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Why Quantify Landscape Pattern?

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Presentation on theme: "Why Quantify Landscape Pattern?"— Presentation transcript:

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2 Why Quantify Landscape Pattern?
Comparison (space & time) Study areas Landscapes Inference Agents of pattern formation Link to ecological processes

3 Programs for Quantifying Landscape Pattern
FRAGSTATS Patch Analyst

4 Quantifying Landscape Pattern
Just because one can measure it, doesn’t mean one should Does the metric make sense?...biologically relevant? Avoid correlated metrics Cover the bases (comp., config., conn.)

5 Landscape Metrics - Considerations
Selecting Metrics…… Subset of metrics needed that: i) explain (capture) variability in pattern ii) minimize redundancy (i.e., correlation among metrics = multicollinearity) O’Neill et al. (1988) Indices of landscape pattern. Landscape Ecology 1: i) eastern U.S. landscapes differentiated using dominance contagion fractal dimension

6 Landscape Metrics - Considerations
Selecting Metrics…… Use species-based metrics Use Principal Components Analysis (PCA)? Use Ecologically Scaled Landscape Indices (ESLI; landscape indices, scale of species, and relationship to process)

7 Quantifying Pattern: Corridors
Internal: Width Contrast Env. Gradient External: Length Curvilinearity Alignment Connectivity (gaps)

8 Quantifying Pattern: Patches
Levels: Patch-level Metrics for indiv. patches Class-level Metrics for all patches of given type or class Zonal or Regional Metrics pooled over 1 or more classes within subregion of landscape Landscape-level Metrics pooled over all patch classes over entire extent

9 Quantifying Pattern: Patches
Composition: Variety & abundance of elements Configuration: Spatial characteristics & dist’n of elements

10 Quantifying Pattern: Patches
Composition: Mean (or mode, median, min, max) Internal heterogeneity (var, range) Spatial Characters: Area (incl. core areas) Perimeter Shape

11 Quantifying Pattern: Landscapes (patch based)
Composition: Number of patch type Patch richness Proportion of each type Proportion of landscape Diversity Shannon’s Diversity Index Simpson’s Divesity Index Evenness Shannon’s Evenness Index Simpson’s Index

12 Quantifying Pattern: Patches
Configuration: Patch Size & Density Mean patch size Patch density Patch size variation Largest patch index

13 Quantifying Pattern: Patches
Configuration: Shape Complexity Shape Index Fractal Dimension Fractals = measure of shape complexity (also amount of edge) Fractal dimension (d) ranges from 1.0 (simple shapes) to 2.0 (more complex shapes) ln(A)/ln(P), where A = area, P = perimeter

14 Quantifying Pattern: Patches
Configuration: Core Area (interior habitat) # core areas Core area density Core area variation Mean core area Core area index

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16 Quantifying Pattern: Patches, Zonal
Configuration: Isolation / Proximity Proximity index Mean nearest neighbor distance

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18 Proximity Index (PXi) = measure of relative isolation of patches; high (absolute) values indicate relative connectedness of patches


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