Landscape pattern analysis
One of the characteristic of complex systems is that they are governed by processes that act at different spatial and temporal scales, and it is in those cross-scale interactions where irreversible positive feedback processes can be triggered and where hierarchical levels constrain the function and structure of lower levels. For example, when landscape fragmentation reduces the connectivity between landscape fragments, dispersal limitations can result in metapopulation extinction (Alados et al. 2009). Grazing play an important role in connecting isolated vegetation fragments increasing ecosystem diversity (Pueyo et al. 2008). Reduction of vegetation fragments and isolation influenced negatively the long-range spatial distribution of the characteristic species; particularly species that have restricted dispersal are very sensitive to the effects of fragmentation.
| Aim of the method/technique |
To describe the landscape structure and its change.
|
| Scale – spatial and temporal |
Regional level
|
| Brief description |
Landscape structure can be characterized by the spatial configuration of landscape cover and its change throughout different periods. Standard landscape metrics have been developed such as: (i) number of patches; (ii) patch size (ha); (iii) patch connectivity. These indices can be used to asses patch fragmentation and loss, as well as isolation. The degree of landscape complexity and spatial self-organization can be estimated by the following indices: (i) patches edge; (ii) mean perimeter-to-area ratio; (iii) fractal dimension; (iv) long-range spatial autocorrelation. Scaling relations and fractal provide a powerful analytical framework that includes the structural complexity of landscape and can be used to detect “emergent patterns” of to predict irreversible transition shifts to LEDD.
|
| Data requirements |
Raster or vector vegetation map for the study area for different periods in time. All these indices can be calculated with the software (FRAGSTAT; FRACSYS 2009) free available on the internet.
|
| Main applications in grazing land regions |
Description of SES and impact assessment. To be used as response or explanatory variables to assess the relationship between SES components
|
| Strengths and weaknesses |
Strong method to describe SESs in different areas or different period of time and the influence of responses to LEDD on landscape structure.
|
