/A i estimate N/A N/A N/A N/A
RO 3000 5000 N/A i estimate 1 95 N/A localities estimate
SI N/A N/A 2 i minimum N/A N/A 2 grids1x1 minimum
ES 36 276 N/A i estimate N/A N/A N/A N/A
FR N/A N/A N/A minimum 87 87 N/A grids1x1 minimum
CZ 77 166 N/A i interval 6 6 N/A localities interval
HU 1200 1600 N/A i estimate N/A N/A N/A N/A
SK 390 390 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 26600 23.66 = ≈ 20000 50000 25000 i minimum b 18.99 = ≈ Y FV x good good good FV FV = FV noChange noChange 22600 b 33.33
BG ALP 400 0.36 = 900 15 35 N/A i minimum b 0.02 = 30 i Y FV = unk unk unk XX FV - U2 - knowledge knowledge 400 b 0.59
DE ALP 4102 3.65 = 4102 N/A N/A N/A i estimate b 0 = 94 grids5x5 Y FV = good good good FV FV = FV noChange noChange 4100 b 6.05
ES ALP 1400 1.25 = > 3487 8033 N/A i estimate a 4.38 = 3487 i Y FV = good good good FV U1 = FV knowledge knowledge 600 b 0.88
FR ALP 22000 19.57 = ≈ 10000 50000 N/A i minimum b 22.79 = ≈ Y Unk FV = good good good FV FV = FV noChange noChange 13300 a 19.62
HR ALP 500 0.44 x x N/A N/A 200 i minimum c 0.15 x x Unk XX x unk unk unk XX XX N/A N/A 500 d 0.74
IT ALP 23300 20.73 = ≈ 136 61200 N/A i estimate b 23.30 = ≈ Y FV = good good good FV FV = FV noChange noChange 13200 b 19.47
PL ALP 1200 1.07 = ≈ 800 850 N/A i estimate b 0.63 x ≈ Y U1 = good poor poor U1 U1 = U1 = noChange noChange 1100 b 1.62
RO ALP 7700 6.85 = 8000 200 4000 N/A i estimate a 1.60 = 5000 i Y FV = good good good FV FV = FV noChange noChange 3000 a 4.42
SE ALP 12200 10.85 = 12200 N/A N/A 20000 i estimate b 15.19 = 20000 i Y FV = good good good FV FV = FV noChange noChange 2200 a 3.24
SI ALP 1846 1.64 = ≈ N/A N/A 32 i minimum b 0.02 = ≈ Y FV = good good good FV FV = FV noChange noChange 900 c 1.33
SK ALP 11174.74 9.94 = ≈ 13949 20090 N/A i estimate b 12.93 = > Y U1 = good good good FV U1 = U1 = N/A N/A 5900 b 8.70
DE ATL 296 74.75 = 537 100 500 150 i estimate a 98.68 = >> grids5x5 N N U2 = bad bad bad U2 U2 = U2 = noChange noChange 200 b 50
UK ATL 100 25.25 = 3500 N/A N/A 2 i minimum a 1.32 = 2000 i Unk Unk XX x poor poor unk U1 U2 = U2 + noChange method 200 a 50
EE BOR 38400 19.14 = ≈ 30800 80000 N/A i estimate b 4.02 = ≈ Y FV = good good poor FV FV = FV noChange noChange 19900 b 22.23
FI BOR 28300 14.10 = ≈ 270000 350000 N/A i estimate b 22.48 = ≈ Y FV = good good poor U1 U1 = U1 x noChange knowledge 16400 a 18.32
LT BOR 30400 15.15 = ≈ 8000 10000 N/A i minimum b 0.65 - ≈ N Y U1 - good poor poor U1 U1 - U1 = noChange noChange 10500 b 11.73
LV BOR 3768 1.88 = x 4500 5000 N/A i estimate b 0.34 = 5000 i Y U1 - good good poor U1 U1 = U1 = knowledge knowledge 4400 a 4.92
SE BOR 99800 49.73 = 99800 N/A N/A 1000000 i estimate b 72.51 = 1000000 i Y FV = good good good FV FV = FV noChange noChange 38300 a 42.79
AT CON 5900 5.22 = ≈ 1000 2000 1500 i minimum b 2.29 x > N Unk U1 x good poor poor U1 U1 = U1 x noChange method 4900 b 6.80
CZ CON 12800 11.33 = 12800 2918 3615 N/A i interval a 4.99 = 4000 i Y U1 = good good poor U1 U1 = U1 = noChange noChange 5800 a 8.04
DE CON 46255 40.95 - > 10000 50000 20000 i estimate b 30.58 - > grids5x5 N Unk U1 - poor poor poor U1 U1 - U1 = noChange genuine 27900 b 38.70
DK CON 100 0.09 = >> N/A 2255 N/A i estimate a 1.72 + >> N N U2 = bad bad bad U2 U2 + U1 = N/A N/A 100 a 0.14
FR CON 7900 6.99 = x 1000 10000 N/A i mean b 8.41 = ≈ Unk Unk U1 = good good unk FV U1 = U1 + N/A genuine 4300 a 5.96
PL CON 30000 26.56 = ≈ 28000 32000 N/A i estimate b 45.87 = > Y U1 - good poor poor U1 U1 - U1 = noChange genuine 25600 b 35.51
RO CON 9500 8.41 = > 3000 5000 N/A i estimate a 6.12 = 5000 i Y FV = good good good FV FV = FV noChange noChange 3100 a 4.30
SI CON 487 0.43 = ≈ N/A N/A 2 i minimum b 0 = ≈ Y FV = good good good FV FV = FV noChange noChange 400 c 0.55
ES MED 400 5.71 = > 36 276 N/A i estimate a 100 - 36 i Y FV x poor poor good FV U1 = FV genuine knowledge 300 b 9.38
FR MED 6600 94.29 = ≈ N/A N/A N/A minimum b 0 = ≈ Unk Unk XX = good poor unk U1 U1 = U1 = noInfo noChange 2900 a 90.63
CZ PAN 2100 49.36 = 2100 77 166 N/A i interval a 6.36 = 200 i Y U1 - good poor poor U1 U1 - U1 = noChange noChange 300 a 13.64
HU PAN 1446 33.99 = ≈ 1200 1600 N/A i estimate a 73.24 - > Y U1 = poor bad poor U2 U2 - U1 + knowledge knowledge 1500 a 68.18
SK PAN 708.04 16.64 = > 390 390 N/A i estimate a 20.40 = > Y U1 = poor poor poor U1 U1 = U1 = N/A N/A 400 b 18.18
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 BOR 200668 1 = ≈ 203708 1313300 1445000 1379150 i 1 = ≈ 1379150 i 2XP = good 2XP MTX = U1 = nong nc U1 A=

12/19

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 ALP 112222.74 1 = ≈ 2GD = ≈ 2GD x 2GD MTX = U1 = nong nc U1 A=

03/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 ATL 396 0EQ = 4037 102 152 i 0EQ = >> i 2XP = 2XP MTX = U2 = nc nc U2 D

12/19

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 PAN 4254.04 1 = ≈ 4325 1667 2156 1911 i 0EQ - > 1911 i 0EQ = poor 2XP MTX - U1 + nong nong U1 C

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 CON 112942 1 - > 112942 47047 104872 65396 i 1 - > i 2GD - 2GD MTX - U1 = nc gen U1 C

12/19

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 MED 7000 1 = ≈ 7000 2GD = ≈ 2GD = poor 2GD MTX = U1 = nc nc U1 D

12/19

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
BG ALP 0.1 2XR = >> 6 10 fstems 2XP - >> 500 fstems 2GD - poor poor poor 2GD MTX - U1 = nong nc U1 0/2

03/20

Bulgarian Biodiversity Foundation

Institution: Bulgarian Biodiversity Foundation

Member State: BG

Bulgarian Biodiversity Foundation
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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.