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SCALETOOL IntroductionDriversBiodiversityPolicies and managementConnectivity and protected areas
Drivers of change and their indicators Scaling of fragmentation Microclimate

Scaling of fragmentation - Maps

Anna V. Scott, Veiko Lehsten, Konstantinos Touloumis, Joseph Tzanopoulos and Simon G. Potts


Habitat availability and connectivity are imperative structural elements in the maintenance of biodiversity, having a major impact on the overall resilience of populations and communities. Habitat loss and fragmentation usually occur together, combining to result in a decrease in the size and connectivity of habitats, and an overall drop in biodiversity (Collinge, 1996). Increases in fragmentation are thought to have a significant effect on species losses (Saunders, Hobbs, & Margules, 1991), whilst increasing the density and connectivity of habitats can increase the numbers of some declining species (Davies, Wilson, Brereton, & Thomas, 2005).

By examining fragmentation across different spatial and temporal scales the risks to biodiversity can be highlighted. By observing temporal trends policy makers and practitioners are better able to understand the way in which their sites, networks, regions and countries might be changing, and highlight areas, habitats and species that are at greatest risk. Matching spatial and temporal scales to species and habitats through scale aware policies and management strategies can improve the effectiveness of nature conservation in the future. Regions that are susceptible to further fragmentation and potential biodiversity losses can be targeted for restoration or conservation management.


Historic CORINE Land Cover Maps from the European Environment Agency provide a solid information base on which to examine changes in the structure of the landscape and highlight the most vulnerable regions. Our work focused on the changes in abundance and connectivity for functional Landcover types between 1990 and 2006. 'Landcover types' were used as a proxy for 'habitats' since complete data on habitats across the EU is not yet available. Some of the land covers were grouped to provide a better representation of fragmentation. The grouped categories used are shown in Table 1.

Table 1: Corine Land Cover categories used for the GUIDOS-MSPA analysis

Functional Landcover categoryCORINE Landcover Categories
Artificial Surfaces CLC 1-11
Agricultural CLC 12-18
Broad-leaved forest CLC 23
Coniferous forest CLC 24
Mixed forest CLC 25
Natural Grasslands CLC 26
Moors and Heathland CLC 27
Open spaces with little or no vegetation CLC30-34
Sclerophyllous CLC28
Transitional wood/shrub CLC29
Wetlands CLC 35-39

The abundance of landcover types was calculated directly from the CORINE dataset. Fragmentation of the CORINE landcovers was examined using an established method of analysis: a Morphological Spatial Pattern Analysis (MSPA) performed by GUIDOS (Soille & Vogt, 2009). MSPA-GUIDOS segments the land cover data into mutually exclusive feature classes (see Table 2) based on their geometry and connectivity. 'Foreground' is considered the area covered by the respective landcover, whilst 'background' is all other land covers. 'Edges' were defined at 100m, with 'core' being un-isolated areas inside of the 100m edge. By using GUIDOS-MSPA an assessment can be made about how fragmented the landscape is based on how many 'islets', 'branches' and 'core' areas there are.

Table 2: Description of Morphological Spatial Pattern Analysis (MSPA) classes

MSPA ClassDescription
Core Interior foreground area excluding foreground perimeter
Islet Disjoint foreground object and too small to contain core
Loop Connected at more than one end to the same core area
Bridge Connected at more than one end to different core areas
PerforationInternal foreground, object perimete
EdgeExternal foreground, object perimeter
BranchConnected at one end to Edge, Perforation, Bridge or Loop

Scaling of fragmentation across spatial and temporal scales is explored in several examples in the attached maps. All results were amalgamated to show changes in habitat, core, islet and bridge landscape structures between 1990 and 2006. This was done at the administrative scale called the Nomenclature of Territorial Units for Statistics (NUTS); NUTS 3 is equivalent to a Local Authority in the UK, and NUTS 0 is equivalent to a Country scale. Changes in habitat are displayed as % change in habitat per NUTS3 region; whilst changes in core, islet and bridge are displayed as % change of the landscape feature (e.g core) within the habitat in question.


There are four main types of landscape change highlighted by the Guidos-MSPA analysis, these are:
  1. Increased cover and connectivity - This is characterised by increased Landcover, increased proportion of bridge structures and decreased islets.
  2. Colonisation - This is characterised by increased Landcover and an increased proportion of islet structures.
  3. Fragmentation and isolation - This is characterised by a decrease or maintenance of Landcover levels, with increasing proportion of islet structures.
  4. Perforation - This is characterised by a decrease in Landcover, a decrease in core structures and an increase in bridge structures.
These four changes are seen in different regions and different habitat types across Europe, as presented in the attached maps.

The ability to predict the habitats that are most vulnerable to loss and fragmentation can help us to target resources for management and protection. Practitioners and policy makers could use the examples given here within their own countries, regions and sites, to assess how historic changes in their landscapes might impact on protected sites, as well as social, economic and environmental sustainability at all scales. Local land managers and practitioners can often gain most information from examining site specific patterns of fragmentation over time. However, regional, national and international scales should also be fully taken into account during conservation planning because the context and connectivity with the wider landscape has a significant impact on individual sites, networks and species.


Landscape changes, including detrimental habitat losses and fragmentation, have been occurring across Europe for many years (Feranec, Jaffrain, Soukup, & Hazeu, 2010), and predictions suggest that many habitats are at further risk of degradation in the coming years. This has serious implications for biodiversity, which suffers significantly with habitat loss and fragmentation. Increasing and improving guidance on green infrastructure strategies and spatial planning across Europe may encourage a greater quantity and quality of such projects. Well implemented spatial planning and green infrastructure strategies, which focus on protected and/or native keystone species and annex 1 habitats may help to limit further fragmentation of natural habitats. More information and resources are available within the SCALESTOOL, as well as in SCALESBOOK.


Collinge, S. K. (1996). Ecological consequences of habitat fragmentation: implications for landscape architecture and planning. Landscape and Urban Planning, 36(1), 59-77.

Davies, Z. G., Wilson, R. J., Brereton, T. M., & Thomas, C. D. (2005). The re-expansion and improving status of the silver-spotted skipper butterfly (Hesperia comma) in Britain: a metapopulation success story. Biological Conservation, 124(2), 189-198.

Feranec, J., Jaffrain, G., Soukup, T., & Hazeu, G. (2010). Determining changes and flows in European landscapes 1990-2000 using CORINE land cover data. Applied Geography, 30(1), 19-35.

Saunders, D. A., Hobbs, R. J., & Margules, C. R. (1991). Biological Consequences of Ecosystem Fragmentation: A Review. Conservation Biology, 5(1), 18-32.

Scott, A.V., Touloumis, K., Lehsten, V., Tzanopoulos, J., Potts, S.G. (2014) Fragmentation across spatial scales, pp. 41-46. In: Henle, K., Potts, S.G., Kunin, W.E., Matsinos, Y.G., Similä, J., Pantis, J.D., Grobelnik, V., Penev, L., Settele, S. (eds.): Scaling in Ecology and Biodiversity Conservation. Pensoft Publishers, Sofia.

Soille, P., & Vogt, P. (2009). Morphological segmentation of binary patterns. Pattern Recognition Letters, 30(4), 456-459.


Vogt, P (2014). Software for morphological Spatial Pattern Analysis (MSPA) performed by GUIDOS. Accessed 05/08/2014.
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