Pacific lamprey Entosphenus tridentatus is an anadromous fish native to the Pacific Northwest of the USA. That has declined substantially over the last 40 years. Effective conservation of this species will require an understanding of the habitat requirements for each life history stage. Because its life cycle contains extended freshwater rearing (3-8 years), the larval stage may be a critical factor limiting abundance of Pacific lamprey. The objective of our study was to estimate the influence of barriers and habitat characteristics on the catch-per-uniteffort (CPUE) of larval Pacific lamprey in the Willamette River Basin, Oregon, USA. We sampled lampreys at multiple locations in wadeable streams throughout the basin in 2011-13 and used an information theoretic approach to examine the relative influence of fine-and large-scale predictors of CPUE. Pacific lamprey was observed across the basin, but its relative abundance appeared to be limited by the presence of natural and artificial barriers in some sub-basins. Lower velocity habitats such as off-channel areas and pools contained higher densities of larval lamprey; mean Pacific lamprey CPUE in off-channel habitats was 4 and 32 times greater than in pools and riffles respectively. Restoration and conservation strategies that improve fish passage, enhance natural hydrologic and depositional processes and increase habitat heterogeneity will likely benefit larval Pacific lamprey.
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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.