Fragmentation of natural and semi-natural areas
Published (reviewed and quality assured)
Justification for indicator selection
MAIN ADVANTAGES OF THE INDICATOR
Methodology: this indicator is based on a simple methodology including mathematical calculations and GIS analyses on the Corine land cover data (CLC).
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: Corine land cover data is available from 23 EU Member States (see metadata for full list). For these 23 countries, data are available as two data points i.e. year 1990 and 2000. For details on temporal coverage per country, see http://dataservice.eea.europa.eu/download. asp?id=16336andfiletype=.pdf. The data can provide for country benchmarking. Additional countries have joined the network and have a first data point in 2000. With an updated CLC2010 more countries can therefore be assessed, some with three data points, others with two. The next update of Corine land cover data will be for the year 2006.
- No rationale references available
The indicator shows the change in average size of patches of natural and semi natural areas, on the basis of land cover maps produced by photo-interpretation of satellite imagery.
% change of area
Policy context and targets
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 patch size of natural and semi natural areas at the pan-European level, by 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). The CLC data are based on 44 land cover classes of which 26 are considered as natural and semi natural for the purpose of this indicator (see Annex 1). These can be grouped into forests, pasture, agricultural mosaics, semi-natural land, inland waters and wetlands.
By calculation of size values for areas belonging to these land cover classes, we have information on the extent of fragmentation which has occurred in the natural and semi-natural areas, within the limitations of the CLC data (see Section on main disadvantages).
Relation of the indicator to the focal area
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.
No targets have been specified
Related policy documents
No related policy documents have been specified
Methodology for indicator calculation
Natural and semi-natural areas are represented by selected land cover categories which are forests, pasture, agricultural mosaics, semi-natural land, inland waters and wetlands. For a given region/ country, the change in average patch size of the selected land cover categories is the difference between two dates in their mean value, calculated as their quadratic mean.
The indicator is produced by using a simple mathematical calculation, the quadratic mean between the mean values of the patch size of a given area between two dates. By using the quadratic mean, the size of the individual objects matters as much as their number: in most cases, strong fragmentation of the larger areas matters more than fragmentation of small ones. At the same time, when a small patch in an area disappears completely (in time 2), the mean value for that area will be greater than at the time it was still present (time 1), unless the number of patches (n) in time 2 can not be less than in time 1. That means that patches with size = 0 have to be taken into account too.
The Quadratic Mean or Root Mean Square (RMS) is the square root of the mean square value of a variable so it is a statistical measure of the magnitude of a varying quantity. It can be calculated for a series of discrete values or for a continuously varying function, using the following formula:
Quadratic Mean or Root Mean Square = SQRT (1/n ((X1)2 + (X2)2 + (X3)2 +........+ (Xn)2 )
where X = Individual score and n = Sample size (number of scores or units)
The values are calculated from the available Corine land cover data following the selection of classes considered as natural or semi-natural areas. The classes proposed here are listed in Annex 1.
Calculation can be done by NUTS level 2 or 3, or by river basin, as well as by country and biogeographical zone. The analysis can be done separately for different classes of patch size (e.g. large, medium and small), in order to capture specific trends and avoid some bias mentioned previously. The analysis can also be performed as aggregated for all selected classes (e.g. those selected for the Green Background Index, see EEA, 2006) or separately by broad habitat types (proxy: land cover types).
Methodology for gap filling
No methodology for gap filling has been specified. Probably this info has been added together with indicator calculation.
No methodology references available.
EEA data references
- No datasets have been specified here.
Data sources in latest figures
No uncertainty has been specified
Data sets uncertainty
No uncertainty has been specified
MAIN DISADVANTAGES OF THE INDICATOR
Methodology: one remaining difficulty with the use of the quadratic mean is with the mere disappearance of small areas (smaller than the arithmetic average) which pushes the indicator up. This means that in the case of smaller areas disappearing completely, which should be interpreted as a loss of diversity in the landscape, it may be expected that the larger areas have increased in size and this will be then interpreted as a positive sign for biodiversity.This can be neglected when dealing with a large number of areas but it may be a problem with a small number of units and a high standard deviation. But even in that case, the distortion is less important with the quadratic mean than with the arithmetic average. A second remark is that this highlights again the multimodal character of the distribution:
averaging large areas with small areas is to some extent arbitrary and should be kept to the purpose of a high level indicator only.
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 are the best available at present to cover large areas of Europe in a harmonised way.
Biodiversity relevance: the indicator does not provide direct information on the impact of habitat fragmentation on the status of species populations.
ANALYSIS OF OPTIONS
The proposed indicator corresponds directly to the CBD proposed indicator for immediate testing under a similar name. The present indicator gives a broad brush picture of the integrity of ecosystems in Europe.
Complementary to this indicator, other measurements of ecosystem integrity should be proposed especially dealing with fragmentation / connectivity in relation to species. Indicators that focus on ecologically more relevant characteristics than 'mean habitat patch size have been developed and tested and are currently available. The JRC-Ispra work on change in spatial pattern of selected ecosystems (see http://forest.jrc.it/biodiversity/) produces indicators that give (per grid cell, nut level, etc.) the state and trends over the 1990-2000 time period of six pattern classes, namely of 'core habitat', 'edge', 'small forest fragments', 'perforation isolated patches', 'branches and short cuts' and/or 'corridors' for selected ecosystems (on the basis of CLC). One of these indicators may complement this indicator, as it has more potential to be linked with functional aspects that are meaningful for biodiversity/species.
Short term work
Work specified here requires to be completed within 1 year from now.
Long term work
Work specified here will require more than 1 year (from now) to be completed.
Work descriptionSUGGESTIONS FOR IMPROVEMENT Include data from the 2006 Corine land cover update when available. This would provide the 3 measurements in time proposed by CBD. Extension to pan-Europe. Develop and test complementary indicators on the changes in spatial patterns of selected ecosystems and on the changes in ecologically scaled fragmentation of habitats with regard to species. See above under 'Analysis of options'. To further improve the indicator, variance could be used together with mean values, as well as extreme values, and polygons could be grouped by size, to provide information on the data quality. Size distribution of the habitat fragments could also be investigated, in order to evaluate patch viability. Finally, a variable informing about coverage of semi-natural areas which have decreased by a certain percentage, for example 70 %, would show unequivocally an important biodiversity lost.
No resource needs have been specified
Deadline2099/01/01 00:00:00 GMT+1
Work descriptionCOSTS RELATED TO DEVELOPING, PRODUCING AND UPDATING THE INDICATOR (as available) The cost of producing this indicator is relatively low. The Corine databases are maintained by the EEA and publicly available on the internet. The data providers are part of the Corine land cover network, which is an active component of the Eionet (European Environment Information and Observation Network). National organisations are responsible for analysing and providing data on CLC. A main cost of producing this indicator lies with the EEA to provide resources for producing the baseline assessment and the updates of the indicator.
No resource needs have been specified
Deadline2099/01/01 00:00:00 GMT+1
Responsibility and ownership
EEA Contact InfoKatarzyna Biala
Frequency of updates
For references, please go to www.eea.europa.eu/soer or scan the QR code.
This briefing is part of the EEA's report The European Environment - State and Outlook 2015. The EEA is an official agency of the EU, tasked with providing information on Europe’s environment.
PDF generated on 19 Dec 2014, 10:56 PM