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Low Hanging Fruits Mora Aronsson ETC-BD/SLU

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Presentation on theme: "Low Hanging Fruits Mora Aronsson ETC-BD/SLU"— Presentation transcript:

1 Low Hanging Fruits Mora Aronsson ETC-BD/SLU
Mora Aronsson – ETC-BD/SLU /7 Vilnius Low Hanging Fruits (Padova /23) Mora Aronsson ETC-BD/SLU

2 Low Hanging Fruits Old priority index

3 Old priority index (worst first) - update
No big changes Two more MS involved Two habitats FV, but same score as 2013?

4 Low Hanging Fruits Background LHF

5 Low Hanging Fruits approach
Can we identify habitats where we can make quick progress? Clear link to reaching Target 1 of the European Union Biodiversity Strategy May provide some ‘good news’ for next State of nature in the EU report

6 Low Hanging Fruits TARGET 1: FULLY IMPLEMENT THE BIRDS AND HABITATS DIRECTIVES To halt the deterioration in the status of all species and habitats covered by EU nature legislation and achieve a significant and measurable improvement in their status so that, by 2020, compared to current assessments: → 100% more habitat assessments and 50% more species assessments under the Habitats Directive show a favourable or improved conservation status; and → 50% more species assessments under the Birds Directive show a secure or improved status.

7 Low Hanging Fruits Method

8 Low Hanging Fruits Step 1: sort & group all features (habitats) according to their conservation status and trend in conservation status: Group 1 – Features that already are in FV Group 2 – U1+ could change to FV Group 3 – U1= could change to U1+ Group 4 – U1x could change to U1+ Group 5 – U1- could change to U1= Group 6 – U2+ could change to U1 Group 7 – U2= could change to U2+ Group 8 – U2x could change to U2+ Group 9 – U2- could change to U2= Group 10 – XX could change to U1+ or U2+

9 The following index is used:
Step 2: The following index is used: Where parameters are scored as: U2 = 2 points, U1 = 1 point, XX = 1 point, FV = 0 point

10 Low Hanging Fruits Step 3: The features are sorted within each LHF Group after their score from lowest to highest. Step 4: For each feature the need for improvement in order to contribute to Target 1 is identified (as far as possible, sometimes there are too many unknowns) and the threats reported in Article 17 (only ‘High’) are taken into account. Step 5: The features are checked by an expert one by one to sort out which of these habitats are true ‘Low Hanging Fruits”, i.e. could reach improvement in a limited period of time.

11 Low Hanging Fruits Result

12 Low Hanging Fruits – Step 1
Step 1 gives the following results after grouping the habitats: Group 1 – Habitats that already are FV – 30 habitats Group 2 – U1+ could change to FV – no habitats Group 3 – U1= could change to U1+ – 29 habitats Group 4 – U1x could change to U1+ – 7 habitats Group 5 – U1- could change to U1= – 19 habitats Group 6 – U2+ could change to U1 – no habitats Group 7 – U2= could change to U2+ – 2 habitats Group 8 – U2x could change to U2+ – 1 habitats Group 9 – U2- could change to U2= – 19 habitats Group 10 – XX could change to U1+ or U2+ – 9 habitats

13 Low Hanging Fruits – Step 2-4

14 Low Hanging Fruits – Step 5
Overlap with worst situation approach - yellow

15 Distribution of potential LHF by habitat group
Number of potential LHF Forest 13 Heath & scrub 3 Freshwater 2 Grassland 1 Wetland

16 Low Hanging Fruits – Next step?
Is the selection of habitats OK? Is the proposed actions OK? What does it cost to reach the target for the habitat? How to prioritize between “worst first” and LHF?

17 Low Hanging Fruits Thank you

18

19 Low Hanging Fruits Step 2: Summing up the conservation status parameters reported for each habitat in each Member State that shares the feature in a particular biogeographic region and divide it with the representation (coverage) of the feature in Natura 2000 (in percent) The following algorithm is proposed: C = A/B then multiplied by 100 A = the sum of the parameters Range, Area and Structure & Function for all Member States in the region where the habitat or the species occurs. B = Coverage of the feature by the Natura 2000 network (in percent) C = Low Hanging Fruit (LHF) score for the habitat For each parameter, the following rules are applied: U2 = 2 points, U1 = 1 point, XX = 1 point, FV = 0 point

20 Low Hanging Fruits A short history Background LHF Method Result Further work

21 First round of seminars
Identify habitats in poor conservation status which occur in several MS where action required and promote cooperation between MS at the same time But for most of these habitats progress will be slow

22 Old priority index (worst first)
Criteria for prioritisation (Criterion A, B and C) Criterion A. Number of MS where habitat types are present. Criterion B. Species and habitat types at unfavourable conservation status 2 points for each Member State in which it has been assessed as Unfavourable-Bad (U2) 1 point if Unfavourable-Inadequate (U1) or Unknown (XX) Criterion C. Trend information 1 point if Unfavourable-Inadequate (U1) or Unknown (XX) Index used (D) – A(B+C) = D

23 Easier to reach Favourable Conservation Status or to improve Conservation Status if
N° of parameters responsible for poor Conservation Status is low The proportion of the habitat covered by Natura 2000 sites is high Expert opinion to identify true ‘Low hanging fruits’

24 Change in conservation status between reporting periods
Low Hanging Fruits Progress according to Target 1 from A17 Change in conservation status between reporting periods CS in FV U1 + U1 U1 - U2 + U2 U2 - XX CS in 2001 - 2006 A (=) C (-) E (x) A (+) B (+) D (=) FV = Favourable, U1 = Unfavourable – inadequate, U2 = Unfavourable – bad, XX = Unknown The signs between brackets indicate the type of change in the conservation status between reporting periods: (=) no change, (+) improvement, (-) deterioration, (x) not known. ‘A’ indicates ‘favourable’ assessments, ‘B’ ‘improved’ assessments, ‘C’ ‘deteriorated’ assessments, ‘D’ unfavourable and unknown assessments that did not change, and ‘E’ assessments that became ‘unknown’.


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