Forecasting Changes in Aquatic Systems and Resilience of Brook Trout

Summary of Phase 2 of the project (2014-2016):

The goal of this project is to improve natural resources management by providing effective, flexible, portable, and transparent modeling results and decision support tools to managers.

The objectives include:

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 policy
Build upon recent meetings with state agencies to apply the North Atlantic LCCsupported models within the state decision-making processes, such as revisions to state water quality criteria for stream temperature.

The Connecticut DEEP and Massachusetts DEP have agreed to participate in this pilot, which will be designed for adoption by interested managers across the region. Specific tasks will include: 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 is 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 project includes the following tasks:

Task 1: Hierarchical modeling framework to account for multiple scales and sources of uncertainty in climate change predictions. UMass will develop 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 will develop 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 will obtain an ‘envelope’ of downscaled global circulation data on precipitation and air temperature and incorporate 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 will develop a web-based application for examining effects of management scenarios on local population persistence.

LCC Staff Contact: Scott Schwenk

• University of Massachusetts Amherst

The Regional Stream Temperature/SHEDS workshop was held Feb 22-23 2017 in Hadley, MA. Forty-four people from state, federal and non-profit agencies attended the meeting. The project team explained the stream temperature database, the stream temperature model, and how the stream temperature model informs the occupancy model. Suggestion from participants were incorporated into v2.0 of "ICE".

In 2015, the project team launched "SHEDS" - the Spatial Hydro-Ecological Decision System. SHEDS is a web application that seamlessly links hydro-ecological datasets, models, and decision support systems. SHEDS provides tools for gaining insight, improving decision making, and supporting better management of hydro-ecological resources.

One of the components of SHEDS is "ICE" - the Integrated Catchment Explorer. ICE is a dynamic visualization tool for exploring catchment characteristics and environmental model predictions across the Northeast. Major products from this project, as well as related projects funded through other sources, have been incorporated into ICE. They include stream temperature models and brook trout occupancy models.

Previous updates and information:

• In September 2015 the research team requested and was granted a no-cost extension of the project until October 2016.
• In October 2014, the research team was awarded a grant totalling $110,000 to expand the existing tools and integrate the models with management and policy.
• The research team provided an update and overview of next steps to the LCC Technical Committee in June 2014, available here.
• In spring 2013, the group submitted a revised task list and timeline, available here.
• In June 2012, the group submitted a project update, available here.
• In March 2012, Ben Letcher gave a webinar on Modeling Salmonid Population Persistence Across the Streamscape, which has been archived and is available to stream.
• In January 2012, a meeting was held to review the status of this project, outline user needs, and to provide input for desired management applications. A writeup of that meeting is available here.

Phase 2 of this project began in 2014. The phase 2 project narrative is available here. The project proposal and award letter are available here.

The original task list and timeline, from fall 2011, is available here. Documentation from the initial phases of this research was created for the Population Persistence Modelling (Task 3) and Hydrology and Stream Temperature (Task 2) components of the project.

In the News

Brook trout study identifies top climate change pressure factor

NALCC-supported research published in Journal of Animal Ecology

NALCC Funding:   FY 2010: $420,000; FY 2014: $110,000

Other Funding:     FY 2010: $200,000; FY 2014: $185,651

Tools

"SHEDS" - Spatial Hydro-Ecological Decision System.

"ICE" - the Integrated Catchment Explorer

Journal Articles

Letcher, B.H., D.J. Hocking, K. O'Neil, A.R. Whiteley, K.H. Nislow, M.J. O'Donnell. A hierarchical model of daily stream temperature using air-water temperature synchronization, autocorrelation, and time lags. PeerJ 4:e1727; DOI 10.7717/peerj.1727

Yoichiro Kanno, B.H. Letcher, A. L. Rosner, K. P. O’Neal, and Keith H. Nislow. 2015. Environmental Factors Affecting Brook Trout Occurrence in Headwater Stream Segments. Transactions of the American Fisheries Society 144:373–382.

Letcher, B.H., P. Schueller, R. Bassar, K.H. Nislow, J.A. Coombs, K. Sakrejda, M. Morrissey, D. Sigourney, A.R. Whitely, M. O'Donnell, T. Dubreuil. In press. Robust estimates of environmental effects on population vital rates: an integrated capture-recapture model of seasonal brook trout growth, survival and movement in a stream network. Journal of Animal Ecology. doi: 10.1111/1365-2656.12308

Kanno,Y., Letcher, B.H., Hitt, N., Boughton, D., Wofford, J., and Zipkin, E. in Press. Seasonal weather patterns drive population vital rates and persistence in a stream fish. Global change biology

Kanno, Y, B. H. Letcher, J.C. Vokoun and E.F. Zipkin, 2014. Spatial variability in survival of adult brook trout within two intensively surveyed headwater stream networks, Canadian Journal of Fisheries and Aquatic Sciences 71: 1010-1019.

Zipkin,E., J. Thorson, K. See, H. Lynch, E. Grant, Y. Kanno, R. Chandler, B.H. Letcher, and J. Royle. 2014. Modeling structured population dynamics using data from unmarked individuals. Ecology: 95(1) doi:10.1890/13-1131.1

Kanno, Y., B.H. Letcher, J.A. Coombs, K.H. Nislow, and A.R. Whiteley. 2014. Linking movement and reproductive history of brook trout to assess habitat connectivity in a heterogenous stream network. Freshwater Biology 59: 142-154.

Kanno, Y., J. C. Vokoun, and B. Letcher. 2013. Paired stream-air temperature measurements reveal fine-scale thermal heterogeneity within headwater brook trout streams networks. River Research and Applications 10.1002/rr.

Whiteley, A; Coombs, J; Hudy, M; Robinson, Z; Colton, A; Nislow, K; Letcher, B.H. 2013.  Fragmentation and patch size shape genetic structure of brook trout populations. Canadian Journal of Fisheries and Aquatic Sciences. 70(5): 678-688, 10.1139/cjfas-2012-0493.

Kanno, Y., J. C. Vokoun, K. E. Holsinger, and B. H. Letcher. 2012. Estimating size-specific brook trout abundance in continuously sampled headwater streams using Bayesian mixed models with zero inflation and overdispersion. Ecology of Freshwater Fish:1–16.

Sigourney, D. B., S. B. Munch, and B. H. Letcher. 2012. Combining a Bayesian nonparametric method with a hierarchical framework to estimate individual and temporal variation in growth. Ecological Modelling 247:125–134.

Steinschneider, S., A. Polebitski, C. Brown, and B. H. Letcher. 2012. Toward a statistical framework to quantify the uncertainties of hydrologic response under climate change. Water Resources Research 48:W11525.

Whiteley, A. R., J. a. Coombs, M. Hudy, Z. Robinson, K. H. Nislow, and B. H. Letcher. 2012. Sampling strategies for estimating brook trout effective population size. Conservation Genetics 13:627-637.

Presentations

Presentation: Forecasting Changes in Aquatic Systems and Brook Trout - Integrating Stream Science Meeting 3-14-2013