Monte Carlo simulation of streamflow of the Salt River, Arizona

EXTRACT (SEE PDF FOR FULL ABSTRACT): Evaluations of the impact of climate change (such as a greenhouse effect) upon water resources should represent both the expected change and the uncertainty in that expectation. Since water resources such as streamflow and reservoir levels depend on a variety of factors, each of which is subject to significant uncertainty, it is desirable to formulate methods of representing that uncertainty in the forcing factors and from this determine the uncertainty in the response variables of interest. We report here progress in the representation of the uncertainty in climate upon the uncertainty in the estimated hydrologic response.

Evaluating the efficacy of managing West Coast groundfish resources through simulations

Management of West Coast groundfish resources by the Pacific Fishery Management Council involves Federal government and academic scientists conducting stock assessments, generally using the stock synthesis framework, applying the 40-10 rule to determine harvest guidelines for resources that are not overfished and conducting rebuilding analyses to determine harvest guidelines for resources that have been designated as overfished. However, this management system has not been evaluated in terms of its ability to satisfy the National Standard 1 goals of the Sustainable Fisheries Act. A Monte Carlo simulation framework is therefore outlined that can be used to make such evaluations. Based on simulations tailored to a situation similar to that of managing the widow rockfish (Sebastes entomelas) resource, it is shown that catches during recovery and thereafter are likely to be highly variable (up to ±30% from one year to the next). Such variability is far greater than has been presented to the decision makers to date. Reductions in interannual variability in catches through additional data collection are, however, unlikely. Rather, improved performance will probably arise from better methods for predicting future recruitment. Rebuilding analyses include quantities such as the year to which the desired probability of recovery applies. The estimates of such quantities are, however, very poorly determined.

Abundance of Belugas, Delphinapterus leucas, in Cook Inlet, Alaska, 1994–2000

Annual abundance estimates of belugas, Delphinapterus leucas, in Cook Inlet were calculated from counts made by aerial observers and aerial video recordings. Whale group-size estimates were corrected for subsurface whales (availability bias) and whales that were at the surface but were missed (detection bias). Logistic regression was used to estimate the probability that entire groups were missed during the systematic surveys, and the results were used to calculate a correction to account for the whales in these missed groups (1.015, CV = 0.03 in 1994–98; 1.021, CV = 0.01 in 1999– 2000). Calculated abundances were 653 (CV = 0.43) in 1994, 491 (CV = 0.44) in 1995, 594 (CV = 0.28) in 1996, 440 (CV = 0.14) in 1997, 347 (CV = 0.29) in 1998, 367 (CV = 0.14) in 1999, and 435 (CV = 0.23, 95% CI=279–679) in 2000. For management purposes the current Nbest = 435 and Nmin = 360. These estimates replace preliminary estimates of 749 for 1994 and 357 for 1999. Monte Carlo simulations indicate a 47% probability that from June 1994 to June 1998 abundance of the Cook Inlet stock of belugas was depleted by 50%. The decline appears to have stopped in 1998.