22.7 References
taxonomy (USDA, 1993), and distributions of 38
fish species (Lee et al., 1997). Soil taxonomy, although derived from an independent database, was
not assessed for the USFS ELC, because soil was
used as a criterion in defining the levels of this
ELC.1ne performance of the ELCs varied with the
pattern of interest and also in some cases with level.
For example, coarse-cover-type classes were most
strongly associated with the direct-variable ELC at
the province level; however, at the section and subsection group levels, the strongest association was
with the indirect-variable ELC. The other two
ELCs did not perform as well at any level. For the
fine-cover-type classification, the direct-variable
ELC performed best at all three levels. For covertype diversity, the direct-variable ELC had the
strongest association at the province level, but the
USFS ELC performed best at the section and subsection group levels. This analysis suggests caution
when using an ELC for a purpose other than that
for which it was designed.
22.6 Conclusion
ELCs are essential to EAs at all assessment scales.
They are used for many different components of an
EA, including stratifying areas for different purposes, serving as input to models, and evaluating
ecological conditions. Four important recommendations in the definition or use of ELCs are the following:
1. Construct ELCs with appropriate variables that
address the objectives of an EA.
2. Test hypothesized relationships between variables used to construct ELCs and the patterns
and processes of interest.
3. Evaluate the performance of ELCs with respect
to the objectives.
4. Evaluate the performance of ELCs before using
them for purposes other than those for which
they were designed and tested.
In practice, it is likely that arbitrary decisions
may be made about which variables to use in the
design of an ELC or which existing ELC to use.
Therefore, emphasis should be placed on the validation of the ELC (recommendations 3 and 4).
Suggestions for future research in the design and
implementation of ELCs for EAs include the following:
1. Quantifying the delineation of ELUs (e.g., Hargrove and Hoffman, 1999).
2. Developing additional techniques to evaluate
ELCs for specific applications.
333
3. Developing methods to more effectively characterize variability within ELUs.
22.7 References
Albert, D. A. 1995. Regional landscape ecosystems of
Michigan, Minnesota, and Wisconsin: a working map
and classification. Fourth revision. GTR-NC-178. St.
Paul, MN: U.S. Dept. Agric., For. Serv., North Central For. Exp. Sta.
Anderson, J. R; Hardy, E. E.; Roach, J. T. 1976. Land
use and land cover classification system for use with
remote sensing data. Geological Survey Professional
Pap. 964 (a revision of the land use classification system as presented in U.S. Geological Circular 671).
Washington, DC: U.S. Govt. Printing Off.
Arno, S. F.; Simmermann, D. G.; Keane, R. E. 1986.
Characterizing succession within a forest habitat
type-an approach designed for resource managers.
Research Note INT-357. Ogden, UT: U.S. Dept.
Agric., For. Serv., Intermountain Res. Sta.
Austin, M. P. 1985. Continuum concept, ordination
methods and niche theory. Ann. Rev. Ecol. Syst. 16:3961.
Austin, M. P.; Smith, T. M .. 1989. A new model for the
continuum concept. Vegetatio 83:35-47.
Austin, M. P.; Yapp, G. A. 1978. Definition of rainfall
regions of southeastern Australia by numerical classification methods. Archiv fur Meterologie, Geophysik
und Bioklimatologie, Series B 26:121-142.
Austin, M. P.; Cunningham, R. B.; Fleming, P. M. 1984.
New approaches to direct gradient analysis using environmental scalars and statistical curve fitting procedures. Vegetatio 55:11-27.
Bailey, R. G. 1976. Ecoregions of the United States. Ogden, UT: U.S. Dept. Agric., For. Serv., Intermountain
Region. Scale 1 : 7,500,000.
Bailey, R G. 1995. Description of the ecoregions of the
United States. Misc. Pub!. 1391. Washington, DC:
U.S. Dept. Agric., For. Servo
Bailey, R. G.; Jensen, M. E.; Cleland, D. T.; Bourgeron,
P. S. 1994. Design and use of ecological mapping
units. In: Jensen, M. E.; Bourgeron, P. S., eds. Volume II: Ecosystem management: principles and applications. PNW-GTR-318. Portland, OR: U.S. Dept.
Agric., For. Serv., Pacific Northw. Res. Sta.: 95-106.
Banner, A.; Meidinger, D. V.; Lea; E. c.; Maxwell,
R. E.; Von Sacken, B. C. 1996. Ecosystem mapping
methods for British Columbia. In: Sims, R A.; Corns,
1. G. W.; Klinka, K., eds. Global to local: ecological
land classification. Dordrecht, The Netherlands:
Kluwer Academic Publishers: 97-117.
Beauchesne, P.; Ducruc, J.-P.; Gerardin, V. 1996. Ecological mapping: a framework for delimiting forest
management units. Environ. Monit. Assess. 39: 173186.
Bhat, G.; Bergstrom, J.; Teasley, R. J.; Bowker, J. M.;
Cordell, H. K. 1998. An ecoregional approach to the
economic valuation of land- and water-based recre-
taxonomy (USDA, 1993), and distributions of 38
fish species (Lee et al., 1997). Soil taxonomy, although derived from an independent database, was
not assessed for the USFS ELC, because soil was
used as a criterion in defining the levels of this
ELC.1ne performance of the ELCs varied with the
pattern of interest and also in some cases with level.
For example, coarse-cover-type classes were most
strongly associated with the direct-variable ELC at
the province level; however, at the section and subsection group levels, the strongest association was
with the indirect-variable ELC. The other two
ELCs did not perform as well at any level. For the
fine-cover-type classification, the direct-variable
ELC performed best at all three levels. For covertype diversity, the direct-variable ELC had the
strongest association at the province level, but the
USFS ELC performed best at the section and subsection group levels. This analysis suggests caution
when using an ELC for a purpose other than that
for which it was designed.
22.6 Conclusion
ELCs are essential to EAs at all assessment scales.
They are used for many different components of an
EA, including stratifying areas for different purposes, serving as input to models, and evaluating
ecological conditions. Four important recommendations in the definition or use of ELCs are the following:
1. Construct ELCs with appropriate variables that
address the objectives of an EA.
2. Test hypothesized relationships between variables used to construct ELCs and the patterns
and processes of interest.
3. Evaluate the performance of ELCs with respect
to the objectives.
4. Evaluate the performance of ELCs before using
them for purposes other than those for which
they were designed and tested.
In practice, it is likely that arbitrary decisions
may be made about which variables to use in the
design of an ELC or which existing ELC to use.
Therefore, emphasis should be placed on the validation of the ELC (recommendations 3 and 4).
Suggestions for future research in the design and
implementation of ELCs for EAs include the following:
1. Quantifying the delineation of ELUs (e.g., Hargrove and Hoffman, 1999).
2. Developing additional techniques to evaluate
ELCs for specific applications.
333
3. Developing methods to more effectively characterize variability within ELUs.
22.7 References
Albert, D. A. 1995. Regional landscape ecosystems of
Michigan, Minnesota, and Wisconsin: a working map
and classification. Fourth revision. GTR-NC-178. St.
Paul, MN: U.S. Dept. Agric., For. Serv., North Central For. Exp. Sta.
Anderson, J. R; Hardy, E. E.; Roach, J. T. 1976. Land
use and land cover classification system for use with
remote sensing data. Geological Survey Professional
Pap. 964 (a revision of the land use classification system as presented in U.S. Geological Circular 671).
Washington, DC: U.S. Govt. Printing Off.
Arno, S. F.; Simmermann, D. G.; Keane, R. E. 1986.
Characterizing succession within a forest habitat
type-an approach designed for resource managers.
Research Note INT-357. Ogden, UT: U.S. Dept.
Agric., For. Serv., Intermountain Res. Sta.
Austin, M. P. 1985. Continuum concept, ordination
methods and niche theory. Ann. Rev. Ecol. Syst. 16:3961.
Austin, M. P.; Smith, T. M .. 1989. A new model for the
continuum concept. Vegetatio 83:35-47.
Austin, M. P.; Yapp, G. A. 1978. Definition of rainfall
regions of southeastern Australia by numerical classification methods. Archiv fur Meterologie, Geophysik
und Bioklimatologie, Series B 26:121-142.
Austin, M. P.; Cunningham, R. B.; Fleming, P. M. 1984.
New approaches to direct gradient analysis using environmental scalars and statistical curve fitting procedures. Vegetatio 55:11-27.
Bailey, R. G. 1976. Ecoregions of the United States. Ogden, UT: U.S. Dept. Agric., For. Serv., Intermountain
Region. Scale 1 : 7,500,000.
Bailey, R G. 1995. Description of the ecoregions of the
United States. Misc. Pub!. 1391. Washington, DC:
U.S. Dept. Agric., For. Servo
Bailey, R. G.; Jensen, M. E.; Cleland, D. T.; Bourgeron,
P. S. 1994. Design and use of ecological mapping
units. In: Jensen, M. E.; Bourgeron, P. S., eds. Volume II: Ecosystem management: principles and applications. PNW-GTR-318. Portland, OR: U.S. Dept.
Agric., For. Serv., Pacific Northw. Res. Sta.: 95-106.
Banner, A.; Meidinger, D. V.; Lea; E. c.; Maxwell,
R. E.; Von Sacken, B. C. 1996. Ecosystem mapping
methods for British Columbia. In: Sims, R A.; Corns,
1. G. W.; Klinka, K., eds. Global to local: ecological
land classification. Dordrecht, The Netherlands:
Kluwer Academic Publishers: 97-117.
Beauchesne, P.; Ducruc, J.-P.; Gerardin, V. 1996. Ecological mapping: a framework for delimiting forest
management units. Environ. Monit. Assess. 39: 173186.
Bhat, G.; Bergstrom, J.; Teasley, R. J.; Bowker, J. M.;
Cordell, H. K. 1998. An ecoregional approach to the
economic valuation of land- and water-based recre-