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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, Felis silvestris, 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
BG 380 1035 N/A i minimum N/A N/A N/A N/A
ES 125 3250 3250 i estimate N/A N/A N/A estimate
FR N/A N/A N/A mean 2600 9100 N/A area mean
HR 403 620 N/A i mean N/A N/A N/A N/A
IT 57 171 N/A i estimate N/A N/A N/A N/A
PL N/A N/A 100 i minimum N/A N/A N/A N/A
RO 2170 2420 N/A i estimate N/A N/A N/A N/A
SI N/A N/A 39 i minimum 39 43 N/A grids1x1 minimum
SK 1000 2000 N/A i estimate N/A N/A N/A N/A
DE 1000 5000 2000 i minimum 83 83 83 grids10x10 minimum
ES 256 7861 6656 i estimate N/A N/A N/A estimate
FR N/A N/A N/A mean 6400 25800 N/A area mean
PT N/A N/A N/A N/A N/A N/A N/A
UK 30 314 N/A i interval N/A N/A N/A N/A
BG 140 380 N/A i minimum N/A N/A N/A N/A
RO 35 40 N/A i estimate N/A N/A N/A N/A
BE 2700 5600 N/A i estimate 1457 N/A N/A grids1x1 estimate
BG 1090 2960 N/A i minimum N/A N/A N/A N/A
CZ N/A 5 N/A i estimate N/A N/A N/A N/A
DE 5000 10000 7000 i estimate 1488 1488 1488 grids10x10 estimate
FR N/A N/A N/A mean 54500 123200 N/A area mean
HR 1613 1863 N/A i mean N/A N/A N/A N/A
IT 80 240 N/A i estimate N/A N/A N/A N/A
LU 334 N/A N/A i minimum 1359 1699 N/A grids1x1 estimate
PL N/A N/A 50 i minimum N/A N/A N/A N/A
RO 4850 5390 N/A i estimate N/A N/A N/A N/A
SI N/A N/A 84 i minimum 84 88 N/A grids1x1 minimum
ES 1557 54544 40482 i estimate N/A N/A N/A estimate
FR N/A N/A N/A mean 100 1800 N/A area mean
GR N/A N/A N/A N/A N/A N/A N/A
HR N/A N/A 200 i minimum N/A N/A N/A minimum
IT 297 891 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
HU N/A N/A 582 i minimum N/A N/A N/A N/A
RO 450 600 N/A i estimate N/A N/A N/A N/A
SK 100 200 N/A i estimate N/A N/A N/A N/A
RO 500 700 N/A i estimate N/A N/A N/A N/A
BE 2 10 N/A i estimate 2 5 N/A grids1x1 estimate
NL N/A N/A N/A 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 25800 15.25 = 25800 380 1035 N/A i minimum b 8.31 - 1027 i Y FV = poor poor poor U1 U1 - U1 x noChange genuine 15400 b 14.75
ES ALP 17400 10.28 = 125 3250 3250 i estimate b 38.16 = 3250 i Y U1 = good good poor FV U1 = FV knowledge knowledge 8500 a 8.14
FR ALP 9700 5.73 = N/A N/A N/A mean b 0 = Y Unk FV = good good unk FV FV = FV noChange noChange 9500 b 9.10
HR ALP 10979 6.49 x 403 620 N/A i mean b 6.01 x x Y FV = good unk good FV FV x N/A N/A 7400 b 7.09
IT ALP 10500 6.21 + 57 171 N/A i estimate b 1.34 + Y FV = good good good FV FV + FV noChange genuine 5000 b 4.79
PL ALP 5300 3.13 u > N/A N/A 100 i minimum b 1.17 u > Unk XX x poor poor unk U1 U1 x U1 x noChange noChange 2900 b 2.78
RO ALP 64200 37.95 = 2170 2420 N/A i estimate a 26.95 = 2170 i Y FV = good good good FV FV = FV noChange noChange 42300 a 40.52
SI ALP 6767 4 = N/A N/A 39 i minimum c 0.46 = Y FV = good good good FV FV = U1 x method method 2900 c 2.78
SK ALP 18540.23 10.96 = > 1000 2000 N/A i estimate b 17.61 = > Y U1 = good poor poor U1 U1 = U1 = N/A N/A 10500 b 10.06
DE ATL 9410 9.81 + >> 1000 5000 2000 i minimum b 22.66 + >> grids10x10 N Y U1 + poor poor poor U1 U2 + U2 + noChange noChange 5800 b 9.76
ES ATL 43600 45.46 = 256 7861 6656 i estimate b 75.40 = 7861 i Y U1 = good poor poor FV U1 = FV knowledge knowledge 23800 a 40.07
FR ATL 27000 28.15 = N/A N/A N/A mean b 0 = Y FV = good good unk FV FV = FV noChange noChange 25200 b 42.42
PT ATL 2500 2.61 x x N/A N/A N/A d 0 - x N Unk U1 - unk unk poor XX U1 - U1 - noChange noChange 1400 d 2.36
UK ATL 13394 13.97 - 43211 30 314 N/A i interval a 1.95 u 3500 i Unk Unk XX u bad bad unk U2 U2 x U2 - noChange method 3200 b 5.39
BG BLS 9500 77.24 = 9500 140 380 N/A i minimum b 87.39 u 380 i Y FV = poor poor poor U1 U1 = U1 x noChange noInfo 5300 b 77.94
RO BLS 2800 22.76 = 35 40 N/A i estimate a 12.61 = 35 i Y FV = good good good FV FV = FV noChange noChange 1500 a 22.06
BE CON 14600 2.74 + 2700 5600 N/A i estimate b 20.08 + > Y U1 = good poor poor U1 U1 + U1 - noChange knowledge 10500 b 2.57
BG CON 73600 13.81 = 73600 1090 2960 N/A i minimum b 9.80 - 351 i Y FV = poor poor poor U1 U1 - U1 x noChange genuine 47300 b 11.57
CZ CON 1700 0.32 + >> N/A 5 N/A i estimate b 0.01 + >> Unk XX x bad bad unk U2 U2 = XX knowledge knowledge 1200 a 0.29
DE CON 112952 21.19 + > 5000 10000 7000 i estimate b 33.88 + > grids10x10 N Y U1 + poor poor poor U1 U1 + U1 + noChange noChange 73100 b 17.89
FR CON 126200 23.68 + N/A N/A N/A mean b 0 + Y FV = good good unk FV FV + FV noChange noChange 127900 b 31.29
HR CON 31076 5.83 = 1613 1863 N/A i mean b 8.41 u x Unk XX x good unk unk XX XX N/A N/A 35500 b 8.69
IT CON 17400 3.26 + 80 240 N/A i estimate b 0.77 + Y FV + good good good FV FV + FV noChange genuine 7300 b 1.79
LU CON 3900 0.73 = 3900 334 N/A N/A i minimum b 1.62 + 1892 grids1x1 Y U1 - poor poor poor U1 U1 = U1 = knowledge noChange 2500 b 0.61
PL CON 2900 0.54 u x N/A N/A 50 i minimum b 0.24 u x Unk XX x poor poor unk U1 U1 x U1 x noChange noChange 1300 b 0.32
RO CON 136000 25.52 = 4850 5390 N/A i estimate a 24.78 = 4850 i Y FV = good good good FV FV = FV noChange noChange 97200 a 23.78
SI CON 12616 2.37 = 12616 N/A N/A 84 i minimum c 0.41 = Y FV = good good good FV FV = U1 x method method 4900 c 1.20
ES MED 387600 67.84 + 1557 54544 40482 i estimate b 98.08 = 54544 i Y U1 = good poor poor FV U1 = FV knowledge knowledge 164600 a 52.32
FR MED 1800 0.32 + N/A N/A N/A mean b 0 x x Unk Y FV = good unk unk XX XX = N/A N/A method noChange 4000 b 1.27
GR MED 84604 14.81 x x N/A N/A N/A d 0 x Unk XX x unk good good FV XX XX noChange noChange 92500 a 29.40
HR MED 12951 2.27 = N/A N/A 200 i minimum c 0.48 x 250 i Unk XX x good unk unk XX XX N/A N/A 17700 b 5.63
IT MED 71100 12.44 + 297 891 N/A i estimate c 1.44 + Y FV = good good good FV FV + FV noChange genuine 29200 b 9.28
PT MED 13300 2.33 x > N/A N/A N/A d 0 - x N Unk U1 - unk unk poor XX U1 - U1 - noChange noChange 6600 d 2.10
HU PAN 16715 48.79 u N/A N/A 582 i minimum c 46.30 u >> Y U1 = poor bad poor U2 U2 x U2 - noChange method 18200 c 59.28
RO PAN 15600 45.54 = 450 600 N/A i estimate a 41.77 = 410 i Y FV = good good good FV FV = FV noChange noChange 10900 a 35.50
SK PAN 1942.91 5.67 = > 100 200 N/A i estimate b 11.93 = > Y U1 = good unk unk XX U1 = U1 = N/A N/A 1600 b 5.21
RO STE 30500 100 = 500 700 N/A i estimate a 100 = 470 i Y FV = good good good FV FV = FV noChange noChange 19700 a 100
BE ATL 1800 0 + >> 2 10 N/A i estimate b 0 + >> N Y U1 = poor poor poor U1 U2 + N/A N/A genuine genuine 200 b 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
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 169186 2GD = ≈ 169186 4274 9635 8517 i 1 = > 9263 i 2GD = good poor poor 2GD MTX = U1 = nc nc U1 D

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 ATL 95904 1 = > 125721 1286 13175 8828 i 2GD = >> 13361 i 2GD = unk poor unk 2GD MTX = U2 - nc nong U2 D

12/19

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 BLS 12300 1 = ≈ 12300 175 420 297 i 1 x ≈ 415 i 0EQ = poor poor poor 2XP MTX = U1 x nc nong U1 D

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 CON 532944 1 + > 532944 15801 26526 20663 i 2GD + > 20663 i 2GD = poor poor poor 2GD MTX + FV nong nong FV B2

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 MED 571355 1 + ≈ 572685 2054 55635 41276 i 2GD = > 55685 i 2GD x good unk unk 2GD MTX = XX = nc nc FV E

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 PAN 34257 1 x > 34257 1132 1382 1257 i 1 x >> 1257 i 2XP = unk unk unk 2XP MTX x U1 = nong nong U1 D

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 STE 30500 0MS = ≈ 30500 500 700 600 i 0MS = ≈ 470 i 0MS = good good good 0MS MTX = FV nc nong FV A=

02/20

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.