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Arismendi I.,Oregon State University | Safeeq M.,Oregon State University | Dunham J.B.,U.S. Geological Survey | Johnson S.L.,Us Forest Service Pacific Northwest Research Station
Environmental Research Letters | Year: 2014

Worldwide, lack of data on stream temperature has motivated the use of regression-based statistical models to predict stream temperatures based on more widely available data on air temperatures. Such models have been widely applied to project responses of stream temperatures under climate change, but the performance of these models has not been fully evaluated. To address this knowledge gap, we examined the performance of two widely used linear and nonlinear regression models that predict stream temperatures based on air temperatures. We evaluated model performance and temporal stability of model parameters in a suite of regulated and unregulated streams with 11-44 years of stream temperature data. Although such models may have validity when predicting stream temperatures within the span of time that corresponds to the data used to develop them, model predictions did not transfer well to other time periods. Validation of model predictions of most recent stream temperatures, based on air temperature-stream temperature relationships from previous time periods often showed poor performance when compared with observed stream temperatures. Overall, model predictions were less robust in regulated streams and they frequently failed in detecting the coldest and warmest temperatures within all sites. In many cases, the magnitude of errors in these predictions falls within a range that equals or exceeds the magnitude of future projections of climate-related changes in stream temperatures reported for the region we studied (between 0.5 and 3.0 C by 2080). The limited ability of regression-based statistical models to accurately project stream temperatures over time likely stems from the fact that underlying processes at play, namely the heat budgets of air and water, are distinctive in each medium and vary among localities and through time. © 2014 IOP Publishing Ltd.

Arismendi I.,Oregon State University | Safeeq M.,Oregon State University | Johnson S.L.,Us Forest Service Pacific Northwest Research Station | Dunham J.B.,U.S. Geological Survey | Haggerty R.,Oregon State University
Hydrobiologia | Year: 2013

Flow and temperature are strongly linked environmental factors driving ecosystem processes in streams. Stream temperature maxima (Tmax_w) and stream flow minima (Qmin) can create periods of stress for aquatic organisms. In mountainous areas, such as western North America, recent shifts toward an earlier spring peak flow and decreases in low flow during summer/fall have been reported. We hypothesized that an earlier peak flow could be shifting the timing of low flow and leading to a decrease in the interval between Tmax_w and Qmin. We also examined if years with extreme low Qmin were associated with years of extreme high Tmax_w. We tested these hypotheses using long-term data from 22 minimally human-influenced streams for the period 1950-2010. We found trends toward a shorter time lag between Tmax_w and Qmin over time and a strong negative association between their magnitudes. Our findings show that aquatic biota may be increasingly experiencing narrower time windows to recover or adapt between these extreme events of low flow and high temperature. This study highlights the importance of evaluating multiple environmental drivers to better gage the effects of the recent climate variability in freshwaters. © 2012 Springer Science+Business Media Dordrecht.

Keane R.E.,U.S. Department of Agriculture | Herynk J.M.,SEM LLC | Toney C.,U S WEST | Urbanski S.P.,U S WEST | And 2 more authors.
Forest Ecology and Management | Year: 2013

Fuel Loading Models (FLMs) and Fuel Characteristic Classification System (FCCSs) fuelbeds are used throughout wildland fire science and management to simplify fuel inputs into fire behavior and effects models, but they have yet to be thoroughly evaluated with field data. In this study, we used a large dataset of Forest Inventory and Analysis (FIA) surface fuel estimates (n=13,138) to create a new fuel classification called Fuel Type Groups (FTGs) from FIA forest type groups, and then keyed an FLM, FCCS, and FTG class to each FIA plot based on fuel loadings and stand conditions. We then compared FIA sampled loadings to the keyed class loading values for four surface fuel components (duff, litter, fine woody debris, coarse woody debris) and to mapped FLM, FCCS, and FTG class loading values from spatial fuel products. We found poor performances (R2<0.30) for most fuel component loadings in all three classifications that, in turn, contributed to poor mapping accuracies. The main reason for the poor performances is the high variability of the four fuel component loadings within classification categories and the inherent scale of this variability does not seem to match the FIA measurement scale or LANDFIRE mapping scale. © 2013 Elsevier B.V.

May C.,James Madison University | Roering J.,University of Oregon | Eaton L.S.,James Madison University | Burnett K.M.,Us Forest Service Pacific Northwest Research Station
Geology | Year: 2013

A fundamental yet unresolved question in fluvial geomorphology is what controls the width of valleys in mountainous terrain. Establishing a predictive relation for valley floor width is critical for realizing links between aquatic ecology and geomorphology because the most productive riverine habitats often occur in low-gradient streams with broad floodplains. Working in the Oregon Coast Range (western United States), we used airborne lidar to explore controls on valley width, and couple these findings with models of salmon habitat potential. We defined how valley floor width varies with drainage area in a catchment that exhibits relatively uniform ridge-and-valley topography sculpted by shallow landslides and debris flows. In drainage areas >0.1 km2, valley width increases as a power law function of drainage area with an exponent of ~0.6. Consequently, valley width increases more rapidly downstream than channel width (exponent of ~0.4), as derived by local hydraulic geometry. We used this baseline valley width-drainage area function to determine how ancient deep-seated landslides in a nearby catchment influence valley width. Anomalously wide valleys tend to occur upstream of, and adjacent to, large landslides, while downstream valley segments are narrower than predicted from our baseline relation. According to coho salmon habitat-potential models, broad valley segments associated with deep-seated landsliding resulted in a greater proportion of the channel network hosting productive habitat. Because large landslides in this area are structurally controlled, our findings indicate a strong link between geologic properties and aquatic habitat. © 2013 Geological Society of America.

Arismendi I.,Oregon State University | Johnson S.L.,Us Forest Service Pacific Northwest Research Station | Dunham J.B.,U.S. Geological Survey | Haggerty R.,Oregon State University
Freshwater Biology | Year: 2013

Temperature is a major driver of ecological processes in stream ecosystems, yet the dynamics of thermal regimes remain poorly described. Most work has focused on relatively simple descriptors that fail to capture the full range of conditions that characterise thermal regimes of streams across seasons or throughout the year. To more completely describe thermal regimes, we developed several descriptors of magnitude, variability, frequency, duration and timing of thermal events throughout a year. We evaluated how these descriptors change over time using long-term (1979-2009), continuous temperature data from five relatively undisturbed cold-water streams in western Oregon, U.S.A. In addition to trends for each descriptor, we evaluated similarities among them, as well as patterns of spatial coherence, and temporal synchrony. Using different groups of descriptors, we were able to more fully capture distinct aspects of the full range of variability in thermal regimes across space and time. A subset of descriptors showed both higher coherence and synchrony and, thus, an appropriate level of responsiveness to examine evidence of regional climatic influences on thermal regimes. Most notably, daily minimum values during winter-spring were the most responsive descriptors to potential climatic influences. Overall, thermal regimes in streams we studied showed high frequency and low variability of cold temperatures during the cold-water period in winter and spring, and high frequency and high variability of warm temperatures during the warm-water period in summer and autumn. The cold and warm periods differed in the distribution of events with a higher frequency and longer duration of warm events in summer than cold events in winter. The cold period exhibited lower variability in the duration of events, but showed more variability in timing. In conclusion, our results highlight the importance of a year-round perspective in identifying the most responsive characteristics or descriptors of thermal regimes in streams. The descriptors we provide herein can be applied across hydro-ecological regions to evaluate spatial and temporal patterns in thermal regimes. Evaluation of coherence and synchrony of different components of thermal regimes can facilitate identification of impacts of regional climate variability or local human or natural influences. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.

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