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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, Amphibians, Epidalea calamita, All bioregions. Annexes N, Y-CTC, N. Show all Amphibians
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 3 grids1x1 estimate N/A N/A 233 adults mean
ES 46 4600 N/A grids1x1 estimate 1000000 5000000 2085700 i estimate
FR 52 5000 N/A grids1x1 estimate N/A N/A N/A estimate
BE 385 740 385 grids1x1 minimum 6800 14800 10000 adults estimate
DE 4599 4599 4599 grids1x1 estimate 342 344 343 grids5x5 estimate
DK N/A N/A N/A estimate N/A N/A 79 localities N/A
ES 301 30100 N/A grids1x1 estimate 10000000 50000000 13447800 i N/A
FR 699 6000 N/A grids1x1 estimate N/A N/A N/A estimate
IE N/A N/A 25 grids1x1 estimate N/A N/A 7542 adults mean
NL N/A N/A 2114 grids1x1 estimate 139158 1350000 N/A i estimate
PT N/A N/A N/A N/A N/A N/A N/A
UK N/A N/A 142 grids1x1 minimum N/A N/A N/A bfemales N/A
EE N/A N/A 23 grids1x1 minimum N/A N/A N/A N/A
LT 3000 3300 N/A grids1x1 minimum N/A N/A N/A N/A
LV N/A N/A 19 grids1x1 minimum N/A N/A N/A N/A
SE N/A N/A 311 grids1x1 estimate 300 400 350 i N/A
AT N/A N/A 3 grids1x1 estimate N/A N/A 109 cmales estimate
BE 90 250 90 grids1x1 minimum 1800 4500 2000 adults estimate
CZ N/A N/A 56 grids1x1 estimate N/A N/A N/A N/A
DE 13320 13320 13320 grids1x1 estimate 1084 1237 1160.50 grids5x5 estimate
DK N/A N/A N/A estimate N/A N/A 115 localities N/A
FR 592 10000 N/A grids1x1 estimate N/A N/A N/A estimate
LU N/A N/A 5 grids1x1 estimate N/A N/A N/A N/A
PL N/A N/A 352 grids1x1 minimum N/A N/A N/A N/A
SE N/A N/A 4645 grids1x1 estimate 990 3350 2550 i estimate
ES 3224 322400 N/A grids1x1 estimate 50000000 100000000 95721200 i estimate
FR 100000 1000000 N/A grids1x1 estimate N/A N/A N/A estimate
PT 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 200 1.15 = > N/A N/A 3 grids1x1 estimate a 0.06 = >> N N U2 - bad bad bad U2 U2 - U2 x genuine genuine 200 a 3.28
ES ALP 11200 64.37 = 46 4600 N/A grids1x1 estimate b 47.88 x 2085701 i Y U1 = poor poor poor U2 U2 = U1 + knowledge knowledge 2000 a 32.79
FR ALP 6000 34.48 = > 52 5000 N/A grids1x1 estimate d 52.06 x > Unk Unk XX - poor poor poor U1 U1 x U1 x noChange noChange 3900 b 63.93
BE ATL 13100 7.93 - > 385 740 385 grids1x1 minimum b 1.49 = >> N N U1 = poor bad poor U2 U2 - U2 - noChange noChange 4700 a 3.11
DE ATL 47499 28.76 - 65307 4599 4599 4599 grids1x1 estimate b 17.82 - 403 grids5x5 N N U1 - poor bad poor U2 U2 - U1 - genuine noChange 17800 b 11.76
DK ATL 3068 1.86 - >> N/A N/A N/A estimate b 0 + >> N N U2 = bad bad bad U2 U2 + U2 x N/A N/A 2400 b 1.59
ES ATL 58400 35.36 = 301 30100 N/A grids1x1 estimate b 58.88 - 13447811 i Y U1 = good bad poor U2 U2 = FV genuine genuine 29200 a 19.30
FR ATL 6207 3.76 - > 699 6000 N/A grids1x1 estimate c 12.98 - > Unk Unk U2 - poor poor poor U1 U2 - U2 x genuine genuine 67500 b 44.61
IE ATL 92 0.06 = 172 N/A N/A 25 grids1x1 estimate a 0.10 u 13000 adults N N U1 + bad bad poor U2 U2 = U2 + noChange knowledge 700 a 0.46
NL ATL 26900 16.29 = N/A N/A 2114 grids1x1 estimate b 8.19 = > Y U1 - good poor poor U1 U1 - U2 - knowledge noChange 22900 a 15.14
PT ATL 6800 4.12 = N/A N/A N/A d 0 x N/ Y FV = good unk unk XX XX XX noChange noChange 3200 c 2.12
UK ATL 3074.13 1.86 = N/A N/A 142 grids1x1 minimum a 0.55 = >> N Unk U1 = poor bad poor U2 U2 = U2 + noChange method 2900 a 1.92
EE BOR 2700 3.84 - > N/A N/A 23 grids1x1 minimum a 0.66 = > N N U1 + poor poor poor U1 U2 = U2 = genuine noChange 1500 a 2.09
LT BOR 64700 91.90 = 3000 3300 N/A grids1x1 minimum c 89.92 x x Y FV u good unk unk XX XX U1 = noChange noChange 68500 c 95.40
LV BOR 2300 3.27 - >> N/A N/A 19 grids1x1 minimum b 0.54 - 19 grids1x1 N Unk U1 x poor poor unk U1 U2 - U1 - genuine noChange 1500 a 2.09
SE BOR 700 0.99 = 700 N/A N/A 311 grids1x1 estimate b 8.88 u 500 i Y U1 u unk poor unk XX U1 x U1 = noChange knowledge 300 b 0.42
AT CON 100 0.02 = >> N/A N/A 3 grids1x1 estimate a 0.01 - >> N N U2 - bad bad bad U2 U2 - U2 - noChange noChange 100 a 0.06
BE CON 5900 1.35 - > 90 250 90 grids1x1 minimum b 0.38 = >> N N U2 = poor bad poor U2 U2 - U2 - noChange noChange 1800 a 0.99
CZ CON 4500 1.03 - > N/A N/A 56 grids1x1 estimate a 0.24 - >> Y U2 - poor bad bad U2 U2 - U2 - genuine genuine 2600 a 1.43
DE CON 194858 44.55 - 267143 13320 13320 13320 grids1x1 estimate b 56.04 - 1646 grids5x5 N N U2 - bad bad bad U2 U2 - U1 = genuine genuine 74800 b 41.19
DK CON 12731 2.91 = >> N/A N/A N/A estimate b 0 = >> N N U2 = bad bad bad U2 U2 = U2 x N/A N/A 5300 b 2.92
FR CON 72800 16.64 u > 592 10000 N/A grids1x1 estimate d 22.28 - > Unk Unk XX u unk unk poor U2 U2 x U2 = noChange noChange 55800 b 30.73
LU CON 400 0.09 = 1200 N/A N/A 5 grids1x1 estimate b 0.02 = 18 grids1x1 N N U2 = bad poor bad U2 U2 = U2 x noChange genuine 300 a 0.17
PL CON 133900 30.61 = N/A N/A 352 grids1x1 minimum b 1.48 = Y FV = good good good FV FV = FV noChange knowledge 35800 b 19.71
SE CON 12200 2.79 = 12200 N/A N/A 4645 grids1x1 estimate b 19.54 u 20000 i Y U1 u unk poor unk XX U2 x U2 = noChange knowledge 5100 b 2.81
ES MED 463100 89.26 = 3224 322400 N/A grids1x1 estimate b 22.84 = 95721203 i Y U1 = good poor poor U2 U2 = FV knowledge knowledge 341600 a 77.65
FR MED 46600 8.98 = 100000 1000000 N/A grids1x1 estimate b 77.16 = < Y Unk FV = good poor poor U1 U1 = U1 = noChange noChange 38400 b 8.73
PT MED 9100 1.75 = N/A N/A N/A N/A 0 x x Y FV = good unk unk XX XX XX noChange noChange 59900 c 13.62
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 17400 1 = > 17400 101 9603 4852 grids1x1 2XP x 2XP - 2XP MTX x U1 + nong nong U1 D

01/20

EEA-ETC/BD

Institution: -

Member State: SK

EEA-ETC/BD
EU28 ATL 165140.13 2GD - 2GD - 2GD - 2GD MTX - U2 - nc nc U2 C

03/20

EEA-ETC/BD

Institution: -

Member State: SK

EEA-ETC/BD
EU28 BOR 70400 2GD = 3353 3653 3503 grids1x1 2GD x 2GD 2GD MTX x U1 = nong nong U1 D

03/20

EEA-ETC/BD

Institution: -

Member State: SK

EEA-ETC/BD
EU28 CON 437389 2GD - 2GD - 2GD - 2GD MTX - U1 = gen gen U1 C

03/20

EEA-ETC/BD

Institution: -

Member State: SK

EEA-ETC/BD
EU28 MED 518800 0EQ = ≈ 518800 2GD = 2GD = good 2GD MTX = FV = nong nc FV D

02/20

EEA-ETC/BD

Institution: -

Member State: SK

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.