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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.

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, Mammals, Mustela putorius, All bioregions. Annexes N, N, Y. Show all Mammals
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 10000 30000 N/A i minimum 1335 1335 N/A grids1x1 minimum
BG 80 80 N/A i minimum N/A N/A N/A N/A
DE N/A N/A N/A i estimate 40 40 40 grids10x10 estimate
ES 170 850 N/A i estimate 33 N/A N/A grids10x10 minimum
FR N/A N/A N/A mean 1800 7000 N/A area mean
HR N/A N/A 632 i mean N/A N/A N/A N/A
IT 58 290 N/A i estimate N/A N/A N/A N/A
PL N/A N/A 1000 i minimum N/A N/A N/A N/A
RO 2800 4300 N/A i minimum N/A N/A N/A N/A
SI N/A N/A 12 i minimum 12 14 N/A grids1x1 minimum
SK 1000 3000 N/A i estimate N/A N/A N/A N/A
BE 2750 8400 5575 i estimate 2750 5800 4275 grids1x1 estimate
DE N/A N/A N/A i estimate 176 186 181 grids10x10 estimate
DK N/A N/A N/A N/A N/A N/A N/A
ES 1800 9200 N/A i estimate 415 N/A N/A grids10x10 N/A
FR N/A N/A N/A mean 87900 178600 N/A area mean
NL 10000 100000 N/A i estimate N/A N/A N/A N/A
PT N/A N/A N/A N/A N/A N/A N/A
UK 67945 99483 83600 i interval N/A N/A N/A N/A
BG 160 160 N/A i minimum N/A N/A N/A N/A
EE 5000 20000 N/A i estimate N/A N/A N/A N/A
FI 3000 7000 N/A i estimate N/A N/A N/A N/A
LT 4000 20000 N/A i minimum N/A N/A N/A N/A
LV 13612 14391 N/A i estimate N/A N/A N/A N/A
SE 6000 29000 17000 i estimate N/A N/A N/A N/A
AT 14000 40000 N/A i minimum 1757 1757 N/A grids1x1 N/A
BE 5160 10320 N/A i estimate N/A N/A 549 grids1x1 estimate
BG 560 560 N/A i minimum N/A N/A N/A N/A
CZ 30000 40000 N/A i estimate N/A N/A N/A N/A
DE N/A N/A N/A i estimate 1334 1364 1351.50 grids10x10 estimate
DK N/A N/A N/A N/A N/A N/A N/A
FR N/A N/A N/A mean 46500 129900 N/A area mean
HR N/A N/A 1777 i mean N/A N/A N/A N/A
IT 272 1360 N/A i estimate N/A N/A N/A N/A
LU 420 N/A N/A i minimum N/A N/A 642 grids1x1 estimate
PL N/A N/A 10000 i minimum N/A N/A N/A N/A
RO 12800 15400 N/A i minimum N/A N/A N/A N/A
SE 4000 11000 7000 i estimate N/A N/A N/A N/A
SI N/A N/A 36 i minimum 36 38 N/A grids1x1 minimum
ES 9400 47000 N/A i estimate 1074 N/A N/A grids10x10 N/A
FR N/A N/A N/A mean 2700 16700 N/A area mean
GR N/A N/A N/A N/A N/A 153 grids10x10 estimate
HR N/A N/A 236 i mean N/A N/A N/A N/A
IT 191 955 N/A i estimate N/A N/A N/A estimate
PT N/A N/A N/A N/A N/A N/A N/A
CZ 1000 2000 N/A i estimate N/A N/A N/A N/A
HU N/A N/A 26135 i estimate N/A N/A N/A N/A
RO 1200 1400 N/A i minimum N/A N/A N/A N/A
SK 1000 3000 N/A i estimate N/A N/A N/A N/A
RO 3200 3400 N/A i minimum 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 48900 29.81 = 10000 30000 N/A i minimum c 71.54 x Y FV x good unk good FV FV x FV noChange noChange 41700 b 40.33
BG ALP 200 0.12 x 200 80 80 N/A i minimum b 0.29 x 80 i Unk XX x unk unk unk XX XX x XX knowledge knowledge 100 b 0.10
DE ALP 4155 2.53 = 4155 N/A N/A N/A i estimate c 0 = 40 grids10x10 Y FV = good good good FV FV = FV noChange noChange 5400 d 5.22
ES ALP 12200 7.44 = 170 850 N/A i estimate c 1.82 x 850 i Y FV = good unk poor FV FV = FV N/A N/A 2700 a 2.61
FR ALP 7000 4.27 = N/A N/A N/A mean b 0 u > Y FV = poor poor poor U1 U1 = U1 - noChange noChange 6900 b 6.67
HR ALP 3805.37 2.32 = N/A N/A 632 i mean c 2.26 x x Y XX x good unk good FV XX N/A N/A N/A d 0
IT ALP 22100 13.47 = x 58 290 N/A i estimate c 0.62 = x Y FV = good good good FV FV = FV noChange noChange 5600 b 5.42
PL ALP 9500 5.79 = N/A N/A 1000 i minimum b 3.58 = Y FV = good good good FV FV = FV noChange noChange 4400 b 4.26
RO ALP 47200 28.77 = x 2800 4300 N/A i minimum b 12.70 = 4300 i Y FV = good good good FV FV + FV N/A N/A 35300 b 34.14
SI ALP 7656 4.67 = 7656 N/A N/A 12 i minimum c 0.04 x x Y FV x good unk unk XX XX XX noChange noChange 700 c 0.68
SK ALP 1348.72 0.82 - > 1000 3000 N/A i estimate c 7.15 - > Y U1 - poor poor poor U1 U1 - U1 - N/A N/A 600 c 0.58
BE ATL 22500 4.59 u 2750 8400 5575 i estimate b 3.72 = > Y U1 - good poor poor U1 U1 x U2 - noChange genuine 18600 b 4.75
DE ATL 70501 14.37 = 70501 N/A N/A N/A i estimate b 0 x grids10x10 Unk U1 - unk poor poor U1 U1 x U1 - noChange method 17700 d 4.52
DK ATL N/A 0 = N/A N/A N/A d 0 - > Y U1 - good poor poor U1 U1 - FV N/A N/A N/A c 0
ES ATL 68200 13.90 = 1800 9200 N/A i estimate b 3.67 x 9200 i Y FV = good unk poor FV FV = U1 = N/A N/A 41900 a 10.69
FR ATL 178600 36.39 = N/A N/A N/A mean b 0 u Unk N U1 x unk unk unk XX U1 x FV genuine genuine 196500 b 50.14
NL ATL 40600 8.27 = 10000 100000 N/A i estimate c 36.75 x N N U1 - good unk poor U1 U1 x U2 - noInfo noInfo 37000 a 9.44
PT ATL 1100 0.22 x x N/A N/A N/A d 0 - x Unk XX - unk poor unk XX U1 x XX noInfo noChange 500 d 0.13
UK ATL 109229 22.26 + 109229 67945 99483 83600 i interval b 55.85 + 83600 i Y FV = good good good FV FV + FV noChange noChange 79700 b 20.34
BG BLS 600 100 u 600 160 160 N/A i minimum b 100 x 160 i Unk XX x unk unk unk XX XX x XX method method 200 b 100
EE BOR 45800 12.56 + 5000 20000 N/A i estimate c 20.66 = Y FV = good good good FV FV + FV noChange noChange 45300 a 17.52
FI BOR 51300 14.07 = 3000 7000 N/A i estimate c 8.26 u > Y FV = good unk unk XX U1 = U1 - noChange knowledge 8700 b 3.37
LT BOR 64700 17.74 = 4000 20000 N/A i minimum c 19.83 = x Y FV = good good good FV FV = FV noChange noChange 68400 c 26.46
LV BOR 64589 17.71 = 64589 13612 14391 N/A i estimate b 23.14 + 10000 i Y FV = good good good FV FV + FV noChange noChange 1900 d 0.74
SE BOR 138300 37.92 + 86700 6000 29000 17000 i estimate c 28.10 u 11000 i Y FV = good good good FV FV = FV noChange noChange 134200 b 51.91
AT CON 38400 3.39 = 14000 40000 N/A i minimum c 25.85 x Y FV x good good good FV FV x FV noChange noChange 33000 b 3.99
BE CON 15000 1.32 u 5160 10320 N/A i estimate b 7.41 = > Y U1 = good unk good FV U1 x U1 - noChange knowledge 12200 b 1.48
BG CON 3000 0.26 x 3000 560 560 N/A i minimum b 0.54 x 560 i Unk XX x unk unk unk XX XX x XX noChange knowledge 700 b 0.08
CZ CON 85300 7.52 = 30000 40000 N/A i estimate c 33.51 x x Y FV = good unk good FV FV = FV noChange noChange 76400 a 9.24
DE CON 283617 25 - x N/A N/A N/A i estimate c 0 - x grids10x10 Unk U1 - unk unk poor XX U1 - U1 x noChange genuine 175300 d 21.20
DK CON N/A 0 = N/A N/A N/A d 0 - > Y U1 - good poor poor U1 U1 - FV N/A N/A N/A c 0
FR CON 129900 11.45 = N/A N/A N/A mean b 0 = Y Unk U1 x unk unk unk XX U1 = FV method noChange 146700 b 17.74
HR CON 17416.99 1.54 = N/A N/A 1777 i mean c 1.70 x x Y XX x good unk unk XX XX N/A N/A N/A d 0
IT CON 72800 6.42 = 272 1360 N/A i estimate c 0.78 = Y FV = good good good FV FV = FV noChange noChange 27400 b 3.31
LU CON 3100 0.27 x 420 N/A N/A i minimum c 0.40 x 2426 grids1x1 Y U1 x good unk poor U1 U1 x XX knowledge noInfo 3100 c 0.37
PL CON 308700 27.21 = N/A N/A 10000 i minimum b 9.57 = Y FV = good good good FV FV = FV noChange noChange 204500 b 24.73
RO CON 141400 12.47 = x 12800 15400 N/A i minimum b 13.50 = 15400 i Y FV = good good good FV FV + FV N/A N/A 125300 b 15.15
SE CON 23100 2.04 = 23100 4000 11000 7000 i estimate b 6.70 u 7000 i Y FV = good good good FV FV = FV noChange noChange 19300 b 2.33
SI CON 12616 1.11 = 12616 N/A N/A 36 i minimum c 0.03 x x Y FV x good unk unk XX XX XX noChange noChange 3100 c 0.37
ES MED 349900 72.74 = 9400 47000 N/A i estimate b 97.21 x 47000 i Y FV = good unk poor FV FV = U1 = N/A N/A 117100 a 65.68
FR MED 16700 3.47 = > N/A N/A N/A mean b 0 x > Y FV = unk unk unk XX U1 = U1 - noChange N/A 22600 b 12.68
GR MED 10914 2.27 x x N/A N/A N/A c 0 x x Unk XX = unk unk unk XX XX XX noChange noChange 9000 c 5.05
HR MED 7496.67 1.56 = N/A N/A 236 i mean c 0.81 x x Y XX x good unk good FV XX N/A N/A N/A d 0
IT MED 74200 15.43 = 191 955 N/A i estimate c 1.98 = Y FV = good good good FV FV = XX noChange noChange 19100 b 10.71
PT MED 21800 4.53 x x N/A N/A N/A d 0 - x Unk XX - unk poor unk XX U1 x XX noInfo noChange 10500 d 5.89
CZ PAN 5800 5.10 = 1000 2000 N/A i estimate c 4.85 x x Y FV = good unk good FV FV = FV noChange noChange 3400 a 4.82
HU PAN 93011 81.77 = N/A N/A 26135 i estimate c 84.48 = Y FV = good good good FV FV = FV noChange method 54900 b 77.87
RO PAN 14800 13.01 = x 1200 1400 N/A i minimum b 4.20 = 1400 i Y FV = good good good FV FV + FV N/A N/A 12000 b 17.02
SK PAN 142.95 0.13 - > 1000 3000 N/A i estimate c 6.47 - > Y U1 - poor poor poor U1 U1 - U1 - N/A N/A 200 c 0.28
RO STE 36000 100 = x 3200 3400 N/A i minimum b 100 = 3400 i Y FV x good good good FV FV + XX N/A N/A 33900 b 100
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 164065 1 = ≈ 164199 15752 40164 27958 i 2GD x ≈ 27958 i 2GD = good good good 2GD MTX x U1 = nong nong U1 A=

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 ATL 490730 1 + ≈ 490730 2GD + > i 2GD - unk unk poor 2GD MTX x U1 = nc nong U1 D

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 BLS 600 1 x ≈ 600 160 160 160 i 1 x ≈ 160 i 0MS x unk unk unk 0MS MTX x XX nc nong XX D

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 BOR 364689 1 + ≈ 313089 31612 90391 60501 i 1 + ≈ 60501 i 0EQ = good good good 2XP MTX + FV nc nong FV A=

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 CON 1134349 1 - ≈ 1162710 2XR x 2XR - unk unk unk 2XR MTX x U1 = nc nong U1 D

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 MED 481010 2GD = > 481010 9827 48191 29009 i 2GD x ≈ 47000 i 2GD = good unk poor 2GD MTX = XX = nong nc XX A=

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 PAN 113753 1 = ≈ 113767 29335 32535 30935 i 2XP = ≈ 30935 i 2XP = good good good 2XP MTX = FV nc nong FV A=

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 STE 36000 0MS = x 3200 3400 3300 i 0MS = ≈ 3400 i 0MS x good good good 0MS MTX + XX nong nong XX A=

12/19

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
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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.