SaRON Program Goals
- To quantify biophysical processes producing the Shifting Habitat Mosaic and associated biodiversity in the observatory rivers, in context of influences on salmonid population structure and productivity
- To devise and promote a new conservation and management protocol for wild salmon rivers that is based on the Shifting Habitat Mosaic model
- To understand if riverine habitat quality, defined as intrinsic capacity for productivity, substantially declined due to lack of fertility associated with chronic over harvest of salmon spawners that import marine nutrients into river ecosystems
- To predict how salmon and salmon habitat will respond to ongoing climate warming
Overview |
The Flathead Lake Biological Station (FLBS) of The University of Montana with the Wild Salmon Center (WSC), Moscow State University (MGU) and other cooperators has assembled a multi-disciplinary team of scientists to document salmonid biodiversity and productivity, as controlled by natural and cultural processes, of a suite of pristine Pacific salmon river ecosystems (observatories). The research focuses on salmonid habitat requirements that appear to vary with life history stage and in relation to population structure. We believe that productivity of habitat is controlled by non-linear biophysical processes that create and maintain a dynamic or constantly Shifting Habitat Mosaic (SHM; described in detail in Stanford et al. 2005) throughout the river corridor from headwaters to the ocean. Our research also addresses how salmon rivers and their stocks will respond to climate change. Runoff and temperature patterns are primary determinants of physical habitat in rivers and therefore critically influence salmon productivity. Since both variables may be changed significantly by climate warming, better resolution of climate effects is needed in order to produce robust conservation strategies for salmon and salmon related biodiversity. Human activities tend to reduce or dampen the variable nature of rivers in ways that should be predictable and, therefore, correctable given a robust understanding and modeling of salmon productivity and population dynamics in the context of the SHM concept.

SaRON Research Site Map
Program History

Salmon carcass returns nutrients to the Kitlope River, B.C.
The program is funded by the Gordon and Betty Moore Foundation as a part of its Wild Salmon Ecosystems Initiative. The FLBS began the program in Kamchatka, Russia, in 2001 under a formal partnership with the WSC and MGU for work on the Kol and Utkholok Rivers. The Kamchatka work is conducted under the auspices of WSC and with logistical support of the WSC office in Petropavlosk as the Kamchatka Salmon Biodiversity Program (KSBP).
In 2004, we expanded the research to North America, and began partnerships with the Yukon Delta National Wildlife Refuge of the US Fish and Wildlife Service for work on the Kwethluk River in Western Alaska and the Na'na'kila Institute and Kitamaat Village Council of the Haisla First Nation for work on the Kitlope River in British Columbia, Canada. In 2005, we added the Lower Skeena River in British Columbia to the observatory network, conducting cooperative research with the Kitsumkalum Band of the Tsimshian First Nation. In 2006 we began cooperative research with the Taku River Tlingit First Nation on the Taku River in British Columbia and Alaska. In 2008, we initiated cooperative research with the Tahltan/Iskut First Nation on the Stikine River in British Columbia, and we expanded the geographical range of study rivers to include the contiguous US, conducting research with the University of Idaho on Big Creek in the Salmon River watershed of Idaho and with the Cow Creek Band of the Umpqua Tribe on the Umpqua River in Oregon.
At all of our observatories, we are proactively involving Federal, State, Provincial, Tribal, NGO and local entities with management or conservation interests in our sites and work. Since the inception of the project, we have expanded our collaborators and partners to include British Columbia Parks; British Columbia Ministry of Environment; Fisheries and Oceans Canada; the Alcan Corporation; Alaska Department of Fish and Game; USGS Alaska Science Center; the US Forest Service, University of Idaho, and University of Washington Department of Fisheries.
In 2007 the project expanded beyond field work on the observatory rivers to include an extensive modeling component. Modelers are now using data collected at the observatories to predict the flow of nutrients and materials through different floodplain habitats, and subsequently to predict the potential productivity of different habitats in different rivers. The ultimate goal of the modeling component is to predict which Pacific salmon rivers have the greatest potential for salmon production, given their habitat and other physical and biological characteristics. Modelers are also examining the potential effects of climate change on salmon rivers.
In order to create, calibrate and expand the models, SaRON field crews have been collecting data from a variety of non-observatory rivers. We have been using the SaRON research protocol to conduct rapid, expedition-style research on what we are calling Synoptic rivers. Using outputs from the Riverscape Analysis Project (RAP), Synoptic rivers are being chosen with a variety of characteristics in order to supply information about the natural range of variation found within salmonid rivers. In 2007, Synoptic research expeditions were conducted on the Aniak and Mulchatna Rivers of Alaska, and the Kalum and Taku Rivers of British Columbia. In 2008, Synoptic research expeditions were conducted on the Chitina and Mulchatna Rivers of Alaska, and on the Stikine, Taku, and Exchamsiks Rivers of British Columbia.
The Salmonid Rivers Observatory Network is planned for a 10-year period (2002 – 2012) to allow for long-term measures of processes and responses. The initial funding period (2002-2006) focused on identification of observatory rivers, partnering, initial field measures and development of the SHM sampling protocol for cross-site comparisons. The current funding period (2007-2010) focuses on continued data collection at the long-term observatories, collecting data from Synoptic rivers for use in productivity modeling efforts, and linking the SaRON outcomes with other FLBS projects such as the Riverscape Analysis Project (RAP) and the Rio Grande (South America) Brown Trout Project.
Currently, we are in an analysis period. We are conducting a thorough analysis of the data, preparing papers on our results for publication, and developing an outreach initiative for conservation purposes.
Methods
- Remote Sensing, Multi-Spectral imagery technology, and field mapping are used to classify and quantify different aquatic and riparian habitat types.
- Acoustic Doppler Profiling technology is used to measure depth and velocity and to characterize hydro-geomorphic characteristics of the study rivers and to link those characteristics to processes, production, and/or past events.
- Water temperature patterns and other physical attributes, such as wood debris, substratum size and groundwater upwelling, are used to characterize habitat types found within the Shifting Habitat Mosaic and are viewed as primary controllers of salmonid food supplies, growth and reproduction.
- River chemistry and nutrient availability in the different rivers and habitat types are measured and examined in relation to productivity of food webs within habitat types.
- Plants and animals, including aquatic invertebrates, algae, particulate organic material, fish (both salmonid and non-salmonid) and terrestrial vegetation in the suite of habitat types are examined in a food web context for Marine Derived Nutrients with stable isotope analysis and for food quality with lipid analyses.
- Non-lethal tissue sampling (fin clips) of the different life stages of fishes, initially focused on rainbow-steelhead, are used to document population genetic structure.
- Measurements of salmonid lengths and weights and analysis of otoliths, morphometry, and scull and bone structure are used to determine growth rates and life history strategies.
- Salmonid biodiversity, habitat and diet selectivity, density, movement, and growth rates in the suite of different habitat types are quantified by electrofishing and snorkelling surveys coupled with measurements of length and weight and analysis of scales and otoliths and genetic studies.
- Modeling of nutrient and material cycling are being used to predict potential productivity of different habitat types within different rivers and their floodplains.
- Modeling of climate change is used to predict the potential effects on salmonid rivers.
Data Management

Benthos Collection on the Kitlope River, B.C.
Though hardware and software technologies have improved dramatically, the ecological community continues to be very slow to integrate technological change. Factors such as budgetary constraints, resistance to change, the availability of individual data management alternatives (i.e. Microsoft Excel), and network interconnectivity combine to form a barrier to entry for many institutions.
In order to address the larger issues of data integrity such as raw data preservation, data entropy, data access and distribution, and inter-project data comparisons, it is incumbent upon project and data managers to implement scalable architectures to manage collection, centralization, processing, archiving, and reporting capabilities before data collection begins.
Flathead Lake Biological Station has addressed these issues in two ways:
We have developed a defined protocol encompassing data collection in the Salmonid Rivers Observatory Network. This protocol allows researchers to work between many sites across multiple ecosystems and countries while capturing consistent data and descriptions (metadata) through standardized collection techniques. For more information on this protocol, please refer to the full project document, available below.
Data Management Demo
We have also created the FLBS Ecodata Portal, an interface to a scalable back-end architecture and data management structure capable of ensuring that distributed data is centralized and processed before data or metadata is lost or simply forgotten.
Researchers enter, display and update data through an access-controlled collaborative web interface.
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