Climate change forecasts for eastern salmonids

Science Center Objects

Small streams in forests are likely to see dramatic shifts as global climate change influences air temperature and rain patterns. We have already seen warmer stream temperatures as air temperatures increase in summer in the Northeastern US. The intensity and duration of floods and droughts are also expected to magnify as future rain patterns shift. This project will evaluate how stream temperature and flow relate to air temperature and precipitation and will use these relationships to predict future stream temperatures and flows.

We will also study how fish populations respond to variation in stream temperatures and flows. Do fish get bigger or smaller when the water is warmer? Are size changes different in different seasons? How does the amount of water in different seasons affect fish survival? We will use mathematical models to describe these relationships and will use the models to understand how fish populations will respond to future stream flow and temperature. This information will be very useful to people who make decisions about natural resource management in small streams.

Global climate change (GCC) presents a major challenge to the conservation and management of fish and wildlife species.  Assessing likely effects of GCC on plant and animal species will be even more challenging than most ecological modeling because new sources of uncertainty will compound our often incomplete understanding of the interacting and propagating effects of multiple sources of existing uncertainty.  We contend that an effective assessment of GCC effects must account explicitly for existing and new sources of uncertainty and how they combine to generate variable levels of confidence in predictions.  Because of the limitations of climate change modeling and other uncertainties that limit the value of mean or “best guess” estimates, risk based methods are increasingly recognized as the appropriate planning approach (Johnson and Weaver 2009).  But risk assessment and management require estimates of probabilities associated with outcomes, which are subject to the multiple sources of uncertainty.  Recent developments in hierarchical Bayesian modeling present a novel approach to  account explicitly for multiple, interacting sources of uncertainty (Smith and Marshall 2008;Bertorelle et al. 2004;Clark et al. 2005).  In addition to dealing with uncertainty, these models can handle very complex, multilayered dynamics that characterize coupled physical/biological systems.  We propose to develop hierarchical models of linked physical/biological processes for assessment of stream fish response to GCC.

The study has three main objectives:

Hierarchical modeling framework to account for multiple scales and sources of uncertainty in climate change predictions.  This approach will be easily adaptable to other stream biota.  In addition, the general hierarchical modeling approach could be applied broadly to any biological system.  We anticipate that Phase II of this proposal (years 4-6) would focus on transferring the approach to other systems.

Statistical model to predict stream flow and temperature based on physical landscape properties.  This model will also have broad applicability beyond the scope of this proposal.  As part of this proposal, the model will provide predictions specific to the range of brook trout and Atlantic salmon.  As with the hierarchical modeling approach, we expect that Phase II of this proposal could develop the model further to apply to most streams nationwide.

Web-based GIS tool for catchment prioritization and evaluation of conservation strategies.  This will be the major application developed for use by managers in this proposal. We will work iteratively with managers to improve functionality and ease of use.

Screenshot of the Interactive Catchment Explorer v2 smaller

The Interactive Catchment Explorer ( allow interactive exploration of environmental data and model output.

(Credit: Ben Letcher, USGS Leetown Science Center. Public domain.)