Presentation Title

Evaluating uncertainty from different sources for population viability analysis under climate change scenarios – what does management need to know? A case study of threatened Chinook salmon

Session Title

Session S-08D: Salmon Recovery: Implementation and Progress I

Conference Track

Species and Food Webs

Conference Name

Salish Sea Ecosystem Conference (2014 : Seattle, Wash.)

Contributing Repository

Digital content made available by University Archives, Heritage Resources, Western Libraries, Western Washington University.

Presenter/Author Information

Lisa G. CrozierFollow

Start Date

1-5-2014 5:00 PM

End Date

1-5-2014 6:30 PM

Abstract

Incorporating climate change projections into recovery planning and ESA Section 7 consultations has become a management imperative. But uncertainty in our biological conclusions stems from many different sources – stochasticity in population dynamics in general, biological sensitivity to climate, and projections in driving factors such as stream flow and temperature. Climate projections themselves contain uncertainty from hydrological modeling, downscaling techniques, GCM process error, and emissions futures. For migratory species, additional uncertainty stems from differential impacts at multiple life stages (e.g., freshwater versus ocean stages). We characterized these various sources of uncertainty in a case study of population viability of Snake River Chinook salmon. We explored over 100 climate scenarios for each of 9 populations with individual sensitivity to climate drivers. We identified the most important areas of uncertainty for targeting restoration or management decisions. For all populations, the uncertainty in future ocean projections outweighed all other sources. The next crucial factor was the biological assessment of the relative population sensitivity to temperature versus stream flow. Uncertainty in climate projections from downscaling methods, GCM or emissions behavior was much less important for management decisions for most populations; however, a subset of populations might either increase or decline depending on future patterns in precipitation. This ranking of uncertainty is useful because it facilitates focused research on studies that will most affect management decisions, and thus have the greatest conservation impact.

Rights

This resource is displayed for educational purposes only and may be subject to U.S. and international copyright laws. For more information about rights or obtaining copies of this resource, please contact University Archives, Heritage Resources, Western Libraries, Western Washington University, Bellingham, WA 98225-9103, USA (360-650-7534; heritage.resources@wwu.edu) and refer to the collection name and identifier. Any materials cited must be attributed to the Salish Sea Ecosystem Conference Records, University Archives, Heritage Resources, Western Libraries, Western Washington University.

Language

English

Format

application/pdf

Type

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May 1st, 5:00 PM May 1st, 6:30 PM

Evaluating uncertainty from different sources for population viability analysis under climate change scenarios – what does management need to know? A case study of threatened Chinook salmon

Room 6C

Incorporating climate change projections into recovery planning and ESA Section 7 consultations has become a management imperative. But uncertainty in our biological conclusions stems from many different sources – stochasticity in population dynamics in general, biological sensitivity to climate, and projections in driving factors such as stream flow and temperature. Climate projections themselves contain uncertainty from hydrological modeling, downscaling techniques, GCM process error, and emissions futures. For migratory species, additional uncertainty stems from differential impacts at multiple life stages (e.g., freshwater versus ocean stages). We characterized these various sources of uncertainty in a case study of population viability of Snake River Chinook salmon. We explored over 100 climate scenarios for each of 9 populations with individual sensitivity to climate drivers. We identified the most important areas of uncertainty for targeting restoration or management decisions. For all populations, the uncertainty in future ocean projections outweighed all other sources. The next crucial factor was the biological assessment of the relative population sensitivity to temperature versus stream flow. Uncertainty in climate projections from downscaling methods, GCM or emissions behavior was much less important for management decisions for most populations; however, a subset of populations might either increase or decline depending on future patterns in precipitation. This ranking of uncertainty is useful because it facilitates focused research on studies that will most affect management decisions, and thus have the greatest conservation impact.