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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, Molluscs, Helix pomatia, All bioregions. Annexes N, N, Y. Show all Molluscs
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 900 1200 1064 grids1x1 estimate N/A N/A N/A N/A
BG N/A N/A 63 grids1x1 minimum N/A N/A N/A N/A
DE 418 418 418 grids1x1 minimum 12 12 12 grids10x10 minimum
FR N/A N/A N/A minimum N/A N/A N/A minimum
HR N/A N/A 4 grids1x1 minimum N/A N/A N/A N/A
IT 300 1000 N/A grids1x1 minimum N/A N/A N/A N/A
PL 96 480 192 grids1x1 estimate N/A N/A N/A N/A
RO N/A N/A 9700 grids1x1 estimate N/A N/A N/A N/A
SI 8 9 N/A grids1x1 minimum N/A N/A N/A N/A
SK 719 719 N/A grids1x1 estimate 20000 100000 N/A i N/A
BE N/A N/A 600 grids1x1 estimate N/A N/A N/A N/A
DE 11135 11135 11135 grids1x1 estimate 126 136 131 grids10x10 estimate
DK N/A N/A N/A N/A N/A N/A N/A
FR N/A N/A N/A minimum N/A N/A N/A minimum
NL N/A N/A 353 grids1x1 estimate N/A N/A N/A N/A
UK N/A N/A 43 grids1x1 estimate N/A N/A 37 grids10x10 estimate
BG N/A N/A 12 grids1x1 minimum N/A N/A N/A N/A
RO N/A N/A 300 grids1x1 estimate N/A N/A N/A N/A
LT N/A N/A 64000 grids1x1 minimum N/A N/A N/A N/A
LV N/A N/A 64457 grids1x1 minimum N/A N/A N/A N/A
SE N/A N/A 842 grids1x1 estimate N/A N/A N/A N/A
AT 450 600 476 grids1x1 estimate N/A N/A N/A N/A
BE N/A N/A 835 grids1x1 estimate N/A N/A N/A N/A
BG N/A N/A 59 grids1x1 minimum N/A N/A N/A N/A
CZ N/A N/A 1289 grids1x1 mean N/A N/A N/A N/A
DE 102311 102311 102311 grids1x1 estimate 1264 1284 1274 grids10x10 estimate
DK N/A N/A N/A N/A N/A N/A N/A
FR N/A N/A N/A minimum N/A N/A N/A minimum
HR N/A N/A 3 grids1x1 minimum N/A N/A N/A N/A
IT 200 700 N/A grids1x1 estimate N/A N/A N/A N/A
LU 1766 1899 N/A grids1x1 estimate N/A N/A N/A N/A
PL 2787 13935 5574 grids1x1 estimate N/A N/A N/A N/A
RO N/A N/A 18100 grids1x1 estimate N/A N/A N/A N/A
SE N/A N/A 233 grids1x1 minimum N/A N/A N/A N/A
SI 40 41 N/A grids1x1 minimum N/A N/A N/A N/A
FR N/A N/A N/A minimum N/A N/A N/A minimum
CZ N/A N/A 94 grids1x1 mean N/A N/A N/A N/A
HU N/A N/A 82677 grids1x1 estimate N/A N/A N/A N/A
RO N/A N/A 1100 grids1x1 estimate N/A N/A N/A N/A
SK 319 319 N/A grids1x1 estimate 20000 100000 N/A i N/A
RO N/A N/A 1100 grids1x1 estimate N/A N/A N/A N/A
IT 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
AT ALP 43300 26.42 = 900 1200 1064 grids1x1 estimate b 8.30 = Y FV = good good good FV FV = FV noChange noChange 33500 a 34.08
BG ALP 12100 7.38 = 12100 N/A N/A 63 grids1x1 minimum c 0.49 u 63 grids1x1 Y FV = unk unk unk XX XX = FV method method 3400 c 3.46
DE ALP 641 0.39 = 418 418 418 grids1x1 minimum c 3.26 = grids10x10 Y FV = good good good FV FV = FV noChange noChange 500 b 0.51
FR ALP 26100 15.93 = N/A N/A N/A minimum d 0 x > Y Unk XX x good unk good FV XX = XX knowledge knowledge 8600 b 8.75
HR ALP 1300 0.79 x x N/A N/A 4 grids1x1 minimum c 0.03 x x Unk XX x unk unk unk XX XX N/A N/A 400 c 0.41
IT ALP 33900 20.68 = 300 1000 N/A grids1x1 minimum c 5.07 = > Y FV = good good good FV U1 = U1 - noChange noInfo 20600 b 20.96
PL ALP 14200 8.66 u 96 480 192 grids1x1 estimate b 1.50 = Y FV = good good good FV FV = FV noChange knowledge 9200 b 9.36
RO ALP 9700 5.92 = N/A N/A 9700 grids1x1 estimate b 75.67 = Y FV = good good good FV FV = N/A N/A knowledge knowledge 6000 a 6.10
SI ALP 7656 4.67 = 7656 8 9 N/A grids1x1 minimum c 0.07 x Y FV x good good good FV FV x FV noChange noChange 900 c 0.92
SK ALP 14992.50 9.15 = 719 719 N/A grids1x1 estimate b 5.61 = Y FV = good good good FV FV = FV N/A knowledge 15200 b 15.46
BE ATL 19900 11.99 = N/A N/A 600 grids1x1 estimate a 4.95 = Y FV = good good good FV FV = XX method method 12100 a 12.98
DE ATL 18799 11.33 = 11135 11135 11135 grids1x1 estimate b 91.79 = grids10x10 Y FV = good good good FV FV = FV noChange noChange 13600 b 14.59
DK ATL N/A 0 x x N/A N/A N/A d 0 x x Unk Unk XX x good unk unk XX XX x XX N/A N/A N/A d 0
FR ATL 112300 67.67 = N/A N/A N/A minimum d 0 x > Y Unk U1 x good unk poor U1 U1 = U1 x knowledge knowledge 58100 b 62.34
NL ATL 6800 4.10 = N/A N/A 353 grids1x1 estimate b 2.91 = Y FV = good good good FV FV = XX method noInfo 5700 a 6.12
UK ATL 8154.48 4.91 = 7294 N/A N/A 43 grids1x1 estimate b 0.35 = > Y FV = good poor good U1 U1 = U1 = noChange noChange 3700 b 3.97
BG BLS 1700 85 = 1700 N/A N/A 12 grids1x1 minimum c 3.85 u 12 grids1x1 Y FV = unk unk unk XX XX = FV method method 600 c 75
RO BLS 300 15 x > N/A N/A 300 grids1x1 estimate b 96.15 x Unk XX x unk unk unk XX XX FV knowledge knowledge 200 a 25
LT BOR 65200 24.98 = N/A N/A 64000 grids1x1 minimum c 49.50 = Y FV = good good good FV FV = FV noChange noChange 68400 c 65.71
LV BOR 64589 24.75 = 64589 N/A N/A 64457 grids1x1 minimum c 49.85 = 64457 grids1x1 Y FV = good good good FV FV = FV noChange noChange N/A b 0
SE BOR 131200 50.27 + 131200 N/A N/A 842 grids1x1 estimate c 0.65 + 750 grids1x1 Y FV + good good good FV FV + N/A N/A method method 35700 b 34.29
AT CON 25500 3.09 = 450 600 476 grids1x1 estimate b 0.36 = Y FV = good good good FV FV = FV noChange noChange 16700 a 3.04
BE CON 14200 1.72 = N/A N/A 835 grids1x1 estimate b 0.64 u Unk XX u good good good FV FV x FV noChange noChange 10500 a 1.91
BG CON 15500 1.88 = 15500 N/A N/A 59 grids1x1 minimum c 0.04 u 59 grids1x1 Y FV = unk unk unk XX XX = FV method method 4700 c 0.85
CZ CON 78700 9.55 = 78700 N/A N/A 1289 grids1x1 mean c 0.98 = Y FV = poor good good FV FV = FV noChange noChange 42500 b 7.73
DE CON 172966 20.98 = 102311 102311 102311 grids1x1 estimate c 77.98 = grids10x10 Y FV = good good good FV FV = FV noChange noChange 118500 b 21.55
DK CON N/A 0 x x N/A N/A N/A d 0 x x Unk Unk XX N good unk unk XX XX x XX N/A N/A N/A d 0
FR CON 120800 14.65 = N/A N/A N/A minimum d 0 x Y Unk U1 x good unk good FV U1 = XX knowledge noChange 39000 b 7.09
HR CON 400 0.05 x x N/A N/A 3 grids1x1 minimum c 0 x x Unk XX x unk unk unk XX XX N/A N/A 300 c 0.05
IT CON 26200 3.18 = 200 700 N/A grids1x1 estimate b 0.34 = > Y FV = good good good FV U1 = U1 - noChange noInfo 12600 b 2.29
LU CON 3800 0.46 = 1766 1899 N/A grids1x1 estimate b 1.40 = Y FV = good good good FV FV = FV noChange noChange 2700 b 0.49
PL CON 312700 37.93 = 2787 13935 5574 grids1x1 estimate b 4.25 = Y FV = good good good FV FV = FV noChange noChange 278500 b 50.64
RO CON 18400 2.23 u > N/A N/A 18100 grids1x1 estimate b 13.80 u Y U1 u good good good FV U1 x FV knowledge knowledge 12700 a 2.31
SE CON 22600 2.74 + 22600 N/A N/A 233 grids1x1 minimum b 0.18 + 200 grids1x1 Y FV + good good good FV FV + N/A N/A knowledge knowledge 9400 b 1.71
SI CON 12616 1.53 = 12616 40 41 N/A grids1x1 minimum c 0.03 x Y FV x good good good FV FV x FV noChange noChange 1900 c 0.35
FR MED 19700 100 = N/A N/A N/A minimum d 0 x > Y Unk XX x good unk good FV XX = XX knowledge knowledge 5600 b 100
CZ PAN 5900 5.66 = 5900 N/A N/A 94 grids1x1 mean c 0.11 = Y FV = good good good FV FV = FV noChange noChange 3100 b 3.19
HU PAN 93011 89.26 = N/A N/A 82677 grids1x1 estimate c 98.20 = Y FV = good good good FV FV = FV noChange noChange 88500 c 91.05
RO PAN 1100 1.06 u > N/A N/A 1100 grids1x1 estimate b 1.31 u Unk U1 u unk unk unk XX U1 x FV knowledge knowledge 900 a 0.93
SK PAN 4191.03 4.02 = 319 319 N/A grids1x1 estimate b 0.38 = Y U1 = good poor poor U1 U1 = FV knowledge knowledge 4700 b 4.84
RO STE 1100 100 x > N/A N/A 1100 grids1x1 estimate b 100 x Unk XX x unk unk unk XX XX FV knowledge knowledge 1100 a 100
IT MED 1900 0 x 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 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 163900 2GD = 12819 grids1x1 1 = 2GD = good good good 2GD MTX = FV nc nong FV A=

03/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 ATL 166000 2GD = 12131 grids1x1 1 x 2GD x good good poor 2GD MTX = XX nong nong XX D

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 BLS 2000 2GD = > 312 grids1x1 2GD x 2GD = unk unk unk 2GD MTX = FV nong nong FV D

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 BOR 261000 0EQ + 129299 grids1x1 0EQ 0EQ = good good good 0EQ MTX + FV nc nong FV A=

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 CON 824400 2GD 131203 grids1x1 2GD = 2GD = good good good 2GD MTX = FV nc nong FV A=

03/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 MED 19700 0MS 0MS x 0MS x good unk good 0MS MTX = XX x nc nong XX D

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 PAN 104200 2GD = 84190 grids1x1 2GD = 2GD = good good good 2GD MTX = FV nc nong U1 A+

03/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 STE 1100 0MS x 1100 grids1x1 0MS x 0MS unk unk unk 0MS MTX FV nong nc FV D

03/20

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.