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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.

Warning: The map does not show the distribution for sensitive species in DE

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

Sensitive spatial information for this species is not shown in the map.

Current selection: 2013-2018, Arthropods, Eriogaster catax, 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 N/A N/A N/A N/A
BG N/A N/A 4 grids1x1 minimum N/A N/A N/A N/A
ES 10 N/A N/A grids1x1 minimum 10 N/A N/A localities minimum
HR N/A N/A 1 grids1x1 minimum N/A N/A N/A N/A
IT 70 140 N/A grids1x1 estimate N/A N/A N/A N/A
SI N/A N/A 5 grids1x1 minimum N/A N/A N/A N/A
SK 43 43 N/A grids1x1 estimate 10000 50000 N/A i N/A
ES 5 N/A N/A grids1x1 minimum 5 N/A N/A localities minimum
FR N/A N/A N/A minimum N/A N/A N/A minimum
AT 50 N/A N/A grids1x1 minimum N/A N/A N/A minimum
BE 4 9 4 grids1x1 minimum 40 400 200 adults estimate
BG N/A N/A 16 grids1x1 minimum N/A N/A N/A N/A
CZ N/A N/A 28 grids1x1 estimate N/A N/A N/A N/A
DE 15 16 15.50 grids1x1 estimate 15 16 15.50 localities estimate
FR N/A N/A N/A minimum N/A N/A N/A minimum
HR N/A N/A 15 grids1x1 minimum N/A N/A N/A N/A
IT 630 1260 N/A grids1x1 estimate N/A N/A N/A N/A
PL N/A N/A 210 grids1x1 estimate N/A N/A 210 localities estimate
RO N/A N/A 4000 grids1x1 estimate N/A N/A N/A N/A
SI N/A N/A 117 grids1x1 minimum N/A N/A N/A N/A
ES 27 N/A N/A grids1x1 minimum 27 N/A N/A localities minimum
FR 49 4900 N/A grids1x1 minimum N/A N/A N/A minimum
GR N/A N/A 253 grids1x1 estimate N/A N/A 3 grids10x10 estimate
HR N/A N/A 5 grids1x1 minimum N/A N/A N/A N/A
IT 600 1200 N/A grids1x1 estimate N/A N/A N/A N/A
CZ N/A N/A 13 grids1x1 estimate N/A N/A N/A N/A
HU N/A N/A 538 grids1x1 minimum 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 22 22 N/A grids1x1 estimate 10000 20000 N/A i N/A
RO N/A N/A 200 grids1x1 estimate N/A N/A N/A N/A
FR N/A N/A N/A minimum N/A N/A N/A minimum
PL N/A N/A 2 grids1x1 estimate N/A N/A 2 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 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 N/A a 0
BG ALP 1800 13.16 u 1800 N/A N/A 4 grids1x1 minimum c 2.38 u 4 grids1x1 N Unk XX x unk unk unk XX XX x FV method method 300 c 7.14
ES ALP 5400 39.49 - 10800 10 N/A N/A grids1x1 minimum c 5.95 x 500 grids1x1 N Y U1 - poor poor poor U1 U2 - U1 x knowledge knowledge 1200 a 28.57
HR ALP 200 1.46 x x N/A N/A 1 grids1x1 minimum c 0.60 x x Unk XX x unk unk unk XX XX N/A N/A 100 d 2.38
IT ALP 3500 25.59 + 70 140 N/A grids1x1 estimate b 62.50 x x N Y FV = good unk good FV FV = U2 x noChange noChange 600 c 14.29
SI ALP 630 4.61 x x N/A N/A 5 grids1x1 minimum c 2.98 x x N Y U1 u unk unk poor XX U1 x XX knowledge knowledge 200 b 4.76
SK ALP 2145.19 15.69 = 43 43 N/A grids1x1 estimate b 25.60 = Y U1 = good poor poor U1 U1 = FV knowledge knowledge 1800 b 42.86
ES ATL 1000 10.20 - 2000 5 N/A N/A grids1x1 minimum c 100 - 250 grids1x1 N Y U1 - poor poor poor U1 U2 - U1 x knowledge knowledge 500 a 5.21
FR ATL 8800 89.80 = N/A N/A N/A minimum d 0 x x Y FV = poor unk poor U1 U1 = U1 x noChange noChange 9100 b 94.79
AT CON 3100 5.88 - > 50 N/A N/A grids1x1 minimum a 0.93 - > Y U1 x poor poor poor U1 U1 - U1 - noChange noChange 1700 a 5.67
BE CON 100 0.19 + >> 4 9 4 grids1x1 minimum b 0.07 x >> N Y U1 - bad bad bad U2 U2 x U2 - noChange knowledge 100 a 0.33
BG CON 5400 10.24 u 5400 N/A N/A 16 grids1x1 minimum c 0.30 = 16 grids1x1 Unk XX x good good unk FV XX x FV method method 2000 c 6.67
CZ CON 2000 3.79 - > N/A N/A 28 grids1x1 estimate a 0.52 - > N N U2 - poor bad poor U2 U2 - U2 - noChange noChange 1100 a 3.67
DE CON 983 1.86 = 2110 15 16 15.50 grids1x1 estimate b 0.29 = 32 localities N N U2 x bad unk unk U2 U2 = U2 = noChange noChange 1000 a 3.33
FR CON 4900 9.30 u x N/A N/A N/A minimum d 0 = x Y Unk FV = unk unk unk XX XX = U1 x noChange noChange 4700 b 15.67
HR CON 2200 4.17 x x N/A N/A 15 grids1x1 minimum c 0.28 x x Unk XX x unk unk unk XX XX N/A N/A 1300 d 4.33
IT CON 19400 36.80 + 630 1260 N/A grids1x1 estimate b 17.50 x x Y FV = good unk good FV FV = U1 x method method 6700 c 22.33
PL CON 5300 10.05 x x N/A N/A 210 grids1x1 estimate b 3.89 x x Y FV x unk poor poor U1 U1 x U1 x noChange noChange 4200 c 14
RO CON 4000 7.59 = > N/A N/A 4000 grids1x1 estimate a 74.07 = Y FV = good good good FV FV = U1 N/A knowledge knowledge 3200 a 10.67
SI CON 5328 10.11 x x N/A N/A 117 grids1x1 minimum b 2.17 x x N Y U1 - unk unk poor XX U1 x U1 x noChange noChange 4000 b 13.33
ES MED 8700 17.96 - 17400 27 N/A N/A grids1x1 minimum c 0.74 - 1350 grids1x1 N Y U1 - poor poor poor U1 U2 - U1 x knowledge knowledge 3300 a 23.74
FR MED 14100 29.11 u x 49 4900 N/A grids1x1 minimum d 67.62 x x Y Unk FV = unk unk unk XX XX x XX noChange noChange 4400 b 31.65
GR MED 240 0.50 = N/A N/A 253 grids1x1 estimate c 6.91 x Unk XX x good poor unk U1 U1 x U1 x noChange noChange 300 c 2.16
HR MED 900 1.86 x x N/A N/A 5 grids1x1 minimum c 0.14 x x Unk XX x unk unk unk XX XX N/A N/A 500 d 3.60
IT MED 24500 50.58 = 600 1200 N/A grids1x1 estimate b 24.59 x Y FV = good unk good FV FV = FV noChange noChange 5400 c 38.85
CZ PAN 2100 7.39 - >> N/A N/A 13 grids1x1 estimate a 0.78 - >> N N U2 - bad bad bad U2 U2 - U2 - noChange noChange 700 a 3.15
HU PAN 24682 86.84 = N/A N/A 538 grids1x1 minimum b 32.16 - > Y U1 - poor unk poor U1 U1 - U1 = noChange knowledge 20500 b 92.34
RO PAN 1100 3.87 = > N/A N/A 1100 grids1x1 estimate b 65.75 = Y FV = good good good FV FV = U1 N/A knowledge knowledge 500 a 2.25
SK PAN 539.46 1.90 = 22 22 N/A grids1x1 estimate b 1.32 = Y FV = good poor poor U1 U1 = FV knowledge knowledge 500 b 2.25
RO STE 200 100 = > N/A N/A 200 grids1x1 estimate b 100 = Y FV = good good good FV FV = U1 N/A knowledge knowledge 100 a 100
FR ALP 3700 0 = N/A N/A N/A minimum d 0 x x Unk Unk FV x unk unk unk XX XX x XX noChange noChange 800 b 0
PL ALP 400 0 x x N/A N/A 2 grids1x1 estimate b 0 x x Unk XX x unk unk unk XX XX XX noChange noChange 200 c 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 13675.19000 2GD - x grids1x1 2GD x grids1x1 2GD - 0EQ MTX - FV = nong nong FV C

01/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 ATL 9800 2GD - grids1x1 2GD x grids1x1 2GD = 2GD MTX = U1 x nc nong U1 D

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 CON 52711 2XP x ≈ 53838 5085.00 5721.00 5400.50 grids1x1 2XP x 2XP = 2XP MTX = U1 - nc nong U1 D

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 MED 48440 2XP - ≈ 57140 934.00 6385.00 3659.50 grids1x1 2XP x 2XP = 2XP MTX - U1 x nong nong XX D

03/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 PAN 28421.46000 2XP = 1673.00 1673.00 1673 grids1x1 2XP - 2XP - 2XP MTX - U1 = nc nong U1 C

02/20

EEA-ETC/BD

Institution: -

Member State:

EEA-ETC/BD
EU28 STE 200 0MS = > 200 grids1x1 0MS = 0MS = good good good 0MS MTX = U1 x nong nong U1 A=

01/20

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.