Modeling the effect of striped bass (Morone saxatilis) on the population viability of Sacramento River winter-run chinook salmon (Onchorhynchus tshawytscha)

We estimated the impact of striped bass (Morone saxatilis) predation on winter-run chinook salmon (Oncorhynchus tshawytscha) with a Bayesian population dynamics model using striped bass and winter-run chinook salmon population abundance data. Winter-run chinook salmon extinction and recovery probabilities under different future striped bass abundance levels were estimated by simulating from the posterior distribution of model parameters. The model predicts that if the striped bass population declines to 512,000 adults as expected in the absence of stocking, winter-run chinook salmon will have about a 28% chance of quasi-extinction (defined as three consecutive spawning runs of fewer than 200 adults) within 50 years. If stocking stabilizes the striped bass population at 700,000 adults, the predicted quasi-extinction probability is 30%. A more ambitious stocking program that maintains a population of 3 million adult striped bass would increase the predicted quasi-extinction probability to 55%. Extinction probability, but not recovery probability, was fairly insensitive to assumptions about density dependence. We conclude that winter-run chinook salmon face a serious extinction risk without augmentation of the striped bass population and that substantial increases in striped bass abundance could significantly increase the threat to winter-run chi-nook salmon if not mitigated by increasing winter chinook salmon survival in some other way.

Modeling red sea urchin (Strongylocentrotus franciscanus) growth using six growth functions

The growth of red sea urchins (Strongylocentrotus franciscanus) was modeled by using tag-recapture data from northern California. Red sea urchins (n=211) ranging in test diameter from 7 to 131 mm were examined for changes in size over one year. We used the function Jt+1 = Jt + f(Jt) to model growth, in which Jt is the jaw size (mm) at tagging, and Jt+1 is the jaw size one year later. The function f(Jt), represents one of six deterministic models: logistic dose response, Gaussian, Tanaka, Ricker, Richards, and von Bertalanffy with 3, 3, 3, 2, 3, and 2 minimization parameters, respectively. We found that three measures of goodness of fi t ranked the models similarly, in the order given. The results from these six models indicate that red sea urchins are slow growing animals (mean of 7.2 ±1.3 years to enter the fishery). We show that poor model selection or data from a limited range of urchin sizes (or both) produces erroneous growth parameter estimates and years-to-fishery estimates. Individual variation in growth dominated spatial variation at shallow and deep sites (F=0.246, n=199, P=0.62). We summarize the six models using a composite growth curve of jaw size, J, as a function of time, t: J = A(B – e–Ct) + Dt, in which each model is distinguished by the constants A, B, C, and D. We suggest that this composite model has the flexibility of the other six models and could be broadly applied. Given the robustness of our results regarding the number of years to enter the fishery, this information could be incorporated into future fishery management plans for red sea urchins in northern California.

Modeling the effect of snow on seasonal runoff within the Truckee River drainage basin

EXTRACT (SEE PDF FOR FULL ABSTRACT): We estimate monthly runoff for a 2-dimensional solution domain containing those areas tributary to Pyramid Lake, Nevada (the Truckee River drainage basin) at a 1-kilometer grid cell spacing. ... To calculate the effect of snow on the hydrologic system, we perform two experiments. In the first we assume that all precipitation falls as rain; in the second we assume that some precipitation falls as snow, thus available water is a combination of rain and snowmelt. We find that considering the effect of snow results in a more accurate representation of mean monthly flow rates, in particular the peak flow during the melt season in the Sierra Nevada. These preliminary results indicate that a relatively simple snow model can improve the representation of Truckee River basin hydrology, significantly reducing errors in modeled seasonal runoff.

Modeling North Pacific temperature and pressure changes from coastal tree-ring chronologies

Climate modeling using coastal tree-ring chronologies has yielded the first summer temperature reconstructions for coastal stations along the Gulf of Alaska and the Pacific Northwest. These land temperature reconstructions are strongly correlated with nearby sea surface temperatures, indicating large-scale ocean-atmospheric influences. Significant progress has also been made in modeling winter land temperatures and sea surface temperatures from coastal and shipboard stations. In addition to temperature, the pressure variability center over the central North Pacific Ocean (PAC), which is related to the strength and location of the Aleutian Low pressure system, could be extended using coastal tree rings.