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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, Canis lupus, All bioregions. Annexes V. 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
BG 360 540 N/A i minimum N/A N/A N/A N/A
FI N/A 3 N/A i estimate N/A N/A N/A N/A
FR 387 477 430 i estimate N/A N/A N/A estimate
HR N/A N/A 75 i mean N/A N/A 20 p estimate
IT 329 375 N/A i minimum N/A N/A N/A N/A
PL N/A N/A 294 i estimate N/A N/A N/A N/A
RO 1500 1800 N/A i estimate N/A N/A N/A N/A
SI 49 53 N/A i interval N/A N/A N/A N/A
SK 300 600 N/A i estimate N/A N/A N/A N/A
DE 27 33 N/A i estimate 13 13 13 p estimate
ES 421 876 421 i estimate 356 N/A N/A grids10x10 minimum
PT N/A N/A 20 i minimum N/A N/A N/A N/A
BG 75 110 N/A i minimum N/A N/A N/A N/A
EE 180 260 N/A i mean 19 28 N/A bfemales mean
FI 165 190 180 i estimate 22 22 N/A bfemales estimate
LT 136 200 N/A i estimate N/A N/A N/A N/A
LV 1126 1187 N/A i estimate N/A N/A N/A N/A
SE 305 415 352 i mean N/A N/A N/A N/A
BG 365 550 N/A i minimum N/A N/A N/A N/A
CZ 5 80 N/A i estimate N/A N/A N/A N/A
DE 125 133 N/A i estimate 60 60 60 p estimate
FR N/A N/A N/A estimate 62 62 N/A estimate
HR N/A N/A 14 i mean 5 6 5 p estimate
IT 317 734 N/A i estimate N/A N/A N/A N/A
PL 896 2288 1592 i estimate N/A N/A N/A interval
RO 1000 1200 N/A i estimate N/A N/A N/A N/A
SI 23 25 N/A i interval N/A N/A N/A N/A
ES 803 1504 803 i estimate 222 N/A N/A grids10x10 minimum
FR N/A N/A N/A estimate N/A N/A N/A estimate
GR 907 1134 1020 i estimate N/A N/A N/A N/A
HR 83 105 95 i mean 25 26 25.50 p estimate
IT 717 1656 N/A i estimate N/A N/A N/A N/A
PT N/A N/A 98 i minimum N/A N/A N/A N/A
HU 40 60 N/A i estimate N/A N/A N/A N/A
SK 2 10 N/A i estimate N/A N/A N/A N/A
AT 6 8 N/A i minimum N/A N/A N/A minimum
ES N/A 10 N/A i minimum N/A N/A N/A N/A
SE N/A 5 N/A i estimate N/A N/A N/A N/A
BE 2 4 2 i estimate N/A N/A N/A N/A
FR N/A N/A N/A estimate N/A N/A N/A estimate
NL N/A N/A N/A N/A N/A N/A N/A
AT 23 28 N/A i minimum N/A N/A N/A minimum
BE N/A N/A 2 i estimate N/A N/A N/A N/A
LU 1 2 N/A i estimate 2 N/A N/A grids1x1 minimum
SE N/A 10 2 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
BG ALP 26000 13.16 = 26000 360 540 N/A i minimum b 11.99 = 375 i Y FV = unk unk unk XX FV = FV knowledge knowledge 13800 b 9.99
FI ALP 4500 2.28 = N/A 3 N/A i estimate b 0.04 = > Y FV = poor poor good U1 U1 = U1 = noChange noChange 1100 a 0.80
FR ALP 24692 12.50 + 387 477 430 i estimate a 11.46 + Y Unk FV + good good good FV FV + FV N/A N/A 23600 a 17.09
HR ALP 8615 4.36 = N/A N/A 75 i mean b 2 = > Y FV + good poor poor U1 U1 + N/A N/A N/A a 0
IT ALP 23100 11.69 + 329 375 N/A i minimum a 9.38 + Y FV = good good good FV FV + FV noChange genuine 19400 b 14.05
PL ALP 12800 6.48 = N/A N/A 294 i estimate b 7.83 = Y FV = good good good FV FV = FV noChange noChange 8000 a 5.79
RO ALP 67300 34.06 = 1500 1800 N/A i estimate a 43.96 = 1600 i Y FV = good good good FV FV = FV noChange noChange 48800 a 35.34
SI ALP 4086 2.07 + 49 53 N/A i interval a 1.36 + Y FV = good good good FV FV + U1 = genuine genuine 3500 a 2.53
SK ALP 26500.79 13.41 = 300 600 N/A i estimate b 11.99 = Y FV + good good good FV FV = FV N/A knowledge 19900 b 14.41
DE ATL 8039 12.79 + >> 27 33 N/A i estimate a 6.37 + >> p N Y U1 = good good poor U1 U2 + U2 + noChange noChange 5400 a 13.11
ES ATL 50600 80.52 = 421 876 421 i estimate b 89.38 u 356 grids10x10 Y FV = unk unk good XX U1 = FV knowledge knowledge 32800 a 79.61
PT ATL 4200 6.68 = N/A N/A 20 i minimum b 4.25 = Unk XX = good good unk FV FV = FV noChange noChange 3000 b 7.28
BG BLS 7200 100 = 7200 75 110 N/A i minimum b 100 = 68 i Y FV = poor poor poor U1 U1 = FV knowledge knowledge 3500 b 100
EE BOR 53500 7.05 + 180 260 N/A i mean a 10.59 + Y FV = good good good FV FV + FV noChange noChange 52300 a 10.32
FI BOR 337400 44.45 + 165 190 180 i estimate a 8.67 = > Y FV = good unk good FV U1 + U1 - noChange genuine 233900 a 46.13
LT BOR 64700 8.52 = 136 200 N/A i estimate b 8.09 = Y FV = good good good FV FV = U1 = genuine genuine 67600 b 13.33
LV BOR 64589 8.51 = 64589 1126 1187 N/A i estimate b 55.69 + 300 i Y FV = good unk good FV FV + FV noChange noChange 37500 a 7.40
SE BOR 238800 31.46 + 238800 305 415 352 i mean a 16.95 + 300 i Y FV = good good good FV FV + FV noChange noChange 115700 a 22.82
BG CON 88800 20.68 = 88800 365 550 N/A i minimum b 11.78 = 477 i Y FV = poor poor poor U1 U1 = FV knowledge knowledge 26600 b 10.90
CZ CON 22800 5.31 + > 5 80 N/A i estimate a 1.09 + > Y FV = poor poor good FV U1 + U2 = genuine genuine 11800 a 4.83
DE CON 22490 5.24 + >> 125 133 N/A i estimate a 3.32 + >> p N Y U1 = good good poor U1 U2 + U2 + noChange noChange 14700 a 6.02
FR CON 17512 4.08 + N/A N/A N/A estimate a 0 + < Y Unk FV + unk unk unk XX FV + FV noChange noChange 27800 a 11.39
HR CON 4688 1.09 + x N/A N/A 14 i mean b 0.36 + > N Unk XX + poor poor poor U1 U1 + N/A N/A N/A a 0
IT CON 31800 7.40 + 317 734 N/A i estimate b 13.53 + Y FV = good good good FV FV + FV noChange genuine 26800 b 10.98
PL CON 149900 34.90 + > 896 2288 1592 i estimate b 40.98 + > Y FV = good good good FV U1 + U1 + noChange noChange 77800 a 31.87
RO CON 87200 20.30 = 1000 1200 N/A i estimate a 28.32 = 1100 i Y FV = good good good FV FV = FV noChange noChange 55700 a 22.82
SI CON 4291 1 + 23 25 N/A i interval a 0.62 + Y FV = good good good FV FV + U1 = genuine genuine 2900 a 1.19
ES MED 70100 26.16 u > 803 1504 803 i estimate b 25.07 u 222 grids10x10 Y FV = unk unk good XX U1 = FV knowledge knowledge 21200 a 10.58
FR MED 27366 10.21 + N/A N/A N/A estimate a 0 + < Y Unk FV + good good good FV FV + FV noChange noChange 25900 a 12.92
GR MED 73305 27.36 + 907 1134 1020 i estimate b 31.85 + > N N U1 + good poor poor U1 U1 + U1 + noChange noChange 73400 b 36.63
HR MED 8887 3.32 = 83 105 95 i mean b 2.97 - > N Unk U1 - good poor poor U1 U1 - N/A N/A N/A a 0
IT MED 64800 24.18 + 717 1656 N/A i estimate b 37.05 + Y FV + good good good FV FV + FV noChange genuine 59400 b 29.64
PT MED 23500 8.77 = > N/A N/A 98 i minimum c 3.06 = > Unk XX = poor poor unk U1 U1 = U1 = noChange noChange 20500 b 10.23
HU PAN 3631 66.88 + > 40 60 N/A i estimate b 89.29 + > Y FV = good poor good U1 U1 + U1 x noChange genuine 3700 a 75.51
SK PAN 1798.45 33.12 + > 2 10 N/A i estimate b 10.71 + > Y U1 + good unk unk XX U1 = U1 = N/A N/A 1200 b 24.49
AT ALP 8900 0 + N/ 6 8 N/A i minimum c 0 x N/ N/A N N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A 5500 b 0
ES ALP N/A 0 x > N/A 10 N/A i minimum b 0 + x Y FV = poor unk good XX U1 x N/A N/A knowledge knowledge N/A a 0
SE ALP 15800 0 N N/ N/A 5 N/A i estimate N/A 0 N N/ N/A N N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A 5700 a 0
BE ATL 1200 0 + N/ 2 4 2 i estimate b 0 N N/ XX N N/A N/A N/A XX XX N/A N/A N/A N/A 1000 b 0
FR ATL 600 0 N N/ N/A N/A N/A estimate a 0 + N/ Unk Unk XX N N/A N/A N/A XX XX x N/A N/A noChange noChange 700 a 0
NL ATL N/A 0 N N/ N/A N/A N/A N/A 0 N N/ N/A 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 0
AT CON 6400 0 + N/ 23 28 N/A i minimum b 0 + N/ N/A N N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A 3600 b 0
BE CON 400 0 u N/ N/A N/A 2 i estimate N/A 0 N N/ N/A N N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A 200 b 0
LU CON 200 0 + >> 1 2 N/A i estimate c 0 + >> N Y FV + unk poor good U1 U2 + N/A N/A genuine genuine 200 c 0
SE CON 12700 0 N N/ N/A 10 2 i estimate N/A 0 N N/ N/A N N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A 2900 a 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 PAN 5429 1 + > 5429 42 70 56 i 1 + > 56 i 2GD = good poor good 2GD MTX + U1 = nc gen U1 B1

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 CON 406681 1 + > 406681 2740 4944 3842 i 2GD + > 3842 i 2GD = unk unk unk 2GD MTX + U1 + nc nc U1 B1

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 ALP 197593.79 1 + ≈ 197593.79 3294 4217 3753 i 2XP = ≈ 3753 i 2XP + good good good 2XP MTX = FV = nc nc FV A=

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 ATL 62839 1 + > 62839 468 929 471 i 2XP x > 471 i 2XP = unk unk unk 2XP MTX = FV = nong nc FV D

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 MED 267958 1 + > 267958 2608 4497 3202 i 2GD + > 3202 i 2GD + unk unk unk 2GD MTX + U1 + nc nc U1 B1

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 BLS 7200 0MS = ≈ 7200 75 110 92 i 0MS = ≈ 68 i 0MS = poor poor poor 0MS MTX = U1 = nc nc U1 D

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 BOR 758989 1 + ≈ 758989 1912 2252 2076 i 2GD + > 2076 i 2GD = good unk good 2GD MTX + U1 = nc gen FV C

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
AT ALP 2XP 2XR >> 2XP 3XP 0/2

03/20

Naturschutzbund Österreich

Institution: Naturschutzbund Österreich

Member State: AT

Naturschutzbund Österreich
AT CON 2XP 2XR 3XP 0/2

03/20

Naturschutzbund Österreich

Institution: Naturschutzbund Österreich

Member State: AT

Naturschutzbund Österreich
BG CON 550 1221 1221 2XP + + good good good 2XP 3XP + FV + FV 0/3

03/20

Union of Hunters and Anglers in Bulgaria

Institution: Union of Hunters and Anglers in Bulgaria

Member State: BG

Union of Hunters and Anglers in Bulgaria
ES ALP N/A 2XP + > 10 30 30 2XP + > 2XP = good good good 2XP MTX + FV = FV A+ 0/1

03/20

REAL FEDERACION ESPAÑOLA DE CAZA

Institution: REAL FEDERACION ESPAÑOLA DE CAZA

Member State: ES

REAL FEDERACION ESPAÑOLA DE CAZA
ES MED 2XP 1040 2013 1500 2GD + > 2GD = 2GD MTX + FV + FV A+ 0/1

03/20

REAL FEDERACION ESPAÑOLA DE CAZA

Institution: REAL FEDERACION ESPAÑOLA DE CAZA

Member State: ES

REAL FEDERACION ESPAÑOLA DE CAZA
EU28 ATL N/A 1 + > 600 1200 900 2XP + > 2XP + 2XP MTX FV = FV A+ 0/1

03/20

REAL FEDERACION ESPAÑOLA DE CAZA

Institution: REAL FEDERACION ESPAÑOLA DE CAZA

Member State: ES

REAL FEDERACION ESPAÑOLA DE CAZA
EU28 BOR 0MS good U1 = FV 0/2

03/20

ANC Tapiola

Institution: ANC Tapiola

Member State: FI

ANC Tapiola
LT BOR 500 i 2XP U1 = FV 0/2

03/20

European Federation for Hunting and Conservat

Institution: European Federation for Hunting and Conservat

Member State: BE

European Federation for Hunting and Conservat
BG ALP poor 2XP 3XP = U1 = U1 D 0/2

03/20

BALKANI Wildlife Society

Institution: BALKANI Wildlife Society

Member State: BG

BALKANI Wildlife Society
BG ALP 540 980 980 + good good good 2XP 3XP + FV FV 0/3

03/20

Union of Hunters and Anglers in Bulgaria

Institution: Union of Hunters and Anglers in Bulgaria

Member State: BG

Union of Hunters and Anglers in Bulgaria
PL CON 2XR 2868 i 2XP 2XR 2XP MTX U1 + U1 0/2

04/20

European Federation for Hunting and Conservat

Institution: European Federation for Hunting and Conservat

Member State: BE

European Federation for Hunting and Conservat
BG BLS 110 241 241 + good good good 2XP 3XP + FV FV 0/3

03/20

Union of Hunters and Anglers in Bulgaria

Institution: Union of Hunters and Anglers in Bulgaria

Member State: BG

Union of Hunters and Anglers in Bulgaria
DE CON 2XR + 2XP + < 2XR = good good good 2XP MTX + U1 + gen gen U1 0/2

04/20

Deutscher Jagdverband

Institution: Deutscher Jagdverband

Member State: DE

Deutscher Jagdverband
DE ATL 2XR + p 2XP + < 2XR = good good good 2XP MTX + FV gen gen U1 0/2

04/20

Deutscher Jagdverband

Institution: Deutscher Jagdverband

Member State: DE

Deutscher Jagdverband
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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.