Grantee Research Project Results
1999 Progress Report: Multi-scaled assessment methods: Prototype development within the Interior Columbia River Basin.
EPA Grant Number: R825465Title: Multi-scaled assessment methods: Prototype development within the Interior Columbia River Basin.
Investigators: Bourgeron, Patrick , Poff, N. LeRoy , Milne, Bruce , Davis, Frank , Humphries, Hope
Institution: University of Colorado at Boulder
EPA Project Officer: Packard, Benjamin H
Project Period: February 1, 1997 through January 31, 2000 (Extended to January 31, 2001)
Project Period Covered by this Report: February 1, 1998 through January 31, 1999
Project Amount: $1,516,180
RFA: Ecological Assessment (1996) RFA Text | Recipients Lists
Research Category: Ecological Indicators/Assessment/Restoration , Aquatic Ecosystems
Objective:
This study of multi-scaled relationships among terrestrial and aquatic variables of importance for ecological assessment in the interior Columbia River Basin (ICRB) has six objectives: link and quantify biophysical and biological patterns of terrestrial and aquatic systems (Objectives 1 and 2), develop new methods for predicting ecological patterns (Objective 3), develop and evaluate the performance of hierarchical ecological classifications (HECs) to represent and scale spatial patterns and processes (Objectives 4 and 5), and prototype methods of representativeness assessments for conservation (Objective 6).Progress Summary:
We conducted further work on Objective 3 in the third year of the project, completing our investigation of the effects of three spatial scales (entire basin, province groups, and provinces), geographic location, and level of biological organization (all vegetation types combined, and four major vegetation types) on regional- and subregional-scale vegetation patterns. For all levels of biological organization, geographic variables contributed most to total variation explained (TVE) at the regional scale. Regional variables consistently contributed more to TVE than local variables. Spatial variables accounted for a relatively small percentage of TVE. Results of other analyses differed among spatial scales, geographic locations within a spatial scale, and levels of biological organization. Work on Objective 3 also included the development of statistical models to determine the response of regional plant species richness to environmental variables categorized into six groups (climate severity, climate variability, energy, topographic heterogeneity, geology, and disturbance). Predictive models were constructed for total richness and richness within four plant functional types. Richness responses to environmental gradients were complex. Climate severity variables were most important in predicting total and forb richness, whereas energy (potential evapotranspiration) contributed most to predicting tree, shrub, and graminoid richness.
We continued work on the study plans for Objectives 4 and 5 developed in the second year of the project. We completed our evaluation and comparison of the power of four HECs to represent and scale aquatic and terrestrial patterns and processes at three spatial scales and concluded that all HECs performed well, although they exhibited wide differences in individual patch size and patch number. The distributions of the HECs in ecological and geographic space were characterized. An electivity index was calculated to determine whether HEC classes were associated with variation in independent data, such as vegetation cover types, fish and wildlife species, soil taxonomy, and hydrological variables. Each HEC successfully recovered regional scale patterns in some of the independent data at multiple scales. We conclude that the use of a specific HEC should be closely matched with project goals.
Objective 6 was addressed in continuing work on assessing the suitability of land areas for conservation and a representativeness assessment of regional conservation networks, using fuzzy logic models incorporated in a knowledge-based (KB) system. Three steps are required for conducting representativeness assessment: (1) delineation of land polygons, (2) determination of the suitability of such polygons for conservation, and (3) selection among land polygons for inclusion in a conservation network. The first two steps were addressed in the second year of the project. In the third year, further work was conducted on step 2, and step 3 was implemented. The application framework implementing the KBs (Ecosystem Management Decision Support System) includes the ability to explicitly evaluate the sensitivity of land polygon suitability ratings to missing data layers. Varying the inclusion of data layers indicated that road density and land use condition have the largest effects on land polygon suitability. Finally, we selected land polygons as candidate members of conservation networks using Sites 1.0, a site selection toolbox implemented in ArcView that uses a simulated annealing algorithm as a heuristic method for efficiently selecting sets of areas. A good solution to the problem of selecting a conservation network is considered to be one in which the ?cost' of the network is minimized, but as many of the targets of conservation (vegetation cover types) as possible are included. We used suitability as a basis for cost and compared the resulting conservation networks to networks selected using area as cost or equal costs.
Our accomplishments and results include: (1) implementation and testing of a knowledge-based system for assessing the suitability of land areas for conservation and for use at different stages of conservation planning, (2) completion of tests of the ability of HECs to represent the regional variation in specific patterns and processes, and (3) integration of ecological classifications in the analysis and modeling of biotic patterns and ecological and conservation assessments.
Journal Articles on this Report : 4 Displayed | Download in RIS Format
Other project views: | All 36 publications | 17 publications in selected types | All 4 journal articles |
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Bourgeron PS, Humphries HC, Barber JA, Turner SJ, Jensen ME, Goodman IA. Impact of broad- and fine-scale patterns on regional landscape characterization using AVHRR-derived land cover data. Ecosystem Health 1999;5(4):234-258. |
R825465 (1998) R825465 (1999) R825465 (Final) |
Exit |
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Jensen ME, Redmond RL, DiBenedetto JP, Bourgeron PS, Goodman IA. Application of ecological classification and predictive vegetation modeling to broad-level assessments of ecosystem health. Environmental Monitoring and Assessment 2000;64(1):197-212. |
R825465 (1999) |
Exit Exit |
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Jensen ME, Dibenedetto JP, Barber JA, Montagne C, Bourgeron PS. Spatial modeling of rangeland potential vegetation environments. Journal of Range Management 2001;54(5):528-536. |
R825465 (1998) R825465 (1999) R825465 (Final) |
Exit |
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Kan AT, Hunter MA, Fu G, Tomson MB. Effectiveness of chemically enhanced solubilization of hydrocarbons. SPE Production & Facilities 1997;12(3):153-158. |
R825465 (1998) R825465 (1999) R825465 (Final) R825513C015 (Final) R825513C016 (Final) |
Exit |
Supplemental Keywords:
watershed, ecosystem, aquatic, multi-scaled assessment, climate, fuzzy logic, modeling, geography., RFA, Scientific Discipline, Ecosystem Protection/Environmental Exposure & Risk, Aquatic Ecosystems & Estuarine Research, Ecosystem/Assessment/Indicators, Ecosystem Protection, exploratory research environmental biology, Chemical Mixtures - Environmental Exposure & Risk, Ecological Effects - Environmental Exposure & Risk, Aquatic Ecosystem, Ecological Effects - Human Health, Ecology and Ecosystems, Ecological Indicators, numerical classification techniques, risk assessment, predicting bioenvironments, biophysical variables, landscape classification, prototype development, regional conservation planning, biological cycling, aquatic ecosystems, evaluating alternative land management strategies, multi-scaled assessment methodsProgress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.