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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, Lucanus cervus, All bioregions. Annexes II. 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 91 grids1x1 estimate N/A N/A N/A N/A
BG N/A N/A 30 grids1x1 minimum N/A N/A N/A N/A
ES 65 6500 N/A grids1x1 estimate N/A N/A 59 localities estimate
FR N/A N/A N/A minimum N/A N/A N/A minimum
HR N/A N/A 98 grids1x1 minimum N/A N/A N/A N/A
IT N/A N/A 11644 grids1x1 estimate N/A N/A N/A N/A
RO N/A N/A 5900 grids1x1 estimate N/A N/A N/A N/A
SI 201 241 N/A grids1x1 estimate N/A N/A N/A N/A
SK 1019 1019 N/A grids1x1 estimate 100000 500000 N/A i N/A
BE N/A N/A 60 grids1x1 minimum N/A N/A N/A N/A
DE 5572 5572 5572 grids1x1 estimate 171 171 171 grids5x5 estimate
ES 351 35100 N/A grids1x1 estimate N/A N/A 1749 localities estimate
FR N/A N/A N/A minimum N/A N/A N/A minimum
NL N/A N/A 238 grids1x1 estimate 2380 30940 N/A i estimate
PT N/A N/A 155 grids1x1 minimum N/A N/A N/A N/A
UK N/A N/A 3503 grids1x1 minimum N/A N/A N/A N/A
BG N/A N/A 81 grids1x1 minimum N/A N/A N/A N/A
RO N/A N/A 700 grids1x1 estimate N/A N/A N/A N/A
SE 1200 1600 1400 grids1x1 estimate 3000 6000 4000 logs estimate
AT N/A N/A 158 grids1x1 minimum N/A N/A N/A N/A
BE 121 142 121 grids1x1 minimum N/A N/A N/A N/A
BG N/A N/A 387 grids1x1 minimum N/A N/A N/A N/A
CZ N/A N/A 664 grids1x1 estimate N/A N/A N/A N/A
DE 54800 54800 54800 grids1x1 estimate 1375 1385 1380 grids5x5 estimate
FR N/A N/A N/A minimum N/A N/A N/A minimum
HR N/A N/A 888 grids1x1 minimum N/A N/A N/A N/A
IT N/A N/A 20672 grids1x1 estimate N/A N/A N/A N/A
PL N/A N/A 850 grids1x1 estimate N/A N/A N/A N/A
RO N/A N/A 25700 grids1x1 estimate N/A N/A N/A N/A
SE 300 400 500 grids1x1 estimate 1000 2000 1300 logs estimate
SI 999 1039 N/A grids1x1 estimate N/A N/A N/A N/A
ES 406 40600 N/A grids1x1 estimate N/A N/A 842 localities estimate
FR N/A N/A N/A minimum N/A N/A N/A minimum
GR N/A N/A 3584 grids1x1 estimate 37 82 N/A grids10x10 estimate
HR N/A N/A 299 grids1x1 minimum N/A N/A N/A N/A
IT N/A N/A 14574 grids1x1 estimate N/A N/A N/A N/A
PT N/A N/A 304 grids1x1 minimum N/A N/A N/A N/A
CZ 277 277 N/A grids1x1 estimate N/A N/A N/A N/A
HU N/A N/A 4240 grids1x1 minimum N/A N/A N/A N/A
RO N/A N/A 2200 grids1x1 estimate N/A N/A N/A N/A
SK 717 717 N/A grids1x1 estimate 100000 300000 N/A i N/A
RO N/A N/A 4800 grids1x1 estimate 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 4900 3.13 x > N/A N/A 91 grids1x1 estimate a 0.41 x > N Unk U2 - poor bad bad U2 U2 x U2 - noChange noChange 3500 a 5.61
BG ALP 23500 15.01 = 23500 N/A N/A 30 grids1x1 minimum b 0.13 x 30 grids1x1 Y FV = good unk good FV FV = FV method method 3400 b 5.45
ES ALP 15400 9.83 = 65 6500 N/A grids1x1 estimate b 14.73 = 6500 grids1x1 Y U1 = good poor poor U1 U1 = U1 x knowledge N/A 4800 a 7.69
FR ALP 34500 22.03 = N/A N/A N/A minimum d 0 = Y Unk FV = good good unk FV FV = FV noChange noChange 14200 b 22.76
HR ALP 11000 7.02 u N/A N/A 98 grids1x1 minimum c 0.44 u x Unk XX x unk unk unk XX XX N/A N/A 4200 d 6.73
IT ALP 40200 25.67 + N/A N/A 11644 grids1x1 estimate b 52.25 + Y FV = good good good FV FV + FV noChange knowledge 14700 b 23.56
RO ALP 5900 3.77 = > N/A N/A 5900 grids1x1 estimate b 26.47 = Y FV = good good good FV FV = U2 N/A knowledge knowledge 3000 a 4.81
SI ALP 7352 4.70 = 201 241 N/A grids1x1 estimate b 0.99 = 240 grids1x1 Y FV = good good good FV FV = U1 = knowledge noChange 5500 b 8.81
SK ALP 13832.13 8.83 = 1019 1019 N/A grids1x1 estimate b 4.57 = Y U1 = good poor poor U1 U1 = FV knowledge knowledge 9100 b 14.58
BE ATL 3300 0.79 - >> N/A N/A 60 grids1x1 minimum b 0.22 - >> N Y U1 u bad poor poor U2 U2 - U2 - knowledge knowledge 1100 a 0.41
DE ATL 27690 6.64 = 27690 5572 5572 5572 grids1x1 estimate c 20.45 = 171 grids5x5 N Y U1 = good poor poor U1 U1 = U1 - noChange knowledge 11900 a 4.42
ES ATL 65500 15.71 = 351 35100 N/A grids1x1 estimate b 65.04 = 35100 grids1x1 Y U1 = good poor poor U1 U1 = U1 x N/A N/A 34800 a 12.92
FR ATL 267000 64.06 = N/A N/A N/A minimum d 0 = Y Unk FV = good good unk FV FV = FV noChange noChange 187800 b 69.71
NL ATL 2100 0.50 = >> N/A N/A 238 grids1x1 estimate b 0.87 = x Unk XX = bad unk unk U2 U2 = U2 = noChange noChange 1800 b 0.67
PT ATL 5900 1.42 = x N/A N/A 155 grids1x1 minimum b 0.57 u x Y XX - good unk poor XX XX XX noChange noChange 3500 b 1.30
UK ATL 45330.79 10.88 = N/A N/A 3503 grids1x1 minimum a 12.85 = Y FV = good good good FV FV = FV noChange noChange 28500 a 10.58
BG BLS 10000 93.46 = 10000 N/A N/A 81 grids1x1 minimum c 10.37 = 81 grids1x1 Y FV = good good good FV FV = FV method method 4900 b 94.23
RO BLS 700 6.54 u > N/A N/A 700 grids1x1 estimate b 89.63 u Y FV u unk unk unk XX FV x N/A N/A knowledge knowledge 300 a 5.77
SE BOR 32400 100 = 26300 1200 1600 1400 grids1x1 estimate b 100 = 4000 logs Y FV = good good good FV FV = U1 = knowledge noChange 19000 b 100
AT CON 8800 1.40 x > N/A N/A 158 grids1x1 minimum b 0.15 x > Y U1 - poor poor poor U1 U1 x U1 x noChange noChange 6200 a 1.82
BE CON 4500 0.72 - > 121 142 121 grids1x1 minimum b 0.11 - > Unk XX x poor poor poor U1 U1 - U1 - noChange noChange 1800 a 0.53
BG CON 89700 14.31 = 89700 N/A N/A 387 grids1x1 minimum b 0.37 = 387 grids1x1 Y FV = good good good FV FV = FV method method 30900 b 9.09
CZ CON 30600 4.88 = N/A N/A 664 grids1x1 estimate a 0.63 = Y FV = good good good FV FV = U1 + noChange noChange 16000 a 4.71
DE CON 135174 21.57 = 135174 54800 54800 54800 grids1x1 estimate b 51.82 = grids5x5 Y FV = good unk good FV FV = FV noChange noChange 76900 a 22.63
FR CON 181800 29.01 = N/A N/A N/A minimum d 0 = Y Unk FV = good good unk FV FV = FV noChange noChange 104400 b 30.72
HR CON 33400 5.33 u N/A N/A 888 grids1x1 minimum c 0.84 u x Unk XX x unk unk unk XX XX N/A N/A 22700 d 6.68
IT CON 81600 13.02 = N/A N/A 20672 grids1x1 estimate b 19.55 + Y FV = good good good FV FV + FV noChange knowledge 37300 b 10.98
PL CON 16000 2.55 x x N/A N/A 850 grids1x1 estimate b 0.80 x x N Unk U1 u unk poor poor U1 U1 x U1 x noChange noChange 8500 b 2.50
RO CON 25700 4.10 = > N/A N/A 25700 grids1x1 estimate b 24.30 = Y FV = good good good FV FV = FV knowledge knowledge 19900 a 5.86
SE CON 6800 1.09 = 5700 300 400 500 grids1x1 estimate b 0.47 = 1300 logs Y FV = good good good FV FV = U1 = knowledge noChange 2700 b 0.79
SI CON 12593 2.01 = 999 1039 N/A grids1x1 estimate b 0.96 = 1030 grids1x1 Y FV = good good good FV FV = U1 = knowledge noChange 12500 b 3.68
ES MED 111900 42.15 + 406 40600 N/A grids1x1 estimate b 52.22 + 40600 grids1x1 Y U1 = good poor poor U1 U1 = U1 x knowledge knowledge 40100 a 31.65
FR MED 65700 24.75 = N/A N/A N/A minimum d 0 = Y Unk FV = good good unk FV FV = FV noChange noChange 41100 b 32.44
GR MED 7369 2.78 = N/A N/A 3584 grids1x1 estimate c 9.13 x 82 grids10x10 Unk XX x good poor unk U1 U1 x U1 x noChange noChange 3700 c 2.92
HR MED 21300 8.02 u x N/A N/A 299 grids1x1 minimum c 0.76 u x Unk XX x unk unk unk XX XX N/A N/A 10400 d 8.21
IT MED 40000 15.07 = N/A N/A 14574 grids1x1 estimate b 37.12 + Y FV = good good good FV FV + FV noChange knowledge 19900 b 15.71
PT MED 19200 7.23 = x N/A N/A 304 grids1x1 minimum b 0.77 u x Y XX - good unk poor XX XX XX noChange noChange 11500 b 9.08
CZ PAN 5600 6.32 = 277 277 N/A grids1x1 estimate a 3.73 = 277 grids1x1 Y FV = good good good FV FV = U1 + noChange noChange 3300 a 4.17
HU PAN 72331 81.57 = N/A N/A 4240 grids1x1 minimum b 57.04 = Y FV = good good good FV FV = FV noChange noChange 68000 b 85.86
RO PAN 2200 2.48 = > N/A N/A 2200 grids1x1 estimate b 29.59 = Unk FV = good good unk FV FV = U1 N/A knowledge knowledge 1500 a 1.89
SK PAN 8546.03 9.64 = 717 717 N/A grids1x1 estimate b 9.64 = Y U1 = good poor poor U1 U1 = FV knowledge knowledge 6400 b 8.08
RO STE 4800 100 = > N/A N/A 4800 grids1x1 estimate b 100 = Y FV = good good good FV FV = U1 N/A knowledge knowledge 3400 a 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 156584.13 1 + < 157764.13 2GD + 2GD = 2GD MTX + U1 = nc nong U1 B2

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 ATL 416820.79 1 = 2GD = > 2GD = good good good 2GD MTX = U1 = nong nc U1 A=

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 BLS 10700 0EQ < 10770 781 grids1x1 0EQ ≈ 781 2XP unk unk unk 2XP MTX = FV = nc nc FV A=

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 BOR 32400 0MS = ≈ 26300 1200 1600 1400 grids1x1 0MS = ≈ 400 males 0MS = good good good 0MS MTX = U1 = nong nc U1 A=

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 CON 626667 1 = < 629467 2GD = 2GD = 2GD MTX + U1 = nong nong U1 A=

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 MED 265469 1 + 2GD + x 2GD = good unk unk 2GD MTX + U1 x nc nong XX B2

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 PAN 88677.03 0EQ = < 88897.03 7434 7434 7434 grids1x1 1 = ≈ 7434 grids1x1 2XP = good good unk 2XP MTX = FV = nc nc FV A=

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 STE 4800 0MS = > 4800 4800 grids1x1 0MS = ≈ 4800 grids1x1 0MS = good good good 0MS MTX = U1 x nong nong U1 A=

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
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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.