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Yellowstone's grizzlies (

Yellowstone’s grizzlies have been studied extensively for over 40 years. A recent monograph [

A weakness in the “minimum population” index is the presence of a strong serial correlation, induced by the fact that each annual estimate contains the counts from 2 other years. Difficulties caused by serial correlation have been assessed by Watt [

An alternative approach using radiotelemetry was applied by Eberhardt, et al. [

The study area constitutes Yellowstone and Grand Teton National Parks, 6 adjacent National Forests plus some state and private lands, and totals about 34,500 km^{2}. It is known as “The Greater Yellowstone Ecosystem” (GYE). The GYE constitutes the Yellowstone Plateau, and surrounding mountain ranges above 1500 m. Long cold winters and short summers characterize the climate. Low elevations are covered by grasslands or shrub steppes. Douglas fir (

The model used here is the exponential

The Durbin-Watson test [

where

Data used here on the “unduplicated” females with cubs in the GYE are those given in

The unduplicated data set was initially assessed by the lowess program, which is essentially a data smoothing program that calculates values from a weighted linear regression of a subset of points adjacent to the current location. It was used to produce Figure

Plot of “unduplicated” data with lowess smoothed line.

The J-shaped nature of the plot is in consequence that measures to protect and enhance grizzly populations in Yellowstone did not take effect until about 1983 [

Plot of “unduplicated” data with fitted exponential function.

The estimate of rate of increase

Estimates of rate of change (

95% Confidence | ||||

METHOD | Estimate of | Bias equation (4) | Interval on | |

Lower | Upper | |||

Regression (log transformed counts) | 0.0526 | — | 0.0422 | 0.07 |

Bootstrap (log transformed counts) | 0.0563 | 2.00E-04 | 0.041 | 0.071 |

Basic bootstrap c.i. | 0.04 | 0.071 | ||

Percentile method c.i. | 0.042 | 0.072 | ||

BCA method c.i. | 0.041 | 0.072 | ||

Nonlinear Least-squares exponential model | 0.0526 | — | 0.039 | 0.066 |

Bootstrap of Nonlinear L.S. Model | 0.0526 | 0.0007 | 0.037 | 0.066 |

Basic bootstrap c.i. | 0.036 | 0.066 | ||

Percentile method c.i. | 0.039 | 0.069 | ||

BCA method c.i. | 0.036 | 0.066 | ||

Generalized linear model (Poisson errors) | 0.054 | — | 0.043 | 0.065 |

The fact that the difference between

The data indicate that the GYE bear population does not yet show signs of approaching an asymptote. This is a bit surprising, inasmuch as Schwartz et al. [

Harris et al. [

Plot of Chao2 data with fitted exponential function.

Conducting live-trapping, marking and radiotelemetry operations on grizzlies are very expensive operations. Hence, the main lesson from the present study is that index studies should also be attempted as a check on results. Transforming observed index data with the Chao2 estimator produced slightly more variable results, so the method may not be useful unless some improvements are possible. The radiotelemetry results provide essential data for management so should also be conducted whenever possible.

The time span of the reported data (approaching 40 years) has led to its use in a long list of applications [

The senior author is grateful to Dr. Richard Knight for the opportunity to work on data for the Yellowstone grizzly bears for over 20 years and to Bonnie M. Blanchard for her continual and cheerful efforts at tabulation and analysis of the data. Dave Stradley of the Gallatin Flying Service provided expert piloting for many hours of “looking for bears”. Support from the Marine Mammal Commission and the National Marine Mammal Laboratory is acknowledged.