Download Interactive influences of climate change and agriculture on aquatic

Interactive influences of climate change and agriculture
on aquatic habitat in a Pacific Northwestern watershed
Sandra J. DeBano,1,† David E. Wooster,1 Jonathan R. Walker,2
Laura E. McMullen,2,4 and Donald A. Horneck3,5
1Department
of Fisheries and Wildlife, Hermiston Agricultural Research and Extension Center, Oregon State University,
2121 South First Street, Hermiston, Oregon 97838 USA
2ICF International, 615 Southwest Alder Street, Portland, Oregon 97205 USA
3Department of Crop and Soil Science, Hermiston Agricultural Research and Extension Center, Oregon State University,
2121 South First Street, Hermiston, Oregon 97838 USA
Citation: DeBano, S. J., D. E. Wooster, J. R. Walker, L. E. McMullen, and D. A. Horneck. 2016. Interactive influences of
climate change and agriculture on aquatic habitat in a Pacific Northwestern watershed. Ecosphere 7(6):e01357. 10.1002/
ecs2.1357
Abstract. Climate change and agricultural intensification are two potential stressors that may pose sig-
nificant threats to aquatic habitats in the inland Pacific Northwest over the next century. Climate change
may impact running water through numerous pathways, including effects on water temperature and
stream flow. In certain regions of the Pacific Northwest, agricultural activities, such as crop production,
may become more profitable if water projects result in more irrigation water. If so, riparian buffers in
these areas may be converted into cropland, which may in turn affect aquatic habitats through increases
in sediment and agrochemical runoff into streams. We used currently available downscaled temperature
and hydrology data in combination with a habitat quality framework developed for Pacific salmon and
trout (Oncorhynchus spp.) to predict how different levels of each stressor, alone and in combination, may
impact aquatic habitats in an inland Pacific Northwest watershed dominated by high-­value agriculture—
the Umatilla Subbasin. We developed spatially explicit predictions for how changes in stream flow and
water temperature associated with three climate change scenarios and loss of riparian buffers in two agricultural intensification scenarios may impact aquatic habitats. We also examined the cumulative effects of
the interaction of extreme climate change and agricultural intensification scenarios. Our results show that
all three climate change scenarios are expected to primarily impact aquatic habitat in the upper Subbasin.
In contrast, agricultural intensification scenarios did not have large impacts on temperature, but are predicted to affect other water quality variables in the lower Subbasin. A moderate scenario of agricultural
intensification had relatively little effect on aquatic habitat, whereas the removal of all riparian buffers
in agriculturally viable areas had a substantially negative effect on sediment, embeddedness, and large
woody debris in the lower Subbasin. Interactions between the most extreme climate change and agricultural intensification scenarios reflected a complementarity of effects, with climate change primarily affecting the upper Subbasin and agricultural intensification primarily impacting the lower Subbasin. This work
suggests that the Umatilla Subbasin and similar watersheds will present a challenging habitat for warm
water-­and pollution-­intolerant species in the coming century.
Key words: agricultural intensification; climate change; low stream flow; Oncorhynchus; Pacific Northwest; runoff;
stream temperature; Umatilla River.
Received 9 October 2015; revised 27 January 2016; accepted 10 February 2016. Corresponding Editor: W. Cross.
Copyright: © 2016 DeBano et al. This is an open access article under the terms of the Creative Commons Attribution
­License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
4 Present address: Columbia Gorge Community College, 400 East Scenic Drive, The Dalles, Oregon 97058 USA.
5 Deceased.
† E-mail: [email protected]
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Introduction
increased air temperatures and to changes in precipitation amounts and patterns (Mantua et al.
2010, Isaak et al. 2012, Wu et al. 2012). The specific response of a basin’s hydrology will be influenced by the type of precipitation that currently
drives its hydrograph. Pacific Northwest basins
have been classified as snowmelt dominant, rain
dominant, or transient (a mix of rain and snow)
(Hamlet et al. 2013). The hydrology of rain and
snow mixed basins, the dominant type of basin in
mid-­elevation areas (1000–2000 m) of the inland
Pacific Northwest, has been predicted by some to
be most strongly impacted by climate change as
rain replaces snow as the dominant winter precipitation (Elsner et al. 2010, Dalton et al. 2013).
In response, the annual hydrologic peak will
occur earlier, resulting in lower summer stream
flows (Elsner et al. 2010). Low stream flows may
be exacerbated by increased evapotranspiration
associated with higher air temperatures and by
changes in summer precipitation, which may
decline by up to 20–40% by the 2080s (Mote and
Salathé 2010).
Changes in stream temperature and flow are
expected to negatively impact aquatic habitat
quality for coldwater species (e.g., Poff et al. 2002,
Heino et al. 2009, Wenger et al. 2011b). Indeed,
several large-­scale, regional studies suggest that
Pacific salmon (Oncorhynchus spp.) will be particularly vulnerable to climate-­induced changes
in habitat (e.g., Mantua et al. 2010, Beechie et al.
2013). However, while these studies provide essential information on regional trends, they provide little resolution at the local watershed level.
The complex and heterogeneous habitats of local
watersheds require higher resolution predictions
of the thermal and hydrologic impacts of climate
change to guide management and restoration efforts (Mantua et al. 2010, Lawrence et al. 2014).
In addition, with few exceptions (Wenger et al.
2011b, Walters et al. 2013, Lawrence et al. 2014),
our knowledge of how climate change will interact with future changes of other stressors is limited.
Stressors occurring at the local and regional
level may exacerbate potential impacts of climate
change (e.g., Walters et al. 2013). In response to
a higher demand for food and biofuels from an
expanding global population (Rosegrant et al.
2009), momentum is growing in the Pacific
Northwest to increase agricultural production. In
Rivers and streams are key providers of multiple ecosystem services, including drinking
water, food, transportation, and irrigation of agricultural crops (MEA 2005). Rivers and streams
also serve as habitat for a variety of economically
and culturally significant plant and animal life,
and in the Pacific Northwest, USA, this includes
several species of threatened and endangered
salmonids (Huppert and Kantor 1998). Numerous human activities have negatively influenced
water quality in the region over the last several
hundred years, including logging, urban and
suburban development, and agriculture (NRC
1996). The future of aquatic systems in the Pacific
Northwest is predicted to continue to be heavily influenced by many of these locally generated stressors. However, global drivers, such as
climate change, may pose even more substantial
threats to aquatic habitats (Rieman and Isaak
2010) and may interact with local-­scale stressors
in ways that compound their effects (e.g., Walters
et al. 2013). Climate change is expected to have
profound impacts on various factors, including
water temperatures and the hydrologic cycle,
that influence the ability of aquatic systems to
provide services (Frederick and Gleick 1999, Poff
et al. 2002, CCSP 2008, Lettenmaier 2008).
Evidence suggests that regional warming is already occurring in the Pacific Northwest (Mote
2003, Hamlet et al. 2007) and predictions from
downscaled global models suggest that air temperatures will continue to rise (Mote and Salathé 2010, Beechie et al. 2013, Dalton et al. 2013).
Elevated air temperatures are expected to lead
to increased stream temperatures. Indeed, water temperatures in some streams in the Pacific
Northwest have already shown detectable increases. For example, Isaak et al. (2012) found
air temperature to be a strong driver of warming
trends in more than 80% of unregulated rivers
they examined. Increased stream temperatures
are predicted to have multiple effects on aquatic
life, not only impacting development, behavior,
and mortality, but also by changing distributions
of plant and animal communities with which
aquatic organisms interact (Poff et al. 2002, Heino
et al. 2009, Ruesch et al. 2012).
Hydrological cycles are also expected to be
impacted by climate change, both in response to
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addition to increasing overall acreage of farming,
there is also interest in converting dryland production systems to irrigated agriculture, which
has much higher crop values relative to dryland
production. These higher crop values not only result from increased yield of crops already grown
in those areas, but irrigation also allows farmers to shift from relatively low-­value crops (e.g.,
wheat) to crops that are an order of magnitude or
greater in value (e.g., watermelon) (Howell 2001).
Because of the economic benefits associated with
irrigated crop production, increasing water availability for agriculture in the inland Pacific Northwest is a high priority. Indeed, recent efforts have
focused on increasing the use of Columbia River
water for irrigation in the region. In July 2015,
the Oregon Legislature passed HB 5005 that provides $50 million in funding for water projects,
including $11 million for pumps and equipment
to provide water for increasing irrigated agriculture in one inland watershed, the Umatilla
Subbasin, with resulting economic benefits for
the region being estimated to exceed $1 billion
a year (OWC 2015, Plaven 2015). As more water
for agriculture is made available and if commodity prices continue to increase, then more land is
expected to be farmed given the potential opportunity costs of not farming. This increase in agricultural intensification in the Pacific Northwest
has the potential to continue to increase even in
the face of the challenges associated with climate
change (e.g., increased evapotranspiration, longer growing seasons), as relatively little of the
Columbia River flow is allocated to agriculture
(6%) compared to many of the nation’s major
rivers (FCRPS 2001). Uncultivated lands, such
as many riparian buffers in arid agroecosystems,
may potentially be converted to cropland. In this
case, streams and rivers may be negatively impacted through loss of riparian vegetation, which
filters pollutants, shades water, and provides organic input into streams (Gregory et al. 1991).
Given the likelihood that climate change and
agricultural intensification may impact many
rivers in the Pacific Northwest, it is imperative to
understand how each acts singly and in combination to impact aquatic habitats in these watersheds. Thus, the objective of our study was to use
locally derived data and expert opinion obtained
through the last decade in combination with
downscaled results from global climate models
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(GCMs) to examine how climate change and agricultural intensification may impact aquatic habitats in a watershed heavily dominated by high-­
value agriculture. We framed these efforts in the
context of how these stressors may affect habitat
of one of the region’s most sensitive groups, Pacific salmon and trout (Oncorhynchus spp.).
Methods
The Umatilla Subbasin: present and future scenarios
The Umatilla Subbasin is a 5931 km2 watershed located within Umatilla and Morrow
Counties in northeastern Oregon (DeBano and
Wooster 2004, Fig. 1). The mainstem Umatilla
River is 143 km, originating in the Blue Mountains
at an elevation of 1768 m and emptying into
the Columbia River at 79 m. The Subbasin experiences strong seasonal fluctuations in both
temperature and precipitation with warm days,
cool nights and little precipitation in the summer
and colder winters, with average temperatures
often only slightly above freezing. Most precipitation occurs during the fall, winter and spring.
The climate of the Subbasin is also strongly
influenced by elevation, with warm and dry
conditions existing in the northwestern, low elevation portion of the Subbasin, where precipitation falls mainly as rain (~12 cm annually),
whereas up to 140 cm of precipitation falls in
high elevation areas of the Blue Mountains,
primarily as snowfall. Approximately 42% of the
area in the Subbasin is cropland, 42% is rangeland, 13% is forest, and 3% is urban. Agriculture
is a major economic driver in the Subbasin, with
the two counties ranking second and third in
farm sales in the state and gross farm and ranch
sales exceeding $480 million annually (ODA
2014). Irrigated crops raised in the lower Subbasin
are of very high value compared to dryland
crops of the upper Subbasin. Currently, only
~27% of all crop land in the Umatilla Subbasin
is irrigated (DeBano and Wooster 2004).
Historically, the Umatilla River supported
populations of spring and fall Chinook ­salmon
(O. tshawytscha), steelhead trout (O. mykiss), and
coho salmon (O. kisutsh) (see Appendix S1 for
a description of life stages). With the advent of
large-­scale irrigated agriculture in the early 1900s,
all native anadromous salmonids except for steelhead were extirpated from the Umatilla Subbasin
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Fig. 1. Location of the Umatilla Subbasin in northeastern Oregon, USA, stream gauges, and land uses
associated with stream reaches.
is believed to have been substantially reduced in
the lower river due to channel engineering (DeBano and Wooster 2004). Thus, the resulting loss in
discharge and increased water temperature associated with water withdrawal in the lower river not
only make the river unsuitable habitat for juvenile
salmonids (Appendix S1), but also have a major
influence on the entire aquatic community (Miller
et al. 2007, Brown et al. 2012, Wooster et al. 2016).
In the future, agricultural intensification in
the Umatilla Subbasin is expected to occur
in concert with climate change, resulting in a
heightened risk of losing multiple ecosystem
services associated with aquatic systems located in its agroecosystems. As more water is made
available in the future for local growers through
water development projects like those recently funded by the Oregon Legislature, dryland
production areas are expected to be converted
to irrigated crop production (OWC 2015, Plaven
(Philips et al. 2000). A series of large water exchanges and restoration projects improved river conditions in the 1980–1990s, and Chinook and coho
were reintroduced (Philips et al. 2000). All salmonid
stocks in the Umatilla Subbasin are currently supplemented with hatchery production. While major
improvements were made in the 1980–1990s and
ongoing efforts at habitat improvement and restoration continue, salmonids and the aquatic systems
of the Umatilla River are still of concern. Steelhead
of the Umatilla River were listed as threatened
in 1998, and although the lower river no longer
completely dries during the irrigation season, up
to 99% of stream flow is lost in the lower river in
summer (Miller et al. 2007). Since much of the lower Umatilla River is alluvial, low flow conditions
related to irrigation diversions may be exacerbated
in some reaches where water is lost to the hyporheic zone, and ameliorated in others where water returns to the surface. However, hyporheic exchange
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we examined interactions of the most extreme
climate change and agricultural intensification
scenarios. More specifics on each scenario are described below.
2015). When this occurs, dryland wheat producers may be able to earn more than ten times that
amount by converting to irrigated agriculture
(e.g., the value of wheat is ~$200–400 per acre
compared to over $10,000 per acre for watermelon; Connor et al. 2002, Galinato et al. 2014, ODA
2014). In such a case, the incentive for farming
any uncultivated area will greatly increase,
potentially resulting in fewer agricultural producers implementing or maintaining riparian
­buffers on their land.
To understand how climate change and agricultural intensification may impact aquatic
habitats in the Umatilla Subbasin, both individually and in concert, we examined how changes
in stream flow and water temperature associated with three climate change scenarios (high,
moderate, and low impact scenarios) and riparian buffer loss associated with two agricultural
intensification scenarios (one extreme and one
moderate) impacted aquatic habitats. Salmonids
in the Umatilla Basin are expected to be sensitive
to both climate change and agricultural intensification, with juvenile stages being particularly
vulnerable (Appendix S1). In addition, to understand the range of effects that may result if
both stressors occur, from best case to worst case,
Environmental attributes examined
Because of their conservation concern and the
key role that salmonids play in Pacific Northwest
watersheds, we chose to focus on environmental
attributes known to impact salmonids at various
life stages (Appendix S1). Specifically, we selected nine of 45 environmental attributes used
in the Ecosystem Diagnosis and Treatment
model (EDT), a spatially explicit model used
to simulate salmonid responses to restoration
and other human activities (Lichatowich et al.
1995, Lestelle et al. 2004). We selected attributes
we believed would be most strongly affected
by climate change and agricultural intensification (Table 1; Appendix S2), and used those
attributes as a general surrogate for stream
condition, since conditions associated with suitable salmonid habitat are also likely to support
other biota in aquatic systems not heavily impacted by humans (Pess et al. 2002, Feist et al.
2003). In addition, the EDT attribute rating
system was used in a Subbasin planning effort
Table 1. Environmental attributes used to describe current conditions in the Umatilla Subbasin in eastern
Oregon, USA and conditions under different climate and agricultural intensification scenarios (see Appendix
S2 for details on estimating values for each attribute). An “X” in the column indicates that the attribute was
included in the scenario development.
Climate
change
Environmental attribute and brief description
Dissolved oxygen (DO)†—average dissolved oxygen within the water column
Embeddedness (Emb)‡—extent that larger cobbles or gravel are surrounded by or
covered by fine sediment
Fine sediment (FnSedi)‡—% substrate comprised of fine sediment
Low flow (FlwLow)§—average daily flow during the normal low flow period
Metals/pollutants in sediments/soils (MetSedSis)†—the extent of heavy metals and
other toxic pollutants within the stream sediment and/or soils adjacent to the
stream channel
Riparian function (RipFunc)‡—intactness of stream and floodplain linkages
Summer water temperature (TmpMonMx)§—a function of the maximum water
temperatures during the summer and the length of time those temperatures are
above certain thresholds
Turbidity (Turb)†—the severity of suspended sediment episodes within the stream
reach
Wood (WdDeb)‡—the amount of large woody debris within the reach
Agricultural
intensification
Both
X
X
X
X
X
X
X
X
X
† Attributes not previously estimated.
‡ Attributes estimated using values established through group consensus of local scientists and land managers in 2004.
§ Attributes previously estimated, but re-­estimated using new methods described in the text.
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for the Northwest Power and Conservation
Council (NWPCC) completed in 2004 (DeBano
and Wooster 2004). At that time, local scientists
and managers worked together to divide the
Subbasin into 284 discrete reaches and to characterize each reach relative to most environmental attributes used in the EDT. Decisions
on values for each reach were made on available
data and consensus of professional judgment
(described in DeBano and Wooster 2004).
EDT environmental attributes are characterized by ranks that represent different levels of
habitat suitability for salmonids. We used the
EDT ranking system for all variables except for
low flow. For low flow estimates, we used flow
values generated by the variable infiltration capacity (VIC) hydrological model (described
in more detail below) and calculated percent
change compared to current conditions. Attributes are briefly described in Table 1, with more
descriptions of attribute rating scales in Appendix S2, Lestelle (2005), and Lestelle et al. (2004).
Of nine attributes examined, we used values estimated for current conditions in the previous
Subbasin planning effort for four attributes (Table 1). For two attributes, low flow (FlwLow) and
summer water temperature rank (TempMonMx),
which had been estimated in the previous effort,
we used new methods to establish current values and to predict future conditions (described
below). The three remaining attributes had not
been previously defined. We quantified reach-­
specific values for each attribute in Table 1 for
current conditions and future scenarios (as described below), and calculated means and coefficients of variation for each attribute and mapped
results using ArcGIS 10.1.
between the magnitude of low flow and high
temperature in western North American
streams. Although increases in winter and
spring flooding events are also an important
factor influencing aquatic habitat (Mantua et al.
2010), we chose to focus on summer flow because of its current limiting role in the Subbasin
(DeBano and Wooster 2004). For stream temperatures, we used the EDT ranking system
because it takes into account both the mean
maximum daily temperature and the number
of days above certain threshold temperatures
(Appendix S2). Salmonids, as well as other
aquatic life, are not only sensitive to temperature extremes, but also the length of time those
extremes are encountered. Prolonged exposure
to temperatures above this threshold can lead
to higher mortality, faster growth rates, altered
life histories, and smaller sizes in salmonids
and other aquatic life (Richter and Kolmes 2005,
Brown et al. 2012).
Stream flow.—To characterize low flow, we
used the Western US Stream Flow Metric Dataset
to predict mean summer flow for current and
future climate scenarios. To avoid including
spring snow melt in summer values, the data set
defines the beginning of summer individually for
each stream segment and each year as the first
day after June 1 when flows fell below the mean
annual value. Summer periods ended on
September 30, regardless of the starting date.
Flow values were generated using the VIC
macroscale hydrologic model (http://www.fs.fed.
us/rm/boise/AWAE/projects/modeled_stream_
flow_metrics.shtml), which predicts several
aspects of the hydrologic regime in the Pacific
Northwest, including mean summer flows
(Wenger et al. 2010). VIC uses meteorological
data from GCMs associated with the A1B
greenhouse gas emissions trajectory, which
assumes moderate accumulation of atmospheric
greenhouse gases (IPCC 2007). We used current
(1978–1997) and six climate change scenarios. A
scenario with the composite of 10 IPCC models
for 2040 and 2080 was used to represent a
moderate scenario (referred to hereafter as “Mod
2040” and “Mod 2080”). The 10 models used in
the ensemble had the lowest bias in simulating
observed climate change in the Pacific Northwest
(Littell et al. 2011). A scenario with the MIROC.3.2
GCM for 2040 and 2080 projects a more severe
Developing climate scenarios
We characterized aquatic environments under
climate change scenarios by altering two attributes, FlwLow and TempMonMx (Table 1). We
chose low flow to be the primary hydrological
variable of interest because, in our area, as in
much of the western United States, low flows
occur in summer and are limiting for many
forms of aquatic life (Harvey et al. 2006, Dewson
et al. 2007). Low flows can exacerbate passage
barriers, increase pollutant concentrations, and
raise water temperatures. In fact, Arismendi
et al. (2013) found a strong negative relationship
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scenario in the Pacific Northwest, with warmer
and drier summers than the ensemble mean
(referred to hereafter as “High 2040” and “High
2080”). The PCM1 GCM projects the least severe
climate change scenario for the Pacific Northwest
as a whole, with cooler and wetter summers than
the ensemble mean (referred to hereafter as “Low
2040” and “Low 2080”). Flow metric files were
used in combination with stream segments
defined in the National Hydrography Dataset
Plus (www.horizon-systems.com/nhdplus/) for
analyses, and we used data at 1/8th of a degree.
Historical data produced by VIC were
“ground-­truthed” using information available
about flows in the Umatilla Subasin, including
expert knowledge and flow data collected by
the Bureau of Reclamation (www.usbr.gov/pn/
hydromet/umatilla/umatea.html). For example,
VIC does not take into account human diversion
activities, which heavily impact the lower 50 km
of the Umatilla River (Miller et al. 2007, Brown
et al. 2012). In cases where reach-­level values generated by the VIC model were contradicted by
current knowledge of the system, future values
generated by VIC were not used given that they
would be based on inaccurate current values.
Instead, for modeling water temperature (see
Stream Temperature Modeling section), we used estimated values for 26 reaches based on gauging
stations on the Umatilla River and expert knowledge to replace inaccurate VIC values. Butter
Creek was the only tributary with no gauges, but
flows on the lower sections are known to be subsurface during summer (DeBano and Wooster
2004). Flow values for these 26 reaches were kept
constant in regression modeling of water temperatures for all future climate scenarios because
reaches are either currently completely dry in
summer and thus will not worsen under climate
change scenarios (e.g., lower Butter Creek) or
because water management practices involving
reservoirs and exchanges are likely to result in
similar flow levels in the future (e.g., the lower
Umatilla River). For all other reaches, predicted
values under different climate change scenarios
are expressed as percent decreases relative to
current conditions.
Stream temperature modeling.—We estimated
water temperatures for each reach by developing
a multiple regression model following Isaak et al.
(2010). However, instead of using parametric
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regression, we used a nonparametric multiple
regression technique (NPMR) (Hyperniche
Version 2.0, McCune and Mefford 2009) to
develop a model to estimate the EDT summer
water temperature rank (TempMonMx) for each
reach based on four independent variables: air
temperature, radiation, flow, and elevation.
NPMR is better suited for addressing ecological
phenomena than other commonly used models
that are additive and often assume linear or
sigmoid response shapes (e.g., multiple linear
regression or logistic regression) (McCune 2006).
In fact, the relationship between air and stream
temperature is often better described by nonlinear
functions, especially at higher air temperatures,
when linear regressions may overestimate stream
responses to climate change (Mohseni and Stefan
1999, Mohseni et al. 1999, Mayer 2012). Unlike
traditional regression approaches, NPMR effect­
ively models responses to multiple environmental
variables using nonparametric curve-­fitting
techniques, with the effect of each variable
depending on the value of other variables
(McCune 2006). Instead of arriving at a global
model, in which coefficients are derived in a
fixed mathematical equation assumed to apply
throughout the sample space, nonparametric
multiplicative regression relies on the data to
generate local models, with the model form
specified using a local multiplicative smoothing
function (McCune 2011). For our data, we used a
local mean estimator and Gaussian weighting
function in a forward step-­wise regression, in
which data points closer to the target point
received greater weight. A cross-­validated R2
(xR2) was used to evaluate model fit; xR2 is more
conservative than traditional R2 because, when
calculating the residual sums of squares, each
individual data point is not used for calculating
the estimate of the response of that point
(McCune 2011).
When developing the regression model, we
used 57 reaches in the Umatilla Subbasin that
are equipped with one or more continuously recording water temperature gauges (http://data.
umatilla.nsn.us/waterquality/temperature.aspx)
(Fig. 1). For reaches with multiple gauges, averages among gauges were used. Data were downloaded and TempMonMx ranks were established
based on an algorithm that takes into account
the maximum daily temperature, as well as the
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­ uration of temperatures above certain threshd
olds during July and August for all years for
which data were available (see Appendix S2 for a
description of temperature ranks).
Values for reach-­specific independent variables used in the temperature regression were
determined both for current conditions (for developing the model) and for future conditions
(for predicting water temperature under future
scenarios). Downscaled air temperatures for the
Umatilla Subbasin were obtained from the University of Idaho (http://nimbus.cos.uidaho.edu/
MACA/) through their Multivariate Adaptive
Constructed Analogs (MACA) Statistical Downscaling Method project (Abatzoglou and Brown
2012). The MACA project has downscaled model output from 14 GCMs of the Coupled Intermodel Comparison Project 5 (CMIP5). Output
is downscaled to 4 km resolution for historical
GCM forcings (1950–2005) and for future Representative Concentration Pathways (rcp) scenarios (2006–2100). Because the models and their
method of incorporating emission scenarios are
different than those used for the VIC modeling,
we used the visualization tool on the MACA
website to select three models that give low, medium, and high temperature predictions for our
region. The inmcm4 model was selected to simulate low warming, the bcc-­csm1-­1 model was
selected to simulate moderate warming, and the
HadGEM2-­CC model was selected to simulate
high ­warming. Data were available for two emission scenarios, a low scenario (RCP4.5) and high
scenario (RCP8.5). We selected the high emission
scenario (RCP8.5), which represents a future
with no climate action and high emissions. Current conditions were characterized using “historical data” generated with the moderate GCM
(bcc-­csm1-­1) as a monthly average. Data generated were the mean monthly daily maximum air
temperatures (tasmax) in a vector format with
temperature points dispersed evenly across the
study area. For the multiple regression, tasmax
for July was used; the mean for 1985–2005 was
used to ­describe current conditions, the mean
from 2030–2050 was used to describe 2040 conditions, and the mean from 2070–2090 was used to
describe 2080 conditions.
Radiation for each reach was estimated using
the approach described by Nagel et al. (2009),
with reach-­specific radiation being dependent
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upon (1) shading by vegetation within the focal reach and the focal reach’s catchment size
(which reflects the role of stream width in affecting radiation) and (2) accumulating effects
of shading of upstream reaches on the focal
reach. Details are described in Appendix S3. We
used mean summer flow obtained from the VIC
model (described above) to characterize current
conditions. Reach-­specific elevation was determined using the most recent version of the
USGS Digital Elevation Model (http://ned.usgs.
gov/).
We selected the NPMR model that explained
the most variation in TempMonMx, regardless
of the number of independent variables (1–4),
as long as the model explained >5% of variation
than a simpler model. This model was then used
as a predictor model to estimate water temperature for each reach in the Umatilla Subbasin.
Developing agricultural intensification scenarios
We modeled two future agricultural scenarios.
One, which we term the Doomsday Scenario,
was designed to investigate what we consider
to be the most extreme agricultural intensification
scenario that could impact riparian areas in the
Umatilla Subbasin. In this scenario, increased
value of agricultural commodities results in all
uncultivated areas in currently farmed lands,
including woody and herbaceous riparian buffers,
becoming cultivated. We limited the conversion
of riparian areas to currently farmed areas (Fig. 1)
because the primary reasons why certain areas
are not cultivated in the Subbasin relate to a
combination of low rainfall, the expense of transporting water to the area, topography, soil depth,
and landownership (e.g., federal, state, and tribal
lands). These factors make it unlikely that many
areas in the upper watershed would be cultivated, even with increased value of crops.
Although it may be unrealistic to assume that
all riparian buffers would be removed in currently farmed areas, the Doomsday Scenario is
designed to provide an estimate of the value
of existing buffers in terms of stream condition
by understanding what conditions would be if
no buffers were present.
We also modeled a less extreme scenario of
agricultural intensification, the 75% Agricultural Intensification Scenario. In this scenario, as
in the Doomsday Scenario, increasing value of
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DEBANO ET AL.
agricultural commodities provides an incentive
for farmers to convert 75% of their existing riparian buffers to cropland. This reduction is incorporated into the model as a change of width,
rather than length, because of the difficulty of
cultivating land at the very edge of the stream.
As with the Doomsday Scenario, the reduction
in buffer width only occurs on land currently
farmed.
Attributes examined and current conditions.—We
examined eight attributes related to agricultural
intensification (Table 1). Of these, current reach-­
specific estimates were available for four
attributes, riparian function (RipFunc), woody
debris (WdDeb), embeddedness (Emb), and fine
sediment (FnSedi), as part of the subbasin
planning effort (DeBano and Wooster 2004).
Current summer water temperature rank
(TmpMonMx) was determined using the
regression technique described above.
Three attributes were not defined for the Umatilla Subbasin in previous efforts: dissolved oxygen (DO), metals and pollutants in sediments
and soils (MetSedSis), and turbidity (Turb). We
estimated current conditions of these attributes,
which all relate to agriculturally derived chemical inputs, by considering five factors: slope,
­precipitation, production type, an index of the
intensity of the production system, and the estimated current riparian function. See Appendix
S4 for a description of methods.
Estimating conditions under future agricultural
scenarios.—As stated above, attributes under
future agricultural scenarios were only changed
for reaches located in agricultural areas. To
estimate the future conditions for RipFunc under
the Doomsday Scenario, we assumed that the
conversion of all riparian buffers to cropland
will result in all current riparian function being
lost in agricultural areas in the Subbasin. Thus
all RipFunc values were changed to the worst
case rank of “4” for reaches located in agricultural
areas (Lestelle 2005). For the 75% Scenario, we
decreased function by increasing the current
RipFunc values by one rank (Lestelle 2005). Any
values greater than 4 were truncated to 4.
To estimate the future conditions for WdDeb
under the Doomsday Scenario, we assumed that
the conversion of all riparian buffers to cropland will result in the loss of all large woody debris in agricultural areas in the Subbasin. Thus
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all ­WdDeb values were changed to the worst
case rank of 4 for reaches located in agricultural ­areas (Lestelle 2005). Although some woody
­debris may move into the lower subbasin from
the ­upper ­subbasin, we assume that most woody
debris contributions will come from more nearby
areas. We ­estimated future conditions under the
75% Scenario for large woody debris by taking
the midpoint between current conditions and the
Doomsday Scenario.
To estimate the future conditions under the
Doomsday Scenario for the three variables associated with agrochemical inputs (DO, MetSedSis, Turb), we assumed that all current riparian
function would be lost in agricultural areas in
the Subbasin, so we simply used the values for
the estimated stream conditions in the absence
of filtering effects that we calculated in establishing current conditions (See Appendix S4).
As with WdDeb, we estimated future conditions
under the 75% Scenario for these four variables
by taking the midpoint between current conditions and the Doomsday Scenario. We chose not
to use simple linear relationships to describe the
effect of buffer reduction on these attributes because past work has suggested that the relationship between riparian buffer width and variables
associated with stream condition are not linear,
with large effects not necessarily manifested until large reductions of width occur (Castelle and
Johnson 2000, Dosskey 2001, Wooster and DeBano 2006).
Future reach-­level conditions for the Doomsday Scenario for Emb and FnSedi were estimated
based on current values of the attributes and current and future values of riparian condition (See
Appendix S5). As with WdDeb, we estimated
conditions under the 75% Scenario for Emb and
FnSedi by taking the midpoint between current
conditions and the Doomsday Scenario conditions. Any values under either scenario that were
greater than 4 were truncated to 4.
We expected TmpMonMx to increase under
the Doomsday Scenario because the removal of
all riparian vegetation would result in the loss
of woody vegetation in riparian areas that currently shade streams. Increases in solar radiation
should lead to increased water temperature. To
estimate changes in water temperatures, we used
the same multiple regression model described in
the ­climate change scenario section, but changed
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the solar radiation term through manipulation
of shade for the Doomsday Scenario only. The
75% Scenario will not result in water temperature
changes because the change is in buffer width,
so that 25% of the current buffers closest to the
stream (and providing the shading effect) will remain intact.
extent of flow decreases, and High 2040 showed
the greatest range in reach-­level low flow values
(Table 2; Fig. 2). All 2080 scenarios showed larger reach-­level flow reductions compared to 2040
scenarios, but Low 2080 showed the largest mean
decrease in low flow and the widest spatial distribution of reduced flow (Table 2; Fig. 2). For all
scenarios, most reaches with losses of flow greater than 10% were located in the upper portion of
the Subbasin (Fig. 2).
Interaction scenarios
We examined four climate change × agricultural
intensification interaction scenarios: Low 2080 ×
75% Scenario, High 2080 × 75% Scenario, Low
2080 × Doomsday, and High 2080 × Doomsday.
In the two climate change × Doomsday interaction scenarios, water temperature was impacted
by changes in both radiation and air temperature.
We used the NPMR model described above to
model the effect that changes in radiation and
air temperature had on water temperature ranks.
For interactions involving the 75% Scenario, water
temperatures took on the values associated with
the interacting climate change scenario, since
there was no loss of shading effect of the 75%
Scenario, and therefore no changes in solar radiation input.
Predicted effects of climate change on stream
temperature
Four variables input into the NPMR model
to predict stream temperature were air temperature, radiation, flow, and elevation. The
MACA downscaled data showed air temperatures increasing basin-­wide under all climate
change scenarios, with more extreme scenarios
associated with higher temperatures and more
warming occurring in 2080 as compared to 2040
(Table 3, Fig. 3). Mean increase at the reach
level ranged from 1.9°C in the Low 2040 scenario to 7.7°C in the High 2080 scenario
(Table 3). Solar radiation estimates for current
conditions averaged 1062.9 ± 46.4 MJ·m−2·yr−1
(Fig. 4) and showed expected patterns of increased radiation in higher order reaches due
to increased stream size and accumulating effects
of upstream radiation. Smaller scale variation
associated with shading by riparian vegetation
is also evident in upper reaches of the Subbasin
(Fig. 4). Reach-­level elevation varied from 82
to 1211 m, with an average of 692 m. A significant NPMR model for current conditions
using 57 gauging stations for stream temperature, incorporating all four predictor variables,
and explaining 61% of the variation in current
conditions was selected (Table 4).
The selected NPMR regression model developed for current conditions was used to predict
stream temperature ranks under future climate
change scenarios by changing air temperature
and flow, as described above. Results showed
that summer water temperature at the reach level, reflected as a ranked EDT attribute, increased
under all climate change scenarios (Table 5). For
2040 scenarios, Low 2040 showed the smallest
increase in temperature rank, and High 2040
the largest. All 2080 scenarios showed increased
stream temperature ranks compared to 2040
Results
Predicted effects of climate change on stream flow
Predictions of current summer flow by the
VIC historical condition scenario (Fig. 2) were
consistent with observed flows in the Umatilla
Subbasin with three exceptions. The lower
50 km of the mainstem Umatilla River are
heavily influenced by water withdrawal (Philips
et al. 2000), which were not reflected in VIC
generated values (Fig. 2). In addition, flow in
the lower reaches of two tributaries, Birch Creek,
and Butter Creek, were overestimated by the
VIC model. The lower reaches of Birch Creek
and most of the lower and east fork of Butter
Creek typically dry completely in summer
(DeBano and Wooster 2004). VIC generated
values for these reaches (delineated with an
“inaccurate data” label in Fig. 2) are not reported for future scenarios since they are based
on inaccurate current values.
For 2040 scenarios, Low 2040 showed the largest mean decline in average summer low flow per
reach compared to current conditions, whereas
Mod and High 2040 showed the greatest spatial
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Fig. 2. Mean summer low flows for current conditions, and reaches predicted to experience >10% flow
reductions compared to current conditions in the Umatilla Subbasin in northeastern Oregon, USA for six climate
change scenarios—a low, moderate, and high warming scenario for 2040 (Low 2040, Mod 2040, High 2040) and
a low, moderate, and high warming scenario for 2080 (Low 2080, Mod 2080, High 2080). Reaches labeled as
“inaccurate data” were not predicted well for current conditions under the VIC model (see text, for more detail).
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Table 2. Current conditions and predicted changes in mean low flow in July in the Umatilla Subbasin in eastern
Oregon, USA under six climate change scenarios—a low, moderate, and high warming scenario for 2040 (Low
2040, Mod 2040, High 2040) and a low, moderate, and high warming scenario for 2080 (Low 2080, Mod 2080,
High 2080). Means and CVs are calculated for the 258 reaches; 26 reaches that were not predicted well for current conditions by the VIC model are not included. See text for more detail.
Scenario
Current
Low 2040
Mod 2040
High 2040
Low 2080
Mod 2080
High 2080
Mean (± CV) flow
per reach (cfs)
Mean % decrease
(± CV)†
Range in % decreases
in flow†
% of reaches with
declines >10%†
40.87 ± 2.43
37.44 ± 2.42
37.46 ± 2.44
37.83 ± 2.43
35.20 ± 2.44
35.96 ± 2.44
36.87 ± 2.44
…
8.59 ± 0.16
7.94 ± 0.30
7.06 ± 0.43
13.88 ± 0.17
11.63 ± 0.29
9.31 ± 0.35
…
3.72 to 12.95
−1.25 to 15.11
−6.25 to 17.32
3.75 to 21.78
−2.50 to 21.58
−6.25 to 20.14
…
8.14
20.16
18.67
92.64
75.97
37.98
† Compared to current conditions.
s­ cenarios (Table 5), but High 2080 and Low 2080
warming were similar. The spatial distribution
of stream temperature changes shows that, for
all climate change scenarios, the highest quality
thermal habitat for coldwater species, located in
the upper portion of the Subbasin (e.g., the upper mainstem Umatilla River, North and South
Forks, Meacham Creek), have essentially disappeared with much of the Subbasin dominated by
temperatures likely to lead to thermal stress or
lethal conditions for sensitive coldwater species
(Fig. 5). EDT ranks above 2.5 (Fig. 5) represent
sub-­lethal and incipient lethal ranges for salmonids, and exceed temperature criteria suitable for
salmonid rearing (Appendix S2).
high temperatures are the most serious threats
associated with reaches located in agricultural
areas (Fig. 1). Increased agricultural intensification is expected to amplify differences
between upper and lower reaches for most
variables. As part of the assumptions of the
scenario itself, riparian vegetation under the
Doomsday Scenario is predicted to disappear
in agriculturally impacted areas, leading to
the worst case values for the riparian function
attribute. Because woody debris is directly
associated with presence of riparian vegetation, that attribute shows a concomitant decrease. However, the impact of riparian
function on other attributes was variable
(Fig. 6) because of the differential effect of
several factors, including current conditions,
how riparian function influenced input of
pollutants, and the morphological and physical
characteristics (e.g., substrate) of particular
reaches (Appendix S5).
Predicted effects of agricultural intensification
scenarios
Estimates for current conditions in the
Subbasin (Fig. 6) show that sedimentation,
riparian function, large woody debris, and
Table 3. Current conditions and predicted changes in reach-­level mean air temperature in July in the Umatilla
Subbasin in eastern Oregon, USA under six climate change scenarios—a low, moderate, and high warming
scenario for 2040 (Low 2040, Mod 2040, High 2040) and a low, moderate, and high warming scenario for 2080
(Low 2080, Mod 2080, High 2080). Means and CVs are calculated for the 284 reaches.
Scenario
Current
Low 2040
Mod 2040
High 2040
Low 2080
Mod 2080
High 2080
Mean ± CV (°C)
Mean increase ± CV (°C)
Range (°C)
29.30 ± 0.09
31.22 ± 0.08
32.05 ± 0.08
32.56 ± 0.08
34.38 ± 0.07
35.67 ± 0.07
37.05 ± 0.07
…
1.92 ± 0.02
2.75 ± 0.01
3.26 ± 0.02
5.08 ± 0.01
6.37 ± 0.02
7.75 ± 0.01
23.81–32.94
25.74–34.84
26.55–35.69
27.05–36.32
28.89–38.08
30.15–39.19
31.53–40.65
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Fig. 3. Mean air temperature for July for current conditions in the Umatilla Subbasin in northeastern Oregon,
USA, and for a low warming scenario for 2040 (Low 2040) and 2080 (Low 2080) and a high warming scenario for
2040 (High 2040) and 2080 (High 2080).
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Fig. 4. Estimated radiation under (a) current conditions and (b) the Doomsday Scenario in the Umatilla
Subbasin in northeastern Oregon, USA. The 75% Agricultural Intensification Scenario is not expected to impact
solar radiation because only the width, not length, of buffers is expected to change.
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intensification. Only water temperature ranks
could be impacted via two different mechanisms
by the two stressors. For climate change, water
temperature could be impacted by changes in
air temperature and flow, whereas for agricultural intensification water temperature could be
impacted by effects on solar radiation. However,
water temperatures in the interaction scenarios
(Doomsday × Low 2080 and Doomsday × High
2080) showed little difference from scenarios
involving climate change only (Table 5) because
of the minimal impact of riparian shading in
the lower basin. The distribution of effects of
the two stressors shows a high degree of spatial
complementary, with effects of agricultural intensification primarily limited to the lower basin
(Fig. 1) and the largest effects of climate change
manifested in the upper basin (Fig. 5).
Table 4. Nonparametric multiplicative regression
model results for the effect of one to four predictor
variables on summer water temperature. All models
are significant at P < 0.05 and n = 57 stream reaches.
Environmental variables
Sensitivities†
xR2
Air temperature
Air temperature, radiation
Air temperature, radiation,
elevation
Air temperature, radiation,
elevation, flow
0.73
0.74, 0.22
0.41, 0.25, 0.14
0.41
0.51
0.55
0.45, 0.21, 0.12, 0.23
0.61
† Sensitivities reflect the relative importance of the environmental variables, with a value of 1 indicating equal change
in the response variable per unit change in an environmental
variable and a value of 0 indicating that change in an environmental variable had no effect on the response variable.
Of all the variables expected to be impacted by agricultural intensification, temperature
showed the least response, remaining essentially unchanged in the agricultural reaches,
even under the Doomsday Scenario. Although
mean solar radiation for all reaches increased
from 1062.8 ± 46.4 MJ·m−2·yr−1 per reach (range:
320.0–3736.0 MJ·m−2·yr−1) in current conditions to 1132.0 ± 53.6 MJ·m−2·yr−1 (range: 320–
4424.2 MJ·m−2·yr−1) in the Doomsday Scenario,
several large tributaries (e.g., Wildhorse Creek,
Butter Creek) did not show substantial increases
in solar radiation under the Doomsday Scenario
because radiation values were already high due
to the fact that very little riparian vegetation currently exists to shade the creeks (Fig. 4). Because
of this fact, combined with the decreasing impact
of shading as river order increases in the lower,
agriculturally impacted reaches, water temperature did not increase, as predicted.
In contrast to temperature, other variables,
like sedimentation showed marked increases
under future agricultural intensification scenarios (Fig. 6). Embeddedness did not show a concomitant change, however, because many of the
reaches in the lower Subbasin have bedrock and
silty substrates.
Discussion
Few studies have examined how climate
change may interact with changes in other
human-­induced stressors in the future (e.g.,
Steen et al. 2010), particularly not in the Pacific
Northwest and not in a spatially explicit manner. Using a model that combines data and
information from a wide range of sources including down-­scaled GCMs, watershed planning and monitoring efforts, and expert opinion,
we found that climate change and agricultural
intensification are likely to have significant and
spatially complementary effects on the Umatilla
Subbasin of eastern Oregon. Of the two stressors, our results suggest that climate change
may pose a more significant threat to coldwater
species in watersheds like the Umatilla Subbasin,
which are already highly impacted by human
activities such as water withdrawal.
Climate change impacts on aquatic habitat in the
Umatilla Subbasin
All climate change models downscaled to the
Umatilla Subbasin predicted reduced low flow
and warmer air temperatures in summer, which
resulted in higher stream temperatures. Summer
low flows were predicted to decrease by ~10%
in many reaches in the upper Subbasin and
were widespread in some scenarios. Although
we were not able to predict flow in the lower
50 km of the mainstem Umatilla River because
Predicted effects of interactions of climate change
and agricultural intensification
For all variables, except temperature ranks,
interaction effects of climate change and agricultural intensification were additive; flow impacts of climate change scenarios combined with
the effect of attributes impacted by agricultural
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flow reductions are expected in reaches in the
upper watershed. Understanding the small
scale distribution of predicted changes within a
watershed is particularly relevant for informing
restoration efforts, which typically proceed at
these smaller scales (Beechie et al. 2013). Further, we found that the climate change model
predicted to have the smallest effect on hydrology for the Pacific Northwest overall had the
largest effect on summer flows in the SubbaMean
sin; the spatial extent of drying in 2080 under
rank ± CV
Range
Scenario
the low warming scenario was much greater
Current
1.9 ± 0.36
1.39–3.73
than the other scenarios. This result highlights
Low 2040
2.3 ± 0.33
1.41–3.71
the importance of downscaling larger regional
Mod 2040
2.4 ± 0.29
1.43–3.77
models to watershed scales as opposed to inferHigh 2040
2.5 ± 0.27
1.45–3.78
ring that large-­scale results can be automaticalLow 2080
2.7 ± 0.21
1.72–3.74
Mod 2080
2.9 ± 0.19
1.74–3.66
ly applied to local systems.
High 2080
2.7 ± 0.19
1.66–3.57
Trends for air temperature also generally
Doomsday
1.9 ± 0.37
1.39–3.73
agreed with regional predictions of significant
Low 2080 × Doomsday
2.7 ± 0.20
1.72–3.75
warming for transient basins; for example, Wu
High 2080 × Doomsday
2.7 ± 0.19
1.66–3.58
et al. (2012) predict a 4.5°C increase in transient
basins of the Pacific Northwest by 2080. However, downscaled results for the Umatilla Subbasin
the VIC model does not take into account in-­ indicate even more severe warming may occur
stream diversions, we anticipate little change in this region (5.1°C to 7.7°C, with an ensemble
in flow in these river kilometers under future mean of 6.4°C).
climate change scenarios. This lower section of
Unlike most studies of climate change effects
the river is currently intensely managed via on stream temperatures, we characterized stream
reservoirs and water exchange programs in temperature as an EDT rank, which is a composattempts to accommodate both salmonid habitat ite variable that takes into account two factors
and irrigation needs (DeBano and Wooster 2004). relevant to summer thermal suitability of habitat
Thus, flow conditions on the lower mainstem for coldwater organisms—maximum daily temUmatilla River currently do not reflect natural perature and the length of time those high temconditions, and this section of river will likely peratures persist. Thus, our results are not simcontinue to be heavily managed in the future. ply predictions of summer stream temperature
These changes in flow, combined with increased increases, but of thermal suitability for coldwater
summer air temperatures, led to all 2080 sce- species such as steelhead. Basin-­wide, we found
narios showing significant reductions or the EDT ranks increased from an average rank of 1.9
virtual elimination of areas that are currently per reach for current conditions to 2.3–2.5 in 2040
prime thermal habitat for some sensitive cold- and 2.7–2.9 for 2080. This change represents the
water species, such as steelhead (Fig. 5).
difference between conditions which are genPredicted effects in the Umatilla Subbasin are erally hospitable to coldwater species to condigenerally consistent with larger scale analyses tions that are generally inhospitable (Appendix
for the Pacific Northwest that suggest that de- S2). These basin-­wide results are consistent with
clining snowpacks will result in earlier spring both regional results (Mantua et al. 2010, Wu
melt and reductions in summer flow ranging et al. 2012, Beechie et al. 2013) and watershed-­
from 10–22% by 2080 (Wu et al. 2012, Beechie level analyses. Although they did not examine
et al. 2013). In addition, our work adds spatial climate-­induced changes in flow, Ruesch et al.
detail and demonstrates the significance of spa- (2012) found thermally suitable habitat for saltial variation in larger scale regional predic- monids in the John Day Basin of Oregon will
tions. In the Umatilla Subbasin, the most ­severe decline substantially by 2100 and Lawrence et al.
Table 5. Mean EDT summer water temperature rank
of 284 reaches in the Umatilla Subbasin in summer
for current conditions and six climate change, one
agricultural intensification, and two interaction scenarios. Climate change scenarios included a low,
moderate, and high warming scenario for 2040 (Low
2040, Mod 2040, High 2040) and a low, moderate,
and high warming scenario for 2080 (Low 2080,
Mod 2080, High 2080).
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Fig. 5. Summer water temperature ranks in the Umatilla Subbasin in northeastern Oregon, USA for current
conditions and under six climate change scenarios—a low, moderate, and high warming scenario for 2040 (Low
2040, Mod 2040, High 2040) and a low, moderate, and high warming scenario for 2080 (Low 2080, Mod 2080,
High 2080).
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Fig. 6. Mean EDT rank values for environmental attributes in reaches located in agricultural areas under current
conditions and 75% Agricultural Intensification and Doomsday Scenarios in the Umatilla Subbasin in northeastern
Oregon, USA. See Table 1 for explanation of environmental attribute abbreviations and Appendix S2 for detailed
descriptions of attribute ranks. In general, values above 2.5 represent serious threats to many sensitive aquatic life
forms (Appendix S2). No error bars are associated with the Doomsday Scenario for Rip Func and WdDeb because
all reaches in agricultural lands in that scenario are assumed to have riparian buffers converted to agriculture.
(2014) predicted warming of 1.2°C by 2040 and
2.3°C in 2080 in the same watershed. Cristea and
Burges (2010) predicted the Wenatchee River
could warm by 2°C in the 2040s and 2.5–3.6°C in
the 2080s in the absence of riparian restoration.
However, our research, along with Lawrence
et al. (2014), is one of the few studies in the Pacific
Northwest to generate reach-­specific predictions
about how climate change will influence stream
temperature through effects on both summer
low flow and air temperature.
Of the four variables in our final regression
model, air temperature was most important, followed by flow and radiation, and with elevation
playing a more minor role. These results correspond well to a regional study of stream temperatures from 1980–2009 by Isaak et al. (2012),
which found that air temperature and discharge
were the dominant factors explaining long-­
term inter-­annual variation in summer stream
temperature. While we used a nonparametric,
multiple-­regression technique to estimate stream
temperature, the best approach to modeling climate change impacts on stream temperature is
much discussed (e.g., Mohseni and Stefan 1999,
Webb et al. 2008, Mayer 2012, Arismendi et al.
2014, Hilderbrand et al. 2014). Correlative relationships between air and stream temperatures
do not necessarily imply causal relationships,
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18
and may exist primarily because both air and
water temperature are responding to the same
temporal fluctuations in solar heat inputs and
other variables, such as stream substrate (Johnson 2004, Arismendi et al. 2014). However, air
temperature can be a significant driver of stream
temperature through direct sensible heat transfer between air and water, long wave atmospheric radiation, and heating of groundwater that
can flow into streams (Mohseni and Stefan 1999,
Caissie 2006, Webb et al. 2008, Isaak et al. 2012).
Causes underlying variation in the slope of the
regression line of air and water temperatures, or
“thermal sensitivity” (Kelleher et al. 2012), have
been a major topic of research in recent years.
Variability in thermal sensitivity among rivers is
reflected in some regional studies (e.g., Arismendi et al. 2012). Low thermal sensitivity may be
driven by groundwater inputs, shading by riparian vegetation, heated effluents from wastewater
and power plants, and river regulation via damming (Mohseni and Stefan 1999, Mohseni et al.
1999, Caissie 2006, Arismendi et al. 2012, Kelleher et al. 2012, Hilderbrand et al. 2014, Luce et al.
2014). For example, Luce et al. (2014) found that
relatively warm streams in the Pacific Northwest, such as those in eastern Oregon, are more
sensitive to changes in air temperature than
cooler stream, such as those in the Cascades.
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DEBANO ET AL.
of the lower subbasin have substantial riparian
vegetation (e.g., cottonwood and alder galleries,
DeBano and Wooster 2004) that were largely reduced or completely removed in the agricultural
scenarios, the ratio of surface water to shading
vegetation is quite large for the lower basin, and
may account for the minimal effect of shading
losses with riparian vegetation removal. Indeed,
other studies in the Pacific Northwest have suggested a minimal effect of shade on high order
streams (e.g., Cristea and Burges 2010, Lawrence
et al. 2014).
Finally, it should be noted that we did not consider many other significant roles that riparian
vegetation plays in this study, including its ability
to moderate stream temperature extremes (Garner et al. 2015), its contribution of allochthonous
organic input into the stream (Webster and Meyer 1997, Wipfli and Baxter 2010), and its provision
of habitat for wildlife (e.g., Merritt and Bateman
2012). We also focused our effects on agricultural impacts manifested strictly through the loss of
riparian vegetation. Other variables may also be
expected to change with increased agricultural
intensification (e.g., instream flow, the type and
amount of agrochemicals applied in uplands).
However, given the uncertainty of the magnitude
and even direction of effects these phenomena
may have on streams in the face of future trends
in agro-­chemical industries and water policy, we
chose not to include these variables in our future scenarios. More work is needed to quantify
the results of all activities associated with agricultural intensification to inform management
­decisions in watersheds where rapid growth of
high-­value agriculture is expected.
Agricultural intensification impacts on aquatic
habitat in the Umatilla Subbasin
Agricultural intensification scenarios impacted
all attributes examined except for water temperature (Fig. 6), with both scenarios having
negative impacts on seven of the eight attributes
in the lower reaches of the Subbasin. The four
attributes most likely to decline to levels that
could pose a threat to aquatic life (i.e., attribute
ranks >2.5; see Appendix S2) are riparian function, large woody debris, sediment, and embeddedness (Fig. 6). Our assumption that
riparian vegetation plays an important role in
filtering out pollutants from agricultural runoff
is supported by numerous studies (Castelle
et al. 1994, Castelle and Johnson 2000, Dosskey
2001) that suggest that even very narrow buffers
of riparian vegetation can substantially filter
out sediment and other pollutants; for example,
buffers ranging from 0.5 m to 50 m retained
from 40% to 100 of sediment entering from
cultivated fields (Dosskey 2001). However, the
effectiveness of riparian buffers can be highly
variable, depending on various factors including
type of vegetation, stream size, land use legacies
and instream condition (Dosskey 2001,
Greenwood et al. 2012). As future research refines our knowledge of the filtering capacity
of riparian vegetation in the Umatilla Subbasin,
predictions can be easily modified using the
algorithm and existing data set.
In contrast to all other aquatic habitat variables, the conversion of riparian vegetation in
agricultural areas in the lower Umatilla Subbasin had minimal effects on stream temperatures,
even with the elimination of all riparian vegetation in agricultural areas that occurred with the
Doomsday Scenario. Although the effect of shading ­provided by riparian vegetation on stream
temperature can be substantial in some systems
(Johnson 2004, Groom et al. 2011), other factors
such as surface area of water exposed to the ambient environment and type of streambed sediment
can swamp out influences of shade in stream energy budgets, making stream temperatures unresponsive even with complete removal of shading
riparian vegetation (Janisch et al. 2012). In addition, shading impacts on stream temperature are
expected to decline as stream order increases and
less of the water’s surface is shaded by adjacent
vegetation (Vannote et al. 1980). Although parts
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Interacting stressors and spatial complementarity
Few studies have examined how climate
change is expected to interact with other future
stressors to impact freshwater habitat in the
Pacific Northwest, except for work investigating
how climate change will affect the range of
invasive fish species and their potential interaction with native salmonids (Wenger et al.
2011b, Lawrence et al. 2014). While several
studies have examined the degree to which
restoration of riparian vegetation may offset
expected negative impacts of climate change
on regional streams and their biota (Battin et al.
2007, Cristea and Burges 2010, Lawrence et al.
19
June 2016 v Volume 7(6) v Article e01357
DEBANO ET AL.
2014), ours is the first to examine the potential
negative effect of riparian buffer reduction that
may result from increased agricultural intensification. Although stream restoration in the
Pacific Northwest is a high priority for many
stakeholders, including those in the Umatilla
Subbasin, a combination of factors faced by
watersheds similar to the Umatilla Subbasin
may provide economic incentives for reducing
or eliminating these buffers, especially in lower
elevation lands suitable for cultivation that are
not governed by minimum buffer regulations
that apply to forested headwater streams. If
water availability increases and farmers can
shift from relatively low-­value crops to high-­
value ones, the cost and benefit analysis underlying buffer creation and maintenance on
private property will change to favor the conversion of buffers to crop production. If this
occurs, our study suggests that agricultural
intensification and climate change effects in the
Umatilla Subbasin will, to a great extent, show
a high degree of spatial complementarity. Like
Battin et al. (2007), we found climate change
impacts are expected to be most pronounced
in the upper watershed; one potential mechanism underlying this pattern is that warming
air temperatures at higher elevations results in
both less snow accumulation in winter and
earlier snowmelt which, in turn, result in lower
and warmer summer flows in low-­order streams
(Battin et al. 2007). Meanwhile, agricultural intensification is expected to most strongly affect
the lower Subbasin, a pattern common in many
western US watersheds, where agricultural activity is often primarily located at lower elevation areas that are suitable for cultivation.
Understanding the spatial distribution of
multiple stressors in watersheds (e.g., whether
they are overlapping or complementary) is key
to informing management of aquatic systems
(Wooster et al. 2012). Spatial complementarity of
multiple stressors may indicate additive effects
rather than synergistic. While complementary
effects in the Umatilla Subbasin may be beneficial in the sense that no particular area of the
watershed is highly degraded by both stressors,
it also means that the spatial extent of human
disturbance is more widespread, with virtually
all parts of the watershed expected to experience declines in quality, albeit in different ways.
v www.esajournals.org
20
However, the lack of overlap of stressors may
be beneficial to coldwater species. If the upper
watershed is not converted to agriculture and riparian buffers remain intact, riparian vegetation
may be able to ameliorate some of the negative
effects of warming temperature. For example,
Arismendi et al. (2012) observed that streams in
western North America with more riparian vegetation and higher baseflows were less likely to
show warming trends. Our results suggest that
the reaches most likely to be influenced by climate change may also be those most likely to retain the buffering effects of riparian vegetation,
potentially weakening the predicted relationship
between air temperature and water temperature.
With regard to the magnitude of effect of each
stressor, our results suggest that aquatic habitats
used by coldwater species will be more negatively impacted by climate change than by the loss
of shade associated with buffer removal in the
Doomsday Scenario. Steen et al. (2010) found
similar results in a study of fish communities in
the Great Lakes region. Although they examined
the interaction of increased urbanization with
climate change instead of agricultural intensification, they found warmer stream temperature
associated with climate change would have larger effects on fish communities than land cover
changes associated with urbanization. In our
case, agricultural intensification is expected to
occur in areas already fairly degraded by agriculture, and only the Doomsday Scenario involved
removing all riparian buffers in these areas. Although this scenario is theoretically possible because the maintenance of riparian buffers next to
streams is not regulated in nonforested lands in
Oregon, it may be unlikely for several reasons,
including the reluctance of farmers to cultivate
land right up to the water’s edge due to bank instability and saturated soils. Thus, the likelihood
of a scenario as severe as the Doomsday one occurring may be relatively small. In contrast, all
climate change scenarios we examined resulted
in the degradation of prime coldwater habitat in
the Subbasin.
Implications for salmonids and restoration
Although the goal of our study was to examine aquatic habitat generally, we used a
salmonid-­based context to frame our study,
both because of their predicted sensitivity to
June 2016 v Volume 7(6) v Article e01357
DEBANO ET AL.
changes in aquatic habitat and because more
is known about salmonids than any other form
of aquatic life in Pacific Northwest systems.
Similar to other watersheds located in the
Columbia Basin, most salmonids in the Umatilla
Subbasin primarily use the upper watershed
for spawning and rearing (Battin et al. 2007,
Appendix S1). Although affected by some
stressors (e.g., railroads, channelization, road
building, timber harvest), these reaches remain
in relatively good condition and support
spawning and rearing habitat for a number
of species of concern, including threatened
steelhead, bull trout (Salvelinus confluentus),
spring Chinook (O. tshawytscha), and Pacific
lamprey (Entosphenus tridentatus) (DeBano and
Wooster 2004, Close et al. 2009). Our work is
consistent with other studies in the Pacific
Northwest suggesting that climate-­impacted
watersheds will present challenging habitat for
salmonids and other coldwater species in the
coming century (e.g., Battin et al. 2007, Cristea
and Burges 2010, Mantua et al. 2010, Ruesch
et al. 2012, Wu et al. 2012). Climate change
effects on salmonids in the Umatilla Basin may
be even more extreme than our analysis suggests because we did not examine other factors
predicted to change that may impact aquatic
habitat, including altered timing of peak runoff,
flooding events, and changes in interspecific
interactions (Wu et al. 2012, Beechie et al.
2013). Responses of fish to altered temperatures
and hydrology may result in expansion, contraction, or movement of species ranges, with
individual species responding in different ways
(Wenger et al. 2011a) and more research is
needed to understand how thermal and hydrological changes will impact specific salmonid species in the Umatilla Subbasin and their
interspecific interactions.
Our study not only predicts that salmonids
will be exposed to warming summer water temperatures and low flow conditions associated
with climate change in the upper subbasin, but
that they may also experience negative effects
under agricultural intensification in the lower
subbasin if riparian buffers are reduced. Salmonids are sensitive to increases in sediment and
pollutants associated with agriculture, including pesticides and fertilizers (Newcombe and
Macdonald 1991, NRC 1996, Jensen et al. 2009,
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Chapman et al. 2014). Sediment input affects salmonids by decreasing spawning success, reducing prey detection and feeding rate, smothering
eggs, entrapping alevins, and settling in interstitial spaces of cobble, which are used by juveniles
for cover (NRC 1996, Jensen et al. 2009, Chapman
et al. 2014). Sedimentation is currently a concern
for the Umatilla River, which is 303(d) listed for
sediment or turbidity from its mouth to its forks
(ODEQ, UBWC, and CTUIR 2001), although it is
more problematic in the lower subbasin (DeBano
and Wooster 2004). Dryland wheat production is
believed to be a major source of anthropogenically derived sedimentation in the Subbasin (DeBano and Wooster 2004). Large areas of dryland
production systems, left fallow with exposed
soil surfaces during the winter, have been identified as a major contributor to sediment movement to streams (NRC 1996). A shift to irrigated
agriculture is unlikely to make sedimentation
worse because the amount of time ground is left
bare is usually reduced. This combined with the
fact that two of the four anadromous salmonids
spawn and rear primarily in the upper reaches
may indicate that impacts on those species under
agricultural intensification may be fairly limited.
However, coho and fall Chinook spawn and rear
in lower reaches of the mainstem Umatilla River
(DeBano and Wooster 2004, Appendix S1), so agricultural intensification may pose special threats
to them.
As outlined by Beechie et al. (2013), modifying
watershed-­level restoration plans for salmonids
in the face of climate change requires examining how flow and stream temperature will be
affected, ideally at the highest spatial resolution
possible, and then determining if those changes
­alter habitat that currently limits salmon recovery.
Then, managers must make a qualitative assessment of whether these changes alter the effectiveness of current restoration actions. Our study
suggests that focusing restoration efforts on the
upper subbasin should continue to be a high priority to the degree that these actions have the best
chance to counteract climate-­induced warming
of stream temperatures, the most limiting factor
predicted for salmonids in the Umatilla Subbasin.
Reconnecting floodplains with the river, creating
or reconnecting side channels, removing levees
and dikes, and planting riparian vegetation will
increase the likelihood of producing resilient river
21
June 2016 v Volume 7(6) v Article e01357
DEBANO ET AL.
systems and salmonid populations (Waples et al.
2009) and the expression of alternative life histories (Beechie et al. 2013). All of these actions are
currently underway in the upper subbasin (Tetra Tech, CTUIR, and the USDA FS 2013). In fact,
other work in the region suggests that restoration
of riparian vegetation has the potential to offset
predicted increases in stream temperatures associated with climate change (Lawrence et al. 2014).
Although we focused on riparian buffer reductions, it is possible that even with growing economic incentives to farm more land, counterbalancing incentives in the form of policy changes or
best management practices will not only prevent
destruction of current buffers, but will encourage
their expansion. If narrow buffers are effective in
filtering agrochemicals from overland flow from
agricultural lands, a supposition supported by
research in the Subbasin (Wooster and DeBano
2006), then farmers considering total buffer removal could be encouraged to leave fairly narrow
riparian buffers intact to reduce agrochemical
runoff and increase sediment filtration. In contrast to riparian and floodplain restoration, Beechie et al. (2013) suggest that instream rehabilitation
efforts such as restoring meanders of straightened
channels, and adding instream structure, such as
log jams and boulders, may be less effective in
ameliorating temperature increases. In addition,
although restoring summer base flows is feasible
for the lower river and is predicted to ameliorate
high water temperatures, low flows, and passage
challenges, it would have no effect on the upper
watershed, where climate change is expected to
exert its most pronounced effects.
available data is well recognized (Kepner et al.
2012). This effort illustrates one way in which
data and professional knowledge collected at
the local level and often obtained in the context
of publically funded natural resource management and planning efforts can be combined
with downscaled hydrology and climate change
modeling results to produce information that
can be used to inform public decision-­making.
Using fairly simple decision rules to categorize
reaches with regard to ranked environmental
variables associated with a widely used salmonid life history model (i.e., EDT attributes)
allowed us to generate spatially explicit predictions about how multiple stressors may affect
a watershed. In the Umatilla Subbasin, we found
that both climate change and agricultural intensification are likely to impact aquatic habitat
in the future, that climate change will probably
exert a stronger effect than agricultural intensification, and that these two stressors not only
present different types of challenges to aquatic
environments, but that the spatial distribution
of their effects generally do not overlap (i.e.,
they are spatially complementary).
This approach could be easily adapted by other
subbasins, particularly in the Pacific Northwest.
As an example, the NWPCC required subbasins
in Oregon, Washington, and Idaho to engage in
subbasin planning to be eligible for the approximately $140 million annual funding provided by
the Bonneville Power Administration to mitigate
and enhance fish and wildlife affected by hydropower dams and to help meet requirements of the
2000 Federal Columbia River Power System Biological Opinion. This effort resulted in plans for
58 tributary watersheds or mainstem segments of
the Columbia River, making it one of the largest
locally led watershed planning efforts in the United States. Most subbasins used EDT modeling for
examining anadromous salmonid species, resulting in local scientists and managers collaborating
to generate reach-­level values for many of the
environmental attributes used in the EDT. Our
study provides one example of how this knowledge can be combined to gain a spatially explicit understanding of how multiple stressors are
likely to impact a local watershed. Approaches
like ours provide a flexible framework in which
­decision rules can be modified to reflect local conditions and updated with new knowledge.
Conclusions
A major challenge in management related
sciences is incorporating the quickly expanding
availability of data in a framework that can
be used by resource managers and policy makers. Many decisions that impact freshwater
systems are made at regional or local levels
or depend on data with local resolution. Yet
most studies use only a fraction of the data
and other information available to examine how
global and regional processes interact together
to affect regional aquatic environments. The
need to couple modeling with scenario analysis
in ways that capitalize on locally and regionally
v www.esajournals.org
22
June 2016 v Volume 7(6) v Article e01357
DEBANO ET AL.
Finally, this work highlights a number of
­research needs. One relates to developing
subbasin-­specific models that take into account
the movement of woody debris, sediment, and
other pollutants through the watershed so that
we can improve our understanding of downstream effects of riparian management on these
attributes. In addition, our knowledge of the
identity, levels, and distribution of many pollutants in the Umatilla River and its tributaries
is limited, as is an understanding of how these
pollutants may interact with each other and other stressors to impact target species. While our
study shows that multiple stressors will impact
freshwater habitat in the Umatilla Subbasin, the
effects of these multiple stressors on aquatic organisms are unclear. The potential of synergistic interactions of multiple stressors on aquatic organisms, especially in the face of climate
change, is a continuing and urgent research need
(Ormerod et al. 2010).
Arismendi, I., M. Safeeq, S. L. Johnson, J. B. Dunham,
and R. Haggerty. 2013. Increasing synchrony of
high temperature and low flow in western North
American streams: Double trouble for coldwater
biota? Hydrobiologia 712:61–70.
Arismendi, I., M. Safeeq, J. B. Dunham, and S. L. Johnson. 2014. Can air temperature be used to project
influences of climate change on stream temperature? Environmental Research Letters 9:084015.
Battin, J., M. W. Wiley, M. H. Ruckelshaus, R. N. Palmer, E. Korb, K. K. Bartz, and H. Imaki. 2007. Projected impacts of climate change on salmon habitat
restoration. Proceedings of the National Academy
of Sciences 104:6720–6725.
Beechie, T., et al. 2013. Restoring salmon habitat for a
changing climate. River Research and Applications
29:939–960.
Brown, P. D., D. Wooster, S. L. Johnson, and S. J. DeBano. 2012. Effects of water withdrawals on macroinvertebrate emergence: unexpected results for
three holometabolous species. River Research and
Applications 28:347–358.
Caissie, D. 2006. The thermal regime of rivers: a review. Freshwater Biology 51:1389–1406.
Castelle, A. J., and A. W. Johnson. 2000. Riparian vegetation effectiveness. Technical Bulletin No. 799.
National Council for Air and Stream Improvement,
Research Triangle Park, North Carolina, USA.
Castelle, A. J., A. Johnson, and C. Conolly. 1994. Wetland and stream buffer size requirements—a review. Journal of Environmental Quality 23:878–882.
CCSP (Climate Change Science Program). 2008. The
effects of climate change on agriculture, land resources, water resources, and biodiversity in the
United States. U.S. Department of Agriculture,
Washington, D.C., USA.
Chapman, J. M., C. L. Proulx, M. A. N. Veilleux, C. Levert, S. Bliss, M.-È. André, N. W. R. Lapointe, and
S. J. Cooke. 2014. Clear as mud: a meta-­analysis on
the effects of sedimentation on freshwater fish and
the effectiveness of sediment-­control measures.
Water Research 56:190–202.
Close, D. A., K. P. Currens, A. D. Jackson, A. J. Wildbill,
J. T. Hanson, J. P. Bronson, and K. Aronsuu. 2009.
Lessons from the reintroduction of a non-charismatic, migratory fish: Pacific lamprey in the upper Umatilla River. Pages 1–21 in L. R. Brown, S.
D. Chase, M. Mesa, R. Beamish and P. B. Moyle,
editors. Biology, management, and conservation of
lampreys in North America. Symposium 72. American Fisheries Society, Bethesda, Maryland, USA.
Connor, J., G. Clough, and S. Herring. 2002. Enterprise
budget: watermelon North Central region. Oregon
State University, Extension Publication EM 8799,
Corvallis, Oregon, USA.
Acknowledgments
This research was funded by the US EPA’s
Science to Achieve Results (STAR) Program
(#RD83456601), managed by the EPA’s Office of
Research and Development (ORD), National Center
for Environmental Research: STAR research supports the Agency’s mission to safeguard human
health and the environment. We thank Katherine
Hegewisch at the Applied Climate Science Lab,
Department of Geography at the University of
Idaho for providing us with downscaled air temperatures under three climate scenarios for the
Umatilla Subbasin. We thank Seth Wenger and
one anonymous reviewer for comments that greatly
improved this manuscript. Publication of this paper
was supported, in part, by the Thomas G. Scott
Publication Fund.
Literature Cited
Abatzoglou, J. T., and T. J. Brown. 2012. A comparison
of statistical downscaling methods suited for wildfire applications. International Journal of Climatology 32:772–780.
Arismendi, I., S. Johnson, J. Dunham, R. Haggerty,
and D. Hockman-Wert. 2012. The paradox of cooling streams in a warming world: regional ­climate
trends do not parallel variable local trends in
stream temperature in the Pacific continental United States. Geophysical Research Letters 39:L10401.
v www.esajournals.org
23
June 2016 v Volume 7(6) v Article e01357
DEBANO ET AL.
energy exchanges and water temperature of an
upland Scottish stream. Hydrological Processes
29:1080–1095.
Greenwood, M. J., J. S. Harding, D. K. Niyogi, and A.
R. McIntosh. 2012. Improving the effectiveness of
riparian management for aquatic invertebrates
in a degraded agricultural landscape: stream size
and land-­use legacies. Journal of Applied Ecology
49:213–222.
Gregory, S. V., F. J. Swanson, W. A. McKee, and K. W.
Cummins. 1991. An ecosystem perspective of riparian zones: focus on links between land and water. BioScience 41:540–550.
Groom, J. D., L. Dent, L. J. Madsen, and J. Fleuret.
2011. Response of western Oregon (USA) stream
temperatures to contemporary forest management.
Forest Ecology and Management 262:1618–1629.
Hamlet, A. F., P. W. Mote, M. P. Clark, and D. P. Lettenmaier. 2007. Twentieth-­century trends in runoff,
evapotranspiration, and soil moisture in the western United States. Journal of Climate 20:1468–1486.
Hamlet, A. F., M. M. Elsner, G. S. Mauger, S.-Y. Lee,
I. Tohver, and R. A. Norheim. 2013. An overview
of the Columbia Basin Climate Change Scenarios
Project: approach, methods, and summary of key
results. Atmosphere-­Ocean 51:392–415.
Harvey, B. C., R. J. Nakamoto, and J. L. White. 2006.
Reduced streamflow lowers dry-­season growth of
rainbow trout in a small stream. Transactions of the
American Fisheries Society 135:998–1005.
Heino, J., R. Virkkala, and H. Toivonen. 2009. Climate
change and freshwater biodiversity: detected patterns, future trends and adaptations in northern
regions. Biological Reviews 84:39–54.
Hilderbrand, R. H., M. T. Kashiwagi, and A. P. Prochaska. 2014. Regional and local scale modeling
of stream temperatures and spatio-­temporal variation in thermal sensitivities. Environmental Management 54:14–22.
Howell, T. A. 2001. Enhancing water use efficiency in
irrigated agriculture. Agronomy Journal 93:281–
289.
Huppert, D., and S. Kantor. 1998. Economic perspectives. Pages 572–595 in R. J. Naiman and R. E. Bilby,
editors. River ecology and management: lessons
from the Pacific Coastal Ecoregion. SpringerVerlag, New York, New York, USA.
IPCC (Intergovernmental Panel on Climate Change).
2007. Climate Change 2007: Working Group 2:
­impacts, adaptation, and vulnerability. Intergovernmental Panel on Climate Change, Geneva,
­Switzerland.
Isaak, D. J., C. H. Luce, B. E. Rieman, D. E. Nagel, E. E.
Peterson, D. L. Horan, S. Parkes, and G. L. Chandler. 2010. Effects of climate change and wildfire on
Cristea, N. C., and S. J. Burges. 2010. An assessment
of the current and future thermal regimes of three
streams located in the Wenatchee River basin,
Washington State: some implications for regional
river basin systems. Climatic Change 102:493–520.
Dalton, M. M., P. W. Mote, and A. K. Snover. 2013. Climate change in the Northwest: implications for our
landscapes, waters, and communities. Island Press,
Washington, D.C., USA.
DeBano, S. J., and D. E. Wooster, technical writers/
editors. 2004. The Umatilla/Willow Subbasin plan.
Northwest Power and Conservation Council, Portland, Oregon, USA. http://www.nwcouncil.org/fw/
Subbasinplanning/umatilla/plan
DeBano, S. J., D. E. Wooster, J. R. Walker, L. McMullen,
and D. Horneck. 2016. Data from: Interactive influences of climate change and agriculture on aquatic
habitat in a Pacific Northwestern watershed. Dryad Digital Repository. http://dx.doi.org/10.5061/
dryad.564q7
Dewson, Z. S., A. B. W. James, and R. G. Death. 2007.
A review of the consequences of decreased flow
for instream habitat and macroinvertebrates. Journal of the North American Benthological Society
26:401–415.
Dosskey, M. G. 2001. Profile: toward quantifying water pollution abatement in response to installing
buffers on crop land. Environmental Management
28:577–598.
Elsner, M. M., L. Cuo, N. Voisin, J. S. Deems, A. F.
Hamlet, J. A. Vano, K. E. B. Mickelson, S. Lee, and
D. P. Lettenmaier. 2010. Implications of 21st century climate change for the hydrology of Washington
State. Climatic Change 102:225–260.
FCRPS (Federal Columbia River Power System). 2001.
The Columbia River system inside story. Bonneville Power Administration, US Army Corps of
Engineers, and US Bureau of Reclamation, Portland, Oregon, USA. https://www.bpa.gov/power/
pg/­columbia_river_inside_story.pdf
Feist, B., A. Steele, G. R. Pess, and R. E. Bilby. 2003. The
influence of scale on salmon habitat restoration priorities. Animal Conservation 6:271–282.
Frederick, K. D., and P. H. Gleick. 1999. Water and
global climate change: potential impacts on U.S.
water resources. Pew Center on Global Climate
Change, Arlington, Virginia, USA.
Galinato, S. P., C. A. Miles, and J. Wimer. 2014. 2013
cost estimation of producing seedless watermelon
in eastern Washington. Washington State University Extension Fact Sheet, FS150E, Pullman, Washington, USA.
Garner, G., I. A. Malcolm, J. P. Sadler, C. P. Millar, and
D. M. Hannah. 2015. Inter-­annual variability in
the effects of riparian woodland on micro-­climate,
v www.esajournals.org
24
June 2016 v Volume 7(6) v Article e01357
DEBANO ET AL.
stream temperatures and salmonid thermal habitat
in a mountain river network. Ecological Applications 20:1350–1371.
Isaak, D. J., S. Wollrab, D. Horan, and G. Chandler.
2012. Climate change effects on stream and river
temperatures across the northwest U.S. from 1980-­
2009 and implications for salmonid fishes. Climatic
Change 113:499–524.
Janisch, J. E., S. M. Wondzell, and W. J. Ehinger. 2012.
Headwater stream temperature: interpreting response after logging, with and without riparian
buffers, Washington, USA. Forest Ecology and
Management 270:302–313.
Jensen, D. W., E. A. Steel, A. H. Fullerton, and G. R.
Pess. 2009. Impact of fine sediment on egg-­to-­fry
survival of Pacific salmon: a meta-­analysis of published studies. Reviews in Fisheries Science 17:348–
359.
Johnson, S. L. 2004. Factors influencing stream temperatures in small streams: substrate effects and a
shading experiment. Canadian Journal of Fisheries
and Aquatic Sciences 61:913–923.
Kelleher, C., T. Wagener, M. Gooseff, B. McGlynn, K.
McGuire, and L. Marshall. 2012. Investigating controls on the thermal sensitivity of Pennsylvania
streams. Hydrological Processes 26:771–785.
Kepner, W. G., M. M. Ramsey, E. S. Brown, M. E. Jarchow, K. J. M. Dickinson, and A. F. Mark. 2012.
Hydrologic futures: using scenario analysis to
evaluate impacts of forecasted land use change on
hydrologic services. Ecosphere 3:art69.
Lawrence, D. J., B. Stewart-Koster, J. D. Olden, A. S.
Ruesch, C. E. Torgersen, J. J. Lawler, D. P. Butcher, and J. K. Crown. 2014. The interactive effects of
climate change, riparian management, and a non-­
native predator on stream-­rearing salmon. Ecological Applications 24:895–912.
Lestelle, L. C. 2005. Guidelines for rating level 2 environmental attributes in Ecosystem Diagnosis and
Treatment (EDT). Mobrand – Jones and Stokes,
Vashon Island, Washington, USA. http://colville.
whydevelop.com/media/files/2005EDTAttribute
Ratings.pdf
Lestelle, L. C., L. E. Mobrand, and W. E. McConnaha.
2004. Information structure of Ecosystem Diagnosis and Treatment (EDT) and habitat rating rules
for Chinook Salmon, Coho Salmon, and Steelhead
Trout. Mobrand Biometrics, Vashon Island, Washington, USA. http://www.webpages.uidaho.edu/
fish510/PDF/coho%20ck%20rules.pdf
Lettenmaier, D. P. 2008. Have we dropped the ball on
water resources research? Journal of Water Resources Planning and Management 134:491–492.
Lichatowich, J. A., L. E. Mobrand, L. Lestelle, and T.
Vogel. 1995. An approach to the diagnosis and
v www.esajournals.org
25
treatment of depleted Pacific salmon populations
in freshwater ecosystems. Fisheries 20:10–18.
Littell, J. S., M. M. Elsner, G. S. Mauger, E. Lutz, A.
F. Hamlet, and E. Salathé. 2011. Regional climate
and hydrologic change in the Northern US Rockies
and Pacific Northwest: internally consistent projections of future climate for resource management.
Climate Impacts Group, University of Washington
College of the Environment, Seattle, Washington,
USA.
http://cses.washington.edu/picea/USFS/
pub/Littell_etal_2010/Littell_etal._2011_Regional_­
Climatic_And_Hydrologic_Change_USFS_USFWS_JVA_17Apr11_reduced.pdf
Luce, C., B. Staab, M. Kramer, S. Wenger, D. Isaak, and
C. McConnell. 2014. Sensitivity of summer stream
temperatures to climate variability in the Pacific
Northwest. Water Resources Research 50:3428–
3443.
Mantua, N., I. Tohver, and A. Hamlet. 2010. Climate
change impacts on streamflow extremes and
summertime stream temperature and their possible consequences for freshwater salmon habitat
in Washington State. Climatic Change 102:187–
223.
Mayer, T. D. 2012. Controls of summer stream temperature in the Pacific Northwest. Journal of Hydrology 475:323–335.
McCune, B. 2006. Nonparametric habitat models with
automatic interactions. Journal of Vegetation Science 17:819–830.
McCune, B. 2011. Nonparametric multiplicative regression for habitat modeling. Oregon State University, Corvallis, Oregon, USA. http://www.pcord.
com/NPMRintro.pdf
McCune, B., and M. J. Mefford. 2009. HyperNiche.
Nonparametric multiplicative habitat modeling,
Version 2. MjM Software, Gleneden Beach, Oregon,
USA.
MEA (Millennium Ecosystem Assessment). 2005.
Chapter 7: freshwater. Pages 165–207 in Ecosystems
and human well-being: current state and trends.
Vol. 1. Island Press, Washington, D.C., USA.
Merritt, D. M., and H. L. Bateman. 2012. Linking
stream flow and groundwater to avian habitat in
a desert riparian system. Ecological Applications
22:1973–1988.
Miller, S. W., D. Wooster, and J. Li. 2007. Resistance and
resilience of macroinvertebrates to irrigation water
withdrawals. Freshwater Biology 52:2494–2510.
Mohseni, O., and H. G. Stefan. 1999. Stream temperature/air temperature relationship: a physical interpretation. Journal of Hydrology 218:128–141.
Mohseni, O., T. R. Erickson, and H. G. Stefan. 1999.
Sensitivity of stream temperatures in the United
States to air temperatures projected under a ­global
June 2016 v Volume 7(6) v Article e01357
DEBANO ET AL.
Richter, A., and S. A. Kolmes. 2005. Maximum temperature limits for Chinook, coho, and chum salmon, and steelhead trout in the Pacific Northwest.
Reviews in Fisheries Science 13:23–49.
Rieman, B. E., and D. J. Isaak. 2010. Climate change,
aquatic ecosystems, and fishes in the Rocky Mountain West: implications and alternatives for management. RMRS-GTR-250. USDA Forest Service,
Rocky Mountain Research Station, Fort Collins,
Colorado, USA.
Rosegrant, M. W., C. Ringler, and T. Zhu. 2009. Water
for agriculture: maintaining food security under
growing scarcity. Annual Review of Environment
and Resources 34:205–222.
Ruesch, A. S., C. E. Torgersen, J. J. Lawler, J. D. Olden,
E. E. Peterson, C. J. Volk, and D. J. Lawrence. 2012.
Projected climate-­induced habitat loss for salmonids in the John Day River network, Oregon, USA.
Conservation Biology 26:873–882.
Steen, P. J., M. J. Wiley, and J. S. Schaeffer. 2010. Predicting future changes in Muskegon River watershed game fish distributions under future land
cover alteration and climate change scenarios.
Transactions of the American Fisheries Society
139:396–412.
Tetra Tech, CTUIR (Confederated Tribes of the Umatilla
Indian Reservation), and the USDA FS (Forest Service). 2013. Meacham Creek floodplain restoration
and in-stream enhancement (phase II) biological
assessment and essential fish habitat assessment.
http://data.umatilla.nsn.us/fisheries/downloads/
MeachamPhaseIIRM6-8.5_BA%20Final_Feb2013.pdf
Vannote, R. L., G. W. Minshall, K. W. Cummins, J. R.
Sedell, and C. E. Cushing. 1980. The river continuum concept. Canadian Journal of Fisheries and
Aquatic Science 37:130–137.
Walters, A. W., K. A. Bartz, and M. M. McClure. 2013.
Interactive effects of water diversion and climate
change for juvenile Chinook salmonid in the
Lemhi River Basin (USA). Conservation Biology
27:1179–1189.
Waples, R., T. Beechie, and G. R. Pess. 2009. Evolutionary history, habitat disturbance regimes, and
anthropogenic changes: What do these mean for
resilience of Pacific Salmon populations? Ecology
and Society 14:3.
Webb, B. W., D. M. Hannah, R. D. Moore, L. E. Brown,
and F. Nobilis. 2008. Recent advances in stream
and river temperature research. Hydrological Processes 22:902–918.
Webster, J. R., and J. L. Meyer, editors. 1997. Stream organic matter budgets. Journal of the North American Benthological Society 16:3–161.
Wenger, S. J., C. H. Luce, A. F. Hamlet, D. J. Isaak,
and H. M. Neville. 2010. Macroscale hydrologic
warming scenario. Water Resources Research
35:3723–3733.
Mote, P. W. 2003. Trends in temperature and precipitation in the Pacific Northwest during the twentieth
century. Northwest Science 77:271–282.
Mote, P. W., and E. P. Salathé Jr. 2010. Future climate in
the Pacific Northwest. Climatic Change 102:29–50.
Nagel, D. E., C. H. Luce, D. J. Isaak, B. G. Gutierrez
Teira, B. E. Rieman, and T. Black. 2009. Spatial
methods for estimating basin-wide riparian solar
radiation at the stream surface and changes resulting from wildlife. White Paper. Boise Aquatic Sciences Laboratory, USFS Rocky Mountain Research
Station, Boise, Idaho, USA.
Newcombe, C. P., and D. D. Macdonald. 1991. Effects
of suspended sediments on aquatic ecosystems.
North American Journal of Fisheries Management
11:72–82.
NRC (National Research Council). 1996. Upstream:
salmon and society in the Pacific Northwest. National Academy Press, Washington, D.C., USA.
ODA (Oregon Department of Agriculture). 2014. Oregon
agriculture: facts and figures. Oregon Department of
Agriculture, Salem, Oregon, USA. http://www.nass.
usda.gov/Statistics_by_State/Oregon/Publications/
facts_and_figures/facts_and_figures.pdf
ODEQ (Oregon Department of Environmental Quality), UBWC (Umatilla Basin Watershed Council), and
CTUIR (Confederated Tribes of the Umatilla Indian
Reservation). 2001. Umatilla River Basin total maximum daily load (TMDL) and water quality plan.
http://www.deq.state.or.us/wq/tmdls/umatilla.htm
Ormerod, S. J., M. Dobson, A. G. Hildrew, and C. R.
Townsend. 2010. Multiple stressors in freshwater
ecosystems. Freshwater Biology 55:1–4.
OWC (Oregon Water Coalition). 2015. District 57 Representative Greg Smith: water is coming to eastern
Oregon. Oregon Water Monthly 22:1–2.
Pess, G. R., D. R. Montgomery, E. A. Steel, R. E. Bilby,
B. E. Feist, and H. M. Greenberg. 2002. Landscape
characteristics, land use, and coho salmon (Oncorhynchus kisutch) abundance, Snohomish River,
Washington, USA. Canadian Journal of Fisheries
and Aquatic Sciences 59:613–623.
Philips, J. L., J. Ory, and A. Talbot. 2000. Anadromous
salmonid recovery in the Umatilla River Basin, Oregon: a case study. Journal of American Water Resources Association 36:1287–1308.
Plaven, G. 2015. Water funding package passes
Legislature. Eastern Oregonian July 4.
Poff, N. L., M. M. Brinson, and J. W. Day. 2002. Aquatic ecosystems and global climate change: potential
impacts on inland freshwater and coastal wetland
ecosystems in the United States. Pew Center on
Global Climate Change, Arlington, Virginia, USA.
v www.esajournals.org
26
June 2016 v Volume 7(6) v Article e01357
DEBANO ET AL.
Wooster, D. E., and S. J. DeBano. 2006. Effect of woody
riparian patches in croplands on stream macroinvertebrates. Archiv für Hydrobiologie 165:241–268.
Wooster, D. E., S. W. Miller, and S. J. DeBano. 2012. An examination of the impact of multiple disturbances on
a river system: taxonomic metrics versus biological
traits. River Research and Applications 28:1630–1643.
Wooster, D. E., S. W. Miller, and S. J. DeBano. 2016. Impact of season-­long water abstraction on invertebrate drift. Hydrobiologia 772:15–30.
Wu, H., J. S. Kimball, M. M. Elsner, N. Mantua, R. F.
Adler, and J. Stanford. 2012. Projected climate
change impacts on the hydrology and temperature
of Pacific Northwest rivers. Water Resources Research 48:W11530.
­ odeling of ecologically relevant flow metrics.
m
Water Resources Research 46:W09513.
Wenger, S. J., et al. 2011a. Role of climate and invasive species in structuring trout distributions in
the interior Columbia River Basin, USA. Canadian Journal of Fisheries and Aquatic Sciences
68:988–1008.
Wenger, S. J., et al. 2011b. Flow regime, temperature,
and biotic interactions drive differential declines
of trout species under climate change. Proceedings
of the National Academy of Sciences 108:14175–
14180.
Wipfli, M. S., and C. V. Baxter. 2010. Linking ecosystems, food webs, and fish production: subsidies in
salmonid watersheds. Fisheries 35:373–387.
Supporting Information
Additional Supporting Information may be found online at: http://onlinelibrary.wiley.com/doi/10.1002/
ecs2.1357/supinfo
Data Availability
Data associated with this paper have been deposited in the Dryad repository: http://dx.doi.org/10.5061/
dryad.564q7 (DeBano et al. 2016).
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