2009 Progress Report: Predicting Relative Risk of Invasion by Saltcedar and Mud Snails in River Networks Under Different Scenarios of Climate Change and Dam Operations in the Western United StatesEPA Grant Number: R833833
Title: Predicting Relative Risk of Invasion by Saltcedar and Mud Snails in River Networks Under Different Scenarios of Climate Change and Dam Operations in the Western United States
Investigators: Poff, N. LeRoy , Auble, Gregor T. , Bledsoe, Brian P. , Dean, Denis , Friedman, Jonathan , Lytle, David , Merritt, David M. , Purkey, David , Raff, David A. , Shafroth, Patrick B.
Current Investigators: Poff, N. LeRoy , Auble, Gregor T. , Bledsoe, Brian P. , Friedman, Jonathan , Lytle, David , Merritt, David M. , Purkey, David , Raff, David A. , Shafroth, Patrick B.
Institution: Colorado State University , Oregon State University , Stockholm Environmental Institute , U.S. Bureau of Reclamation , U.S. Forest Service , United States Geological Survey [USGS]
EPA Project Officer: Hiscock, Michael
Project Period: July 1, 2008 through June 30, 2012 (Extended to June 30, 2013)
Project Period Covered by this Report: July 1, 2008 through June 30,2009
Project Amount: $599,748
RFA: Ecological Impacts from the Interactions of Climate Change, Land Use Change and Invasive Species: A Joint Research Solicitation - EPA, USDA (2007) RFA Text | Recipients Lists
Research Category: Global Climate Change , Aquatic Ecosystems , Ecosystems , Climate Change
Objective:This project seeks to predict the establishment and spread of invasive species in rivers subject to novel climatic conditions. Changes in temperature and precipitation are expected to combine with human water needs to alter flow regimes in many watersheds. Thermal shifts and novel discharge patterns may then influence population and community processes, potentially disfavoring native species while facilitating invasion by harmful non-natives.
Progress Summary:During this stage of project development, we focused on determining a suitable river network for the study area. We considered the climatic, topographic, biogeographic and anthropogenic attributes of several candidate river networks before deciding to implement our research in the Upper Green River system.
We conducted two group meetings at Colorado State University to facilitate discussion of the priorities for the hydrologic, geomorphic and biological model components. During these meetings, we agreed to adopt methodology developed by the US Bureau of Reclamation for downscaling the output of general circulation models (run under several development scenarios) to an ecologically meaningful scale. We also determined that the WEAP (Watershed Evaluation And Planning) model could provide sufficiently detailed hydrologic representations for our purposes, and that further spatiotemporal disaggregation would be unnecessary.
Following these decisions, parameterization of the WEAP model began. This process involved the collection of various spatial data layers required to generate this semi-distributed model’s rainfall-runoff predictions. In addition to physiographic (temperature, precipitation intensity, elevation, soils, cover types, etc.) data, the WEAP model also requires information concerning the operation of any modeled water infrastructure. During this reporting period, the geomorphic classification system we proposed to use as a means of subdividing the drainage network into habitat units with similar physical form was also under development by members of Bledsoe’s group. Collaboration between project members and those responsible for its progression ensured that it would adequately meet the project needs.
Paralleling the progress toward determining a study area, deciding on a methodology for deriving climate inputs, agreeing on the spatiotemporal scale and resolution of the hydrologic model component, and coding and testing of the geomorphic model component, members of Poff’s group and the U.S. Geological Survey researched and debated the various options for modeling the invasion dynamics. Our emphasis during this reporting period has been a careful assessment of the tradeoffs and benefits associated with, for example, static statistical representations of invasion versus analytical or algorithmic ones that include explicit representations of population processes. In particular, when comparing strategies for the biological model component, project members debated the relative importance of data requirements, computational and conceptual tractability, representation of uncertainty and ease of interpreting results.