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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 GR

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, Arthropods, Lycaena dispar, All bioregions. Annexes II, IV. Show all Arthropods
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 N/A N/A 21 grids1x1 minimum N/A N/A N/A N/A
BG N/A N/A 3 grids1x1 minimum N/A N/A N/A N/A
HR N/A N/A 7 grids1x1 minimum N/A N/A N/A N/A
IT N/A N/A 29 grids1x1 estimate N/A N/A N/A N/A
PL 110 330 200 grids1x1 estimate N/A N/A 22 localities estimate
RO N/A N/A 8600 grids1x1 estimate N/A N/A N/A N/A
SI 56 63 N/A grids1x1 minimum N/A N/A N/A N/A
SK 162 162 N/A grids1x1 estimate 8124 109569 N/A i N/A
FR 391 39100 N/A grids1x1 minimum N/A N/A N/A minimum
NL N/A N/A 62 grids1x1 estimate 200 1200 N/A i estimate
BG N/A N/A 7 grids1x1 minimum N/A N/A N/A N/A
RO N/A N/A 1100 grids1x1 estimate N/A N/A N/A N/A
EE 167 1000 N/A grids1x1 estimate N/A N/A N/A N/A
FI N/A N/A 56 grids1x1 minimum N/A N/A N/A N/A
LT N/A N/A 957 grids1x1 estimate N/A N/A N/A N/A
LV N/A N/A 343 grids1x1 estimate N/A N/A N/A N/A
AT N/A N/A 180 grids1x1 minimum N/A N/A N/A N/A
BE 157 280 157 grids1x1 minimum 300 3000 1000 adults estimate
BG N/A N/A 47 grids1x1 minimum N/A N/A N/A N/A
CZ N/A N/A 704 grids1x1 estimate N/A N/A N/A N/A
DE 639 1449 N/A grids1x1 estimate 572 619 595.50 grids5x5 estimate
FR 614 61400 N/A grids1x1 minimum N/A N/A N/A minimum
HR N/A N/A 184 grids1x1 minimum N/A N/A N/A N/A
IT N/A N/A 314 grids1x1 estimate N/A N/A N/A N/A
LU N/A N/A 1292 grids1x1 estimate N/A N/A N/A N/A
PL 3630 10890 7500 grids1x1 estimate N/A N/A 726 localities minimum
RO N/A N/A 24000 grids1x1 estimate N/A N/A N/A N/A
SI 597 604 N/A grids1x1 minimum N/A N/A N/A N/A
GR N/A N/A 5534 grids1x1 estimate 50 100 N/A adults estimate
HR N/A N/A 2 grids1x1 minimum N/A N/A N/A N/A
IT N/A N/A 18 grids1x1 estimate N/A N/A N/A N/A
CZ N/A N/A 73 grids1x1 estimate N/A N/A N/A N/A
HU N/A N/A 1925 grids1x1 minimum N/A N/A N/A N/A
RO N/A N/A 2200 grids1x1 estimate N/A N/A N/A N/A
SK 99 99 N/A grids1x1 estimate 69489 466365 N/A i N/A
RO N/A N/A 4700 grids1x1 estimate N/A N/A N/A N/A
FR N/A N/A 13 grids1x1 estimate N/A N/A 260 i estimate
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 2100 3.76 = N/A N/A 21 grids1x1 minimum b 0.23 = Y FV = good good good FV FV = FV noChange noChange 1500 b 7.28
BG ALP 8400 15.05 u 8400 N/A N/A 3 grids1x1 minimum c 0.03 u 3 grids1x1 Y FV = good unk good FV XX x FV method method 1200 c 5.83
HR ALP 2100 3.76 u x N/A N/A 7 grids1x1 minimum c 0.08 u x Unk U1 - unk unk unk XX U1 x N/A N/A 1200 d 5.83
IT ALP 7800 13.98 = N/A N/A 29 grids1x1 estimate b 0.32 = N N U1 - good good poor FV U1 - N/A N/A knowledge knowledge 1300 b 6.31
PL ALP 8300 14.88 = 110 330 200 grids1x1 estimate b 2.20 = x Y FV = good good good FV FV = FV noChange noChange 2500 b 12.14
RO ALP 8600 15.41 = > N/A N/A 8600 grids1x1 estimate b 94.70 = Y FV = good good good FV FV = FV knowledge knowledge 4400 a 21.36
SI ALP 4847 8.69 = 56 63 N/A grids1x1 minimum b 0.66 = Y FV = good good good FV FV = FV noChange noChange 1700 b 8.25
SK ALP 13650.99 24.47 = 162 162 N/A grids1x1 estimate b 1.78 = Y U1 = good poor poor U1 U1 = FV knowledge knowledge 6800 b 33.01
FR ATL 104100 99.62 = 391 39100 N/A grids1x1 minimum b 99.69 x > Y Unk U1 = good good good FV U1 = FV noChange noChange 47300 b 99.16
NL ATL 400 0.38 = >> N/A N/A 62 grids1x1 estimate a 0.31 + >> N N U2 - bad bad bad U2 U2 = U2 - noChange genuine 400 a 0.84
BG BLS 8200 88.17 u 8200 N/A N/A 7 grids1x1 minimum c 0.63 u 7 grids1x1 Y FV = good unk good FV XX x FV method method 1900 c 76
RO BLS 1100 11.83 = > N/A N/A 1100 grids1x1 estimate b 99.37 = Y FV = good good good FV FV = U1 N/A knowledge knowledge 600 a 24
EE BOR 32200 18.83 + 167 1000 N/A grids1x1 estimate a 30.09 + Y FV = good good good FV FV + FV noChange noChange 13100 a 27.01
FI BOR 8900 5.21 + N/A N/A 56 grids1x1 minimum b 2.89 + Y FV = good good good FV FV + FV noChange method 3300 a 6.80
LT BOR 65300 38.19 = N/A N/A 957 grids1x1 estimate b 49.34 u N Unk U1 u good unk poor XX U1 x U1 + knowledge knowledge 32100 b 66.19
LV BOR 64589 37.77 = 64589 N/A N/A 343 grids1x1 estimate b 17.68 + Y FV = good good good FV FV = FV noChange noChange N/A b 0
AT CON 10700 1.64 = N/A N/A 180 grids1x1 minimum b 0.27 = Y FV = good good good FV FV = FV noChange noChange 7900 b 2.74
BE CON 1426 0.22 = 157 280 157 grids1x1 minimum b 0.23 = Y FV + good good good FV FV + FV noChange noChange 1400 a 0.48
BG CON 47700 7.29 = 47700 N/A N/A 47 grids1x1 minimum c 0.07 = 47 grids1x1 Y FV = unk unk unk XX FV = FV method method 10300 c 3.57
CZ CON 61100 9.34 + N/A N/A 704 grids1x1 estimate a 1.05 + Y FV = good good good FV FV + FV noChange noChange 30600 a 10.60
DE CON 57281 8.75 + 639 1449 N/A grids1x1 estimate b 1.56 + 595 grids5x5 Y FV + good good good FV FV + FV noChange noChange 32900 b 11.40
FR CON 153300 23.43 = 614 61400 N/A grids1x1 minimum b 46.26 x Y FV = good good good FV FV = FV noChange noChange 62700 b 21.72
HR CON 26900 4.11 u N/A N/A 184 grids1x1 minimum c 0.27 u x Unk U1 - unk unk unk XX U1 x N/A N/A 12300 d 4.26
IT CON 57800 8.83 = N/A N/A 314 grids1x1 estimate a 0.47 = N Y U1 - good good poor U1 U1 - FV noChange knowledge 30000 b 10.39
LU CON 2900 0.44 = N/A N/A 1292 grids1x1 estimate b 1.93 u Y U1 - good poor unk U1 U1 x FV knowledge knowledge 2400 b 0.83
PL CON 199400 30.47 = 3630 10890 7500 grids1x1 estimate b 11.19 = Y FV = good good good FV FV = FV noChange noChange 73500 b 25.46
RO CON 24000 3.67 = > N/A N/A 24000 grids1x1 estimate b 35.81 = Y FV = good good good FV FV = FV knowledge knowledge 16900 a 5.85
SI CON 11825 1.81 = 597 604 N/A grids1x1 minimum b 0.90 = Y FV = good good good FV FV = FV noChange noChange 7800 b 2.70
GR MED 17420 78.75 = N/A N/A 5534 grids1x1 estimate c 99.64 - >> Unk XX x good bad unk U2 U2 - U2 - noChange noChange 5800 c 77.33
HR MED 300 1.36 u x N/A N/A 2 grids1x1 minimum c 0.04 u >> Unk U1 u unk unk unk XX U2 x N/A N/A 300 d 4
IT MED 4400 19.89 = N/A N/A 18 grids1x1 estimate b 0.32 = > N N U1 - good poor poor U1 U1 - U1 - noChange noChange 1400 b 18.67
CZ PAN 5400 7.79 = N/A N/A 73 grids1x1 estimate a 1.70 = Y FV = good good good FV FV = FV noChange genuine 2200 a 4.26
HU PAN 56210 81.10 = N/A N/A 1925 grids1x1 minimum b 44.80 = Y U1 u good good poor U1 U1 = U1 = noChange noChange 44500 b 86.24
RO PAN 2200 3.17 = > N/A N/A 2200 grids1x1 estimate b 51.20 = Y FV = good good good FV FV = U1 N/A knowledge knowledge 1600 a 3.10
SK PAN 5496.04 7.93 = 99 99 N/A grids1x1 estimate b 2.30 = Y U1 = good poor poor U1 U1 = FV knowledge knowledge 3300 b 6.40
RO STE 4700 100 = > N/A N/A 4700 grids1x1 estimate b 100 = Y FV = good good good FV FV = U1 N/A knowledge knowledge 3300 a 100
FR ALP 4000 0 = N/A N/A 13 grids1x1 estimate c 0 x Y FV = good good good FV FV = FV noChange noChange 1500 b 0
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 55797.99 2XP = ≈ 55797.99 8988.00 9215.00 9081.50 grids1x1 2XP = grids1x1 2XP = 2XP MTX = FV = nc nc FV A=

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 ATL 104500 2XP = ≈ 104500 453.00 39162.00 19807.50 grids1x1 2XP x > 2XP = 2XP MTX = U1 = nc nc U1 D

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 BLS 9300 2XP x > 1107.00 1107.00 1107 grids1x1 2XP = 0EQ = good good good 0EQ MTX = FV = nc nc FV A=

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 BOR 170989 0EQ = ≈ 170989 1523.00 2356.00 1939.50 grids1x1 0EQ + 2XP x good good 2XP MTX + U1 + nc nc U1 B1

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 CON 654332 2XP = ≈ 654332 32358.00 101344.00 67029.50 grids1x1 2XP x 2XP = 2XP MTX + FV = nc nong U1 A=

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 MED 22120 2XP = ≈ 22120 5554 grids1x1 2XP - >> 2XP - 2XP MTX - U2 - nc nc XX C

03/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 PAN 69306.04 0EQ = > 69306.04 4297.00 4297.00 4297 grids1x1 2XP = 2XP good 2XP MTX = U1 = nc nc U1 D

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 STE 4700 0MS = > 4700 grids1x1 0MS = 0MS = good good good 0MS MTX = U1 = nong nong U1 A=

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.