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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, Fish, Thymallus thymallus, All bioregions. Annexes N, N, Y. Show all Fish
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 N/A N/A 392 grids1x1 estimate N/A N/A N/A N/A
DE 63 63 63 grids1x1 minimum 15 15 15 grids5x5 minimum
FI N/A N/A 1000 grids1x1 minimum N/A N/A N/A N/A
FR 700 5000 N/A grids1x1 mean N/A N/A N/A mean
HR N/A N/A 22 grids1x1 minimum N/A N/A N/A N/A
IT 1229 4480 N/A grids1x1 estimate N/A N/A N/A N/A
PL N/A N/A 2204 grids1x1 estimate N/A N/A N/A N/A
RO N/A N/A 617 grids1x1 minimum N/A N/A N/A N/A
SE N/A N/A 34456 grids1x1 estimate 476154 815444 645799 adults N/A
SI 144 149 N/A grids1x1 estimate N/A N/A N/A N/A
SK 200 300 N/A grids1x1 estimate 10000 50000 N/A i N/A
BE 1 40 1 grids1x1 minimum 200 8000 200 i minimum
DE 192 192 192 grids1x1 minimum 83 83 83 grids5x5 minimum
DK N/A N/A N/A estimate N/A N/A 23 localities N/A
UK N/A N/A 308 grids1x1 minimum N/A N/A N/A N/A
EE N/A N/A 578 grids1x1 estimate N/A N/A N/A N/A
FI N/A N/A 4000 grids1x1 minimum N/A N/A N/A N/A
LT N/A N/A 1820 grids1x1 minimum N/A N/A N/A N/A
LV N/A N/A 1440 grids1x1 estimate N/A N/A N/A N/A
SE N/A N/A 113555 grids1x1 estimate 6802200 11649200 9225700 adults mean
AT N/A N/A 392 grids1x1 estimate N/A N/A N/A N/A
BE 76 1400 76 grids1x1 minimum 15000 250000 15000 i minimum
CZ N/A N/A 116 grids1x1 estimate 77 77 N/A grids10x10 N/A
DE 2553 2553 2553 grids1x1 estimate 1006 1183 1006 grids5x5 estimate
DK N/A N/A N/A estimate N/A N/A N/A localities N/A
FR 2000 20000 N/A grids1x1 estimate N/A N/A N/A estimate
HR N/A N/A 4 grids1x1 minimum N/A N/A N/A N/A
IT 551 1543 N/A grids1x1 estimate N/A N/A N/A N/A
LU 300 400 N/A grids1x1 estimate N/A N/A N/A N/A
PL N/A N/A 7974 grids1x1 estimate N/A N/A N/A N/A
RO N/A N/A 225 grids1x1 minimum N/A N/A N/A N/A
SI 135 140 N/A grids1x1 estimate N/A N/A N/A N/A
FI N/A N/A 50 grids1x1 minimum N/A N/A N/A N/A
SE N/A N/A 14231 grids1x1 estimate 500000 1000000 750000 adults estimate
FR 200 3000 N/A grids1x1 estimate N/A N/A N/A estimate
CZ N/A N/A 2 grids1x1 estimate N/A N/A 3 grids10x10 estimate
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 22100 10.14 = N/A N/A 392 grids1x1 estimate a 0.87 - > Y U1 + good poor poor U1 U1 - U1 - noChange noChange 16400 a 14.98
DE ALP 2973 1.36 = 63 63 63 grids1x1 minimum b 0.14 - >> grids5x5 N Y U1 - good poor poor U1 U2 - U2 + noChange genuine 1600 b 1.46
FI ALP 20300 9.31 = N/A N/A 1000 grids1x1 minimum a 2.23 = Y FV = good good good FV FV = FV noChange method 9800 b 8.95
FR ALP 4000 1.84 - > 700 5000 N/A grids1x1 mean c 6.35 - > N N U2 - bad bad bad U2 U2 - U1 - noChange noChange 500 b 0.46
HR ALP 2000 0.92 x x N/A N/A 22 grids1x1 minimum c 0.05 x x Y FV u good unk good FV XX N/A N/A 1700 b 1.55
IT ALP 40700 18.67 = >> 1229 4480 N/A grids1x1 estimate b 6.36 - >> Y FV = good poor poor U1 U2 - U2 - knowledge knowledge 12200 b 11.14
PL ALP 10300 4.73 u N/A N/A 2204 grids1x1 estimate b 4.91 u > Y FV = good poor good U1 U1 x U1 - noChange knowledge 3200 b 2.92
RO ALP 15900 7.29 + x N/A N/A 617 grids1x1 minimum b 1.38 - x Y U2 - bad bad bad U2 U2 - U1 - genuine genuine 16300 b 14.89
SE ALP 69100 31.70 = 65600 N/A N/A 34456 grids1x1 estimate a 76.82 = 500000 adults Y FV = good good good FV FV = FV noChange N/A 18400 a 16.80
SI ALP 7066 3.24 = 144 149 N/A grids1x1 estimate b 0.33 - Y U1 - good poor poor U1 U1 - U1 = noChange genuine 3400 b 3.11
SK ALP 23540.49 10.80 - > 200 300 N/A grids1x1 estimate b 0.56 - > Y U1 - poor poor poor U1 U2 - U2 - N/A N/A 26000 b 23.74
BE ATL 900 1.30 u x 1 40 1 grids1x1 minimum b 0.20 - >> N N U2 = unk bad bad U2 U2 x N/A N/A noChange noChange 100 a 0.32
DE ATL 12718 18.40 - >> 192 192 192 grids1x1 minimum b 38.32 - 146 grids5x5 N N U2 - bad unk unk U2 U2 - U2 - noChange noChange 6500 b 20.57
DK ATL 5041 7.29 - > N/A N/A N/A estimate a 0 - >> Unk Unk XX x poor bad unk U2 U2 - U2 x N/A N/A 1600 a 5.06
UK ATL 50471.61 73.01 = N/A N/A 308 grids1x1 minimum b 61.48 = N N U1 = good good poor U1 U1 = XX knowledge noChange 23400 b 74.05
EE BOR 8700 1.61 = N/A N/A 578 grids1x1 estimate b 0.48 = > Y U1 + good poor good FV U1 + U1 + knowledge noChange 4600 b 2.89
FI BOR 241100 44.74 u N/A N/A 4000 grids1x1 minimum b 3.30 = Y XX u good unk unk XX XX U1 = method method 67600 b 42.44
LT BOR 64787 12.02 = N/A N/A 1820 grids1x1 minimum b 1.50 = 1820 grids1x1 Y FV = good good good FV FV = FV knowledge knowledge 15300 b 9.60
LV BOR 15700 2.91 = x N/A N/A 1440 grids1x1 estimate b 1.19 = 1500 grids1x1 Y FV = good poor good U1 U1 = U2 = knowledge noChange 11300 b 7.09
SE BOR 208600 38.71 = 208600 N/A N/A 113555 grids1x1 estimate a 93.54 = 5500000 adults Y FV = good good good FV FV = FV noChange N/A 60500 a 37.98
AT CON 13200 4.02 = > N/A N/A 392 grids1x1 estimate a 1.64 - >> Y U1 - good bad poor U2 U2 - U2 - noChange noChange 9700 a 6.94
BE CON 11900 3.62 = 76 1400 76 grids1x1 minimum b 0.32 - > Y FV = good good good FV U1 - FV knowledge knowledge 4800 a 3.43
CZ CON 11300 3.44 - > N/A N/A 116 grids1x1 estimate b 0.49 - >> N N U2 = poor bad poor U2 U2 - U1 - genuine noChange 7500 b 5.36
DE CON 161656 49.23 = 2553 2553 2553 grids1x1 estimate b 10.69 - > grids5x5 N N U1 - good unk poor U1 U1 - U1 - noChange noChange 71800 b 51.36
DK CON N/A 0 - >> N/A N/A N/A estimate a 0 - >> Unk Unk XX x bad bad unk U2 U2 - U2 x N/A N/A 100 a 0.07
FR CON 49300 15.01 = > 2000 20000 N/A grids1x1 estimate b 46.07 - > Unk Unk U1 = poor bad bad U2 U2 - U2 = noChange noChange 12200 b 8.73
HR CON 300 0.09 - x N/A N/A 4 grids1x1 minimum c 0.02 - x Y U1 u unk unk poor XX U1 - N/A N/A 100 b 0.07
IT CON 21000 6.39 = >> 551 1543 N/A grids1x1 estimate b 4.39 - >> Y FV = poor poor poor U1 U2 - U2 - noChange noChange 3900 b 2.79
LU CON 2400 0.73 = 300 400 N/A grids1x1 estimate b 1.47 - >> N N U1 - good bad poor U2 U2 - U2 = noChange genuine 2000 b 1.43
PL CON 45900 13.98 u N/A N/A 7974 grids1x1 estimate b 33.40 u > Y FV = good poor good U1 U1 x U1 - noChange knowledge 15900 b 11.37
RO CON 3300 1 - x N/A N/A 225 grids1x1 minimum b 0.94 - x Y U2 - bad bad bad U2 U2 - U1 - genuine genuine 8400 b 6.01
SI CON 8127 2.47 = 135 140 N/A grids1x1 estimate b 0.58 - Y U1 - good poor poor U1 U1 - U1 = noChange genuine 3400 b 2.43
FI MBAL 9900 33.11 = > N/A N/A 50 grids1x1 minimum c 0.35 - > N N U1 - bad bad bad U2 U2 - N/A N/A method method N/A b 0
SE MBAL 20000 66.89 = 28200 N/A N/A 14231 grids1x1 estimate c 99.65 - 750000 adults N Unk U1 = bad bad poor U2 U2 - U2 - noChange noChange 1000 a 100
FR MED 1100 100 u 200 3000 N/A grids1x1 estimate b 100 - > N Unk U1 - poor poor poor U1 U1 - U1 = genuine genuine 800 b 100
CZ PAN 400 100 = > N/A N/A 2 grids1x1 estimate b 100 = > N N U2 = bad bad bad U2 U2 = U2 = genuine noChange N/A 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 217980 2GD - >> 41027 48683 44855 grids1x1 2GD - >> 2GD - poor poor poor 2GD MTX - U2 - nc nc U1 C

12/19

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 ATL 69131 2GD - > 501 540 501 grids1x1 2GD - >> 2GD - bad bad bad 2GD MTX - U2 x nc nong U1 C

12/19

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 BOR 538887 2GD = 121393 121393 121393 grids1x1 2GD = 2GD good unk unk 2GD MTX = U1 = nc nc U1 D

12/19

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 CON 328383 2GD = > 14326 34747 23875 grids1x1 2GD - > grids1x1 2GD - bad bad bad 2GD MTX - U1 - gen nc U1 C

12/19

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 MBAL 29900 2XP = >> 14281 14281 14281 grids1x1 2XP - >> 2XP = bad bad poor 2XP MTX - nong nong U2 C

03/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 MED 1100 0MS x > 200 3000 1600 grids1x1 0MS - > 0MS - poor poor poor 0MS MTX - U1 = nc gen U1 C

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 PAN 400 0MS = > 2 2 2 grids1x1 0MS = >> 0MS = bad bad bad 0MS MTX = U2 = nc nc FV C

12/19

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.