Before–after, control–impact (BACI) experimental designs are commonly used in large-scale environmental experiments, but these designs can be confounded by location and time interactions. Staircase designs, where replicate treatments are staggered temporally, have been suggested as an alternative to BACI designs. We performed a simulation study based on data from an ongoing watershed-scale restoration experiment within three streams to test the effectiveness of adding large wood to increase habitat complexity and abundance and productivity of juvenile steelhead (Oncorhynchus mykiss). We compared the power of two asymmetric BACI (aBACI) designs with two staircase designs for detecting changes in the density of steelhead (fish·m–2). A staircase design where treatments were temporally staggered in one treatment section in each stream had the highest power and best precision, especially when the innate spatial and temporal variances of steelhead density were large. A traditional BACI performed the worst, and a variation on another BACI and staircase design had intermediate performance. Multistream staircase designs are also more logistically and economically feasible and can maximize learning by replicating experiments across different stream types.

Before-after-control-impact (BACI) experimental designs are commonly used in large-scale experiments to test for environmental impacts. However, high natural variability of environmental conditions and populations, and low replication in both treatment and control areas in time and space hampers detection of responses. We compare the power of two asymmetric BACI (aBACI) designs to two staircase designs for detecting changes in juvenile steelhead ( Oncorhynchus mykiss ) abundance associated with a watershed-scale stream restoration experiment. We performed a simulation study to estimate the effect of a 25% increase in steelhead abundance using spatial and temporal estimates of variance from an ongoing study, and determined the power of each design. Experimental designs were then applied to three streams and each stream was composed of three 4 km long sections . We compared the power of a single treatment section in one stream (BACI-1), three simultaneous treatments of all sections in one stream (BACI-3), three sequential treatments in one stream (STAIRCASE-1), and three sequential treatments in one section in each stream (STAIRCASE-3). All designs had ≥ 94% power to detect a 25% increase in abundance assuming average variance. Under worst-case variance (i.e., upper 95% confidence limits of historical variance estimates), the STAIRCASE-3 design outperformed the BACI-1, BACI-3, and STAIRCASE-1 designs (i.e., 77%, 41%, 8%, and 33% power respectively). All the designs estimated the effect of the simulated 25% abundance increase, but the length of the confidence interval was much shorter for the STAIRCASE-3 design compared to the other designs, which had confidence intervals 58-596% longer. The STAIRCASE-3 design continued to have high power (88%) to detect a 10% change in abundance, but the power of the other designs was much lower (range 34-56%). Our study demonstrates that staircase designs can have significant advantages over BACI designs and therefore should be more widely used for testing environmental impacts.

Environmental stressors associated with human land and water-use activities have degraded many riparian ecosystems across the western United States. These stressors include (i) the widespread expansion of invasive plant species that displace native vegetation and exacerbate streamflow and sediment regime alteration; (ii) agricultural and urban development in valley bottoms that decouple streams and rivers from their floodplains and reduce instream wood recruitment and retention; and (iii) flow modification that reduces water quantity and quality, degrading aquatic habitats. Here we apply a novel drainage network model to assess the impacts of multiple stressors on reach-scale riparian condition across two large U.S. regions. In this application, we performed a riparian condition assessment evaluating three dominant stressors: (1) riparian vegetation departure from historical condition; (2) land-use intensity within valley bottoms; and (3) floodplain fragmentation caused by infrastructure within valley bottoms, combining these stressors in a fuzzy inference system. We used freely available, geospatial data to estimate reach-scale (500 m) riparian condition for 52,800 km of perennial streams and rivers, 25,600 km in Utah, and 27,200 km in 12 watersheds of the interior Columbia River Basin (CRB). Model outputs showed that riparian condition has been at least moderately impaired across ≈70% of the streams and rivers in Utah and ≈49% in the CRB. We found 84% agreement (Cohen's ĸ = 0.79) between modeled reaches and field plots, indicating that modeled riparian condition reasonably approximates on-the-ground conditions. Our approach to assessing riparian condition can be used to prioritize watershed-scale floodplain conservation and restoration by providing network-scale data on the extent and severity of riparian degradation. The approach that we applied here is flexible and can be expanded to run with additional riparian stressor data and/or finer resolution input data.

Despite substantial effort and resources being invested in habitat rehabilitation for stream fishes, mechanistic approaches to designing and evaluating how habitat actions influence the fish populations they are intended to benefit remain rare. We used a net rate of energy intake (NREI) model to examine expected and observed changes in energetic habitat quality and capacity from woody debris additions in a 40 m long study reach being treated as part of a restoration experiment in Asotin Creek, Washington. We simulated depths, velocities, and NREI values for pre-treatment, expected, and post-treatment habitat conditions, and we compared pre-treatment versus expected and pre-treatment versus post-treatment simulation results. The pre-treatment versus expected topography simulations suggested treatment would increase energetically favorable area, mean NREI, and capacity in the study reach. Pre-treatment versus post-treatment comparisons yielded similar predictions, though to smaller magnitudes, likely due to the short time span and single high-flow event between pre- and post-treatment data collection. We feel the NREI modelling approach is an important tool for improving the efficacy of habitat rehabilitation actions for stream fishes.

Floodplain riparian ecosystems support unique vegetation communities and high biodiversity relative to terrestrial landscapes. Accordingly, estimating riparian ecosystem health across landscapes is critical for sustainable river management. However, methods that identify local riparian vegetation condition, an effective proxy for riparian health, have not been applied across broad, regional extents. Here we present an index to assess reach-scale (500 m segment) riparian vegetation condition across entire drainage networks within large, physiographically-diverse regions. We estimated riparian vegetation condition for 53,250 km of perennial streams and rivers, 25,685 km in Utah, and 27,565 km in twelve watersheds of the interior Columbia River Basin (CRB), USA. We used nationally available, existing land cover classification derived from 30 m Landsat imagery (LANDFIRE EVT) and a modeled estimate of pre-European settlement land cover (LANDFIRE BpS). The index characterizes riparian vegetation condition as the ratio of existing native riparian vegetation cover to pre-European settlement riparian vegetation cover at a given reach. Roughly 62% of Utah and 48% of CRB watersheds showed significant (>33%) to large (>66%) departure from historic condition. Riparian vegetation change was predominantly caused by human land-use impacts (development and agriculture), or vegetation change (native riparian to invasive or upland vegetation types) that likely resulted from flow and disturbance regime alteration. Through comparisons to ground-based classification results, we estimate the existing vegetation component of the index to be 85% accurate. Our assessments yielded riparian condition maps that will help resource managers better prioritize sites and treatments for reach-scale conservation and restoration activities.

Substantial research effort has been devoted to understanding stream-dwelling salmonids’ use of summer rearing and growth habitat, with a subset of studies focusing on foraging position selection and the energetic trade-offs of differential habitat use. To date, however, cost–benefit analyses for most foraging model studies have focused on small sampling areas such as individual habitat units. To address this knowledge gap, we applied a mechanistic foraging model to 22 stream reaches (100–400 m) from two watersheds within the Columbia River Basin. We found a strong, positive correlation (R2= 0.61, p < 0.001) between predicted carrying capacities and observed fish densities. Predicted proportion of suitable habitat was weakly correlated with observed fish density (R2= 0.18, p = 0.051), but the mean net rate of energy intake prediction in sampling reaches was not a significant predictor of observed fish biomass. Our results suggest spatial configuration of habitat, in addition to quantity and quality, is an important determinant of habitat use. Further, carrying capacity predicted by the model shows promise as a habitat metric. We also evaluated the feasibility of applying this data-intensive modeling approach in a large-scale monitoring program to examine habitat quality and quantity. Though the approach can be computationally expensive, we feel the model’s ability to integrate physical habitat metrics (e.g., depth, velocity) with important biological considerations like food availability and temperature is a benefit that far outweighs associated costs. We feel this modeling approach has great potential as a tool to help understand habitat use in drift-feeding fishes.

We conducted simulations to compare the precision and bias of survival estimates from Cormack-Jolly-Seber (CJS) and Barker models to known parameter values based on empirical data for steelhead/resident Rainbow Trout Oncorhynchus mykiss from the John Day River, Oregon. We simulated seasonal differences in recapture and survival rates, and we varied the number of fish tagged, recapture and resight rates, sample site size, and fish movement (migratory or resident). Survival estimates from the Barker model had higher precision and lower or equal bias in comparison with estimates from the CJS model under almost all simulation scenarios. The precision of Barker survival estimates increased the most as the number of tagged fish increased from 50 to 200 (CV D 0.4-0.09). The Barker model's superior performance was dependent on the availability of resight data; such data are becoming more readily available, especially in places where large numbers of individuals are PIT-tagged and where an interrogation infrastructure exists (e.g., Columbia River basin). Tagging of 75-100 fish/site during high-capture periods (e.g., summer and fall) and focusing on the resighting of fish with fixed or mobile interrogators during low-capture periods (i.e., winter and spring) may be the most cost-effective strategy for improving estimates of juvenile steelhead survival.

Hybridization and introgression between introduced and native salmonids threaten the continued persistence of many inland cutthroat trout species. Environmental models have been developed to predict the spread of introgression, but few studies have assessed the role of propagule pressure. We used an extensive set of fish Stocking records and geographic information system (GIS) data to produce a spatially explicit index of potential propagule pressure exerted by introduced rainbow trout in the Upper Kootenay River, British Columbia, Canada. We then used logistic regression and the information-theoretic approach to test the ability of a set of environmental and spatial variables to predict the level of introgression between native westslope cutthroat trout and introduced rainbow trout. Introgression was assessed using between four and seven co-dominant, diagnostic nuclear markers at 45 sites in 31 different streams. The best model for predicting introgression included our GIS propagule pressure index and an environmental variable that accounted for the biogeoclimatic zone of the site (r2=0.62). This model was 1.4 times more likely to explain introgression than the next-best model, which consisted of only the propagule pressure index variable. We created a composite model based on the model-averaged results of the seven top models that included environmental, spatial, and propagule pressure variables. The propagule pressure index had the highest importance weight (0.995) of all variables tested and was negatively related to sites with no introgression. This study used an index of propagule pressure and demonstrated that propagule pressure had the greatest influence on the level of introgression between a native and introduced trout in a human-induced hybrid zone.

Introgressive hybridization (introgression) between native westslope cutthroat front Oncorhynchus clarkii lewisi and introduced rainbow front O. mykiss in the tipper Kootenay River, British Columbia. appears to be recent and is partly attributed to rainbow trout stocking in Koocanusa Reservoir starting in 1988, fit 1998, rainbow trout stocking was stopped or replaced with the stocking of triploids throughout the watershed. The goal of this research was to determine the effect of the change in stocking practices oil the level of introgression between westslope cutthroat trout and rainbow trout. We monitored 14 sites front 1999 to 2007 using four co-dominant, diagnostic nuclear markers. Sample sites were categorized its (1) open if no fish migration barriers existed between the site and the reservoir or (2) closed if migration barriers were present between the site and the reservoir. We classified fish its pure westslope cutthroat trout if no rainbow trout alleles were detected fish were classified its hybrids if they had in least one rainbow trout allele present, We also classified fish into parental and hybrid types based on their multilocus genotypes. Open sites had more hybrids (15.8%) than closed sites (4.8%; chi(2) = 23.38. df = 1, P < 0.0001). Westslope cutthroat trout backcrosses were the most common hybrid genotype in both Open and closed sites. At open sites near the reservoir, introgression levels stayed relatively high (20-30%) and pure rainbow trout and rainbow trout backcross individuals were common. Introgression significantly increased at two of three Sites surveyed at intermediate distances upstream front the reservoir (i.e.. 27-87 km). The new, stocking, program does not appear to have reduced introgression or prevented the spread of hybrid individuals ill the upper Kootenay River, and more active management strategies will be required to prevent further introgression and loss of unique westslope Cutthroat trout populations.