3.10 References
acterization process. The assessment area is usually readily defined by the specific objectives of the
study (e.g., Quigley and Arbelbide, 1997). However, the spatial scale for data collection and analysis may differ from the spatial scale of the assessment area, and the choice of a particular analysis
scale may influence the results. In the Interior Columbia Basin Ecosystem Management Project,
analyses of terrestrial and aquatic patterns were
conducted either basinwide or, using data from
restricted geographic locations, were conducted
within provinces, sections, or subsections (Quigley
and Arbelbide, 1997). For example, a vegetation
structural stage data layer, important for determining landscape trends (Hann et al., 1997), was extrapolated from sampled to unsampled areas at
coarse and midscales (Keane et al., 1996; O'Hara
et al., 1996), without an assessment of the impact
of the grain, extent, and spatial variability of the
data on the results. Another effort to extrapolate the
distribution of structural stages from an intensively
studied site (Cohen and Spies, 1992) to a larger area
and a broader range of ecological conditions
showed clear advantages as well as serious limitations of the approach (Cohen et al., 1995). Therefore, it is critical to know the impact of the spatial
scale of the data on characterization and analysis
of landscape patterns.
Weaknesses in the use of GIS, remotely sensed
data, and regional and landscape surveys, include
(1) the lack of testing of the impact ofthe grain and
extent of the data on the results, (2) the inability to
predict the relative magnitude of spatial variability
in different types of variables across the full range
of conditions found in an area, and (3) the lack of
standardized, repeatable methods for assessing the
representativeness of individual study landscapes
across multiple spatial scales and ecological conditions. Strengths include (1) the ability to take advantage of the remarkable advances in remotely
sensed data, GIS, and modeling, (2) often lower
costs than for intensive assessments of individual
landscapes, and (3) easier implementation than
ground-based surveys. This approach is included in
the landscape characterization pursued by EMAP
(O'Neill et al., 1994; Kapner et al., 1995).
3.9 Conclusions
Ecosystems exist at multiple scales, from global to
local. They are defined by associations of biotic
and abiotic components and the interactions among
them. Each component has multiple attributes, but
not all components are equally important in ecosys49
tem characterization at all spatial scales. The challenges of ecosystem characterization include selecting the attributes and properties that best define
ecosystems at all spatial scales, delineating boundaries between spatial representations of ecological
units, defining and quantifying ecosystem properties, and extrapolating results to different geographic locations and across spatial scales.
The following principles should be followed during the ecosystem characterization phase of an ecological assessment.
1. Ecological classifications and mapping units
must be defined according to precisely specified
assessment goals.
2. Ecosystem patterns must be understood in terms
of the processes and constraints generating them
across their natural range of spatial and temporal scales.
3. Ecosystem characterization is influenced by the
grain and extent of remotely sensed and groundbased data. The impact of data collected on the
delineation of ecosystems and the range of spatial scales and geographic locations at which
these data can be used should be evaluated.
4. The utility of ecosystem characterization depends on the formulation of testable hypotheses
about ecological relations and on validating the
extrapolation of results across geographic areas
and spatial scales.
5. Ecosystem characterization usually is concerned
primarily with spatial variability. Temporal
variability and its interaction with spatial variability should also be investigated.
The following reviews and syntheses provide
good sourceS of information and references on specific aspects of ecosystem characterization and on
worldwide applications under different ecological,
political, and socioeconomic conditions: Jensen
and Bourgeron (1994), Klijn (1994), Sims et al.
(1996), and Grossman et al. (1999).
3.10 References
Allen, T. F. H.; Starr, T. B. 1982. Hierarchy: perspectives for ecological complexity. Chicago: University of
Chicago Press.
Allen, T. F. H.; Hoekstra, T. W.; O'Neill, R. V. 1984. Interlevel relations in ecological research and management: some working principles from hierarchy theory.
RM-GTR-llO. Fort Collins, CO: U.S. Dept. Agric.,
For. Serv., Rocky Mountain For. Range Exp. Sta.
Amoros, C.; Rostan, J. C.; Pautou, G.; Bravard, J. P.
1987. The reversible process concept applied to the
acterization process. The assessment area is usually readily defined by the specific objectives of the
study (e.g., Quigley and Arbelbide, 1997). However, the spatial scale for data collection and analysis may differ from the spatial scale of the assessment area, and the choice of a particular analysis
scale may influence the results. In the Interior Columbia Basin Ecosystem Management Project,
analyses of terrestrial and aquatic patterns were
conducted either basinwide or, using data from
restricted geographic locations, were conducted
within provinces, sections, or subsections (Quigley
and Arbelbide, 1997). For example, a vegetation
structural stage data layer, important for determining landscape trends (Hann et al., 1997), was extrapolated from sampled to unsampled areas at
coarse and midscales (Keane et al., 1996; O'Hara
et al., 1996), without an assessment of the impact
of the grain, extent, and spatial variability of the
data on the results. Another effort to extrapolate the
distribution of structural stages from an intensively
studied site (Cohen and Spies, 1992) to a larger area
and a broader range of ecological conditions
showed clear advantages as well as serious limitations of the approach (Cohen et al., 1995). Therefore, it is critical to know the impact of the spatial
scale of the data on characterization and analysis
of landscape patterns.
Weaknesses in the use of GIS, remotely sensed
data, and regional and landscape surveys, include
(1) the lack of testing of the impact ofthe grain and
extent of the data on the results, (2) the inability to
predict the relative magnitude of spatial variability
in different types of variables across the full range
of conditions found in an area, and (3) the lack of
standardized, repeatable methods for assessing the
representativeness of individual study landscapes
across multiple spatial scales and ecological conditions. Strengths include (1) the ability to take advantage of the remarkable advances in remotely
sensed data, GIS, and modeling, (2) often lower
costs than for intensive assessments of individual
landscapes, and (3) easier implementation than
ground-based surveys. This approach is included in
the landscape characterization pursued by EMAP
(O'Neill et al., 1994; Kapner et al., 1995).
3.9 Conclusions
Ecosystems exist at multiple scales, from global to
local. They are defined by associations of biotic
and abiotic components and the interactions among
them. Each component has multiple attributes, but
not all components are equally important in ecosys49
tem characterization at all spatial scales. The challenges of ecosystem characterization include selecting the attributes and properties that best define
ecosystems at all spatial scales, delineating boundaries between spatial representations of ecological
units, defining and quantifying ecosystem properties, and extrapolating results to different geographic locations and across spatial scales.
The following principles should be followed during the ecosystem characterization phase of an ecological assessment.
1. Ecological classifications and mapping units
must be defined according to precisely specified
assessment goals.
2. Ecosystem patterns must be understood in terms
of the processes and constraints generating them
across their natural range of spatial and temporal scales.
3. Ecosystem characterization is influenced by the
grain and extent of remotely sensed and groundbased data. The impact of data collected on the
delineation of ecosystems and the range of spatial scales and geographic locations at which
these data can be used should be evaluated.
4. The utility of ecosystem characterization depends on the formulation of testable hypotheses
about ecological relations and on validating the
extrapolation of results across geographic areas
and spatial scales.
5. Ecosystem characterization usually is concerned
primarily with spatial variability. Temporal
variability and its interaction with spatial variability should also be investigated.
The following reviews and syntheses provide
good sourceS of information and references on specific aspects of ecosystem characterization and on
worldwide applications under different ecological,
political, and socioeconomic conditions: Jensen
and Bourgeron (1994), Klijn (1994), Sims et al.
(1996), and Grossman et al. (1999).
3.10 References
Allen, T. F. H.; Starr, T. B. 1982. Hierarchy: perspectives for ecological complexity. Chicago: University of
Chicago Press.
Allen, T. F. H.; Hoekstra, T. W.; O'Neill, R. V. 1984. Interlevel relations in ecological research and management: some working principles from hierarchy theory.
RM-GTR-llO. Fort Collins, CO: U.S. Dept. Agric.,
For. Serv., Rocky Mountain For. Range Exp. Sta.
Amoros, C.; Rostan, J. C.; Pautou, G.; Bravard, J. P.
1987. The reversible process concept applied to the