hnv farmland in germany€¦ · agriculture maintains or contributes to a high level of...

HNV Farmland in Germany HNV Farmland in Germany –– A sample approach for A sample approach for

monitoring and evaluation monitoring and evaluation ––

presentation in presentation in PPäärnurnu / Estonia / Estonia on 17. on 17. juinjuin 20082008

Dr. Rainer Dr. Rainer OppermannOppermann (IFAB)(IFAB)

Partners in the projectIFAB (Mannheim) – PAN (München) – ILN (Singen)

Structure of the presentationStructure of the presentation

1) Types of indicators

2) Definition HNV – Types of HNV farmland in Germany

3) Different methodical approaches in Europe

4) Analysis of data sources in Germany

5) Classification of German biotope data as HNV-type s

6) Method for Germany: random sample-based monitorin g

7) Discussion and perspectives

Dr. Rainer Oppermann - Coordination of the projectIFAB – Institut für Agrarökologie und Biodiversität, Mannheim

Institute for agroecology and biodiversity

Daniel Fuchs PAN - Planungsbüro für angewandten Naturschutz GmbH, München

planning institution for applied nature conservation

Alfons KrismannILN - Institut für Landschaftsökologie und Naturschutz (ILN) Singen

Institute for landscape ecology and nature conservation

Project by order of the German Federal Agency of Natu re ConservationSupervisor: Dr. A. Doerpinghaus, M. Neukirchen

Partners in the HNVPartners in the HNV --projectproject

1)1) TypesTypes of of HNVHNV--indicatorsindicators withinwithin thethe CMEF CMEF

● Baseline Indicator 18 : Biodiversity: High nature value Farmland and forestry, measured as UAA of HNV Farmland, in h ectares.

● Result Indicator 6: Area under successful management contributing to biodiversity and HNV Farming / Fore stry, measured as the total area of HNV Farmland an Fores try under successful land management, in hectares.

● Impact Indicator 5: Maintenance of HNV Farming and Forestry, measured as changes in High Nature Value areas and defined in terms of quantitative and qualitative changes .

2)2) Definition HNVDefinition HNV

“High nature value (HNV) farmland are those areas i n Europe where

agriculture maintains or contributes to a high leve l of biodiversity”.

�� HNV farmland is divided into three main types (according to Andersen et al. 2003):

Type 1: Farmland with a high proportion of semi-natural vegetation.

Type 2: Farmland dominated by low intensity agriculture or a mosaic of semi-natural and cultivated land and small-scale features.

Type 3: Farmland supporting rare species or a high proportion of European or World populations.

2)2) TypesTypes of HNV in Germany (of HNV in Germany ( examplesexamples ))

Typ 1: Farmland with a high proportion of semi-natural vegetation.


Typ 2: Farmland dominated by low intensity agriculture or a mosaic of semi-natural and cultivated land and small-scale features.


Typ 3: Farmland important for rare species or a high proportion of European or World populations.

2)2) Definition HNVDefinition HNVThe HNV-indicator consists of three definition-part s:

Calculation of HNV farmland as area-indicator:

HNV farmland = sum of HNV farmland-areas types 1, 2 and 3

● as absolute hectare-information and

● as part of the agricultural landscape

� furthermore a qualitative differentiation is needed for the monitoring

type 1

type 2

type 3Schematic presentation of the three definition-parts. All

three types partly interfere with each other. The total

area of HNV farmland is the sum of areas of all three

definition-parts in consideration of overlapping (the

same area is not counted several times).

3)3) Different Different methodsmethods in Europein Europe

regularly, annual update middle, corresponds to main natural geographic regions

goodSwitzerland

regularly, annual update, but indicator is in practice only in one federal state (Nordrhein-Westfalen)

moderate, analysis up to federal state level and to natural geographic regions

goodÖFS (Germany)

regularlymoderate, but low amount of samples for further arealdifferentiation

good data baseGreat Britain

sample approaches

regularlyvery good, up to community levellike FranceBelgium

regularlyvery good, up to community levelrelatively bad concerning nature value: indicator corresponds only indirectly to HNV-areas, calculation is complex

France

regularlynot specificateddiffuse, several alternatives given

EU-approach (IEEP)

updatearea coverageRelevance of real nature qualityapproach / country

4)4) Analysis of Analysis of datadata sourcessources in Germanyin Germany

● Research to biotope data in all federal states.

● Application of the biotope list of the German Fede ral Agency of Nature Conservation.

● Focus in biotope types recorded also in the federal states: translation of the federal key to the states keys (realized in an earlier project).

● Comparison of biotope and FFH data with HNV data (e xamples).

● Classification of existing biotope data to HNV-type s.

● Selection of species for type 3 under consideration of existing data (FFH-und bird-monitoring).

6-20 %sum

0-2%species habitates

0-2 %Mixed orchards

1-10 %species-rich arable land

3-10 %FFH-types 6510, 6520 etc. / species-rich grassland

1-5 %biotopes (hedges, shrubberies etc.)

1-3 %Semi-natural vegetation

area HNV-farmland

main types HNV-farmland:


6-20 %sum

barely0-2%species habitates

barely0-2 %Mixed orchards

not / barely1-10 %species-rich arable land

partly3-10 %FFH-types 6510, 6520 etc. / species-rich grassland

moderate good1-5 %biotopes (hedges, shrubberies etc.)

very good1-3 %Semi-natural vegetation

Coverage withexisting data

area HNV-farmland

main types HNV-farmland:


conclusion:

● biotope data is heterogeneous and incomplete.

● data is only +/- complete for „classic“ biotopes like fens, semi-dry grassland and other

● Some HNV types with the most relevant areas are recorded completely insufficient:�� species-rich grassland�� species-rich arable land�� structure-biotopes like hedges, mixed orchards, bou ndary ridges

● Update of data is irregularly or not sure.


Consequences (alternatives) for the implementation of an indicator:

● biotope data shall be updated and there will be org anised a regular update

or

● random samples will be taken with a representative number of sample plots: registration of all needed data, regular upd ate of the samples

A third way – use of biotope data and completing the samples is more difficult than a complete random sampling and is not in discussion any longer.


5)5) ClassificationClassification of of biotopebiotope datadata to to HNVHNV--typestypesclassification of FFH-types to HNV farmland (types 1 an d 2)

Code LRT1330 Atlantische Salzwiesen (Glauco-Puccinellietalia maritimae)1340 Salzwiesen im Binnenland2320 Trockene Sandheiden mit Calluna und

Empetrum nigrum [Dünen im Binnenland]4010 Feuchte Heiden des nordatlantischen Raums mit Erica tetralix4030 Trockene europäische Heiden4060 Alpine und boreale Heiden5130 Formationen von Juniperus communis auf

Kalkheiden und -rasen6110 Lückige basophile oder Kalk-Pionierrasen (Alysso-Sedion albi)6120 Trockene, kalkreiche Sandrasen6130 Schwermetallrasen (Violetalia calametariae)6150 Boreo-alpines Grasland auf Silikatsubstraten6170 Alpine und subalpine Kalkrasen

5)5) ClassificationClassification of of biotopebiotope datadata to to HNVHNV--typestypesclassification of FFH-types to HNV farmland (types 1 an d 2)

Code LRT6210 Naturnahe Kalk-Trockenrasen und deren

Verbuschungsstadien6230 Artenreiche montane Borstgrasrasen (und submontan

auf dem europäischen Festland) auf Silikatböden6240 Subpannonische Steppen-Trockenrasen

[Festucetaliae vallesiacae]6410 Pfeifengraswiesen auf kalkreichem Boden, torfigen

und tonig-schluffigen Böden (Molinion caeruleae)6430 Feuchte Hochstaudenfluren6440 Brenndolden-Auenwiesen (Cnidion dubii)6510 Magere Flachland-Mähwiesen6520 Berg-Mähwiesen7210 Kalkreiche Sümpfe mit Cladium mariscus

und Arten des Caricion davallianae7230 Kalkreiche Niedermoore

5)5) ClassificationClassification of of biotopebiotope datadata to to HNVHNV--typestypesclassification of extensively utilized grassland to HNV farmland

(types 1 and 2)

Differentiation with a list of key species

Transect across the parcel

Detailed data on each parcel

Evaluation Method Grassland

Transect method (Example Baden-Württemberg)

Counting indicator species in each third of a transectacross the parcel

A grassland parcel is defined as „rich in species“, whenthere are at least 4 indicator species in each third of the transect (out of the set of 28 indicator species)

5)5) ClassificationClassification of of biotopebiotope datadata to to HNVHNV--typestypeslandscape-elements (Typ 2)

● Parcel edges and edge strctures with at least 1 m width and 10 m length and if structure rich

● Ruderal parcels with at least 1 m width and 10 m length and if structure rich

● Shrubberies incl. edges with at least 1 m width and 10 m length and if structure rich, at least 3 wood species, percentage of conifers less than 20 %

● Solitaire trees, alleys, tree rows (without confers)

● Small scale woods and wood edges within the landscape if structure rich, at least 3 wood species, percentage of conifers less than 20 %

● Forest edges only forest edges if rich in structure(categories 1-3 in 5 categories-scale)

● Structure rich field paths and roads● Small water courses at least 20 cm depth and 1 m width (incl.

edges)

5)5) ClassificationClassification of of biotopebiotope datadata to to HNVHNV--typestypeslandscape-elements (Typ 2)

● Quellen, natürliche und naturnahe Gewässer, Bäche inkl. Fließgewässer begleitende Erlen- und Eschenwälder Fließgewässer 2. und 3. Ordnung (inkl. Randstreifen, Böschungen, Gehölzgalerien)

● Trockenmauern, verfügte Natursteinmauern, Sand-, Lehm-, Lößwand ab 1 m Höhe und 10 m Länge

● Steinriegel, Fels(riegel) ab 10 m²

● Natürlich dystrophe, oligotrophe bis eutrophe Weiher/ Tümpel, eutrophe Altwasser keine Nutzung, inkl. Verlandungsbereich und Böschungen, Wasserfläche max. 1 ha

● Steinbrüche / Lehmkuhlen / Erdaufbrüche nicht genutzt, bei Lage außerhalb landw. Nutzfläche erst ab 1 ha Größe

● Feuchtgebietselemente (Großseggenriede, krautigeUfersäume an Gewässern und Land-Schilfbestand) keine Hochmoore, keine Randbereiche von Flüssen und Seen

● Hochstauden- und Hochgrasfluren nur artenreiche Bestände oder Bestände mit mindestens einer Rote-Liste-Pflanzenart

● Species rich arable land at least 3 key species present

● Species rich vineyards at least 3 key species present

● Extensivly utilized pastures Classification with the key species rich grassland (at least 4 key species in a transect)

● Orchards and alleys of fruit trees at least 1.6 m stems; either whole parcel or parts of parcel

● Fallow land / set aside land only self greened parcelsnot: permanent fallow land

5)5) ClassificationClassification of of biotopebiotope datadata to to HNVHNV--typestypesextensively managed areas (Type 2)

Examples for species of FFH-annexes II und IV● mammals: Hamster (Cricetus cricetus)● amphibs: Laubfrosch (Hyla arborea), Knoblauchkröte,

Moorfrosch, Kammmolch● butterflies: Ameisenbläuling (Maculinea nausithous)● dragonflies : Grüne Mosaikjungfer, Helm-Azurjungfer, Vogel-

Azurjungfer

Examples for breeding birds● Suitable for consideration: Bekassine (Gallinago gallinago),

Wachtelkönig (Crex crex), Wiesenpieper (Anthus pratensis), Braunkehlchen (Saxicola rubetra), Grauammer (Emberizacalandra); not: Kiebitz (Vanellus vanellus), Rotmilan (Milvus milvus)

5)5) ClassificationClassification of of datadata to to HNVHNV--typestypesclassification of species-habitates to HNV farmland (T ype 3)

principles

● area-representative random-sampling, representative for whole Germany as well

as for each federal state

● stratification-based sample-net of the breeding bird-monitoring (synergy effects)

● consistent and low-input method for data record

● regular and assured update (independent programme): update every two years

● reference to whole farmland area by extrapolation

● results can be obtained also for the evaluation of AEM

6) Method: random sample-based monitoring

proposal for GermanySample tied to breeding bird-monitoring= 2.637 sample areas (= ~ 200/ federal state)

advantages● basic data and information is available, e.g.

coordinates, aerial photos, landuse data etc.● stratificated sample (= comparatively low

sample size)● bird data available, combined evaluation

possible● Evaluation together with data from agro-

environmental programmes, if InVeKoS-data are available

disadvantages● further differentiation within natural geographic

regions is complex● sample size at minimum level

6)6) MethodMethod : : randomrandom samplesample --basedbased monitoringmonitoring

four examples

6)6) MethodMethod : : randomrandom samplesample --basedbased monitoringmonitoring

size of sample area 1.000 m x 1.000 m = 100 ha

In this sample ca. 3/4 forests, 1/4 farmland

percentage of the HNV-areas: about 50 % of the farmland

- species-rich arable land- species-rich grassland- extensively managed

grazing land- wet grassland- ruderal area- hedges- rivers

6)6) Method: random sampleMethod: random sample --based monitoringbased monitoringExample for one sample area (middle of Germany, sou th of Kassel)

size of sample area 1.000 m x 1.000 m = 100 ha

In this sample: 100 % farmland percentage of the HNV-farmland < 1 %

- alleys

6)6) MethodMethod : : randomrandom samplesample --basedbased monitoringmonitoringExample for one sample area (Eastern Germany, east of Ber lin)

size of sample area1.000 m x 1.000 m = 100 ha

In this sample ca. 1/3 forest and residential area, 2/3 farmland

percentage of the HNV-farmland about 20 %

- mixed orchards- species-rich grassland- fallow area with HNV quality- hedges / shrubberies- rivers

6)6) MethodMethod : : randomrandom samplesample --basedbased monitoringmonitoringExample for one sample area (southern Germany, west of St uttgart)

size of sample area1.000 m x 1.000 m = 100 ha

In this sample ca. 10 % residen-tial area, 90 % farmland

percentage of HNV-farmlandabout 15 % of the farmland

- extensively managed meadowsand pastures with HNV-quality

- fallow areas with HNV-quality- hedges / shrubberies

6)6) MethodMethod : : randomrandom samplesample --basedbased monitoringmonitoringExample for one sample area (northern Germany, south of Ki el)

12822637

25235047933

9763654

8798331715891

…..

21

HNV Typ 2 (ha)

…..

28

HNV-Anteil

an LNF Typ 2 (%)

…..

HNV Typ 3 (ha)

…..

15

HNV Typ 1 (ha)

…..

20

HNV-Anteil

an LNF Typ 1 (%)

…..

…..

HNV-Anteil

an LNF Typ 3 (%)

…..

74

LNF (ha)

…..

36

HNV gesamt

(ha)*

…..sum

……

….

492

HNV-Anteil

an LNF (%)

sampleareaNr.

6)6) MethodMethod : : randomrandom samplesample --basedbased monitoringmonitoringresult table: detailed figures on HNV farmland types 1-3 in [ha] and [%]

* total area of types 1, 2 and 3 -> HNV farmland-indicator

further qualitative data on● Surface of several biotope types and species habitates

● multi-level data on biotope-quality

6)6) Methode:Methode: Stichprobenbasiertes MonitoringStichprobenbasiertes Monitoring

example for data-chart for analysis and monitoringqualitative record of all parcels in thesample areasin 5 categories(use of charac-teristic speciesand structureparameters)

Seminaturalvegetation

Extensivelyutilized parcelswith HNV quality and landscapeelements

Comparison of ecologic data with IACS-data,

� development of AEM-areas – not-AEM-areas

� comparison of different qualities in view of AEM-measures and landscape differences

� all in all with about 200 sample areas, data from about 600 – 6.000 plots for comparing is available for the overall evaluation in one federal state

6)6) FurtherFurther analysisanalysiscomparison AEM-areas – not-AEM-areas (e.g. west of Stut tgart)

● method matched and cost-optimized for HNV farmland-indicator

● available data is not used (except Nordrhein-Westfalen)

● updates can be centrally organized

● safe method (no dependencies)

● „all-inclusive-package“: fast realizable, relatively low price

● evaluation of agro-environmental measures partly possible

realization of this indicator-concept in 2008 possible,

if money is provided from state and federal states

7)7) DiscussionDiscussion and and perspectiveperspective

● Implementation of this method will formally be decided

today (17. juin 2008) by a gremium of „Bund and Länder“

(state and 16 federal states)

● Eventually the number of sample areas will be reduced

from 2.637 to 1.000 sample areas (representative on

national level)

● Still open: coordination of the implementation on national

level or on federal state level

�� Implementation will probably start in autumn 2008

8.) 8.) ActualActual performanceperformance

Thank you for your attention!

For further information: [email protected]

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