Cougar Dispersal and Natal Homing in a Desert Environment

We present a review of cougar dispersal literature and the first evidence of natural (i.e., unmanipulated) homing behavior by a dispersing male cougar (Puma concolor) that sustained severe injuries crossing the northern Mojave Desert. Based on Global Positioning System and ground tracking data, the male traveled a total distance of 981.1 km at 5.03 km/d, including 170.31 km from the Desert National Wildlife Refuge to the northwestern Grand Canyon, where he sustained severe injuries. The interkill interval increased from 7.1 ± 2.7 d while he was in his natal range to 17.5 ± 4.9 d during dispersal. While homing, the male appeared to consume only reptiles until he died, 33.7 km from his capture site. In desert environments where prey availability is low, homing behavior may be an important strategy for dispersing cougars, providing a mechanism for persistence when the best quality habitats they encounter are already occupied by adult residents. Therefore, managing for habitat connectivity can ensure successful homing as well as dispersal on a greater scale than has been previously suggested. Elucidating the mechanisms that trigger homing during dispersal may provide critical insight into animal movements often overlooked as mundane behavior

Choosing Statistical Models to Assess Biological Interaction as a Departure from Additivity of Effects

Vanderweele and Knol define biological interaction as an instance wherein “two exposures physically interact to bring about the outcome.” A hallmark of biological interaction is that the total effect, produced when factors act together, differs from the sum of effects when the factors operate independently. Epidemiologists construct statistical models to assess biological interaction. The form of the statistical model determines whether it is suited to detecting departures from additivity of effects or for detecting departures from multiplicativity of effects. A consensus exists that biological interaction should be assessed as a departure from additivity of effects.This paper compares three statistical models’ assessment of a data example that appears in several epidemiology textbooks to illustrate biological interaction in a binomial outcome. A linear binomial model quantifies departure from additivity in the data example in terms of differences in probabilities. It generates directly interpretable estimates and 95% confidence intervals for parameters including the interaction contrast (IC). Log binomial and logistic regression models detect no departure from multiplicativity in the data example. However, their estimates contribute to calculation of a “Relative Excess Risk Due to Interaction” (RERI), a measure of departure from additivity on a relative risk scale. The linear binomial model directly produces interpretable assessments of departures from additivity of effects and deserves wider use in research and in the teaching of epidemiology. Strategies exist to address the model’s limitations

A Reference Model for Providing Statistical Consulting Services in an Academic Library Setting

Princeton University Library, through its Data and Statistical Services (DSS) unit, goes further than many libraries in providing consulting on statistical methods as well as software support for data library users. Princeton requires all third and fourth year undergraduates to do independent original research papers and theses in their disciplines of concentration. These requirements create a clientele of students who need to conduct relatively sophisticated statistical analysis, but who may or may not possess the necessary skills required to do so. This paper describes the model we employ at Princeton DSS to help these patrons, drawing on our experience as data consultants to discuss how it works in practice

The Excitation of N2_2H+^+ in Interstellar Molecular Clouds. I - Models

We present LVG and non-local radiative transfer calculations involving the rotational and hyperfine structure of the spectrum of N$_2$H$^+$ with collisional rate coefficients recently derived by us. The goal of this study is to check the validity of the assumptions made to treat the hyperfine structure and to study the physical mechanisms leading to the observed hyperfine anomalies. We find that the usual hypothesis of identical excitation temperatures for all hyperfine components of the $J$=1-0 transition is not correct within the range of densities existing in cold dense cores, i.e., a few 10$^4$ \textless n(H$_2$) \textless a few 10$^6$ cm$^{-3}$. This is due to different radiative trapping effects in the hyperfine components. Moreover, within this range of densities and considering the typical abundance of N$_2$H$^+$, the total opacity of rotational lines has to be derived taking into account the hyperfine structure. The error made when only considering the rotational energy structure can be as large as 100%. Using non-local models we find that, due to saturation, hyperfine anomalies appear as soon as the total opacity of the $J$=1-0 transition becomes larger than $\simeq$ 20. Radiative scattering in less dense regions enhance these anomalies, and particularly, induce a differential increase of the excitation temperatures of the hyperfine components. This process is more effective for the transitions with the highest opacities for which emerging intensities are also reduced by self-absorption effects. These effects are not as critical as in HCO$^+$ or HCN, but should be taken into account when interpreting the spatial extent of the N$_2$H$^+$ emission in dark clouds.Comment: 13 pages, 12 figure