A lidar-based assessment of riparian shade and large wood potential in the Skagit River watershed,WA

Wild salmon stocks in the Pacific Northwest are imperiled by a variety of declining habitat factors, including riparian shade and in-channel large wood. In this paper, a relatively simple lidar model of the riparian canopy was used along anadromous streams in the Skagit River watershed in western Washington State, United States, to delineate where riparian trees were most lacking, and where restoration efforts would have the greatest benefit in terms of shade and large wood recruitment potential. Within a 45-m riparian buffer, 61% of riparian zones were currently incapable of delivering large wood to the stream. Current potential for large wood recruitment is greatest adjacent to stream edges and falls off rapidly with distance from the channel. Approximately 99% of large wood recruitment potential lies within 45 m of the channel edge, and 50% of the wood potential is within 9 m. A hypothetical canopy model in which all trees mature to a 100-year height would provide 18% more shade distributed over the entire watershed, and 90% more shade in the tributaries. Most of the potential gains in improved shade and large wood contributions are in agricultural areas, as opposed to forestry or urban land uses. The shade and large wood models were constructed from widely available geographic information system tools and are readily transferable to other watersheds with similar characteristics. Model outputs are intended for use in planning restoration projects, as an input to stream temperature models, and to inform policy on restoration priorities and regulatory buffer widths.     

Repeatability,Sensitivity, and Uncertainty Analyses of the BANCS Model Developed to Predict Annual Streambank Erosion Rates

Accelerated streambank erosion caused by channel instability can be the leading cause of sediment impairment of streams. Obtaining accurate streambank erosion rates for sediment budgeting and prioritizing mitigation efforts can be difficult and costly. One approach to quantifying streambank erosion rates is through the development and implementation of an empirically derived “Bank Assessment for Non‐point Source Consequences of Sediment” (BANCS) model. This study aims to improve the BANCS model application by evaluating repeatability between users and identifying sensitive and/or uncertain model inputs. Statistical analysis of streambank evaluations conducted by 10 different individuals suggests the implementation of the BANCS model may not be repeatable. This finding may be due to sensitive model inputs, such as streambank height and near‐bank stress level prediction method selection, and/or uncertain model inputs, such as bank material identification and the associated adjustment of erosion potential. Furthermore, it was found assessing streambanks as a group by obtaining a measure of central tendency from individual evaluations, as well as obtaining a higher level of training, may improve model implementation precision. Application of these suggestions may result in improved prediction of streambank erosion rates utilizing the BANCS model methodology.     

A Framework to Integrate Habitat Monitoring and Restoration with Endangered Insect Recovery

Monitoring is essential to track the long-term recovery of endangered species. Greater emphasis on habitat monitoring is especially important for taxa whose populations may be difficult to quantify (e.g., insects) or when true recovery (delisting) requires continuous species-specific habitat management. In this paper, we outline and implement a standardized framework to facilitate the integration of habitat monitoring with species recovery efforts. The framework has five parts: (1) identify appropriate sample units, (2) select measurable indicators of habitat requirements, (3) determine rating categories for these indicators, (4) design and implement appropriate data collection protocols, and (5) synthesize the ratings into an overall measure of habitat potential. Following these steps, we developed a set of recovery criteria to estimate habitat potential and initially assess restoration activities in the context of recovering an endangered insect, the Karner blue butterfly (Lycaeides melissa samuelis). We recommend basing the habitat potential grading scheme on recovery plan criteria, the latest information on species biology, and working hypotheses as needed. The habitat-based assessment framework helps to identify which recovery areas and habitat patches are worth investing in and what type of site-specific restoration work is needed. We propose that the transparency and decision-making process in endangered insect recovery efforts could be improved through adaptive management that explicitly identifies and tracks progress toward habitat objectives and ultimate population recovery.     

Channel Evolution Models as Predictors of Sediment Yield

This paper recounts our predictions of channel evolution of the Black Vermillion River (BVR) and sediment yields associated with the evolutionary sequence. Channel design parameters allowed for the prediction of stable channel form and coincident sediment yields. Measured erosion rates and basin‐specific bank erosion curves aided in prediction of the stream channel succession time frame. This understanding is critical in determining how and when to mitigate a myriad of instability consequences. The BVR drains approximately 1,062 km² in the glaciated region of Northeast Kansas. Once tallgrass prairie, the basin has been modified extensively for agricultural production. As such, channelization has shortened the river by nearly 26 km from pre‐European dimensions; shortening combined with the construction of numerous flow‐through structures have produced dramatic impacts on discharge and sediment dynamics. Nine stream reaches were established within three main tributaries of the BVR in 2007. Reaches averaged 490 m in length, were surveyed, and assessed for channel stability, while resurveys were conducted annually through 2010 to monitor change. This work illustrates the association of current stream state, in‐channel sediment contributions, and prediction of future erosion rates based on stream evolution informed by multiple models. Our findings suggest greater and more rapid sedimentation of a federal reservoir than has been predicted using standard sediment prediction methods.