For elk (Cervus elaphus) in the Gallatin drainage of the Greater Yellowstone Ecosystem, Montana, USA, wolf movements caused local predation risk to vary substantially on a time scale of days. Spatially and temporally fine-scaled data from GPS radio collars show that elk moved into the protective cover of wooded areas when wolves were present, reducing their use of preferred grassland foraging habitats that had high predation risk. By constraining habitat selection, wolves may have greater effects on elk dynamics than would be predicted on the basis of direct predation alone. Based on changes in the woody vegetation following the reintroduction of wolves, it has been suggested that antipredator responses by elk may be driving a trophic cascade in the Yellowstone ecosystem. However, studies to date have been hampered by a lack of direct data on spatial variation in predation risk, and the ways in which elk respond to variation in risk. Our data support a central portion of the hypothesis that elk antipredator behavior could drive a trophic cascade, but changes in elk numbers are also likely to have affected elk-plant interactions.

Truncated Poisson and truncated negative binomial count data models, as well as standard count data models, OLS, nonlinear normal, and truncated nonlinear normal MLE were used to estimate demand for deer hunting in California. The truncated count data estimators and their properties are reviewed. A large sample (N = 2223) allowed random segmenting of the data into specification, estimation, and out‐of‐sample prediction portions. Statistics of interest are therefore unbiased by the specification search, and the prediction results allow comparison of the statistical models' robustness. The new estimators are found to be more appropriate for estimating and predicting demand and social benefits than the alternative estimators based on a variety of criteria.

No abstract

No abstract