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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 LU

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, Myotis dasycneme, All bioregions. Annexes Y, 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
RO 200 400 N/A i minimum N/A N/A N/A N/A
SK 145 596 N/A i estimate N/A N/A N/A N/A
BE 190 420 N/A i estimate N/A N/A N/A N/A
DE N/A N/A N/A i minimum 159 160 159.50 grids5x5 minimum
DK N/A N/A N/A N/A N/A 13 localities N/A
FR 40 50 N/A i mean N/A N/A N/A mean
NL 4500 8000 N/A i estimate 4000 5500 4500 bfemales estimate
EE 1200 2800 N/A i estimate N/A N/A 721 grids1x1 estimate
LT N/A N/A 1355 i estimate N/A N/A N/A N/A
LV 5000 10000 N/A i estimate N/A N/A N/A N/A
SE 700 2100 1400 i estimate N/A N/A 54 grids1x1 estimate
BE 160 270 160 i minimum 160 270 160 iwintering minimum
DE N/A N/A N/A i estimate 234 239 236.50 grids5x5 estimate
DK N/A N/A N/A N/A N/A 35 localities N/A
FR N/A N/A N/A i estimate N/A N/A N/A estimate
HR N/A N/A 6 i minimum N/A N/A N/A N/A
PL 1000 5000 N/A i estimate N/A N/A 179 grids1x1 minimum
RO 300 500 N/A i minimum N/A N/A N/A N/A
SE 150 450 300 i estimate N/A N/A 13 grids1x1 estimate
HU N/A N/A N/A minimum N/A N/A 169 grids1x1 N/A
RO 100 200 N/A i minimum N/A N/A N/A N/A
SK 18 35 N/A i estimate N/A N/A N/A N/A
PL N/A N/A 9 i minimum N/A N/A 9 grids1x1 minimum
UK N/A N/A N/A N/A N/A N/A N/A
FI 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
CZ 1 10 N/A i estimate N/A N/A N/A N/A
LU 1 N/A N/A i minimum N/A N/A N/A N/A
CZ N/A 1 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
RO ALP 1800 26.72 = 200 400 N/A i minimum b 44.74 = Y U1 = poor poor poor U1 U1 = U1 = knowledge knowledge 500 b 12.82
SK ALP 4936.03 73.28 + 145 596 N/A i estimate c 55.26 + Y FV x good good good FV FV = XX knowledge knowledge 3400 b 87.18
BE ATL 19000 18.70 + 190 420 N/A i estimate c 4.62 u >> Unk XX x good poor unk U1 U2 x U2 - noChange method 4800 b 10.41
DE ATL 44234 43.53 = N/A N/A N/A i minimum b 0 - 159 grids5x5 N Unk U1 - good poor poor U1 U1 - U1 x noChange knowledge 13300 b 28.85
DK ATL 8680 8.54 = N/A N/A N/A d 0 u x Unk Y FV = good unk good FV FV x FV N/A N/A 1300 b 2.82
FR ATL 500 0.49 = >> 40 50 N/A i mean a 0.68 = >> Unk Unk XX = unk unk unk XX U2 = U2 - noChange noChange 500 a 1.08
NL ATL 29200 28.74 x 4500 8000 N/A i estimate b 94.70 - > Y U1 - poor poor poor U1 U1 - FV genuine method 26200 b 56.83
EE BOR 46500 22.65 + 1200 2800 N/A i estimate b 16.32 + Y FV = good good good FV FV + U1 x knowledge knowledge 16000 a 34.12
LT BOR 65200 31.76 = N/A N/A 1355 i estimate b 11.06 x > Y XX u good poor unk XX XX U1 = noChange noChange 16500 b 35.18
LV BOR 64589 31.46 = 64589 5000 10000 N/A i estimate b 61.20 + 5000 i Y FV = good good poor U1 U1 + U1 - noChange noChange 7900 b 16.84
SE BOR 29000 14.13 + 30000 700 2100 1400 i estimate c 11.42 + 1500 i Y FV = good poor unk U2 U2 + U2 x noChange genuine 6500 c 13.86
BE CON 8100 5.35 + 160 270 160 i minimum a 4.14 u >> Unk XX x good poor unk U1 U2 x U2 x noChange genuine 3300 b 7.38
DE CON 94262 62.22 = > N/A N/A N/A i estimate b 0 - > grids5x5 Unk U1 - poor unk unk XX U1 - U1 = noChange method 21200 b 47.43
DK CON 11545 7.62 = N/A N/A N/A d 0 u x Unk Y FV = good unk good FV FV x FV N/A N/A 3900 b 8.72
FR CON N/A 0 - >> N/A N/A N/A i estimate b 0 - >> Unk Unk XX x unk unk unk XX U2 - U2 x noChange noChange 100 a 0.22
HR CON 3600 2.38 x >> N/A N/A 6 i minimum c 0.16 x >> N Unk U1 x unk bad bad U2 U2 x N/A N/A 3300 b 7.38
PL CON 21800 14.39 x 1000 5000 N/A i estimate b 77.60 = x N Y U1 u unk unk unk XX U1 x U1 x noChange noChange 9500 b 21.25
RO CON 5600 3.70 = 300 500 N/A i minimum b 10.35 = Y U1 = poor poor poor U1 U1 = U1 = knowledge knowledge 1300 b 2.91
SE CON 6600 4.36 = 15000 150 450 300 i estimate c 7.76 = 1000 i Y FV = bad unk unk U2 U2 = U2 x noChange method 2100 c 4.70
HU PAN 52166 94.45 = N/A N/A N/A minimum c 0 u Y U1 - good poor poor U1 U1 x U1 = noChange method 11700 c 89.31
RO PAN 1800 3.26 = 100 200 N/A i minimum b 84.99 = Y U1 = poor poor poor U1 U1 = U1 = knowledge knowledge 600 b 4.58
SK PAN 1267.39 2.29 + 18 35 N/A i estimate c 15.01 + Y FV x good good good FV FV = XX knowledge knowledge 800 b 6.11
PL ALP 2100 0 x x N/A N/A 9 i minimum b 0 x x Unk XX x unk unk unk XX XX XX noChange noChange 600 b 0
UK 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 noChange noChange N/A d 0
FI BOR 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 300 a 0
BG CON 100 0 u x N/A N/A N/A i minimum b 0 u N/ i Unk XX x unk unk unk XX XX x XX noChange method 100 b 0
CZ CON 800 0 - >> 1 10 N/A i estimate c 0 - >> Y FV = bad bad good U2 U2 = U2 = noChange noChange 800 a 0
LU CON 100 0 x x 1 N/A N/A i minimum c 0 x x Unk XX x unk unk unk XX XX XX method noChange 100 c 0
CZ PAN 100 0 - >> N/A 1 N/A i estimate c 0 - N/ Y XX = bad bad good U2 U2 = U2 = noChange noChange N/A 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 2XP + x i 2XP + > 2XP x poor poor poor 2XP MTX x XX = nong nong XX D

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 ATL 2XR + x i 2XR - > 2XR - good poor poor 2XR MTX = U1 x nc nc U1 D

03/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 BOR 2XP + i 2XP + 2XP = good poor poor 2XP MTX = U1 = nc nc U1 D

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 CON 2XR = > 2XR = > 2XR x unk unk unk 2XR MTX = U1 = nc nc U1 D

12/19

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 PAN 2XR = 2XR = > 2XR - good poor poor 2XR MTX = U1 = nc nc U1 D

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.