Fragmentation of natural and semi-natural areas

Assessment versions

Published (reviewed and quality assured)

• No published assessments

Rationale

Justification for indicator selection

MAIN ADVANTAGES OF THE INDICATOR

Methodology: this indicator is based on a simple methodology, which includes mathematical calculations and GIS analysis on Corine Land Cover (CLC) data.

Biodiversity relevance: the indicator has a high relevance for biodiversity because it indicates changes in the patch size of natural and semi-natural areas of any type of ecosystem across Europe. If the patch size of these areas decreases drastically, it will have a negative influence on the habitat types present and the species dependent on these habitat types.

Geographical and temporal coverage: For details on geographical and temporal coverage for Corine Land Cover, see

2000: http://www.eea.europa.eu/data-and-maps/data/corine-land-cover-2000-raster-2#tab-gis-data

2006: http://www.eea.europa.eu/data-and-maps/data/corine-land-cover-2006-raster-3

Scientific references

• No rationale references available

Indicator definition

This indicator shows the proportion of and trends in natural and semi natural areas, on the basis of land cover maps produced by the photo-interpretation of satellite imagery.

Units

Percentage change of area

Policy context and targets

Context description

The indicator is intended to address the question of ecosystem integrity by providing a measurement of 'disintegration' of the countryside across Europe.

Land use in Europe has changed substantially during the past century. The changes in land use have, in turn, affected the size of natural and semi-natural patches of land and have introduced fast growing fragmentation of the wider countryside. This indicator gives information on the trends in surface area of natural and semi natural areas at pan-European level, through the calculation of values derived from land cover maps.

Land cover maps are developed from satellite imagery based on the spectral properties of each pixel within a scene. For this indicator we use data from the Corine Land Cover database (CooRdinate Information on the Environment - Corine).

By calculating the areas belonging to these land cover classes, information on the extent of fragmentation that has occurred in the natural and semi-natural areas is obtained, within the limitations of the CLC data (see Section on main disadvantages).

Relation of the indicator to the CBD Strategic goals and EU targets

Natural and semi-natural areas represent an important integrity component of any given ecosystem, by supporting the full range of ecosystem services and the majority of species and habitats to be found in this type of ecosystem. If the size of such areas decreases, the integrity of the whole ecosystem is at risk. This in turn might affect the potential of the given ecosystem to deliver goods and services.

Targets

EU 2020 Biodiversity Strategy - target 2

Related policy documents

• EU 2020 Biodiversity Strategy
  in the Communication: Our life insurance, our natural capital: an EU biodiversity strategy to 2020 (COM(2011) 244) the European Commission has adopted a new strategy to halt the loss of biodiversity and ecosystem services in the EU by 2020. There are six main targets, and 20 actions to help Europe reach its goal. The six targets cover: - Full implementation of EU nature legislation to protect biodiversity - Better protection for ecosystems, and more use of green infrastructure - More sustainable agriculture and forestry - Better management of fish stocks - Tighter controls on invasive alien species - A bigger EU contribution to averting global biodiversity loss

Methodology

Methodology for indicator calculation

Figures 1, 2, 3 and 4 use data from Corine Land Cover (CLC) for the years 2000 and 2006. Hence, they have the same geographical coverage and class definition as CLC itself. Please note that the CLC map provides broad patterns of land cover/uses with a minimum mapping unit of 25 hectares and therefore enables the observation of broad patterns of change.

Patterns of natural/semi-natural landscapes (Figure 1)

For the calculation, natural/semi-natural lands include the following CLC classes: Forests (3.1), Scrub and/or herbaceous vegetation (3.2), Open spaces with little or no vegetation (3.3), Inland wetlands (4.1) and Maritime wetlands (4.2).

Three landscape patterns enable the landscape fragmentation in European countries and the trend in the period 2000-2006 to be described. They are based on a mosaic index (Estreguil et al., 2012, 2013) that is defined according to the composition in terms of natural/semi-natural, artificial surfaces (CLC class 1) and agricultural areas (CLC class 2) in the 1km² surroundings of each natural/semi-natural land pixel (1 ha): (1) ‘core natural’ pattern, where natural/semi-natural lands are distributed in relatively ‘unfragmented’ large patches (with at least 80% natural neighbourhood), (2) ‘mixed natural’ pattern, where they are fragmented by agricultural and/or artificial land, still in a natural/semi-natural context (with at least 60% natural neighbourhood), and (3) ‘some natural’ pattern, where they are embedded in predominant agricultural or artificial context (less than 60% natural neighbourhood).

Patterns of forest landscapes (Figure 2)

For the calculation, forest lands include the CLC classes Broad-leaved forest (3.1.1), Coniferous forest (3.1.2) and Mixed forest (3.1.3), as well as young plantations with 500 subjects per hectare and transitional woodland where canopy closure is greater than 50%. Natural/semi-natural non-forested lands include CLC classes 3.2 and 3.3 (natural/semi-natural non-wooded vegetation), wetlands (CLC class 4), young plantations (<500 subjects/ha), other transitional wooded land, clear cuts, burnt areas and forest nurseries.

Similarly to the patterns of natural/semi-natural lands, forest lands are described according to three pattern types based on a mosaic index (Estreguil et al., 2012, 2013), which describes how much forest land (1 ha) is likely ‘unfragmented’ or adjacent to mainly natural/semi-natural lands in their immediate (1 km²) surroundings (‘core natural’ pattern, with at least 80% natural neighbourhood) and how much is fragmented by agriculture and/or artificial lands, still in a natural context (‘mixed natural’ pattern, with at least 60% natural neighbourhood) or embedded as islets and linear features in predominantly agricultural or artificial lands (‘some natural’ pattern, less than 60% natural neighbourhood).

The trend of the ‘core natural’ pattern share for 2000-2006 is shown according to these intervals: below -1% (--), between -1% and -0.1% (-), between -0.1% and 0.1% (=), between 0.1% and 1% (+) and above 1% (++).

Forest connectivity (Figures 3 and 4)

Forest connectivity is measured at landscape level as a function of forest availability (forest area), forest topology, distance and landscape suitability between forest patches for a given species dispersal capability. A forest connectivity index (Estreguil et al., 2012, 2013) is calculated per landscape unit of 25 km x 25 km for forest dwelling species dispersing on average 1 km. Landscapes including woods have a varying connectivity index that ranges from above 0% (few woodlands and highly isolated) to 100% (all woods maximally connected). The shares of landscapes in three different connectivity ranges (<30%, 30-50%, >50%) are shown per country in Figure 3. The change of forest area is studied at landscape level in relation to the change in connectivity for the period 2000-2006 (Figure 4).

Further information

JRC EFDAC (European Forest Data Centre) Map viewer at http://efdac.jrc.ec.europa.eu/ (go to map viewer and select Forest Pattern Query)

JRC Forest Action Web site: http://forest.jrc.ec.europa.eu/activities/forest-pattern-fragmentation/

Methodology for gap filling

No methodology for gap filling has been specified. Probably this info has been added together with indicator calculation.

Methodology references

No methodology references available.

Data specifications

EEA data references

• Corine Land Cover 2006 raster data provided by European Environment Agency (EEA)
• Corine Land Cover 2000 raster data provided by European Environment Agency (EEA)

External data references

• Broad scale Connectivity 2006 and trends 1990-2000-2006
• Landscape mosaic pattern maps raster data years 2000 and 2006

Data sources in latest figures

Uncertainties

Methodology uncertainty

No uncertainty has been specified

Data sets uncertainty

No uncertainty has been specified

Rationale uncertainty

MAIN DISADVANTAGES OF THE INDICATOR

Data set resolution: the main disadvantage of using the CLC data set is that fragmentation occurring below the threshold of minimum resolution of 25 Ha is not detectable. The CLC data, however, is the best currently available to cover large areas of Europe in a harmonised way.

MAIN ADVANTAGES OF THE INDICATOR

Biodiversity relevance: the indicator does not provide direct information on the impact of habitat fragmentation on the status of species populations, but can contribute to the forest ecosystem assessment and semi-natural landscapes.