The scientists found that local variability in stream habitat, such as water depth and instream cover, play a greater role in reducing the effects of timber harvest and climate change on trout than previously realized. Instream cover and shade improve trout survival by providing a place to hide from predators.
The Alsea Watershed Study Revisited in the Oregon Coast Range provided a unique opportunity to investigate and compare the stream temperature responses to contemporary forest harvesting practices (i.e., maintenance of riparian vegetation) with the impacts from historical (1960s) harvesting practices (i.e., no riparian vegetation).
To investigate effects of headwater logging on downstream coastal cutthroat trout (Oncorhynchus clarkii clarkii) populations, we monitored stream habitat and biotic indicators including biomass, abundance, growth, movement, and survival over 8 years using a paired-watershed approach.
To examine seasonal and spatial factors affecting prey consumption by Oncorhynchus trout, we examined trout diet from mainstem and tributary sites at Hinkle Creek, Oregon.
Little information is available on the effects of implanting 23-mm passive integrated transponder (PIT) tags in salmonids less than 90 mm fork length (FL). Using juvenile steelhead Oncorhynchus mykiss (range, 73–97 mm FL), we compared instantaneous growth rates and survival among three experimental groups: control, surgery with no tag, and surgery with tag.
The shape and configuration of branched networks influence ecological patterns and processes. Recent investigations of network influences in riverine ecology stress the need to quantify spatial structure not only in a two-dimensional plane, but also in networks. An initial step in understanding data from stream networks is discerning non-random patterns along the network. On the other hand, data collected in the network may be spatially autocorrelated and thus not suitable for traditional statistical analyses. Here we provide a method that uses commercially available software to construct an empirical variogram to describe spatial pattern in the relative abundance of coastal cutthroat trout in headwater stream networks. We describe the mathematical and practical considerations involved in calculating a variogram using a non-Euclidean distance metric to incorporate the network pathway structure in the analysis of spatial variability, and use a non-parametric technique to ascertain if the pattern in the empirical variogram is non-random.
Aquatic ecologists working in small streams are challenged with the task of identifying stream habitats, the spatial distribution and temporal persistence (i.e., rate of change) of habitat, and the timing and manner in which habitats are used by stream fishes. Because temporal variation of stream habitats and the mobility of stream fishes complicate species abundance-habitat association models (Van Horne 1983), the identification of high quality aquatic habitats is often problematic. In an attempt to assess habitat quality of a stream network in western Oregon, we evaluated the persistence of abundance patterns and habitat associations of coastal cutthroat trout Oncorhynchus clarkii clarkii by monitoring stream sections of high and low relative abundance for 13 months. Simultaneous habitat evaluations provided insight into factors affecting distribution patterns in main stem and tributary streams.
Glyphosate, aminomethylphosphonic acid (AMPA), imazapyr, sulfometuron methyl (SMM), and metsulfuron methyl (MSM) were measured in streamwater collected during and after a routine application of herbicides to a forestry site in Oregon’s Coast Range. Samples were collected at three stations: HIGH at the fish/no-fish interface in the middle of the harvest/spray unit; MID at the bottom of the unit; and LOW downstream of the unit. All herbicides were applied by helicopter in a single tank mix. AMPA, imazapyr, SMM, and MSM were not detected (ND) in any sample at 15, 600, 500, and 1000 ng/L, respectively. A pulse of glyphosate peaking at ≈62 ng/L manifested at HIGH during the application. Glyphosate pulses peaking at 115 ng/L (MID) and 42 ng/L (HIGH) were found during the first two post-application storm events 8 and 10 days after treatment (DAT), respectively: glyphosate was <20 ng/L (ND) at all stations during all subsequent storm events. All glyphosate pulses were short-lived (4 to 12 h). Glyphosate in baseflow was ≈25 ng/L at all stations 3 DAT and was still ≈25 ng/L at HIGH, but ND at the other stations, 8 DAT: subsequently, glyphosate was ND in baseflow at all stations. These results show that aquatic organisms were subjected to multiple short-duration, low-concentration glyphosate pulses corresponding to a cumulative time-weighted average (TWA) exposure of 6634 ng/L*h. Comparisons to TWA exposures associated with a range of toxicological endpoints for sensitive aquatic organisms suggests a margin of safety exceeding 100 at the experimental site, with the only potential exception resulting from the ability of fish to detect glyphosate via olfaction. For imazapyr, SMM, and MSM the NDs were at concentrations low enough to rule out effects on all organisms other than aquatic plants, and the low concentration and (assumed) pulsed nature of any exposure should mitigate this potential.
The effect of bedrock permeability and underlying catchment boundaries on stream base flow mean transit time (MTT) and MTT scaling relationships in headwater catchments is poorly understood. Here we examine the effect of bedrock permeability on MTT and MTT scaling relations by comparing 15 nested research catchments in western Oregon; half within the HJ Andrews Experimental Forest and half at the site of the Alsea Watershed Study. The two sites share remarkably similar vegetation, topography, and climate and differ only in bedrock permeability (one poorly permeable volcanic rock and the other more permeable sandstone). We found longer MTTs in the catchments with more permeable fractured and weathered sandstone
bedrock than in the catchments with tight, volcanic bedrock (on average, 6.2 versus 1.8 years, respectively). At the permeable bedrock site, 67% of the variance in MTT across catchments scales was explained by drainage area, with no significant correlation to topographic characteristics. The poorly permeable site had opposite scaling relations, where MTT showed no correlation to drainage area but the ratio of median flow path length to median flow path gradient explained 91% of the variance in MTT across seven catchment scales. Despite these differences, hydrometric analyses, including flow duration and recession analysis, and storm response analysis, show that the two sites share relatively indistinguishable hydrodynamic behavior. These results show that similar catchment forms and hydrologic regimes hide different subsurface routing, storage, and scaling behavior—a major issue if only hydrometric data are used to define hydrological similarity for assessing land use or climate change response.
In Part 1 of this two-part series, Hale and McDonnell (2016) showed that bedrock permeability controlled base flow mean transit times (MTTs) and MTT scaling relations across two different catchment geologies in western Oregon. This paper presents a process-based investigation of storage and release in the more permeable catchments to explain the longer MTTs and (catchment) area-dependent scaling. Our field-based study includes hydrometric, MTT, and groundwater dating to better understand the role of subsurface catchment storage in setting base flow MTTs. We show that base flow MTTs were controlled by a mixture of water from discrete storage zones: (1) soil, (2) shallow hillslope bedrock, (3) deep hillslope bedrock, (4) surficial alluvial plain, and (5) suballuvial bedrock. We hypothesize that the relative contributions from each component change with catchment area. Our results indicate that the positive MTT-area scaling relationship observed in Part 1 is a result of older, longer flow path water from the suballuvial zone becoming a larger proportion of streamflow in a downstream direction (i.e., with increasing catchment area). Our work suggests that the subsurface permeability structure represents the most basic control on how subsurface water is stored and therefore is perhaps the best direct predictor of base flow MTT (i.e., better than previously derived morphometric-based predictors). Our discrete storage zone concept is a process explanation
for the observed scaling behavior of Hale and McDonnell (2016), thereby linking patterns and processes at scales from 0.1 to 100 km2.