About the Columbia River Estuary Conceptual Model project

Purpose

The purpose of this effort is to develop an integrated conceptual model of the lower Columbia River and estuary. This model is intended to provide a technical basis for restoration planning, monitoring, and research needs identification.

Background and Needs

Comprehensive research, monitoring, and evaluation (RME) are called for in the NOAA Fisheries Serviceís 2004 Biological Opinion (BIOP) on Operation of the Federal Columbia River Power System and the Federal Columbia River Salmon Recovery Strategy. Toward this end, NOAA Fisheries and the federal Action Agencies have developed a RME Implementation Plan (IP) Workgroup. The goal of this workgroup, as its name suggests, is to develop a RME Implementation Plan that fulfills Action Items in the BIOPís Reasonable and Prudent Alternative (RPA). The IP Workgroup for RME is composed of a Technical/Policy Oversight Group and six subgroups: Status Monitoring, Effectiveness Research, Hydro, Hatchery, Data Management, and Estuary/Ocean (EOS). In September 2002, BPA contracted with Pacific Northwest National Laboratory (PNNL) to facilitate the EOS.

While the estuary/ocean RME effort is well underway, the technical understanding of the ecosystem and the specific actions required to both restore and monitor it are diverse and not well integrated. In order to assist in organizing the understanding of the ecosystem, as well as provide a working basis for decisions on how best to restore the ecosystem, a conceptual model was proposed. The conceptual model is an important element of estuary RME, as well as habitat restoration planning. Several ecosystem models for the Columbia estuary are available:

Corps of Engineers (2001) included such a model as an appendix to the Biological Assessment for the Channel Improvements Project of the Corps of Engineers. The intent of this model was to provide a systematic approach to assessing the potential impacts from channel deepening. To this end, the various component boxes in the model were used as topics discussed in the biological assessment. The format of the model was kept very simple in order to be easy to follow. This resulted in a loss of information on the ecosystem because the known complexities were simplified (e.g., the food web).

Bottom et al. (2001) present the framework for a conceptual model in Salmon at Riverís End, which is guiding salmonid research in the LCR. This model focuses entirely on juvenile use of the estuary. The report presents a comprehensive assessment of the potential aspects of juvenile salmon use of estuarine habitats. Using information on behavior and energetic requirements, swimming ability, bathymetry and circulation modeling, Bottom et al. define zones within the estuary that are most likely utilized by ocean-type juvenile salmon. The model is guiding a comprehensive research program aimed at further elucidating estuarine conditions that would result in increased fitness of juvenile salmon populations. This information is critical to understanding what habitat should be restored, preserved and protected to help salmon recover.

Although not specific to the Columbia estuary, Proctor et al. (1980) developed an extensive ecosystem conceptual model for coastal systems of the Pacific Northwest. The strength of the Proctor et al. model lies in the details of major processes and cycles (e.g., element cycles) that are included. In addition, it presents a typology for various habitat complexes, as well as a scheme for ecosystem succession. Although comprehensive in its coverage of typology and processes, it is not specific to any coastal or estuarine system, and provides no quantification of processes.

Numerical models covering various processes are either developed or under development for the Columbia estuary by Antonio Baptista (Oregon Graduate Institute), David Jay (Oregon Graduate Institute), and the Corps of Engineers. Baptistaís model has focused on circulation and water properties predictions, whereas Jayís models and that of the Corps of Engineers focus on sediment dynamics. The strength of these models is that they incorporate forcing factors (e.g., climate, flow regulation) highly important to habitat formation and water properties in the estuary.

Tarang Khangaonkar (Battelle Memorial Institute) recently developed a numerical hydrology model for the Chinook River estuary (Baker Bay). The model was designed to predict potential flooding of properties as a result of modifications of the tide gate at the mouth of the estuary.

A model that clearly and explicitly addresses the factors controlling habitat development and maintenance is needed because understanding these factors is critical to the successful restoration of habitats supportive of salmon that will be self-maintaining in the long run. The conceptual model presented here was developed to meet the following needs:

1. Integrate and consolidate the existing estuary ecosystem models as appropriate.

2. Provide an effective communication tool.

3. Form the basis for numerical models of the estuary.

4. Provide organization and focus for the research and assessment of cumulative effects of restoration.

Model Description

At the core of the model is the assumption that the structure (i.e., the primary habitats) is formed through the actions of physical and chemical processes termed controlling factors. In turn, the habitats carry out ecological processes that result in ecological functions; i.e., structure and function are correlated. Finally, the model assumes that factors that can affect the structure, processes, and functions of the ecosystem are acted upon primarily at the controlling factor level. The model has been constructed around the framework provided by the relationships between these five components. For example, disturbances such as abnormal flooding events result in alterations to the controlling factors, with ramifications for habitat structure, processes and, finally, functions. Although this simple example ignores feedback loops as well as the direct effects of catastrophic events on functions, it provides a simple, logical sequence that can be followed to assess the potential impacts of natural and non-natural disturbances. The model is written in html format to enable the reader to follow such logical sequences by simply clicking on the hyperlinks of interest on the computer screen.

The model was designed to perform as a management tool. For example, the model organization provides a means to identify the major existing disturbances (e.g., dikes around former tidal wetlands), which aids in planning the specific actions required to restore these systems. Data gaps in the model point to key research needs where information on linkages is weak or non-existent. Aspects of the system that show well developed and understood linkages would be most efficient and effective to include in a monitoring program can also be elucidated by examination of the relationships between components of the model that are relevant to particular projects, sites, or habitat types.

Following the latest thinking (Simenstad et al. 2004), we chose to describe habitat types that make up ecosystem complexes. A complex may include a variety of habitats such as deep channel, shallow subtidal slope, mud/sand flat, unvegetated sand (not used here), emergent marsh, and scrub-shrub forested wetland. We have added submerged aquatic vegetation to the original list. The complexes include not only the vegetated areas, but also the distributory channels and other features of natural habitats, and therefore represent natural landscape elements. The basis for using this typology is that landscape elements are believed to represent the requisite set of features utilized by many animal species. In addition, evolution of habitats proceeds as the development of complexes, disturbances are reflected in changes in the structure of ecosystem complexes, and restoration actions should focus on development of natural complexes through re-establishing the requisite set of controlling factors. Because the ecosystem complexes proposed by Simenstad et al. are draft, these number and type of complexes may change.

A conceptual model is intended to show key linkages between elements of the ecosystem, and can eventually be used as the basis for one or more comprehensive numerical models of the ecosystem. Where available, the model contains quantitative and semi-quantitative model equations. These equations are not necessarily developed specifically for the Columbia estuary, but indicate models that could potentially be used to calculate and predict the effects of changes in the system. We made no attempt to link quantitative models. The model format was kept as simple as possible to maximize clarity and ease of use. Complexities are indicated as multiple linkages and in descriptive material provided within the model. We have also provided sources of information (i.e., to web sites) containing numerical models (e.g., CORIE) of aspects of the system.

The html format facilitates navigation throughout the model on a computer. Using this format, the model can easily be incorporated into an Internet web site where it would be available for wide use. Changes to information in the model can be updated easily simply by changing information contained in an Excel spreadsheet. Updates to the spreadsheet are automatically transferred to all appropriate locations in the model. This makes the model live and amenable to improvements as new interpretations and data become available.

Conclusion

This model brings together into one easily navigated electronic tool the information provided by existing models of subcomponents of the estuary as well as the state of the science knowledge of general estuarine controlling factors, stressors, structures, processes, and functions. It provides a basis and structure in which knowledge about the Columbia estuary, as it becomes available, can be incorporated through updates to a spreadsheet in commonly used software. For example, as new information is posted to the World Wide Web by organizations conducting research in the estuary, hyperlinks to this information can be added to the spreadsheet in order to keep the model up to date. The model also has the potential to be further developed by additions such as: a) comprehensive literature lists concerning each aspect of the estuary, b) contact information for key researchers in various areas of the estuary, c) full maps of the historical and present conditions of the habitats; d) more links to monitoring information such as the U.S. Geological Survey water quality data; e) linkages to regional climate models and ocean circulation models; f) an adaptive management module; and, g) linkages to site maps where research, monitoring and restoration are presently being conducted, with meta data on these activities. Once implemented, the model will allow updates, corrections, and additional linkages to information as it becomes available.

This synthetic model has been designed for use by estuary managers on a personal computer, it also can easily be transferred to a website and thus made accessible by the public and staff with the numerous agencies and organizations currently working in the estuary. As a key tool for adaptive management (Thom 2000), it can be updated as our knowledge of the estuary increases through fundamental and applied research and restoration actions.

Acknowledgements

This document was developed by Ron Thom, Nathan Evans, Amy Borde, Chris May, Jeff Ward and Gary Johnson of PNNL, with additional input and review by Katherine Sobocinski, Greg Williams, and Heida Diefenderfer, also of PNNL.

Contact

Ronald M. Thom, Ph.D

Staff Scientist and Manager - Coastal Assessment and Restoration Group

Marine Research Operations, Pacific Northwest National Laboratory (PNNL)

1529 W. Sequim Bay Road, Sequim, WA 98382

360-681-3657 (phone)

360-681-3681 (fax)

ron.thom@pnl.gov

Suggested Citation:

Thom, R.M., A.B. Borde, N.R. Evans, C.W. May, G.E. Johnson, J.A. Ward. 2004. A Conceptual Model for the Lower Columbia River Estuary Prepared by Pacific Northwest National Laboratory for the U.S. Army Corps of Engineers, Portland District.

Stressors Controlling Factors Ecosystem Complex Structure Ecosystem Complex Processes Ecosystem Functions Home Site Map References