Scale

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• Scale
• What is scale?
• Why is scale important in landscape ecology?
• What are the correct scales to use?
• Scaling
• UP bottom-up approach
• Down top-down approach
• A few rules in scaling
• How to study scalar structure?
• Reading Chapter 2

Common usage of scale
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Definition
Scale is the spatial or temporal domain of an
object or process. In general, the scales of
structures/patterns we see and scales of the
processes that create or maintain them are
positively correlated but this is not always the
case. Scale is characterized by both grain (i.e.,
resolution) and extent Grain smallest unit
of measure about which one has information
Extent Total area (or duration of time) over
which we are considering a phenomenon Grain and
extent set the scale and limit which entities and
cycles may be observed. If we don't see
something, it is merely due to inappropriate
measurement (i.e., poorly chosen grain and
extent). We want to bracket the process or
structure of interest.
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Schematic of two components of spatial scales
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Why is scale important in landscape ecology?
Nature of landscape ecology Nature and
landscapes are organized hierarchically. All
natural features are scale dependent Our
ability to develop theories of pattern-process
relationships will be dependent on understanding
scales of description and scales at which
relationships naturally occur Incorrect
coupling between the scale of a pattern and the
process that creates it limits the predictability
of future ecological system states which, in
turn, inhibits development of realistic land
management plans (a purely applied reason)
There are also some sampling and statistical
reasons (e.g., want to sample at a scale that
ensures independent replicates)
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Scale and Processes
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Two predominant views on choosing scales   A few
scales drive ecological functions and,
therefore, we should choose the right scales
(Holling 1991) Example on disturbance regimes of
different scales Natural disturbance regime -
the long-term pattern of frequency, intensity,
spatial extent, internal heterogeneity of
disturbances) A boreal forest has large,
intense, stand-initiating disturbances resulting
in a coarse-grained pattern of relatively young,
even-aged forest whereas Wetter, temperate
rainforests have smaller, less intense
disturbances that kill trees in patches of a
single to a few trees resulting in a
finer-grained mosaic of uneven-aged
patches   Multiple scale analysis is needed
(Levin 1992) The relative importance of
parameters controlling ecological processes
varies with scale, e.g., locally, fire initiation
depends on topographic position, fuel load butat
large spatial scales, frequency and extent of
fire are determined by longer-term weather and
climate   Cumulative effects of stand-level
(i.e., finer scale) management are expressed at
the landscape level. e.g., small patch clearcuts
remove a trivial amount of habitat for
latesuccessional species, but cumulatively, the
population may be threatened by fragmentation of
the watershed   Some local scale activities can
have large-scale impacts. e.g., downstream
effects of small landslide upstream.  
landscape may exhibit critical thresholds at
which ecological processes show qualitative
changes. e.g., disturbance spread controlled by
frequency when habitat area is below threshold
but by intensity when above threshold
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 Rationale for multiple scale approach (cont.)
Multiple life stages or scales of structure may
be required by an organism. e.g., the northern
spotted owl example   Small scale processes can
interact to create bottom-up controls of
landscape-level patterns and processes. e.g.,
fine-scale local edaphic factors result in the
distribution of common stand types and less
common hemlock-hardwood but at the coarse scale,
nearly pure hardwood patches are associated with
disturbances to the matrix (Pastor and Broschart
1990).   large-scale processes can exert
top-down control creating context for finer scale
dynamics. e.g., infrequent, extreme events
(Yellowstone fires) will influence species
distribution and composition for ages   The
bottom line is that the scale of study will
affect conclusions about pattern-process
relates.   Whichever view one espouses, all agree
that to understand ecological phenomena, we must
study them at the inherent scales (or multiple
scales) at which they occur
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Up Scaling Bottom-up approach Begins with
individuals or entity based measurement and adds
appropriate constraints to explain the result
phenomena at higher levels. The objective is to
use information that is available at finer scales
to predict at larger scales. The bottom-up
approach is necessary because of the suite of
multiple scales and understanding of mechanism
causing larger scale phenomena. We must to learn
how to aggregate and simplify, retaining
essential information without getting bogged down
in unnecessary details. Examples Stand
dynamics model (Urban et al.) or early
succession Prediction of carbon storage at
global scales Predict deer population of a
region (e.g.,MW) Species richness and
diversity of an landscape
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Down Scaling Top-Down approach Use the concept
of constraint to predict phenomena at finer
scales. The objective is to identify the
constrains that are important at each
level. Examples Ecological Land Types in
Upper Michigan Global climate change GCM Þ
Regionalized model Þ Local Weather Condition Þ
forest microclimate World's Vegetation
Landscape dynamics Books in libraries
subdirectories on your computer
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A Few Rules in Scaling Across scales, we can
learn how information is translated. We have to
determine what information is preserved and lost
as one moves from one scale to another.
Predictions based on either approach need clear
identification of parameters (i.e., independent
variables) at different scales. This is because
any processes important at one scale are
frequently not important (or predictive) at other
scales, and different information is often lost
as spatial data are considered at coarse scale of
resolution. Identify an array of scales at
which the study processes can be detected. The
key is study an ecological phenomenon across all
these scales rather than choose a "correct"
scale. In another word, our effort is to detect
patterns occurring at multiple scales.
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How do we study scalar structure?
Quantitative methods such as geostatistics,
wavelet analysis, spectrum analysis, fractal
analysis, and computer simulations explore or
identify scales of pattern (and process).
Leaf viewed from afar
Leaf viewed microscopically Drawings by (Kandis
Elliot)
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Wu Li 2005
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Scale and Scaling in Landscape Ecology