why quantify landscape pattern?
DESCRIPTION
Why Quantify Landscape Pattern?. Comparison (space & time) Study areas Landscapes Inference Agents of pattern formation Link to ecological processes. Programs for Quantifying Landscape Pattern. FRAGSTATS - PowerPoint PPT PresentationTRANSCRIPT
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Why Quantify Landscape Pattern?
• Comparison (space & time)– Study areas– Landscapes
• Inference– Agents of pattern
formation– Link to ecological
processes
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Programs for Quantifying Landscape Pattern
• FRAGSTATS– http://www.umass.edu/
landeco/research/fragstats/documents/Metrics/Metrics%20TOC.htm
• Patch Analyst– http://flash.lakeheadu.ca/
~rrempel/patch/
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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.)
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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 1:153-162
• i) eastern U.S. landscapes differentiated using– dominance– contagion– fractal dimension
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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)
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Quantifying Pattern: Corridors
• Internal:– Width
– Contrast
– Env. Gradient
• External:– Length
– Curvilinearity
– Alignment
– Env. Gradient
– Connectivity (gaps)
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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
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Quantifying Pattern: Patches
• Composition:– Variety & abundance
of elements
• Configuration:– Spatial characteristics
& dist’n of elements
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Quantifying Pattern: Patches
• Composition:– Mean (or mode,
median, min, max)
– Internal heterogeneity (var, range)
• Spatial Characters:– Area (incl. core areas)
– Perimeter
– Shape
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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
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Quantifying Pattern: Patches• Configuration:
– Patch Size & Density
• Mean patch size
• Patch density
• Patch size variation
• Largest patch index
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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
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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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Quantifying Pattern: Patches, Zonal
• Configuration:
– Isolation / Proximity
• Proximity index
• Mean nearest neighbor distance
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• Proximity Index (PXi) = measure of relative isolation of patches; high (absolute) values indicate relative connectedness of patches