The occurrence of fish species may be strongly influenced by a stream's thermal regime (magnitude, frequency, variation, and timing). For instance, magnitude and frequency provide information about sublethal temperatures, variability in temperature can affect behavioral thermoregulation and bioenergetics, and timing of thermal events may cue life history events, such as spawning and migration. We explored the relationship between thermal regimes and the occurrences of native Bull Trout Salvelinus confluentus and nonnative Brook Trout Salvelinus fontinalis and Brown Trout Salmo trutta across 87 sites in the upper Klamath River basin, Oregon. Our objectives were to associate descriptors of the thermal regime with trout occurrence, predict the probability of Bull Trout occurrence, and estimate upper thermal tolerances of the trout species. We found that each species was associated with a different suite of thermal regime descriptors. Bull Trout were present at sites that were cooler, had fewer high‐temperature events, had less variability, and took longer to warm. Brook Trout were also observed at cooler sites with fewer high‐temperature events, but the sites were more variable and Brook Trout occurrence was not associated with a timing descriptor. In contrast, Brown Trout were present at sites that were warmer and reached higher temperatures faster, but they were not associated with frequency or variability descriptors. Among the descriptors considered, magnitude (specifically June degree‐days) was the most important in predicting the probability of Bull Trout occurrence, and model predictions were strengthened by including Brook Trout occurrence. Last, all three trout species exhibited contrasting patterns of tolerating longer exposures to lower temperatures. Tolerance limits for Bull Trout were lower than those for Brook Trout and Brown Trout, with contrasts especially evident for thermal maxima. Our results confirm the value of exploring a suite of thermal regime descriptors for understanding the distribution and occurrence of fishes. Moreover, these descriptors and their relationships to fish should be considered with future changes in land use, water use, or climate. Received March 4, 2016; accepted July 27, 2016 Published online October 11, 2016
We evaluated the probability of detecting larval lampreys using different methods of backpack electrofishing in wadeable streams in the U.S. Pacific Northwest. Our primary objective was to compare capture of lampreys using electrofishing with standard settings for salmon and trout to settings specifically adapted for capture of lampreys. Field work consisted of removal sampling by means of backpack electrofishing in 19 sites in streams representing a broad range of conditions in the region. Captures of lampreys at these sites were analyzed with a modified removalsampling model and Bayesian estimation to measure the relative odds of capture using the lamprey-specific settings compared with the standard salmonid settings. We found that the odds of capture were 2.66 (95% credible interval, 0.87-78.18) times greater for the lamprey-specific settings relative to standard salmonid settings. When estimates of capture probability were applied to estimating the probabilities of detection, we found high (>0.80) detectability when the actual number of lampreys in a site was greater than 10 individuals and effort was at least two passes of electrofishing, regardless of the settings used. Further work is needed to evaluate key assumptions in our approach, including the evaluation of individual-specific capture probabilities and population closure. For now our results suggest comparable results are possible for detection of lampreys by using backpack electrofishing with salmonid-or lamprey-specific settings.
Intermittent and ephemeral streams represent more than half of the length of the global river network. Dryland freshwater ecosystems are especially vulnerable to changes in human-related water uses as well as shifts in terrestrial climates. Yet, the description and quantification of patterns of flow permanence in these systems is challenging mostly due to difficulties in instrumentation. Here, we took advantage of existing stream temperature datasets in dryland streams in the northwest Great Basin desert, USA, to extract critical information on climate-sensitive patterns of flow permanence. We used a signal detection technique, Hidden Markov Models (HMMs), to extract information from daily time series of stream temperature to diagnose patterns of stream drying. Specifically, we applied HMMs to time series of daily standard deviation (SD) of stream temperature (i.e., dry stream channels typically display highly variable daily temperature records compared to wet stream channels) between April and August (2015-2016). We used information from paired stream and air temperature data loggers as well as co-located stream temperature data loggers with electrical resistors as confirmatory sources of the timing of stream drying. We expanded our approach to an entire stream network to illustrate the utility of the method to detect patterns of flow permanence over a broader spatial extent. We successfully identified and separated signals characteristic of wet and dry stream conditions and their shifts over time. Most of our study sites within the entire stream network exhibited a single state over the entire season (80%), but a portion of them showed one or more shifts among states (17%). We provide recommendations to use this approach based on a series of simple steps. Our findings illustrate a successful method that can be used to rigorously quantify flow permanence regimes in streams using existing records of stream temperature.
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