The objective of this project was to develop tools to assist managers in protecting and restoring streams for brook trout and other aquatic resources in the face of threats such as climate change and development.
Summary of Phase 2 of the project (2014-2016):The goal of the second phase of this project was to improve natural resources management by providing effective, flexible, portable, and transparent modeling results and decision support tools to managers.
The objectives included:
1) Expand existing tools to additional portions of LCC region a) Extend the stream temperature and stream flow models to the full geographic area of the North Atlantic LCC, plus the headwaters of the Atlantic-draining watersheds (e.g., Chesapeake, Delaware, Hudson). b) In coordination with the Eastern Brook Trout Joint Venture and other researchers studying brook trout, expand the brook trout occupancy models to the same region as the stream temperature and flow models.
2) Integrate models with management and policyBuild upon recent meetings with state agencies to apply the North Atlantic LCC-supported models within the state decision-making processes, such as revisions to state water quality criteria for stream temperature.
The Connecticut DEEP and Massachusetts DEP agreed to participate in this pilot, which was designed for adoption by interested managers across the region. Specific tasks included: a) further adapting stream and fish models; b) customizing maps and graphics for decision support; c) modifying the existing map viewer for prioritization of watersheds; and d) exploring the potential for real-time updates of model results based on state-provided data.
Summary of Phase 1 of the project (2011-2014):The objective of this project was to develop a web-based decision support system for evaluating effects of alternative management scenarios on local population persistence of brook trout under different climate change scenarios. The first phase of the project included the following tasks:
Task 1: Hierarchical modeling framework to account for multiple scales and sources of uncertainty in climate change predictions. UMass developed the theory and application of a hierarchical Bayesian model to forecast local (catchment scale) population persistence of brook trout.
Task 2: Statistical models to predict stream flow and temperature based on air temperature and precipitation. UMass developed an empirical model for the relationship between air temperature and water temperature as a function of local environmental conditions.
Task 3: Incorporate climate change forecasts into population persistence models. UMass obtained an ‘envelope’ of downscaled global circulation data on precipitation and air temperature and incorporated these into the models in Task 1 using relationships from Task 2 in order to forecast local population persistence across climate change scenarios.
Task 4: Develop a decision support system for evaluating effects of alternate management strategies in the face of climate change. UMass developed a web-based application for examining effects of management scenarios on local population persistence.
This project was co-funded by the North Atlantic Landscape Conservation Cooperative and Northeast Climate Adaptation Science Center.
