Title: Connectivity and Socio-ecological Vulnerability of the Oregon LandSea Boundary

How these concepts will explicitly address the 3 “legs” [Human Dimension, Big Data, Risk and
Uncertainty] of the Risk and Uncertainty Quantification in Marine Science Program:

Human Dimension:
1. Current management practices in these watersheds and the implications for management
of the ecosystem services/functions in the future.
2. The policy, social, and cultural frameworks required to address socioecological
vulnerabilities in the watershed and make the system more resilient.
3. Societal impacts from changes to the watershed both in economic and cultural terms.

Big Data:
1. High temporal resolution river water and sediment discharge time series analysis for
available gauge locations and periods of record.
2. Land use and various geophysical attribute (lithology, topography, slope, etc.) data for the
watersheds in question.
3. Spatial and temporal data compilation and statistical modeling along the sediment routing
system over the last century for four Oregon watersheds.

Risk and Uncertainty Quantification:
1. Uncertainty related to landscape connectivity between freshwater and estuarine systems.
2. Combined risks posed by human alterations of the landscape (especially altered fluvial
sediment flux) and changing climate to ecosystem functioning (e.g., tidal saline wetland
morphodynamics, coastal stream hydrodynamics).
3. Risk of ecosystem service alteration to coastal communities that rely upon these systems.

Faculty Contacts:
Lori Cramer, School of Public Policy: lcramer@oregonstate.edu
James Molyneux, Statistics: molyneuj@oregonstate.edu
Mary Santelmann, Water Resources: Mary.Santelmann@oregonstate.edu
Rob Wheatcroft, Ocean Ecology & Biogeochemistry: Rob.Wheatcroft@oregonstate.edu

Topic: The Oregon coastal margin is a highly connected landscape. Small, mountainous rivers drain the
Oregon Coast Range, transporting sediment and dissolved particulates, including nutrients, to
estuaries. Within estuaries, a fraction of this material accumulates in coastal wetlands. Combined
with marine (e.g. tidal energy, relative sea level rise) and interestuarine conditions (e.g., wave
energy, dredging, urbanization), variability in stream flow regime controls estuarine morphology.
Estuaries along the Oregon coast exhibit diverse morphologies, the reasons for which are not
wholly understood. Intertidal zones, for instance, sometimes exhibit gradual elevational shifts
from mud flat to high marsh, whereas instances of bimodal elevation distribution are present
elsewhere. Additionally, some estuaries appear to be accumulating sediment rapidly despite
relatively slow relative sea level rise over the last century (e.g., Nehalem Bay), whereas others
appear to be drowning (e.g., Alsea Bay; Peck et al. in prep ). Elucidation of the drivers of these
differences has significant implications for understanding how these systems function and
determining their resiliency to future changes.

Freshwater hydrologic landscape classifications (HLCs) could be used in combination with
estuary morphology characterizations to better understand connectivity between freshwater/saltwater
systems and whole margin vulnerability to future changes across a wide range of coastal Oregon systems.
For example, whole system research could lead to better understanding of how storms propagate through the landscape;
how synchronous higher high tides and high streamflow events might impact estuarine habitat or human infrastructure;
and where overlap occurs between vulnerable watersheds and vulnerable estuaries. We propose to characterize the relationship
between freshwater and estuarine systems along the Oregon margin by creating classification schemes along the landsea
boundary. These typologiescould then be statistically compared to marine (e.g., tidal energy, relative sea level rise),
terrestrial (e.g., freshwater input, sediment supply), and interestuarine (e.g., wave energy,
dredging, urbanization) drivers to determine what primarily influences coastal aquatic systems.
We will fit a spatiotemporal statistical model to predict areas most vulnerable to the effects of
climate change and humanland use alteration. Here we define vulnerability as the areas most
susceptible to change. For instance, within watersheds, streams that are more likely to
demonstrate increasingly asynchronous periods of optimal streamflow and temperature for
salmonids. Additionally, within estuarine systems, loss of tidal saline wetland extent or elevation
relative to mean sea level would indicate drowning of the marsh surface. Vulnerability as used
here, is not limited to ecological change; it is coupled with human, cultural, and social systems.
Because coastal communities rely heavily upon these systems and the ecosystem services they
provide, environmental vulnerability informs preventative and adaptive management strategies.
Knowledge of the degree to which changing climate and human land use have historically
impacted the watersheds can then be used to assess the future social and policy implications
needed to increase resistance to potential degradation.

Oregon’s coastal watersheds provide numerous economically and socially important ecosystem
services. Watersheds and their estuaries provide critical linkages to marine environments for
native migratory species such as Pacific salmon ( Oncorhynchus spp. ). Tidal saline wetlands also
provide flood protection; biogeochemical filtration of sediments, nutrients, and pollutants; area
for recreation; and carbon sequestration. These areas are also home to many fishing communities
as well as Native American tribes that have economic and cultural ties to the area.
However, the coupled terrestrial estuarine human system is under threat from climate change
stressors and human land use intensification. There is much uncertainty related to how these
systems will respond to climate stressors and human land use change. Determining vulnerability
within these landscapes under future scenarios of change is thus critical in assessing the
resiliency of these systems and the services they provide. Assessing the vulnerability of these
systems will also aid in the ability to make comprehensive fact based
policy suggestions in order to protect and maintain these watersheds.

Existing Data:
Historical aerial photography, maintained by the University of Oregon Aerial Photography
Collection, and Light Detection and Ranging (LiDAR) digital elevation models (DEMs) from the
Oregon Department of Geology and Mineral Industries (DOGAMI) will be used to characterize a
number of Oregon estuaries in terms of elevation distributions and changing vegetated marsh
aerial extents over the last century. Wetland profiles are additionally summarized by Adamus et
al. (2005). Changes in relative sea level over the last century along the Oregon coast will be
characterized using NOAA tide gauge data. Sediment supply to the coast will be estimated using
the USGS stream gauge system and the USGS SPARROW (SPAtially Referenced Regression on
Watershed attributes) model (Wise & O’Connor 2016). Geophysical data from LiDAR DEMs, STATSGO2
(Digital General Soil Map of the United States; NRCS), NetMap (TerrainWorks, 2019), and StreamCat
(Hill et al., 2016) will be used to classify coastal watersheds. Data for response metrics, including streamflow and temperature,
will be downloaded from available USGS river gauge stations. Case study watersheds will
include the Smith River and the Siletz river, for which there are 410
years (15 minute intervals) of streamflow data at a number of upstream (3rd or 4th order) sites.
Historical settlement data, including information available from the U.S. Census and the
National Archives for Indians/Native American repository will be analyzed, as well as data from
Regional Natural Resource Agencies (e.g., Oregon Department of Fish and Wildlife) to
contextualize the cultural and economic impact of human activity in the estuaries over time. In
order to determine potential management impacts, a brief overview of current policy and
management practices as well as proposed legislation will be included.

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