Geology topics

S.G. Hayes

Publications and source records attributed to S.G. Hayes.

2 recordsLinked to original sources

USGS2002

Factors leading to different viability predictions for a grizzly bear data set

Population viability analysis programs are being used increasingly in research and management applications, but there has not been a systematic study of the congruence of different program predictions based on a single data set. We performed such an analysis using four population viability analysis computer programs: GAPPS, INMAT, RAMAS/AGE, and VORTEX. The standardized demographic rates used in all programs were generalized from hypothetical increasing and decreasing grizzly bear ( Ursus arctos horribilis ) populations. Idiosyncracies of input format for each program led to minor differences in intrinsic growth rates that translated into striking differences in estimates of extinction rates and expected population size. In contrast, the addition of demographic stochasticity, environmental stochasticity, and inbreeding costs caused only a small divergence in viability predictions. But, the addition of density dependence caused large deviations between the programs despite our best attempts to use the same density-dependent functions. Population viability programs differ in how density dependence is incorporated, and the necessary functions are difficult to parameterize accurately. Thus, we recommend that unless data clearly suggest a particular density-dependent model, predictions based on population viability analysis should include at least one scenario without density dependence. Further, we describe output metrics that may differ between programs; development of future software could benefit from standardized input and output formats across different programs.

Conservation Biology↗

USGS1998

A female black bear denning habitat model using a geographic information system

We used the Mahalanobis distance statistic and a raster geographic information system (GIS) to model potential black bear ( Ursus americanus ) denning habitat in the Ouachita Mountains of Arkansas. The Mahalanobis distance statistic was used to represent the standard squared distance between sample variates in the GIS database (forest cover type, elevation, slope, aspect, distance to streams, distance to roads, and forest cover richness) and variates at known bear dens. Two models were developed: a generalized model for all den locations and another specific to dens in rock cavities. Differences between habitat at den sites and habitat across the study area were represented in 2 new GIS themes as Mahalanobis distance values. Cells similar to the mean vector derived from the known dens had low Mahalanobis distance values, and dissimilar cells had high values. The reliability of the predictive model was tested by overlaying den locations collected subsequent to original model development on the resultant den habitat themes. Although the generalized model demonstrated poor reliability, the model specific to rock dens had good reliability. Bears were more likely to choose rock den locations with low Mahalanobis distance values and less likely to choose those with high values. The model can be used to plan the timing and extent of management actions (e.g., road building, prescribed fire, timber harvest) most appropriate for those sites with high or low denning potential.

Arkansas↗