Landscape Pattern Analysis — Characterizing Landscape Patterns – Conceptual Foundation

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Landscape Pattern Analysis — Characterizing Landscape Patterns – Conceptual Foundation

Characterizing landscape patterns ? conceptual foundation

Instructor: K. McGarigal

Assigned Reading: Turner et al. 2001 (Chapter 5); Gustafson (1998)

Objective: Provide a basic understanding of how to characterize and quantify landscape pattern.
Highlight importance of landscape definition in landscape pattern analysis and the difference
between measured and functional heterogeneity.

Topics covered:

1. Pattern analysis in context
2. The importance of scale
3. Scope of analysis
4. Levels of heterogeneity
5. Components of landscape structure
6. Structural versus functional metrics
7. Limitations in the use and interpretation of metrics
(Sticky Note comment Nate
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8.1

1. Pattern Analysis in Context
Landscape ecology, if not ecology in general, is largely founded on the notion that
environmental patterns strongly influence ecological processes. The habitats in which organisms
live, for example, are spatially structured at a number of scales, and these patterns interact with
organism perception and behavior to drive the higher level processes of population dynamics and
community structure (Johnson et al. 1992). Anthropogenic activities (e.g. development, timber
harvest) can disrupt the structural integrity of landscapes and is expected to impede, or in some
cases facilitate, ecological flows (e.g., movement of organisms) across the landscape (Gardner et
al. 1993). A disruption in landscape patterns may therefore compromise its functional integrity
by interfering with critical ecological processes necessary for population persistence and the
maintenance of biodiversity and ecosystem function (With 2000). Consequently, much emphasis
has been placed on developing methods to quantify landscape patterns, which is considered
prerequisite to the study of pattern-process relationships (e.g., O'Neill et al. 1988, Turner 1990,
Turner and Gardner 1991, Baker and Cai 1992, McGarigal and Marks 1995). This has resulted in
the development of hundreds of indices of landscape patterns. Unfortunately, according to
Gustafson (1998), Othe distinction between what can be mapped and measured and the patterns
that are ecologically relevant to the phenomenon under investigation or management is
sometimes blurred.O

8.2

2. Importance of Scale
There are at least two different aspects of scale regarding categorical map patterns that have
important implications for the choice and interpretation of individual landscape metrics.

(1) Spatial Scale.?It is important to recognize the practical implications of the choice of grain
and extent for a particular application. Many of the landscape metrics are particularly sensitive to
grain. Metrics involving edge or perimeter will be affected; edge lengths will be biased upwards
in proportion to the grain size?larger grains result in greater bias. Edge lengths can vary by as
much as 25-50% over vector calculations depending on grain size. Metrics based on cell
adjacency information such as the contagion index of Li and Reynolds (1993) will be affected as
well, because grain size effects the proportional distribution of adjacencies. In this case, as
resolution is increased (grain size reduced), the proportional abundance of like adjacencies (cells
of the same class) increases, and the measured contagion increases. Similarly, the measured
landscape patterns will often vary with extent. Intuitively this makes sense, because as the
landscape extent increases, new patch types may be encountered and habitat configurations may
change in response to underlying environmental or land use gradients.
8.3

The ratio of grain to extent for a particular analysis warrants special consideration. If the ratio is
very small (i.e., a coarse-grained map), the boundary of the landscape can have a profound
influence on the value of certain metrics. Landscape metrics are computed solely from patches
contained within the landscape boundary. If the landscape extent is small relative to the scale of
the phenomenon under consideration and the landscape is an OopenO system relative to that
organism or process, then any metric will have questionable meaning. Metrics based on nearest
neighbor distance or employing a search radius can be particularly misleading. In general,
boundary effects increase as the landscape extent decreases relative to the patchiness or
heterogeneity of the landscape. The key point is that some landscape metrics are likely to be very
sensitive to this ratio (e.g., those based on nearest-neighbor distances such as the mean proximity
index.

8.4

(2) Thematic Resolution.?Thematic resolution has dramatic influences on the types of
associations that can be made and on the nature of the patterns that can be mapped from that
variable. Thematic resolution typically has a pronounced influence on both the composition and
configuration of the map and thus directly affects all quantitative measures of landscape pattern.
At the simplest level, for example, thematic resolution determines the number of classes or patch
types represented and thus affects all composition metrics such as the measures of landscape
diversity.
8.5

3. Scope of Analysis
The scope of analysis pertains to the scale and or focus of the investigation. There are three
levels of analysis that represent fundamentally different conceptualizations of landscape patterns
and that have important implications for the choice and interpretation of individual landscape
metrics and the form of the results.

(1) Focal patch analysis.?Under the patch mosaic model of landscape structure the focus of the
investigation may be on individual patches (instead of the aggregate properties of patches);
specifically, the spatial character and/or context of individual focal patches. This is a Opatch-
centricO perspective on landscape patterns in which the scope of analysis is restricted to the
characterization of individual focal patches. In this case, each focal patch is characterized
according to one or more patch-level metrics (see below). The results of a focal patch analysis is
typically given in the form of a table, where each row represents a separate patch and each
column represents a separate patch metric.
(2) Local landscape structure.?In many applications it may be appropriate to assume that
organisms experience landscape structure as local pattern gradients that vary through space
according to the perception and influence distance of the particular organism or process. Thus,
instead of analyzing global landscape patterns, e.g., as measured by conventional landscape
metrics for the entire landscape (see below), we would be better served by quantifying the local
8.6

landscape pattern across space as it may be experienced by the organism of interest, given their
perceptual abilities. The local landscape structure can be examined by passing a Omoving
windowO of fixed or