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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, Hyla arborea, All bioregions. Annexes N, Y, 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 177 177 N/A grids1x1 minimum N/A N/A N/A N/A
BG N/A N/A 61 grids1x1 minimum N/A N/A N/A N/A
DE 894 894 894 grids1x1 estimate 6 6 6 grids5x5 estimate
FR 4 10 N/A grids1x1 estimate N/A N/A N/A estimate
HR N/A N/A 22 grids1x1 minimum N/A N/A N/A N/A
IT 7 8 N/A grids1x1 estimate N/A N/A N/A N/A
PL N/A N/A 14 grids1x1 minimum N/A N/A N/A N/A
RO 2 50 5 grids1x1 minimum N/A N/A N/A N/A
SI 54 60 N/A grids1x1 minimum N/A N/A N/A N/A
SK 149 149 N/A grids1x1 estimate 10000 50000 N/A i N/A
BE N/A N/A 115 grids1x1 estimate N/A N/A 14000 i N/A
DE 14515 14515 14515 grids1x1 estimate 323 324 323.50 grids5x5 estimate
FR N/A N/A N/A minimum N/A N/A N/A minimum
NL N/A N/A 344 grids1x1 estimate 12000 15000 N/A i estimate
BG N/A N/A 28 grids1x1 minimum N/A N/A N/A N/A
RO 2 50 5 grids1x1 minimum N/A N/A N/A N/A
LT 20 30 N/A grids1x1 minimum 2000 3000 N/A i minimum
LV 68 N/A N/A grids1x1 minimum N/A N/A N/A N/A
AT 319 319 N/A grids1x1 minimum N/A N/A N/A N/A
BG N/A N/A 407 grids1x1 minimum N/A N/A N/A N/A
CZ N/A N/A 3431 grids1x1 estimate N/A N/A N/A N/A
DE 96246 96246 96246 grids1x1 estimate 2199 2252 2225.50 grids5x5 estimate
DK N/A N/A N/A estimate N/A N/A 89 localities N/A
FR 629 60000 N/A grids1x1 estimate N/A N/A N/A estimate
HR N/A N/A 165 grids1x1 minimum N/A N/A N/A N/A
IT 6 6 N/A grids1x1 estimate N/A N/A N/A N/A
LU N/A N/A 11 grids1x1 estimate N/A N/A N/A N/A
PL N/A N/A 928 grids1x1 minimum N/A N/A N/A N/A
RO 2 50 5 grids1x1 minimum N/A N/A N/A N/A
SE N/A N/A 2791 grids1x1 estimate 16000 25000 18000 i N/A
SI 339 345 N/A grids1x1 minimum N/A N/A N/A N/A
GR 5678 7508 N/A grids1x1 estimate N/A N/A N/A N/A
HR N/A N/A 101 grids1x1 minimum N/A N/A N/A N/A
CZ N/A N/A 340 grids1x1 estimate N/A N/A N/A N/A
HU N/A N/A 1580 grids1x1 estimate N/A N/A N/A N/A
RO 2 50 5 grids1x1 minimum N/A N/A N/A N/A
SK 283 283 N/A grids1x1 estimate 100000 1000000 N/A i N/A
RO 2 50 5 grids1x1 minimum 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 6900 8.91 - > 177 177 N/A grids1x1 minimum c 12.70 - >> Unk N U2 - unk poor bad U2 U2 - U1 - genuine genuine 5100 c 19.25
BG ALP 8300 10.72 = 8300 N/A N/A 61 grids1x1 minimum b 4.38 = 61 grids1x1 Y FV = good good good FV FV = U1 = method noChange 1300 b 4.91
DE ALP 2431 3.14 - >> 894 894 894 grids1x1 estimate b 64.16 - 13 grids5x5 N N U2 - bad bad bad U2 U2 - U1 - genuine noChange 1100 b 4.15
FR ALP 400 0.52 - > 4 10 N/A grids1x1 estimate c 0.50 - >> N Unk U1 u poor poor poor U1 U2 - U2 x genuine genuine 500 b 1.89
HR ALP 8400 10.85 x x N/A N/A 22 grids1x1 minimum c 1.58 x x Unk XX x unk unk unk XX XX N/A N/A 1400 c 5.28
IT ALP 300 0.39 = 7 8 N/A grids1x1 estimate b 0.54 - > Y FV = good poor good U1 U1 - N/A N/A noInfo noInfo 300 b 1.13
PL ALP 6300 8.13 = N/A N/A 14 grids1x1 minimum b 1 x Unk XX u unk poor unk XX XX XX knowledge noChange 1400 b 5.28
RO ALP 34000 43.90 = 2 50 5 grids1x1 minimum b 0.36 = 5 grids1x1 Y FV = good good good FV FV = U1 N/A noChange noChange 6500 b 24.53
SI ALP 4363 5.63 = 54 60 N/A grids1x1 minimum b 4.09 x > Unk XX x good unk unk XX U1 x U1 - noChange method 2700 b 10.19
SK ALP 6050.82 7.81 x 149 149 N/A grids1x1 estimate c 10.69 x Y U1 = unk poor poor U1 U1 x U1 = N/A N/A 6200 b 23.40
BE ATL 3000 1.47 + N/A N/A 115 grids1x1 estimate a 0.77 + > Y FV + good good good FV U1 + U2 + genuine noChange 1500 a 0.96
DE ATL 40823 19.99 - > 14515 14515 14515 grids1x1 estimate b 96.93 - 375 grids5x5 N Y U1 - poor unk unk XX U1 - U1 - noChange noChange 17200 b 10.96
FR ATL 155000 75.90 = N/A N/A N/A minimum c 0 - < Y U1 - bad bad bad U2 U2 - N/A N/A genuine genuine 134000 b 85.40
NL ATL 5400 2.64 + N/A N/A 344 grids1x1 estimate a 2.30 + N N U1 + good poor poor U1 U1 + FV method method 4200 a 2.68
BG BLS 2700 29.35 = 2700 N/A N/A 28 grids1x1 minimum b 84.85 = 28 grids1x1 Y FV = good good good FV FV = U1 - knowledge knowledge 700 b 18.92
RO BLS 6500 70.65 = 2 50 5 grids1x1 minimum b 15.15 = 5 grids1x1 Y FV = good good good FV FV = FV noChange noChange 3000 b 81.08
LT BOR 1000 15.63 + x 20 30 N/A grids1x1 minimum b 26.88 + > Y U1 = good poor poor U1 U1 + U1 = noChange noChange 900 b 23.68
LV BOR 5400 84.38 + 68 N/A N/A grids1x1 minimum a 73.12 + 68 grids1x1 Unk XX x good unk unk XX U1 = FV knowledge knowledge 2900 a 76.32
AT CON 12900 1.55 - > 319 319 N/A grids1x1 minimum c 0.24 - >> Unk N U2 - unk poor bad U2 U2 - U1 - genuine genuine 8700 c 2.15
BG CON 41100 4.93 = 41100 N/A N/A 407 grids1x1 minimum b 0.30 = 407 grids1x1 Y FV = good good good FV FV = U1 x knowledge knowledge 10800 b 2.67
CZ CON 77100 9.25 = N/A N/A 3431 grids1x1 estimate a 2.54 = Y FV = good good good FV FV = FV method method 50900 a 12.59
DE CON 207317 24.87 - > 96246 96246 96246 grids1x1 estimate b 71.31 - 2650 grids5x5 N Y U1 - poor poor poor U1 U1 - U1 - noChange noChange 113900 b 28.17
DK CON 4837 0.58 = > N/A N/A N/A estimate b 0 + > N Y FV = poor poor good U1 U1 + U1 x N/A N/A 3400 b 0.84
FR CON 72300 8.67 - > 629 60000 N/A grids1x1 estimate d 22.46 - < Unk Unk U1 - poor poor poor U1 U2 - U1 - knowledge noChange 57500 b 14.22
HR CON 30400 3.65 x x N/A N/A 165 grids1x1 minimum c 0.12 x x Unk XX x unk unk unk XX XX N/A N/A 9500 c 2.35
IT CON 300 0.04 = 6 6 N/A grids1x1 estimate b 0 - > Y FV = good poor good U1 U1 - N/A N/A noInfo noInfo 200 b 0.05
LU CON 500 0.06 + 1100 N/A N/A 11 grids1x1 estimate a 0.01 + 33 grids1x1 N N U2 + poor poor bad U2 U2 + U2 - noChange genuine 300 a 0.07
PL CON 273600 32.82 = N/A N/A 928 grids1x1 minimum b 0.69 - > Y U1 - good poor poor U1 U1 - FV knowledge knowledge 92700 b 22.92
RO CON 98700 11.84 = 2 50 5 grids1x1 minimum b 0 = 5 grids1x1 Y XX = good good unk FV FV = U1 N/A noChange noChange 45500 b 11.25
SE CON 2900 0.35 = 2900 N/A N/A 2791 grids1x1 estimate b 2.07 u 20000 i Y U1 - good good unk FV U1 x FV method method 2800 b 0.69
SI CON 11583 1.39 = 339 345 N/A grids1x1 minimum b 0.25 x > Unk U1 x good unk unk XX U1 x U1 - noChange method 8200 b 2.03
GR MED 25106.45 57.05 = 5678 7508 N/A grids1x1 estimate b 98.49 = Y FV = good good good FV FV = FV noChange noChange 14300 b 72.22
HR MED 18900 42.95 x x N/A N/A 101 grids1x1 minimum c 1.51 x x Unk XX x unk unk unk XX XX N/A N/A 5500 c 27.78
CZ PAN 6300 5.24 = N/A N/A 340 grids1x1 estimate a 15.40 = Y FV = good good good FV FV = FV method method 3200 a 3.56
HU PAN 93011 77.32 = N/A N/A 1580 grids1x1 estimate b 71.56 = Y FV = good good good FV FV = FV noChange noChange 74300 b 82.74
RO PAN 15200 12.64 = 2 50 5 grids1x1 minimum b 0.23 = 5 grids1x1 Y XX = good good unk FV FV = U1 N/A noChange noChange 6100 b 6.79
SK PAN 5784.70 4.81 = 283 283 N/A grids1x1 estimate b 12.82 = Y FV x good poor poor U1 U1 = U1 = N/A N/A 6200 b 6.90
RO STE 25700 100 = 2 50 5 grids1x1 minimum b 100 = 5 grids1x1 Y FV = good good good FV FV = U1 N/A noChange noChange 10300 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 77444.82 2GD = 1384 1445 1393.5 grids1x1 2GD - 2GD - 2GD MTX - gen gen C

03/20

EEA-ETC/BD

Institution: -

Member State: SK

EEA-ETC/BD
EU28 ATL 204223 2GD = 2GD - 2GD - 2GD MTX - nong nong C

03/20

EEA-ETC/BD

Institution: -

Member State: SK

EEA-ETC/BD
EU28 BLS 9200 0EQ = ≈ 9200 33 grids1x1 0EQ = 33 grids1x1 0EQ = good good good 0EQ MTX = U1 - nong nong U1 A=

01/20

EEA-ETC/BD

Institution: -

Member State: SK

EEA-ETC/BD
EU28 BOR 6400 2XP + 88 98 93 grids1x1 2XP + > grids1x1 2XP x good 2XP MTX = FV = nong nc FV D

03/20

EEA-ETC/BD

Institution: -

Member State: SK

EEA-ETC/BD
EU28 CON 833537 2GD - 2GD - 2GD - 2GD MTX - nc nong C

03/20

EEA-ETC/BD

Institution: -

Member State: SK

EEA-ETC/BD
EU28 MED 44006.45 2GD x 5779 7609 6694 grids1x1 2GD = 2GD x 2GD MTX = nong nong D

03/20

EEA-ETC/BD

Institution: -

Member State: SK

EEA-ETC/BD
EU28 PAN 120295.7 0EQ = ≈ 120295.7 2205 2253 2208 grids1x1 0EQ = grids1x1 2GD = good 2GD MTX = U1 = nong nc U1 A=

02/20

EEA-ETC/BD

Institution: -

Member State: SK

EEA-ETC/BD
EU28 STE 25700 0MS = ≈ 25700 2 50 5 grids1x1 0MS = 5 grids1x1 0MS = good good good 0MS MTX = U1 x nong nong U1 A=

01/20

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.