Article 17 web tool

Log in

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, Myotis brandtii, All bioregions. Annexes N, Y-HTL, 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 45 N/A N/A grids1x1 minimum N/A N/A N/A N/A
BG N/A N/A 4 grids1x1 minimum N/A N/A N/A N/A
DE 186 186 186 grids1x1 estimate N/A N/A N/A localities N/A
FR 4300 4300 N/A grids1x1 mean N/A N/A N/A mean
HR N/A N/A 7 grids1x1 minimum N/A N/A N/A N/A
IT 45 450 N/A grids1x1 estimate N/A N/A N/A N/A
PL N/A N/A 2100 grids1x1 minimum 5000 15000 N/A i estimate
SI 3 4 N/A grids1x1 minimum N/A N/A N/A N/A
SK 113 113 N/A grids1x1 estimate 789 1461 N/A i N/A
BE N/A N/A 17 grids1x1 minimum N/A N/A N/A N/A
DE 7257 7257 7257 grids1x1 minimum 138 141 139.50 localities minimum
DK N/A N/A N/A N/A N/A N/A localities N/A
FR 6600 6600 N/A grids1x1 mean N/A N/A N/A mean
NL N/A N/A 17 grids1x1 estimate 50 500 250 i estimate
UK N/A N/A 2662 grids1x1 minimum N/A N/A N/A N/A
EE N/A N/A 53 grids1x1 minimum N/A N/A N/A N/A
FI 149 81600 N/A grids1x1 estimate N/A N/A N/A N/A
LT N/A N/A 103 grids1x1 minimum N/A N/A N/A N/A
LV N/A N/A 38046 grids1x1 estimate N/A N/A N/A N/A
SE N/A N/A 1385 grids1x1 estimate 550000 1650000 1100000 i estimate
AT 15 N/A N/A grids1x1 minimum N/A N/A N/A N/A
BE N/A N/A 21 grids1x1 minimum 460 2300 N/A iwintering estimate
BG N/A N/A 4 grids1x1 minimum N/A N/A N/A N/A
CZ 1389 1389 N/A grids1x1 estimate N/A N/A N/A N/A
DE 70954 70954 70954 grids1x1 estimate 738 765 751.50 localities estimate
DK N/A N/A N/A N/A N/A 5 localities N/A
FR 6600 6600 N/A grids1x1 mean N/A N/A N/A mean
HR N/A N/A 9 grids1x1 minimum N/A N/A N/A N/A
LU N/A N/A 1200 grids1x1 estimate N/A N/A N/A N/A
PL N/A N/A 6800 grids1x1 minimum 15000 45000 N/A i estimate
SE N/A N/A 190 grids1x1 estimate 28000 83000 55000 i estimate
SI 5 6 N/A grids1x1 minimum N/A N/A N/A N/A
GR N/A N/A 3152 grids1x1 estimate 69 87 N/A grids5x5 estimate
IT 20 200 N/A grids1x1 estimate N/A N/A N/A N/A
CZ 76 76 N/A grids1x1 estimate N/A N/A N/A N/A
HU N/A N/A 120 grids1x1 estimate N/A N/A N/A N/A
SK 11 11 N/A grids1x1 estimate N/A 50 N/A i N/A
IE N/A N/A N/A N/A N/A N/A N/A
FR 1500 1500 N/A grids1x1 mean N/A N/A N/A mean
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 4500 10.21 = > 45 N/A N/A grids1x1 minimum b 0.64 x > Y FV = good unk good FV U1 = U1 x noChange knowledge 3700 b 13.70
BG ALP 8100 18.38 = 8100 N/A N/A 4 grids1x1 minimum b 0.06 = 4 grids1x1 Y FV = unk unk unk XX FV = XX method method 6100 b 22.59
DE ALP 1929 4.38 = 186 186 186 grids1x1 estimate d 2.65 x x localities Y FV = good unk good FV FV = XX method noChange 500 c 1.85
FR ALP 5000 11.35 = 4300 4300 N/A grids1x1 mean d 61.38 x x N Y FV = unk unk good XX XX = U1 x knowledge noChange 3700 b 13.70
HR ALP 3700 8.40 x >> N/A N/A 7 grids1x1 minimum c 0.10 x >> N Unk XX x unk unk poor XX U2 x N/A N/A 3500 b 12.96
IT ALP 2000 4.54 = x 45 450 N/A grids1x1 estimate c 3.53 x x Y FV = good unk good FV XX XX noChange noChange 900 b 3.33
PL ALP 6300 14.30 = N/A N/A 2100 grids1x1 minimum b 29.97 + Y FV = good good good FV FV + FV noChange noChange 2100 b 7.78
SI ALP 5216 11.84 x x 3 4 N/A grids1x1 minimum c 0.05 x x Unk XX x unk unk unk XX XX XX noChange noChange 300 b 1.11
SK ALP 7322.64 16.62 + 113 113 N/A grids1x1 estimate c 1.61 + Y FV x good good good FV FV = XX knowledge knowledge 6200 b 22.96
BE ATL 5700 2.84 x x N/A N/A 17 grids1x1 minimum c 0.10 x x Unk XX x unk unk unk XX XX XX noChange noChange 1100 c 0.99
DE ATL 41033 20.44 = 7257 7257 7257 grids1x1 minimum c 43.84 = > localities N Y U1 = unk unk unk XX U1 = U1 = noChange noChange 11800 c 10.63
DK ATL 6 0 u x N/A N/A N/A d 0 u > Unk Unk XX u unk unk unk XX XX XX N/A N/A N/A b 0
FR ATL 8800 4.38 x x 6600 6600 N/A grids1x1 mean d 39.87 x x Unk Unk XX x unk unk unk XX XX x XX noChange noChange 7000 b 6.31
NL ATL 900 0.45 x x N/A N/A 17 grids1x1 estimate b 0.10 x >> Unk XX x unk unk unk XX U2 x U2 + noChange noInfo 900 b 0.81
UK ATL 144270 71.88 = 126401 N/A N/A 2662 grids1x1 minimum c 16.08 = x Y FV = good unk good FV FV = FV noChange noChange 90200 c 81.26
EE BOR 5900 1.19 = N/A N/A 53 grids1x1 minimum b 0.07 + x Unk XX x good good good FV FV + FV noChange genuine 2500 a 3.13
FI BOR 81600 16.51 = 149 81600 N/A grids1x1 estimate b 50.80 x x Y XX x good unk unk XX XX XX noChange noChange 9900 a 12.41
LT BOR 65200 13.19 x N/A N/A 103 grids1x1 minimum c 0.13 x > Unk XX x unk unk unk XX XX XX noChange noChange 7800 b 9.77
LV BOR 64589 13.06 = 64589 N/A N/A 38046 grids1x1 estimate c 47.28 + Y XX x good good unk FV FV = XX noChange noChange 400 c 0.50
SE BOR 277100 56.05 = 277100 N/A N/A 1385 grids1x1 estimate c 1.72 = 1100000 i Y FV = good good good FV FV = FV noChange noChange 59200 b 74.19
AT CON 1600 0.36 = > 15 N/A N/A grids1x1 minimum b 0.02 x > Y FV = good unk good FV U1 = U1 x noChange knowledge 1400 b 0.85
BE CON 6900 1.55 - x N/A N/A 21 grids1x1 minimum b 0.02 x x Unk XX x good unk unk XX XX XX noChange noChange 1100 c 0.66
BG CON 8000 1.80 = 8000 N/A N/A 4 grids1x1 minimum b 0 = 4 grids1x1 Y FV = unk unk unk XX FV = XX method method 4600 b 2.78
CZ CON 71900 16.20 = 1389 1389 N/A grids1x1 estimate a 1.59 = > Y FV = good poor good FV U1 = U1 = noChange noChange 25000 a 15.10
DE CON 274838 61.92 = 274838 70954 70954 70954 grids1x1 estimate b 81.38 x > localities Unk U1 - unk unk unk XX U1 x U1 x noChange noChange 90700 c 54.77
DK CON 390 0.09 u N/A N/A N/A d 0 u > Unk Unk XX u good unk unk XX XX XX N/A N/A 400 b 0.24
FR CON 25000 5.63 = 6600 6600 N/A grids1x1 mean d 7.57 x x Y Y FV = unk unk good XX XX = U1 = knowledge noChange 19700 b 11.90
HR CON 600 0.14 x >> N/A N/A 9 grids1x1 minimum b 0.01 x >> N Unk XX x unk unk poor XX U2 x N/A N/A 6000 b 3.62
LU CON 3600 0.81 x N/A N/A 1200 grids1x1 estimate c 1.38 x x Unk XX x good unk unk XX XX XX noChange noChange 2900 c 1.75
PL CON 16400 3.69 = N/A N/A 6800 grids1x1 minimum c 7.80 + Y FV = good good good FV FV + FV noChange noChange 6600 b 3.99
SE CON 23700 5.34 = 23700 N/A N/A 190 grids1x1 estimate c 0.22 = 55000 i Y FV = good good good FV FV = FV noChange noChange 6700 b 4.05
SI CON 10967 2.47 x x 5 6 N/A grids1x1 minimum c 0.01 x x Unk XX x unk unk unk XX XX XX noChange noChange 500 b 0.30
GR MED 5012 83.37 x > N/A N/A 3152 grids1x1 estimate b 96.63 x x Unk XX x poor unk unk XX U1 x U1 x noChange noChange 3200 b 96.97
IT MED 1000 16.63 = x 20 200 N/A grids1x1 estimate c 3.37 x x Y FV = good unk good FV XX XX noChange noChange 100 b 3.03
CZ PAN 5000 12.61 = 76 76 N/A grids1x1 estimate a 36.71 = > Y FV = good poor good FV U1 = U1 = noChange noChange 900 a 7.76
HU PAN 33782 85.21 u > N/A N/A 120 grids1x1 estimate c 57.97 u > Unk U1 x poor unk poor U1 U1 x U1 - noChange method 9700 c 83.62
SK PAN 865.11 2.18 + 11 11 N/A grids1x1 estimate c 5.31 + Y XX x good unk unk XX XX XX N/A N/A 1000 b 8.62
IE 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 XX N/A N/A N/A N/A N/A N/A 0
FR MED 1700 0 x x 1500 1500 N/A grids1x1 mean d 0 x x Unk Unk XX = unk unk unk XX XX x XX noChange noChange 900 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 ALP 44067.64 2GD + 6803 7209 7006 grids1x1 2GD + x 2GD x 2GD MTX = XX x nong nong XX D

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 ATL 200709 2XR = 2XR = 2XR = 2XR MTX = U2 = nong nc U2 B1

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 BOR 494389 0EQ = ≈ 494389 39736 121187 80461.5 grids1x1 2GD x 2GD x 2GD MTX = XX x nong nong XX A=

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 CON 443895 2GD = 2GD x 2GD - 2GD MTX x U1 x nc nc U1 D

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 MED 6012 2XP x 3172 3352 3262 grids1x1 0EQ x x 2XP x 2XP MTX x U1 x nc nc XX D

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 PAN 39647.1 1 x < 43025.3 207 207 207 grids1x1 1 x < 226.6 2XP x 2XP MTX x U1 - nc nong 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.