- Program Areas
- Installation Energy and Water
- Environmental Restoration
- Munitions Response
- Resource Conservation and Resiliency
- Natural Resources
- Infrastructure Resiliency
- Air Quality
- Weapons Systems and Platforms
Flow-Population Models for Tracking Non-Stationary Changes in Riparian and Aquatic Ecosystems
Dr. David Lytle | Oregon State University
Climate change is expected to alter temperature and precipitation patterns on military lands throughout the western United States. This will alter the timing, frequency, and magnitude of flood and drought events. These changes in streamflow regime will directly affect populations of aquatic organisms (fish, aquatic invertebrates, riparian vegetation) and indirectly affect stream‐dependent birds, reptiles, and mammals, including federally threatened and endangered species and other at-risk species. Although climate models as drivers of hydrologic models are becoming increasingly sophisticated in their ability to enable forecasting changes in streamflow regime at small spatial scales (e.g., <144 km2), current species population models do not accommodate the non-stationary effects that shifting flow regimes can exert on population trajectories and viability. Thus, a critical gap remains between our ability to model how climate change will alter streamflow regimes and our ability to predict how these changes will impact management‐sensitive aquatic and riparian organisms. The objective of this project is to fill this knowledge gap by designing, testing, and implementing flow‐population models that integrate non‐stationary flow regime dynamics with quantitative population models to forecast potential impacts on aquatic and riparian taxa.
This project will combine the: (1) development of novel flow‐population models for riparian vegetation, fish, and aquatic invertebrates; (2) parameterization of model vital rates using long-term datasets from military and other lands; and (3) implementation of models to forecast how changing climate regimes will affect aquatic populations across a suite of western U.S. military installations. For Objective 1, the team will build flow‐population models that are suitable for capturing the non‐stationary, stochastic dynamics that flow regimes exert on populations. Importantly, a “flow‐response guild” approach will be followed, in which groups of species that share similar responses to flow regime attributes will be modeled. Objective 2 involves the parameterization of models using data from aridland military installations and other long‐term sites. This data‐intensive objective will enable testing of model predictions and calibration of models so they directly apply to groups of species occurring on aridland military installations. In Objective 3, the team will use the modeling approach to forecast the ecological effects of changing streamflow regimes. This objective will explore future climate change scenarios and their effects on aquatic and riparian organisms.
This research will provide a critical link between landscape‐level climate projections and population responses of organisms. This link will enable researchers and managers to anticipate how climate‐driven changes to precipitation will change current distributions of aquatic and riparian organisms. The project also will produce ready‐to‐use web‐based tools for managers that will enable them to explore the consequences of proposed management actions on relevant flow‐response guilds, without requiring direct mastery of the underlying mathematical models. (Anticipated Project Completion - 2019)