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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 HR

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, Mammals, Lynx lynx, 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
AT 12 16 N/A i minimum N/A N/A N/A N/A
BG N/A N/A N/A i minimum N/A N/A N/A N/A
FI 4 6 N/A i estimate N/A N/A N/A N/A
FR 13 21 N/A i estimate N/A N/A N/A estimate
HR N/A N/A 40 i minimum N/A N/A N/A N/A
IT N/A N/A 2 i estimate N/A N/A N/A N/A
PL N/A N/A 56 i minimum N/A N/A N/A N/A
RO 1500 1700 N/A i estimate N/A N/A N/A N/A
SE 159 248 212 i mean N/A N/A N/A N/A
SI 9 13 N/A i estimate N/A N/A N/A N/A
SK 300 400 N/A i estimate N/A N/A N/A N/A
EE 300 420 N/A i mean 46 64 N/A bfemales mean
FI 1865 1990 N/A i estimate 332 375 N/A bfemales estimate
LT N/A N/A 150 i minimum N/A N/A N/A N/A
LV 1633 1747 N/A i estimate N/A N/A N/A N/A
SE 681 1056 903 i mean N/A N/A N/A N/A
AT 5 19 N/A i minimum N/A N/A N/A N/A
BG N/A N/A N/A i minimum N/A N/A N/A N/A
CZ 65 100 N/A i estimate N/A N/A N/A N/A
DE 47 69 N/A i estimate 16 16 16 bfemales estimate
FR 95 151 N/A i estimate N/A N/A N/A estimate
PL N/A N/A 67 i minimum N/A N/A N/A N/A
RO 600 700 N/A i estimate N/A N/A N/A N/A
SI 1 2 N/A i estimate N/A N/A N/A N/A
GR N/A N/A N/A N/A N/A N/A N/A
HU 10 25 N/A i estimate N/A N/A N/A N/A
NL N/A N/A N/A N/A N/A N/A N/A
BG N/A N/A N/A i minimum N/A N/A N/A N/A
HR N/A N/A 5 i estimate N/A N/A N/A N/A
SE N/A 10 5 i N/A N/A N/A N/A
FR 95 151 N/A i estimate N/A N/A N/A estimate
HR N/A N/A 10 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
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 4700 2.21 + >> 12 16 N/A i minimum b 0.61 x > N Y FV x bad poor poor U2 U2 x U2 x noChange noChange 3600 b 2.99
BG ALP 6600 3.10 u 6600 N/A N/A N/A i minimum c 0 x Unk XX x unk unk unk XX XX x U1 + method method 700 b 0.58
FI ALP 16400 7.71 = 4 6 N/A i estimate b 0.22 = Y FV = unk unk good XX FV = FV noChange noChange 4500 a 3.74
FR ALP 1200 0.56 = > 13 21 N/A i estimate b 0.74 = > Unk Y FV + unk unk unk XX U1 + U1 x noChange noChange 6500 b 5.40
HR ALP 8327 3.91 = N/A N/A 40 i minimum b 1.73 u >> N Unk U1 u good poor poor U1 U2 x N/A N/A N/A b 0
IT ALP 200 0.09 - >> N/A N/A 2 i estimate a 0.09 - >> Y FV = bad bad good U2 U2 - U2 - noChange noChange 200 a 0.17
PL ALP 12700 5.97 = N/A N/A 56 i minimum b 2.43 = > Y FV = good poor poor U1 U1 = U1 - noChange noChange 7500 a 6.23
RO ALP 63300 29.76 = 1500 1700 N/A i estimate a 69.35 = 1700 i Y FV = good good good FV FV = FV noChange noChange 47100 a 39.15
SE ALP 81300 38.22 = 81300 159 248 212 i mean a 9.19 = 160 i Y FV = good good good FV FV = FV noChange noChange 32500 b 27.02
SI ALP 3270 1.54 - > 9 13 N/A i estimate c 0.48 - >> Y FV = good good good FV U2 - U2 - noChange noChange 2700 b 2.24
SK ALP 14712.97 6.92 = > 300 400 N/A i estimate b 15.17 = Y U1 = good good good FV U1 = U1 = N/A N/A 15000 b 12.47
EE BOR 52600 6.12 + 300 420 N/A i mean a 7.16 - > Y FV = good good good FV U2 = FV genuine noChange 53100 a 8.70
FI BOR 346100 40.26 = 1865 1990 N/A i estimate a 38.32 + Y FV = good good good FV FV + FV N/A N/A 265500 a 43.52
LT BOR 56530 6.58 = N/A N/A 150 i minimum b 2.98 + > Unk U1 = good unk unk XX U1 + U2 = knowledge knowledge 68200 b 11.18
LV BOR 64589 7.51 = 64589 1633 1747 N/A i estimate b 33.60 + 600 i Y FV = good unk good FV FV + FV noChange noChange 24900 a 4.08
SE BOR 339900 39.54 + 339900 681 1056 903 i mean a 17.95 = 710 i Y FV = good good good FV FV = FV noChange noChange 198400 b 32.52
AT CON 3500 2.52 = > 5 19 N/A i minimum b 1.21 = > N Y FV = poor poor poor U1 U1 = U1 x noChange knowledge 2000 b 2.22
BG CON 13900 10.02 u 13900 N/A N/A N/A i minimum c 0 x Unk XX x unk unk unk XX XX x U1 + method method 1600 b 1.78
CZ CON 29600 21.35 + > 65 100 N/A i estimate a 8.30 = > Y FV = poor poor good U1 U1 + U1 = noChange noChange 14700 a 16.33
DE CON 9538 6.88 + >> 47 69 N/A i estimate a 5.84 + >> bfemales N Y U1 - poor poor poor U1 U2 = U2 x noChange method 6800 a 7.56
FR CON 14568 10.51 + 95 151 N/A i estimate b 12.37 + > Unk Y FV = unk unk good XX U1 + FV noChange noChange 21100 b 23.44
PL CON 19900 14.35 = > N/A N/A 67 i minimum b 6.74 = > N N U1 = poor poor bad U2 U2 = U2 - noChange noChange 11200 a 12.44
RO CON 45700 32.96 = 600 700 N/A i estimate a 65.39 = 600 i Y FV = good good good FV FV = FV noChange noChange 31200 a 34.67
SI CON 1957 1.41 - > 1 2 N/A i estimate c 0.15 - >> Y FV = good good good FV U2 - U2 - noChange noChange 1400 b 1.56
GR MED 2127 100 x x N/A N/A N/A d 0 x x Unk XX x unk unk unk XX XX XX noChange noChange 2500 c 100
HU PAN 3255 100 = > 10 25 N/A i estimate c 100 = >> Y U1 = poor bad poor U2 U2 = U2 x noChange knowledge 2500 a 100
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
BG BLS 800 0 x 800 N/A N/A N/A i minimum c 0 x Unk XX x unk unk unk XX XX x U1 + method method 300 b 0
HR CON 1234 0 x > N/A N/A 5 i estimate b 0 x x N Unk U1 x poor poor poor U1 U1 x N/A N/A N/A b 0
SE CON 8800 0 N N/ N/A 10 5 i b 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 b 0
FR MED 99 0 = x 95 151 N/A i estimate a 0 = x Unk Unk XX x unk unk unk XX XX = N/A N/A noChange noChange 300 b 0
HR MED 2388 0 x x N/A N/A 10 i estimate c 0 x x N Unk U1 x poor poor poor U1 U1 x N/A N/A N/A b 0
SK PAN 326.98 0 x > 2 10 N/A i estimate b 0 x > Y U1 x poor poor poor U1 U1 = U1 = N/A N/A 400 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 PAN 3255 0MS = > 3255 10 25 17 i 0MS = >> 10 i 0MS = poor bad poor 0MS MTX = U2 x nc nc U2 D

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 CON 138663 1 + > 138663 880 1108 994 i 1 + > 994 i 2GD = poor poor good 2GD MTX + U1 = nc nong U1 B1

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 MED 4614 0EQ x x 105 161 133 i 0EQ x x 2XR x unk unk unk 2XR MTX x XX nc nong U2 E

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 ALP 212709 1 = > 212709 2095 2502 2307 i 1 = > 2307 i 2XP = good poor good 2XP MTX = FV = nong nc FV D

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 ATL 0MS 0MS 0MS 0MS MTX

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 BLS 800 0MS x 0MS x 0MS x unk unk unk 0MS MTX x

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 BOR 859719 1 + ≈ 859719 4629 5363 5030 i 2XP + ≈ 5030 i 2XP = good unk good 2XP MTX + FV nc nong FV A=

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
BG CON 2XP 2XP 2GD 2XP MTX U1 = U1 0/2

03/20

Bulgarian Biodiversity Foundation

Institution: Bulgarian Biodiversity Foundation

Member State: BG

Bulgarian Biodiversity Foundation
BG ALP 2XP 2XP 2GD 2XP MTX FV = FV 0/2

03/20

Bulgarian Biodiversity Foundation

Institution: Bulgarian Biodiversity Foundation

Member State: BG

Bulgarian Biodiversity Foundation
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.