Using a Food Web Model to Inform the Design of River Restoration
Author | : Joseph R. Benjamin |
Publisher | : |
Total Pages | : 24 |
Release | : 2018 |
ISBN-13 | : OCLC:1119519598 |
ISBN-10 | : |
Rating | : 4/5 ( Downloads) |
Download or read book Using a Food Web Model to Inform the Design of River Restoration written by Joseph R. Benjamin and published by . This book was released on 2018 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the decline of Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss), habitat restoration actions in freshwater tributaries have been implemented to improve conditions for juveniles. Typically, physical (for example, hydrologic and engineering) based models are used to design restoration alternatives with the assumption that biological responses will be improved with changes to the physical habitat. Biological models rarely are used. Here, we describe simulations of a food web model, the Aquatic Trophic Productivity (ATP) model, to aid in the design of a restoration project in the Methow River, north-central Washington. The ATP model mechanistically links environmental conditions of the stream to the dynamics of river food webs, and can be used to simulate how alternative river restoration designs influence the potential for river reaches to sustain fish production. Four restoration design alternatives were identified that encompassed varying levels of side channel and floodplain reconnection and large wood addition. Our model simulations suggest that design alternatives focused on reconnecting side channels and the adjacent floodplain may provide the greatest increase in fish capacity. These results were robust to a range of discharge and thermal regimes that naturally occur in the Methow River. Our results suggest that biological models, such as the ATP model, can be used during the restoration planning phase to increase the effectiveness of restoration actions. Moreover, the use of multiple modeling efforts, both physical and biological, when evaluating restoration design alternatives provides a better understanding of the potential outcome of restoration actions.