Restoration efforts required for achieving the objectives of the … · 2016-05-19 · 5 sessions...

Restoration efforts

required for achieving

the objectives of the

Birds and Habitats

Directives

Ms Constance von Briskorn, BIO by Deloitte

Dr Jake Bicknell, University of Kent DICE

Copenhagen, 18th November 2015

5 sessions

Agenda

Introduction to the study – BIO by Deloitte

Objectives and overview

1st work component: Restoration needs – University of Kent

Methods, data, results

2nd work component: Restoration objectives – BIO by Deloitte

Methods, data, results

3rd work component: Restoration efforts – University of Kent

Case studies

Key messages and conclusions – BIO by Deloitte

© 2015 Deloitte SA 2

Introduction to

the study

3 © 2015 Deloitte SA

Context and rationale

4

Past

Implementation of Nature Directives has progressed,

but is still not complete

Today

What has already been done?

What still needs to be done?

By 2020

Full implementation of Nature Directives

Restoration of 15% of degraded ecosystems

Our questions

What restoration needs exist for

listed habitat types and species?

Have MS set adequate

restoration objectives?

Do they have consistent

approaches towards restoration?

Our needs

better define/quantify what is

needed for implementing the

Directives

© 2015 Deloitte SA

Specific objectives


… efforts

… objectives … needs

Restoration: “any (active or passive) measure that can be expressed in area terms and/or in population

figures and is likely to improve the conservation status of a habitat type or a species of the Nature

Directives”.

Providing a first synthetic

view of restoration

Restoration needs: “total

amount of restoration

measures required for a

habitat type or a species of

the Nature Directives to

achieve a FCS”.

Restoration objectives:

“objectives that a national or

regional authority has set for

restoring individual habitat

types/species per

biogeographical region, within a

pre-defined period of time”.

Restoration efforts: “level of ambition of MS, whether objectives

are appropriate to restoration needs, whether MS have a

consistent approach towards restoration across habitat types,

species, scales, over time, whether MS have set priorities among

their restoration objectives”

And taking stock of

Scope


European territory

of EU 27

All habitat types

listed in Annex I of

Habitats Directive

All species listed in

Annexes II, IV & V

of the Habitats

Directive

All bird species

covered by the

Birds Directive

Across terrestrial

and marine

biogeographical

regions

Methods and data sources


Restoration needs for listed habitat types and species

Restoration objectives set by MS

Case studies of restoration efforts by MS

Assessment of needs (quantitative)

Habitat types:

• Additional restoration needs = FRA – current area

• Improvement needs = summing existing area of habitat types that

requires improvement of structure and functions

• Importance of Natura 2000

Species from the Habitats Directive

• Population recovery needs = FRP – current populations

Bird species from the Birds Directive

Identification of objectives (semi-quantitative)

• How many (only) qualitative?

• How many measurable/ quantitative?

Case studies of restoration (most qualitative, some quantitative)

• Analysis of MS approaches towards restoration objectives vs needs, and

of priorities

Art.17

reporting

Art.12

reporting

PAFs

Birds SAP

Information

provided by

MS via replies

to factsheets

Study’s key challenge: the data


Current

area FRA Structure

and

functions

Additional

area

needs

Restoration

needs Area

improvement

needs

Restoration

objectives

Corresponding quantified

objectives

Adequate restoration

efforts

Data availability and quality

9

Art 17/ Art 12

coverage

Our dataset Restoration

needs

Restoration

objectives from PAFs

Habitat

types

229 habitat types

26 MS

3032 individual

assessments

2772 individual assessments

= 91%

= cover approx. 2 500 000 km2,

of which approx.

1 800 000 is terrestrial and 600

000 is marine

Needs calculated

for approx. 90%

of the dataset

depending on

restoration type

• 1334 objectives

• From 15 MS

• Targeting 184

habitat types

• 17% measurable/

quantitative

Species

1232 species

26 MS

7122 individual

assessments

6910 individual assessments

= 97%

Needs calculated

for 45% of

dataset

• 2888 objectives

• From 15 MS

• Targeting 640

species

• of which approx.

2,2% measurable/

quantitative

Birds

533 species

27 MS

7756 individual

assessments

NA

NA

?

?

Data availability = 100% = 75% = 50% = 25% = NA

Data quality = good? = medium = poor ?

Study’s outputs


Deliverables

Report : core results + case

studies

Database

Results

Analysed at aggregate level:

restoration needs → core results of

the report and in DB

Analysed a aggregatelevel/ on

case by case basis: restoration

objectives → a little in core results

and in DB, most in case studies

Analysed on case by case basis:

restoration efforts → in case

studies

Highlighting data gaps

Restoration needs: current

datasets do not allow to

allocate needs to Natura 2000,

nor to calculate needs for birds

Restoration objectives: current

PAFs do nor provide enough

measurable/quantitative

objectives

Restoration efforts could not

be assessed at an aggregate

level

1st work Component Assessing restoration needs


Overview of restoration needs data

12

9%

91%

Unsuitable data

Suitable data (2772)

Habitat types

© 2015 Deloitte SA

29,2%

41,2%

20,2%

9,5%

Structure and Functions FV

Structure and Functions U1

Structure and Functions U2

Structure and Functions Unknown

6%

29%

56%

9%

FRA quantified and greaterthan the current area

FRA is an operator: > or >>than current area

FRA = / ≈ to current area

FRA unknown

Unit: individual assessements

Overview of restoration needs data

13

Species of the Habitats Directive

© 2015 Deloitte SA

3%

97%

Unsuitable data

Suitable data (6910)

21%

14%

10%

55%

FRP ≈ current mimimum population

FRP > current mimimum population

FRP >> current mimimum population

FRP unknown

Unit: individual assessements

Habitat types – methods – example of grasslands

14

Legend Methods

Sum of current area of assessments where structure and

functions is FV

Sum of current area of assessments under each category

Did not use the 10-25% thresholds (Art 17 guidance)

Sum of current area of assessments where structure and

functions is unknown

Difference between FRA and current area

Median percentage increase using operators (3.7% for >, 10%

for >>)

Structure and functions of current area

Additional area

Habitat types – results by habitat groups

15

Habitat types – results by habitat groups

16

Habitat types – results by MS (terrestrial)

17

Habitat types – results by MS (marine)

18

Habitat types – restoration needs in SE

19

Habitat types – top 20 by additional area needs

20

Western Taiga

Habitat types – top 20 by improvement needs

21

Reefs

Habitat types – allocating restoration needs to

Natura 2000 – Example of freshwater habitats

22

50,23% 49,77%

Area in need ofimprovement

Area withstructure andfunctions in FVstate

Area inside Natura 2000 (approx. 18,5%)

Unknown where improvement

needs will be distributed – only

proportions inside and outside

Natura 2000

So for freshwater habitats:

Improvement needs within

Natura 2000: 18% (11 000 km2)

Improvement needs outside

Natura 2000: 82% (47 500 km2)

Area inside Natura 2000 (approx. 18,5%) Area outside Natura 2000 (approx. 81,5%)

Current area: 178 602 km2

Habitat types – allocating restoration needs to

Natura 2000 – Example of freshwater habitats

23

50,23% 49,77%

Area in need ofimprovement

Area withstructure andfunctions in FVstate

Current area: 178 602 km2

Even more difficult to allocate

additional area needs: Will

they be distributed evenenly?

Using the same approach,

additional needs within

Natura 2000 are about 43

km2 and outside about 83

km2.

Key message: in its current form,

Art 17 reporting does not allow

good estimates of how Natura

2000 will contribute to restoration

needs

?

Species – results per taxa


2nd work component Analysis of restoration objectives from PAFs


Objectives – methods


Creating a typology

Reviewing PAFs,

assigning objectives to

either qualitative,

quantitative,

measurable or unknown

and identifying the

parameter of

conservation status

they target (area,

structure and functions,

population, habitat for

the species)

Semi-quantitative

analysis investigating

as far as possible the

appropriateness of

these objectives to

restoration needs

Qualitative = objectives whose content is less informative. E.g.

““increasing the area of habitat X”

Quanti-

tative

= involve an exact figure. E.g. “expected outcome is 400 ha

of habitat type 2130, restored to provide habitats for

Lacerta agilis”.

Measurable = could be “converted” into quantitative objectives by using

extra data or making assumptions. They can contain

quantified information that requires additional calculation to

be converted into an exact figure (e.g. “at least 30 % of all

degraded areas are restored”), detailed site information

(e.g. “hydrological regime is restored in at least 30 Natura

2000 sites”) or indicators (e.g. “to improve the overall

conservation status of habitat X from U2 to U1)

Other Objectives targeting indirect factors affecting the

conservation status such as specific threats (e.g. by-catch)

or the policy and legal framework (e.g. “enhancing the level

of legal protection for species X” or “implementing agri-

environmental measures to protect habitat type Y), or which

were not specified (e.g. when a habitat type or a species is

said to be prioritised for conservation action, but no further

information is provided)

Results for habitat types – number of quantitative/

measurable objectives

27 27 0

50

100

150

200

250

300

350

BE BG CY DE DK EE FR HU IE IT LU LV PL SE UK

Number of objectives

Number of objectives which aremeasurable or quantitative

0

50

100

150

200

250

300


Number of objectives which are measurableor quantitative

Results at habitat group level

Results at MS level

Results for habitat types – parameters targeted

28 28


Results at MS level

0

50

100

150

200

250

300

350


Number of objectives targeting area

Number of objectives targeting structure andfunctions

0

50

100

150

200

250

300

350



Number of objectives targeting area

Number of objectives targeting structure andfunctions

Results for species– number of quantitative/

measurable objectives

29 29

Results at taxon level

Results at MS level

8 4

21

2 6 5 6 5 7 0

20

40

60

80

100

120

140

160

0

200

400

600

800

1000

1200

1400

1600



6 2 3 1 52

0

100

200

300

400

500

600

700

800




Results for species– parameters targeted

30 30


Results at MS level

0

200

400

600

800

1000

1200

1400

1600


Number of objectives targeting a specific parameter(population or habitat for the species)

24 1 3 78

540

72

0

100

200

300

400

500

600

700

800



Number of objectives targeting a specific parameter(population or habitat for the species)

3rd Work component Case studies of restoration efforts


Add picture

Setting quantitative objectives for birds at national

level – example from the Netherlands

32

• Set objectives for 111 breeding and non-breeding bird

species, expressed as the total population size in the

Netherlands

Species

(code ) Breeding

Art.12

minimum

population

Art12.

maximum

population

Population

objective33

Required

population

increase

Population

unit

Acrocephalus

arundinaceus

(A298)

B 150 200 300 100 – 150 P

Charadrius

hiaticula

(A137)

B 350 480 420 0 – 60 P

Grus grus

(A639-B) NB 4700 4700 350 0 I

Recurvirostra

avosetta

(A132-A)

NB 1208 6253 1000 3747 – 8792 I

3 steps approach

Setting quantitative objectives for habitat types in

line with restoration needs – example from NL

33

For each

habitat type,

assessment of

current area,

S&F and

status of key

species

Habitat types clustered into so-called

‘restoration categories’

(‘uitbreidingscategorieën’), which indicate

whether the habitat requires area expansion,

improvements in S&F, or both, and the degree

to which each of these are needed.

Assessment of

additional area need,,

according to the

‘restoration category’ to

which the habitat is

assigned.

Trend in area

compared to

historic range

Structure &

function

RedList-status of

typical species

Restoratio

n category

FRA; A=current area; H=historic

area; In general: 1994 equals

current area

(More or less)

stable or

increasing

(More or less) stable Favourable or NA 1A1 FRA equal to area 1994

Unfavourable 1A2 FRA equal to area 1994

Somewhat reduced Favourable or NA 1B1 FRA equal to area 1994

Unfavourable 1B2 FRA greater than area 1994

Strongly reduced Favourable or NA 1C1 FRA greater than area 1994

Unfavourable 1C2 FRA much greater than area 1994

Decrease < 1%

per year

(More or less) stable Favourable or NA 2A1 FRA equal to area 1994

Unfavourable 2A2 FRA = A + 0.05/0.10 * (H-A)

Somewhat reduced Favourable or NA 2B1 FRA = A + 0.05/0.10 * (H-A)

Unfavourable 2B2 FRA = A + 0.05/0.10 * (H-A)

Strongly reduced Favourable or NA 2C1 FRA = A + 0.05/0.10 * (H-A)

Unfavourable 2C2 FRA = A + 0.10/0.25 * (H-A)

Decrease > 1%

per year

(More or less) stable Favourable or NA 3A1 FRA = A + 0.05/0.10 * (H-A)

Unfavourable 3A2 FRA = A + 0.10/0.25 * (H-A)

Somewhat reduced Favourable or NA 3B1 FRA = A + 0.10/0.25 * (H-A)

Unfavourable 3B2 FRA = A + 0.25/0.75 * (H-A) [1]

Strongly reduced Favourable or NA 3C1 FRA = A + 0.25/0.75 * (H-A) [1]

Unfavourable 3C2 FRA = A + 0.75/1.00 * (H-A) [2]

Setting coherent restoration objectives

- Avoid double-counting: an example from

Flanders

34

%

Overlap

© 2015 Deloitte SA

• Deduction of

overlap from

additional

habitat area

of relevant

species

• Examine overlap between species’ and habitat types’

ecological requirements and related additional area

needs

• Determine and quantify overlap

Additional area

needs for

species

Additional area

needs for

habitat types’

Additional area

needs

for

Species

minus

overlap

Area of

Overlap

Benefits of the approach:

Optimizing restoration efforts

Increasing cost efficiency

Setting coherent restoration objectives - setting

priorities outside Natura 2000: example from

Denmark

Denmark defined priorities for open habitat beyond Natura 2000 in 2010, in their Green

Growth Agreement for 2011-2015, which include measures for the active management

of 40 000 ha of open habitat outside Natura 2000 (Fourth Country Report to CBD,

Denmark, 2009). According to the Danish PAF, these 40 000 ha constitute 27% of the

habitat area requiring active management,.

The Danish Nature Protection Act includes provisions which prohibit the change of the

natural conditions in a number of habitats of certain sizes throughout the country, e.g.

lakes > 100 m2 and bogs, salt marshes, natural grasslands and heaths > 2500 m2.

Most of these generally protected habitats constitute or include natural habitat types or

habitats for species covered by the annexes of the Nature Directives. Sixty percent of

these generally protected habitats are found outside Natura 2000 sites.


Different rationales across MS

Restoration priorities


Degree of responsibility

in FR, HU, NL, BE and UK

Example: from HU: The majority (90%) of the Pannonian biogeographical region is on

Hungarian territory, while the rest is shared by Romania, Slovakia and the Czech

Republic. Hungary has taken its large responsibility for this biogeographical region as one

of the starting points for identifying its conservation priorities: for habitat types the priority

is assessed according to the national surface covered by individual habitat types, and its

share compared to the total surface within the Pannonian region. In total, 14 habitat types

and 11 species are considered as conservation priorities on this basis.

Text

Multidimensional prioritization: the example of Tuscany

In its Regional Biodiversity Strategy, Tuscany presents a multi-criteria scoring method to

identify priority habitat types and species, for conservation in general, based on the

following criteria:

• Vulnerability

• Quality

• Tuscan Contribution to Community objectives

• Tuscan Contribution to the National Range

Each of these parameters is assigned a numerical value

Key messages

& conclusions


Key messages: what needs to be done


Promoting solid approaches and exchange of best practices on setting of objectives

and priorities across MS:

• ensure completeness and coherence of relevant data in Article 12/17 & PAFs

• use Life+ Integrated projects to improve the setting of needs, objectives and priorities

Improving the potential for expressing habitat restoration needs from national Art.

17 reports:

• habitat area figures should be based on actual area data & should be quality-

checked!

• promote/make obligatory the setting of FRAs

• structures and functions in U1/U2: need to provide share of area with S&F in

Favourable status

Improving potential of PAFs for expressing habitat restoration objectives:

• review PAF structure so as to encourage MS to provide habitat-type specific area

information in the PAFs

• encourage MS to clearly distinguish in PAFs between improvement needs and needs

to additional area (if any)

Improving potential of Article 12 for expressing restoration needs for bird

populations : setting of FRVs for bird populations

The roadmap


MS roadmap

1. Complement existing data

2. Improve quality of data

3. Set quantified restoration objectives

4. Set priorities among restoration objectives and try having consistent/

integrative approaches towards restoration

EU roadmap

1. Harmonize reporting format on Art.17 and Art.12 so as to improve

comparability of data

2. Support MS in their efforts to have integrated approaches towards

restoration

Thank you!


Contacts

Ms Constance von Briskorn, BIO by Deloitte

[email protected]

Dr. Jake Bicknell, University of Kent (DICE)

[email protected]

Study team BIO by Deloitte, University of Kent (DICE), VU University Amsterdam (VU), Stichting

BirdLife Europe

41 © 2015 Deloitte SA © 2015 Deloitte SA

In association whith

mailto:[email protected]

mailto:[email protected]

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