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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 AT

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, Ursus arctos, All bioregions. Annexes N, Y, N. 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 2 8 N/A i minimum N/A N/A N/A minimum
BG 343 510 N/A i estimate N/A N/A N/A N/A
ES 31 33 N/A i estimate 10 N/A N/A bfemales estimate
FI 30 60 N/A i estimate N/A N/A N/A N/A
FR N/A N/A 43 i estimate N/A N/A N/A estimate
HR N/A N/A 750 i estimate N/A N/A N/A N/A
IT 45 63 N/A i estimate N/A N/A N/A N/A
PL 99 166 122 i interval N/A N/A N/A N/A
RO 4650 5150 N/A i mean N/A N/A N/A N/A
SE 619 666 643 i interval N/A N/A N/A N/A
SI 409 491 N/A i interval N/A N/A N/A N/A
SK 900 1300 N/A i estimate N/A N/A N/A N/A
ES 243 292 N/A i estimate 35 41 40 bfemales estimate
EE 650 700 N/A i mean 58 74 N/A bfemales mean
FI 1900 2200 2050 i estimate N/A N/A N/A N/A
LV 23 30 N/A i minimum N/A N/A N/A N/A
SE 2152 2314 2234 i interval N/A N/A N/A N/A
BG 27 40 N/A i estimate N/A N/A N/A N/A
CZ N/A 3 N/A i N/A N/A N/A N/A
RO 1800 2050 N/A i estimate N/A N/A N/A N/A
SI 136 164 N/A i interval N/A N/A N/A N/A
ES 55 N/A N/A i estimate 10 N/A N/A bfemales estimate
GR 400 500 N/A i estimate N/A N/A N/A N/A
HR N/A N/A 83 i estimate N/A N/A N/A N/A
IT 45 69 N/A i interval N/A N/A N/A N/A
HR N/A N/A 167 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 7200 2.92 - >> 2 8 N/A i minimum b 0.06 - >> Y FV = bad bad good U2 U2 - U2 - noChange noChange 4000 b 2.55
BG ALP 23800 9.65 = 23800 343 510 N/A i estimate a 4.98 - 480 i Y FV = poor poor poor U1 U1 - FV knowledge method 13600 a 8.66
ES ALP 9200 3.73 + 31 33 N/A i estimate b 0.37 + 200 i Y FV = poor poor good FV U2 + U2 + genuine noChange 5400 a 3.44
FI ALP 12700 5.15 = 30 60 N/A i estimate c 0.53 = Y FV = good good good FV FV = FV noChange noChange 3500 a 2.23
FR ALP 2438 0.99 - > N/A N/A 43 i estimate a 0.50 + > N Y FV = good good good FV U2 + U1 + genuine genuine 4300 a 2.74
HR ALP 6325 2.57 = N/A N/A 750 i estimate a 8.75 = Y FV = good good good FV FV = N/A N/A 9700 a 6.18
IT ALP 7600 3.08 + 45 63 N/A i estimate a 0.63 = > Y FV = good good good FV U1 + U1 + noChange genuine 6600 b 4.20
PL ALP 11500 4.66 = 99 166 122 i interval a 1.42 u N Unk U1 = good good poor U1 U1 = U1 - noChange knowledge 7000 a 4.46
RO ALP 66800 27.09 = 4650 5150 N/A i mean a 57.17 + 4590 i Y FV = good good good FV FV + FV noChange noChange 48100 a 30.64
SE ALP 70600 28.63 = 70600 619 666 643 i interval a 7.50 = 310 i Y FV = good good good FV FV = FV noChange noChange 29700 b 18.92
SI ALP 7209 2.92 = 409 491 N/A i interval a 5.25 + < Y FV = good good good FV FV + FV noChange genuine 7200 a 4.59
SK ALP 21213.28 8.60 + 900 1300 N/A i estimate b 12.83 + Y FV + good good good FV FV + FV N/A knowledge 17900 b 11.40
ES ATL 24500 100 + 243 292 N/A i estimate a 100 + 292 i Y U1 = good poor poor U1 U1 + U1 + noChange noChange 16000 a 100
EE BOR 47500 6.94 + 650 700 N/A i mean a 13.54 + Y FV = good good good FV FV + FV genuine genuine 46200 a 10.11
FI BOR 335500 49.05 = 1900 2200 2050 i estimate a 41.12 + Y FV = good good good FV FV + FV noChange method 253200 a 55.42
LV BOR 55700 8.14 = x 23 30 N/A i minimum c 0.53 + 30 i Unk XX = unk good unk XX U1 + U2 + genuine genuine 6000 b 1.31
SE BOR 245300 35.86 + 245300 2152 2314 2234 i interval a 44.81 = 1090 i Y FV = good good good FV FV + FV genuine noChange 151500 b 33.16
BG CON 33000 30.30 = 33000 27 40 N/A i estimate a 1.59 - 45 i Y FV = poor poor poor U1 U1 - U1 = noChange noChange 5900 a 12.29
CZ CON 3100 2.85 = N/ N/A 3 N/A i a 0.07 = N/ Y U1 = bad bad poor U2 U2 = U2 = noChange noChange 2000 a 4.17
RO CON 65600 60.23 = 1800 2050 N/A i estimate a 91.23 = 1370 i Y FV = good good good FV FV = FV noChange noChange 33600 a 70
SI CON 7220 6.63 = 136 164 N/A i interval a 7.11 + < Y FV = good good good FV FV + FV noChange genuine 6500 a 13.54
ES MED 13800 25.46 + > 55 N/A N/A i estimate a 8.53 + 55 i Y FV = good poor good U1 U1 + N/A N/A genuine genuine 6200 a 14.76
GR MED 36663 67.65 + 400 500 N/A i estimate b 69.77 + > Y U1 + good unk good FV U1 + U1 + noChange noChange 24100 b 57.38
HR MED 1730 3.19 + N/A N/A 83 i estimate a 12.87 = Unk XX x good good unk FV FV = N/A N/A 10600 a 25.24
IT MED 2000 3.69 = > 45 69 N/A i interval a 8.84 = >> Y FV = good good good FV U2 = U2 - genuine noChange 1100 b 2.62
HR CON 1200 0 + x N/A N/A 167 i estimate a 0 = N/A N N/A N/A N/A N/A N/A N/A N/A N/A 3900 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 ATL 24500 0MS + ≈ 24500 243 292 267 i 0MS + > 267 i 0MS = good poor poor 0MS MTX + U1 + nc nc U1 B1

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 CON 108920 1 = ≈ 120630 1963 2257 2110 i 2XP = ≈ 2110 i 2XP = good good good 2XP MTX = FV gen nong FV C

03/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 MED 54193 1 + > 54193 583 707 645 i 2XP + > 645 i 2XP + good unk good 2XP MTX + U1 + nc nc U1 B1

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 ALP 246585 1 = > 246585 7921 9240 8570 i 1 + > 8570 i 2XP = good good good 2XP MTX + FV nong nong FV B2

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 BOR 684000 1 + ≈ 684000 4725 5244 4985 i 1 + ≈ 4985 i 2XP = good good good 2XP MTX + FV nc nong FV A=

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
BG CON 2XP - 2XP x MTX FV FV 0/2

03/20

BALKANI Wildlife Society

Institution: BALKANI Wildlife Society

Member State: BG

BALKANI Wildlife Society
BG ALP 2XP - 2XP bad bad MTX FV FV 0/2

03/20

BALKANI Wildlife Society

Institution: BALKANI Wildlife Society

Member State: BG

BALKANI Wildlife Society
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.