Transcript Document
Scale
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What is scale?
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Why is scale important in landscape ecology?
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What are the correct scales to use?
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Scaling: UP: bottom-up approach Down: top-down approach
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A few rules in scaling
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How to study scalar structure?
Reading : Chapter 2
Common usage of ‘scale’
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.
Schematic of two components of spatial scales
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);
Scale and Processes
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
Natural disturbance regime
of different scales =- 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 but at 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 late successional 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
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
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
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 Regionalized model Local Weather Condition forest microclimate World's Vegetation Landscape dynamics Books in libraries & subdirectories on your computer
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.
Scales of Disturbance
(Delcourt et al. 1983)
How do we study scalar structure?
Q
uantitative 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)
Wu & Li 2005