Often researchers are tasked with describing a process in nature that remains hidden beneath layers of disaggregated information.  By developing a modeling framework that integrates these layers of data, researchers can gain an understanding of both the true process, and the measurement error associated with the individual layers.  Under the US Endangered Species Act (ESA), co-managers are required to develop recovery plans that measure the status of protected species relative to their recovery goals, but this effort remains difficult because the data collection varies across agencies, space and time.  Rather than ignore the uncertainty in these variable data streams, I will explicitly account for it through an integrated modeling framework.  With the collaboration from state, federal and tribal agencies, I will demonstrate how combining layers of data from many field offices will improve our understanding of specific metrics related to the recovery goals for loggerhead sea turtles and Chinook salmon, both of which are co-managed by NOAA fisheries.  For threatened loggerheads, trends in nest count abundance are the primary metric describing population status; however, the loggerhead’s complex life-history makes it difficult for co-managers to infer status beyond just a couple of years.  Using an integrated mixed-effect model, I will develop a method for improving long range forecasts of nest abundance by using a growth model to map indices of juvenile abundance from in-water surveys to future nest counts.  For spring/summer Chinook salmon, decreases in juvenile survival has been demonstrated to occur at low to moderate spawning abundances for many of the 31 threatened populations in the Snake River Basin; however, these analyses have failed to recognize the effects of measurement error in the adult spawner estimates.  Using a mixed-effect model, I will integrate all of the spawner abundance estimators into a single modeling framework, and determine whether explicitly accounting for measurement error weakens the argument of reduced juvenile survival for these threatened populations.  Aside from the modeling aspects of this proposal, this research represents the collaboration of numerous scientists and agencies who share a commitment to improving our understanding of protected species.  As the coordinator of these research efforts, I see this proposal as a valuable example of the gains that can be achieved through collaboration.


Project Members:

Brandon Chasco, Department of Fisheries and Wildlife, Oregon State University

Selina Heppell, Department of Fisheries and Wildlife, Oregon State University

James T. Thorson, National Oceanographic and Atmospheric Administration

Grant Thompson, National Oceanographic and Atmospheric Administration

Ben Dalziel, Department of Integrative Biology, Oregon State University


Funding Sources:

NOAA Fisheries/Sea Grant Population and Ecosystem Dynamics Fellowship