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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, Arthropods, Cerambyx cerdo, All bioregions. Annexes Y, Y, N. Show all Arthropods
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 N/A grids1x1 estimate N/A N/A N/A N/A
BG N/A N/A 5 grids1x1 minimum N/A N/A N/A N/A
ES 8 800 N/A grids1x1 estimate 10 N/A N/A localities minimum
FR 26 2600 N/A grids1x1 minimum N/A N/A N/A minimum
HR N/A N/A 6 grids1x1 minimum N/A N/A N/A N/A
IT N/A N/A 3888 grids1x1 estimate N/A N/A N/A N/A
PL N/A N/A N/A grids1x1 estimate N/A N/A N/A N/A
RO 10 200 N/A grids1x1 mean 1 14 N/A localities estimate
SK 884 884 N/A grids1x1 estimate 50000 400000 N/A i N/A
DE 2 6 N/A grids1x1 estimate 2 2 2 localities estimate
ES 25 2500 N/A grids1x1 estimate 65 N/A N/A localities estimate
FR 437 43700 N/A grids1x1 minimum N/A N/A N/A minimum
PT N/A N/A 3 grids1x1 minimum N/A N/A N/A N/A
BG N/A N/A 48 grids1x1 minimum N/A N/A N/A N/A
SE 4 5 4 grids1x1 mean 5 10 6 trees mean
AT 153 153 N/A grids1x1 interval N/A N/A N/A N/A
BG N/A N/A 95 grids1x1 minimum N/A N/A N/A N/A
CZ N/A N/A 117 grids1x1 estimate N/A N/A N/A N/A
DE 6919 6919 6919 grids1x1 estimate 207 212 209.50 localities estimate
FR 153 15300 N/A grids1x1 minimum N/A N/A N/A minimum
HR N/A N/A 40 grids1x1 minimum N/A N/A N/A N/A
IT N/A N/A 11345 grids1x1 estimate N/A N/A N/A N/A
PL N/A N/A 133 grids1x1 minimum N/A N/A N/A N/A
RO 44 440 N/A grids1x1 estimate 10 44 N/A localities estimate
SE N/A N/A N/A grids1x1 estimate N/A N/A N/A trees estimate
SI N/A N/A 31 grids1x1 minimum N/A N/A N/A N/A
ES 82 8200 N/A grids1x1 estimate 180 N/A N/A localities minimum
FR 212 21200 N/A grids1x1 minimum N/A N/A N/A minimum
GR N/A N/A 2245 grids1x1 estimate 23 55 N/A grids10x10 estimate
HR N/A N/A 47 grids1x1 minimum N/A N/A N/A N/A
IT N/A N/A 17247 grids1x1 estimate N/A N/A N/A N/A
PT N/A N/A 10 grids1x1 minimum N/A N/A N/A N/A
CZ N/A N/A 286 grids1x1 estimate N/A N/A N/A N/A
HU N/A N/A 1532 grids1x1 minimum N/A N/A N/A N/A
RO 4 40 N/A grids1x1 estimate 1 4 N/A localities estimate
SK 608 608 N/A grids1x1 estimate 50000 200000 N/A i N/A
RO 7 70 N/A grids1x1 estimate 1 7 N/A localities 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 N/A 0 = >> N/A N/A N/A grids1x1 estimate c 0 = >> Unk Unk U2 x bad bad bad U2 U2 = U2 = noChange noChange N/A a 0
BG ALP 21600 35.69 u 21600 N/A N/A 5 grids1x1 minimum c 0.08 = 5 grids1x1 Y FV = good good good FV FV = FV method method 1600 c 10.19
ES ALP 2700 4.46 = 8 800 N/A grids1x1 estimate b 6.12 = 10 localities Y FV = poor poor poor U1 U1 = U1 + noChange knowledge 500 a 3.18
FR ALP 7600 12.56 = 26 2600 N/A grids1x1 minimum c 19.88 x Y FV x good good unk FV FV x FV noChange noChange 1200 b 7.64
HR ALP 7 0.01 x x N/A N/A 6 grids1x1 minimum c 0.09 x x Unk XX x unk unk unk XX XX N/A N/A 100 d 0.64
IT ALP 19400 32.06 + N/A N/A 3888 grids1x1 estimate b 58.86 = N Y FV = good good good FV FV + U1 - noChange noChange 5000 b 31.85
PL ALP N/A 0 x x N/A N/A N/A grids1x1 estimate c 0 x x Unk XX x unk unk unk XX XX XX noChange noChange N/A b 0
RO ALP 1400 2.31 = > 10 200 N/A grids1x1 mean b 1.59 = 400 grids1x1 Y U1 = poor poor poor U1 U1 = U2 N/A knowledge noChange 800 b 5.10
SK ALP 7812.47 12.91 - > 884 884 N/A grids1x1 estimate c 13.38 = > Y U1 = good poor poor U1 U1 - U1 - N/A N/A 6500 b 41.40
DE ATL 316 0.21 - 718 2 6 N/A grids1x1 estimate b 0.02 - >> localities N N U2 - bad bad bad U2 U2 - U2 = noChange genuine 200 a 0.41
ES ATL 8500 5.57 + 25 2500 N/A grids1x1 estimate b 5.41 = 65 localities Y U1 = poor poor poor U1 U1 + U1 + noChange noChange 2800 a 5.75
FR ATL 143700 94.22 - > 437 43700 N/A grids1x1 minimum c 94.56 - > Y Unk U1 - poor poor unk U1 U1 - U1 = noChange noChange 45300 b 93.02
PT ATL N/A 0 = x N/A N/A 3 grids1x1 minimum c 0.01 u x Y XX = good unk unk XX XX XX noChange N/A 400 c 0.82
BG BLS 9100 100 = 9100 N/A N/A 48 grids1x1 minimum c 100 = 48 grids1x1 Y FV = good good good FV FV = FV method method 3500 c 100
SE BOR 100 100 = 4400 4 5 4 grids1x1 mean a 100 = 500 trees N Unk U2 = unk unk unk XX U2 = U2 - noChange noChange 100 a 100
AT CON 2900 1.04 - > 153 153 N/A grids1x1 interval a 0.57 + > Y U1 - poor bad bad U2 U2 - U2 - knowledge knowledge 2300 a 2.44
BG CON 84900 30.56 = 84900 N/A N/A 95 grids1x1 minimum c 0.35 = 95 grids1x1 Y FV = good good good FV FV = U1 - noChange method 13800 c 14.62
CZ CON 6400 2.30 + N/A N/A 117 grids1x1 estimate a 0.44 + Y U1 = good good poor FV U1 + U2 = knowledge knowledge 2700 a 2.86
DE CON 20343 7.32 x > 6919 6919 6919 grids1x1 estimate c 25.82 = > localities N N U2 - poor unk bad U2 U2 - U2 - noChange noChange 15100 a 16
FR CON 46100 16.59 = x 153 15300 N/A grids1x1 minimum c 28.83 - > Unk Unk U1 - unk poor poor U1 U1 - U1 = noChange noChange 13900 b 14.72
HR CON 7100 2.56 x > N/A N/A 40 grids1x1 minimum c 0.15 x x Unk XX x poor unk unk XX U1 x N/A N/A 2900 d 3.07
IT CON 74500 26.81 = N/A N/A 11345 grids1x1 estimate b 42.33 = Y FV = good good good FV FV = FV noChange noChange 24100 b 25.53
PL CON 28300 10.19 u x N/A N/A 133 grids1x1 minimum b 0.50 u x N Unk U1 u unk poor poor U1 U1 x U1 - noChange knowledge 13300 b 14.09
RO CON 4400 1.58 = > 44 440 N/A grids1x1 estimate b 0.90 = 500 grids1x1 Y U1 = poor poor poor U1 U1 = U1 N/A knowledge noChange 4300 b 4.56
SE CON N/A 0 N N/ N/A N/A N/A grids1x1 estimate b 0 N N/ XX N unk unk unk XX XX N/A N/A N/A N/A N/A a 0
SI CON 2907 1.05 - > N/A N/A 31 grids1x1 minimum c 0.12 x 36 grids1x1 N Unk U1 - poor unk poor U1 U1 - U1 - noChange noChange 2000 c 2.12
ES MED 22400 11.65 = 82 8200 N/A grids1x1 estimate b 12.04 = 180 localities Y U1 = poor poor poor U1 U1 = U1 - noChange knowledge 8700 a 12.46
FR MED 54000 28.08 = 212 21200 N/A grids1x1 minimum c 31.13 x x Y FV = good good unk FV FV = FV noChange noChange 21600 b 30.95
GR MED 5018 2.61 = N/A N/A 2245 grids1x1 estimate c 6.53 x 55 grids10x10 Unk XX x good poor unk U1 U1 x U1 x noChange noChange 2300 c 3.30
HR MED 8000 4.16 x x N/A N/A 47 grids1x1 minimum c 0.14 x x Unk XX x unk unk unk XX XX N/A N/A 3700 d 5.30
IT MED 92000 47.84 = N/A N/A 17247 grids1x1 estimate b 50.14 = Y FV = good good good FV FV = FV noChange noChange 28500 b 40.83
PT MED 10900 5.67 = x N/A N/A 10 grids1x1 minimum c 0.03 u x Y XX u good unk unk XX XX XX noChange N/A 5000 c 7.16
CZ PAN 4400 8.41 + N/A N/A 286 grids1x1 estimate a 11.68 + Y U1 + good good poor FV U1 + U2 - genuine genuine 1800 a 4.42
HU PAN 42232 80.69 = N/A N/A 1532 grids1x1 minimum b 62.58 = Y FV = good good good FV FV = U1 = knowledge noChange 32600 b 80.10
RO PAN 400 0.76 = > 4 40 N/A grids1x1 estimate b 0.90 = 45 grids1x1 Y U1 = poor poor poor U1 U1 = U1 N/A noChange noChange 500 b 1.23
SK PAN 5309.69 10.14 - > 608 608 N/A grids1x1 estimate c 24.84 = > Y U1 - poor poor poor U1 U2 - U1 - knowledge N/A 5800 b 14.25
RO STE 900 100 = > 7 70 N/A grids1x1 estimate b 100 = 300 grids1x1 Y U1 = good poor poor U1 U1 = U1 N/A noChange noChange 700 b 100
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 60519.47 1 + < 61440.72 4827 8383 6605 grids1x1 2GD = 2GD = 2GD MTX = U1 - nc nong U1 D

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 ATL 2GD - 2GD - 2GD - 2GD MTX - U1 = nc nong U1 C

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 BLS 9100 0MS = 9100 48 grids1x1 0MS = 48 grids1x1 0MS good good good 0MS MTX = FV = nong nc FV A=

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 BOR 100 0MS = 4400 4 5 4 grids1x1 0MS = 0MS = unk unk unk 0MS MTX = U2 - nc nong U2 D

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 CON 277850 1 = < 281615 19030 34573 26801.5 grids1x1 2XP - 2XP - 2XP MTX - U1 - nong nc U1 C

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 MED 192318 1 = ≈ 192318 19843 48949 34396 grids1x1 2XP x 2XP = 2XP MTX = U1 - nong nong XX A=

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 PAN 52341.69 1 = < 52912.66 2130 2466 2448 grids1x1 1 = < 2531.8 grids1x1 2XP - 2XP MTX - U1 = nc nong U1 C

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 STE 900 0MS = > 7 70 38.5 grids1x1 0MS = 300 grids1x1 0MS = good poor poor 0MS MTX = U1 x 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.