Emergence of Landscape Ecology

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Emergence of Landscape Ecology
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• Equilibrium View
• Constant species composition
• Disturbance succession subordinate factors
• Ecosystems self-contained
• Internal dynamics shape trajectory
• No need to look outside boundaries to understand
  ecosystem dynamics

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Emergence of Landscape Ecology

• Dynamic View
• Disturbance ecosystem response key factors
• Disturbance counter equilibrium
• Ecosystems NOT self-contained
• Multiple scales of processes, outside inside
• Essential to examine spatial temporal context

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Scale

• Whats the big deal?

• Seminal pubs
• Allen Starr (1982) Hierarchy perspectives
  for ecological complexity
• Delcourt et al. (1983) Quaternary Science
  Review 1153-175
• ONeill et al. (1986) A hierarchical concept of
  ecosystems

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Ecological Scaling Scale Pattern

• Acts in the ecological theatre (Hutchinson 1965)
  are played out across various scales of space
  time
• To understand these dramas, one must select the
  appropriate scale

Speciation Extinction
Species Migrations
Secondary Succession
Windthrow
Fire
Treefalls
Recruitment
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Ecological Scaling Scale Pattern

• Different patterns emerge, depending on the scale
  of investigation

Regional Scale (thousands of ha)
Local Scale (4 ha plots)
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Ecological Scaling Components of Scale

• Grain minimum resolution of the data
• Cell size (raster data)
• Min. polygon size (vector data)

• Extent scope or domain of the data
• Size of landscape or study area

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Ecological Scale

• Scale characterized by
• grain smallest spatial resolution of data
• e.g., grid cell size, pixel size, quadrat size
  (resolution)
• Fine Coarse

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Ecological Scale

• Scale characterized by
• extent size of overall study area (scope or
  domain of the data)
• Small Large

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Ecological Scaling Components of Scale

• Minimum Patch Size min. size considered gt
  resolution of data (defined by grain)
• Size of landscape or study area

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Ecological Scaling Definitions

• Ecological scale cartographic scale are exactly
  opposite
• Ecological scale size (extent) of landscape
• Cartographic scale ratio of map to real distance

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Scale in Ecology Geography

• ecological vs. cartographic scale

Ecology Geography
Small (Fine) Fine resolution Small Extent Coarse resolution Large Extent
Large (Broad) Coarse resolution Large extent Fine resolution Small extent
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Scale in Ecology Geography

• ecological vs. cartographic scale
• e.g., map scale
• 124,000 vs. 13,000
• fine vs. coarse
• large vs. small extent

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124,000
1200,000
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Ecological Scaling Components of Scale

• Grain and extent are correlated
• Information content often correlated with grain
• Grain and extent set lower and upper limits of
  resolution in the data, respectively.

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Ecological Scaling Components of Scale

• From an organism-centered perspective, grain and
  extent may be defined as the degree of acuity of
  a stationary organism with respect to short- and
  long-range perceptual ability

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Ecological Scaling Components of Scale

• Grain finest component of environment that can
  be differentiated up close
• Extent range at which a relevant object can be
  distinguished from a fixed vantage point

Extent
Grain
Coarse
Fine
Scale
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Ecological Scaling Components of Scale

• From an anthropocentric perspective, grain and
  extent may be defined on the basis of management
  objectives
• Grain finest unit of mgt (e.g., stand)
• Extent total area under management (e.g.,
  forest)

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Ecological Scaling Components of Scale

• In practice, grain and extent often dictated by
  scale of available spatial data (e.g., imagery),
  logistics, or technical capabilities

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Ecological Scaling Components of Scale

• Critical that grain and extent be defined for a
  study and represent ecological phenomenon or
  organism studied.
• Otherwise, patterns detected have little meaning
  and/or conclusions could be wrong

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Scale Jargon

• scale vs. level of organization

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Ecological Scaling Implications of Scale

• As one changes scale, statistical relationships
  may change
• Magnitude or sign of correlations
• Importance of variables
• Variance relationships

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Implications of Changes in Scale

• Processes and/or patterns may change
• Hierarchy theory structural understanding of
  scale-dependent phenomena

Example Abundance of forest insects sampled at
different distance Intervals in leaf litter,
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Implications of Changes in Scale
Insects sampled at 10-m intervals for 100 m
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Implications of Changes in Scale
Insects sampled at 2000-m intervals for 20,000 m
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Identifying the Right Scale(s)

• No clear algorithm for defining
• Autocorrelation Independence

• Life history correlates
• Dependent on objectives and organisms

• Multiscale analysis!
• e.g., Australian leadbeaters possum

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Multiscale Analysis

• Species-specific perception of landscape features
  scale-dependent
• e.g., mesopredators in Indiana

• Modeling species distributions in fragmented
  landscapes

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Hierarchy Theory

• Lower levels provide mechanistic explanations
• Higher levels provide constraints

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Scale Hierarchy Theory

• Hierarchical structure of systems helps us
  explain phenomena
• Why? next lower level
• So What? next higher level

• minimum 3 hierarchical levels needed

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Constraints (significance)
Level of Focus (level of interest)
Components (explanation)
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Constraints
Community
Why are long-tailed weasel populations declining
in fragmented landscapes?
Population
Components
Individual
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Constraints
Community
Why are long-tailed weasel populations declining
in fragmented landscapes?
Population
Small body size mobility
Individual
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Predators Competitors Prey distn
Community
Why are long-tailed weasel populations declining
in fragmented landscapes?
Population
Components
Individual
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Scale Hierarchy Theory

• Change scale
• influential variables might not change, but
• shift in relative importance likely

Example Predicting rate of decomposition of
plant matter Local scale lignin content
environ. variability Global scale temperature
precip.